ORCID Profile
0000-0003-3076-5891
Current Organisations
Academic Medical Center
,
Amsterdam UMC
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Publisher: Society for Neuroscience
Date: 07-2018
DOI: 10.1523/ENEURO.0240-18.2018
Abstract: “Slips of action” occur in everyday life when we momentarily lose sight of a goal (for ex le, when in a rush or distracted). Associative models propose that these habitual responses can be activated via a direct stimulus-response (S-R) mechanism, regardless of the current hedonic value of the outcome. The slips-of-action task (SOAT) has been extensively used in both healthy and pathological populations to measure habit tendencies, the likelihood of making erroneous responses for devalued outcomes. Inspection of behavioral performance does not reveal, however, whether the impairments were due to impaired goal-directed control or aberrantly strong habit formation. In the current study, we used functional MRI while human participants performed both the instrumental training and SOAT test phases, to elucidate the relative contributions of these mechanisms to performance on the SOAT. On trials in which conflict arises between competing goal-directed and habitual responses, we observed increased activation across areas including the anterior cingulate cortex, paracingulate gyrus, lateral orbitofrontal cortex (OFC), insula, and inferior frontal gyrus (IFG). Responding for devalued outcomes was related to increased activation in the premotor cortex and cerebellum, implicating these regions in habitual responding. Increased activation in the caudate, dorsolateral prefrontal cortex (dlPFC), and frontal pole during training was associated with better performance during the test phase, indicative of goal-directed action control. These results endorse interpretation of the SOAT in terms of competing goal-directed and habitual mechanisms and highlight that cognitive control processes present an additional bottleneck for successful performance on this task.
Publisher: Royal College of Psychiatrists
Date: 27-06-2022
DOI: 10.1192/BJO.2022.516
Abstract: Recent paradigm shifts suggest that psychopathology manifests through dynamic interactions between in idual symptoms. To investigate the longitudinal relationships between symptoms in a transdiagnostic s le of patients with psychiatric disorders. A two-wave, cross-lagged panel network model of 15 nodes representing symptoms of depression, (social) anxiety and attenuated psychotic symptoms was estimated, using baseline and 1-year follow-up data of 222 in iduals with psychiatric disorders. Centrality indices were calculated to determine important predictors and outcomes. Our results demonstrated that the strongest relationships in the network were between (a) more suicidal ideation predicting more negative self-view, and (b) autoregressive relationships of social anxiety symptoms positively reinforcing themselves. Negative self-view was the most predictable node in the network as it had the highest ‘in-expected influence’ centrality, and may be an important transdiagnostic outcome symptom. The results give insight into longitudinal interactions between symptoms, which interact in ways that do not adhere to broader diagnostic categories. Our results suggest that self-view can also be a transdiagnostic outcome of psychopathology rather than just a predictor, as is normally posited, and may especially have an important relationship with suicidal ideation. Overall, our study demonstrates the dynamic complexity of psychopathology, and further supports the importance of investigating symptom interactions of different psychopathological dimensions over time and across disorders.
Publisher: Springer Science and Business Media LLC
Date: 20-03-2020
DOI: 10.1038/S41398-020-0705-1
Abstract: This review summarizes the last decade of work by the ENIGMA ( E nhancing N euro I maging G enetics through M eta A nalysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has ersified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of “big data” (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA’s activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across erse s les and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
Publisher: Cambridge University Press (CUP)
Date: 24-06-2021
DOI: 10.1017/S0033291721001781
Abstract: Patients with psychiatric disorders often experience cognitive dysfunction, but the precise relationship between cognitive deficits and psychopathology remains unclear. We investigated the relationships between domains of cognitive functioning and psychopathology in a transdiagnostic s le using a data-driven approach. Cross-sectional network analyses were conducted to investigate the relationships between domains of psychopathology and cognitive functioning and detect clusters in the network. This naturalistic transdiagnostic s le consists of 1016 psychiatric patients who have a variety of psychiatric diagnoses, such as depressive disorders, anxiety disorders, obsessive−compulsive and related disorders, and schizophrenia spectrum and other psychotic disorders. Psychopathology symptoms were assessed using various questionnaires. Core cognitive domains were assessed with a battery of automated tests. Network analysis detected three clusters that we labelled: general psychopathology, substance use, and cognition. Depressive and anxiety symptoms, verbal memory, and visual attention were the most central nodes in the network. Most associations between cognitive functioning and symptoms were negative, i.e. increased symptom severity was associated with worse cognitive functioning. Cannabis use, (subclinical) psychotic experiences, and anhedonia had the strongest total negative relationships with cognitive variables. Cognitive functioning and psychopathology are independent but related dimensions, which interact in a transdiagnostic manner. Depression, anxiety, verbal memory, and visual attention are especially relevant in this network and can be considered independent transdiagnostic targets for research and treatment in psychiatry. Moreover, future research on cognitive functioning in psychopathology should take a transdiagnostic approach, focusing on symptom-specific interactions with cognitive domains rather than investigating cognitive functioning within diagnostic categories.
