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Friston K. Computational psychiatry: from synapses to sentience. Mol Psychiatry 2023; 28:256-268. [PMID: 36056173 PMCID: PMC7614021 DOI: 10.1038/s41380-022-01743-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 08/08/2022] [Accepted: 08/11/2022] [Indexed: 01/09/2023]
Abstract
This review considers computational psychiatry from a particular viewpoint: namely, a commitment to explaining psychopathology in terms of pathophysiology. It rests on the notion of a generative model as underwriting (i) sentient processing in the brain, and (ii) the scientific process in psychiatry. The story starts with a view of the brain-from cognitive and computational neuroscience-as an organ of inference and prediction. This offers a formal description of neuronal message passing, distributed processing and belief propagation in neuronal networks; and how certain kinds of dysconnection lead to aberrant belief updating and false inference. The dysconnections in question can be read as a pernicious synaptopathy that fits comfortably with formal notions of how we-or our brains-encode uncertainty or its complement, precision. It then considers how the ensuing process theories are tested empirically, with an emphasis on the computational modelling of neuronal circuits and synaptic gain control that mediates attentional set, active inference, learning and planning. The opportunities afforded by this sort of modelling are considered in light of in silico experiments; namely, computational neuropsychology, computational phenotyping and the promises of a computational nosology for psychiatry. The resulting survey of computational approaches is not scholarly or exhaustive. Rather, its aim is to review a theoretical narrative that is emerging across subdisciplines within psychiatry and empirical scales of investigation. These range from epilepsy research to neurodegenerative disorders; from post-traumatic stress disorder to the management of chronic pain, from schizophrenia to functional medical symptoms.
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Affiliation(s)
- Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, WC1N 3AR, UK.
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2
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Burgher B, Whybird G, Koussis N, Scott JG, Cocchi L, Breakspear M. Sub-optimal modulation of gain by the cognitive control system in young adults with early psychosis. Transl Psychiatry 2021; 11:549. [PMID: 34707092 PMCID: PMC8551269 DOI: 10.1038/s41398-021-01673-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 09/27/2021] [Accepted: 10/06/2021] [Indexed: 11/09/2022] Open
Abstract
Executive dysfunctions in early psychosis (EP) are subtle but persistent, hindering recovery. We asked whether changes in the cognitive control system (CCS) disrupt the response to increased cognitive load in persons with EP. In all, 30 EP and 30 control participants undertook multimodal MRI. Computational models of structural and effective connectivity amongst regions in the CCS were informed by cortical responses to the multi-source interference task, a paradigm that selectively introduces stimulus conflict. EP participants showed greater activation of CCS regions, including the superior parietal cortex, and were disproportionately slower at resolving stimulus conflict in the task. Computational models of the effective connectivity underlying this behavioral response suggest that the normative (control) group resolved stimulus conflict through an efficient and direct modulation of gain between the visual cortex and the anterior insula (AI). In contrast, the EP group utilized an indirect path, with parallel and multi-region hops to resolve stimulus conflict at the AI. Individual differences in task performance were dependent on initial linear gain modulations in the EP group versus a single nonlinear modulation in the control group. Effective connectivity in the EP group was associated with reduced structural integration amongst those connections critical for task execution. CCS engagement during stimulus conflict is hampered in EP owing to inefficient use of higher-order network interactions, with high tonic gain impeding task-relevant (phasic) signal amplification.
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Affiliation(s)
- Bjorn Burgher
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia. .,Metro-North Mental Health Service, Brisbane, QLD, Australia.
| | | | - Nikitas Koussis
- grid.266842.c0000 0000 8831 109XCollege of Engineering Science and Environment, College of Health and Medicine, University of Newcastle, Callaghan, NSW Australia
| | - James G. Scott
- grid.1049.c0000 0001 2294 1395QIMR Berghofer Medical Research Institute, Herston, QLD Australia ,Metro-North Mental Health Service, Brisbane, QLD Australia
| | - Luca Cocchi
- grid.1049.c0000 0001 2294 1395QIMR Berghofer Medical Research Institute, Herston, QLD Australia
| | - Michael Breakspear
- grid.266842.c0000 0000 8831 109XCollege of Engineering Science and Environment, College of Health and Medicine, University of Newcastle, Callaghan, NSW Australia
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3
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Csukly G, Szabó Á, Polgár P, Farkas K, Gyebnár G, Kozák LR, Stefanics G. Fronto-thalamic structural and effective connectivity and delusions in schizophrenia: a combined DTI/DCM study. Psychol Med 2021; 51:2083-2093. [PMID: 32329710 PMCID: PMC8426148 DOI: 10.1017/s0033291720000859] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 02/07/2020] [Accepted: 03/20/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Schizophrenia (SZ) is a complex disorder characterized by a range of behavioral and cognitive symptoms as well as structural and functional alterations in multiple cortical and subcortical structures. SZ is associated with reduced functional network connectivity involving core regions such as the anterior cingulate cortex (ACC) and the thalamus. However, little is known whether effective coupling, the directed influence of one structure over the other, is altered during rest in the ACC-thalamus network. METHODS We collected resting-state fMRI and diffusion-weighted MRI data from 18 patients and 20 healthy controls. We analyzed fronto-thalamic effective connectivity using dynamic causal modeling for cross-spectral densities in a network consisting of the ACC and the left and right medio-dorsal thalamic regions. We studied structural connectivity using fractional anisotropy (FA). RESULTS We found decreased coupling strength from the right thalamus to the ACC and from the right thalamus to the left thalamus, as well as increased inhibitory intrinsic connectivity in the right thalamus in patients relative to controls. ACC-to-left thalamus coupling strength correlated with the Positive and Negative Syndrome Scale (PANSS) total positive syndrome score and with delusion score. Whole-brain structural analysis revealed several tracts with reduced FA in patients, with a maximum decrease in white matter tracts containing fronto-thalamic and cingulo-thalamic fibers. CONCLUSIONS We found altered effective and structural connectivity within the ACC-thalamus network in SZ. Our results indicate that ACC-thalamus network activity at rest is characterized by reduced thalamus-to-ACC coupling. We suggest that positive symptoms may arise as a consequence of compensatory measures to imbalanced fronto-thalamic coupling.
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Affiliation(s)
- Gábor Csukly
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Ádám Szabó
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary
| | - Patrícia Polgár
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Kinga Farkas
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Gyula Gyebnár
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary
| | - Lajos R. Kozák
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary
| | - Gábor Stefanics
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Wilfriedstrasse 6, 8032, Zurich, Switzerland
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4
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"First-episode psychosis: Structural covariance deficits in salience network correlate with symptoms severity". J Psychiatr Res 2021; 136:409-420. [PMID: 33647856 DOI: 10.1016/j.jpsychires.2021.01.044] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 01/08/2021] [Accepted: 01/23/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND Patterns of coordinated variations of gray matter (GM) morphology across individuals are promising indicators of disease. However, it remains unclear if they can help characterize first-episode psychosis (FEP) and symptoms' severity. METHODS Sixty-seven FEP and 67 matched healthy controls (HC) were assessed with structural MRI to evaluate the existence of distributed GM structural covariance patterns associated to brain areas belonging to salience network. Voxel-based morphometry (VBM) and structural covariance differences, investigated with salience network seed-based Partial Least Square, were applied to explore differences between groups. GM density associations with Raven's intelligent quotient (IQ) and Positive and Negative Syndrome Scale (PANSS) scores were investigated. RESULTS Univariate VBM results gave trend without significant GM differences across groups. GM and IQ correlated positively in both groups: in FEP, mostly in hippocampus, insula, and fronto-temporal structures, while in HC mostly in amygdala, thalamus and fronto-temporal regions. GM and PANSS scores correlated negatively in FEP, with widespread clusters located in limbic regions. Multivariate analysis showed strong and opposite structural GM covariance with salience network for FEP and HC. Moreover, structural covariance of the salience network in FEP correlated negatively with severity of clinical symptoms. CONCLUSION Our study provides evidence supporting the insular dysfunction model of psychosis. Reduced structural GM covariance of the salience network, with its association to symptom's severity, appears a promising morphometry feature for FEP detection.
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Gifford G, Crossley N, Morgan S, Kempton MJ, Dazzan P, Modinos G, Azis M, Samson C, Bonoldi I, Quinn B, Smart SE, Antoniades M, Bossong MG, Broome MR, Perez J, Howes OD, Stone JM, Allen P, Grace AA, McGuire P. Integrated metastate functional connectivity networks predict change in symptom severity in clinical high risk for psychosis. Hum Brain Mapp 2021; 42:439-451. [PMID: 33048435 PMCID: PMC7775992 DOI: 10.1002/hbm.25235] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 08/28/2020] [Accepted: 09/29/2020] [Indexed: 01/22/2023] Open
Abstract
The ability to identify biomarkers of psychosis risk is essential in defining effective preventive measures to potentially circumvent the transition to psychosis. Using samples of people at clinical high risk for psychosis (CHR) and Healthy controls (HC) who were administered a task fMRI paradigm, we used a framework for labelling time windows of fMRI scans as 'integrated' FC networks to provide a granular representation of functional connectivity (FC). Periods of integration were defined using the 'cartographic profile' of time windows and k-means clustering, and sub-network discovery was carried out using Network Based Statistics (NBS). There were no network differences between CHR and HC groups. Within the CHR group, using integrated FC networks, we identified a sub-network negatively associated with longitudinal changes in the severity of psychotic symptoms. This sub-network comprised brain areas implicated in bottom-up sensory processing and in integration with motor control, suggesting it may be related to the demands of the fMRI task. These data suggest that extracting integrated FC networks may be useful in the investigation of biomarkers of psychosis risk.
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Affiliation(s)
- George Gifford
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Nicolas Crossley
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Sarah Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, UK.,The Alan Turing Institute, London, UK
| | - Matthew J Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,South London and Maudsley NHS Trust, Maudsley Hospital, London, UK
| | - Gemma Modinos
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Matilda Azis
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Carly Samson
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ilaria Bonoldi
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,South London and Maudsley NHS Trust, Maudsley Hospital, London, UK
| | - Beverly Quinn
- CAMEO Early Intervention in Psychosis Service, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Sophie E Smart
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Mathilde Antoniades
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Department of Psychiatry, Icahn Medical School, Mt Sinai Hospital, New York, New York, USA
| | - Matthijs G Bossong
- Department of Psychiatry, UMC Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Matthew R Broome
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
| | - Jesus Perez
- CAMEO Early Intervention in Psychosis Service, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,South London and Maudsley NHS Trust, Maudsley Hospital, London, UK
| | - James M Stone
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,South London and Maudsley NHS Trust, Maudsley Hospital, London, UK.,Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Paul Allen
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Department of Psychology, University of Roehampton, London, UK
| | - Anthony A Grace
- Departments of Neuroscience, Psychiatry and Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,South London and Maudsley NHS Trust, Maudsley Hospital, London, UK
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Liloia D, Brasso C, Cauda F, Mancuso L, Nani A, Manuello J, Costa T, Duca S, Rocca P. Updating and characterizing neuroanatomical markers in high-risk subjects, recently diagnosed and chronic patients with schizophrenia: A revised coordinate-based meta-analysis. Neurosci Biobehav Rev 2021; 123:83-103. [PMID: 33497790 DOI: 10.1016/j.neubiorev.2021.01.010] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 01/07/2021] [Accepted: 01/15/2021] [Indexed: 01/10/2023]
Abstract
Characterizing neuroanatomical markers of different stages of schizophrenia (SZ) to assess pathophysiological models of how the disorder develops is an important target for the clinical practice. We performed a meta-analysis of voxel-based morphometry studies of genetic and clinical high-risk subjects (g-/c-HR), recently diagnosed (RDSZ) and chronic SZ patients (ChSZ). We quantified gray matter (GM) changes associated with these four conditions and compared them with contrast and conjunctional data. We performed the behavioral analysis and networks decomposition of alterations to obtain their functional characterization. Results reveal a cortical-subcortical, left-to-right homotopic progression of GM loss. The right anterior cingulate is the only altered region found altered among c-HR, RDSZ and ChSZ. Contrast analyses show left-lateralized insular, amygdalar and parahippocampal GM reduction in RDSZ, which appears bilateral in ChSZ. Functional decomposition shows involvement of the salience network, with an enlargement of the sensorimotor network in RDSZ and the thalamus-basal nuclei network in ChSZ. These findings support the current neuroprogressive models of SZ and integrate this deterioration with the clinical evolution of the disease.
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Affiliation(s)
- Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Claudio Brasso
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy.
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy.
| | - Lorenzo Mancuso
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Andrea Nani
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy.
| | - Sergio Duca
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Paola Rocca
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy.
