ORCID Profile
0000-0003-0679-4959
Current Organisation
University of Melbourne
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Neurocognitive Patterns and Neural Networks | Sensory Systems | Neurosciences | Decision Making | Biological psychology | Biomedical Instrumentation | Psychology | Sensory systems | Cognitive neuroscience | Central Nervous System | Human Biophysics | Sensory Processes, Perception and Performance | Biological Physics | Biomedical imaging
Expanding Knowledge in the Biological Sciences | Expanding Knowledge in Psychology and Cognitive Sciences | Expanding Knowledge in Engineering | Expanding Knowledge in the Medical and Health Sciences | Expanding Knowledge in Technology |
Publisher: Elsevier BV
Date: 03-2009
Publisher: Cold Spring Harbor Laboratory
Date: 25-10-2022
DOI: 10.1101/2022.10.24.513606
Abstract: Neurocomputational accounts of psychosis propose mechanisms for how information is integrated into a predictive model of the world, in attempts to understand the occurrence of altered perceptual experiences. Conflicting Bayesian theories postulate aberrations in either top-down or bottom-up processing. The top-down theory predicts an overreliance on prior beliefs or expectations resulting in aberrant perceptual experiences, whereas the bottom-up theory predicts an overreliance on current sensory information, as aberrant salience is directed towards objectively uninformative stimuli. This study empirically adjudicates between these models. We use a perceptual decision-making task in a neurotypical population with varying degrees of psychotic-like experiences. Bayesian modelling was used to compute in iduals’ reliance on prior relative to sensory information. Across two datasets (discovery dataset n=363 independent replication in validation dataset n=782) we showed that psychotic-like experiences were associated with an overweighting of sensory information relative to prior expectations, which seem to be driven by decreased precision afforded to prior information. However, when prior information was more uncertain, participants with greater psychotic-like experiences encoded sensory information with greater noise. Greater psychotic-like experiences were also associated with generally heightened perceptions of task instability, which we suggest may be the cause for the observed aberrant precision in the encoding both prior and likelihood information. Our study lends empirical support to notions of both weaker bottom-up and weaker (rather than stronger) top-down perceptual processes, as well as aberrancies in belief updating that extend into the non-clinical continuum of psychosis.
Publisher: Center for Open Science
Date: 21-09-2023
Publisher: Springer Science and Business Media LLC
Date: 23-04-2008
Publisher: Cold Spring Harbor Laboratory
Date: 23-12-2022
DOI: 10.1101/2022.12.23.521691
Abstract: Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can h er the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.
Publisher: Cold Spring Harbor Laboratory
Date: 25-01-2019
DOI: 10.1101/525519
Abstract: Our survival depends on how well we can rapidly detect threats in our environment. To facilitate this, the brain is faster to bring threatening or rewarding visual stimuli into conscious awareness than neutral stimuli. Unexpected events may indicate a potential threat, and yet we tend to respond slower to unexpected than expected stimuli. It is unclear if or how these effects of emotion and expectation interact with one’s conscious experience. To investigate this, we presented neutral and fearful faces with different probabilities of occurance in a breaking continuous flash suppression (bCFS) paradigm. Across two experiments, we discovered that fulfilled prior expectations hastened responses to neutral faces but had either no significant effect (Experiment 1) or the opposite effect (Experiment 2) on fearful faces. Drift diffusion modelling revealed that, while prior expectations accelerated stimulus encoding time (associated with the visual cortex), evidence was accumulated at an especially rapid rate for unexpected fearful faces (associated with activity in the right inferior frontal gyrus). Hence, these findings demonstrate a novel interaction between emotion and expectation during bCFS, driven by a unique influence of surprising fearful stimuli that expedites evidence accumulation in a fronto-occipital network.
Publisher: Oxford University Press (OUP)
Date: 09-01-2015
Publisher: Oxford University PressNew York
Date: 30-04-2010
DOI: 10.1093/ACPROF:OSO/9780195372731.003.0015
Abstract: Developments in M/EEG analysis allows for models that are sophisticated enough to capture the full richness of the data. This chapter focuses on dynamic causal modeling (DCM) for M/EEG, which entails the inversion of informed spatiotemporal models of observed responses. The idea is to model condition-specific responses over channels and peristimulus time with the same model, where the differences among conditions are explained by changes in only a few key parameters. The face and predictive validity of DCM have been established, which makes it a potentially useful tool for group studies.
Publisher: Elsevier BV
Date: 06-2007
DOI: 10.1016/J.NEUROIMAGE.2007.02.046
Abstract: Dynamic causal modelling is an approach to characterising evoked responses as measured by magneto/electroencephalography (M/EEG). A dynamic causal model (DCM) is a spatiotemporal, generative network model for event-related fields/responses (ERP/ERF) data. Using Bayesian model inversion, one can compute the posterior distributions of the DCM's physiological parameters and its marginal likelihood for model comparison. Model comparison can be used to test mechanistic hypotheses about how electrophysiological data were generated. In this work, we look at the relative importance of changes in intrinsic (within source) and extrinsic (between sources) connections in generating mismatch responses. In short, we introduce the modulation of intrinsic connectivity to the DCM framework. This is useful for testing hypotheses about adaptation of neuronal responses to local influences, in relation to influences that are mediated by long-range extrinsic connections (forward, backward, and lateral) from other sources. We illustrate this extension using synthetic data and empirical data from an oddball ERP experiment.
