ORCID Profile
0000-0003-1762-5499
Current Organisation
University of Sydney
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Neurocognitive Patterns and Neural Networks | Astronomical and Space Sciences | Cognitive Science | Knowledge Representation and Machine Learning | Cosmology and Extragalactic Astronomy | Decision Making
Expanding Knowledge in the Physical Sciences | Expanding Knowledge in the Information and Computing Sciences | The Media | Expanding Knowledge in Psychology and Cognitive Sciences | Expanding Knowledge in the Mathematical Sciences |
Publisher: Springer Science and Business Media LLC
Date: 10-12-2020
DOI: 10.1038/S41467-020-19716-7
Abstract: The biological mechanisms that allow the brain to balance flexibility and integration remain poorly understood. A potential solution may lie in a unique aspect of neurobiology, which is that numerous brain systems contain diffuse synaptic connectivity. Here, we demonstrate that increasing diffuse cortical coupling within a validated biophysical corticothalamic model traverses the system through a quasi-critical regime in which spatial heterogeneities in input noise support transient critical dynamics in distributed subregions. The presence of quasi-critical states coincides with known signatures of complex, adaptive brain network dynamics. Finally, we demonstrate the presence of similar dynamic signatures in empirical whole-brain human neuroimaging data. Together, our results establish that modulating the balance between local and diffuse synaptic coupling in a thalamocortical model subtends the emergence of quasi-critical brain states that act to flexibly transition the brain between unique modes of information processing.
Publisher: Wiley
Date: 04-01-2012
DOI: 10.1002/MDS.24900
Abstract: Visual misperception and hallucinations represent a major problem in advanced PD. The pathophysiological mechanisms underlying these symptoms remain poorly understood, with limited tests for their assessment. A recent hypothesis has suggested that visual misperception and hallucinations may arise from disrupted processing in the attentional networks. To assess and quantify visual misperceptions, we developed the novel bistable percept paradigm (BPP), which consists of a battery of "single" and "hidden" monochromatic images that subjects are required to study until they are satisfied that they have recognized everything that the image may represent. In this experiment, 45 patients and 18 age-matched controls performed the BPP. Using an error score value derived from the control group, 23 patients were identified as having significant deficits on the task. Compared to patients who were unimpaired on the task, this group of patients had significantly higher levels of self-reported hallucinations on the SCales for Outcomes in PArkinson's Disease-Psychiatric Complications and also symptoms of rapid eye movement sleep behavior disorder (RBD). Furthermore, impairment on the BPP was associated with significantly reduced performance on an attentional set-shifting task. Patients with impaired performance on the BPP had higher rates of hallucinations, increased symptoms of RBD, and poorer performance on set shifting, suggesting disrupted processing within the attentional control networks. We propose that the BPP may offer a novel approach for exploring the neural correlates underlying visual hallucinations and misperceptions in PD.
Publisher: Oxford University Press (OUP)
Date: 18-10-2013
DOI: 10.1093/BRAIN/AWT272
Abstract: Recent neuroimaging evidence has led to the proposal that freezing of gait in Parkinson's disease is due to dysfunctional interactions between frontoparietal cortical regions and subcortical structures, such as the striatum. However, to date, no study has employed task-based functional connectivity analyses to explore this hypothesis. In this study, we used a data-driven multivariate approach to explore the impaired communication between distributed neuronal networks in 10 patients with Parkinson's disease and freezing of gait, and 10 matched patients with no clinical history of freezing behaviour. Patients performed a virtual reality gait task on two separate occasions (once ON and once OFF their regular dopaminergic medication) while functional magnetic resonance imaging data were collected. Group-level independent component analysis was used to extract the subject-specific time courses associated with five well-known neuronal networks: the motor network, the right- and left cognitive control networks, the ventral attention network and the basal ganglia network. We subsequently analysed both the activation and connectivity of these neuronal networks between the two groups with respect to dopaminergic state and cognitive load while performing the virtual reality gait task. During task performance, all patients used the left cognitive control network and the ventral attention network and in addition, showed increased connectivity between the bilateral cognitive control networks. However, patients with freezing demonstrated functional decoupling between the basal ganglia network and the cognitive control network in each hemisphere. This decoupling was also associated with paroxysmal motor arrests. These results support the hypothesis that freezing behaviour in Parkinson's disease is because of impaired communication between complimentary yet competing neural networks.
Publisher: Research Square Platform LLC
Date: 13-01-2022
DOI: 10.21203/RS.3.RS-1040925/V1
Abstract: Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macroscale neuroanatomy and how they shape emergent function remains poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography scans in ,200 healthy in iduals to construct a whole-brain 3-D normative atlas of 18 receptors and transporters across 9 different neurotransmitter systems. We find that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncover a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we find both expected and novel associations between receptor distributions and cortical thinning patterns across 13 disorders. We replicate all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.
Publisher: Elsevier BV
Date: 08-2023
Publisher: Oxford University Press (OUP)
Date: 2023
DOI: 10.1093/BRAINCOMMS/FCAD129
Abstract: Reduced heart rate variability can be an early sign of autonomic dysfunction in neurodegenerative diseases and may be related to brain dysfunction in the central autonomic network. As yet, such autonomic dysfunction has not been examined during sleep—which is an ideal physiological state to study brain–heart interaction as both the central and peripheral nervous systems behave differently compared to during wakefulness. Therefore, the primary aim of the current study was to examine whether heart rate variability during nocturnal sleep, specifically slow wave (deep) sleep, is associated with central autonomic network functional connectivity in older adults ‘at-risk’ of dementia. Older adults (n = 78 age range = 50–88 years 64% female) attending a memory clinic for cognitive concerns underwent resting-state functional magnetic resonance imaging and an overnight polysomnography. From these, central autonomic network functional connectivity strength and heart rate variability data during sleep were derived, respectively. High-frequency heart rate variability was extracted to index parasympathetic activity during distinct periods of sleep, including slow wave sleep as well as secondary outcomes of non-rapid eye movement sleep, wake after sleep onset, and rapid eye movement sleep. General linear models were used to examine associations between central autonomic network functional connectivity and high-frequency heart rate variability. Analyses revealed that increased high-frequency heart rate variability during slow wave sleep was associated with stronger functional connectivity (F = 3.98, P = 0.022) in two core brain regions within the central autonomic network, the right anterior insular and posterior midcingulate cortex, as well as stronger functional connectivity (F = 6.21, P = 0.005) between broader central autonomic network brain regions—the right amygdala with three sub-nuclei of the thalamus. There were no significant associations between high-frequency heart rate variability and central autonomic network connectivity during wake after sleep onset or rapid eye movement sleep. These findings show that in older adults ‘at-risk’ of dementia, parasympathetic regulation during slow wave sleep is uniquely linked to differential functional connectivity within both core and broader central autonomic network brain regions. It is possible that dysfunctional brain–heart interactions manifest primarily during this specific period of sleep known for its role in memory and metabolic clearance. Further studies elucidating the pathophysiology and directionality of this relationship should be conducted to determine if heart rate variability drives neurodegeneration, or if brain degeneration within the central autonomic network promotes aberrant heart rate variability.
Publisher: Elsevier BV
Date: 06-2022
DOI: 10.1016/J.TICS.2022.03.006
Abstract: Neural dynamics are shaped and constrained by the projections of a small nucleus in the pons: the noradrenergic locus coeruleus (LC). Much like a bow to the brain's violin, activity in the LC lacks content specificity, but instead dynamically shapes the excitability and receptivity of neurons across the brain. In this review, we explain how the style of the bowing technique, which is analogous to different firing modes in the LC, affects distinct activity patterns in the rest of the brain. Through this analogical lens, we provide intuitive insights into how the complex activity of the LC acts to coordinate adaptive neural dynamics.
Publisher: Wiley
Date: 10-10-2005
Publisher: Center for Open Science
Date: 24-12-2018
Abstract: The brain is a complex dynamical system composed of many interacting sub-regions. Knowledge of how these interactions reconfigure over time is critical to a full understanding of the brain’s functional architecture, the neural basis of flexible cognition and behavior, and how neural systems are disrupted in psychiatric and neurological illness. The idea that we might be able to study neural and cognitive dynamics through analysis of neuroimaging data has catalyzed substantial interest in methods which seek to estimate moment-to-moment fluctuations in functional connectivity (often referred to as “dynamic” or time-varying connectivity TVC). At the same time, debates have emerged regarding the application of TVC analyses to resting fMRI data, and about the statistical validity, physiological origins, and cognitive relevance of resting TVC. These and other unresolved issues complicate the interpretation of resting TVC findings and limit the insights which can be gained from this otherwise promising research area. This article reviews the current resting TVC literature in light of these issues. We introduce core concepts, define key terms, summarize current controversies and open questions, and present a forward-looking perspective on how resting TVC analyses can be rigorously applied to investigate a wide range of questions in cognitive and systems neuroscience.
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 02-2015
DOI: 10.1016/J.JOCN.2014.06.097
Abstract: Patient-centred care is increasingly being recognised as an integral aspect of improving the quality of health care services. There has been a recent interest in taking a patient-centred approach to Parkinson's disease (PD) care by involving patients in shared decision making, as well as providing access to multidisciplinary teams of medical practitioners, PD nurse specialists, and allied health professionals. However, to our knowledge there are no data regarding patient preferences for interventions in PD management. The present study examined the relative importance of issues regarding quality of life for people living with PD in Australia using a self-administered survey. Overall, respondents ranked more research funding in PD (mean rank, 340.42) as the most important issue, access to PD nurses (285.50) in second place, followed by access to multidisciplinary facilities/clinics with allied health professionals (283.39) in third place, subsidised PD treatments (233.50) in fourth place, and better general practitioner education (184.69) as the least important issue of the options offered. There was a statistically significant difference between the five issues (H[4] = 65.38, p < 0.001). Within the framework of patient-centred care, public funding allocations perhaps should be based on what patients want. As such, these findings suggest that for people living with a chronic, progressive, incurable illness, research is highly valued.
Publisher: Proceedings of the National Academy of Sciences
Date: 04-02-2019
Abstract: Humans spend much of their waking life engaged in mind wandering. Underlying brain systems supporting this complex ability have been established in healthy in iduals, yet it remains unclear how mind wandering is altered in neuropsychiatric populations. We reveal changes in the thought profiles elicited during periods of low cognitive demand in dementia, resulting in reduced mind wandering and an increased propensity toward stimulus-bound thought. These altered thought profiles were associated with structural and functional brain changes in the hippoc us, default, and frontoparietal networks, key regions implicated in internal mentation in healthy in iduals. Our findings provide a unique clinical validation of current theoretical models of mind wandering and reveal a dimension of cognitive dysfunction that has received scant attention in dementia.
Publisher: Springer Science and Business Media LLC
Date: 15-08-2017
DOI: 10.1007/S11682-017-9754-3
Abstract: Parkinson's disease (PD) is frequently accompanied by cognitive and neuropsychiatric symptoms including impairments in affective processing. Despite this, mechanisms underlying vulnerability to deficits in affective processing remain unclear. In this study, we utilized functional Magnetic Resonance Imaging (fMRI) and an Affective Go-NoGo paradigm, to examine the neural correlates of emotional valence processing in PD. Results suggest that PD is associated with aberrant processing of emotional valence in subcortical limbic structures. Specifically, we found significant group-by-valence interactions in the ventral striatum and amygdala in response to words of differing emotional valence. Our findings contribute to a broader understanding of affective processing in PD and may provide insights into the mechanisms underlying vulnerability to mood disorders in PD.
Publisher: Cambridge University Press (CUP)
Date: 2016
DOI: 10.1017/S0140525X1500165X
Abstract: Although meta-analytic neuroimaging studies demonstrate a relative lack of specificity in the brain, this evidence may be the result of limits inherent to these types of studies. From this perspective, we review recent findings that suggest that brain function is most appropriately categorized according to the computational capacity of each brain system, rather than the specific task states that elicit its activity.
Publisher: Springer Science and Business Media LLC
Date: 12-2021
DOI: 10.1186/S40708-021-00147-Z
Abstract: Here, we combine network neuroscience and machine learning to reveal connections between the brain’s network structure and the emerging network structure of an artificial neural network. Specifically, we train a shallow, feedforward neural network to classify hand-written digits and then used a combination of systems neuroscience and information-theoretic tools to perform ‘virtual brain analytics’ on the resultant edge weights and activity patterns of each node. We identify three distinct phases of network reconfiguration across learning, each of which are characterized by unique topological and information-theoretic signatures. Each phase involves aligning the connections of the neural network with patterns of information contained in the input dataset or preceding layers (as relevant). We also observe a process of low-dimensional category separation in the network as a function of learning. Our results offer a systems-level perspective of how artificial neural networks function—in terms of multi-stage reorganization of edge weights and activity patterns to effectively exploit the information content of input data during edge-weight training—while simultaneously enriching our understanding of the methods used by systems neuroscience.
Publisher: Elsevier BV
Date: 07-2018
DOI: 10.1016/J.PARKRELDIS.2018.03.009
Abstract: Freezing of gait is a devastating symptom of Parkinson's disease and other forms of parkinsonism. It poses a major burden on both patients and their families, as freezing often leads to falls, fall-related injuries and a loss of independence. Treating freezing of gait is difficult for a variety of reasons: it has a paroxysmal and unpredictable nature a multifaceted pathophysiology, with an interplay between motor elements (disturbed stepping mechanisms) and non-motor elements (cognitive decline, anxiety) and a complex (and likely heterogeneous) underlying neural substrate, involving multiple failing neural networks. In recent years, advances in translational neuroscience have offered new insights into the pathophysiology underlying freezing. Furthermore, the mechanisms behind the effectiveness of available treatments (or lack thereof) are better understood. Driven by these concepts, researchers and clinicians have begun to improve currently available treatment options, and develop new and better treatment methods. Here, we evaluate the range of pharmacological (i.e. closed-looped approaches), surgical (i.e. multi-target and adaptive deep brain and spinal cord stimulation) and behavioural (i.e. biofeedback and cueing on demand) treatment options that are under development, and propose novel avenues that are likely to play a crucial role in the clinical management of freezing of gait in the near future. The outcomes of this review suggest that the successful future management of freezing of gait will require in idualized treatments that can be implemented in an on-demand manner in response to imminent freezing. With this review we hope to guide much-needed advances in treating this devastating symptom of Parkinson's disease.
Publisher: Cold Spring Harbor Laboratory
Date: 29-08-2019
DOI: 10.1101/747162
Abstract: Both natural and engineered networks are often modular. Whether a network node interacts with only nodes from its own module or nodes from multiple modules provides insight into its functional role. The participation coeffcient ( PC ) is typically used to measure this attribute although its value also depends on the size of the module it belongs to, often leading to non-intuitive identification of highly connected nodes. Here, we develop a normalized PC that overcomes the module size bias associated with the conventional PC . Using brain, C.elegans , airport and simulated networks, we show that our measure of participation alleviates the module size bias, while preserving conceptual and mathematical properties, of the classic formulation of PC . Unlike the conventional PC , we identify London and New York as high participators in the air traffic network and demonstrate stronger associations with working memory in human brain networks, yielding new insights into nodal participation across network modules.
Publisher: Cold Spring Harbor Laboratory
Date: 24-02-2017
DOI: 10.1101/111278
Abstract: Models of hallucinations across disorders emphasise an imbalance between sensory input and top-down influences over perception. However, the psychological and mechanistic correlates of this imbalance remain underspecified. Visual hallucinations in Parkinson’s disease (PD) are associated with impairments in lower level visual processes and attention, accompanied by over activity and connectivity in higher-order association brain networks. PD therefore provides an attractive framework to explore the relative contributions of bottom-up versus top-down disturbances in hallucinations. Here, we characterised sensory processing in PD patients with and without visual hallucinations, and in healthy controls, by fitting a hierarchical drift diffusion model (hDDM) to an attentional task. The hDDM uses Bayesian estimates to decompose reaction time and response output into parameters reflecting drift rates of evidence accumulation, decision thresholds and non-decision time. We observed slower drift rates in PD patients with hallucinations, which were insensitive to changes in task demand. In contrast, wider decision boundaries and shorter non-decision times relative to controls were found in PD regardless of hallucinator status. Inefficient and less flexible sensory evidence accumulation emerge as unique features of PD hallucinators. We integrate these results with current models of hallucinations, suggesting that slow and inefficient sensory input in PD is less informative, and may therefore be down-weighted leading to an over reliance on top-down influences. Our findings provide a novel computational framework to better specify the impairments in dynamic sensory processing that are a risk factor for visual hallucinations.
Publisher: Wiley
Date: 09-06-2010
DOI: 10.1002/MDS.23005
Abstract: Freezing of gait (FOG) in Parkinson's disease (PD) is common and the pathophysiology of FOG is poorly understood. It has been hypothesized to reflect complementary yet competing frontostriatal pathways that reduce the ability to keep different tasks (motor or cognitive) on-line. This inability to "set-shift" has been proposed to trigger a freezing episode. If correct, this hypothesis would predict a differential pattern of executive dysfunction with FOG being most specifically related to attentional set-shifting. In this study, 31 patients with a range of self-reported FOG symptom severities were administered tests of executive functioning. The results demonstrate that FOG symptoms were selectively correlated with poorer performance on tasks of set-shifting, but not with a range of other executive tasks. This was apparent even after controlling for slowed processing speed, disease stage and depressive symptoms. The results support the recently proposed hypothesis for the pathophysiology underlying FOG in PD.
Publisher: Oxford University Press (OUP)
Date: 05-2020
Abstract: This scientific commentary refers to ‘Cognitive load lifies Parkinson’s tremor through excitatory network influences onto the thalamus’, by Dirkx etal. (doi: 10.1093/brain/awaa083).
Publisher: Frontiers Media SA
Date: 24-11-2022
DOI: 10.3389/FNHUM.2022.1062487
Abstract: Neuroscience has had access to high-resolution recordings of large-scale cortical activity and structure for decades, but still lacks a generally adopted basis to analyze and interrelate results from different in iduals and experiments. Here it is argued that the natural oscillatory modes of the cortex—cortical eigenmodes—provide a physically preferred framework for systematic comparisons across experimental conditions and imaging modalities. In this framework, eigenmodes are analogous to notes of a musical instrument, while commonly used statistical patterns parallel frequently played chords. This intuitive perspective avoids problems that often arise in neuroimaging analyses, and connects to underlying mechanisms of brain activity. We envisage this approach will lead to novel insights into whole-brain function, both in existing and prospective datasets, and facilitate a unification of empirical findings across presently disparate analysis paradigms and measurement modalities.
Publisher: Elsevier BV
Date: 03-2014
DOI: 10.1016/J.CLINPH.2013.09.006
Abstract: We sought to characterize the electrophysiological signature of Freezing of gait in Parkinson's disease. We examined 24 patients with idiopathic Parkinson's disease and significant freezing of gait as they performed a series of timed up-and-go tasks in their 'off' state while electroencephalographic data was collected from four scalp leads. Fast Fourier Transformation was utilized to explore the power spectral density between periods of normal walking and periods of freezing, as well as during the transition between the two states. In addition, Cross Spectrum and Cross Frequency analyses were used to explore the role of impaired temporal and spatial connectivity. When compared to walking, episodes of freezing were associated with a significant increase in theta band power within the central and frontal leads. The transition from normal walking to freezing of gait was also associated with increased theta frequency coupling between the central and frontal leads, along with an increase in cross-frequency coupling in the central lead. Episodes of freezing of gait in Parkinson's disease are associated with abnormal oscillatory activity in the brain. These results provide novel insights into the pattern of spatiotemporal dynamics underlying freezing of gait and may provide a potential means for therapeutic prediction and alleviation of freezing episodes in susceptible patients.
Publisher: Elsevier BV
Date: 03-2015
Publisher: Wiley
Date: 25-11-2014
DOI: 10.1002/HBM.22701
Publisher: Elsevier BV
Date: 05-2014
DOI: 10.1016/J.PNEUROBIO.2014.01.004
Abstract: Visual hallucinations are common across a number of disorders but to date, a unifying pathophysiology underlying these phenomena has not been described. In this manuscript, we combine insights from neuropathological, neuropsychological and neuroimaging studies to propose a testable common neural mechanism for visual hallucinations. We propose that 'simple' visual hallucinations arise from disturbances within regions responsible for the primary processing of visual information, however with no further modulation of perceptual content by attention. In contrast, 'complex' visual hallucinations reflect dysfunction within and between the Attentional Control Networks, leading to the inappropriate interpretation of ambiguous percepts. The incorrect information perceived by hallucinators is often differentially interpreted depending on the time-course and the neuroarchitecture underlying the interpretation. Disorders with 'complex' hallucinations without retained insight are proposed to be associated with a reduction in the activity within the Dorsal Attention Network. The review concludes by showing that a variety of pathological processes can ultimately manifest in any of these three categories, depending on the precise location of the impairment.
Publisher: Elsevier BV
Date: 04-2021
DOI: 10.1016/J.PNEUROBIO.2020.101951
Abstract: The human brain is a complex, adaptive system comprised of billions of cells with trillions of connections. The interactions between the elements of the system oppose this seemingly limitless capacity by constraining the system's dynamic repertoire, enforcing distributed neural states that balance integration and differentiation. How this trade-off is mediated by the brain, and how the emergent, distributed neural patterns give rise to cognition and awareness, remains poorly understood. Here, I argue that the thalamus is well-placed to arbitrate the interactions between distributed neural assemblies in the cerebral cortex. Different classes of thalamocortical connections are hypothesized to promote either feed-forward or feedback processing modes in the cerebral cortex. This activity can be conceptualized as emerging dynamically from an evolving attractor landscape, with the relative engagement of distinct distributed circuits providing differing constraints over the manner in which brain state trajectories change over time. In addition, inputs to the distinct thalamic populations from the cerebellum and basal ganglia, respectively, are proposed to differentially shape the attractor landscape, and hence, the temporal evolution of cortical assemblies. The coordinated engagement of these neural macrosystems is then shown to share key characteristics with prominent models of cognition, attention and conscious awareness. In this way, the crucial role of the thalamus in mediating the distributed, multi-scale network organization of the central nervous system can be related to higher brain function.