Publisher: Elsevier BV
Date: 07-2023
Publisher: Cold Spring Harbor Laboratory
Date: 18-06-2019
DOI: 10.1101/673012
Abstract: Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders. Structural T1-weighted whole-brain MRI of controls ( n =5,827) and patients with ADHD (n=2,271), ASD (n=1,777), and OCD (n=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. We examined subcortical volume, cortical thickness and surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults using linear mixed-effects models adjusting for age, sex and site (and ICV for subcortical and surface area measures). We found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippoc al volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed. Our findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippoc al alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders.
Publisher: Research Square Platform LLC
Date: 23-10-2020
DOI: 10.21203/RS.3.RS-87419/V1
Abstract: Recent findings in neuroimaging and epigenetics offer important insights into brain structures and biological pathways of altered gene expression associated with posttraumatic stress disorder (PTSD). However, it is unknown to what extent epigenetic mechanisms are associated with PTSD and its neurobiology in youth. Therefore, we combine genome-wide epigenetic and structural neuroimaging measures in a Dutch cohort of youth with PTSD (ages 8-18 years). We aimed to replicate findings in a similar independent American cohort. We found significant methylome-wide associations for pediatric PTSD (FDR p .05) compared to non-PTSD control groups (traumatized and non-traumatized youth). Methylation differences on 9 genes were replicated, including genes related to glucocorticoid functioning. In both cohorts, methylation on OLFM3 gene was further associated with anterior hippoc al volume. These findings point to molecular pathways involved in inflammation, stress response, and neuroplasticity as potential contributors to neural abnormalities and provide potentially unique biomarkers and treatment targets for pediatric PTSD.
Publisher: Springer Science and Business Media LLC
Date: 07-10-2021
DOI: 10.1038/S41398-021-01619-W
Abstract: Major depressive disorder (MDD) is associated with abnormal neural circuitry. It can be measured by assessing functional connectivity (FC) at resting-state functional MRI, that may help identifying neural markers of MDD and provide further efficient diagnosis and monitor treatment outcomes. The main aim of the present study is to investigate, in an unbiased way, functional alterations in patients with MDD using a large multi-center dataset from the PsyMRI consortium including 1546 participants from 19 centers ( www.psymri.com ). After applying strict exclusion criteria, the final s le consisted of 606 MDD patients (age: 35.8 ± 11.9 y.o. females: 60.7%) and 476 healthy participants (age: 33.3 ± 11.0 y.o. females: 56.7%). We found significant relative hypoconnectivity within somatosensory motor (SMN), salience (SN) networks and between SMN, SN, dorsal attention (DAN), and visual (VN) networks in MDD patients. No significant differences were detected within the default mode (DMN) and frontoparietal networks (FPN). In addition, alterations in network organization were observed in terms of significantly lower network segregation of SMN in MDD patients. Although medicated patients showed significantly lower FC within DMN, FPN, and SN than unmedicated patients, there were no differences between medicated and unmedicated groups in terms of network organization in SMN. We conclude that the network organization of cortical networks, involved in processing of sensory information, might be a more stable neuroimaging marker for MDD than previously assumed alterations in higher-order neural networks like DMN and FPN.