Publisher: Society for Neuroscience
Date: 07-2020
DOI: 10.1523/ENEURO.0139-20.2020
Abstract: Humans show striking limitations in information processing when multitasking yet can modify these limits with practice. Such limitations have been linked to a frontal-parietal network, but recent models of decision-making implicate a striatal-cortical network. We adjudicated these accounts by investigating the circuitry underpinning multitasking in 100 human in iduals and the plasticity caused by practice. We observed that multitasking costs, and their practice-induced remediation, are best explained by modulations in information transfer between the striatum and the cortical areas that represent stimulus-response mappings. Specifically, our results support the view that multitasking stems at least in part from taxation in information sharing between the putamen and pre-supplementary motor area (pre-SMA). Moreover, we propose that modulations to information transfer between these two regions leads to practice-induced improvements in multitasking.
Publisher: Cold Spring Harbor Laboratory
Date: 09-09-2019
DOI: 10.1101/747204
Abstract: Recent studies have shown that prediction and attention can interact under various circumstances, suggesting that the two processes are based on interdependent neural mechanisms. In the visual modality, attention can be deployed to the location of a task-relevant stimulus (‘spatial attention’) or to a specific feature of the stimulus, such as colour or shape, irrespective of its location (‘feature-based attention’). Here we asked whether predictive processes are influenced by feature-based attention outside the current spatial focus of attention. Across two experiments, we recorded neural activity with electroencephalography (EEG) as human observers performed a feature-based attention task at fixation and ignored a stream of peripheral stimuli with predictable or surprising features. Central targets were defined by a single feature (colour or orientation) and differed in salience across the two experiments. Task-irrelevant peripheral patterns usually comprised one particular conjunction of features (standards), but occasionally deviated in one or both features (deviants). Consistent with previous studies, we found reliable effects of feature-based attention and prediction on neural responses to task-irrelevant patterns in both experiments. Crucially, we observed an interaction between prediction and feature-based attention in both experiments: the neural effect of feature-based attention was larger for surprising patterns than it was for predicted patterns. These findings suggest that global effects of feature-based attention depend on surprise, and are consistent with the idea that attention optimises the precision of predictions by modulating the gain of prediction errors. Two principal mechanisms facilitate the efficient processing of sensory information: prediction uses prior information to guide the interpretation of sensory events, whereas attention biases the processing of these events according to their behavioural relevance. A recent theory proposes to reconcile attention and prediction under a unifying framework, casting attention as a ‘precision optimisation’ mechanism that enhances the gain of prediction errors. Crucially, this theory suggests that attention and prediction interact to modulate neural responses, but this hypothesis remains to be tested with respect to feature-based attention mechanisms outside the spatial focus of attention. Here we show that global effects of feature-based attention are enhanced when stimuli possess surprising features, suggesting that feature-based attention and prediction are interdependent neural mechanisms.
Publisher: eLife Sciences Publications, Ltd
Date: 09-12-2018
Publisher: Proceedings of the National Academy of Sciences
Date: 26-12-2007
Abstract: Neuronal responses to stimuli, measured electrophysiologically, unfold over several hundred milliseconds. Typically, they show characteristic waveforms with early and late components. It is thought that early or exogenous components reflect a perturbation of neuronal dynamics by sensory input bottom-up processing. Conversely, later, endogenous components have been ascribed to recurrent dynamics among hierarchically disposed cortical processing levels, top-down effects. Here, we show that evoked brain responses are generated by recurrent dynamics in cortical networks, and late components of event-related responses are mediated by backward connections. This evidence is furnished by dynamic causal modeling of mismatch responses, elicited in an oddball paradigm. We used the evidence for models with and without backward connections to assess their likelihood as a function of peristimulus time and show that backward connections are necessary to explain late components. Furthermore, we were able to quantify the contribution of backward connections to evoked responses and to source activity, again as a function of peristimulus time. These results link a generic feature of brain responses to changes in the sensorium and a key architectural component of functional anatomy namely, backward connections are necessary for recurrent interactions among levels of cortical hierarchies. This is the theoretical cornerstone of most modern theories of perceptual inference and learning.
Publisher: Elsevier BV
Date: 11-2014
Publisher: Society for Neuroscience
Date: 10-06-2015
Publisher: Elsevier BV
Date: 08-2008
Publisher: Center for Open Science
Date: 21-09-2023
Publisher: MIT Press - Journals
Date: 05-2017
DOI: 10.1162/JOCN_A_01085
Abstract: Predictive coding models of attention propose that attention and prediction operate synergistically to optimize perception, as reflected in interactive effects on early sensory neural responses. It is yet unclear whether attention and prediction based on the temporal attributes of expected events operate in a similar fashion. We investigated how attention and prediction based on timing interact by manipulating the task relevance and a priori probability of auditory stimulus onset timing within a go/no-go task while recording EEG. Preparatory activity, as indexed via the contingent negative variation, reflected temporally specific anticipation as a function of both attention and prediction. Higher stimulus probability led to significant predictive N1 suppression however, we failed to find an effect of task relevance on N1 litude and an interaction of task relevance with prediction. We suggest the predictability of sensory timing is the predominant influence on early sensory responses where a priori probabilities allow for strong prior beliefs. When this is the case, we find that the effects of temporal prediction on early sensory responses are independent of the task relevance of sensory stimuli. Our findings contribute to the expansion of predictive coding frameworks to include the role of timing in sensory processing.