Publisher: Cold Spring Harbor Laboratory
Date: 03-05-2017
DOI: 10.1101/133611
Abstract: Flexible interaction between brain regions enables neural systems to transfer and process information adaptively for goal-directed behaviors. In the current study, we investigated neural substrates that interact with task-evoked functional connectivity during cognitive control. We conducted a human fMRI study where participants selectively attended to a category of visual stimuli in the presence of competing distractors from another stimulus category. To study flexible interactions between brain regions, we performed a dynamic functional connectivity analysis to estimate temporal changes in connectivity strength between brain regions under different levels of cognitive control. Consistent with theoretical predictions, we found that cognitive control selectively enhances functional connectivity for prioritizing the processing of task-relevant information. By regressing temporal changes in connectivity strength against activity patterns elsewhere in the brain, we localized frontal and parietal regions that potentially provide top-down biasing signals for influencing, or reading information out from, task-evoked functional connectivity. Our results suggest that in addition to modulating local activity, fronto-parietal regions could also exert top-down biasing signals to influence functional connectivity between distributed brain regions.
Publisher: Springer Science and Business Media LLC
Date: 16-10-2014
DOI: 10.1007/S00415-014-7524-3
Abstract: Freezing of gait (FOG) is a disabling motor symptom experienced by a large proportion of patients with Parkinson's disease (PD). While it is known that FOG contributes to lower health-related quality of life (HRQoL), previous studies have not accounted for other important factors when measuring the specific impact of this symptom. The aim of this study was to examine FOG and HRQoL while controlling for other factors that are known to impact patient well-being, including cognition, motor severity, sleep disturbance and mood. Two hundred and three patients with idiopathic PD (86 with FOG) were included in the study. All patients were between Hoehn and Yahr stages I-III. A forced entry multiple regression model evaluating the relative contribution of all symptoms was conducted, controlling for time since diagnosis and current dopaminergic treatment. Entering all significantly correlated variables into the regression model accounted for the majority of variance exploring HRQoL. Self-reported sleep-wake disturbances, depressive and anxious symptoms and FOG were in idually significant predictors. FOG accounted for the highest amount of unique variance. While sleep-wake disturbance and mood have a significant negative impact on HRQoL in PD, the emergence of FOG represents the most substantial predictor among patients in the earlier clinical stages of disease. This finding presumably reflects the disabling loss of independence and fear of injury associated with FOG and underlines the importance of efforts to reduce this common symptom.
Publisher: Oxford University Press (OUP)
Date: 12-03-2013
DOI: 10.1093/BRAIN/AWT049
Abstract: Freezing of gait is a devastating symptom of advanced Parkinson's disease yet the neural correlates of this phenomenon remain poorly understood. In this study, severity of freezing of gait was assessed in 18 patients with Parkinson's disease on a series of timed 'up and go' tasks, in which all patients suffered from episodes of clinical freezing of gait. The same patients also underwent functional magnetic resonance imaging with a virtual reality gait paradigm, performance on which has recently been shown to correlate with actual episodes of freezing of gait. Statistical parametric maps were created that compared the blood oxygen level-dependent response associated with paroxysmal motor arrests (freezing) to periods of normal motor output. The results of a random effects analysis revealed that these events were associated with a decreased blood oxygen level-dependent response in sensorimotor regions and an increased response within frontoparietal cortical regions. These signal changes were inversely correlated with the severity of clinical freezing of gait. Motor arrests were also associated with decreased blood oxygen level-dependent signal bilaterally in the head of caudate nucleus, the thalamus and the globus pallidus internus. Utilizing a mixed event-related/block design, we found that the decreased blood oxygen level-dependent response in the globus pallidus and the subthalamic nucleus persisted even after controlling for the effects of cognitive load, a finding which supports the notion that paroxysmal increases in basal ganglia outflow are associated with the freezing phenomenon. This method also revealed a decrease in the blood oxygen level-dependent response within the mesencephalic locomotor region during motor arrests, the magnitude of which was positively correlated with the severity of clinical freezing of gait. These results provide novel insights into the pathophysiology underlying freezing of gait and lend support to models of freezing of gait that implicate dysfunction across coordinated neural networks.
Publisher: IEEE
Date: 08-2012
Publisher: Oxford University Press (OUP)
Date: 18-03-2019
DOI: 10.1093/BRAIN/AWZ034
Abstract: Using a dynamic graph theoretical approach, Shine et al. show that in iduals with Parkinson’s disease demonstrate heightened network-level integration during the ‘Off’ state that is inversely correlated with motor symptom severity. Network-level integration relates to two measures of neurocognitive reserve, suggesting a protective function for ‘Off’ state integration.
Publisher: Public Library of Science (PLoS)
Date: 30-01-2013
Publisher: Springer Science and Business Media LLC
Date: 15-08-2022
DOI: 10.1038/S41467-022-32381-2
Abstract: In the absence of external stimuli, neural activity continuously evolves from one configuration to another. Whether these transitions or explorations follow some underlying arrangement or lack a predictable ordered plan remains to be determined. Here, using fMRI data from highly s led in iduals (~5 hours of resting-state data per in idual), we aimed to reveal the rules that govern transitions in brain activity at rest. Our Topological Data Analysis based Mapper approach characterized a highly visited transition state of the brain that acts as a switch between different neural configurations to organize the spontaneous brain activity. Further, while the transition state was characterized by a uniform representation of canonical resting-state networks (RSNs), the periphery of the landscape was dominated by a subject-specific combination of RSNs. Altogether, we revealed rules or principles that organize spontaneous brain activity using a precision dynamics approach.
Publisher: Frontiers Media SA
Date: 2013
Publisher: The Royal Society
Date: 14-04-2023
Abstract: How is the massive dimensionality and complexity of the microscopic constituents of the nervous system brought under sufficiently tight control so as to coordinate adaptive behaviour? A powerful means for striking this balance is to poise neurons close to the critical point of a phase transition, at which a small change in neuronal excitability can manifest a nonlinear augmentation in neuronal activity. How the brain could mediate this critical transition is a key open question in neuroscience. Here, I propose that the different arms of the ascending arousal system provide the brain with a erse set of heterogeneous control parameters that can be used to modulate the excitability and receptivity of target neurons—in other words, to act as control parameters for mediating critical neuronal order. Through a series of worked ex les, I demonstrate how the neuromodulatory arousal system can interact with the inherent topological complexity of neuronal subsystems in the brain to mediate complex adaptive behaviour.
Publisher: Elsevier BV
Date: 11-2015
DOI: 10.1016/J.NEUROIMAGE.2015.07.064
Abstract: Functional connectivity provides an informative and powerful framework for exploring brain organization. Despite this, few statistical methods are available for the accurate estimation of dynamic changes in functional network architecture. To date, the majority of existing statistical techniques have assumed that connectivity structure is stationary, which is in direct contrast to emerging data that suggests that the strength of connectivity between regions is variable over time. Therefore, the development of statistical methods that enable exploration of dynamic changes in functional connectivity is currently of great importance to the neuroscience community. In this paper, we introduce the 'Multiplication of Temporal Derivatives' (MTD) and then demonstrate the utility of this metric to: (i) detect dynamic changes in connectivity using data from a novel state-switching simulation (ii) accurately estimate graph structure in a previously-described 'ground-truth' simulated dataset and (iii) identify task-driven alterations in functional connectivity. We show that the MTD is more sensitive than existing sliding-window methods in detecting dynamic alterations in connectivity structure across a range of correlation strengths and window lengths in simulated data. In addition to the temporal precision offered by MTD, we demonstrate that the metric is also able to accurately estimate stationary network structure in both simulated and real task-based data, suggesting that the method may be used to identify dynamic changes in network structure as they evolve through time.
Publisher: Society for Neuroscience
Date: 03-09-2014
Publisher: Mary Ann Liebert Inc
Date: 11-2015
Abstract: The study of resting-state networks provides an informative paradigm for understanding the functional architecture of the human brain. Although investigating specialized resting-state networks has led to significant advances in our understanding of brain organization, the manner in which information is integrated across these networks remains unclear. Here, we have developed and validated a data-driven methodology for describing the topography of resting-state network convergence in the human brain. Our results demonstrate the importance of an ensemble of cortical and subcortical regions in supporting the convergence of multiple resting-state networks, including the rostral anterior cingulate, precuneus, posterior cingulate cortex, posterior parietal cortex, dorsal prefrontal cortex, along with the caudate head, anterior claustrum, and posterior thalamus. In addition, we have demonstrated a significant correlation between voxel-wise network convergence and global brain connectivity, emphasizing the importance of resting-state network convergence in facilitating global brain communication. Finally, we examined the convergence of systems within each of the in idual resting-state networks in the brain, revealing the heterogeneity by which in idual resting-state networks balance the competing demands of specialized processing against the integration of information. Together, our results suggest that the convergence of resting-state networks represents an important organizational principle underpinning systems-level integration in the human brain.
Publisher: Springer Science and Business Media LLC
Date: 21-02-2019
DOI: 10.1038/S41593-019-0347-X
Abstract: In the version of this article initially published, Kaylena A. Ehgoetz Martens' name was misspelled as Kayla. The error has been corrected in the HTML and PDF versions of the article.
Publisher: Society for Neuroscience
Date: 06-04-2018
DOI: 10.1523/JNEUROSCI.0217-18.2018
Abstract: Evidence for intrinsic functional connectivity (FC) within the human brain is largely from neuroimaging studies of hemodynamic activity. Data are lacking from anatomically precise electrophysiological recordings in the most widely studied nodes of human brain networks. Here we used a combination of fMRI and electrocorticography (ECoG) in five human neurosurgical patients with electrodes in the canonical “default” (medial prefrontal and posteromedial cortex), “dorsal attention” (frontal eye fields and superior parietal lobule), and “frontoparietal control” (inferior parietal lobule and dorsolateral prefrontal cortex) networks. In this unique cohort, simultaneous intracranial recordings within these networks were anatomically matched across different in iduals. Within each network and for each in idual, we found a positive, and reproducible, spatial correlation for FC measures obtained from resting-state fMRI and separately recorded ECoG in the same brains. This relationship was reliably identified for electrophysiological FC based on slow ( Hz) fluctuations of high-frequency broadband (70–170 Hz) power, both during wakeful rest and sleep. A similar FC organization was often recovered when using lower-frequency (1–70 Hz) power, but anatomical specificity and consistency were greatest for the high-frequency broadband range. An interfrequency comparison of fluctuations in FC revealed that high and low-frequency ranges often temporally erged from one another, suggesting that multiple neurophysiological sources may underlie variations in FC. Together, our work offers a generalizable electrophysiological basis for intrinsic FC and its dynamics across in iduals, brain networks, and behavioral states. SIGNIFICANCE STATEMENT The study of human brain networks during wakeful “rest”, largely with fMRI, is now a major focus in both cognitive and clinical neuroscience. However, little is known about the neurophysiology of these networks and their dynamics. We studied neural activity during wakeful rest and sleep within neurosurgical patients with directly implanted electrodes. We found that network activity patterns showed striking similarities between fMRI and direct recordings in the same brains. With improved resolution of direct recordings, we also found that networks were best characterized with specific activity frequencies and that different frequencies show different profiles of within-network activity over time. Our work clarifies how networks spontaneously organize themselves across in iduals, brain networks, and behavioral states.
Publisher: Informa UK Limited
Date: 08-05-2018
Publisher: Elsevier BV
Date: 05-2013
DOI: 10.1016/J.CLINEURO.2012.06.027
Abstract: We sought to concurrently examine the specific motor, cognitive and affective contributions to self-reported FOG symptoms. Ninety-six patients with Parkinson's disease completed the validated freezing of gait questionnaire and had their motor function scored on section three of the Unified Parkinson's Disease Rating Scale questionnaire. A 5-choice reaction time task was administered in order to measure cognitive processing speed and the Beck Depression Inventory was utilised to assess affective disturbance. The results showed that after controlling disease duration and dopaminergic medication dose, the triad of motor disability, cognitive processing speed and affective symptoms were all significant independent predictors of scores on the freezing of gait questionnaire. These findings suggest the need to consider the interplay between distinct motor, cognitive and affective domains in aetiological studies of freezing and the development of future therapies.
Publisher: MIT Press - Journals
Date: 09-2018
DOI: 10.1162/NETN_A_00042
Abstract: The human brain is able to flexibly adapt its information processing capacity to meet a variety of cognitive challenges. Recent evidence suggests that this flexibility is reflected in the dynamic reorganization of the functional connectome. The ascending catecholaminergic arousal systems of the brain are a plausible candidate mechanism for driving alterations in network architecture, enabling efficient deployment of cognitive resources when the environment demands them. We tested this hypothesis by analyzing both resting-state and task-based fMRI data following the administration of atomoxetine, a noradrenaline reuptake inhibitor, compared with placebo, in two separate human fMRI studies. Our results demonstrate that the manipulation of central catecholamine levels leads to a reorganization of the functional connectome in a manner that is sensitive to ongoing cognitive demands.
Publisher: Elsevier BV
Date: 2014
Publisher: Wiley
Date: 12-05-2022
DOI: 10.1111/GEB.13513
Abstract: Understanding the variation in community composition and species abundances (i.e., β‐ ersity) is at the heart of community ecology. A common approach to examine β‐ ersity is to evaluate directional variation in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distance. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 148 datasets comprising different types of organisms and environments. Global. 1990 to present. From diatoms to mammals. We measured the strength of the decay using ranked Mantel tests (Mantel r ) and the rate of distance decay as the slope of an exponential fit using generalized linear models. We used null models to test whether functional similarity decays faster or slower than expected given the taxonomic decay along the spatial and environmental distance. We also unveiled the factors driving the rate of decay across the datasets, including latitude, spatial extent, realm and organismal features. Taxonomic distance decay was stronger than functional distance decay along both spatial and environmental distance. Functional distance decay was random given the taxonomic distance decay. The rate of taxonomic and functional spatial distance decay was fastest in the datasets from mid‐latitudes. Overall, datasets covering larger spatial extents showed a lower rate of decay along spatial distance but a higher rate of decay along environmental distance. Marine ecosystems had the slowest rate of decay along environmental distances. In general, taxonomic distance decay is a useful tool for biogeographical research because it reflects dispersal‐related factors in addition to species responses to climatic and environmental variables. Moreover, functional distance decay might be a cost‐effective option for investigating community changes in heterogeneous environments.
Publisher: eLife Sciences Publications, Ltd
Date: 08-10-2021
DOI: 10.7554/ELIFE.69480
Abstract: Hubs in the human brain support behaviors that arise from brain network interactions. Previous studies have identified hub regions in the human thalamus that are connected with multiple functional networks. However, the behavioral significance of thalamic hubs has yet to be established. Our framework predicts that thalamic subregions with strong hub properties are broadly involved in functions across multiple cognitive domains. To test this prediction, we studied human patients with focal thalamic lesions in conjunction with network analyses of the human thalamocortical functional connectome. In support of our prediction, lesions to thalamic subregions with stronger hub properties were associated with widespread deficits in executive, language, and memory functions, whereas lesions to thalamic subregions with weaker hub properties were associated with more limited deficits. These results highlight how a large-scale network model can broaden our understanding of thalamic function for human cognition.
Publisher: Wiley
Date: 08-02-2020
DOI: 10.1002/MDS.27995
Publisher: Springer Science and Business Media LLC
Date: 03-04-2018
DOI: 10.1007/S00415-018-8846-3
Abstract: Freezing of gait (FOG) is a common symptom in advanced Parkinson's disease (PD). Despite current advances, the neural mechanisms underpinning this disturbance remain poorly understood. To this end, we investigated the structural organisation of the white matter connectome in PD freezers and PD non-freezers. We hypothesized that freezers would show an altered network architecture, which could hinder the effective information processing that characterizes the disorder. Twenty-six freezers and twenty-four well-matched non-freezers were included in this study. Using diffusion tensor imaging, we investigated the modularity and integration of the regional connectome by calculating the module degree z score and the participation coefficient, respectively. Compared to non-freezers, freezers demonstrated lower participation coefficients in the right caudate, thalamus, and hippoc us, as well as within superior frontal and parietal cortical regions. Importantly, several of these nodes were found within the brain's 'rich club'. Furthermore, group differences in module degree z scores within cortical frontal and sensory processing areas were found. Together, our results suggest that changes in the structural network topology contribute to the manifestation of FOG in PD, specifically due to a lack of structural integration between key information processing hubs of the brain.
Publisher: Oxford University Press (OUP)
Date: 03-02-2018
Abstract: Flexible interactions between brain regions enable neural systems to adaptively transfer and process information. However, the neural substrates that regulate adaptive communications between brain regions are understudied. In this human fMRI study, we investigated this issue by tracking time-varying, task-evoked changes in functional connectivity between localized occipitotemporal regions while participants performed different tasks on the same visually presented stimuli. We found that functional connectivity between ventral temporal and the primary visual regions selectively increased during the processing of task-relevant information. Further, additional task demands selectively strengthen these targeted connectivity patterns. To identify candidate regions that contribute to this increase in inter-regional coupling, we regressed the task-specific time-varying connectivity strength between primary visual and occipitotemporal regions against voxel-wise activity patterns elsewhere in the brain. This allowed us to identify a set of frontal and parietal regions whose activity increased as a function of task-evoked functional connectivity. These results suggest that frontoparietal regions may provide top-down biasing signals to influence task-specific interactions between brain regions.
Publisher: Elsevier BV
Date: 02-2015
DOI: 10.1016/J.BANDC.2014.11.001
Abstract: Self-generated cognition, or mind wandering, refers to the quintessentially human tendency to withdraw from the immediate external environment and engage in internally driven mentation. This thought activity is suggested to be underpinned by a distributed set of regions in the brain, referred to as the default network. To date, experimental assessment of mind wandering has typically taken place during performance of a concurrent attention-demanding task. The attentional demands of concurrent tasks can influence the emergence of mind wandering, and their application to clinical disorders with reduced cognitive resources is limited. Furthermore, few paradigms have investigated the phenomenological content of mind wandering episodes. Here, we present data from a novel thought s ling task that measures both the frequency and qualitative content of mind wandering, in the absence of a concurrent task to reduce cognitive demand. The task was validated in a non-pathological cohort of 31 older controls and resting-state functional connectivity analyses in a subset of participants (n=18) was conducted to explore the neural bases of mind wandering. Overall, instances of mind wandering were found to occur in 37% of experimental trials. Resting state functional connectivity analyses confirmed that mind wandering frequency was associated with regional patterns of both increased and decreased default network connectivity, namely in the temporal lobe, posterior cingulate cortex and dorsal medial prefrontal cortex. Our findings demonstrate that the novel task provides a context of low cognitive demand, which is conducive to mind wandering. Furthermore, performance on the task is associated with specific patterns of functional connectivity in the default network. Together, this new paradigm offers an important avenue to investigate the frequency and content of mind wandering in the context of low cognitive demands, and has significant potential to be applied in clinical conditions with reduced cognitive resources.
Publisher: eLife Sciences Publications, Ltd
Date: 29-11-2022
Publisher: Springer Science and Business Media LLC
Date: 06-05-2021
DOI: 10.1038/S41593-021-00824-6
Abstract: Decades of neurobiological research have disclosed the erse manners in which the response properties of neurons are dynamically modulated to support adaptive cognitive functions. This neuromodulation is achieved through alterations in the biophysical properties of the neuron. However, changes in cognitive function do not arise directly from the modulation of in idual neurons, but are mediated by population dynamics in mesoscopic neural ensembles. Understanding this multiscale mapping is an important but nontrivial issue. Here, we bridge these different levels of description by showing how computational models parametrically map classic neuromodulatory processes onto systems-level models of neural activity. The ensuing critical balance of systems-level activity supports perception and action, although our knowledge of this mapping remains incomplete. In this way, quantitative models that link microscale neuronal neuromodulation to systems-level brain function highlight gaps in knowledge and suggest new directions for integrating theoretical and experimental work.
Publisher: Springer Science and Business Media LLC
Date: 22-04-2015
Abstract: The neural substrates of visual hallucinations remain an enigma, due primarily to the difficulties associated with directly interrogating the brain during hallucinatory episodes. To delineate the functional patterns of brain network activity and connectivity underlying visual hallucinations in Parkinson’s disease. In this study, we combined functional magnetic resonance imaging (MRI) with a behavioral task capable of eliciting visual misperceptions, a confirmed surrogate for visual hallucinations, in 35 patients with idiopathic Parkinson’s disease. We then applied an independent component analysis to extract time series information for large-scale neuronal networks that have been previously implicated in the pathophysiology of visual hallucinations. These data were subjected to a task-based functional connectivity analysis, thus providing the first objective description of the neural activity and connectivity during visual hallucinations in patients with Parkinson’s disease. Correct performance of the task was associated with increased activity in primary visual regions however, during visual misperceptions, this same visual network became actively coupled with the default mode network (DMN). Further, the frequency of misperception errors on the task was positively correlated with the strength of connectivity between these two systems, as well as with decreased activity in the dorsal attention network (DAN), and with impaired connectivity between the DAN and the DMNs, and ventral attention networks. Finally, each of the network abnormalities identified in our analysis were significantly correlated with two independent clinical measures of hallucination severity. Together, these results provide evidence that visual hallucinations are due to increased engagement of the DMN with the primary visual system, and emphasize the role of dysfunctional engagement of attentional networks in the pathophysiology of hallucinations.