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7
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Esménio S, Soares JM, Oliveira-Silva P, Gonçalves ÓF, Friston K, Fernandes Coutinho J. Changes in the Effective Connectivity of the Social Brain When Making Inferences About Close Others vs. the Self. Front Hum Neurosci 2020; 14:151. [PMID: 32410974 PMCID: PMC7202326 DOI: 10.3389/fnhum.2020.00151] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 04/06/2020] [Indexed: 11/16/2022] Open
Abstract
Previous research showed that the ability to make inferences about our own and other’s mental states rely on common brain pathways; particularly in the case of close relationships (e.g., romantic relationships). Despite the evidence for shared neural representations of self and others, less is known about the distributed processing within these common neural networks, particularly whether there are specific patterns of internode communication when focusing on other vs. self. This study aimed to characterize context-sensitive coupling among social brain regions involved in self and other understanding. Participants underwent an fMRI while watching emotional video vignettes of their romantic partner and elaborated on their partner’s (other-condition) or on their own experience (self-condition). We used dynamic causal modeling (DCM) to quantify the associated changes in effective connectivity (EC) in a network of brain regions involved in social cognition including the temporoparietal junction (TPJ), the posterior cingulate (PCC)/precuneus and middle temporal gyrus (MTG). DCM revealed that: the PCC plays a central coordination role within this network, the bilateral MTG receives driving inputs from other nodes suggesting that social information is first processed in language comprehension regions; the right TPJ evidenced a selective increase in its sensitivity when focusing on the other’s experience, relative to focusing on oneself.
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Affiliation(s)
- Sofia Esménio
- Psychological Neuroscience Laboratory, CIPsi, School of Psychology, University of Minho, Campus Gualtar, Braga, Portugal
| | - José Miguel Soares
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, Braga, Portugal.,ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal.,Clinical Academic Center, Braga, Portugal
| | - Patrícia Oliveira-Silva
- Human Neurobehavioral Laboratory, CEDH-Research Centre for Human Development, Faculdade de Educação e Psicologia, Universidade Católica Portuguesa, Porto, Portugal
| | - Óscar F Gonçalves
- Psychological Neuroscience Laboratory, CIPsi, School of Psychology, University of Minho, Campus Gualtar, Braga, Portugal.,Spaulding Center for Neuromodulation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, United States
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Joana Fernandes Coutinho
- Psychological Neuroscience Laboratory, CIPsi, School of Psychology, University of Minho, Campus Gualtar, Braga, Portugal
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8
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Cole DM, Diaconescu AO, Pfeiffer UJ, Brodersen KH, Mathys CD, Julkowski D, Ruhrmann S, Schilbach L, Tittgemeyer M, Vogeley K, Stephan KE. Atypical processing of uncertainty in individuals at risk for psychosis. NEUROIMAGE-CLINICAL 2020; 26:102239. [PMID: 32182575 PMCID: PMC7076146 DOI: 10.1016/j.nicl.2020.102239] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 02/24/2020] [Accepted: 03/06/2020] [Indexed: 12/28/2022]
Abstract
Humans at psychosis clinical high risk (CHR) over-estimate environmental volatility. Low-level prediction error (PE) signals evoke increased frontal activity in CHR. Volatility-related PEs are associated with reduced frontal activity in CHR. Frontal cortical activation to low-level PEs reflects impaired clinical functioning. Atypical PE learning signal representations may promote delusion formation in CHR.
Current theories of psychosis highlight the role of abnormal learning signals, i.e., prediction errors (PEs) and uncertainty, in the formation of delusional beliefs. We employed computational analyses of behaviour and functional magnetic resonance imaging (fMRI) to examine whether such abnormalities are evident in clinical high risk (CHR) individuals. Non-medicated CHR individuals (n = 13) and control participants (n = 13) performed a probabilistic learning paradigm during fMRI data acquisition. We used a hierarchical Bayesian model to infer subject-specific computations from behaviour – with a focus on PEs and uncertainty (or its inverse, precision) at different levels, including environmental ‘volatility’ – and used these computational quantities for analyses of fMRI data. Computational modelling of CHR individuals’ behaviour indicated volatility estimates converged to significantly higher levels than in controls. Model-based fMRI demonstrated increased activity in prefrontal and insular regions of CHR individuals in response to precision-weighted low-level outcome PEs, while activations of prefrontal, orbitofrontal and anterior insula cortex by higher-level PEs (that serve to update volatility estimates) were reduced. Additionally, prefrontal cortical activity in response to outcome PEs in CHR was negatively associated with clinical measures of global functioning. Our results suggest a multi-faceted learning abnormality in CHR individuals under conditions of environmental uncertainty, comprising higher levels of volatility estimates combined with reduced cortical activation, and abnormally high activations in prefrontal and insular areas by precision-weighted outcome PEs. This atypical representation of high- and low-level learning signals might reflect a predisposition to delusion formation.
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Affiliation(s)
- David M Cole
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zurich, Psychiatric Hospital of the University of Zurich, Zurich, Switzerland.
| | - Andreea O Diaconescu
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland; Department of Psychiatry (UPK), University of Basel, Basel, Switzerland; Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), University of Toronto, Toronto, Canada
| | - Ulrich J Pfeiffer
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Kay H Brodersen
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
| | - Christoph D Mathys
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland; Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy; Interacting Minds Centre, Aarhus University, Aarhus, Denmark
| | - Dominika Julkowski
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Stephan Ruhrmann
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Leonhard Schilbach
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany; Graduate School for Systemic Neuroscience, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany; Ludwig-Maximilians-Universität München, Munich, Germany; Kliniken der Heinrich-Heine-Universität/LVR-Klinik Düsseldorf, Düsseldorf, Germany
| | - Marc Tittgemeyer
- Max Planck Institute for Metabolism Research, Cologne, Germany; Cologne Cluster of Excellence in Cellular Stress and Aging associated Disease (CECAD), Germany
| | - Kai Vogeley
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany; Institute for Neuroscience and Medicine - Cognitive Neuroscience (INM3), Research Center Juelich, Juelich, Germany
| | - Klaas E Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland; Max Planck Institute for Metabolism Research, Cologne, Germany; Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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9
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Allen P, Moore H, Corcoran CM, Gilleen J, Kozhuharova P, Reichenberg A, Malaspina D. Emerging Temporal Lobe Dysfunction in People at Clinical High Risk for Psychosis. Front Psychiatry 2019; 10:298. [PMID: 31133894 PMCID: PMC6526750 DOI: 10.3389/fpsyt.2019.00298] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Accepted: 04/16/2019] [Indexed: 12/13/2022] Open
Abstract
Clinical high-risk (CHR) individuals have been increasingly utilized to investigate the prodromal phases of psychosis and progression to illness. Research has identified medial and lateral temporal lobe abnormalities in CHR individuals. Dysfunction in the medial temporal lobe, particularly the hippocampus, is linked to dysregulation of glutamate and dopamine via a hippocampal-striatal-midbrain network that may lead to aberrant signaling of salience underpinning the formation of delusions. Similarly, lateral temporal dysfunction may be linked to the disorganized speech and language impairments observed in the CHR stage. Here, we summarize the significance of these neurobiological findings in terms of emergent psychotic symptoms and conversion to psychosis in CHR populations. We propose key questions for future work with the aim to identify the neural mechanisms that underlie the development of psychosis.
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Affiliation(s)
- Paul Allen
- Department of Psychology, University of Roehampton, London, United Kingdom
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Holly Moore
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY, United States
- New York State Psychiatric Institute, University of Columbia, New York, NY, United States
| | - Cheryl M. Corcoran
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - James Gilleen
- Department of Psychology, University of Roehampton, London, United Kingdom
| | - Petya Kozhuharova
- Department of Psychology, University of Roehampton, London, United Kingdom
| | - Avi Reichenberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Dolores Malaspina
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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10
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Esménio S, Soares JM, Oliveira-Silva P, Zeidman P, Razi A, Gonçalves ÓF, Friston K, Coutinho J. Using resting-state DMN effective connectivity to characterize the neurofunctional architecture of empathy. Sci Rep 2019; 9:2603. [PMID: 30796260 PMCID: PMC6385316 DOI: 10.1038/s41598-019-38801-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 12/18/2018] [Indexed: 12/31/2022] Open
Abstract
Neuroimaging studies in social neuroscience have largely relied on functional connectivity (FC) methods to characterize the functional integration between different brain regions. However, these methods have limited utility in social-cognitive studies that aim to understand the directed information flow among brain areas that underlies complex psychological processes. In this study we combined functional and effective connectivity approaches to characterize the functional integration within the Default Mode Network (DMN) and its role in self-perceived empathy. Forty-two participants underwent a resting state fMRI scan and completed a questionnaire of dyadic empathy. Independent Component Analysis (ICA) showed that higher empathy scores were associated with an increased contribution of the medial prefrontal cortex (mPFC) to the DMN spatial mode. Dynamic causal modelling (DCM) combined with Canonical Variance Analysis (CVA) revealed that this association was mediated indirectly by the posterior cingulate cortex (PCC) via the right inferior parietal lobule (IPL). More specifically, in participants with higher scores in empathy, the PCC had a greater effect on bilateral IPL and the right IPL had a greater influence on mPFC. These results highlight the importance of using analytic approaches that address directed and hierarchical connectivity within networks, when studying complex psychological phenomena, such as empathy.
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Affiliation(s)
- Sofia Esménio
- Neuropsychophysiology Lab, Psychology School, Minho University, Campus Gualtar, Braga, Portugal.
| | - José M Soares
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Campus Gualtar,, Braga, Portugal
- ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães, Portugal
- Clinical Academic Center, Braga, Portugal
| | - P Oliveira-Silva
- Faculty of Education and Psychology, Catholic University of Portugal, Porto, Portugal
| | - Peter Zeidman
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
| | - Adeel Razi
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
| | - Óscar F Gonçalves
- Neuropsychophysiology Lab, Psychology School, Minho University, Campus Gualtar, Braga, Portugal
- Applied Psychology Bouvé College of Health Sciences Northeastern University Harvard Medical School, Boston, USA
| | - Karl Friston
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
| | - Joana Coutinho
- Neuropsychophysiology Lab, Psychology School, Minho University, Campus Gualtar, Braga, Portugal
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11
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Psychotic symptoms influence the development of anterior cingulate BOLD variability in 22q11.2 deletion syndrome. Schizophr Res 2018; 193:319-328. [PMID: 28803847 DOI: 10.1016/j.schres.2017.08.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 08/03/2017] [Accepted: 08/03/2017] [Indexed: 11/23/2022]
Abstract
Chromosome 22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental disorder associated with a broad phenotype of clinical, cognitive and psychiatric features. Due to the very high prevalence of schizophrenia (30-40%), the investigation of psychotic symptoms in the syndrome is promising to reveal biomarkers for the development of psychosis, also in the general population. Since schizophrenia is seen as a disorder of the dynamic interactions between brain networks, we here investigated brain dynamics, assessed by the variability of blood oxygenation level dependent (BOLD) signals, in patients with psychotic symptoms. We included 28 patients with 22q11DS presenting higher positive psychotic symptoms, 29 patients with lower positive psychotic symptoms and 69 healthy controls between 10 and 30years old. To overcome limitations of mass-univariate approaches, we employed multivariate analysis, namely partial least squares correlation, combined with proper statistical testing, to analyze resting-state BOLD signal variability and its age-relationship in patients with positive psychotic symptoms. Our results revealed a missing positive age-relationship in the dorsal anterior cingulate cortex (dACC) in patients with higher positive psychotic symptoms, leading to globally lower variability in the dACC in those patients. Patients without positive psychotic symptoms and healthy controls had the same developmental trajectory in this region. Alterations of brain structure and function in the ACC have been previously reported in 22q11DS and linked to psychotic symptoms. The present results support the implication of this region in the development of psychotic symptoms and suggest aberrant BOLD signal variability development as a potential biomarker for psychosis.
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12
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Dauvermann MR, Moorhead TW, Watson AR, Duff B, Romaniuk L, Hall J, Roberts N, Lee GL, Hughes ZA, Brandon NJ, Whitcher B, Blackwood DH, McIntosh AM, Lawrie SM. Verbal working memory and functional large-scale networks in schizophrenia. Psychiatry Res Neuroimaging 2017; 270:86-96. [PMID: 29111478 DOI: 10.1016/j.pscychresns.2017.10.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2017] [Revised: 09/16/2017] [Accepted: 10/20/2017] [Indexed: 12/17/2022]
Abstract
The aim of this study was to test whether bilinear and nonlinear effective connectivity (EC) measures of working memory fMRI data can differentiate between patients with schizophrenia (SZ) and healthy controls (HC). We applied bilinear and nonlinear Dynamic Causal Modeling (DCM) for the analysis of verbal working memory in 16 SZ and 21 HC. The connection strengths with nonlinear modulation between the dorsolateral prefrontal cortex (DLPFC) and the ventral tegmental area/substantia nigra (VTA/SN) were evaluated. We used Bayesian Model Selection at the group and family levels to compare the optimal bilinear and nonlinear models. Bayesian Model Averaging was used to assess the connection strengths with nonlinear modulation. The DCM analyses revealed that SZ and HC used different bilinear networks despite comparable behavioral performance. In addition, the connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area showed differences between SZ and HC. The adoption of different functional networks in SZ and HC indicated neurobiological alterations underlying working memory performance, including different connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area. These novel findings may increase our understanding of connectivity in working memory in schizophrenia.