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 07-2018
DOI: 10.1016/J.SCHRES.2018.01.026
Abstract: 22q11.2 deletion syndrome (22q11.2DS) is one of the most common copy number variants and confers a markedly increased risk for schizophrenia. As such, 22q11.2DS is a homogeneous genetic liability model which enables studies to delineate functional abnormalities that may precede disease onset. Mismatch negativity (MMN), a brain marker of change detection, is reduced in people with schizophrenia compared to healthy controls. Using dynamic causal modelling (DCM), previous studies showed that top-down effective connectivity linking the frontal and temporal cortex is reduced in schizophrenia relative to healthy controls in MMN tasks. In the search for early risk-markers for schizophrenia we investigated the neural basis of change detection in a group with 22q11.2DS. We recorded high-density EEG from 19 young non-psychotic 22q11.2 deletion carriers, as well as from 27 healthy non-carriers with comparable age distribution and sex ratio, while they listened to a sequence of sounds arranged in a roving oddball paradigm. Despite finding no significant reduction in the MMN responses, whole-scalp spatiotemporal analysis of responses to the tones revealed a greater fronto-temporal N1 component in the 22q11.2 deletion carriers. DCM showed reduced intrinsic connection within right primary auditory cortex as well as in the top-down, connection from the right inferior frontal gyrus to right superior temporal gyrus for 22q11.2 deletion carriers although not surviving correction for multiple comparison. We discuss these findings in terms of reduced adaptation and a general increased sensitivity to tones in 22q11.2DS.
Publisher: Wiley
Date: 09-04-2009
DOI: 10.1002/HBM.20775
Publisher: American Association for the Advancement of Science (AAAS)
Date: 13-05-2011
Abstract: Discerning the neural correlates of (un)consciousness sheds light on the mechanisms underlying vegetative states.
Publisher: Elsevier BV
Date: 2012
Publisher: Elsevier BV
Date: 06-2021
Publisher: Elsevier BV
Date: 05-2013
Publisher: SAGE Publications
Date: 2011
DOI: 10.1068/I0411
Abstract: Surprising events in the environment can impair task performance. This might be due to complete distraction, leading to lapses during which performance is reduced to guessing. Alternatively, unpredictability might cause a graded withdrawal of perceptual resources from the task at hand and thereby reduce sensitivity. Here we attempt to distinguish between these two mechanisms. Listeners performed a novel auditory pitch—duration discrimination, where stimulus loudness changed occasionally and incidentally to the task. Responses were slower and less accurate in the surprising condition, where loudness changed unpredictably, than in the predictable condition, where the loudness was held constant. By explicitly modelling both lapses and changes in sensitivity, we found that unpredictable changes diminished sensitivity but did not increase the rate of lapses. These findings suggest that background environmental uncertainty can disrupt goal-directed behaviour. This graded processing strategy might be adaptive in potentially threatening contexts, and reflect a flexible system for automatic allocation of perceptual resources.
Publisher: Oxford University Press (OUP)
Date: 06-01-2021
Abstract: Recent theories in computational psychiatry propose that unusual perceptual experiences and delusional beliefs may emerge as a consequence of aberrant inference and disruptions in sensory learning. The current study investigates these theories and examines the alterations that are specific to schizophrenia spectrum disorders vs those that occur as psychotic phenomena intensify, regardless of diagnosis. We recruited 66 participants: 22 schizophrenia spectrum inpatients, 22 nonpsychotic inpatients, and 22 nonclinical controls. Participants completed the reversal oddball task with volatility manipulated. We recorded neural responses with electroencephalography and measured behavioral errors to inferences on sound probabilities. Furthermore, we explored neural dynamics using dynamic causal modeling (DCM). Attenuated prediction errors (PEs) were specifically observed in the schizophrenia spectrum, with reductions in mismatch negativity in stable, and P300 in volatile, contexts. Conversely, aberrations in connectivity were observed across all participants as psychotic phenomena increased. DCM revealed that impaired sensory learning behavior was associated with decreased intrinsic connectivity in the left primary auditory cortex and right inferior frontal gyrus (IFG) connectivity in the latter was also reduced with greater severity of psychotic experiences. Moreover, people who experienced more hallucinations and psychotic-like symptoms had decreased bottom-up and increased top-down frontotemporal connectivity, respectively. The findings provide evidence that reduced PEs are specific to the schizophrenia spectrum, but deficits in brain connectivity are aligned on the psychosis continuum. Along the continuum, psychotic experiences were related to an aberrant interplay between top-down, bottom-up, and intrinsic connectivity in the IFG during sensory uncertainty. These findings provide novel insights into psychosis neurocomputational pathophysiology.
Publisher: Oxford University Press (OUP)
Date: 08-2011
Publisher: Elsevier BV
Date: 10-2009
Publisher: Cold Spring Harbor Laboratory
Date: 07-03-2018
DOI: 10.1101/277368
Abstract: Our ability to rapidly detect threats is thought to be subserved by a subcortical pathway that quickly conveys visual information to the amygdala. This neural shortcut has been demonstrated in animals but has rarely been shown in the human brain. Importantly, it remains unclear whether such a pathway might influence neural activity and behaviour. We conducted a multimodal neuroimaging study of 622 participants from the Human Connectome Project. We applied probabilistic tractography to diffusion-weighted images, reconstructing a subcortical pathway to the amygdala from the superior colliculus via the pulvinar. We then computationally modelled the flow of neural activity during a face-viewing task and found evidence for a functionally-afferent pulvinar-amygdala pathway. Critically, in iduals with greater fibre density in this pathway also had stronger dynamic coupling and enhanced fearful face recognition. Our findings provide converging evidence for the recruitment of an afferent subcortical pulvinar connection to the amygdala that facilitates fear recognition.