Publisher: Springer Science and Business Media LLC
Date: 22-10-2015
Abstract: Freezing of gait is a debilitating symptom affecting many patients with Parkinson’s disease (PD), causing severe immobility and decreased quality of life. Turning is known to be the most common trigger for freezing and also causes the highest rates of falls. However, the pathophysiological basis for these effects is not well understood. This study used a virtual reality paradigm in combination with functional magnetic resonance imaging to explore the neural correlates underlying turning in 17 PD patients with freezing of gait (FOG) and 10 PD patients without FOG while off their dopaminergic medication. Participants used foot pedals to navigate a virtual environment, which allowed for blood oxygen level-dependent (BOLD) responses and footstep latencies to be compared between periods of straight “walking” and periods of turning through 90°. BOLD data were then analyzed using a mixed effects analysis. Within group similarities revealed that overall, PD patients with freezing relied heavily on cortical control to enable effective stepping with increased visual cortex activation during turning. Between groups differences showed that when turning, patients with freezing preferentially activated inferior frontal regions that have been implicated in the recruitment of a putative stopping network. In addition, freezers failed to activate premotor and superior parietal cortices. Finally, increased task-based functional connectivity was found in subcortical regions associated with gait and stopping within the freezers group during turning. These findings suggest that an increased propensity towards stopping in combination with reduced sensorimotor integration may underlie the neurobiology of freezing of gait during turning.
Publisher: Cold Spring Harbor Laboratory
Date: 10-06-2020
DOI: 10.1101/2020.06.09.141416
Abstract: The biological mechanisms that allow the brain to balance flexibility and integration remain poorly understood. A potential solution to this mystery may lie in a unique aspect of neurobiology, which is that numerous brain systems contain diffuse synaptic connectivity. In this manuscript, we demonstrate that increasing diffuse cortical coupling within a validated biophysical corticothalamic model traverses the system through a quasi-critical regime in which spatial heterogeneities in input noise support transient critical dynamics in distributed sub-regions. We then demonstrate that the presence of quasi-critical states coincides with known signatures of complex, adaptive brain network dynamics. Finally, we demonstrate the presence of similar dynamic signatures in empirical whole brain human neuroimaging data. Together, our results establish that modulating the balance between local and diffuse synaptic coupling in a thalamocortical model subtends the emergence of quasi-critical brain states that act to flexibly transition the brain between unique modes of information processing.
Publisher: Springer Science and Business Media LLC
Date: 21-06-2021
Publisher: Wiley
Date: 25-03-2018
DOI: 10.1111/SPC3.12382
Publisher: Oxford University Press (OUP)
Date: 20-04-2023
Abstract: Schizophrenia is a polygenetic mental disorder with heterogeneous positive and negative symptom constellations, and is associated with abnormal cortical connectivity. The thalamus has a coordinative role in cortical function and is key to the development of the cerebral cortex. Conversely, altered functional organization of the thalamus might relate to overarching cortical disruptions in schizophrenia, anchored in development. Here, we contrasted resting-state fMRI in 86 antipsychotic-naive first-episode early-onset schizophrenia (EOS) patients and 91 typically developing controls to study whether macroscale thalamic organization is altered in EOS. Employing dimensional reduction techniques on thalamocortical functional connectome (FC), we derived lateral–medial and anterior–posterior thalamic functional axes. We observed increased segregation of macroscale thalamic functional organization in EOS patients, which was related to altered thalamocortical interactions both in unimodal and transmodal networks. Using an ex vivo approximation of core-matrix cell distribution, we found that core cells particularly underlie the macroscale abnormalities in EOS patients. Moreover, the disruptions were associated with schizophrenia-related gene expression maps. Behavioral and disorder decoding analyses indicated that the macroscale hierarchy disturbances might perturb both perceptual and abstract cognitive functions and contribute to negative syndromes in patients. These findings provide mechanistic evidence for disrupted thalamocortical system in schizophrenia, suggesting a unitary pathophysiological framework.
Publisher: Cold Spring Harbor Laboratory
Date: 30-08-2017
DOI: 10.1101/182444
Abstract: Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascending neuromodulatory nuclei. To test this hypothesis in silico , we studied the effects of neural gain on network dynamics in a model of large-scale neuronal dynamics. We found that increases in neural gain pushed the network through an abrupt dynamical transition, leading to an integrated network topology that was maximal in frontoparietal ‘rich club’ regions. This gain-mediated transition was also associated with increased topological complexity, as well as increased variability in time-resolved topological structure, further highlighting the potential computational benefits of the gain-mediated network transition. These results support the hypothesis that neural gain modulation has the computational capacity to mediate the balance between integration and segregation in the brain.
Publisher: Wiley
Date: 07-2018
DOI: 10.1002/MDS.27417
Abstract: The purpose of this study is to identify and characterize subtypes of freezing of gait by using a novel questionnaire designed to delineate freezing patterns based on self-reported and behavioral gait assessment. A total of 41 Parkinson's patients with freezing completed the Characterizing Freezing of Gait questionnaire that identifies situations that exacerbate freezing. This instrument underwent examination for construct validity and internal consistency, after which a data-driven clustering approach was employed to identify distinct patterns amongst in idual responses. Behavioral freezing assessments in both dopaminergic states were compared across 3 identified subgroups. This novel questionnaire demonstrated construct validity (severity scores correlated with percentage of time frozen r = 0.54) and internal consistency (Cronbach's α = .937), and thus demonstrated promising utility for identifying patterns of freezing that are independently related to motor, anxiety, and attentional impairments. Patients with freezing may be dissociable based on underlying neurobiological underpinnings that would have significant implications for targeting future treatments. © 2018 International Parkinson and Movement Disorder Society.
Publisher: Cold Spring Harbor Laboratory
Date: 10-05-2021
DOI: 10.1101/2021.05.10.443403
Abstract: Hubs in the human brain support behaviors that arise from brain network interactions. Previous studies have identified hub regions in the human thalamus that are connected with multiple functional networks. However, the behavioral significance of thalamic hubs has yet to be established. Our framework predicts that thalamic subregions with strong hub properties are broadly involved in functions across multiple cognitive domains. To test this prediction, we studied human patients with focal thalamic lesions in conjunction with network analyses of the human thalamocortical functional connectome. In support of our prediction, lesions to thalamic subregions with stronger hub properties were associated with widespread deficits in executive, language, and memory functions, whereas lesions to thalamic subregions with weaker hub properties were associated with more limited deficits. These results highlight how a large-scale network model can broaden our understanding of thalamic function for human cognition.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 21-04-2023
Abstract: Nanowire networks (NWNs) mimic the brain’s neurosynaptic connectivity and emergent dynamics. Consequently, NWNs may also emulate the synaptic processes that enable higher-order cognitive functions such as learning and memory. A quintessential cognitive task used to measure human working memory is the n -back task. In this study, task variations inspired by the n -back task are implemented in a NWN device, and external feedback is applied to emulate brain-like supervised and reinforcement learning. NWNs are found to retain information in working memory to at least n = 7 steps back, remarkably similar to the originally proposed “seven plus or minus two” rule for human subjects. Simulations elucidate how synapse-like NWN junction plasticity depends on previous synaptic modifications, analogous to “synaptic metaplasticity” in the brain, and how memory is consolidated via strengthening and pruning of synaptic conductance pathways.
Publisher: Cold Spring Harbor Laboratory
Date: 18-02-2018
DOI: 10.1101/266635
Abstract: The human brain integrates erse cognitive processes into a coherent whole, shifting fluidly as a function of changing environmental demands. Despite recent progress, the neurobiological mechanisms responsible for this dynamic system-level integration remain poorly understood. Here, we used multi-task fMRI data from the Human Connectome Project to examine the spatiotemporal architecture of cognition in the human brain. By investigating the spatial, dynamic and molecular signatures of system-wide neural activity across a range of cognitive tasks, we show that large-scale neuronal activity converges onto a low dimensional manifold that facilitates the dynamic execution of erse task states. Flow within this attractor space is associated with dissociable cognitive functions, and with unique patterns of network-level topology and information processing complexity. The axes of the low-dimensional neurocognitive architecture align with regional differences in the density of neuromodulatory receptors, which in turn relate to distinct signatures of network controllability estimated from the structural connectome. These results advance our understanding of functional brain organization by emphasizing the interface between low dimensional neural activity, network topology, neuromodulatory systems and cognitive function. A erse set of neuromodulators facilitates the formation of a dynamic, low-dimensional integrative core in the brain that is recruited by erse cognitive demands
Publisher: American Psychological Association (APA)
Date: 06-2016
DOI: 10.1037/BNE0000137
Abstract: This study aimed to identify default mode network (DMN) functional connectivity deficits in patients with mild cognitive impairment (MCI) and sleep disturbance, relative to those with MCI and no sleep disturbance. A control group was included to aid in identifying DMN changes specific to MCI. A cross-sectional, single-center study was performed at the Brain and Mind Research Centre in Sydney, Australia. Participants (95 adults over the age of 65: 38 controls and 57 meeting criteria for MCI) underwent resting-state functional MRI along with comprehensive neuropsychological, medical, and psychiatric assessment. Self-report data were collected including sleep quality assessment via the Pittsburgh Sleep Quality Index. A total score of greater than 5 on the Pittsburgh Sleep Quality Index was used to signify the presence of significant sleep disturbance, as per commonly used methodology. Using this criterion, 53% (n = 30) of our MCI group were classified as sleep-disturbed. Whereas the total group of MCI subjects and controls demonstrated no significant differences, sleep-disturbed MCIs demonstrated increased connectivity between temporal and parietal regions, and decreased connectivity between the prefrontal cortex and the temporoparietal junction relative to sleep-disturbed controls. Relative to those MCIs without sleep disturbance, sleep-disturbed MCI participants demonstrated significantly diminished DMN connectivity between temporal and parietal regions, a finding that was particularly pronounced in amnestic MCI. Sleep disturbance in MCI is associated with distinct alterations in DMN functional connectivity in brain regions underpinning salient memory and sleep systems. Future studies may build on these results via experimental manipulation and objective measurement of sleep. (PsycINFO Database Record
Publisher: Wiley
Date: 08-2012
DOI: 10.1002/MDS.25104
Abstract: Patients with advanced Parkinson's disease (PD) commonly suffer with significant executive dysfunction and concomitant visual hallucinations. Although the underlying pathophysiology remains poorly understood, numerous studies have highlighted the strong association between these neuropsychiatric features, suggesting common neural pathways. Although previous neuroimaging studies have identified widespread volume loss across a number of cortical regions, to date, no studies have utilized proton magnetic resonance spectroscopy to provide insights into how neurometabolic changes may relate to such symptoms. Twenty patients with PD and 20 healthy controls underwent spectroscopy to determine the N-acetyl aspartate/creatine (NAA/Cr) ratio, which reflects the degree of neuronal integrity in neurodegenerative diseases. Voxels were obtained from the anterior cingulate cortex (ACC), an area critical for a wide range of executive mechanisms as well as from a control volume in the posterior cingulate cortex (PCC). Compared to controls, patients with PD had lower NAA/Cr ratios in the ACC. In turn, lower NAA/Cr ratios significantly correlated with poorer executive function on tasks of attentional set-shifting and response inhibition, as well as more-severe psychotic symptoms and poorer performance on the Bistable Percept Paradigm, a neuropsychological probe of visual hallucinations. NAA/Cr ratios were significantly lower in hallucinators, compared to nonhallucinators, within the ACC, but did not differ in the PCC. These results suggest that loss of neuronal integrity within the ACC plays an important role in the pathophysiology underlying executive functioning and visual hallucinations in PD. © 2012 Movement Disorder Society.
Publisher: Society for Neuroscience
Date: 09-11-2022
DOI: 10.1523/JNEUROSCI.1503-22.2022
Abstract: Biological neural networks adapt and learn in erse behavioral contexts. Artificial neural networks (ANNs) have exploited biological properties to solve complex problems. However, despite their effectiveness for specific tasks, ANNs are yet to realize the flexibility and adaptability of biological cognition. This review highlights recent advances in computational and experimental research to advance our understanding of biological and artificial intelligence. In particular, we discuss critical mechanisms from the cellular, systems, and cognitive neuroscience fields that have contributed to refining the architecture and training algorithms of ANNs. Additionally, we discuss how recent work used ANNs to understand complex neuronal correlates of cognition and to process high throughput behavioral data.
Publisher: Cold Spring Harbor Laboratory
Date: 11-07-2022
DOI: 10.1101/2022.07.10.499497
Abstract: A characteristic feature of human cognition is our ability to ‘multi-task’ – performing two or more tasks in parallel – particularly when one task is well-learned. How the brain supports this capacity remains poorly understood. Most past studies have focussed on identifying the areas of the brain – typically the dorsolateral prefrontal cortex – that are required to navigate information processing bottlenecks. In contrast, we take a systems neuroscience approach to test the hypothesis that the capacity to conduct effective parallel processing relies on a distributed architecture that interconnects the cerebral cortex with the cerebellum. The latter structure contains over half of the neurons in the adult human brain, and is well-suited to support the fast, effective, dynamic sequences required to perform tasks relatively automatically. By delegating stereotyped within-task computations to the cerebellum, the cerebral cortex can be freed up to focus on the more challenging aspects of performing the tasks in parallel. To test this hypothesis, we analysed task-based fMRI data from 50 participants who performed a task in which they either balanced an avatar on a screen (‘Balance’), performed serial-7 subtractions (‘Calculation’) or performed both in parallel (‘Dual-Task’). Using a set of approaches that include dimensionality reduction, structure-function coupling and time-varying functional connectivity, we provide robust evidence in support of our hypothesis. We conclude that distributed interactions between the cerebral cortex and cerebellum are crucially involved in parallel processing in the human brain.
Publisher: Wiley
Date: 26-04-2021
DOI: 10.1002/MDS.28615
Abstract: Pathology in the noradrenergic A6 locus coeruleus has not been compared with more rostral dopaminergic A9 substantia nigra and A10 ventral tegmental area, and cholinergic Ch4 basal nucleus and Ch1/2 septal regions in the same cases of Parkinson's disease (PD). To determine whether there is a gradient of caudal to rostral cell loss in PD. Postmortem brains were collected from longitudinally followed donors with PD (n = 14) and aged‐matched healthy donors (n = 13), six with restricted brainstem Lewy pathology (RLP), fixed in formalin and serial tissue slabs processed for cell and pathological quantitation. Noradrenergic A6 neurons were assessed and compared with previously published midbrain and basal forebrain data. From these data, regression estimates of pathological onset and progression were determined. Restricted Lewy pathology (RLP) cases had high pathological variability but no significant reduction in neurons. Pathology containing A6 neuron loss started at PD diagnosis and progressed faster (2.4% p.a) than the loss of dopaminergic A9 neurons (2% loss p.a.). Cases with dementia had significantly more pathology in noradrenergic and cholinergic neurons, had greater noradrenergic A6 neuron loss (29% more, progressing at 3.2% p.a.), and a selective loss of lateral A10 nonmelanized dopamine‐producing neurons (starting a decade following diagnosis). These findings show that in the same Parkinson's disease cases cell loss in these neurotransmitter systems does not follow a strict caudal to rostral trajectory and suggests symptom onset may relate to substantial pathology in the noradrenergic A6 locus coeruleus neurons in people with reduced dopamine‐producing A9 substantia nigra neurons. © 2021 International Parkinson and Movement Disorder Society
Publisher: Elsevier BV
Date: 2022
Publisher: Cold Spring Harbor Laboratory
Date: 19-03-2021
DOI: 10.1101/2021.03.17.435827
Abstract: Understanding the variation in community composition and species abundances, i.e., β- ersity, is at the heart of community ecology. A common approach to examine β- ersity is to evaluate directional turnover in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distances. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 149 datasets comprising different types of organisms and environments. We modelled an exponential distance decay for each dataset using generalized linear models and extracted r 2 and slope to analyse the strength and the rate of the decay. We studied whether taxonomic or functional similarity has stronger decay across the spatial and environmental distances. We also unveiled the factors driving the rate of decay across the datasets, including latitude, spatial extent, realm, and organismal features. Taxonomic distance decay was stronger along spatial and environmental distances compared with functional distance decay. The rate of taxonomic spatial distance decay was the fastest in the datasets from mid-latitudes while the rate of functional decay increased with latitude. Overall, datasets covering larger spatial extents showed a lower rate of decay along spatial distances but a higher rate of decay along environmental distances. Marine ecosystems had the slowest rate of decay. This synthesis is an important step towards a more holistic understanding of patterns and drivers of taxonomic and functional β- ersity.
Publisher: Frontiers Media SA
Date: 06-03-2020
Publisher: Springer Science and Business Media LLC
Date: 17-02-2022
DOI: 10.1038/S41531-022-00279-X
Abstract: Cognitive fluctuations are a characteristic and distressing disturbance of attention and consciousness seen in patients with Dementia with Lewy bodies and Parkinson’s disease dementia. It has been proposed that fluctuations result from disruption of key neuromodulatory systems supporting states of attention and wakefulness which are normally characterised by temporally variable and highly integrated functional network architectures. In this study, patients with DLB ( n = 25) and age-matched controls ( n = 49) were assessed using dynamic resting state fMRI. A dynamic network signature of reduced temporal variability and integration was identified in DLB patients compared to controls. Reduced temporal variability correlated significantly with fluctuation-related measures using a sustained attention task. A less integrated (more segregated) functional network architecture was seen in DLB patients compared to the control group, with regions of reduced integration observed across dorsal and ventral attention, sensorimotor, visual, cingulo-opercular and cingulo-parietal networks. Reduced network integration correlated positively with subjective and objective measures of fluctuations. Regions of reduced integration and unstable regional assignments significantly matched areas of expression of specific classes of noradrenergic and cholinergic receptors across the cerebral cortex. Correlating topological measures with maps of neurotransmitter/neuromodulator receptor gene expression, we found that regions of reduced integration and unstable modular assignments correlated significantly with the pattern of expression of subclasses of noradrenergic and cholinergic receptors across the cerebral cortex. Altogether, these findings demonstrate that cognitive fluctuations are associated with an imaging signature of dynamic network impairment linked to specific neurotransmitters/neuromodulators within the ascending arousal system, highlighting novel potential diagnostic and therapeutic approaches for this troubling symptom.
Publisher: Cold Spring Harbor Laboratory
Date: 03-08-2018
DOI: 10.1101/383141
Abstract: An inefficient integration between bottom-up visual input and higher-order visual processing regions is implicated in the manifestation of visual hallucinations (VH) in Parkinson’s disease (PD). Using graph theory, the current study aimed to investigate white matter contributions to this perceptual imbalance hypothesis. Twenty-nine PD patients reported their hallucinatory behaviour on a questionnaire and performed a behavioural test that has been shown to elicit misperceptions. A composite score derived from these measures was used as a proxy for hallucinations severity and was correlated to connectivity strength of the network using the Network Based Statistic approach. The results showed that the severity of VH was associated with reduced connectivity within a large sub-network. This network included the majority of the erse club and showed overall greater between - and within-module scores, compared to nodes not associated with hallucination severity. Furthermore, a reduction in between-module connectivity in the lateral occipital cortex, insula and pars orbitalis, as well as decreased within-module connectivity in the prefrontal, somatosensory and primary visual cortices were associated with VH severity. In contrast, the severity of VH was associated with an increase in between - and within-module connectivity in the orbitofrontal and temporal cortex, as well as regions comprising the dorsal attentional and DMN. These results suggest that the severity of VHs is associated with marked alterations in structural network topology, highlighted by a reduction in connectivity strength across a large sub-network, as well as changes in participation across top-down visual processing centres, visual and attentional networks. Therefore, impaired integration across the perceptual hierarchy may result in the inefficient transfer of information that gives rise to VHs in PD.
Publisher: Oxford University Press (OUP)
Date: 07-09-2023
Publisher: Cold Spring Harbor Laboratory
Date: 26-10-2023
Publisher: Cold Spring Harbor Laboratory
Date: 27-07-2017
DOI: 10.1101/169102
Abstract: The human brain is able to flexibly adapt its information processing capacity to meet a variety of cognitive challenges. Recent evidence suggests that this flexibility is reflected in the dynamic reorganization of the functional connectome. The ascending catecholaminergic arousal systems of the brain are a plausible candidate mechanism for driving alterations in network architecture, enabling efficient deployment of cognitive resources when the environment demands them. We tested this hypothesis by analyzing both task-free and task-based fMRI data following the administration of atomoxetine, a noradrenaline reuptake inhibitor, compared to placebo, in two separate human fMRI studies. Our results demonstrate that the manipulation of central catecholamine levels leads to a reorganization of the functional connectome in a manner that is sensitive to ongoing cognitive demands.
Publisher: Cold Spring Harbor Laboratory
Date: 15-07-2023
DOI: 10.1101/2023.07.13.548934
Abstract: Investigations into the neural basis of conscious perception span multiple scales and levels of analysis. There is, however, a theoretical and methodological gap between advances made at the microscopic scale in animal models and those made at the macroscopic scale in human cognitive neuroscience that places a fundamental limit on our understanding of the neurobiological basis of consciousness. Here, we use computational modelling to bridge this gap. Specifically, we show that the same mechanism that underlies threshold detection in mice – apical dendrite mediated burst firing in thick-tufted layer V pyramidal neurons – determines perceptual dominance in a thalamocortical model of binocular rivalry – a staple task in the cognitive neuroscience of consciousness. The model conforms to the constraints imposed by decades of previous research into binocular rivalry and generalises to the more sophisticated rivalry tasks studied in humans generating novel, testable, explanations of the role of expectation and attention in rivalry. Our model, therefore, provides an empirically-tractable bridge between cellular-level mechanisms and conscious perception.