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Affiliation(s)
- Maria R Dauvermann
- Division of Psychiatry, Royal Edinburgh Hospital, Morningside Park, University of Edinburgh, Edinburgh EH10 5HF, UK; School of Psychology, National University of Ireland Galway, University Road, Galway, Ireland; McGovern Institute for Brain Research, Massachusetts Institute of Technology, 43 Vassar Street, Cambridge, MA 02139, USA.
| | - Thomas Wj Moorhead
- Division of Psychiatry, Royal Edinburgh Hospital, Morningside Park, University of Edinburgh, Edinburgh EH10 5HF, UK
| | - Andrew R Watson
- Division of Psychiatry, Royal Edinburgh Hospital, Morningside Park, University of Edinburgh, Edinburgh EH10 5HF, UK
| | - Barbara Duff
- Division of Psychiatry, Royal Edinburgh Hospital, Morningside Park, University of Edinburgh, Edinburgh EH10 5HF, UK
| | - Liana Romaniuk
- Division of Psychiatry, Royal Edinburgh Hospital, Morningside Park, University of Edinburgh, Edinburgh EH10 5HF, UK
| | - Jeremy Hall
- Division of Psychiatry, Royal Edinburgh Hospital, Morningside Park, University of Edinburgh, Edinburgh EH10 5HF, UK; Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
| | - Neil Roberts
- Clinical Research Imaging Centre, University of Edinburgh, Edinburgh, UK; British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
| | - Graham L Lee
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, 43 Vassar Street, Cambridge, MA 02139, USA
| | - Zoë A Hughes
- Neuroscience Research Unit, Pfizer Inc., Cambridge, MA, USA
| | - Nicholas J Brandon
- Neuroscience Research Unit, Pfizer Inc., Cambridge, MA, USA; IMED Neuroscience Unit, AstraZeneca, Waltham, MA, USA
| | - Brandon Whitcher
- Clinical and Translational Imaging, Pfizer Inc., Cambridge, MA, USA
| | - Douglas Hr Blackwood
- Division of Psychiatry, Royal Edinburgh Hospital, Morningside Park, University of Edinburgh, Edinburgh EH10 5HF, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, Morningside Park, University of Edinburgh, Edinburgh EH10 5HF, UK
| | - Stephen M Lawrie
- Division of Psychiatry, Royal Edinburgh Hospital, Morningside Park, University of Edinburgh, Edinburgh EH10 5HF, UK
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13
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Ma J, Leung LS. Involvement of posterior cingulate cortex in ketamine-induced psychosis relevant behaviors in rats. Behav Brain Res 2017; 338:17-27. [PMID: 28993219 DOI: 10.1016/j.bbr.2017.09.051] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Revised: 09/26/2017] [Accepted: 09/28/2017] [Indexed: 12/16/2022]
Abstract
The involvement of posterior cingulate cortex (PCC) on ketamine-induced psychosis relevant behaviors was investigated in rats. Bilateral infusion of muscimol, a GABAA receptor agonist, into the PCC significantly antagonized ketamine-induced deficit in prepulse inhibition of a startle reflex (PPI), deficit in gating of hippocampal auditory evoked potentials, and behavioral hyperlocomotion in a dose dependent manner. Local infusion of ketamine directly into the PCC also induced a PPI deficit. Systemic injection of ketamine (3mg/kg,s.c.) induced an increase in power of electrographic activity in the gamma band (30-100Hz) in both the PCC and the hippocampus; peak theta (4-10Hz) power was not significantly altered, but peak theta frequency was increased by ketamine. In order to exclude volume conduction from the hippocampus to PCC, inactivation of the hippocampus was made by local infusion of muscimol into the hippocampus prior to ketamine administration. Muscimol in the hippocampus effectively blocked ketamine-induced increase of gamma power in the hippocampus but not in the PCC, suggesting independent generation of gamma waves in PCC and hippocampus. It is suggested that the PCC is part of the brain network mediating ketamine-induced psychosis related behaviors.
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Affiliation(s)
- Jingyi Ma
- Department of Physiology and Pharmacology, The University of Western Ontario, London N6A 5C1, Canada.
| | - L Stan Leung
- Department of Physiology and Pharmacology, The University of Western Ontario, London N6A 5C1, Canada; Graduate Program in Neuroscience, The University of Western Ontario, London N6A 5C1, Canada
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Friston K, Brown HR, Siemerkus J, Stephan KE. The dysconnection hypothesis (2016). Schizophr Res 2016; 176:83-94. [PMID: 27450778 PMCID: PMC5147460 DOI: 10.1016/j.schres.2016.07.014] [Citation(s) in RCA: 358] [Impact Index Per Article: 44.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Revised: 07/06/2016] [Accepted: 07/15/2016] [Indexed: 02/06/2023]
Abstract
Twenty years have passed since the dysconnection hypothesis was first proposed (Friston and Frith, 1995; Weinberger, 1993). In that time, neuroscience has witnessed tremendous advances: we now live in a world of non-invasive neuroanatomy, computational neuroimaging and the Bayesian brain. The genomics era has come and gone. Connectomics and large-scale neuroinformatics initiatives are emerging everywhere. So where is the dysconnection hypothesis now? This article considers how the notion of schizophrenia as a dysconnection syndrome has developed - and how it has been enriched by recent advances in clinical neuroscience. In particular, we examine the dysconnection hypothesis in the context of (i) theoretical neurobiology and computational psychiatry; (ii) the empirical insights afforded by neuroimaging and associated connectomics - and (iii) how bottom-up (molecular biology and genetics) and top-down (systems biology) perspectives are converging on the mechanisms and nature of dysconnections in schizophrenia.
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Affiliation(s)
- Karl Friston
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, UK.
| | - Harriet R. Brown
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, UK,Oxford Centre for Human Brain Activity, University of Oxford, UK
| | - Jakob Siemerkus
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland,Department of Psychiatry, Psychotherapy and Psychosomatics, Zurich, Switzerland
| | - Klaas E. Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland
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15
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Chen JE, Glover GH. Functional Magnetic Resonance Imaging Methods. Neuropsychol Rev 2015; 25:289-313. [PMID: 26248581 PMCID: PMC4565730 DOI: 10.1007/s11065-015-9294-9] [Citation(s) in RCA: 88] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2015] [Accepted: 07/28/2015] [Indexed: 12/11/2022]
Abstract
Since its inception in 1992, Functional Magnetic Resonance Imaging (fMRI) has become an indispensible tool for studying cognition in both the healthy and dysfunctional brain. FMRI monitors changes in the oxygenation of brain tissue resulting from altered metabolism consequent to a task-based evoked neural response or from spontaneous fluctuations in neural activity in the absence of conscious mentation (the "resting state"). Task-based studies have revealed neural correlates of a large number of important cognitive processes, while fMRI studies performed in the resting state have demonstrated brain-wide networks that result from brain regions with synchronized, apparently spontaneous activity. In this article, we review the methods used to acquire and analyze fMRI signals.
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Affiliation(s)
- Jingyuan E Chen
- Department of Radiology, Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA,
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16
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Fonville L, Cohen Kadosh K, Drakesmith M, Dutt A, Zammit S, Mollon J, Reichenberg A, Lewis G, Jones DK, David AS. Psychotic Experiences, Working Memory, and the Developing Brain: A Multimodal Neuroimaging Study. Cereb Cortex 2015; 25:4828-38. [PMID: 26286920 PMCID: PMC4635922 DOI: 10.1093/cercor/bhv181] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Psychotic experiences (PEs) occur in the general population, especially in children and adolescents, and are associated with poor psychosocial outcomes, impaired cognition, and increased risk of transition to psychosis. It is unknown how the presence and persistence of PEs during early adulthood affects cognition and brain function. The current study assessed working memory as well as brain function and structure in 149 individuals, with and without PEs, drawn from a population cohort. Observer-rated PEs were classified as persistent or transient on the basis of longitudinal assessments. Working memory was assessed using the n-back task during fMRI. Dynamic causal modeling (DCM) was used to characterize frontoparietal network configuration and voxel-based morphometry was utilized to examine gray matter. Those with persistent, but not transient, PEs performed worse on the n-back task, compared with controls, yet showed no significant differences in regional brain activation or brain structure. DCM analyses revealed greater emphasis on frontal connectivity within a frontoparietal network in those with PEs compared with controls. We propose that these findings portray an altered configuration of working memory function in the brain, potentially indicative of an adaptive response to atypical development associated with the manifestation of PEs.
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Affiliation(s)
- Leon Fonville
- Section of Cognitive Neuropsychiatry, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | | | - Mark Drakesmith
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology Institute of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Anirban Dutt
- Section of Cognitive Neuropsychiatry, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Stanley Zammit
- Institute of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK Centre for Academic Mental Health, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Josephine Mollon
- Section of Cognitive Neuropsychiatry, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Abraham Reichenberg
- Section of Cognitive Neuropsychiatry, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK Department of Psychiatry, Icahn School of Medicine, Mount Sinai Hospital, New York, NY, USA
| | - Glyn Lewis
- Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology Institute of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Anthony S David
- Section of Cognitive Neuropsychiatry, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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17
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Yoon YB, Yun JY, Jung WH, Cho KIK, Kim SN, Lee TY, Park HY, Kwon JS. Altered Fronto-Temporal Functional Connectivity in Individuals at Ultra-High-Risk of Developing Psychosis. PLoS One 2015; 10:e0135347. [PMID: 26267069 PMCID: PMC4534425 DOI: 10.1371/journal.pone.0135347] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2015] [Accepted: 07/21/2015] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The superior temporal gyrus (STG) is one of the key regions implicated in psychosis, given that abnormalities in this region are associated with an increased risk of conversion from an at-risk mental state to psychosis. However, inconsistent results regarding the functional connectivity strength of the STG have been reported, and the regional heterogeneous characteristics of the STG should be considered. METHODS To investigate the distinctive functional connection of each subregion in the STG, we parcellated the STG of each hemisphere into three regions: the planum temporale, Heschl's gyrus, and planum polare. Resting-state functional magnetic resonance imaging was obtained from 22 first-episode psychosis (FEP) patients, 41 individuals at ultra-high-risk for psychosis (UHR), and 47 demographically matched healthy controls. RESULTS Significant group differences (in seed-based connectivity) were demonstrated in the left planum temporale and from both the right and left Heschl's gyrus seeds. From the left planum temporale seed, the FEP and UHR groups exhibited increased connectivity to the bilateral dorsolateral prefrontal cortex. In contrast, the FEP and UHR groups demonstrated decreased connectivity from the bilateral Heschl's gyrus seeds to the dorsal anterior cingulate cortex. The enhanced connectivity between the left planum temporale and right dorsolateral prefrontal cortex was positively correlated with positive symptom severity in individuals at UHR (r = .34, p = .03). CONCLUSIONS These findings corroborate the fronto-temporal connectivity disruption hypothesis in schizophrenia by providing evidence supporting the altered fronto-temporal intrinsic functional connection at earlier stages of psychosis. Our data indicate that subregion-specific aberrant fronto-temporal interactions exist in the STG at the early stage of psychosis, thus suggesting that these aberrancies are the neural underpinning of proneness to psychosis.
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Affiliation(s)
- Youngwoo Bryan Yoon
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Je-Yeon Yun
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Wi Hoon Jung
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Institute of Human Behavioral Medicine, Seoul National University-Medical Research Center, Seoul, Republic of Korea
| | - Kang Ik K. Cho
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Sung Nyun Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Tae Young Lee
- Institute of Human Behavioral Medicine, Seoul National University-Medical Research Center, Seoul, Republic of Korea
| | - Hye Yoon Park
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Institute of Human Behavioral Medicine, Seoul National University-Medical Research Center, Seoul, Republic of Korea
- * E-mail:
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18
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Pettersson-Yeo W, Benetti S, Frisciata S, Catani M, Williams SC, Allen P, McGuire P, Mechelli A. Does neuroanatomy account for superior temporal dysfunction in early psychosis? A multimodal MRI investigation. J Psychiatry Neurosci 2015; 40:100-7. [PMID: 25338016 PMCID: PMC4354815 DOI: 10.1503/jpn.140082] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Neuroimaging studies of ultra-high risk (UHR) and first-episode psychosis (FEP) have revealed widespread alterations in brain structure and function. Recent evidence suggests there is an intrinsic relationship between these 2 types of alterations; however, there is very little research linking these 2 modalities in the early stages of psychosis. METHODS To test the hypothesis that functional alteration in UHR and FEP articipants would be associated with corresponding structural alteration, we examined brain function and structure in these participants as well as in a group of healthy controls using multimodal MRI. The data were analyzed using statistical parametric mapping. RESULTS We included 24 participants in the FEP group, 18 in the UHR group and 21 in the control group. Patients in the FEP group showed a reduction in functional activation in the left superior temporal gyrus relative to controls, and the UHR group showed intermediate values. The same region showed a corresponding reduction in grey matter volume in the FEP group relative to controls. However, while the difference in grey matter volume remained significant after including functional activation as a covariate of no interest, the reduction in functional activation was no longer evident after including grey matter volume as a covariate of no interest. LIMITATIONS Our sample size was relatively small. All participants in the FEP group and 2 in the UHR group had received antipsychotic medication, which may have impacted neurofunction and/or neuroanatomy. CONCLUSION Our results suggest that superior temporal dysfunction in early psychosis is accounted for by a corresponding alteration in grey matter volume. This finding has important implications for the interpretation of functional alteration in early psychosis.