Publisher: Springer Netherlands
Date: 2008
Publisher: Frontiers Media SA
Date: 08-01-2019
Publisher: Research Square Platform LLC
Date: 06-2023
DOI: 10.21203/RS.3.RS-2925196/V1
Abstract: Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated in iduals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this common causal network (CCN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis (Principal Component Analysis, PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CCN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CCN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes. This evidence further supports that treatment interventions converge on a CCN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.
Publisher: American Psychiatric Association Publishing
Date: 06-2017
Publisher: Elsevier BV
Date: 06-2018
DOI: 10.1016/J.DRUGALCDEP.2018.03.010
Abstract: Neuroimaging studies have demonstrated gray matter (GM) volume abnormalities in substance users. While the majority of substance users are polysubstance users, very little is known about the relation between GM volume abnormalities and polysubstance use. In this study we assessed the relation between GM volume, and the use of alcohol, tobacco, cocaine and cannabis as well as the total number of substances used, in a s le of 169 males: 15 non-substance users, 89 moderate drinkers, 27 moderate drinkers who also smoke tobacco, 13 moderate drinkers who also smoke tobacco and use cocaine, 10 heavy drinkers who smoke tobacco and use cocaine and 15 heavy drinkers who smoke tobacco, cannabis and use cocaine. Regression analyses showed that there was a negative relation between the number of substances used and volume of the dorsal medial prefrontal cortex (mPFC) and the ventral mPFC. Without controlling for the use of other substances, the volume of the dorsal mPFC was negatively associated with the use of alcohol, tobacco, and cocaine. After controlling for the use of other substances, a negative relation was found between tobacco and cocaine and volume of the thalami and ventrolateral PFC, respectively. These findings indicate that mPFC alterations may not be substance-specific, but rather related to the number of substances used, whereas, thalamic and ventrolateral PFC pathology is specifically associated with tobacco and cocaine use, respectively. These findings are important, as the differential alterations in GM volume may underlie different cognitive deficits associated with substance use disorders.
Publisher: Elsevier BV
Date: 10-2017
DOI: 10.1016/J.DRUGALCDEP.2017.06.025
Abstract: Glutamate and GABA play an important role in substance dependence. However, it remains unclear whether this holds true for different substance use disorders and how this is related to risk-related traits such as impulsivity. We, therefore, compared Glx (as a proxy measure for glutamate) and GABA concentrations in the dorsal anterior cingulate cortex (dACC) of 48 male cigarette smokers, 61 male smoking polysubstance users, and 90 male healthy controls, and investigated the relationship with self-reported impulsivity and substance use. Glx and GABA concentrations were measured using proton Magnetic Resonance Spectroscopy. Impulsivity, smoking, alcohol and cocaine use severity and cannabis use were measured using self-report instruments. Results indicate a trend towards group differences in Glx. Post-hoc analyses showed a difference between smokers and healthy controls (p=0.04) and a trend towards higher concentrations in smoking polysubstance users and healthy controls (p=0.09), but no differences between smokers and smoking polysubstance users. dACC GABA concentrations were not significantly different between groups. Smoking polysubstance users were more impulsive than smokers, and both groups were more impulsive than controls. No significant associations were observed between dACC neurotransmitter concentrations and impulsivity and level and severity of smoking, alcohol or cocaine use or the presence of cannabis use. The results indicate that differences in dACC Glx are unrelated to type and level of substance use. No final conclusion can be drawn on the lack of GABA differences due to assessment difficulties. The relationship between dACC neurotransmitter concentrations and cognitive impairments other than self-reported impulsivity should be further investigated.
Publisher: American Psychiatric Association Publishing
Date: 2017
Publisher: Research Square Platform LLC
Date: 26-08-2021
DOI: 10.21203/RS.3.RS-736917/V1
Abstract: Attention-deficit/hyperactivity disorder (ADHD) is characterized by neurobiological heterogeneity, possibly explaining why not all patients benefit from a given treatment. As a means to select the right treatment (stratification), biomarkers may aid in personalizing treatment prescription, thereby increasing remission rates.The present study introduces a clinically interpretable and actionable, age- and sex-standardized biomarker based on in idual alpha peak frequency (iAPF) assessed during resting-state electroencephalography (EEG). The biomarker was developed in a heterogeneous s le (N=4249), and stratifies patients with a higher iAPF to Methylphenidate (MPH N=336) and those with a lower iAPF to Neurofeedback (NFB N=136), resulting in a predicted gain in normalized remission of 17-30%. Blinded out-of-s le validation studies for MPH (N=58) and NFB (N=96) corroborated these findings, yielding a predicted gain in stratified normalized remission of 36% and 29%, respectively.These findings suggest that acknowledging neurobiological heterogeneity can inform stratification of patients to their in idual best treatment and enhance remission rates.