Publisher: Cold Spring Harbor Laboratory
Date: 02-10-2020
DOI: 10.1101/2020.09.30.321679
Abstract: Network neuroscience has yielded crucial insights into the systems-level organisation of the brain, however the indirect nature of neuroimaging recordings has rendered the discovery of generative mechanisms for a given function inherently challenging. In parallel, neural network machine-learning models have exhibited breakthrough performance in tackling a range of complex problems, however the principles that govern learning-induced modifications to network structure remain poorly understood, in part due to a lack of analytic tools to quantify the dynamics of network structure. While the question of how network reconfiguration supports learning is mirrored in machine learning and network neuroscience, the different contexts of these fields provides a timely opportunity to bring them together synergistically to investigate the problem. Here we combine these two approaches to reveal connections between the brain’s network structure and the emerging network structure of an artificial neural network. Specifically, we train a shallow, feedforward neural network to classify handwritten digits and then used a combination of systems neuroscience and information theoretic tools to perform ‘virtual brain analytics’ on the resultant edge weights and activity patterns of each node. We identify three distinct phases of network reconfiguration across learning, each of which are characterised by unique topological and information-theoretic signatures. Each phase involves aligning the connections of the neural network with patterns of information contained in the input dataset or preceding layers (as relevant). We also observe a process of low-dimensional category separation in the network as a function of learning. Our results offer a systems-level perspective of how artificial neural networks function – in terms of multi-stage reorganization of edge weights and activity patterns to effectively exploit the information content of input data during edge-weight training – while simultaneously enriching our understanding of the methods used by systems neuroscience.
Publisher: MIT Press - Journals
Date: 2020
DOI: 10.1162/NETN_A_00116
Abstract: The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge of the spatiotemporal organization of these interactions is critical for establishing a solid understanding of the brain’s functional architecture and the relationship between neural dynamics and cognition in health and disease. The possibility of studying these dynamics through careful analysis of neuroimaging data has catalyzed substantial interest in methods that estimate time-resolved fluctuations in functional connectivity (often referred to as “dynamic” or time-varying functional connectivity TVFC). At the same time, debates have emerged regarding the application of TVFC analyses to resting fMRI data, and about the statistical validity, physiological origins, and cognitive and behavioral relevance of resting TVFC. These and other unresolved issues complicate interpretation of resting TVFC findings and limit the insights that can be gained from this promising new research area. This article brings together scientists with a variety of perspectives on resting TVFC to review the current literature in light of these issues. We introduce core concepts, define key terms, summarize controversies and open questions, and present a forward-looking perspective on how resting TVFC analyses can be rigorously and productively applied to investigate a wide range of questions in cognitive and systems neuroscience.
Publisher: Wiley
Date: 12-12-2015
Publisher: MIT Press
Date: 2022
DOI: 10.1162/NETN_A_00230
Abstract: Most human neuroscience research to date has focused on statistical approaches that describe stationary patterns of localized neural activity or blood flow. While these patterns are often interpreted in light of dynamic, information-processing concepts, the static, local, and inferential nature of the statistical approach makes it challenging to directly link neuroimaging results to plausible underlying neural mechanisms. Here, we argue that dynamical systems theory provides the crucial mechanistic framework for characterizing both the brain’s time-varying quality and its partial stability in the face of perturbations, and hence, that this perspective can have a profound impact on the interpretation of human neuroimaging results and their relationship with behavior. After briefly reviewing some key terminology, we identify three key ways in which neuroimaging analyses can embrace a dynamical systems perspective: by shifting from a local to a more global perspective, by focusing on dynamics instead of static snapshots of neural activity, and by embracing modeling approaches that map neural dynamics using “forward” models. Through this approach, we envisage le opportunities for neuroimaging researchers to enrich their understanding of the dynamic neural mechanisms that support a wide array of brain functions, both in health and in the setting of psychopathology.
Publisher: Cold Spring Harbor Laboratory
Date: 02-08-2018
DOI: 10.1101/382994
Abstract: Parkinson’s disease is primarily characterised by diminished dopaminergic function, however the impact of these impairments on large-scale brain dynamics remains unclear. It has been difficult to disentangle the direct effects of Parkinson’s disease from compensatory changes that reconfigure the functional signature of the whole brain network. To examine the causal role of dopamine depletion in network-level topology, we investigated time-varying network structure in 37 in iduals with idiopathic Parkinson’s disease, both ‘On’ and ‘Off’ dopamine replacement therapy, along with 50 age-matched, healthy control subjects using resting-state functional MRI. By tracking dynamic network-level topology, we found that the Parkinson’s disease ‘Off’ state was associated with greater network-level integration than in the ‘On’ state. The extent of integration in the ‘Off’ state inversely correlated with motor symptom severity, suggesting that a shift toward a more integrated network topology may be a compensatory mechanism associated with preserved motor function in the dopamine depleted ‘Off’ state. Furthermore, we were able to demonstrate that measures of both cognitive and brain reserve (i.e., premorbid intelligence and whole brain grey matter volume) had a positive relationship with the relative increase in network integration observed in the dopaminergic ‘Off’ state. This suggests that each of these factors plays an important role in promoting network integration in the dopaminergic ‘Off’ state. Our findings provide a mechanistic basis for understanding the PD ‘Off’ state and provide a further conceptual link with network-level reconfiguration. Together, our results highlight the mechanisms responsible for pathological and compensatory change in Parkinson’s disease.
Publisher: Cold Spring Harbor Laboratory
Date: 26-09-2017
DOI: 10.1101/194092
Abstract: Mind wandering represents the human capacity for internally focussed thought, and relies upon the brain’s default network and its interactions with attentional networks. Studies have characterised mind wandering in healthy people, yet there is limited understanding of how this capacity is affected in clinical populations. This study used a validated thought-s ling task to probe mind wandering capacity in two neurodegenerative disorders: behavioural variant frontotemporal dementia (bvFTD n=35) and Alzheimer’s disease (AD n=24), compared to older controls (n=37). These patient groups were selected due to canonical structural and functional changes across sites of the default and frontoparietal networks, and well-defined impairments in cognitive processes that support mind wandering. Relative to controls, bvFTD patients displayed significantly reduced mind wandering capacity, offset by a significant increase in stimulus-bound thought. In contrast, AD patients demonstrated comparable levels of mind wandering to controls, in the context of a relatively subtle shift towards stimulus-/task-related forms of thought. In the patient groups, mind wandering was associated with grey matter integrity in the hippoc us arahippoc us, striatum, insula and orbitofrontal cortex. Resting state functional connectivity revealed associations between mind wandering capacity and connectivity within and between regions of the frontoparietal and default networks, with distinct patterns evident in patients vs. controls. These findings support a relationship between altered mind wandering capacity in neurodegenerative disorders, and structural and functional integrity of the default and frontoparietal networks. This study highlights a dimension of cognitive dysfunction not well documented in neurodegenerative disorders, and validates current models of mind wandering in a clinical population. Humans spend much of their waking life engaged in mind wandering. Underlying brain systems supporting this complex ability have been established in healthy in iduals, yet it remains unclear how mind wandering is altered in neuropsychiatric populations. We reveal changes in the thought profiles elicited during periods of low cognitive demand in dementia, resulting in reduced mind wandering and an increased propensity towards stimulus-bound thought. These altered thought profiles were associated with structural and functional brain changes in the hippoc us, default and frontoparietal networks key regions implicated in internal mentation in healthy in iduals. Our findings provide a unique clinical validation of current theoretical models of mind wandering, and reveal a dimension of cognitive dysfunction that has received scant attention in dementia.
Publisher: Elsevier BV
Date: 11-2021
Publisher: Elsevier BV
Date: 08-2014
DOI: 10.1016/J.PARKRELDIS.2014.04.027
Abstract: Neuropsychiatric symptoms (NPS) in Parkinson's disease (PD) have been mostly attributed to neurotransmitter imbalances. However, recent findings suggest that gray matter atrophy also contributes to NPS in PD. We contrast PD patients with different levels of NPS, who are well-matched for dopaminergic medication levels and disease stage, to identify the fronto-striatal gray matter atrophy areas associated with NPS in PD. Fifty mild, non-demented PD patients were included. We median-split the group via a neuropsychiatric screening tool (Cambridge Behavioural Inventory-Revised), which resulted in higher vs. lower NPS groups (n = 25 in each group). Using T1 brain scans acquired on a 3 Tesla MRI scanner, voxel-based morphometry analysis was applied to characterize the pattern of fronto-striatal gray matter atrophy associated with elevated NPS. We found that the higher NPS group was characterized by greater atrophy in the prefrontal cortex, but not striatal areas. This was further corroborated by a post-hoc analysis cross-correlating the severity of NPS with gray matter loss across the whole PD group, which revealed that atrophy in the orbitofrontal cortex and frontal pole was specifically associated with elevated NPS. Prefrontal cortex atrophy in PD has an additional effect to dopamine replacement therapy on the generation of NPS in these patients. These findings are an important step towards the delineation of atrophy vs. neurochemical imbalance in PD, and the results emphasize the importance of considering interactions between prefrontal atrophy and neurochemical dysfunction in the genesis of neuropsychiatric symptoms in PD.
Publisher: Springer Science and Business Media LLC
Date: 26-03-2023
DOI: 10.1186/S40035-023-00347-Z
Abstract: In stressful or anxiety-provoking situations, most people with Parkinson’s disease (PD) experience a general worsening of motor symptoms, including their gait impairments. However, a proportion of patients actually report benefits from experiencing—or even purposely inducing—stressful or high-arousal situations. Using data from a large-scale international survey study among 4324 people with PD and gait impairments within the online Fox Insight (USA) and ParkinsonNEXT (NL) cohorts, we demonstrate that in iduals with PD deploy an array of mental state alteration strategies to cope with their gait impairment. Crucially, these strategies differ along an axis of arousal—some act to heighten, whereas others diminish, overall sympathetic tone. Together, our observations suggest that arousal may act as a double-edged sword for gait control in PD. We propose a theoretical, neurobiological framework to explain why heightened arousal can have detrimental effects on the occurrence and severity of gait impairments in some in iduals, while alleviating them in others. Specifically, we postulate that this seemingly contradictory phenomenon is explained by the inherent features of the ascending arousal system: namely, that arousal is related to task performance by an inverted u-shaped curve (the so-called Yerkes and Dodson relationship). We propose that the noradrenergic locus coeruleus plays an important role in modulating PD symptom severity and expression, by regulating arousal and by mediating network-level functional integration across the brain. The ability of the locus coeruleus to facilitate dynamic ‘cross-talk’ between distinct, otherwise largely segregated brain regions may facilitate the necessary cerebral compensation for gait impairments in PD. In the presence of suboptimal arousal, compensatory networks may be too segregated to allow for adequate compensation. Conversely, with supraoptimal arousal, increased cross-talk between competing inputs of these complementary networks may emerge and become dysfunctional. Because the locus coeruleus degenerates with disease progression, finetuning of this delicate balance becomes increasingly difficult, heightening the need for mental strategies to self-modulate arousal and facilitate shifting from a sub- or supraoptimal state of arousal to improve gait performance. Recognition of this underlying mechanism emphasises the importance of PD-specific rehabilitation strategies to alleviate gait disability.
Publisher: Oxford University Press (OUP)
Date: 08-06-2016
Publisher: Oxford University Press (OUP)
Date: 20-01-2016
DOI: 10.1093/BRAIN/AWV399
Abstract: Pathophysiological and atrophic changes in the cerebellum are documented in Parkinson's disease. Without compensatory activity, such abnormalities could potentially have more widespread effects on both motor and non-motor symptoms. We examined how atrophic change in the cerebellum impacts functional connectivity patterns within the cerebellum and between cerebellar-cortical networks in 42 patients with Parkinson's disease and 29 control subjects. Voxel-based morphometry confirmed grey matter loss across the motor and cognitive cerebellar territories in the patient cohort. The extent of cerebellar atrophy correlated with decreased resting-state connectivity between the cerebellum and large-scale cortical networks, including the sensorimotor, dorsal attention and default networks, but with increased connectivity between the cerebellum and frontoparietal networks. The severity of patients' motor impairment was predicted by a combination of cerebellar atrophy and decreased cerebellar-sensorimotor connectivity. These findings demonstrate that cerebellar atrophy is related to both increases and decreases in cerebellar-cortical connectivity in Parkinson's disease, identifying potential cerebellar driven functional changes associated with sensorimotor deficits. A post hoc analysis exploring the effect of atrophy in the subthalamic nucleus, a cerebellar input source, confirmed that a significant negative relationship between grey matter volume and intrinsic cerebellar connectivity seen in controls was absent in the patients. This suggests that the modulatory relationship of the subthalamic nucleus on intracerebellar connectivity is lost in Parkinson's disease, which may contribute to pathological activation within the cerebellum. The results confirm significant changes in cerebellar network activity in Parkinson's disease and reveal that such changes occur in association with atrophy of the cerebellum.
Publisher: MIT Press - Journals
Date: 2020
DOI: 10.1162/NETN_A_00127
Abstract: Both natural and engineered networks are often modular. Whether a network node interacts with only nodes from its own module or nodes from multiple modules provides insight into its functional role. The participation coefficient ( PC) is typically used to measure this attribute, although its value also depends on the size and connectedness of the module it belongs to and may lead to nonintuitive identification of highly connected nodes. Here, we develop a normalized PC that reduces the influence of intramodular connectivity compared with the conventional PC. Using brain, C. elegans, airport, and simulated networks, we show that our measure of participation is not influenced by the size or connectedness of modules, while preserving conceptual and mathematical properties, of the classic formulation of PC. Unlike the conventional PC, we identify London and New York as high participators in the air traffic network and demonstrate stronger associations with working memory in human brain networks, yielding new insights into nodal participation across network modules.
Publisher: SAGE Publications
Date: 14-11-2014
Abstract: Freezing of gait is a disabling symptom of Parkinson’s disease that causes a paroxysmal cessation of normal footsteps while walking. Despite a great deal of empirical research, the pathophysiological mechanisms underlying the symptom remain unclear. In this targeted review, we synthesize recent insights from research into freezing in an effort to clarify the neurobiological basis of this phenomenon. We conclude that freezing manifests via a common neural pathway in which transient increases in inhibitory basal ganglia output lead to decreased activity within the brainstem structures that coordinate gait. This cascade may be triggered through dopaminergic depletion in the striatum and over-activity within the subthalamic nucleus. These insights may benefit both the diagnostic and therapeutic management of freezing in Parkinson’s disease.
Publisher: Springer Science and Business Media LLC
Date: 26-05-2023
Publisher: Springer Science and Business Media LLC
Date: 09-12-2015
DOI: 10.1038/NCOMMS9885
Abstract: Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy in iduals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders.
Publisher: Wiley
Date: 05-04-2022
DOI: 10.1002/MDS.28999
Abstract: Freezing of gait is a complex paroxysmal phenomenon that is associated with a variety of sensorimotor, cognitive and affective deficits, and significantly impacts quality of life in patients with Parkinson's disease (PD). Despite a growing body of evidence that suggests anxiety may be a crucial contributor to freezing of gait, no research study to date has investigated neural underpinnings of anxiety‐induced freezing of gait. Here, we aimed to investigate how anxiety‐inducing contexts might “set the stage for freezing,” through the ascending arousal system, by examining an anxiety‐inducing virtual reality gait paradigm inside functional magnetic resonance imaging (fMRI). We used a virtual reality gait paradigm that has been validated to elicit anxiety by having participants navigate a virtual plank, while simultaneously collecting task‐based fMRI from in iduals with idiopathic PD with confirmed freezing of gait. First, we established that the threatening condition provoked more freezing when compared to the non‐threatening condition. By using a dynamic connectivity analysis, we identified patterns of increased “cross‐talk” within and between motor, limbic, and cognitive networks in the threatening conditions. We established that the threatening condition was associated with heightened network integration. We confirmed the sympathetic nature of this phenomenon by demonstrating an increase in pupil dilation during the anxiety‐inducing condition of the virtual reality gait paradigm in a secondary experiment. In conclusion, our findings represent a neurobiological mechanistic pathway through which heightened sympathetic arousal related to anxiety could foster increased “cross‐talk” between distributed cortical networks that ultimately manifest as paroxysmal episodes of freezing of gait. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
Publisher: Springer Science and Business Media LLC
Date: 03-03-2016
DOI: 10.1007/S00702-016-1528-3
Abstract: Mechanistic insights into visual hallucinations (VH) in Parkinson's disease (PD) have suggested a role for impaired attentional processes. The current study tested 25 PD patients with and 28 PD patients without VH on the attentional network test. Hallucinators had significantly lower accuracy rates compared to non-hallucinators, but no differences were found in reaction times. This suggests that hallucinators show deficits in attentional processes and conflict monitoring. Our findings provide novel behavioural insights that dovetail with current neurobiological frameworks of VH.
Publisher: Frontiers Media SA
Date: 2013
Publisher: IEEE
Date: 08-2014
Publisher: Elsevier BV
Date: 07-2019
DOI: 10.1016/J.TICS.2019.04.002
Abstract: Cognitive function relies on the dynamic cooperation of specialized regions of the brain however, the elements of the system responsible for coordinating this interaction remain poorly understood. In this Opinion article I argue that this capacity is mediated in part by competitive and cooperative dynamic interactions between two prominent metabotropic neuromodulatory systems - the cholinergic basal forebrain and the noradrenergic locus coeruleus (LC). I assert that activity in these projection nuclei regulates the amount of segregation and integration within the whole brain network by modulating the activity of a erse set of specialized regions of the brain on a timescale relevant for cognition and attention.
Publisher: eLife Sciences Publications, Ltd
Date: 24-01-2018
Publisher: Cold Spring Harbor Laboratory
Date: 14-06-2018
DOI: 10.1101/347658
Abstract: A mismatch between top-down expectations and incoming sensory information is thought to be associated with hallucinations across a range of neuropsychiatric disorders. In Parkinson’s disease with visual hallucinations, abnormal activity within the default network, and its pattern of connectivity with early visual regions, has been identified as a potential pathological source of the internally generated expectations that override incoming sensory input. In the context of attention deficits and visual dysfunction, mental imagery and perceptual expectancies generated across the default network are suggested to exert excessive influence over earlier visual regions, leading to aberrant perceptual experiences. Whilst converging neuroimaging evidence has identified unconstrained default network activity in Parkinson’s disease with hallucinations, to date there has been a lack of behavioural evidence to confirm the consequences of an over-engaged default mode network – therefore the contributions it might make to hallucination phenomenology remain speculative. To address this, we administered a validated thought-s ling task to 38 Parkinson’s disease patients (18 with hallucinations 20 without) and 40 controls, to test the hypothesis that in iduals with hallucinations experience an increased frequency of mind-wandering – a form of spontaneous cognition strongly associated with mental imagery and default network activity. The neural correlates of mind-wandering frequency were examined in relation to resting-state functional connectivity. Our results showed that patients with hallucinations exhibited significantly higher mind-wandering frequencies compared to non-hallucinators, who in turn had reduced levels of mind-wandering relative to controls. Inter-network connectivity and seed-to-voxel analyses confirmed that increased mind-wandering in the hallucinating vs. non-hallucinating group was associated with greater coupling between the primary visual cortex and dorsal default network. Taken together, both elevated mind-wandering and increased default-visual network coupling emerged as a distinguishing feature of the hallucinatory phenotype. We propose that the finding of increased mind-wandering reflects unconstrained spontaneous thought and mental imagery, which in turn furnish the content of visual hallucinations. Our findings suggest that primary visual cortex to dorsal default network coupling may provide a neural substrate by which regions of the default network exert disproportionate influence over ongoing visual perception. These findings refine current models of visual hallucinations by identifying a specific cognitive phenomenon and neural substrate consistent with the top-down influences over perception that have been implicated in visual hallucinations.
Publisher: Proceedings of the National Academy of Sciences
Date: 08-08-2022
Abstract: Brain activity is constrained by local availability of chemical energy, which is generated through compartmentalized metabolic processes. By analyzing data of whole human brain gene expression, we characterize the spatial distribution of seven glucose and monocarboxylate membrane transporters that mediate astrocyte–neuron lactate shuttle transfer of energy. We found that the gene coding for neuronal MCT2 is the only gene enriched in cerebral cortex where its abundance is inversely correlated with cortical thickness. Coexpression network analysis revealed that MCT2 was the only gene participating in an organized gene cluster enriched in K + dynamics. Indeed, the expression of K ATP subunits, which mediate lactate increases with spiking activity, is spatially coupled to MCT2 distribution. Notably, MCT2 expression correlated with fluorodeoxyglucose positron emission tomography task-dependent glucose utilization. Finally, the MCT2 messenger RNA gradient closely overlaps with functional MRI brain regions associated with attention, arousal, and stress. Our results highlight neuronal MCT2 lactate transporter as a key component of the cross-talk between astrocytes and neurons and a link between metabolism, cortical structure, and state-dependent brain function.
Publisher: Elsevier BV
Date: 09-2011
DOI: 10.1016/J.JOCN.2011.02.007
Abstract: Freezing of gait is a paroxysmal phenomenon most commonly found in patients with advanced Parkinson's Disease. The pathophysiological mechanisms underlying this behaviour remain uncertain despite a well-characterised phenotype. Freezing behaviour extends beyond gait to affecting speech and upper limb function, suggesting that there is likely to be a universal mechanism underlying the phenomenon. This paper identifies the essential features required for a comprehensive model of freezing and evaluates a number of hypotheses that seek to explain the phenomenon. It appears likely that the pathophysiology of freezing involves context-dependant dysfunction across multiple levels of the neurological system, including cortical, subcortical and brainstem regions.