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Affiliation(s)
- William Pettersson-Yeo
- Correspondence to: W. Pettersson-Yeo, Department of Psychosis Studies, PO Box 67, Institute of Psychiatry, King’s College London, De Crespigny Park, London UK SE5 8AF;
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19
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Dutt A, Tseng HH, Fonville L, Drakesmith M, Su L, Evans J, Zammit S, Jones D, Lewis G, David AS. Exploring neural dysfunction in 'clinical high risk' for psychosis: a quantitative review of fMRI studies. J Psychiatr Res 2015; 61:122-34. [PMID: 25479766 DOI: 10.1016/j.jpsychires.2014.08.018] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2014] [Revised: 08/06/2014] [Accepted: 08/26/2014] [Indexed: 01/10/2023]
Abstract
Individuals at clinical high risk (CHR) of developing psychosis present with widespread functional abnormalities in the brain. Cognitive deficits, including working memory (WM) problems, as commonly elicited by n-back tasks, are observed in CHR individuals. However, functional MRI (fMRI) studies, comprising a heterogeneous cluster of general and social cognition paradigms, have not necessarily demonstrated consistent and conclusive results in this population. Hence, a comprehensive review of fMRI studies, spanning almost one decade, was carried out to observe for general trends with respect to brain regions and cognitive systems most likely to be dysfunctional in CHR individuals. 32 studies were included for this review, out of which 22 met the criteria for quantitative analysis using activation likelihood estimation (ALE). Task related contrast activations were firstly analysed by comparing CHR and healthy control participants in the total pooled sample, followed by a comparison of general cognitive function studies (excluding social cognition paradigms), and finally by only looking at n-back working memory task based studies. Findings from the ALE implicated four key dysfunctional and distinct neural regions in the CHR group, namely the right inferior parietal lobule (rIPL), the left medial frontal gyrus (lmFG), the left superior temporal gyrus (lSTG) and the right fronto-polar cortex (rFPC) of the superior frontal gyrus (SFG). Narrowing down to relatively few significant dysfunctional neural regions is a step forward in reducing the apparent ambiguity of overall findings, which would help to target specific neural regions and pathways of interest for future research in CHR populations.
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Affiliation(s)
- Anirban Dutt
- Institute of Psychiatry, King's College London, London, UK.
| | | | - Leon Fonville
- Institute of Psychiatry, King's College London, London, UK
| | - Mark Drakesmith
- Cardiff University Brain Research Imaging Centre, Cardiff, UK
| | - Liang Su
- Institute of Psychiatry, King's College London, London, UK
| | - John Evans
- Cardiff University Brain Research Imaging Centre, Cardiff, UK
| | - Stanley Zammit
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Derek Jones
- Cardiff University Brain Research Imaging Centre, Cardiff, UK
| | - Glyn Lewis
- Division of Psychiatry, University College London, London, UK
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20
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Andreou C, Leicht G, Nolte G, Polomac N, Moritz S, Karow A, Hanganu-Opatz IL, Engel AK, Mulert C. Resting-state theta-band connectivity and verbal memory in schizophrenia and in the high-risk state. Schizophr Res 2015; 161:299-307. [PMID: 25553979 DOI: 10.1016/j.schres.2014.12.018] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2014] [Revised: 12/08/2014] [Accepted: 12/10/2014] [Indexed: 10/24/2022]
Abstract
BACKGROUND Disturbed functional connectivity is assumed to underlie neurocognitive deficits in patients with schizophrenia. As neurocognitive deficits are already present in the high-risk state, identification of the neural networks involved in this core feature of schizophrenia is essential to our understanding of the disorder. Resting-state studies enable such investigations, while at the same time avoiding the known confounder of impaired task performance in patients. The aim of the present study was to investigate EEG resting-state connectivity in high-risk individuals (HR) compared to first episode patients with schizophrenia (SZ) and to healthy controls (HC), and its association with cognitive deficits. METHODS 64-channel resting-state EEG recordings (eyes closed) were obtained for 28 HR, 19 stable SZ, and 23 HC, matched for age, education, and parental education. The imaginary coherence-based multivariate interaction measure (MIM) was used as a measure of connectivity across 80 cortical regions and six frequency bands. Mean connectivity at each region was compared across groups using the non-parametric randomization approach. Additionally, the network-based statistic was applied to identify affected networks in patients. RESULTS SZ displayed increased theta-band resting-state MIM connectivity across midline, sensorimotor, orbitofrontal regions and the left temporoparietal junction. HR displayed intermediate theta-band connectivity patterns that did not differ from either SZ or HC. Mean theta-band connectivity within the above network partially mediated verbal memory deficits in SZ and HR. CONCLUSIONS Aberrant theta-band connectivity may represent a trait characteristic of schizophrenia associated with neurocognitive deficits. As such, it might constitute a promising target for novel treatment applications.
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Affiliation(s)
- Christina Andreou
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
| | - Gregor Leicht
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Guido Nolte
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Nenad Polomac
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Steffen Moritz
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Anne Karow
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ileana L Hanganu-Opatz
- Developmental Neurophysiology, Institute of Neuroanatomy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Andreas K Engel
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christoph Mulert
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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21
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Benetti S, Pettersson-Yeo W, Allen P, Catani M, Williams S, Barsaglini A, Kambeitz-Ilankovic LM, McGuire P, Mechelli A. Auditory verbal hallucinations and brain dysconnectivity in the perisylvian language network: a multimodal investigation. Schizophr Bull 2015; 41:192-200. [PMID: 24361862 PMCID: PMC4266279 DOI: 10.1093/schbul/sbt172] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Neuroimaging studies of schizophrenia have indicated that the development of auditory verbal hallucinations (AVHs) is associated with altered structural and functional connectivity within the perisylvian language network. However, these studies focussed mainly on either structural or functional alterations in patients with chronic schizophrenia. Therefore, they were unable to examine the relationship between the 2 types of measures and could not establish whether the observed alterations would be expressed in the early stage of the illness. We used diffusion tensor imaging and functional magnetic resonance imaging to examine white matter integrity and functional connectivity within the left perisylvian language network of 46 individuals with an at risk mental state for psychosis or a first episode of the illness, including 28 who had developed AVH group and 18 who had not (nonauditory verbal hallucination [nAVH] group), and 22 healthy controls. Inferences were made at P < .05 (corrected). The nAVH group relative to healthy controls showed a reduction of both white matter integrity and functional connectivity as well as a disruption of the normal structure-function relationship along the fronto-temporal pathway. For all measures, the AVH group showed intermediate values between healthy controls and the nAVH group. These findings seem to suggest that, in the early stage of the disorder, a significant impairment of fronto-temporal connectivity is evident in patients who do not experience AVHs. This is consistent with the hypothesis that, whilst mild disruption of connectivity might still enable the emergence of AVHs, more severe alterations may prevent the occurrence of the hallucinatory experience.
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Affiliation(s)
- Stefania Benetti
- Department of Psychosis Studies, King's College Health Partners, King's College London, London, UK; Centre for Mind/Brain Sciences, University of Trento, Trento, Italy;
| | - William Pettersson-Yeo
- Department of Psychosis Studies, King’s College Health Partners, King’s College London, London, UK
| | - Paul Allen
- Department of Psychosis Studies, King’s College Health Partners, King’s College London, London, UK
| | - Marco Catani
- Department of Forensic and Neurodevelopmental Science, King’s College Health Partners, King’s College London, London, UK
| | - Steven Williams
- Department of Neuroimaging, King’s College Health Partners, King’s College London, London, UK
| | - Alessio Barsaglini
- Department of General Psychology, Università degli Studi di Padova, Padova, Italy
| | - Lana M. Kambeitz-Ilankovic
- Department of Psychosis Studies, King’s College Health Partners, King’s College London, London, UK;,Department of Psychiatry, Ludwig-Maximilians University, Munich, Germany
| | - Philip McGuire
- Department of Psychosis Studies, King’s College Health Partners, King’s College London, London, UK
| | - Andrea Mechelli
- Department of Psychosis Studies, King's College Health Partners, King's College London, London, UK;
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Scariati E, Schaer M, Richiardi J, Schneider M, Debbané M, Van De Ville D, Eliez S. Identifying 22q11.2 Deletion Syndrome and Psychosis Using Resting-State Connectivity Patterns. Brain Topogr 2014; 27:808-21. [DOI: 10.1007/s10548-014-0356-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 02/12/2014] [Indexed: 11/30/2022]
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Andreou C, Faber PL, Leicht G, Schoettle D, Polomac N, Hanganu-Opatz IL, Lehmann D, Mulert C. Resting-state connectivity in the prodromal phase of schizophrenia: insights from EEG microstates. Schizophr Res 2014; 152:513-20. [PMID: 24389056 DOI: 10.1016/j.schres.2013.12.008] [Citation(s) in RCA: 88] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2013] [Revised: 11/22/2013] [Accepted: 12/10/2013] [Indexed: 11/17/2022]
Abstract
INTRODUCTION Resting-state EEG microstates are thought to reflect the momentary local states and interactions of distributed neural networks in the brain. Several changes in resting-state EEG microstates have been described in acutely ill patients with schizophrenia, but it is not known whether these represent trait or state abnormalities. The present study aimed to investigate this issue by assessing EEG microstate characteristics in high-risk individuals (HR) and clinically stable first-episode patients with schizophrenia (SZ) with low symptom levels, compared to each other and healthy controls (HC). METHOD Participants were 18 HR, 18 SZ, and 22 HC subjects. 64-channel resting-state EEG recordings were used for microstate analyses. Microstates were clustered into four classes (A-D) according to their topography. Temporal parameters and topographies of microstates were compared among groups. RESULTS Microstate class A displayed higher coverage and occurrence in HR than SZ and HC, while microstate class B covered significantly more time in SZ compared to both HR and HC. Microstate class B displayed an aberrant spatial configuration in SZ, and to a lesser extent also in HR, compared to HC, with patients exhibiting significantly higher activity in the vicinity of the left posterior cingulate. DISCUSSION Microstate abnormalities observed in HR were similar to those previously reported in acutely ill patients with schizophrenia. Moreover, there was evidence that HR and SZ might share specific disturbances in brain functional connectivity. These findings raise the possibility that certain abnormalities in resting-state EEG microstates might be associated with an increased risk for psychosis.
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Affiliation(s)
- Christina Andreou
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany.
| | - Pascal L Faber
- The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, CH-8032 Zurich, Switzerland
| | - Gregor Leicht
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany
| | - Daniel Schoettle
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany
| | - Nenad Polomac
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany
| | - Ileana L Hanganu-Opatz
- Developmental Neurophysiology, Center for Molecular Neurobiology, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany
| | - Dietrich Lehmann
- The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, CH-8032 Zurich, Switzerland
| | - Christoph Mulert
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany
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Smieskova R, Marmy J, Schmidt A, Bendfeldt K, Riecher-Rӧssler A, Walter M, Lang UE, Borgwardt S. Do subjects at clinical high risk for psychosis differ from those with a genetic high risk?--A systematic review of structural and functional brain abnormalities. Curr Med Chem 2014; 20:467-81. [PMID: 23157639 PMCID: PMC3580804 DOI: 10.2174/0929867311320030018] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2012] [Revised: 10/25/2012] [Accepted: 10/30/2012] [Indexed: 11/22/2022]
Abstract
Introduction: Pre-psychotic and early psychotic characteristics are investigated in the high-risk (HR) populations for psychosis. There are two different approaches based either on hereditary factors (genetic high risk, G-HR) or on the clinically manifested symptoms (clinical high risk, C-HR). Common features are an increased risk for development of psychosis and similar cognitive as well as structural and functional brain abnormalities. Methods: We reviewed the existing literature on longitudinal structural, and on functional imaging studies, which included G-HR and/or C-HR individuals for psychosis, healthy controls (HC) and/or first episode of psychosis (FEP) or schizophrenia patients (SCZ). Results: With respect to structural brain abnormalities, vulnerability to psychosis was associated with deficits in frontal, temporal, and cingulate regions in HR, with additional insular and caudate deficits in C-HR population. Furthermore, C-HR had progressive prefrontal deficits related to the transition to psychosis. With respect to functional brain abnormalities, vulnerability to psychosis was associated with prefrontal, cingulate and middle temporal abnormalities in HR, with additional parietal, superior temporal, and insular abnormalities in C-HR population. Transition-to-psychosis related differences emphasized prefrontal, hippocampal and striatal components, more often detectable in C-HR population. Multimodal studies directly associated psychotic symptoms displayed in altered prefrontal and hippocampal activations with striatal dopamine and thalamic glutamate functions. Conclusion: There is an evidence for similar structural and functional brain abnormalities within the whole HR population, with more pronounced deficits in the C-HR population. The most consistent evidence for abnormality in the prefrontal cortex reported in structural, functional and multimodal studies of HR population may underlie the complexity of higher cognitive functions that are impaired during HR mental state for psychosis.
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Affiliation(s)
- R Smieskova
- Department of Psychiatry, University of Basel, c/o University Hospital Basel, Petersgraben 4, Basel 4031, Switzerland.