Publisher: Elsevier BV
Date: 2016
DOI: 10.1016/J.CLINPH.2015.06.026
Abstract: We investigated the neurophysiological mechanisms underpinning the generation of the mismatch negativity (MMN) and its development from adolescence to early adulthood. We used dynamic causal modelling (DCM) to study connectivity models for healthy adults and adolescents. MMN was elicited with an auditory oddball paradigm in two groups of healthy subjects with mean age 14 (n=52) and 26 (n=26). We tested models with different hierarchical complexities including up to five cortical nodes. We showed that the network generating MMN consisted of 5 nodes that could modulate all intra- and internodal connections. The inversion of this model showed that adolescents had reduced backward connection from rIFG to rSTG (p<0.04) together with increased excitatory activity in rSTG (p<0.02). There was a reduced modulation of excitability in rSTG (p<0.02) and of forward connectivity from lA1 to lSTG (p<0.03). The cortical network generating MMN continues to develop in adolescence up to adulthood. Cortical regions in the temporal and frontal lobes, involved in auditory processing, mature with increasing fronto-temporal connectivity together with increased sensitivity in the temporal regions for changes in sound stimuli. This study may offer an explanation for the neurobiological maturation of the MMN in adolescence.
Publisher: Society for Neuroscience
Date: 02-04-2014
DOI: 10.1523/JNEUROSCI.3765-13.2014
Abstract: Detecting the location of salient sounds in the environment rests on the brain's ability to use differences in sounds arriving at both ears. Functional neuroimaging studies in humans indicate that the left and right auditory hemispaces are coded asymmetrically, with a rightward attentional bias that reflects spatial attention in vision. Neuropsychological observations in patients with spatial neglect have led to the formulation of two competing models: the orientation bias and right-hemisphere dominance models. The orientation bias model posits a symmetrical mapping between one side of the sensorium and the contralateral hemisphere, with mutual inhibition of the ipsilateral hemisphere. The right-hemisphere dominance model introduces a functional asymmetry in the brain's coding of space: the left hemisphere represents the right side, whereas the right hemisphere represents both sides of the sensorium. We used Dynamic Causal Modeling of effective connectivity and Bayesian model comparison to adjudicate between these alternative network architectures, based on human electroencephalographic data acquired during an auditory location oddball paradigm. Our results support a hemispheric asymmetry in a frontoparietal network that conforms to the right-hemisphere dominance model. We show that, within this frontoparietal network, forward connectivity increases selectively in the hemisphere contralateral to the side of sensory stimulation. We interpret this finding in light of hierarchical predictive coding as a selective increase in attentional gain, which is mediated by feedforward connections that carry precision-weighted prediction errors during perceptual inference. This finding supports the disconnection hypothesis of unilateral neglect and has implications for theories of its etiology.
Publisher: Springer Science and Business Media LLC
Date: 08-04-2020
Publisher: Springer Science and Business Media LLC
Date: 21-08-2018
Publisher: Elsevier BV
Date: 10-2015
Publisher: Cold Spring Harbor Laboratory
Date: 17-01-2019
DOI: 10.1101/522185
Abstract: The human brain is thought to optimise the encoding of incoming sensory information through two principal mechanisms: prediction uses stored information to guide the interpretation of forthcoming sensory events, and attention prioritizes these events according to their behavioural relevance. Despite the ubiquitous contributions of attention and prediction to various aspects of perception and cognition, it remains unknown how they interact to modulate information processing in the brain. A recent extension of predictive coding theory suggests that attention optimises the expected precision of predictions by modulating the synaptic gain of prediction error units. Since prediction errors code for the difference between predictions and sensory signals, this model would suggest that attention increases the selectivity for mismatch information in the neural response to a surprising stimulus. Alternative predictive coding models proposes that attention increases the activity of prediction (or ‘representation’) neurons, and would therefore suggest that attention and prediction synergistically modulate selectivity for feature information in the brain. Here we applied multivariate forward encoding techniques to neural activity recorded via electroencephalography (EEG) as human observers performed a simple visual task, to test for the effect of attention on both mismatch and feature information in the neural response to surprising stimuli. Participants attended or ignored a periodic stream of gratings, the orientations of which could be either predictable, surprising, or unpredictable. We found that surprising stimuli evoked neural responses that were encoded according to the difference between predicted and observed stimulus features, and that attention facilitated the encoding of this type of information in the brain. These findings advance our understanding of how attention and prediction modulate information processing in the brain, and support the theory that attention optimises precision expectations during hierarchical inference by increasing the gain of prediction errors.