Publisher: Center for Open Science
Date: 12-02-2021
Abstract: Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open and inclusive environment. Departing from the formats of typical scientific workshops, these events are based on grassroots projects and training, and foster open and reproducible scientific practices. We describe here the multifaceted, lasting benefits of Brainhacks for in idual participants, particularly early career researchers. We further highlight the unique contributions that Brainhacks can make to the research community, contributing to scientific progress by complementing opportunities available in conventional formats.
Publisher: Elsevier BV
Date: 05-2018
DOI: 10.1016/J.TINS.2018.03.004
Abstract: In 2001 Raichle and colleagues showed that, at rest, brain activity fluctuates near a metabolically active equilibrium: a 'default mode' of brain function. This finding broke ranks with the prevailing 'task-rest' dichotomy to position the brain as continuously active, balancing the deployment of resources according to current and anticipated needs.
Publisher: Elsevier BV
Date: 11-2013
DOI: 10.1016/J.PARKRELDIS.2013.06.002
Abstract: The freezing phenomenon is among the most disabling symptoms of Parkinson's disease (PD) manifesting most commonly as Freezing of Gait with a paroxysmal cessation of effective stepping. Recent studies have suggested that freezing is related to both impairments in conflict resolution as well as the processing of environmentally salient information. In this study, we utilized a virtual reality gait paradigm to investigate differences in motor outflow between PD patients with (n = 36) and without (n = 37) Freezing of Gait, as well as age-matched healthy controls (n = 18). Subjects were required to navigate a realistic on-screen environment with the use of foot pedals to simulate stepping whilst responding to either cues associated with conflict resolution (congruent 'Red', 'Green' or 'Blue') or environmental salience (wide, narrow and sliding doorways). Footstep latency was used as a measure of motor output. Significantly increased stepping latencies were observed in freezers compared to non-freezers (p = 0.004) and controls (p = 0.016) in response to stimuli requiring the inhibition of implicitly cued behavior ('red' cue). Patients with Freezing of Gait also demonstrated increased motor latency compared to non-freezers and controls specifically in response to environmentally salient triggers including narrow doorways (p = 0.03 and 0.01 respectively) and the opening of a sliding door (p = 0.036 and 0.048 respectively). Performance on the paradigm in relation to these triggers correlated significantly with self-reported freezing severity. These results suggest that deficits in conflict resolution and visuospatial processing may reflect some of the neural mechanisms associated with freezing behavior and that these can be probed in a virtual reality environment.
Publisher: Elsevier BV
Date: 06-2011
DOI: 10.1016/J.JOCN.2011.02.003
Abstract: Despite being common, the pathophysiological mechanisms underlying the phenomenon of freezing in patients with Parkinson's disease (PD) remain poorly understood. Recent work has shown that freezing behaviour can be provoked through the use of a computer-based virtual reality task, allowing for the exploration of freezing with functional MRI (fMRI). This article describes a single patient with PD who performed a virtual-reality walking task, both "On" and "Off" dopaminergic medication, while fMRI data were obtained. The results showed distinct BOLD patterns during "walking", "dual-task walking" and during episodes of freezing. The results of this single study highlight the potential utility of this approach in elucidating the underlying neural correlate of freezing behaviour in PD.
Publisher: Elsevier BV
Date: 11-2021
DOI: 10.1016/J.NEUROIMAGE.2021.118510
Abstract: Dimensionality reduction techniques offer a unique perspective on brain state dynamics, in which systems-level activity can be tracked through the engagement of a small number of component trajectories. Used in combination with neuroimaging data collected during the performance of cognitive tasks, these approaches can expose the otherwise latent dimensions upon which the brain reconfigures in order to facilitate cognitive performance. Here, we utilized Principal Component Analysis to transform parcellated BOLD timeseries from an fMRI dataset in which 70 human subjects performed an instruction based visuomotor learning task into orthogonal low-dimensional components. We then used Linear Discriminant Analysis to maximise the mean differences between the low-dimensional signatures of fast-and-slow reaction times and early-and-late learners, while also conserving variance present within these groups. The resultant basis set allowed us to describe meaningful differences between these groups and, importantly, to detail the patterns of brain activity which underpin these differences. Our results demonstrate non-linear interactions between three key brain activation maps with convergent trajectories observed at higher task repetitions consistent with optimization. Furthermore, we show subjects with the greatest reaction time improvements have delayed recruitment of left dorsal and lateral prefrontal cortex, as well as deactivation in parts of the occipital lobe and motor cortex, and that the slowest performers have weaker recruitment of somatosensory association cortex and left ventral visual stream, as well as weaker deactivation in the dorsal lateral prefrontal cortex. Overall our results highlight the utility of a kinematic description of brain states, whereby reformatting data into low-dimensional trajectories sensitive to the subtleties of a task can capture non-linear trends in a tractable manner and permit hypothesis generation at the level of brain states.
Publisher: Wiley
Date: 23-09-2011
DOI: 10.1002/MDS.23896
Abstract: Visual misperceptions and hallucinations are a major cause of distress in patients with Parkinson's disease (PD), particularly in the advanced stages of the condition. Recent work has provided a framework for understanding the pathogenesis of these symptoms, implicating impairments from the retina to the integration of external information with preformed internal images. In this article, we propose a novel hypothesis that attempts to explain the presence of visual misperceptions and hallucinations in PD through the aberrant coordination of complimentary yet competing neural networks. We propose that hallucinations in PD reflect the relative inability to recruit activation in the dorsal attention network in the presence of an ambiguous percept, leading to overreliance on default mode network processing and salience arising from the ventral attention network. This inability is proposed to stem from improper function across cortical and subcortical structures secondary to the presence of Lewy body pathology. This hypothesis may be empirically tested by the use of targeted cognitive paradigms. In turn, this may assist our understanding of the pathophysiological mechanisms and cognitive processes contributing to visual misperceptions and hallucinations and ultimately may inform more effective treatment strategies for this troubling symptom.
Publisher: Elsevier BV
Date: 05-2017
DOI: 10.1016/J.NEUROIMAGE.2017.02.073
Abstract: Impairments in motor automaticity cause patients with Parkinson's disease to rely on attentional resources during gait, resulting in greater motor variability and a higher risk of falls. Although dopaminergic circuitry is known to play an important role in motor automaticity, little evidence exists on the neural mechanisms underlying the breakdown of locomotor automaticity in Parkinson's disease. This impedes clinical management and is in great part due to mobility restrictions that accompany the neuroimaging of gait. This study therefore utilized a virtual reality gait paradigm in conjunction with functional MRI to investigate the role of dopaminergic medication on lower limb motor automaticity in 23 patients with Parkinson's disease that were measured both on and off dopaminergic medication. Participants either operated foot pedals to navigate a corridor ('walk' condition) or watched the screen while a researcher operated the paradigm from outside the scanner ('watch' condition), a setting that controlled for the non-motor aspects of the task. Step time variability during walk was used as a surrogate measure for motor automaticity (where higher variability equates to reduced automaticity), and patients demonstrated a predicted increase in step time variability during the dopaminergic "off" state. During the "off" state, subjects showed an increased blood oxygen level-dependent response in the bilateral orbitofrontal cortices (walk>watch). To estimate step time variability, a parametric modulator was designed that allowed for the examination of brain regions associated with periods of decreased automaticity. This analysis showed that patients on dopaminergic medication recruited the cerebellum during periods of increasing variability, whereas patients off medication instead relied upon cortical regions implicated in cognitive control. Finally, a task-based functional connectivity analysis was conducted to examine the manner in which dopamine modulates large-scale network interactions during gait. A main effect of medication was found for functional connectivity within an attentional motor network and a significant condition by medication interaction for functional connectivity was found within the striatum. Furthermore, functional connectivity within the striatum correlated strongly with increasing step time variability during walk in the off state (r=0.616, p=0.002), but not in the on state (r=-0.233, p=0.284). Post-hoc analyses revealed that functional connectivity in the dopamine depleted state within an orbitofrontal-striatal limbic circuit was correlated with worse step time variability (r=0.653, p<0.001). Overall, this study demonstrates that dopamine ameliorates gait automaticity in Parkinson's disease by altering striatal, limbic and cerebellar processing, thereby informing future therapeutic avenues for gait and falls prevention.
Publisher: Springer Science and Business Media LLC
Date: 10-01-2022
DOI: 10.1038/S41467-021-26978-2
Abstract: The emergence of distributed patterns of neural activity supporting brain functions and behavior can be understood by study of the brain’s low-dimensional topology. Functional neuroimaging demonstrates that brain activity linked to adaptive behavior is constrained to low-dimensional manifolds. In human participants, we tested whether these low-dimensional constraints preserve working memory performance following local neuronal perturbations. We combined multi-session functional magnetic resonance imaging, non-invasive transcranial magnetic stimulation (TMS), and methods translated from the fields of complex systems and computational biology to assess the functional link between changes in local neural activity and the reshaping of task-related low dimensional trajectories of brain activity. We show that specific reconfigurations of low-dimensional trajectories of brain activity sustain effective working memory performance following TMS manipulation of local activity on, but not off, the space traversed by these trajectories. We highlight an association between the multi-scale changes in brain activity underpinning cognitive function.
Publisher: Elsevier BV
Date: 10-2018
DOI: 10.1016/J.NEUROIMAGE.2017.08.010
Abstract: Recent methodological advances have enabled researchers to track the network structure of the human brain over time. Together, these studies provide novel insights into effective brain function, highlighting the importance of the systems-level perspective in understanding the manner in which the human brain organizes its activity to facilitate behavior. Here, we review a range of recent fMRI and electrophysiological studies that have mapped the relationship between inter-regional communication and network structure across a erse range of brain states. In doing so, we identify both behavioral and biological axes that may underlie the tendency for network reconfiguration. We conclude our review by providing suggestions for future research endeavors that may help to refine our understanding of the functioning of the human brain.
Publisher: Elsevier BV
Date: 07-2023
Publisher: Research Square Platform LLC
Date: 22-12-2022
DOI: 10.21203/RS.3.RS-2356429/V1
Abstract: Perception is thought to rely upon evolving activity within a recurrent, distributed thalamocortical network whose interconnections are modulated by bursts of noradrenaline. To test this hypothesis, we leveraged a combination of pupillometry, fMRI and recurrent neural network modelling of an ambiguous figures task. Shifts in the perceptual interpretation of an ambiguous image were associated with peaks in pupil diameter, implicating noradrenergic gain alteration in the perceptual switch. We trained a recurrent neural network to perform an analogous perceptual categorisation task, and then manipulated the gain of the RNN to mimic the effect of noradrenaline. We observed an earlier perceptual shift as a function of heightened gain. Leveraging a low-dimensional readout of the RNN dynamics, and a measure of the energy landscape traversed by the dynamics, we developed two novel predictions: perceptual switches should co-occur with peaks in low-dimensional brain state velocity and with flattened energy landscape dynamics. We used whole-brain fMRI data to confirm these predictions. These results confirm the core role of the noradrenergic system in the large-scale network reconfigurations that mediate perception.
Publisher: Research Square Platform LLC
Date: 02-05-2023
DOI: 10.21203/RS.3.RS-2356429/V2
Abstract: Perception is thought to rely upon evolving activity within a recurrent, distributed thalamocortical network whose interconnections are modulated by bursts of ascending neuromodulatory neurotransmitters, such as noradrenaline. To test this hypothesis, we leveraged a combination of pupillometry, fMRI and recurrent neural network modelling of an ambiguous figures task. Qualitative shifts in the perceptual interpretation of an ambiguous image were associated with peaks in pupil diameter, an indirect readout of phasic noradrenergic bursts. Based on previous modelling work, we hypothesized that increases in neuromodulatory tone led to neural gain alteration so as to causally mediate perceptual switches. To test this hypothesis, we trained a recurrent neural network to perform an analogous perceptual categorisation task, and then manipulated the gain of the RNN to mimic the effect of neuromodulators, such as noradrenaline. As predicted, we observed an earlier perceptual shift as a function of heightened gain. Leveraging a low-dimensional readout of the RNN dynamics, and a measure of the energy landscape traversed by the dynamics, we developed two novel predictions: perceptual switches should co-occur with peaks in low-dimensional brain state velocity and with flattened energy landscape dynamics. We used whole-brain fMRI data to confirm these predictions. These results confirm the core role of the neuromodulatory system in the large-scale network reconfigurations that mediate perceptual switches.
Publisher: Research Square Platform LLC
Date: 27-09-2023
Publisher: Springer Science and Business Media LLC
Date: 18-05-2018
DOI: 10.1038/S41531-018-0052-6
Abstract: The pathophysiological mechanism of freezing of gait (FoG) has been linked to executive dysfunction. Cognitive training (CT) is a non-pharmacological intervention which has been shown to improve executive functioning in Parkinson’s disease (PD). This study aimed to explore whether targeted CT can reduce the severity of FoG in PD. Patients with PD who self-reported FoG and were free from dementia were randomly allocated to receive either a CT intervention or an active control. Both groups were clinician-facilitated and conducted twice-weekly for seven weeks. The primary outcome was percentage of time spent frozen during a Timed Up and Go task, assessed both on and off dopaminergic medications. Secondary outcomes included multiple neuropsychological and psychosocial measures. A full analysis was first conducted on all participants randomized, followed by a s le of interest including only those who had objective FoG at baseline, and completed the intervention. Sixty-five patients were randomized into the study. The s le of interest included 20 in the CT group and 18 in the active control group. The primary outcome of percentage time spent frozen during a gait task was significantly improved in the CT group compared to active controls in the on-state. There were no differences in the off-state. Patients who received CT also demonstrated improved processing speed and reduced daytime sleepiness compared to those in the active control. The findings suggest that CT can reduce the severity of FoG in the on-state, however replication in a larger s le is required.
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 10-2022
DOI: 10.1016/J.NEUROIMAGE.2022.119455
Abstract: Complex cognitive abilities are thought to arise from the ability of the brain to adaptively reconfigure its internal network structure as a function of task demands. Recent work has suggested that this inherent flexibility may in part be conferred by the widespread projections of the ascending arousal systems. While the different components of the ascending arousal system are often studied in isolation, there are anatomical connections between neuromodulatory hubs that we hypothesise are crucial for mediating key features of adaptive network dynamics, such as the balance between integration and segregation. To test this hypothesis, we estimated the strength of structural connectivity between key hubs of the noradrenergic and cholinergic arousal systems (the locus coeruleus [LC] and nucleus basalis of Meynert [nbM], respectively). We then asked whether the strength of structural LC and nbM inter-connectivity was related to in idual differences in the emergent, dynamical signatures of functional integration measured from resting state fMRI data, such as network and attractor topography. We observed a significant positive relationship between the strength of white-matter connections between the LC and nbM and the extent of network-level integration following BOLD signal peaks in LC relative to nbM activity. In addition, in iduals with denser white-matter streamlines interconnecting neuromodulatory hubs also demonstrated a heightened ability to shift to novel brain states. These results suggest that in iduals with stronger structural connectivity between the noradrenergic and cholinergic systems have a greater capacity to mediate the flexible network dynamics required to support complex, adaptive behaviour. Furthermore, our results highlight the underlying static features of the neuromodulatory hubs can impose some constraints on the dynamic features of the brain.
Publisher: Springer Science and Business Media LLC
Date: 21-01-2019
DOI: 10.1038/S41593-018-0312-0
Abstract: The human brain integrates erse cognitive processes into a coherent whole, shifting fluidly as a function of changing environmental demands. Despite recent progress, the neurobiological mechanisms responsible for this dynamic system-level integration remain poorly understood. Here we investigated the spatial, dynamic, and molecular signatures of system-wide neural activity across a range of cognitive tasks. We found that neuronal activity converged onto a low-dimensional manifold that facilitates the execution of erse task states. Flow within this attractor space was associated with dissociable cognitive functions, unique patterns of network-level topology, and in idual differences in fluid intelligence. The axes of the low-dimensional neurocognitive architecture aligned with regional differences in the density of neuromodulatory receptors, which in turn relate to distinct signatures of network controllability estimated from the structural connectome. These results advance our understanding of functional brain organization by emphasizing the interface between neural activity, neuromodulatory systems, and cognitive function.
Publisher: Cold Spring Harbor Laboratory
Date: 16-10-2023
Publisher: Wiley
Date: 11-2018
DOI: 10.1002/MDC3.12683
Publisher: eLife Sciences Publications, Ltd
Date: 20-12-2022
DOI: 10.7554/ELIFE.81282
Abstract: Thalamocortical interaction is a ubiquitous functional motif in the mammalian brain. Previously (Hwang et al., 2021), we reported that lesions to network hubs in the human thalamus are associated with multi-domain behavioral impairments in language, memory, and executive functions. Here, we show how task-evoked thalamic activity is organized to support these broad cognitive abilities. We analyzed functional magnetic resonance imaging (MRI) data from human subjects that performed 127 tasks encompassing a broad range of cognitive representations. We first investigated the spatial organization of task-evoked activity and found a basis set of activity patterns evoked to support processing needs of each task. Specifically, the anterior, medial, and posterior-medial thalamus exhibit hub-like activity profiles that are suggestive of broad functional participation. These thalamic task hubs overlapped with network hubs interlinking cortical systems. To further determine the cognitive relevance of thalamic activity and thalamocortical functional connectivity, we built a data-driven thalamocortical model to test whether thalamic activity can be used to predict cortical task activity. The thalamocortical model predicted task-specific cortical activity patterns, and outperformed comparison models built on cortical, hippoc al, and striatal regions. Simulated lesions to low-dimensional, multi-task thalamic hub regions impaired task activity prediction. This simulation result was further supported by profiles of neuropsychological impairments in human patients with focal thalamic lesions. In summary, our results suggest a general organizational principle of how the human thalamocortical system supports cognitive task activity.
Publisher: Wiley
Date: 05-04-2011
DOI: 10.1002/MDS.23640
Abstract: Sleep disturbance may represent a risk factor for the development of dementia in Parkinson's disease. However, prior studies exploring the association between specific sleep-wake disturbances and neuropsychological functions have been limited. In this study, 101 patients with idiopathic Parkinson's disease were assessed neurologically, underwent neuropsychological testing, and completed self-report questionnaires covering nocturnal disturbance, excessive daytime sleepiness, and symptoms of rapid eye movement sleep behavior disorder. Univariate correlations revealed differential patterns of neuropsychological performance in relation to nocturnal sleep disturbance, excessive daytime sleepiness, and rapid eye movement sleep behavior disorder. After controlling for potential confounders, excessive daytime sleepiness remained a significant predictor of slowed processing speed, and rapid eye movement sleep behavior disorder predicted working memory and verbal fluency performance. The relationships between nocturnal sleep disturbance and memory appeared to be mediated by education. These findings highlight the critical role that specific sleep-wake disturbances in Parkinson's disease might have on neuropsychological functioning, which may reflect common neural underpinnings. © 2011 Movement Disorder Society.
Publisher: Elsevier BV
Date: 2022
Publisher: Wiley
Date: 26-06-2023
DOI: 10.1002/MDS.29506
Abstract: Parkinson's disease (PD) rest tremor emerges from pathological activity in the basal ganglia and cerebello‐thalamo‐cortical circuits. A well‐known clinical feature is the waxing and waning of PD tremor litude, but the mechanisms that drive this variability are unclear. Previous work has shown that arousal lifies PD tremor by increasing between‐network connectivity. Furthermore, brain states in PD are biased toward integration rather than segregation, a pattern that is also associated with increased arousal. The aim was to test the hypothesis that fluctuations in integrative brain states and/or arousal drive spontaneous fluctuations in PD rest tremor. We compared the temporal relationship between cerebral integration, the ascending arousal system, and tremor, both during cognitive load and in the resting state. In 40 tremor‐dominant PD patients, we performed functional magnetic resonance imaging using concurrent tremor recordings and proxy measures of the ascending arousal system (pupil diameter, heart rate). We calculated whole‐brain dynamic functional connectivity and used graph theory to determine a scan‐by‐scan measure of cerebral integration, which we related to the onset of tremor episodes. Fluctuations in cerebral integration were time locked to spontaneous changes in tremor litude: cerebral integration increased 13 seconds before tremor onset and predicted the litude of subsequent increases in tremor litude. During but not before tremor episodes, pupil diameter and heart rate increased and correlated with tremor litude. Integrative brain states are an important cerebral environment in which tremor‐related activity emerges, which is then lified by the ascending arousal system. New treatments focused on attenuating enhanced cerebral integration in PD may reduce tremor. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Publisher: Cambridge University Press (CUP)
Date: 2016
DOI: 10.1017/S0140525X15002599
Abstract: Modern conceptions of brain function consider the brain as a “predictive organ,” where learned regularities about the world are utilised to facilitate perception of incoming sensory input. Critically, this process hinges on a role for cognitive penetrability. We review a mechanism to explain this process and expand our previous proposals of cognitive penetrability in visual recognition to social vision and visual hallucinations.