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25
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Diwadkar VA, Bakshi N, Gupta G, Pruitt P, White R, Eickhoff SB. Dysfunction and Dysconnection in Cortical-Striatal Networks during Sustained Attention: Genetic Risk for Schizophrenia or Bipolar Disorder and its Impact on Brain Network Function. Front Psychiatry 2014; 5:50. [PMID: 24847286 PMCID: PMC4023040 DOI: 10.3389/fpsyt.2014.00050] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2013] [Accepted: 04/28/2014] [Indexed: 01/08/2023] Open
Abstract
Abnormalities in the brain's attention network may represent early identifiable neurobiological impairments in individuals at increased risk for schizophrenia or bipolar disorder. Here, we provide evidence of dysfunctional regional and network function in adolescents at higher genetic risk for schizophrenia or bipolar disorder [henceforth higher risk (HGR)]. During fMRI, participants engaged in a sustained attention task with variable demands. The task alternated between attention (120 s), visual control (passive viewing; 120 s), and rest (20 s) epochs. Low and high demand attention conditions were created using the rapid presentation of two- or three-digit numbers. Subjects were required to detect repeated presentation of numbers. We demonstrate that the recruitment of cortical and striatal regions are disordered in HGR: relative to typical controls (TC), HGR showed lower recruitment of the dorsal prefrontal cortex, but higher recruitment of the superior parietal cortex. This imbalance was more dramatic in the basal ganglia. There, a group by task demand interaction was observed, such that increased attention demand led to increased engagement in TC, but disengagement in HGR. These activation studies were complemented by network analyses using dynamic causal modeling. Competing model architectures were assessed across a network of cortical-striatal regions, distinguished at a second level using random-effects Bayesian model selection. In the winning architecture, HGR were characterized by significant reductions in coupling across both frontal-striatal and frontal-parietal pathways. The effective connectivity analyses indicate emergent network dysconnection, consistent with findings in patients with schizophrenia. Emergent patterns of regional dysfunction and dysconnection in cortical-striatal pathways may provide functional biological signatures in the adolescent risk-state for psychiatric illness.
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Affiliation(s)
- Vaibhav A Diwadkar
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University , Detroit, MI , USA
| | - Neil Bakshi
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University , Detroit, MI , USA
| | - Gita Gupta
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University , Detroit, MI , USA
| | - Patrick Pruitt
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University , Detroit, MI , USA
| | - Richard White
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University , Detroit, MI , USA
| | - Simon B Eickhoff
- Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine University Düsseldorf , Düsseldorf , Germany ; Institute of Neuroscience and Medicine (INM-1), Research Center Jülich , Jülich , Germany
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26
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Dauvermann MR, Whalley HC, Schmidt A, Lee GL, Romaniuk L, Roberts N, Johnstone EC, Lawrie SM, Moorhead TWJ. Computational neuropsychiatry - schizophrenia as a cognitive brain network disorder. Front Psychiatry 2014; 5:30. [PMID: 24723894 PMCID: PMC3971172 DOI: 10.3389/fpsyt.2014.00030] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2013] [Accepted: 03/10/2014] [Indexed: 11/13/2022] Open
Abstract
Computational modeling of functional brain networks in fMRI data has advanced the understanding of higher cognitive function. It is hypothesized that functional networks mediating higher cognitive processes are disrupted in people with schizophrenia. In this article, we review studies that applied measures of functional and effective connectivity to fMRI data during cognitive tasks, in particular working memory fMRI studies. We provide a conceptual summary of the main findings in fMRI data and their relationship with neurotransmitter systems, which are known to be altered in individuals with schizophrenia. We consider possible developments in computational neuropsychiatry, which are likely to further our understanding of how key functional networks are altered in schizophrenia.
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Affiliation(s)
- Maria R Dauvermann
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh , Edinburgh , UK
| | - Heather C Whalley
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh , Edinburgh , UK
| | - André Schmidt
- Department of Psychiatry, University of Basel , Basel , Switzerland ; Medical Image Analysis Center, University Hospital Basel , Basel , Switzerland
| | - Graham L Lee
- McGovern Institute for Brain Research, Massachusetts Institute of Technology , Cambridge, MA , USA
| | - Liana Romaniuk
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh , Edinburgh , UK
| | - Neil Roberts
- Clinical Research Imaging Centre, QMRI, University of Edinburgh , Edinburgh , UK
| | - Eve C Johnstone
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh , Edinburgh , UK
| | - Stephen M Lawrie
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh , Edinburgh , UK
| | - Thomas W J Moorhead
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh , Edinburgh , UK
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27
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Roiser JP, Wigton R, Kilner JM, Mendez MA, Hon N, Friston KJ, Joyce EM. Dysconnectivity in the frontoparietal attention network in schizophrenia. Front Psychiatry 2013; 4:176. [PMID: 24399975 PMCID: PMC3871715 DOI: 10.3389/fpsyt.2013.00176] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2013] [Accepted: 12/09/2013] [Indexed: 11/13/2022] Open
Abstract
Cognitive impairment is common in patients with schizophrenia, and even those with relatively preserved function perform worse than healthy volunteers (HVs) on attentional tasks. This is consistent with the hypothesis that connectivity - in the frontoparietal network (FPN) activated during attention - is disrupted in schizophrenia. We examined attentional effects on connectivity in the FPN, in schizophrenia, using magnetoencephalography (MEG). Twenty-three HVs and 19 first-episode schizophrenia patients were scanned during a simple visual change test, known to activate the FPN, in which attention was monitored and directed with an orthogonal flicker-detection task. Dynamic causal modeling (DCM) of evoked responses was used to assess effective connectivity - and its modulation by changes in the attended stimulus dimension - in the following network: higher visual area; temporoparietal junction (TPJ); intraparietal sulcus (IPS); dorsal anterior cingulate cortex; and ventrolateral prefrontal cortex. The final MEG analysis included 18 HVs and 14 schizophrenia patients. While all participants were able to maintain attention, HVs responded slightly, but non-significantly, more accurately than schizophrenia patients. HVs, but not schizophrenia patients, exhibited greater cortical responses to attended visual changes. Bayesian model comparison revealed that a DCM with attention dependent changes in both top-down and bottom-up connections best explained responses by patients with schizophrenia, while in HVs the best model required only bottom-up changes. Quantitative comparison of connectivity estimates revealed a significant group difference in changes in the right IPS-TPJ connection: schizophrenia patients showed relative reductions in connectivity during attended stimulus changes. Crucially, this reduction predicted lower intelligence. These data are consistent with the hypothesis that functional dysconnections in the FPN contribute to cognitive impairment in schizophrenia.
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Affiliation(s)
- Jonathan P. Roiser
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Rebekah Wigton
- Psychosis Studies, Cognition and Schizophrenia Imaging Lab, Institute of Psychiatry, King’s College London, London, UK
| | - James M. Kilner
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
- Institute of Neurology, University College London, London, UK
| | - Maria A. Mendez
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, King’s College London, London, UK
| | - Nicholas Hon
- Department of Psychology, National University of Singapore, Singapore
| | - Karl J. Friston
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
| | - Eileen M. Joyce
- Institute of Neurology, University College London, London, UK
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28
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Pettersson-Yeo W, Benetti S, Marquand AF, Dell‘Acqua F, Williams SCR, Allen P, Prata D, McGuire P, Mechelli A. Using genetic, cognitive and multi-modal neuroimaging data to identify ultra-high-risk and first-episode psychosis at the individual level. Psychol Med 2013; 43:2547-62. [PMID: 23507081 PMCID: PMC3821374 DOI: 10.1017/s003329171300024x] [Citation(s) in RCA: 85] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2012] [Revised: 01/15/2013] [Accepted: 01/16/2013] [Indexed: 11/07/2022]
Abstract
BACKGROUND Group-level results suggest that relative to healthy controls (HCs), ultra-high-risk (UHR) and first-episode psychosis (FEP) subjects show alterations in neuroanatomy, neurofunction and cognition that may be mediated genetically. It is unclear, however, whether these groups can be differentiated at single-subject level, for instance using the machine learning analysis support vector machine (SVM). Here, we used a multimodal approach to examine the ability of structural magnetic resonance imaging (sMRI), functional MRI (fMRI), diffusion tensor neuroimaging (DTI), genetic and cognitive data to differentiate between UHR, FEP and HC subjects at the single-subject level using SVM. METHOD Three age- and gender-matched SVM paired comparison groups were created comprising 19, 19 and 15 subject pairs for FEP versus HC, UHR versus HC and FEP versus UHR, respectively. Genetic, sMRI, DTI, fMRI and cognitive data were obtained for each participant and the ability of each to discriminate subjects at the individual level in conjunction with SVM was tested. RESULTS Successful classification accuracies (p < 0.05) comprised FEP versus HC (genotype, 67.86%; DTI, 65.79%; fMRI, 65.79% and 68.42%; cognitive data, 73.69%), UHR versus HC (sMRI, 68.42%; DTI, 65.79%), and FEP versus UHR (sMRI, 76.67%; fMRI, 73.33%; cognitive data, 66.67%). CONCLUSIONS The results suggest that FEP subjects are identifiable at the individual level using a range of biological and cognitive measures. Comparatively, only sMRI and DTI allowed discrimination of UHR from HC subjects. For the first time FEP and UHR subjects have been shown to be directly differentiable at the single-subject level using cognitive, sMRI and fMRI data. Preliminarily, the results support clinical development of SVM to help inform identification of FEP and UHR subjects, though future work is needed to provide enhanced levels of accuracy.
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Affiliation(s)
- W. Pettersson-Yeo
- Department of Psychosis Studies, King's College London, Institute of Psychiatry, De Crespigny Park, London, UK
| | - S. Benetti
- Department of Psychosis Studies, King's College London, Institute of Psychiatry, De Crespigny Park, London, UK
| | - A. F. Marquand
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, De Crespigny Park, London, UK
| | - F. Dell‘Acqua
- Department of Forensic and Neurodevelopmental Science, King's College London, Institute of Psychiatry, De Crespigny Park, London, UK
- NIHR Biomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust and Institute of Psychiatry, King's College London, London, UK
| | - S. C. R. Williams
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, De Crespigny Park, London, UK
| | - P. Allen
- Department of Psychosis Studies, King's College London, Institute of Psychiatry, De Crespigny Park, London, UK
| | - D. Prata
- Department of Psychosis Studies, King's College London, Institute of Psychiatry, De Crespigny Park, London, UK
| | - P. McGuire
- Department of Psychosis Studies, King's College London, Institute of Psychiatry, De Crespigny Park, London, UK
| | - A. Mechelli
- Department of Psychosis Studies, King's College London, Institute of Psychiatry, De Crespigny Park, London, UK
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The application of nonlinear Dynamic Causal Modelling for fMRI in subjects at high genetic risk of schizophrenia. Neuroimage 2013; 73:16-29. [PMID: 23384525 DOI: 10.1016/j.neuroimage.2013.01.063] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2012] [Revised: 01/17/2013] [Accepted: 01/22/2013] [Indexed: 01/22/2023] Open
Abstract
Nonlinear Dynamic Causal Modelling (DCM) for fMRI provides computational modelling of gating mechanisms at the neuronal population level. It allows for estimations of connection strengths with nonlinear modulation within task-dependent networks. This paper presents an application of nonlinear DCM in subjects at high familial risk of schizophrenia performing the Hayling Sentence Completion Task (HSCT). We analysed scans of 19 healthy controls and 46 subjects at high familial risk of schizophrenia, which included 26 high risk subjects without psychotic symptoms and 20 subjects with psychotic symptoms. The activity-dependent network consists of the intra parietal cortex (IPS), inferior frontal gyrus (IFG), middle temporal gyrus (MTG), anterior cingulate cortex (ACC) and the mediodorsal (MD) thalamus. The connections between the MD thalamus and the IFG were gated by the MD thalamus. We used DCM to investigate altered connection strength of these connections. Bayesian Model Selection (BMS) at the group and family level was used to compare the optimal bilinear and nonlinear models. Bayesian Model Averaging (BMA) was used to assess the connection strengths with the gating from the MD thalamus and the IFG. The nonlinear models provided the better explanation of the data. Furthermore, the BMA analysis showed significantly lower connection strength of the thalamocortical connection with nonlinear modulation from the MD thalamus in high risk subjects with psychotic symptoms and those who subsequently developed schizophrenia. These findings demonstrate that nonlinear DCM provides a method to investigate altered connectivity at the level of neural circuits. The reduced connection strength with thalamic gating may be a neurobiomarker implicated in the development of psychotic symptoms. This study suggests that nonlinear DCM could lead to new insights into functional and effective dysconnection at the network level in subjects at high familial risk.
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Samartzis L, Dima D, Fusar-Poli P, Kyriakopoulos M. White Matter Alterations in Early Stages of Schizophrenia: A Systematic Review of Diffusion Tensor Imaging Studies. J Neuroimaging 2013; 24:101-10. [DOI: 10.1111/j.1552-6569.2012.00779.x] [Citation(s) in RCA: 172] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2012] [Revised: 09/18/2012] [Accepted: 10/06/2012] [Indexed: 12/15/2022] Open
Affiliation(s)
- Lampros Samartzis
- Department of Psychosis Studies; Institute of Psychiatry; King's Health Partners, King's College London; London UK
- Athalassa Psychiatric Hospital; Cyprus Mental Health Services; Nicosia Cyprus
| | - Danai Dima
- Department of Psychosis Studies; Institute of Psychiatry; King's Health Partners, King's College London; London UK
| | - Paolo Fusar-Poli
- Department of Psychosis Studies; Institute of Psychiatry; King's Health Partners, King's College London; London UK
| | - Marinos Kyriakopoulos
- Department of Psychosis Studies; Institute of Psychiatry; King's Health Partners, King's College London; London UK
- National and Specialist Children's Inpatient Unit; South London and Maudsley NHS Foundation Trust; London UK
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31
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Bodatsch M, Klosterkötter J, Müller R, Ruhrmann S. Basic disturbances of information processing in psychosis prediction. Front Psychiatry 2013; 4:93. [PMID: 23986723 PMCID: PMC3750943 DOI: 10.3389/fpsyt.2013.00093] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2013] [Accepted: 08/09/2013] [Indexed: 11/13/2022] Open
Abstract
The basic symptoms (BS) approach provides a valid instrument in predicting psychosis onset and represents moreover a significant heuristic framework for research. The term "basic symptoms" denotes subtle changes of cognition and perception in the earliest and prodromal stages of psychosis development. BS are thought to correspond to disturbances of neural information processing. Following the heuristic implications of the BS approach, the present paper aims at exploring disturbances of information processing, revealed by functional magnetic resonance imaging (fMRI) and electro-encephalographic as characteristics of the at-risk state of psychosis. Furthermore, since high-risk studies employing ultra-high-risk criteria revealed non-conversion rates commonly exceeding 50%, thus warranting approaches that increase specificity, the potential contribution of neural information processing disturbances to psychosis prediction is reviewed. In summary, the at-risk state seems to be associated with information processing disturbances. Moreover, fMRI investigations suggested that disturbances of language processing domains might be a characteristic of the prodromal state. Neurophysiological studies revealed that disturbances of sensory processing may assist psychosis prediction in allowing for a quantification of risk in terms of magnitude and time. The latter finding represents a significant advancement since an estimation of the time to event has not yet been achieved by clinical approaches. Some evidence suggests a close relationship between self-experienced BS and neural information processing. With regard to future research, the relationship between neural information processing disturbances and different clinical risk concepts warrants further investigations. Thereby, a possible time sequence in the prodromal phase might be of particular interest.