Publisher: Center for Open Science
Date: 27-04-2023
Abstract: Bayesian inference suggests that perception is inferred from a weighted integration of prior contextual beliefs with current sensory evidence (likelihood) about the world around us. The perceived precision or uncertainty associated with prior and likelihood information is used to guide perceptual decision making, such that more weight is placed on the source of information with greater precision. This provides a framework for understanding a spectrum of clinical transdiagnostic symptoms associated with aberrant perception, as well as in idual differences in the general population. Whilst behavioural paradigms are commonly used to characterise in idual differences in perception as a trait-like characteristic, measurement reliability in these behavioural tasks is rarely assessed. To remedy this gap, we empirically evaluate the reliability of a perceptual decision-making task that quantifies in idual differences in Bayesian belief updating in terms of the relative precision weighting afforded to prior and likelihood information (i.e., sensory weight). We analysed data from participants (n = 37) who performed this task twice. We found that the precision afforded to prior and likelihood information showed high internal consistency and good test re-test reliability (ICC = 0.86, 95%CI[0.72, 0.93]) when averaged across participants, as well as at the in idual level using hierarchical modelling. Our results provide support for the assumption that Bayesian belief updating operates as a stable, trait-like characteristic in perceptual decision making. We discuss the utility and applicability of reliable perceptual decision-making paradigms as a measure of in idual differences in the general population, as well as a diagnostic tool in psychiatric research.
Publisher: Elsevier BV
Date: 07-2007
Publisher: Society for Neuroscience
Date: 10-03-2017
DOI: 10.1523/JNEUROSCI.3525-16.2017
Abstract: There is significant controversy over the existence and function of a direct subcortical visual pathway to the amygdala. It is thought that this pathway rapidly transmits low spatial frequency information to the amygdala independently of the cortex, and yet the directionality of this function has never been determined. We used magnetoencephalography to measure neural activity while human participants discriminated the gender of neutral and fearful faces filtered for low or high spatial frequencies. We applied dynamic causal modeling to demonstrate that the most likely underlying neural network consisted of a pulvinar-amygdala connection that was uninfluenced by spatial frequency or emotion, and a cortical-amygdala connection that conveyed high spatial frequencies. Crucially, data-driven neural simulations revealed a clear temporal advantage of the subcortical connection over the cortical connection in influencing amygdala activity. Thus, our findings support the existence of a rapid subcortical pathway that is nonselective in terms of the spatial frequency or emotional content of faces. We propose that that the “coarseness” of the subcortical route may be better reframed as “generalized.” SIGNIFICANCE STATEMENT The human amygdala coordinates how we respond to biologically relevant stimuli, such as threat or reward. It has been postulated that the amygdala first receives visual input via a rapid subcortical route that conveys “coarse” information, namely, low spatial frequencies. For the first time, the present paper provides direction-specific evidence from computational modeling that the subcortical route plays a generalized role in visual processing by rapidly transmitting raw, unfiltered information directly to the amygdala. This calls into question a widely held assumption across human and animal research that fear responses are produced faster by low spatial frequencies. Our proposed mechanism suggests organisms quickly generate fear responses to a wide range of visual properties, heavily implicating future research on anxiety-prevention strategies.
Publisher: Cold Spring Harbor Laboratory
Date: 23-10-2021
DOI: 10.1101/2021.10.21.464885
Abstract: A general consensus persists that sensory-perceptual differences in autism, such as hypersensitivities to light or sound, result from an overreliance on new (rather than prior) sensory observations. However, conflicting Bayesian accounts of autism remain unresolved as to whether such alterations are caused by more precise sensory observations (precise likelihood model) or by forming a less precise model of the sensory context (hypo-priors model). We used a decision-under-uncertainty paradigm that manipulated uncertainty in both likelihoods and priors. Contrary to model predictions we found no differences in reliance on likelihood in autistic group (AS) compared to neurotypicals (NT) and found no differences in subjective prior variance between groups. However, we found reduced context adjustment in the AS group compared to NT. Further, the AS group showed heightened variability in their relative weighting of sensory information (vs. prior) on a trial-by-trial basis. When participants were aligned on a continuum of autistic traits, we found no associations with likelihood reliance or prior variance but found an increased likelihood precision with autistic traits. These findings together provide empirical evidence for intact priors, precise likelihood, reduced context updating and heightened variability during sensory learning in autism.
Publisher: Association for Research in Vision and Ophthalmology (ARVO)
Date: 10-01-2019
DOI: 10.1167/19.1.3
Abstract: Neural processing of sensory input in the brain takes time, and for that reason our awareness of visual events lags behind their actual occurrence. One way the brain might compensate to minimize the impact of the resulting delays is through extrapolation. Extrapolation mechanisms have been argued to underlie perceptual illusions in which moving and static stimuli are mislocalised relative to one another (such as the flash-lag and related effects). However, where in the visual hierarchy such extrapolation processes take place remains unknown. Here, we address this question by identifying monocular and binocular contributions to the flash-grab illusion. In this illusion, a brief target is flashed on a moving background that reverses direction. As a result, the perceived position of the target is shifted in the direction of the reversal. We show that the illusion is attenuated, but not eliminated, when the motion reversal and the target are presented dichoptically to separate eyes. This reveals extrapolation mechanisms at both monocular and binocular processing stages contribute to the illusion. We interpret the results in a hierarchical predictive coding framework, and argue that prediction errors in this framework manifest directly as perceptual illusions.
Publisher: Center for Open Science
Date: 02-06-2023
Abstract: Recent research suggests that autistic females may possess superior socio-cognitive abilities compared to autistic males, potentially contributing to underdiagnosis in females. However, it remains unclear if autistic females are better at camouflaging their symptoms or if differences arise from distinct neurophysiological functioning in this subgroup. This study aimed to address the question by employing an oddball paradigm involving spatially filtered faces in a s le of 41 autistic and 48 non-autistic adults. Analysis of event-related potentials and sources revealed a neurophysiological profile in autistic females that fell between those of autistic males and non-autistic females, highlighting sex differences in autism from the initial stages of face processing. This finding underscores the urgent need to explore sex and gender differences in autism research and encourages efforts toward a clearer definition of the camouflaging construct.