Publisher: Oxford University Press (OUP)
Date: 23-07-2022
Abstract: The neuromodulatory arousal system imbues the nervous system with the flexibility and robustness required to facilitate adaptive behaviour. While there are well understood mechanisms linking dopamine, noradrenaline and acetylcholine to distinct behavioural states, similar conclusions have not been as readily available for serotonin. Fascinatingly, despite clear links between serotonergic function and cognitive capacities as erse as reward processing, exploration, and the psychedelic experience, over 95% of the serotonin in the body is released in the gastrointestinal tract, where it controls digestive muscle contractions (peristalsis). Here, we argue that framing neural serotonin as a rostral extension of the gastrointestinal serotonergic system dissolves much of the mystery associated with the central serotonergic system. Specifically, we outline that central serotonin activity mimics the effects of a digestion/satiety circuit mediated by hypothalamic control over descending serotonergic nuclei in the brainstem. We review commonalities and differences between these two circuits, with a focus on the heterogeneous expression of different classes of serotonin receptors in the brain. Much in the way that serotonin-induced peristalsis facilitates the work of digestion, serotonergic influences over cognition can be reframed as performing the work of cognition. Extending this analogy, we argue that the central serotonergic system allows the brain to arbitrate between different cognitive modes as a function of serotonergic tone: low activity facilitates cognitive automaticity, whereas higher activity helps to identify flexible solutions to problems, particularly if and when the initial responses fail. This perspective sheds light on otherwise disparate capacities mediated by serotonin, and also helps to understand why there are such pervasive links between serotonergic pathology and the symptoms of psychiatric disorders.
Publisher: Elsevier BV
Date: 12-2022
DOI: 10.1016/J.NEUBIOREV.2022.104921
Abstract: The thalamus plays a crucial role in higher-order emergent functions of the brain, including working memory, attention and conscious awareness. How this small subcortical structure supports these crucial capacities remains poorly understood. In this manuscript, I argue that the connections between the thalamus and the superior colliculus, along with their topological location within the broader systems-level circuitry of the brain, play a crucial role in shaping complex, adaptive dynamics. Through these connections, the superior colliculus is proposed to mediate conscious awareness of highly-valued sensory phenomena, and hence, to maximise the adaptive nature of subsequent actions engaged by the networks of the ventral tier of the thalamus. This perspective leads to multiple testable predictions that will shape research questions regarding the interactions between distributed systems supported by unique regions within the thalamus.
Publisher: Elsevier BV
Date: 09-2014
DOI: 10.1016/J.JNS.2014.06.054
Abstract: Freezing of gait (FOG) is a disabling form of gait disturbance that is common in the advanced stages of Parkinson's disease (PD). Despite its prevalence, methods of studying and assessing FOG are limited. We have previously shown that a virtual reality paradigm was able to distinguish between those who report FOG ("freezers") and those who do not report FOG ("non-freezers"). In this paradigm, 'freezers' were found to have prolonged footstep latency in response to known triggers of FOG including doorways, sliding doors and dual-tasking. In this study, we employed the same paradigm to assess performance of 27 freezers and 14 non-freezers in their clinical 'on' and 'off' medication states. In this study, only participants in the freezing group demonstrated statistically significant increases in latencies experienced in the 'off' state compared to the 'on' state in response to wide and narrow doorways and the opening of a sliding door. By contrast, these behavioral differences were not apparent in non-freezers. Furthermore the delay was specific to environmental cues and was not due to generalized slowing in the 'off' state. The findings suggest that this motor delay when processing environmentally salient cues is specific to freezers and is partially mediated by dopamine-dependent neurocircuitry.
Publisher: Elsevier BV
Date: 2017
Publisher: Elsevier BV
Date: 06-2014
DOI: 10.1016/J.NEUBIOREV.2014.04.010
Abstract: Besides the continuous motor impairments that characterize Parkinson's disease (PD), patients are frequently troubled by sudden paroxysmal arrests or brief episodes of movement breakdown, referred to as 'freezing'. Freezing of gait (FOG) is common in advanced PD and typically occurs in walking conditions that challenge dynamic motor-cognitive control. Mounting evidence suggests that episodic motor phenomena during repetitive upper limb (e.g. writing), lower limb (e.g. foot tapping) and speech sequences resemble FOG and may share some underlying neural mechanisms. However, the precise association between gait and non-gait freezing phenomena remains controversial. This review aimed to clarify this association based on literature on non-gait freezing published between 2000 and 2013. We focused on clinical and epidemiological features of the episodes and their relevance to current influential models of FOG, including recent neuroimaging studies that used a non-gait freezing paradigm as a proxy for FOG. Although not capturing the full complexity of FOG, the neurobehavioral insights obtained with non-gait freezing paradigms will contribute to an increased understanding of disturbed brain-behavior output in PD.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2015
Publisher: Wiley
Date: 22-08-2014
DOI: 10.1002/MDS.26004
Abstract: One of the most challenging tasks in neuroscience is to be able to meaningfully connect information across the different levels of investigation, from molecular or structural biology to the resulting behavior and cognition. Visual hallucinations are a frequent occurrence in Parkinson's disease and significantly contribute to the burden of the disease. Because of the widespread pathological processes implicated in visual hallucinations in Parkinson's disease, a final common mechanism that explains their manifestation will require an integrative approach, in which consideration is taken across all complementary levels of analysis. This review considers the leading hypothetical frameworks for visual hallucinations in Parkinson's disease, summarizing the key aspects of each in an attempt to highlight the aspects of the condition that such a unifying hypothesis must explain. These competing hypotheses include implications of dream imagery intrusion, deficits in reality monitoring, and impairments in visual perception and attention.
Publisher: Oxford University Press (OUP)
Date: 15-10-2019
DOI: 10.1093/BRAIN/AWZ311
Abstract: Fluctuating cognition is a complex and disabling symptom that is seen most frequently in the context of Lewy body dementias encompassing dementia with Lewy bodies and Parkinson’s disease dementia. In fact, since their description over three decades ago, cognitive fluctuations have remained a core diagnostic feature of dementia with Lewy bodies, the second most common dementia in the elderly. In the absence of reliable biomarkers for Lewy body pathology, the inclusion of such patients in therapeutic trials depends on the accurate identification of such core clinical features. Yet despite their diagnostic relevance, cognitive fluctuations remain poorly understood, in part due to the lack of a cohesive clinical and scientific explanation of the phenomenon itself. Motivated by this challenge, the present review examines the history, clinical phenomenology and assessment of cognitive fluctuations in the Lewy body dementias. Based on these data, the key neuropsychological, neurophysiological and neuroimaging correlates of cognitive fluctuations are described and integrated into a novel testable heuristic framework from which new insights may be gained.
Publisher: Elsevier BV
Date: 06-2021
Publisher: Cold Spring Harbor Laboratory
Date: 06-12-2020
DOI: 10.1101/2020.12.04.412551
Abstract: Previous research has shown that the autonomic nervous system provides essential constraints over ongoing cognitive function. However, there is currently a relative lack of direct empirical evidence for how this interaction manifests in the brain at the macro-scale level. Here, we examine the role of ascending arousal and attentional load on large-scale network dynamics by combining pupillometry, functional MRI and graph theoretical analysis to analyze data from a visual motion-tracking task with a parametric load manipulation. We found that attentional load effects were observable in measures of pupil diameter and in a set of brain regions that parametrically modulated their BOLD activity and meso-scale network-level integration. In addition, the regional patterns of network reconfiguration were correlated with the spatial distribution of the α 2a adrenergic receptor. Our results further solidify the relationship between ascending noradrenergic activity, large-scale network integration, and cognitive task performance. In our daily lives, it is usual to encounter highly demanding cognitive tasks. They have been traditionally regarded as challenges that are solved mainly through cerebral activity, specifically via information-processing steps carried by neurons in the cerebral cortex. Activity in cortical networks thus constitutes a key factor for improving our understanding cognitive processes. However, recent evidence has shown that evolutionary older players in the central nervous system, such as brainstem’s ascending modulatory systems, might play an equally important role in erse cognitive mechanisms. Our article examines the role of the ascending arousal system on large-scale network dynamics by combining pupillometry, functional MRI and graph theoretical analysis .
Publisher: Cold Spring Harbor Laboratory
Date: 29-08-2022
DOI: 10.1101/2022.08.29.505672
Abstract: Noradrenaline (NA) release from the brainstem nucleus locus coeruleus (LC) changes activity and connectivity in neuronal networks across the brain, thus modulating multiple behavioural states. NA release is mediated by both tonic and burst-like neuronal LC activity. However, it remains unknown whether the functional changes in downstream projection areas depend on these firing patterns. Using optogenetics, pupillometry, photometry, and functional MRI in mice, we show that tonic and burst LC firing patterns elicit brain responses that are specific to the activation frequency and temporal pattern. Tonic activation of the LC evokes nonlinear responses in prefrontal, limbic, and cerebellar regions, in line with the proposed inverted-U relationship between LC activity and behaviour. We further demonstrate that LC activity enhances network integration and acts as a facilitator of brain state transitions, hence increasing brain flexibility. Together, these findings reveal how the LC-NA system achieves a nuanced regulation of global circuit operations.
Publisher: IOP Publishing
Date: 23-08-2021
Abstract: The human brain seemingly effortlessly performs multiple concurrent and elaborate tasks in response to complex, dynamic sensory input from our environment. This capability has been attributed to the highly modular structure of the brain, enabling specific task assignment among different regions and limiting interference between them. Here, we compare the structure and functional capabilities of different bio-physically inspired and biological networks. We then focus on the influence of topological properties on the functional performance of highly modular, bio-physically inspired neuro-memristive nanowire networks (NWNs). We perform two benchmark reservoir computing tasks (memory capacity and nonlinear transformation) on simulated networks and show that while random networks outperform NWNs on independent tasks, NWNs with highly segregated modules achieve the best performance on simultaneous tasks. Conversely, networks that share too many resources, such as networks with random structure, perform poorly in multitasking. Overall, our results show that structural properties such as modularity play a critical role in trafficking information flow, preventing information from spreading indiscriminately throughout NWNs.
Publisher: Proceedings of the National Academy of Sciences
Date: 15-08-2016
Abstract: The brain is an inherently dynamic organ however, the manner in which the brain changes over longitudinal time remains poorly understood. An understanding of these dynamic mechanisms is critical for understanding normal childhood development and aging as well as neurological and psychiatric disease states. Here, we leverage data collected in a single in idual over the course of 2 y to investigate changes in brain organization over time. In doing so, we show intermittent fluctuations in brain network configuration that were associated with separable patterns of time-resolved interactions between neural regions. The states also directly relate to alterations in whole-brain information processing and self-reported attention. In addition, the patterns that we observed were replicated in a separate longitudinal dataset.
Publisher: Cold Spring Harbor Laboratory
Date: 24-02-2023
DOI: 10.1101/2023.02.22.529544
Abstract: Consciousness is thought to be regulated by bidirectional information transfer between the cortex and thalamus, but the nature of this bidirectional communication - and its possible disruption in unconsciousness - remains poorly understood. Here, we present two main findings elucidating mechanisms of corticothalamic information transfer during conscious states. First, we identify a highly preserved spectral channel of cortical-thalamic communication which is present during conscious states but which is diminished during the loss of consciousness and enhanced during psychedelic states. Specifically, we show that in humans, mice, and rats, information sent from either the cortex or thalamus via δ / θ / α waves (~1.5-13 Hz) is consistently encoded by the other brain region by high γ waves (~50-100 Hz) moroever, unconsciousness induced by propofol anesthesia or generalized spike-and-wave seizures diminishes this cross-frequency communication, whereas the psychedelic 5-methoxy- N,N /-dimethyltryptamine (5-MeO-DMT) enhances this interregional communication. Second, we leverage numerical simulations and neural electrophysiology recordings from the thalamus and cortex of human patients, rats, and mice to show that these changes in cross-frequency cortical-thalamic information transfer are mediated by excursions of low-frequency thalamocortical electrodynamics toward/away from edge-of-chaos criticality, or the phase transition from stability to chaos. Overall, our findings link thalamic-cortical communication to consciousness, and further offer a novel, mathematically well-defined framework to explain the disruption to thalamic-cortical information transfer during unconscious states.
Publisher: Elsevier BV
Date: 06-2016
Publisher: Public Library of Science (PLoS)
Date: 15-10-2019
Publisher: Cold Spring Harbor Laboratory
Date: 07-2022
DOI: 10.1101/2022.06.28.497905
Abstract: Thalamocortical interaction is a ubiquitous functional motif in the mammalian brain. Previously (Hwang et al., 2021), we reported that lesions to network hubs in the human thalamus are associated with multi-domain behavioral impairments in language, memory, and executive functions. Here we show how task-evoked thalamic activity and thalamocortical interactions are organized to support these broad cognitive abilities. To address this question, we analyzed functional MRI data from human subjects that performed 127 tasks encompassing a broad range of cognitive representations. We first investigated the spatial organization of task-evoked activity and found that multi-task thalamic activity converged onto a low-dimensional structure, through which a basis set of activity patterns are evoked to support processing needs of each task. Specifically, the anterior, medial, and posterior-medial thalamus exhibit hub-like activity profiles that are suggestive of broad functional participation. These thalamic task hubs overlapped with network hubs interlinking cortical systems. To further determine the cognitive relevance of thalamocortical interactions, we built a data-driven thalamocortical interaction model to test whether thalamocortical functional connectivity transformed thalamic activity to cortical task activity. The thalamocortical model predicted task-specific cortical activity patterns, and outperformed comparison models built on cortical, hippoc al, and striatal regions. Simulated lesions to low-dimensional, multi-task thalamic hub regions impaired task activity prediction. This simulation result was further supported by profiles of neuropsychological impairments in human patients with focal thalamic lesions. In summary, our results suggest a general organizational principle of how thalamocortical interactions support cognitive task activity. Human thalamic activity transformed via thalamocortical functional connectivity to support task representations across functional domains.
Publisher: Elsevier BV
Date: 03-2018
Publisher: Springer International Publishing
Date: 2017
Publisher: MIT Press - Journals
Date: 2021
DOI: 10.1162/NETN_A_00205
Abstract: Previous research has shown that the autonomic nervous system provides essential constraints over ongoing cognitive function. However, there is currently a relative lack of direct empirical evidence for how this interaction manifests in the brain at the macroscale level. Here, we examine the role of ascending arousal and attentional load on large-scale network dynamics by combining pupillometry, functional MRI, and graph theoretical analysis to analyze data from a visual motion-tracking task with a parametric load manipulation. We found that attentional load effects were observable in measures of pupil diameter and in a set of brain regions that parametrically modulated their BOLD activity and mesoscale network-level integration. In addition, the regional patterns of network reconfiguration were correlated with the spatial distribution of the α2a adrenergic receptor. Our results further solidify the relationship between ascending noradrenergic activity, large-scale network integration, and cognitive task performance.
Publisher: Cold Spring Harbor Laboratory
Date: 20-03-2018
DOI: 10.1101/285171
Abstract: Thousands of papers using resting-state functional magnetic resonance imaging (RS-fMRI) have been published on brain disorders. Results in each paper may have survived correction for multiple comparison. However, since there have been no robust results from large scale meta-analysis, we do not know how many of published results are truly positives. The present meta-analytic work included 60 original studies, with 57 studies (4 datasets, 2266 participants) that used a between-group design and 3 studies (1 dataset, 107 participants) that employed a within-group design. To evaluate the effect size of brain disorders, a very large neuroimaging dataset ranging from neurological to psychiatric isorders together with healthy in iduals have been analyzed. Parkinson’s disease off levodopa (PD-off) included 687 participants from 15 studies. PD on levodopa (PD-on) included 261 participants from 9 studies. Autism spectrum disorder (ASD) included 958 participants from 27 studies. The meta-analyses of a metric named litude of low frequency fluctuation (ALFF) showed that the effect size (Hedges’ g ) was 0.19 - 0.39 for the 4 datasets using between-group design and 0.46 for the dataset using within-group design. The effect size of PD-off, PD-on and ASD were 0.23, 0.39, and 0.19, respectively. Using the meta-analysis results as the robust results, the between-group design results of each study showed high false negative rates (median 99%), high false discovery rates (median 86%), and low accuracy (median 1%), regardless of whether stringent or liberal multiple comparison correction was used. The findings were similar for 4 RS-fMRI metrics including ALFF, regional homogeneity, and degree centrality, as well as for another widely used RS-fMRI metric namely seed-based functional connectivity. These observations suggest that multiple comparison correction does not control for false discoveries across multiple studies when the effect sizes are relatively small. Meta-analysis on un-thresholded t -maps is critical for the recovery of ground truth. We recommend that to achieve high reproducibility through meta-analysis, the neuroimaging research field should share raw data or, at minimum, provide un-thresholded statistical images.
Publisher: Springer Science and Business Media LLC
Date: 22-07-2014
DOI: 10.1007/S00702-014-1271-6
Abstract: Freezing of gait is a frequent and disabling symptom experienced by many patients with Parkinson's disease. A number of executive deficits have been shown to be associated with the phenomenon suggesting a common underlying pathophysiology, which as of yet remains unclear. Neuroimaging studies have also implicated the role of the cognitive control network in patients with freezing. To explore this concept, the current study examined error-monitoring as a measure of cognitive control. Thirty-four patients with and 38 without freezing of gait, who were otherwise well matched on disease severity, completed a colour-word interference task that allowed the specific assessment of error monitoring during conflict. Whilst both groups performed colour-naming and word-reading tasks equally well, those patients with freezing showed a pattern between conditions whereby they were better able to monitor performance and self-correct errors in the pure inhibition task but not after a switching rule was introduced. The novel results shown here provide insight into possible pathophysiological mechanisms involved in cognitive load and error monitoring in patients with freezing of gait. These results provide further evidence for the role of functional frontostriatal circuitry impairments in patients with freezing of gait and have implications for future studies and possible therapeutic interventions.
Publisher: Frontiers Media SA
Date: 29-04-2014
Publisher: Elsevier BV
Date: 03-2018
DOI: 10.1016/J.JAD.2017.12.052
Abstract: The present study investigated Default Mode Network (DMN) functional connectivity in subjects with a lifetime history of major depression, comparing those with and without current sleep disturbance. Controls were included to assess DMN abnormalities specific to depression. A total of 93 adults aged 50 years and over were recruited from the Healthy Brain Ageing Clinic at the Brain and Mind Centre, Sydney, Australia. The s le comprised two groups, including 22 controls and 71 participants with a lifetime history of DSM-IV major depression (with depressive episode current or remitted). 52 of those with a lifetime history of depression also met criteria for Mild Cognitive Impairment (MCI). Participants underwent resting-state fMRI along with comprehensive psychiatric, neuropsychological, and medical assessment. Subjective sleep quality was assessed via the Pittsburgh Sleep Quality Index (PSQI). Sleep disturbance was defined as a PSQI score > 5. A total of 68% (n = 48) of cases with a lifetime history of depression met criteria for sleep-disturbance. DMN functional connectivity was assessed via ROI-to-ROI analyses. Relative to controls, those with lifetime major depression demonstrated significantly increased functional connectivity between the ventromedial prefrontal cortex and the temporal pole. Within the depression group (n = 48), those with current sleep disturbance had significantly increased connectivity between the anterior medial prefrontal cortex and both the parahippoc al cortex and the hippoc al formation, relative to those without sleep disturbance (n = 23). These results were present after controlling for MCI diagnosis. Current sleep disturbance together with depression is associated with distinct abnormalities in DMN functioning incorporating regions responsible for self-reflection and declarative memory processes. Impaired sleep is associated with increased connectivity between these regions. Future studies may augment these findings with complementary imaging techniques including cortical thickness and diffusion tensor imaging, as well as high density electroencephalogram recording.
Publisher: Public Library of Science (PLoS)
Date: 21-06-2013
Publisher: Springer Science and Business Media LLC
Date: 14-10-2021
DOI: 10.1038/S41467-021-26268-X
Abstract: Models of cognitive function typically focus on the cerebral cortex and hence overlook functional links to subcortical structures. This view does not consider the role of the highly-conserved ascending arousal system’s role and the computational capacities it provides the brain. We test the hypothesis that the ascending arousal system modulates cortical neural gain to alter the low-dimensional energy landscape of cortical dynamics. Here we use spontaneous functional magnetic resonance imaging data to study phasic bursts in both locus coeruleus and basal forebrain, demonstrating precise time-locked relationships between brainstem activity, low-dimensional energy landscapes, network topology, and spatiotemporal travelling waves. We extend our analysis to a cohort of experienced meditators and demonstrate locus coeruleus-mediated network dynamics were associated with internal shifts in conscious awareness. Together, these results present a view of brain organization that highlights the ascending arousal system’s role in shaping both the dynamics of the cerebral cortex and conscious awareness.
Publisher: Wiley
Date: 13-06-2013
DOI: 10.1002/HBM.22321
Publisher: IEEE
Date: 08-2015
Publisher: Oxford University Press (OUP)
Date: 02-11-2014
DOI: 10.1093/BRAIN/AWU315
Publisher: American Psychological Association (APA)
Date: 03-2023
DOI: 10.1037/XHP0001073
Publisher: Wiley
Date: 13-01-2019
DOI: 10.1002/HBM.24506
Publisher: IEEE
Date: 07-2013
Publisher: Springer Science and Business Media LLC
Date: 27-08-2015
Abstract: The concept of differing clinical phenotypes within Parkinson’s disease (PD) is well represented in the literature. However, there is no consensus as to whether any particular disease phenotype is associated with an increased risk of mild cognitive impairment (MCI) using the newly proposed Movement Disorders Society diagnostic criteria for this feature. To explore the expression of PD-MCI in relation to the heterogeneity of idiopathic PD. A cluster analysis incorporating a range of specific demographic, clinical and cognitive variables was performed on 209 patients in the early stages of PD (between Hoehn and Yahr stages I–III). Post hoc analyses exploring variables not included in the clustering solution were performed to interrogate the veracity of the subgroups generated. This study identified four distinct PD cohorts: a younger disease-onset subgroup, a tremor dominant subgroup, a non-tremor dominant subgroup, and a subgroup with rapid disease progression. The present study identified a differential expression of PD-MCI across these subgroups, with the highest frequency observed in the non-tremor dominant cluster. The non-tremor dominant subgroup was also associated with a higher prevalence of freezing of gait, hallucinations, daytime somnolence, and rapid eye movement sleep behavior disorder compared with other subgroups. This study confirms the existence of heterogeneity within the early clinical stages of PD and for the first time highlights the differential expression of PD-MCI using the newly defined diagnostic criteria for this feature. An improved understanding of PD-MCI and its clinical relationships may lead to an improved understanding of the pathophysiology underlying heterogeneity in PD.