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Affiliation(s)
- Mitja Bodatsch
- Department of Psychiatry and Psychotherapy, University of Cologne , Cologne , Germany
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Wood SJ, Reniers RLEP, Heinze K. Neuroimaging findings in the at-risk mental state: a review of recent literature. CANADIAN JOURNAL OF PSYCHIATRY. REVUE CANADIENNE DE PSYCHIATRIE 2013; 58:13-8. [PMID: 23327751 DOI: 10.1177/070674371305800104] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The at-risk mental state (ARMS) has been the subject of much interest during the past 15 years. A great deal of effort has been expended to identify neuroimaging markers that can inform our understanding of the risk state and to help predict who will transition to frank psychotic illness. Recently, there has been an explosion of neuroimaging literature from people with an ARMS, which has meant that reviews and meta-analyses lack currency. Here we review papers published in the past 2 years, and contrast their findings with previous reports. While it is clear that people in the ARMS do show brain alterations when compared with healthy control subjects, there is an overall lack of consistency as to which of these alterations predict the development of psychosis. This problem arises because of variations in methodology (in patient recruitment, region of interest, method of analysis, and functional task employed), but there has also been too little effort put into replicating previous research. Nonetheless, there are areas of promise, notably that activation of the stress system and increased striatal dopamine synthesis seem to mark out patients in the ARMS most at risk for later transition. Future studies should focus on these areas, and on network-level analysis, incorporating graph theoretical approaches and intrinsic connectivity networks.
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Affiliation(s)
- Stephen J Wood
- Professor of Adolescent Brain Development and Mental Health, School of Psychology, University of Birmingham, Edgbaston, England.
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Kahan J, Mancini L, Urner M, Friston K, Hariz M, Holl E, White M, Ruge D, Jahanshahi M, Boertien T, Yousry T, Thornton JS, Limousin P, Zrinzo L, Foltynie T. Therapeutic subthalamic nucleus deep brain stimulation reverses cortico-thalamic coupling during voluntary movements in Parkinson's disease. PLoS One 2012; 7:e50270. [PMID: 23300524 PMCID: PMC3530565 DOI: 10.1371/journal.pone.0050270] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2012] [Accepted: 10/18/2012] [Indexed: 01/11/2023] Open
Abstract
Deep brain stimulation of the subthalamic nucleus (STN DBS) has become an accepted treatment for patients experiencing the motor complications of Parkinson's disease (PD). While its successes are becoming increasingly apparent, the mechanisms underlying its action remain unclear. Multiple studies using radiotracer-based imaging have investigated DBS-induced regional changes in neural activity. However, little is known about the effect of DBS on connectivity within neural networks; in other words, whether DBS impacts upon functional integration of specialized regions of cortex. In this work, we report the first findings of fMRI in 10 subjects with PD and fully implanted DBS hardware receiving efficacious stimulation. Despite the technical demands associated with the safe acquisition of fMRI data from patients with implanted hardware, robust activation changes were identified in the insula cortex and thalamus in response to therapeutic STN DBS. We then quantified the neuromodulatory effects of DBS and compared sixteen dynamic causal models of effective connectivity between the two identified nodes. Using Bayesian model comparison, we found unequivocal evidence for the modulation of extrinsic (between region), i.e. cortico-thalamic and thalamo-cortical connections. Using Bayesian model parameter averaging we found that during voluntary movements, DBS reversed the effective connectivity between regions of the cortex and thalamus. This casts the therapeutic effects of DBS in a fundamentally new light, emphasising a role in changing distributed cortico-subcortical interactions. We conclude that STN DBS does impact upon the effective connectivity between the cortex and thalamus by changing their sensitivities to extrinsic afferents. Furthermore, we confirm that fMRI is both feasible and is tolerated well by these patients provided strict safety measures are adhered to.
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Affiliation(s)
- Josh Kahan
- Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, United Kingdom.
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Ma L, Steinberg JL, Hasan KM, Narayana PA, Kramer LA, Moeller FG. Stochastic dynamic causal modeling of working memory connections in cocaine dependence. Hum Brain Mapp 2012; 35:760-78. [PMID: 23151990 DOI: 10.1002/hbm.22212] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2011] [Revised: 08/21/2012] [Accepted: 09/19/2012] [Indexed: 11/10/2022] Open
Abstract
Although reduced working memory brain activation has been reported in several brain regions of cocaine-dependent subjects compared with controls, very little is known about whether there is altered connectivity of working memory pathways in cocaine dependence. This study addresses this issue by using functional magnetic resonance imaging-based stochastic dynamic causal modeling (DCM) analysis to study the effective connectivity of 19 cocaine-dependent subjects and 14 healthy controls while performing a working memory task. Stochastic DCM is an advanced method that has recently been implemented in SPM8 that can obtain improved estimates, relative to deterministic DCM, of hidden neuronal causes before convolution with the hemodynamic response. Thus, stochastic DCM may be less influenced by the confounding effects of variations in blood oxygen level-dependent response caused by disease or drugs. Based on the significant regional activation common to both groups and consistent with previous working memory activation studies, seven regions of interest were chosen as nodes for DCM analyses. Bayesian family level inference, Bayesian model selection analyses, and Bayesian model averaging (BMA) were conducted. BMA showed that the cocaine-dependent subjects had large differences compared with the control subjects in the strengths of prefrontal-striatal modulatory (B matrix) DCM parameters. These findings are consistent with altered cortical-striatal networks that may be related to reduced dopamine function in cocaine dependence. As far as we are aware, this is the first between-group DCM study using stochastic methodology.
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Affiliation(s)
- Liangsuo Ma
- Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center, Houston, Texas
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Brown TT, Jernigan TL. Brain development during the preschool years. Neuropsychol Rev 2012; 22:313-33. [PMID: 23007644 DOI: 10.1007/s11065-012-9214-1] [Citation(s) in RCA: 192] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2012] [Accepted: 09/13/2012] [Indexed: 01/16/2023]
Abstract
The preschool years represent a time of expansive mental growth, with the initial expression of many psychological abilities that will continue to be refined into young adulthood. Likewise, brain development during this age is characterized by its "blossoming" nature, showing some of its most dynamic and elaborative anatomical and physiological changes. In this article, we review human brain development during the preschool years, sampling scientific evidence from a variety of sources. First, we cover neurobiological foundations of early postnatal development, explaining some of the primary mechanisms seen at a larger scale within neuroimaging studies. Next, we review evidence from both structural and functional imaging studies, which now accounts for a large portion of our current understanding of typical brain development. Within anatomical imaging, we focus on studies of developing brain morphology and tissue properties, including diffusivity of white matter fiber tracts. We also present new data on changes during the preschool years in cortical area, thickness, and volume. Physiological brain development is then reviewed, touching on influential results from several different functional imaging and recording modalities in the preschool and early school-age years, including positron emission tomography (PET), electroencephalography (EEG) and event-related potentials (ERP), functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS). Here, more space is devoted to explaining some of the key methodological factors that are required for interpretation. We end with a section on multimodal and multidimensional imaging approaches, which we believe will be critical for increasing our understanding of brain development and its relationship to cognitive and behavioral growth in the preschool years and beyond.
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Affiliation(s)
- Timothy T Brown
- Multimodal Imaging Laboratory, University of California-San Diego, La Jolla, CA 92093, USA.
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Whalley HC, Papmeyer M, Sprooten E, Lawrie SM, Sussmann JE, McIntosh AM. Review of functional magnetic resonance imaging studies comparing bipolar disorder and schizophrenia. Bipolar Disord 2012; 14:411-31. [PMID: 22631622 DOI: 10.1111/j.1399-5618.2012.01016.x] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Although bipolar disorder (BD) and schizophrenia (SCZ) have a number of clinical features and certain susceptibility genes in common, they are considered separate disorders, and it is unclear which aspects of pathophysiology are specific to each condition. Here, we examine the functional magnetic resonance imaging (fMRI) literature to determine the evidence for diagnosis-specific patterns of brain activation in the two patient groups. METHOD A systematic search was performed to identify fMRI studies directly comparing BD and SCZ to examine evidence for diagnosis-specific activation patterns. Studies were categorized into (i) those investigating emotion, reward, or memory, (ii) those describing executive function or language tasks, and (iii) those looking at the resting state or default mode networks. Studies reporting estimates of sensitivity and specificity of classification are also summarized, followed by studies reporting associations with symptom severity measures. RESULTS In total, 21 studies were identified including patients (n = 729) and healthy subjects (n = 465). Relative over-activation in the medial temporal lobe and associated structures was found in BD versus SCZ in tasks involving emotion or memory. Evidence of differences between the disorders in prefrontal regions was less consistent. Accuracy values for assignment of diagnosis were generally lower in BD than in SCZ. Few studies reported significant symptom associations; however, these generally implicated limbic regions in association with manic symptoms. CONCLUSIONS Although there are a limited number of studies and a cautious approach is warranted, activation differences were found in the medial temporal lobe and associated limbic regions, suggesting the presence of differences in the neurobiological substrates of SCZ and BD. Future studies examining symptom dimensions, risk-associated genes, and the effects of medication will aid clarification of the mechanisms behind these differences.
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Affiliation(s)
- Heather C Whalley
- Division of Psychiatry, School of Molecular and Clinical Medicine, University of Edinburgh, Edinburgh, UK.
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Effect of variation in diacylglycerol kinase η (DGKH) gene on brain function in a cohort at familial risk of bipolar disorder. Neuropsychopharmacology 2012; 37:919-28. [PMID: 22048461 PMCID: PMC3280657 DOI: 10.1038/npp.2011.272] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Several lines of evidence indicate that the diacylglycerol kinase eta (DGKH) gene is implicated in the etiology of bipolar disorder (BD). However, the functional neural mechanisms of DGKH's risk association remain unknown. Therefore, we examined the effects of three haplotype-tagging risk variants in DGKH (single nucleotide polymorphisms rs9315885, rs1012053, and rs1170191) on brain activation using a verbal fluency functional magnetic resonance imaging task. The subject groups consisted of young individuals at high familial risk of BD (n=81) and a comparison group of healthy controls (n=75). Individuals were grouped based on risk haplotypes described in previous studies. There was a significant risk haplotype*group interaction in the left medial frontal gyrus (BA10, involving anterior cingulate BA32), left precuneus, and right parahippocampal gyrus. All regions demonstrated greater activation during the baseline condition than sentence completion. Individuals at high familial risk for BD homozygous for the DGKH risk haplotype demonstrated relatively greater activation (poor suppression) of these regions during the task vs the low-risk haplotype subjects. The reverse pattern was seen for the control subjects. These findings suggest that there are differential effects of the DGKH gene in healthy controls vs the bipolar high-risk group, which manifests as a failure to disengage default-mode regions in those at familial risk carrying the risk haplotype.
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Fornito A, Zalesky A, Pantelis C, Bullmore ET. Schizophrenia, neuroimaging and connectomics. Neuroimage 2012; 62:2296-314. [PMID: 22387165 DOI: 10.1016/j.neuroimage.2011.12.090] [Citation(s) in RCA: 530] [Impact Index Per Article: 44.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2011] [Revised: 11/15/2011] [Accepted: 12/15/2011] [Indexed: 10/28/2022] Open
Abstract
Schizophrenia is frequently characterized as a disorder of brain connectivity. Neuroimaging has played a central role in supporting this view, with nearly two decades of research providing abundant evidence of structural and functional connectivity abnormalities in the disorder. In recent years, our understanding of how schizophrenia affects brain networks has been greatly advanced by attempts to map the complete set of inter-regional interactions comprising the brain's intricate web of connectivity; i.e., the human connectome. Imaging connectomics refers to the use of neuroimaging techniques to generate these maps which, combined with the application of graph theoretic methods, has enabled relatively comprehensive mapping of brain network connectivity and topology in unprecedented detail. Here, we review the application of these techniques to the study of schizophrenia, focusing principally on magnetic resonance imaging (MRI) research, while drawing attention to key methodological issues in the field. The published findings suggest that schizophrenia is associated with a widespread and possibly context-independent functional connectivity deficit, upon which are superimposed more circumscribed, context-dependent alterations associated with transient states of hyper- and/or hypo-connectivity. In some cases, these changes in inter-regional functional coupling dynamics can be related to measures of intra-regional dysfunction. Topological disturbances of functional brain networks in schizophrenia point to reduced local network connectivity and modular structure, as well as increased global integration and network robustness. Some, but not all, of these functional abnormalities appear to have an anatomical basis, though the relationship between the two is complex. By comprehensively mapping connectomic disturbances in patients with schizophrenia across the entire brain, this work has provided important insights into the highly distributed character of neural abnormalities in the disorder, and the potential functional consequences that these disturbances entail.