Publisher: eLife Sciences Publications, Ltd
Date: 16-01-2019
DOI: 10.7554/ELIFE.40766
Abstract: Our ability to rapidly detect threats is thought to be subserved by a subcortical pathway that quickly conveys visual information to the amygdala. This neural shortcut has been demonstrated in animals but has rarely been shown in the human brain. Importantly, it remains unclear whether such a pathway might influence neural activity and behavior. We conducted a multimodal neuroimaging study of 622 participants from the Human Connectome Project. We applied probabilistic tractography to diffusion-weighted images, reconstructing a subcortical pathway to the amygdala from the superior colliculus via the pulvinar. We then computationally modeled the flow of haemodynamic activity during a face-viewing task and found evidence for a functionally afferent pulvinar-amygdala pathway. Critically, in iduals with greater fibre density in this pathway also had stronger dynamic coupling and enhanced fearful face recognition. Our findings provide converging evidence for the recruitment of an afferent subcortical pulvinar connection to the amygdala that facilitates fear recognition. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that minor issues remain unresolved ( xref ref-type="decision-letter" rid="SA1" see decision letter /xref ).
Publisher: Cold Spring Harbor Laboratory
Date: 08-02-2019
DOI: 10.1101/544452
Abstract: Our sensory systems actively predict sensory information based on previously learnt patterns. An inability to accurately predict forthcoming information results in prediction errors. In iduals with schizophrenia consistently show reduced auditory prediction errors as well as reduced microstructure in auditory white matter pathways. However, it is not clear if also healthy in iduals with psychotic experiences demonstrate such deficits. Participants underwent electroencephalography (EEG) recordings while listening to a simple two-tone duration deviant oddball paradigm (N=103) and a stochastic oddball paradigm (N=89). A subset of participants (N=89) also underwent diffusion-weighted magnetic resonance imaging (MRI), from which fractional anisotropy (FA), a measure of overall white matter microstructure, was obtained for auditory pathways namely the auditory interhemispheric pathway, as well as the left and right arcuate fasciculi. We investigated both structural and functional predictors of positive psychotic experiences in healthy participants as measured by the Community Assessment for Psychic Experiences positive dimension (CAPE+) scores. Prediction errors evoked by the classical oddball paradigm failed to reveal significant effects, whereas the stochastic oddball paradigm revealed significant clusters at typical mismatch negativity periods predictive of CAPE+ scores. Furthermore, we show that white matter microstructure from auditory pathways in addition to mismatches significantly predict CAPE+ scores. We suggest that structural and functional prediction error measures together may have potential in predicting psychotic experiences in the healthy population.
Publisher: Frontiers Media SA
Date: 23-05-2018
Publisher: Center for Open Science
Date: 21-09-2023
Publisher: Elsevier BV
Date: 2018
DOI: 10.1016/J.SCHRES.2017.04.019
Abstract: Sensory prediction errors are fundamental brain responses that signal a violation of expectation in either the internal or external sensory environment, and are therefore crucial for survival and adaptive behaviour. Patients with schizophrenia show deficits in these internal and external sensory prediction errors, which can be measured using electroencephalography (EEG) components such as N1 and mismatch negativity (MMN), respectively. New evidence suggests that these deficits in sensory prediction errors are more widely distributed on a continuum of psychosis, whereas psychotic experiences exist to varying degrees throughout the general population. In this paper, we review recent findings in sensory prediction errors in the auditory domain across the continuum of psychosis, and discuss these in light of the predictive coding hypothesis.
Publisher: Elsevier BV
Date: 09-2017
Publisher: Public Library of Science (PLoS)
Date: 07-11-2013
Publisher: Cold Spring Harbor Laboratory
Date: 22-09-2017
DOI: 10.1101/192583
Abstract: A lesion to the right hemisphere of the brain often leads to perceptual neglect of the left side of the sensorium. The fact that lesions to different cortical regions lead to the same symptoms points to neglect as a dysconnection syndrome that may result from the dysconnection of a distributed network, rather than a disruption of computation in any particular brain region. To test this hypothesis, we used Bayesian analysis of effective connectivity based on electroencephalographic recordings in patients with left-sided neglect after a right-hemisphere lesion. While age-matched healthy controls showed a contralateral increase in connection strength between parietal and frontal cortex with respect to the laterality of the stimuli, neglect patients showed a dysconnection between parietal and frontal cortex in the right hemisphere when stimuli appeared on their neglected side, but preserved connectivity in the left hemisphere when stimuli appeared on their right. Crucially, this parieto-frontal feedback connectivity was aggravated in patients with more severe symptoms. In contrast, patients and controls did not show differences in the local connectivity within regions. These findings suggest that the aetiology of neglect may lie in the dysconnection of a distributed network, rather than the disruption of any particular brain region.
Publisher: Research Square Platform LLC
Date: 13-03-2023
DOI: 10.21203/RS.3.RS-2649734/V1
Abstract: Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can h er the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.