Publisher: Oxford University Press (OUP)
Date: 30-10-2019
DOI: 10.1093/BRAIN/AWZ325
Abstract: The neurobiology of gait freezing in Parkinson’s disease is poorly understood and therapies are largely ineffective. Using a virtual reality task to elicit freezing intra-operatively during implantation of DBS electrodes, Georgiades et al. identify pathological subthalamic nucleus activity associated with freezing onset and discernible from that of volitional stopping.
Publisher: Elsevier BV
Date: 10-2016
Abstract: Protecting the skin from ultraviolet (UV) radiation is critical during adolescence to reduce the risk of developing skin cancer later in life, but adolescents tend to be less likely to engage in sun-protective behaviours than adults. The present study examined changes and trends (2001/02-2011/12) in sun-protection behaviours among adolescents living in Western Australia - a region with high levels of UV radiation. A cross-sectional survey was conducted during 10 summers between 2001/02 and 2011/12 to investigate how often adolescents engaged in various sun-protection behaviours, including outdoor protective measures (wearing a hat, wearing protective clothing, using sunscreen, wearing sunglasses, seeking shade) and avoidance of UV radiation by staying inside. Hat use significantly decreased between 2001/02 and 2011/12, whereas use of sunscreen and wearing covering clothes were unchanged in most survey years relative to 2001/02. Use of sunglasses peaked in 2006/07 and 2007/08, but returned to first survey year levels in 2011/12, while staying inside was more frequently reported from 2006/07 onwards. New approaches are needed to minimise reactance responses in adolescents while fostering favourable attitudes to sun protection. Implications and opportunities for interventions to promote better sun-protection practices among adolescents are provided.
Publisher: Wiley
Date: 16-03-2015
DOI: 10.1002/MDC3.12139
Abstract: People diagnosed with Parkinson's disease (PD) frequently experience visual and non‐visual hallucinations often with comorbid psychosis, however, there is currently no gold standard tool for accurately assessing these symptoms. To address this problem, we designed a novel questionnaire to evaluate the presence of hallucinatory and psychotic symptoms in PD, as well as related symptoms, such as attentional dysfunction and sleep disturbance. We administered the 20‐item Psychosis and Hallucinations Questionnaire (PsycH‐Q) and three common questionnaire measures in a large cohort of 197 patients with idiopathic PD via a postal survey. We established concurrent validity, convergent validity, and internal consistency of the questionnaire and then assessed test‐retest reliability in a subcohort of 44 patients. PsycH‐Q was found to be a valid instrument when analogous items were compared across three other existing tools (Spearman's rho range: 0.34–0.64 P 0.01). PsycH‐Q demonstrated a strong relationship between self‐reported hallucinations and psychosis and symptoms of the broader hallucinatory phenotype (Kendall's tau = 0.41 P 0.01 positive predictive value = 0.97). PsycH‐Q also displayed a high level of internal consistency (Cronbach's alpha = 0.900 range, 0.696–0.923) and reproducibility (intraclass correlation coefficient = 0.928). PsycH‐Q is a simple, valid, self‐completed instrument that reliably identifies hallucinations and psychosis in PD and has the ability to characterize related patterns of attentional and sleep impairments. As such, PsycH‐Q is a highly valuable tool for use in both clinical and research settings.
Publisher: The Royal Society
Date: 14-12-2020
Abstract: Mind-wandering has become a captivating topic for cognitive neuroscientists. By now, it is reasonably well described in terms of its phenomenology and the large-scale neural networks that support it. However, we know very little about what neurobiological mechanisms trigger a mind-wandering episode and sustain the mind-wandering brain state. Here, we focus on the role of ascending neuromodulatory systems (i.e. acetylcholine, noradrenaline, serotonin and dopamine) in shaping mind-wandering. We advance the hypothesis that the hippoc al sharp wave-ripple (SWR) is a compelling candidate for a brain state that can trigger mind-wandering episodes. This hippoc al rhythm, which occurs spontaneously in quiescent behavioural states, is capable of propagating widespread activity in the default network and is functionally associated with recollective, associative, imagination and simulation processes. The occurrence of the SWR is heavily dependent on hippoc al neuromodulatory tone. We describe how the interplay of neuromodulators may promote the hippoc al SWR and trigger mind-wandering episodes. We then identify the global neuromodulatory signatures that shape the evolution of the mind-wandering brain state. Under our proposed framework, mind-wandering emerges due to the interplay between neuromodulatory systems that influence the transitions between brain states, which either facilitate, or impede, a wandering mind. This article is part of the theme issue ‘Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation'.
Publisher: Cold Spring Harbor Laboratory
Date: 19-01-2021
DOI: 10.1101/2021.01.16.426941
Abstract: Human brain dynamics are organized into a multi-scale network structure that contains multiple tight-knit, meso-scale communities. Recent work has demonstrated that many psychological capacities, as well as impairments in cognitive function secondary to damage, can be mapped onto organizing principles at this mesoscopic scale. However, we still don’t know the rules that govern the dynamic interactions between regions that are constrained by the topology of the broader network. In this preregistered study, we utilized a unique human dataset in which whole brain BOLD-fMRI activity was recorded simultaneously with intracranial electrical stimulation, to characterize the effects of direct neural stimulation on the dynamic reconfiguration of the broader network. Direct neural stimulation increased the extent to which the stimulation site’s own mesoscale community integrated with the rest of the brain. Further, we found that these network changes depended on the topological role of the stimulation site itself: stimulating regions with high participation coefficients led to global integration, whereas stimulating sites with low participation coefficients integrated that regions’ own community with the rest of the brain. These findings provide direct causal evidence for how network topology shapes and constrains inter-regional coordination, and suggest applications for targeted therapeutic interventions in patients with deep-brain stimulation.
Publisher: Cold Spring Harbor Laboratory
Date: 23-04-2019
DOI: 10.1101/617027
Abstract: Interacting sets of nodes and fluctuations in their interaction are important properties of a dynamic network system. In some cases the edges reflecting these interactions are directly quantifiable from the data collected. However, in many cases (such as functional magnetic resonance imaging (fMRI) data), the edges must be inferred from statistical relations between the nodes. Here we present a new method, Temporal Communities through Trajectory Clustering (TCTC), that derives time-varying communities directly from time-series data collected from the nodes in a network. First, we verify TCTC on resting and task fMRI data by showing that time-averaged results correspond with expected static connectivity results. We then show that the time-varying communities correlate and predict single-trial behaviour. This new perspective on temporal community detection of node-collected data identifies robust communities revealing ongoing spatiotemporal community configurations during task performance.
Publisher: Wiley
Date: 11-06-2020
DOI: 10.1002/MDS.28114
Publisher: Springer Science and Business Media LLC
Date: 13-10-2015
DOI: 10.1007/S00415-015-7910-5
Abstract: Freezing of gait is a poorly understood symptom of Parkinson's disease (PD) that is commonly accompanied by executive dysfunction. This study employed an antisaccade task to measure deficits in inhibitory control in patients with freezing, and to determine if these are associated with a specific pattern of grey matter loss using voxel-based morphometry. PD patients with (n = 15) and without (n = 11) freezing along with 10 age-matched controls were included. A simple prosaccade task was administered, followed by a second antisaccade task that required subjects to either look towards or away from a peripheral target. Behavioral results from the antisaccade task were entered as covariates in the voxel-based morphometry analysis. Patient and control groups performed equally well on the first task. However, patients with freezing were significantly worse on the second, which was driven by a specific impairment in suppressing their responses toward the target on the antisaccade trials. Impaired antisaccade performance was associated with grey matter loss across bilateral visual and fronto-parietal regions. These results suggest that patients with freezing have a significant deficit of inhibitory control that is associated with volume reductions in regions crucial for orchestrating both complex motor behaviors and cognitive control. These findings highlight the inter-relationship between freezing of gait and cognition and confirm that dysfunction along common neural pathways is likely to mediate the widespread cognitive dysfunction that emerges with this symptom.
Publisher: Elsevier BV
Date: 10-2016
Publisher: Springer Science and Business Media LLC
Date: 05-08-2020
DOI: 10.1038/S41597-020-00595-Y
Abstract: Mapping the causal effects of one brain region on another is a challenging problem in neuroscience that we approached through invasive direct manipulation of brain function together with concurrent whole-brain measurement of the effects produced. Here we establish a unique resource and present data from 26 human patients who underwent electrical stimulation during functional magnetic resonance imaging (es-fMRI). The patients had medically refractory epilepsy requiring surgically implanted intracranial electrodes in cortical and subcortical locations. One or multiple contacts on these electrodes were stimulated while simultaneously recording BOLD-fMRI activity in a block design. Multiple runs exist for patients with different stimulation sites. We describe the resource, data collection process, preprocessing using the fMRIPrep analysis pipeline and management of artifacts, and provide end-user analyses to visualize distal brain activation produced by site-specific electrical stimulation. The data are organized according to the brain imaging data structure (BIDS) specification, and are available for analysis or future dataset contributions on openneuro.org including both raw and preprocessed data.
Publisher: Cold Spring Harbor Laboratory
Date: 19-03-2019
DOI: 10.1101/581538
Abstract: A key component of the flexibility and complexity of the brain is its ability to dynamically adapt its functional network structure between integrated and segregated brain states depending on the demands of different cognitive tasks. Integrated states are prevalent when performing tasks of high complexity, such as maintaining items in working memory, consistent with models of a global workspace architecture. Recent work has suggested that the balance between integration and segregation is under the control of ascending neuromodulatory systems, such as the noradrenergic system. In a previous large-scale nonlinear oscillator model of neuronal network dynamics, we showed that manipulating neural gain led to a ‘critical’ transition in phase synchrony that was associated with a shift from segregated to integrated topology, thus confirming our original prediction. In this study, we advance these results by demonstrating that the gain-mediated phase transition is characterized by a shift in the underlying dynamics of neural information processing. Specifically, the dynamics of the subcritical (segregated) regime are dominated by information storage, whereas the supercritical (integrated) regime is associated with increased information transfer (measured via transfer entropy). Operating near to the critical regime with respect to modulating neural gain would thus appear to provide computational advantages, offering flexibility in the information processing that can be performed with only subtle changes in gain control. Our results thus link studies of whole-brain network topology and the ascending arousal system with information processing dynamics, and suggest that the constraints imposed by the ascending arousal system constrain low-dimensional modes of information processing within the brain. Higher brain function relies on a dynamic balance between functional integration and segregation. Previous work has shown that this balance is mediated in part by alterations in neural gain, which are thought to relate to projections from ascending neuromodulatory nuclei, such as the locus coeruleus. Here, we extend this work by demonstrating that the modulation of neural gain alters the information processing dynamics of the neural components of a biophysical neural model. Specifically, we find that low levels of neural gain are characterized by high Active Information Storage, whereas higher levels of neural gain are associated with an increase in inter-regional Transfer Entropy. Our results suggest that the modulation of neural gain via the ascending arousal system may fundamentally alter the information processing mode of the brain, which in turn has important implications for understanding the biophysical basis of cognition.
Publisher: Springer Science and Business Media LLC
Date: 29-12-2023
Publisher: Springer Science and Business Media LLC
Date: 27-10-2023
Publisher: Cold Spring Harbor Laboratory
Date: 13-05-2022
DOI: 10.1101/2022.05.11.489776
Abstract: Schizophrenia is a polygenetic mental disorder with heterogeneous positive and negative symptom constellations, and is associated with abnormal cortical connectivity. The thalamus has a coordinative role in cortical function and is key to the development of the cerebral cortex. Conversely, altered functional organization of the thalamus might relate to overarching cortical disruptions in schizophrenia, anchored in development. Here, we contrasted resting-state fMRI in 99 antipsychotic-naive first-episode early-onset schizophrenia (EOS) patients and 100 typically developing controls to study whether macroscale thalamic organization is altered in EOS. Employing dimensional reduction techniques on thalamocortical functional connectome, we derived lateral-medial and anterior-posterior thalamic functional axes. We observed increased segregation of macroscale thalamic functional organization in EOS patients, which was related to altered thalamocortical interactions both in unimodal and transmodal networks. Using an ex vivo approximation of core-matrix cell distribution, we found that core cells particularly underlie the macroscale abnormalities in EOS patients. Moreover, the disruptions were associated with schizophrenia-related gene expression maps. Behavioral and disorder decoding analyses indicated that the macroscale hierarchy disturbances might perturb both perceptual and abstract cognitive functions and contribute to negative syndromes in schizophrenia, suggesting a unitary pathophysiological framework of schizophrenia.
Publisher: Elsevier BV
Date: 09-2014
Publisher: Elsevier BV
Date: 11-2016
DOI: 10.1016/J.NEUROSCIENCE.2016.09.019
Abstract: Freezing of gait (FOG) is a common, disabling symptom of Parkinson's disease (PD) that is associated with deficits in motor initiation and inhibition. Understanding of underlying neurobiological mechanisms has been limited by difficulties in eliciting and objectively characterizing such gait phenomena in the clinical setting. However, recent work suggests that virtual reality (VR) techniques might offer the potential to study motor control. This study utilized a VR paradigm to explore deficits in motor initiation and stopping performance, including stop failure in PD patients with (Freezers, 31) and without (Non-Freezers, 23) FOG, and healthy age-matched Controls (15). The VR task required subjects to respond to a series of start and stop cues while navigating a corridor using ankle flexion/extension movements on foot pedals. We found that Freezers experienced slower motor output initiation and more frequent start hesitations (SHs) (initiations greater than twice a subject's usual initiation latency) compared to Non-Freezers and Controls. Freezers also showed more marked inhibitory impairments, taking significantly longer to execute motor inhibition, and experiencing an increased frequency of failed stopping in response to stop cues compared to Non-Freezers and Controls. Stopping impairments were exacerbated by stop cues requiring additional cognitive processing. These results suggest that PD patients with FOG have marked impairments in motor initiation and inhibition that are not prominent in patients without FOG, nor healthy controls. Future work combining such VR paradigms with neuroimaging techniques and intra-operative deep brain recordings may increase our understanding of these phenomena, promoting the development of novel technologies and therapeutic approaches.
Publisher: Cold Spring Harbor Laboratory
Date: 28-02-2020
DOI: 10.1101/2020.02.28.970350
Abstract: Recent neuroimaging experiments have defined low-dimensional gradients of functional connectivity in the cerebral cortex that subserve a spectrum of capacities that span from sensation to cognition. Despite well-known anatomical connections to the cortex, the subcortical areas that support cortical functional organization have been relatively overlooked. One such structure is the thalamus, which maintains extensive anatomical and functional connections with the cerebral cortex across the cortical mantle. The thalamus has a heterogeneous cytoarchitecture, with at least two distinct cell classes that send differential projections to the cortex: granular-projecting ‘Core’ cells and supragranular-projecting ‘Matrix’ cells. Here we use high-resolution 7T resting-state fMRI data and the relative amount of two calcium-binding proteins, parvalbumin and calbindin, to infer the relative distribution of these two cell-types (Core and Matrix, respectively) in the thalamus. First, we demonstrate that thalamocortical connectivity recapitulates large-scale, low-dimensional connectivity gradients within the cerebral cortex. Next, we show that diffusely-projecting Matrix regions preferentially correlate with cortical regions with longer intrinsic fMRI timescales. We then show that the Core–Matrix architecture of the thalamus is important for understanding network topology in a manner that supports dynamic integration of signals distributed across the brain. Finally, we replicate our main results in a distinct 3T resting-state fMRI dataset. Linking molecular and functional neuroimaging data, our findings highlight the importance of the thalamic organization for understanding low-dimensional gradients of cortical connectivity.
Publisher: Elsevier
Date: 2021
Publisher: Society for Neuroscience
Date: 11-09-2017
DOI: 10.1523/JNEUROSCI.1574-17.2017
Abstract: To determine the spatiotemporal relationships among intrinsic networks of the human brain, we recruited seven neurosurgical patients (four males and three females) who were implanted with intracranial depth electrodes. We first identified canonical resting-state networks at the in idual subject level using an iterative matching procedure on each subject's resting-state fMRI data. We then introduced single electrical pulses to fMRI pre-identified nodes of the default network (DN), frontoparietal network (FPN), and salience network (SN) while recording evoked responses in other recording sites within the same networks. We found bidirectional signal flow across the three networks, albeit with distinct patterns of evoked responses within different time windows. We used a data-driven clustering approach to show that stimulation of the FPN and SN evoked a rapid ( ms) response that was predominantly higher within the SN sites, whereas stimulation of the DN led to sustained responses in later time windows (85–200 ms). Stimulations in the medial temporal lobe components of the DN evoked relatively late effects ( ms) in other nodes of the DN, as well as FPN and SN. Our results provide temporal information about the patterns of signal flow between intrinsic networks that provide insights into the spatiotemporal dynamics that are likely to constrain the architecture of the brain networks supporting human cognition and behavior. SIGNIFICANCE STATEMENT Despite great progress in the functional neuroimaging of the human brain, we still do not know the precise set of rules that define the patterns of temporal organization between large-scale networks of the brain. In this study, we stimulated and then recorded electrical evoked potentials within and between three large-scale networks of the brain, the default network (DN), frontoparietal network (FPN), and salience network (SN), in seven subjects undergoing invasive neurosurgery. Using a data-driven clustering approach, we observed distinct temporal and directional patterns between the three networks, with FPN and SN activity predominant in early windows and DN stimulation affecting the network in later windows. These results provide important temporal information about the interactions between brain networks supporting human cognition and behavior.
Publisher: Wiley
Date: 03-09-2010
DOI: 10.1002/MDS.23331
Abstract: Using the Cambridge Behavior Inventory-Revised, this study evaluated the relationship between caregiver ratings of cognitive change and neuropsychological performance. In sixty-one nondemented patients with Parkinson's Disease (PD mean age = 64.5 years, MMSE = 28.7), 62% met criteria for mild cognitive impairment. This group were rated as having more overall change as well as memory and behavior change. Caregiver ratings were related to poorer psychomotor speed, learning/memory, language, and executive functioning. The capacity for caregivers to rate mild cognitive change in PD may be useful to assist in early screening and intervention approaches.
Publisher: Oxford University Press (OUP)
Date: 09-03-2018
DOI: 10.1093/BRAIN/AWY019
Abstract: Freezing of gait is a complex, heterogeneous, and highly variable phenomenon whose pathophysiology and neural signature remains enigmatic. Evidence suggests that freezing is associated with impairments across cognitive, motor and affective domains however, most research to date has focused on investigating one axis of freezing of gait in isolation. This has led to inconsistent findings and a range of different pathophysiological models of freezing of gait, due in large part to the tendency for studies to investigate freezing of gait as a homogeneous entity. To investigate the neural mechanisms of this heterogeneity, we used an established virtual reality paradigm to elicit freezing behaviour in 41 Parkinson's disease patients with freezing of gait and examined in idual differences in the component processes (i.e. cognitive, motor and affective function) that underlie freezing of gait in conjunction with task-based functional MRI. First, we combined three unique components of the freezing phenotype: impaired set-shifting ability, step time variability, and self-reported anxiety and depression in a principal components analysis to estimate the severity of freezing behaviour with a multivariate approach. By combining these measures, we were then able to interrogate the pattern of task-based functional connectivity associated with freezing (compared to normal foot tapping) in a sub-cohort of 20 participants who experienced sufficient amounts of freezing during task functional MRI. Specifically, we used the first principal component from our behavioural analysis to classify patterns of functional connectivity into those that were associated with: (i) increased severity (ii) increased compensation or (iii) those that were independent of freezing severity. Coupling between the cognitive and limbic networks was associated with 'worse freezing severity', whereas anti-coupling between the putamen and the cognitive and limbic networks was related to 'increased compensation'. Additionally, anti-coupling between cognitive cortical regions and the caudate nucleus were 'independent of freezing severity' and thus may represent common neural underpinnings of freezing that are unaffected by heterogenous factors. Finally, we related these connectivity patterns to each of the in idual components (cognitive, motor, affective) in turn, thus exposing latent heterogeneity in the freezing phenotype, while also identifying critical functional network signatures that may represent potential targets for novel therapeutic intervention. In conclusion, our findings provide confirmatory evidence for systems-level impairments in the pathophysiology of freezing of gait and further advance our understanding of the whole-brain deficits that mediate symptom expression in Parkinson's disease.
Publisher: Elsevier BV
Date: 11-2020
Publisher: MIT Press
Date: 2023
DOI: 10.1162/NETN_A_00308
Abstract: A characteristic feature of human cognition is our ability to ‘multi-task’—performing two or more tasks in parallel—particularly when one task is well learned. How the brain supports this capacity remains poorly understood. Most past studies have focussed on identifying the areas of the brain—typically the dorsolateral prefrontal cortex—that are required to navigate information-processing bottlenecks. In contrast, we take a systems neuroscience approach to test the hypothesis that the capacity to conduct effective parallel processing relies on a distributed architecture that interconnects the cerebral cortex with the cerebellum. The latter structure contains over half of the neurons in the adult human brain and is well suited to support the fast, effective, dynamic sequences required to perform tasks relatively automatically. By delegating stereotyped within-task computations to the cerebellum, the cerebral cortex can be freed up to focus on the more challenging aspects of performing the tasks in parallel. To test this hypothesis, we analysed task-based fMRI data from 50 participants who performed a task in which they either balanced an avatar on a screen (balance), performed serial-7 subtractions (calculation) or performed both in parallel (dual task). Using a set of approaches that include dimensionality reduction, structure-function coupling, and time-varying functional connectivity, we provide robust evidence in support of our hypothesis. We conclude that distributed interactions between the cerebral cortex and cerebellum are crucially involved in parallel processing in the human brain.