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Affiliation(s)
- Alex Fornito
- Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, Australia.
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Fusar-Poli P. Voxel-wise meta-analysis of fMRI studies in patients at clinical high risk for psychosis. J Psychiatry Neurosci 2012; 37:106-12. [PMID: 22146150 PMCID: PMC3297070 DOI: 10.1503/jpn.110021] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2011] [Revised: 07/25/2011] [Accepted: 09/06/2011] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Reliable neurofunctional markers of increased vulnerability to psychosis are needed to improve the predictive value of psychosis risk syndrome and inform preventive interventions. METHODS I performed a signed differential mapping (SDM) voxel-wise meta-analysis of functional magnetic resonance imaging (fMRI) studies of patients at clinical high risk for psychosis. RESULTS Ten studies were included in the analysis. Compared with controls, high-risk patients showed reduced neural activation in the left inferior frontal gyrus (Brodmann area [BA] 9) and in a cluster spanning the bilateral medial frontal gyrus (BA 8,6), bilateral superior frontal gyrus (BA 8,6)and the left anterior cingulate (BA 32). There was no publication bias. Heterogeneity across studies was low. Sensitivity analysis confirmed the robustness of the findings. LIMITATIONS The cross-sectional nature of the included studies prevented the comparison of high-risk patients who later experienced a psychotic episode with those who did not. Other caveats are reflected in methodologic heterogeneity across tasks employed by different individual imaging studies. CONCLUSION Reduced neurofunctional activation in prefrontal regions may represent a neurophysiologic correlate of increased vulnerability to psychosis.
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Affiliation(s)
- Paolo Fusar-Poli
- Department of Psychosis Studies, Institute of Psychiatry, King’s College London, London, United Kingdom
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Egerton A, Borgwardt SJ, Tognin S, Howes OD, McGuire P, Allen P. An overview of functional, structural and neurochemical imaging studies in individuals with a clinical high risk for psychosis. ACTA ACUST UNITED AC 2011. [DOI: 10.2217/npy.11.51] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Smieskova R, Allen P, Simon A, Aston J, Bendfeldt K, Drewe J, Gruber K, Gschwandtner U, Klarhoefer M, Lenz C, Scheffler K, Stieglitz RD, Radue EW, McGuire P, Riecher-Rössler A, Borgwardt SJ. Different duration of at-risk mental state associated with neurofunctional abnormalities. A multimodal imaging study. Hum Brain Mapp 2011; 33:2281-94. [PMID: 21922599 DOI: 10.1002/hbm.21360] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2011] [Revised: 03/22/2011] [Accepted: 04/26/2011] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVES Neurofunctional alterations are correlates of vulnerability to psychosis, as well as of the disorder itself. How these abnormalities relate to different probabilities for later transition to psychosis is unclear. We investigated vulnerability- versus disease-related versus resilience biomarkers of psychosis during working memory (WM) processing in individuals with an at-risk mental state (ARMS). EXPERIMENTAL DESIGN Patients with "first-episode psychosis" (FEP, n = 21), short-term ARMS (ARMS-ST, n = 17), long-term ARMS (ARMS-LT, n = 16), and healthy controls (HC, n = 20) were investigated with an n-back WM task. We examined functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) data in conjunction using biological parametric mapping (BPM) toolbox. PRINCIPAL OBSERVATIONS There were no differences in accuracy, but the FEP and the ARMS-ST group had longer reaction times compared with the HC and the ARMS-LT group. With the 2-back > 0-back contrast, we found reduced functional activation in ARMS-ST and FEP compared with the HC group in parietal and middle frontal regions. Relative to ARMS-LT individuals, FEP patients showed decreased activation in the bilateral inferior frontal gyrus and insula, and in the left prefrontal cortex. Compared with the ARMS-LT, the ARMS-ST subjects showed reduced activation in the right inferior frontal gyrus and insula. Reduced insular and prefrontal activation was associated with gray matter volume reduction in the same area in the ARMS-LT group. CONCLUSIONS These findings suggest that vulnerability to psychosis was associated with neurofunctional alterations in fronto-temporo-parietal networks in a WM task. Neurofunctional differences within the ARMS were related to different duration of the prodromal state and resilience factors.
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Affiliation(s)
- Renata Smieskova
- Department of Psychiatry, University of Basel, c/o University Hospital Basel, Petersgraben 4, Basel 4031, Switzerland
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Fornito A, Yoon J, Zalesky A, Bullmore ET, Carter CS. General and specific functional connectivity disturbances in first-episode schizophrenia during cognitive control performance. Biol Psychiatry 2011; 70:64-72. [PMID: 21514570 PMCID: PMC4015465 DOI: 10.1016/j.biopsych.2011.02.019] [Citation(s) in RCA: 217] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2010] [Revised: 01/11/2011] [Accepted: 02/10/2011] [Indexed: 12/24/2022]
Abstract
BACKGROUND Cognitive control impairments in schizophrenia are thought to arise from dysfunction of interconnected networks of brain regions, but interrogating the functional dynamics of large-scale brain networks during cognitive task performance has proved difficult. We used functional magnetic resonance imaging to generate event-related whole-brain functional connectivity networks in participants with first-episode schizophrenia and healthy control subjects performing a cognitive control task. METHODS Functional connectivity during cognitive control performance was assessed between each pair of 78 brain regions in 23 patients and 25 control subjects. Network properties examined were region-wise connectivity, edge-wise connectivity, global path length, clustering, small-worldness, global efficiency, and local efficiency. RESULTS Patients showed widespread functional connectivity deficits in a large-scale network of brain regions, which primarily affected connectivity between frontal cortex and posterior regions and occurred irrespective of task context. A more circumscribed and task-specific connectivity impairment in frontoparietal systems related to cognitive control was also apparent. Global properties of network topology in patients were relatively intact. CONCLUSIONS The first episode of schizophrenia is associated with a generalized connectivity impairment affecting most brain regions but that is particularly pronounced for frontal cortex. Superimposed on this generalized deficit, patients show more specific cognitive-control-related functional connectivity reductions in frontoparietal regions. These connectivity deficits occur in the context of relatively preserved global network organization.
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Affiliation(s)
- Alex Fornito
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
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Fusar-Poli P, Crossley N, Woolley J, Carletti F, Perez-Iglesias R, Broome M, Johns L, Tabraham P, Bramon E, McGuire P. White matter alterations related to P300 abnormalities in individuals at high risk for psychosis: an MRI-EEG study. J Psychiatry Neurosci 2011; 36:239-48. [PMID: 21299920 PMCID: PMC3120892 DOI: 10.1503/jpn.100083] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
BACKGROUND Psychosis onset is characterized by white matter and electrophysiologic abnormalities. The relation between these factors in the development of illness is almost unknown. We studied the relation between white matter volumes and P300 in prodromal psychosis. METHODS We assessed white matter volume (detected using magnetic resonance imaging) and electrophysiologic response during an oddball task (P300) in healthy controls and individuals at high clinical risk for psychosis (with an "at-risk mental state" [ARMS]). RESULTS We included 41 controls and 39 patients with an ARMS in our study. A psychotic disorder developed in 26% of the ARMS group within the follow-up period of 2 years. The P300 amplitude was significantly lower in the ARMS group than in the control group. The ARMS group showed reduced volume of white matter underlying the left superior temporal gyrus and the left superior frontal gyrus and increased volume of white matter underlying the right insula and the right angular gyrus compared with controls. Relative to individuals who did not later become psychotic, the subgroup in whom psychosis subsequently developed had a smaller volume of white matter underlying the left precuneus and the right middle temporal gyrus and increased volume in the white matter underlying the right middle frontal gyrus. We observed a significant interaction in the right middle frontal gyrus: white matter volume was negatively associated with P300 amplitude in the ARMS group and positively associated with P300 amplitude in the control group. LIMITATIONS The voxel-based morphometry method alone cannot determine whether abnormal white matter volumes are due to an altered number of axonal connections or decreased myelination. CONCLUSION P300 abnormalities precede the onset of psychosis and are directly related to white matter alterations, representing a correlate of an increased vulnerability to disease.
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Affiliation(s)
- Paolo Fusar-Poli
- Psychosis Clinical Academic Group, Institute of Psychiatry, King's Health Partners, King's College London, London, UK.
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Brodersen KH, Schofield TM, Leff AP, Ong CS, Lomakina EI, Buhmann JM, Stephan KE. Generative embedding for model-based classification of fMRI data. PLoS Comput Biol 2011; 7:e1002079. [PMID: 21731479 PMCID: PMC3121683 DOI: 10.1371/journal.pcbi.1002079] [Citation(s) in RCA: 129] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2011] [Accepted: 04/20/2011] [Indexed: 01/22/2023] Open
Abstract
Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in ‘hidden’ physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups. Neurological and psychiatric spectrum disorders are typically defined in terms of particular symptom sets, despite increasing evidence that the same symptom may be caused by very different pathologies. Pathophysiological classification and effective treatment of such disorders will increasingly require a mechanistic understanding of inter-individual differences and clinical tools for making accurate diagnostic inference in individual patients. Previous classification studies have shown that functional magnetic resonance imaging (fMRI) can be used to differentiate between healthy controls and neurological or psychiatric patients. However, these studies are typically based on descriptive patterns and indirect measures of neural activity, and they rarely afford mechanistic insights into the underlying condition. In this paper, we address this challenge by proposing a classification approach that rests on a model of brain function and exploits the rich discriminative information encoded in directed interregional connection strengths. Based on an fMRI dataset acquired from moderately aphasic patients and healthy controls, we illustrate that our approach enables more accurate classification and deeper mechanistic insights about disease processes than conventional classification methods.
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Affiliation(s)
- Kay H Brodersen
- Department of Computer Science, ETH Zurich, Zurich, Switzerland.
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Ma L, Steinberg JL, Hasan KM, Narayana PA, Kramer LA, Moeller FG. Working memory load modulation of parieto-frontal connections: evidence from dynamic causal modeling. Hum Brain Mapp 2011; 33:1850-67. [PMID: 21692148 DOI: 10.1002/hbm.21329] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2010] [Revised: 02/20/2011] [Accepted: 03/17/2011] [Indexed: 11/07/2022] Open
Abstract
Previous neuroimaging studies have shown that working memory load has marked effects on regional neural activation. However, the mechanism through which working memory load modulates brain connectivity is still unclear. In this study, this issue was addressed using dynamic causal modeling (DCM) based on functional magnetic resonance imaging (fMRI) data. Eighteen normal healthy subjects were scanned while they performed a working memory task with variable memory load, as parameterized by two levels of memory delay and three levels of digit load (number of digits presented in each visual stimulus). Eight regions of interest, i.e., bilateral middle frontal gyrus (MFG), anterior cingulate cortex (ACC), inferior frontal cortex (IFC), and posterior parietal cortex (PPC), were chosen for DCM analyses. Analysis of the behavioral data during the fMRI scan revealed that accuracy decreased as digit load increased. Bayesian inference on model structure indicated that a bilinear DCM in which memory delay was the driving input to bilateral PPC and in which digit load modulated several parieto-frontal connections was the optimal model. Analysis of model parameters showed that higher digit load enhanced connection from L PPC to L IFC, and lower digit load inhibited connection from R PPC to L ACC. These findings suggest that working memory load modulates brain connectivity in a parieto-frontal network, and may reflect altered neuronal processes, e.g., information processing or error monitoring, with the change in working memory load. Hum Brain Mapp, 2012. © 2011 Wiley Periodicals, Inc.
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Affiliation(s)
- Liangsuo Ma
- Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center, Houston, Texas 77054, USA.
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Hypo-activation in the executive core of the sustained attention network in adolescent offspring of schizophrenia patients mediated by premorbid functional deficits. Psychiatry Res 2011; 192:91-9. [PMID: 21497490 PMCID: PMC3085585 DOI: 10.1016/j.pscychresns.2010.12.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2010] [Revised: 11/24/2010] [Accepted: 12/09/2010] [Indexed: 01/17/2023]
Abstract
Adolescent offspring of schizophrenia patients (SCZ-Off) are vulnerable to psychiatric disorders. Assessing relationships between clinical and biological measures (such as functional magnetic resonance imaging, fMRI) may elucidate pathways of vulnerability in this group. Here we assessed the relationship between clinically assessed premorbid function, and cortico-striatal activity during sustained attention in controls (HC: with no family history of psychosis) and SCZ-Off. Subjects (n=39) were assessed using the Structured Interview for Prodromal Syndromes and the Scale of Prodromal Symptoms. Based on the Global Assessment of Functioning (GAF) score, SCZ-Off were cleaved into "high" or "low" clinically functioning sub-groups (SCZ-Off(HF), SCZ-Off(LF) respectively). During fMRI, subjects participated in a modified continuous performance task (CPT-IP). fMRI was conducted on a Bruker MedSpec 4T system (345 EPI scans; TR=2s; 24 slices; 3.8×3.8×4mm). Results show SCZ-Off(LF) evinced less activation than both HC and SCZ-Off(HF) in the executive core of the brain's attentional system (anterior cingulate, dorsal prefrontal cortex and caudate), but not visuo-spatial regions such as primary visual or superior parietal cortex. Differences were independent of behavioral performance, and reduction in activity was related to GAF score in a dose-dependent manner. Assessing the relationship between clinical measures and brain activity in domains such as attention provides a window into mechanisms of vulnerability in the developing adolescent brain.