Publisher: Elsevier
Date: 2007
Publisher: Public Library of Science (PLoS)
Date: 27-02-2019
Publisher: Wiley
Date: 25-09-2019
DOI: 10.1002/HBM.24392
Publisher: Public Library of Science (PLoS)
Date: 10-07-2019
Publisher: Elsevier BV
Date: 09-2012
Publisher: Public Library of Science (PLoS)
Date: 28-03-2013
Publisher: Public Library of Science (PLoS)
Date: 21-02-2013
Publisher: Society for Neuroscience
Date: 20-07-2020
Publisher: Elsevier BV
Date: 09-2014
DOI: 10.1016/J.CLINPH.2014.01.015
Abstract: We investigated the neurophysiological mechanisms underpinning the generation of the mismatch negativity (MMN) in the ageing brain. We used dynamic causal modelling (DCM) to study connectivity models for healthy young and old subjects. MMN was elicited with an auditory odd-ball paradigm in two groups of healthy subjects with mean age 74 (n=30) and 26 (n=26). DCM was implemented using up to five cortical nodes. We tested models with different hierarchical complexities. We showed that the network generating MMN consisted of 5 nodes that could modulate all intra- and inter-nodal connections. The inversion of this model showed that old subjects had increased input from rSTG to the rIFG (p<0.01) together with increased inhibition of pyramidal cells (p<0.05). Furthermore, there was reduced modulation of activity within rIFG (p<0.02) on stimulus change. The age related change in MMN is due to a decline in frontal-based control mechanisms, with alterations in connectivity between temporal and frontal regions together with a dysregulation of the excitatory-inhibitory balance in the rIFG. This study provides for the first time a neurobiological explanation for the age related changes of the MMN in the ageing brain.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 02-12-2011
Abstract: King et al . raise some technical issues about our recent study showing impaired top-down processes in the vegetative state. We welcome the opportunity to provide more details about our methods and results and to resolve their concerns. We substantiate our interpretation of the results and provide a point-by-point response to the issues raised.
Publisher: Frontiers Media SA
Date: 22-12-2015
Publisher: Elsevier BV
Date: 08-2012
DOI: 10.1016/J.CUB.2012.06.012
Abstract: A visual subcortical pathway to the amygdala that undergoes structural plastic strengthening in blindsight has been identified in humans - neuroanatomical evidence for a pathway that might mediate rapid non-conscious processing of salient information.
Publisher: Cold Spring Harbor Laboratory
Date: 03-2019
DOI: 10.1101/564450
Abstract: Humans show striking limitations in information processing when multitasking, yet can modify these limits with practice. Such limitations have been linked to a frontal-parietal network, but recent models of decision-making implicate a striatal-cortical network. We adjudicated these accounts by investigating the circuitry underpinning multitasking in 100 in iduals and the plasticity caused by practice. We observed that multitasking costs, and their practice induced remediation, are best explained by modulations in information transfer between the striatum and the cortical areas that represent stimulus-response mappings. Specifically, our results support the view that multitasking stems at least in part from taxation in information sharing between the putamen and pre-supplementary motor area (pre-SMA). Moreover, we propose that modulations to information transfer between these two regions leads to practice-induced improvements in multitasking. Humans show striking limitations in information processing when multitasking, yet can modify these limits with practice. Such limitations have been linked to a frontal-parietal network, but recent models of decision-making implicate a striatal-cortical network. We adjudicated these accounts by investigating the circuitry underpinning multitasking in 100 in iduals and the plasticity caused by practice. Our results support the view that multitasking stems at least in part from taxation in information sharing between the putamen and pre-supplementary motor area (pre-SMA). We therefore show that models of cognitive capacity limits must consider how subcortical and cortical structures interface to produce cognitive behaviours, and we propose a novel neurophysiological substrate of multitasking limitations.
Publisher: Cold Spring Harbor Laboratory
Date: 09-12-2021
DOI: 10.1101/2021.12.08.471716
Abstract: Bayesian models of autism suggest that disruptions in context-sensitive prediction error weighting may underpin sensory perceptual alterations, such as hypersensitivities. We used an auditory oddball paradigm with pure tones arising from high or low uncertainity contexts to determine whether autistic in iduals display differences in context adjustment relative to neurotypicals. We did not find group differences in early prediction error responses indexed by mismatch negativity. However, the autism group had larger evoked responses to outliers, at 300ms latency suggesting a greater reorienting of attention to surprising sounds. A dimensional approach revealed a positive correlation between context-dependent prediction errors and auditory sensitivities, but not with autistic traits. These findings suggest that autism studies may benefit from accounting for sensory sensitivities in group comparisons. We find no differences in brain responses (EEG litudes) between autistic and neurotypical adults when listening to two contexts of tone patterns. However, we find a larger difference in the EEG litude when shifting between low to high uncertainity streams of tones, as sensory sensitivities (but not autistic traits) increase. These findings show that perceptual alterations maybe a function of sensory sensitivities, but not necessarily autistic traits. We suggest that future EEG studies in autism may benefit from accounting for sensory sensitivities.
Publisher: Elsevier BV
Date: 06-2021
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 2017
Publisher: Wiley
Date: 19-02-2015
DOI: 10.1002/HBM.22762
Publisher: Center for Open Science
Date: 21-09-2023
Publisher: Mary Ann Liebert Inc
Date: 02-2012
Abstract: The last 10 years witnessed a considerable increase in our knowledge of brain function in survivors to severe brain injuries with disorders of consciousness (DOC). At the same time, a growing interest developed for the use of functional neuroimaging as a new diagnostic tool in these patients. In this context, particular attention has been devoted to connectivity studies-as these, more than measures of brain metabolism, may be more appropriate to capture the dynamics of large populations of neurons. Here, we will review the pros and cons of various connectivity methods as potential diagnostic tools in brain-damaged patients with DOC. We will also discuss the relevance of the study of the level versus the contents of consciousness in this context.