Publisher: eLife Sciences Publications, Ltd
Date: 29-01-2018
DOI: 10.7554/ELIFE.31130
Abstract: Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascending neuromodulatory nuclei. To test this hypothesis in silico, we studied the effects of neural gain on network dynamics in a model of large-scale neuronal dynamics. We found that increases in neural gain directed the network through an abrupt dynamical transition, leading to an integrated network topology that was maximal in frontoparietal ‘rich club’ regions. This gain-mediated transition was also associated with increased topological complexity, as well as increased variability in time-resolved topological structure, further highlighting the potential computational benefits of the gain-mediated network transition. These results support the hypothesis that neural gain modulation has the computational capacity to mediate the balance between integration and segregation in the brain.
Publisher: Wiley
Date: 15-01-2023
DOI: 10.1002/ALZ.12937
Abstract: The neuromodulatory subcortical system (NSS) nuclei are critical hubs for survival, hedonic tone, and homeostasis. Tau‐associated NSS degeneration occurs early in Alzheimer's disease (AD) pathogenesis, long before the emergence of pathognomonic memory dysfunction and cortical lesions. Accumulating evidence supports the role of NSS dysfunction and degeneration in the behavioral and neuropsychiatric manifestations featured early in AD. Experimental studies even suggest that AD‐associated NSS degeneration drives brain neuroinflammatory status and contributes to disease progression, including the exacerbation of cortical lesions. Given the important pathophysiologic and etiologic roles that involve the NSS in early AD stages, there is an urgent need to expand our understanding of the mechanisms underlying NSS vulnerability and more precisely detail the clinical progression of NSS changes in AD. Here, the NSS Professional Interest Area of the International Society to Advance Alzheimer's Research and Treatment highlights knowledge gaps about NSS within AD and provides recommendations for priorities specific to clinical research, biomarker development, modeling, and intervention. Neuromodulatory nuclei degenerate in early Alzheimer's disease pathological stages. Alzheimer's pathophysiology is exacerbated by neuromodulatory nuclei degeneration. Neuromodulatory nuclei degeneration drives neuropsychiatric symptoms in dementia. Biomarkers of neuromodulatory integrity would be value‐creating for dementia care. Neuromodulatory nuclei present strategic prospects for disease‐modifying therapies.
Publisher: Elsevier BV
Date: 12-2016
DOI: 10.1016/J.NEUBIOREV.2016.08.036
Abstract: Higher brain function requires integration of distributed neuronal activity across large-scale brain networks. Recent scientific advances at the interface of subcortical brain anatomy and network science have highlighted the possible contribution of subcortical structures to large-scale network communication. We begin our review by examining neuroanatomical literature suggesting that erse neural systems converge within the architecture of the basal ganglia and thalamus. These findings dovetail with those of recent network analyses that have demonstrated that the basal ganglia and thalamus belong to an ensemble of highly interconnected network hubs. A synthesis of these findings suggests a new view of the subcortex, in which the basal ganglia and thalamus form part of a core circuit that supports large-scale integration of functionally erse neural signals. Finally, we close with an overview of some of the major opportunities and challenges facing subcortical-inclusive descriptions of large-scale network communication in the human brain.
Publisher: Cold Spring Harbor Laboratory
Date: 30-03-2021
DOI: 10.1101/2021.03.30.437635
Abstract: Models of cognitive function typically focus on the cerebral cortex and hence overlook functional links to subcortical structures. This view neglects the highly-conserved ascending arousal system’s role and the computational capacities it provides the brain. In this study, we test the hypothesis that the ascending arousal system modulates cortical neural gain to alter the low-dimensional energy landscape of cortical dynamics. Our analyses of spontaneous functional magnetic resonance imaging data and phasic bursts in both locus coeruleus and basal forebrain demonstrate precise time-locked relationships between brainstem activity, low-dimensional energy landscapes, network topology, and spatiotemporal travelling waves. We extend our analysis to a cohort of experienced meditators and demonstrate locus coeruleus-mediated network dynamics were associated with internal shifts in conscious awareness. Together, these results present a novel view of brain organization that highlights the ascending arousal system’s role in shaping both the dynamics of the cerebral cortex and conscious awareness.
Publisher: Elsevier BV
Date: 06-2014
DOI: 10.1016/J.PARKRELDIS.2014.02.028
Abstract: Previous studies have associated freezing of gait in Parkinson's disease with the presence of specific phenotypic features such as mood disturbances, REM sleep behavior disorder and selective cognitive impairments. However, it is not clear whether these features are present in the earlier stages of disease or simply represent a more general pattern of progression. To investigate this issue, the current study evaluated motor, cognitive, affective and autonomic features as well as REM sleep behavior disorder in Parkinson's disease patients in the early stages of the condition. Thirty-eight freezers and fifty-three non-freezers with disease duration of less than five years and a Hoehn and Yahr stage of less than three were included in this study. The groups were matched on a number of key disease features including age, disease duration, motor severity and dopamine dose equivalence. Furthermore, patients were assessed on measures of motor, cognitive, affective and autonomic features, as well as REM sleep behavior disorder. Compared to non-freezers, patients with freezing of gait had significantly more non-tremor symptoms and a selective impairment on executive functions, such as set-shifting ability and working memory. Freezers and non-freezers did not differ on measures of tremor, autonomic function, REM sleep behavior disorder, mood or more general cognition. These results suggest the pathophysiological mechanisms underlying freezing of gait in the early clinical stages of Parkinson's disease are likely to be related to specific changes in the frontostriatal pathways rather than being due to brainstem or more diffuse neuropathology.
Publisher: SAGE Publications
Date: 08-01-2017
Abstract: Visual hallucinations (VH) are a common feature of Parkinson disease (PD) however, the cognitive profile preceding the onset of VH has not yet been established. The present study investigated longitudinal neuropsychological performance of patients with PD who developed VH during follow-up compared to a group who did not develop VH. The patient groups were matched for demographic and disease severity variables at their baseline assessments. Patients who developed VH displayed impaired performance at baseline on measures of psychomotor speed, executive functioning, reaction time, and attention compared to patients who did not develop VH. These results demonstrate a profile of cognitive deficits specific to patients with PD at risk of developing VH and implicate attentional dysfunction in the early pathogenesis of VH.
Publisher: Wiley
Date: 14-02-2020
DOI: 10.1002/HBM.24950
Publisher: American Physical Society (APS)
Date: 12-02-2021
Publisher: Elsevier BV
Date: 11-2017
DOI: 10.1016/J.BPSC.2017.04.007
Abstract: Models of hallucinations emphasize imbalance between sensory input and top-down influences over perception, as false perceptual inference can arise when top-down predictions are afforded too much precision (certainty) relative to sensory evidence. Visual hallucinations in Parkinson's disease (PD) are associated with lower-level visual and attentional impairments, accompanied by overactivity in higher-order association brain networks. PD therefore provides an attractive framework to explore contributions of bottom-up versus top-down disturbances in hallucinations. We characterized sensory processing during perceptual decision making in patients with PD with (n = 20) and without (n = 25) visual hallucinations and control subjects (n = 12), by fitting a hierarchical drift diffusion model to an attentional task. The hierarchical drift diffusion model uses Bayesian estimates to decompose task performance into parameters reflecting drift rates of evidence accumulation, decision thresholds, and nondecision time. We observed slower drift rates in patients with hallucinations, which were less sensitive to changes in task demand. In contrast, wider decision boundaries and shorter nondecision times relative to control subjects were found in patients with PD regardless of hallucinator status. Inefficient and less flexible sensory evidence accumulation emerges as a unique feature of PD hallucinators. We integrate these results with evidence accumulation and predictive coding models of hallucinations, suggesting that in PD sensory evidence is less informative and may therefore be down-weighted, resulting in overreliance on top-down influences. Considering impaired drift rates as an approximation of reduced sensory precision, our findings provide a novel computational framework to specify impairments in sensory processing that contribute to development of visual hallucinations.
Publisher: Elsevier BV
Date: 09-2013
DOI: 10.1016/J.PARKRELDIS.2013.04.020
Abstract: Given the heterogeneity of mild cognitive deficits in non-demented Parkinson's disease (PD), sensitive and anatomically specific behavioural measures are crucial when evaluating cognition in this patient group. Inhibitory dysfunction is one such deficit increasingly being recognised in non-demented PD however, few clinical measures exist to detect it and its associated fronto-striatal pathology. In 50 non-demented PD patients and 27 controls we employ a novel measure, the Excluded Letter Fluency (ELF) test, to objectively assess inhibitory dysfunction. ELF results were also contrasted with an established inhibitory measure (Hayling Test) and covaried against grey matter atrophy via voxel-based morphometry analysis in a subset of patients. The findings show that patients made significantly more rule-break errors than controls on the ELF and this measure was more sensitive than the Hayling in detecting inhibitory dysfunction, classifying over 76% of patients in logistic regression analysis. Importantly, ELF rule-break errors correlated with grey matter atrophy in known inhibitory-control regions (orbitofrontal cortex, inferior frontal gyrus and ventral striatum). The ELF is a brief bedside task that efficiently detects inhibitory dysfunction in non-demented PD. The utility of this novel behavioural measure is further substantiated by its anatomical specificity for fronto-striatal inhibitory control regions.
Publisher: Elsevier BV
Date: 04-2020
Publisher: eLife Sciences Publications, Ltd
Date: 25-08-2021
Publisher: Oxford University Press (OUP)
Date: 29-07-2019
Abstract: Past studies have demonstrated that flexible interactions between brain regions support a wide range of goal-directed behaviors. However, the neural mechanisms that underlie adaptive communication between brain regions are not well understood. In this study, we combined theta-burst transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging to investigate the sources of top-down biasing signals that influence task-evoked functional connectivity. Subjects viewed sequences of images of faces and buildings and were required to detect repetitions (2-back vs. 1-back) of the attended stimuli category (faces or buildings). We found that functional connectivity between ventral temporal cortex and the primary visual cortex (VC) increased during processing of task-relevant stimuli, especially during higher memory loads. Furthermore, the strength of functional connectivity was greater for correct trials. Increases in task-evoked functional connectivity strength were correlated with increases in activity in multiple frontal, parietal, and subcortical (caudate and thalamus) regions. Finally, we found that TMS to superior intraparietal sulcus (IPS), but not to primary somatosensory cortex, decreased task-specific modulation in connectivity patterns between the primary VC and the parahippoc al place area. These findings demonstrate that the human IPS is a source of top-down biasing signals that modulate task-evoked functional connectivity among task-relevant cortical regions.
Publisher: Oxford University Press (OUP)
Date: 26-10-2015
DOI: 10.1093/BRAIN/AWV315
Abstract: Adherence to social norms is compromised in a variety of neuropsychiatric conditions. Functional neuroimaging studies have investigated social norm compliance in healthy in iduals, leading to the identification of a network of fronto-subcortical regions that underpins this ability. However, there is a lack of corroborative evidence from human lesion models investigating the structural anatomy of norm compliance across this fronto-subcortical network. To address this, we developed a neuroeconomic task to investigate social norm compliance in a neurodegenerative lesion model: behavioural variant frontotemporal dementia, a condition characterized by gross social dysfunction. The task assessed norm compliance across three behaviours that are well-studied in the neuroeconomics literature: fairness, prosocial and punishing behaviours. We administered our novel version of the Ultimatum Game in 22 patients with behavioural variant frontotemporal dementia and 22 age-matched controls, to assess how decision-making behaviour was modulated in response to (i) fairness of monetary offers and (ii) social context of monetary offers designed to produce either prosocial or punishing behaviours. Voxel-based morphometry was used to characterize patterns of grey matter atrophy associated with task performance. Acceptance rates between patients and controls were equivalent when only fairness was manipulated. However, patients were impaired in modulating their decisions in response to social contextual information. Patients' performance in the punishment condition was consistent with a reduced tendency to engage in punishment this was associated with decreased grey matter volume in the anterior cingulate, orbitofrontal cortex, left dorsolateral prefrontal cortex and right inferior frontal gyrus. In the prosocial condition, patients' performance suggested a reduced expression of prosocial behaviour, associated with decreased grey matter in the anterior insula, lateral orbitofrontal cortex, anterior cingulate and dorsal striatum. Acceptance rates in the Ultimatum Game were also significantly related to impairments in the everyday expression of empathic concern. In conclusion, we demonstrate that compliance to basic social norms (fairness) can be maintained in behavioural variant frontotemporal dementia however, more complex normative behaviours (prosociality, punishment) that require integration of social contextual information are disrupted in association with atrophy in key fronto-striatal regions. These results suggest that the integration of social contextual information to guide normative behaviour is uniquely impaired in behavioural variant frontotemporal dementia, and may explain other common features of the condition including gullibility and impaired empathy. Our findings also converge with previous functional neuroimaging investigations in healthy in iduals and provide the first description of the structural anatomy of social norm compliance in a neurodegenerative lesion model.
Publisher: Cold Spring Harbor Laboratory
Date: 30-10-2021
DOI: 10.1101/2021.10.28.466336
Abstract: Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macroscale neuroanatomy and how they shape emergent function remains poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from 200 healthy in iduals to construct a whole-brain 3-D normative atlas of 19 receptors and transporters across 9 different neurotransmitter systems. We find that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncover a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we find both expected and novel associations between receptor distributions and cortical thinning patterns across 13 disorders. We replicate all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.
Publisher: Center for Open Science
Date: 29-01-2023
Abstract: Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma C aign, here we provide our framework and vision to understand the erse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state of the art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges.
Publisher: Cold Spring Harbor Laboratory
Date: 06-08-2021
DOI: 10.1101/2021.08.05.455149
Abstract: Even in the absence of external stimuli, neural activity is both highly dynamic and organized across multiple spatiotemporal scales. The continuous evolution of brain activity patterns during rest is believed to help maintain a rich repertoire of possible functional configurations that relate to typical and atypical cognitive phenomena. Whether these transitions or “explorations” follow some underlying arrangement or instead lack a predictable ordered plan remains to be determined. Here, using a precision dynamics approach, we aimed at revealing the rules that govern transitions in brain activity at rest at the single participant level. We hypothesized that by revealing and characterizing the overall landscape of whole brain configurations (or states) we could interpret the rules (if any) that govern transitions in brain activity at rest. To generate the landscape of whole-brain configurations we used Topological Data Analysis based Mapper approach. Across all participants, we consistently observed a rich topographic landscape in which the transition of activity from one state to the next involved a central hub-like “transition state.” The hub topography was characterized as a shared attractor-like basin where all canonical resting-state networks were represented equally. The surrounding periphery of the landscape had distinct network configurations. The intermediate transition state and traversal through it via a topographic gradient seemed to provide the underlying structure for the continuous evolution of brain activity patterns at rest. In addition, differences in the landscape architecture were more consistent within than between subjects, providing evidence of idiosyncratic dynamics and potential utility in precision medicine.
Publisher: The Royal Society
Date: 07-01-2015
Abstract: Visual hallucinations occur when our conscious experience does not accurately reflect external reality. However, these dissociations also regularly occur when we imagine the world around us in the absence of visual stimulation. We used two novel behavioural paradigms to objectively measure visual hallucinations and voluntary mental imagery in 19 in iduals with Parkinson's disease (ten with visual hallucinations nine without) and ten healthy, age-matched controls. We then used this behavioural overlap to interrogate the connectivity both within and between the major attentional control networks using resting-state functional magnetic resonance imaging. Patients with visual hallucinations had elevated mental imagery strength compared with patients without hallucinations and controls. Specifically, the sensory strength of imagery predicted the frequency of visual hallucinations. Together, hallucinations and mental imagery predicted multiple abnormalities in functional connectivity both within and between the attentional control networks, as measured with resting-state functional magnetic resonance imaging. However, the two phenomena were also dissociable at the neural level, with both mental imagery and visual misperceptions associated with specific abnormalities in attentional network connectivity. Our results provide the first evidence of both the shared and unique neural correlates of these two similar, yet distinct phenomena.
Publisher: Springer Science and Business Media LLC
Date: 27-10-2022
DOI: 10.1038/S41593-022-01186-3
Abstract: Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macro-scale neuroanatomy and how they shape emergent function remain poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from more than 1,200 healthy in iduals to construct a whole-brain three-dimensional normative atlas of 19 receptors and transporters across nine different neurotransmitter systems. We found that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting-state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncovered a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we found both expected and novel associations between receptor distributions and cortical abnormality patterns across 13 disorders. We replicated all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.
Publisher: Cold Spring Harbor Laboratory
Date: 04-06-2019
DOI: 10.1101/659508
Abstract: In network neuroscience, temporal network models have gained popularity. In these models, network properties have been related to cognition and behaviour. Here we demonstrate that calculating nodal properties that are dependent on temporal community structure (such as the participation coefficient) in time-varying contexts can potentially lead to misleading results. Specifically, with regards to the participation coefficient, increases in integration can be inferred when the opposite is occuring. Further, we present a temporal extension to the participation coefficient measure (temporal participation coefficient) that circumnavigates this problem by jointly considering all community partitions assigned to a node through time. The proposed method allows us to track a node’s integration through time while adjusting for the possible changes in the community structure of the overall network.
Publisher: Oxford University Press (OUP)
Date: 24-04-2017
DOI: 10.1093/BRAIN/AWX063
Publisher: Cold Spring Harbor Laboratory
Date: 05-05-2022
DOI: 10.1101/2022.05.05.490687
Abstract: The regulation of moment-to-moment neural variability may permit effective responses to changing cognitive demands. However, the mechanisms that support variability regulation are unknown. In the context of working memory, we leverage the largest available PET and fMRI dataset to jointly consider three lenses through which neural variability regulation could be understood: dopamine capacity, network-level functional integration, and flexible decision processes. We show that with greater working memory load, upregulation of variability was associated with elevated dopamine capacity and heightened functional integration, effects dominantly expressed in the striato-thalamic system rather than cortex. Strikingly, behavioral modeling revealed that working memory load evoked substantial decision biases during evidence accumulation, and those who jointly expressed a more optimal decision bias and higher dopamine capacity were most likely to upregulate striato-thalamic variability under load. We argue that the ability to align striato-thalamic variability to level of demand may be a hallmark of a well-functioning brain.
Publisher: eLife Sciences Publications, Ltd
Date: 04-09-2020
Publisher: Wiley
Date: 25-05-2023
DOI: 10.1002/MDS.29455
Abstract: Gait freezing is a common, disabling symptom of Parkinson's disease characterized by sudden motor arrest during walking. Adaptive deep brain stimulation devices that detect freezing and deliver real‐time, symptom‐specific stimulation are a potential treatment strategy. Real‐time alterations in subthalamic nucleus firing patterns have been demonstrated with lower limb freezing, however, whether similar abnormal signatures occur with freezing provoked by cognitive load, is unknown. We obtained subthalamic nucleus microelectrode recordings from eight Parkinson's disease patients performing a validated virtual reality gait task, requiring responses to on‐screen cognitive cues while maintaining motor output. Signal analysis during 15 trials containing freezing or significant motor output slowing precipitated by dual‐tasking demonstrated reduced θ frequency (3–8 Hz) firing compared to 18 unaffected trials. These preliminary results reveal a potential neurobiological basis for the interplay between cognitive factors and gait disturbances including freezing in Parkinson's disease, informing development of adaptive deep brain stimulation protocols. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Publisher: Cold Spring Harbor Laboratory
Date: 20-05-2020
DOI: 10.1101/2020.05.18.102657
Abstract: Mapping the causal effects of one brain region on another (effective connectivity) is a challenging problem in neuroscience, since it requires invasive direct manipulation of brain function, together with whole-brain measurement of the effects produced. Here we establish a unique resource and present data from 26 human patients who underwent electrical stimulation during functional magnetic resonance imaging (es-fMRI). The patients had medically refractory epilepsy requiring surgically implanted intracranial electrodes in cortical and subcortical locations. One or multiple contacts on these electrodes were stimulated while simultaneously recording BOLD-fMRI activity in a block design. Multiple runs exist for patients with different stimulation sites. We describe the resource, data collection process, preprocessing using the fMRIPrep analysis pipeline and management of artifacts, and provide end-user analyses to visualize distal brain activation produced by site-specific electrical stimulation. The data are organized according to the brain imaging data structure (BIDS) specification, and are available for analysis or future dataset contributions on openneuro.org including both raw and preprocessed data.
Publisher: Elsevier BV
Date: 12-2019
DOI: 10.1016/J.NEURON.2019.09.002
Abstract: Cognitive activity emerges from large-scale neuronal dynamics that are constrained to a low-dimensional manifold. How this low-dimensional manifold scales with cognitive complexity, and which brain regions regulate this process, are not well understood. We addressed this issue by analyzing sub-second high-field fMRI data acquired during performance of a task that systematically varied the complexity of cognitive reasoning. We show that task performance reconfigures the low-dimensional manifold and that deviations from these patterns relate to performance errors. We further demonstrate that in idual differences in thalamic activity relate to reconfigurations of the low-dimensional architecture during task engagement.
Start Date: 2011
End Date: 2014
Amount: $265,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 03-2020
End Date: 12-2024
Amount: $476,198.00
Funder: Australian Research Council
View Funded Activity