Publisher: Elsevier BV
Date: 06-2020
Publisher: Center for Open Science
Date: 04-07-2019
Abstract: This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1,400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has ersified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of “big data” (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA’s activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across erse s les and associated genetic, environmental, demographic, cognitive and psychosocial factors.
Publisher: Wiley
Date: 10-03-2015
DOI: 10.1002/HBM.22779
Publisher: Springer Science and Business Media LLC
Date: 11-05-2020
DOI: 10.1186/S12888-020-02624-X
Abstract: Patients with psychiatric disorders, such as major depressive disorder, schizophrenia or obsessive-compulsive disorder, often suffer from cognitive dysfunction. The nature of these dysfunctions and their relation with clinical symptoms and biological parameters is not yet clear. Traditionally, cognitive dysfunction is studied in patients with specific psychiatric disorders, disregarding the fact that cognitive deficits are shared across disorders. The Across study aims to investigate cognitive functioning and its relation with psychiatric symptoms and biological parameters transdiagnostically and longitudinally. The study recruits patients diagnosed with a variety of psychiatric disorders and has a longitudinal cohort design with an assessment at baseline and at one-year follow-up. The primary outcome measure is cognitive functioning. The secondary outcome measures include clinical symptoms, electroencephalographic, genetic and blood markers (e.g., fatty acids), and hair cortisol concentration levels. The Across study provides an opportunity for a transdiagnostic, bottom-up, data-driven approach of investigating cognition in relation to symptoms and biological parameters longitudinally in patients with psychiatric disorders. The study may help to find new clusters of symptoms, biological markers, and cognitive dysfunctions that have better prognostic value than the current diagnostic categories. Furthermore, increased insight into the relationship among cognitive deficits, biological parameters, and psychiatric symptoms can lead to new treatment possibilities. Netherlands Trial Register (NTR): NL8170 .
Publisher: Elsevier BV
Date: 08-2013
DOI: 10.1016/J.DRUGALCDEP.2013.05.007
Abstract: Adult attention deficit/hyperactivity disorder (ADHD) is highly comorbid with other psychiatric disorders, including substance use disorders (SUD). Patients with ADHD and SUD comorbidity respond less well to pharmacological treatment (e.g., methylphenidate), have more severe ADHD symptoms, and are generally more impulsive than ADHD patients without SUD. However, little is known about structural brain abnormalities that may differentiate ADHD patients with and without comorbid SUD. We compared regional grey matter volumes of 10 non-medicated male ADHD patients with comorbid cocaine dependence, 14 non-medicated male ADHD patients without cocaine dependence and 15 healthy control participants matched for age and premorbid intellectual functioning, using voxel-based morphometry (VBM) using both a whole-brain analysis and a priori ROI analysis based on the existing ADHD VBM literature. In a whole brain analysis, ADHD patients with and without cocaine dependence showed smaller volumes in the right putamen and cerebellum compared to healthy controls. In addition, ADHD patients without cocaine dependence showed larger volumes in the midbrain and in the precentral gyrus compared to healthy control participants and larger volumes in the occipital cortex compared to ADHD patients with comorbid cocaine dependence. A direct comparison using the a priori defined ROI approach showed that ADHD patients with cocaine dependence had smaller putamen volumes than ADHD patients without cocaine dependence. ADHD patients with cocaine dependence show more profound grey matter volume reductions in the striatum compared to ADHD patients without cocaine dependence. Possible implications for treatment are discussed.
Publisher: Springer Science and Business Media LLC
Date: 26-06-2023
Publisher: American Psychiatric Association Publishing
Date: 05-2018
No related grants have been discovered for Guido van Wingen.