Publisher: Oxford University Press (OUP)
Date: 10-04-2017
Abstract: Predictive coding posits that the human brain continually monitors the environment for regularities and detects inconsistencies. It is unclear, however, what effect attention has on expectation processes, as there have been relatively few studies and the results of these have yielded contradictory findings. Here, we employed Bayesian model comparison to adjudicate between 2 alternative computational models. The "Opposition" model states that attention boosts neural responses equally to predicted and unpredicted stimuli, whereas the "Interaction" model assumes that attentional boosting of neural signals depends on the level of predictability. We designed a novel, audiospatial attention task that orthogonally manipulated attention and prediction by playing oddball sequences in either the attended or unattended ear. We observed sensory prediction error responses, with electroencephalography, across all attentional manipulations. Crucially, posterior probability maps revealed that, overall, the Opposition model better explained scalp and source data, suggesting that attention boosts responses to predicted and unpredicted stimuli equally. Furthermore, Dynamic Causal Modeling showed that these Opposition effects were expressed in plastic changes within the mismatch negativity network. Our findings provide empirical evidence for a computational model of the opposing interplay of attention and expectation in the brain.
Publisher: American Physiological Society
Date: 05-2009
Abstract: This article describes the use of dynamic causal modeling to test hypotheses about the genesis of evoked responses. Specifically, we consider the mismatch negativity (MMN), a well-characterized response to deviant sounds and one of the most widely studied evoked responses. There have been several mechanistic accounts of how the MMN might arise. It has been suggested that the MMN results from a comparison between sensory input and a memory trace of previous input, although others have argued that local adaptation, due to stimulus repetition, is sufficient to explain the MMN. Thus the precise mechanisms underlying the generation of the MMN remain unclear. This study tests some biologically plausible spatiotemporal dipole models that rest on changes in extrinsic top-down connections (that enable comparison) and intrinsic changes (that model adaptation). Dynamic causal modeling suggested that responses to deviants are best explained by changes in effective connectivity both within and between cortical sources in a hierarchical network of distributed sources. Our model comparison suggests that both adaptation and memory comparison operate in concert to produce the early (N1 enhancement) and late (MMN) parts of the response to frequency deviants. We consider these mechanisms in the light of predictive coding and hierarchical inference in the brain.
Publisher: Elsevier BV
Date: 07-2019
DOI: 10.1016/J.NEUROIMAGE.2019.04.008
Abstract: Auditory prediction errors, i.e. the mismatch between predicted, forthcoming auditory sensations and actual sensory input, trigger the detection of surprising auditory events in the environment. Auditory mismatches engage a hierarchical functional network of cortical sources, which are also interconnected by auditory white matter pathways. Hence it is plausible that these structural and functional networks are quantitatively related. The present study set out to investigate whether structural connectivity of auditory white matter pathways enables the effective connectivity underpinning auditory mismatch responses. Participants (N = 89) underwent diffusion weighted magnetic resonance imaging (MRI) and electroencephalographic (EEG) recordings. Anatomically-constrained tractography was used to extract auditory white matter pathways, namely the bilateral arcuate fasciculi, inferior fronto-occipital fasciculi (IFOF), and the auditory interhemispheric pathway, from which Apparent Fibre Density (AFD) was calculated. EEG data were recorded in the same participants during a stochastic oddball paradigm, which was used to elicit auditory prediction error responses. Dynamic causal modelling was used to investigate the effective connectivity underlying auditory mismatch responses generated in brain regions interconnected by the above mentioned auditory white matter pathways. Our results showed that brain areas interconnected by all auditory white matter pathways best explained the dynamics of auditory mismatch responses. Furthermore, AFD in the right arcuate fasciculus was significantly associated with the effective connectivity between the cortical regions that lie within it. Taken together, these findings indicate that auditory prediction errors recruit a fronto-temporal network of brain regions that are effectively and structurally connected by auditory white matter pathways.
Publisher: Cold Spring Harbor Laboratory
Date: 28-09-2016
DOI: 10.1101/078097
Abstract: There is significant controversy over the anatomical existence and potential function of a direct subcortical visual pathway to the amygdala. It is thought that this pathway rapidly transmits low spatial frequency information to the amygdala independently of the cortex and yet this function has never been causally determined. In this study, neural activity was measured using magnetoencephalography (MEG) while participants discriminated the gender of neutral and fearful faces filtered for low or high spatial frequencies. Dynamic causal modelling (DCM) revealed that the most likely underlying neural network consisted of a subcortical pulvino-amygdala connection that was not modulated by spatial frequency or emotion and a cortico-amygdala connection that conveyed predominantly high spatial frequencies. Crucially, data-driven neural simulations demonstrated a clear temporal advantage of the subcortical route (70ms) over the cortical route (155ms) in influencing amygdala activity. Thus, our findings support the existence of a rapid functional subcortical pathway that is unselective of the spatial frequency or emotional content of faces.
Start Date: 2013
End Date: 07-2016
Amount: $375,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 03-2018
End Date: 12-2021
Amount: $414,792.00
Funder: Australian Research Council
View Funded ActivityStart Date: 06-2014
End Date: 12-2021
Amount: $20,000,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2023
End Date: 12-2023
Amount: $930,213.00
Funder: Australian Research Council
View Funded Activity