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Brodersen KH, Haiss F, Ong CS, Jung F, Tittgemeyer M, Buhmann JM, Weber B, Stephan KE. Model-based feature construction for multivariate decoding. Neuroimage 2011; 56:601-15. [PMID: 20406688 PMCID: PMC3112410 DOI: 10.1016/j.neuroimage.2010.04.036] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2009] [Revised: 04/04/2010] [Accepted: 04/14/2010] [Indexed: 11/16/2022] Open
Abstract
Conventional decoding methods in neuroscience aim to predict discrete brain states from multivariate correlates of neural activity. This approach faces two important challenges. First, a small number of examples are typically represented by a much larger number of features, making it hard to select the few informative features that allow for accurate predictions. Second, accuracy estimates and information maps often remain descriptive and can be hard to interpret. In this paper, we propose a model-based decoding approach that addresses both challenges from a new angle. Our method involves (i) inverting a dynamic causal model of neurophysiological data in a trial-by-trial fashion; (ii) training and testing a discriminative classifier on a strongly reduced feature space derived from trial-wise estimates of the model parameters; and (iii) reconstructing the separating hyperplane. Since the approach is model-based, it provides a principled dimensionality reduction of the feature space; in addition, if the model is neurobiologically plausible, decoding results may offer a mechanistically meaningful interpretation. The proposed method can be used in conjunction with a variety of modelling approaches and brain data, and supports decoding of either trial or subject labels. Moreover, it can supplement evidence-based approaches for model-based decoding and enable structural model selection in cases where Bayesian model selection cannot be applied. Here, we illustrate its application using dynamic causal modelling (DCM) of electrophysiological recordings in rodents. We demonstrate that the approach achieves significant above-chance performance and, at the same time, allows for a neurobiological interpretation of the results.
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Affiliation(s)
- Kay H Brodersen
- Department of Computer Science, ETH Zurich, Zurich, Switzerland.
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Lord LD, Allen P, Expert P, Howes O, Lambiotte R, McGuire P, Bose SK, Hyde S, Turkheimer FE. Characterization of the anterior cingulate's role in the at-risk mental state using graph theory. Neuroimage 2011; 56:1531-9. [PMID: 21316462 DOI: 10.1016/j.neuroimage.2011.02.012] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2010] [Revised: 01/12/2011] [Accepted: 02/02/2011] [Indexed: 12/11/2022] Open
Abstract
The onset of positive symptoms in schizophrenia is often preceded by a prodromal phase characterized by neurocognitive abnormalities as well as changes in brain structure and function. Increasing efforts have been made to identify individuals at elevated risk of developing schizophrenia, as early intervention may help prevent progression towards psychosis. The present study uses functional MRI and graph theoretical analysis to characterize the organization of a functional brain network in at-risk mental state patients with varying symptoms assessed with the PANSS and healthy volunteers during performance of a verbal fluency task known to recruit frontal lobe networks and to be impaired in psychosis. We first examined between-groups differences in total network connectivity and global network compactness/efficiency. We then addressed the role of specific brain regions in the network organization by calculating the node-specific "betweeness centrality", "degree centrality" and "local average path length" metrics; different ways of assessing a region's importance in a network. We focused our analysis on the anterior cingulate cortex (ACC); a region known to support executive function that is structurally and functionally impaired in at-risk mental state patients. Although global network connectivity and efficiency were maintained in at-risk patients relative to the controls, we report a significant decrease in the contribution of the ACC to task-relevant network organization in at risk subjects with elevated symptoms (PANSS ≥ 45) relative to both the controls and the less symptomatic at-risk subjects, as reflected by a reduction in the topological centrality of the ACC. These findings provide evidence of network abnormalities and anterior cingulate cortex dysfunction in people with prodromal signs of schizophrenia.
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Affiliation(s)
- Louis-David Lord
- Department of Experimental Medicine, Imperial College London, London, UK.
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Baharnoori M, Bartholomeusz C, Boucher AA, Buchy L, Chaddock C, Chiliza B, Föcking M, Fornito A, Gallego JA, Hori H, Huf G, Jabbar GA, Kang SH, El Kissi Y, Merchán-Naranjo J, Modinos G, Abdel-Fadeel NA, Neubeck AK, Ng HP, Novak G, Owolabi O, Prata DP, Rao NP, Riecansky I, Smith DC, Souza RP, Thienel R, Trotman HD, Uchida H, Woodberry KA, O'Shea A, DeLisi LE. The 2nd Schizophrenia International Research Society Conference, 10-14 April 2010, Florence, Italy: summaries of oral sessions. Schizophr Res 2010; 124:e1-62. [PMID: 20934307 PMCID: PMC4182935 DOI: 10.1016/j.schres.2010.09.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2010] [Revised: 08/30/2010] [Accepted: 09/01/2010] [Indexed: 01/06/2023]
Abstract
The 2nd Schizophrenia International Research Society Conference, was held in Florence, Italy, April 10-15, 2010. Student travel awardees served as rapporteurs of each oral session and focused their summaries on the most significant findings that emerged from each session and the discussions that followed. The following report is a composite of these reviews. It is hoped that it will provide an overview for those who were present, but could not participate in all sessions, and those who did not have the opportunity to attend, but who would be interested in an update on current investigations ongoing in the field of schizophrenia research.
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Affiliation(s)
- Moogeh Baharnoori
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, 6875 LaSalle Blvd, Montreal, Quebec, Canada H4H 1R3, phone (514) 761-6131 ext 3346,
| | - Cali Bartholomeusz
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Level 2-3, Alan Gilbert Building, 161 Barry St, Carlton South, Victoria 3053, Australia, phone +61 3 8344 1878, fax +61 3 9348 0469,
| | - Aurelie A. Boucher
- Brain and Mind Research Institute, 100 Mallett Street, Camperdown NSW 2050, Australia, phone +61 (0)2 9351 0948, fax +61 (0)2 9351 0652,
| | - Lisa Buchy
- Douglas Hospital Research Centre, 6875 LaSalle Blvd, Verdun, Québec, Canada, H4H 1R3 phone: 514-761-6131 x 3386, fax: 514-888-4064,
| | - Christopher Chaddock
- PO67, Section of Neuroimaging, Division of Psychological Medicine, Institute of Psychiatry, De Crespigny Park, London, SE5 8AF, phone 020 7848 0919, mobile 07734 867854 fax 020 7848 0976,
| | - Bonga Chiliza
- Department of Psychiatry, University of Stellenbosch, Tygerberg, 7505, South Africa, phone: +27 (0)21 9389227, fax +27 (0)21 9389738,
| | - Melanie Föcking
- Department of Psychiatry, Royal College of Surgeons in Ireland, Education and Research Centre, Beaumont Hospital, Dublin 9, Ireland, phone +353 1 809 3857, fax +353 1 809 3741,
| | - Alex Fornito
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Downing Site, Downing St, Cambridge, UK, CB2 3EB, phone +44 (0) 1223 764670, fax +44 (0) 1223 336581,
| | - Juan A. Gallego
- The Zucker Hillside Hospital, Psychiatry Research, 75-59 263rd St, Glen Oaks, NY 11004, phone 718-470-8177, fax 718-343-1659,
| | - Hiroaki Hori
- Department of Mental Disorder Research, National Institute of Neuroscience, NCNP, 4-1-1, Ogawahigashi, Kodaira, Tokyo, 187-8502, JAPAN, phone: +81 42 341 2711; fax: +81 42 346 1744,
| | - Gisele Huf
- National Institute of Quality Control in Health - Oswaldo Cruz Foundation.Av. Brasil 4365 Manguinhos Rio de Janeiro RJ BRAZIL 21045-900, phone + 55 21 38655112, fax + 55 21 38655139,
| | - Gul A. Jabbar
- Clinical Research Coordinator, Harvard Medical School Department of Psychiatry, 940 Belmont Street 2-B, Brockton, MA 02301, office (774) 826-1624, cell (845) 981-9514, fax (774) 286-1076,
| | - Shi Hyun Kang
- Seoul National Hospital, 30-1 Junggok3-dong Gwangjin-gu, Seoul, 143-711, Korea, phone +82-2-2204-0326, fax +82-2-2204-0394,
| | - Yousri El Kissi
- Psychiatry department, Farhat Hached Hospital. Ibn Jazzar Street, 4002 Sousse. Tunisia. phone + 216 98468626, fax + 216 73226702,
| | - Jessica Merchán-Naranjo
- Adolescent Unit. Department of Psychiatry. Hospital General Universitario Gregorio Marañón. Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain. C/Ibiza 43, C.P:28009, phone +34 914265005, fax +34 914265004,
| | - Gemma Modinos
- Department of Psychosis Studies (PO67), Institute of Psychiatry, King's College London, King's Health Partners, De Crespigny Park, SE5 8AF London, United Kingdo, phone +44 (0)20 78480917, fax +44 (0)20 78480976,
| | - Nashaat A.M. Abdel-Fadeel
- Minia University, Egypt, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, phone 617 953 0414, fax 617-998-5007, ,
| | - Anna-Karin Neubeck
- Project Manager at Karolinska Institute, Skinnarviksringen 12, 117 27 Stockholm, Sweden, phone +46708777908,
| | - Hsiao Piau Ng
- Singapore Bioimaging Consortium, A*STAR, Singapore; Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, phone 857-544-0192, fax 617-525-6150,
| | - Gabriela Novak
- University of Toronto, Medical Sciences Building, Room 4345, 1 King's College Circle, Toronto, Ontario, M5S 1A8, phone (416) 946-8219, fax (416) 971-2868,
| | - Olasunmbo.O. Owolabi
- Department of Anatomy, Faculty of Basic Medical Sciences, College of Health Science University of Ilorin, Ilorin, Nigeria, phone +2348030764811,
| | - Diana P. Prata
- Department of Psychosis Studies, King’s College London, King’s Health Partners, Institute of Psychiatry, De Crespigny Park, London, SE5 8AF, UK, phone +44(0)2078480917, fax +44(0)2078480976,
| | - Naren P. Rao
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Hosur Road, Bangalore, 560029 Karnataka, India, phone +91 9448342379,
| | - Igor Riecansky
- Address: Institute of Normal and Pathological Physiology, Slovak Academy of Sciences, Sienkiewiczova 1, 813 71 Bratislava, Slovakia, phone +421-2-52 92 62 76, fax +421-2-52 96 85 16,
| | - Darryl C. Smith
- 3336 Mt Pleasant St. NW #2, Washington, DC 20010, phone 202.494.3892,
| | - Renan P. Souza
- Centre for Addiction and Mental Health 250 College St R31 Toronto - Ontario - Canada M5T1R8, phone +14165358501 x4883, fax +14169794666,
| | - Renate Thienel
- Postdoctoral Research Fellow, PRC Brain and Mental Health, University of Newcastle, Mc Auley Centre Level 5, Mater Hospital, Edith Street, Waratah NSW 2298, phone +61 (2) 40335636,
| | - Hanan D. Trotman
- 36 Eagle Row, Atlanta, GA 30322, phone 404-727-8384, fax 404-727-1284,
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University School of Medicine, Psychopharmacology Research Program, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan, phone +81.3.3353.1211(x62454), fax +81.3.5379.0187,
| | - Kristen A. Woodberry
- Landmark Center 2 East, 401 Park Drive, Boston, MA 02215, phone 617-998-5022, fax 617-998-5007,
| | - Anne O'Shea
- Coordinator of reports. Harvard Medical School, VA Boston Healthcare System, 940 Belmont Street, Brockton, MA 02301, phone 774-826-1374, anne_o’
| | - Lynn E. DeLisi
- VA Boston Healthcare System and Harvard Medical School, 940 Belmont Street, Brockton, MA 02301, phone 774-826-1355, fax 774-826-2721
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Dysconnectivity in schizophrenia: where are we now? Neurosci Biobehav Rev 2010; 35:1110-24. [PMID: 21115039 DOI: 10.1016/j.neubiorev.2010.11.004] [Citation(s) in RCA: 480] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2010] [Revised: 11/02/2010] [Accepted: 11/20/2010] [Indexed: 01/14/2023]
Abstract
The disconnection hypothesis suggests that the core symptoms of schizophrenia (SZ) are related to aberrant, or 'dys-', connectivity between distinct brain regions. A proliferation of functional and structural neuroimaging studies have been conducted to investigate this hypothesis, across the full course of the disorder; from people at Ultra-High-Risk of developing psychosis to patients with chronic SZ. However the results of these studies have not always been consistent, and to date, there have been no attempts to summarise the results of both methodologies in conjunction. In this article, we systematically review both the structural and functional connectivity literature in SZ. The main trends to emerge are that schizophrenia is associated with connectivity reductions, as opposed to increases, relative to healthy controls, and that this is particularly evident in the connections involving the frontal lobe. These two trends appear to apply across all stages of the disorder, and to be independent of the neuroimaging methodology employed. We discuss the potential implications of these trends, and identify possible future investigative directions.
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