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Fouladirad S, Chen LV, Roes M, Chinchani A, Percival C, Khangura J, Zahid H, Moscovitz A, Arreaza L, Wun C, Sanford N, Balzan R, Moritz S, Menon M, Woodward TS. Functional brain networks underlying probabilistic reasoning and delusions in schizophrenia. Psychiatry Res Neuroimaging 2022; 323:111472. [PMID: 35405574 DOI: 10.1016/j.pscychresns.2022.111472] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 02/20/2022] [Accepted: 03/28/2022] [Indexed: 10/18/2022]
Abstract
Delusions in schizophrenia are false beliefs that are assigned certainty and not afforded the scrutiny that normally gives rise to doubt, even under conditions of weak evidence. The goal of the current functional magnetic resonance imaging (fMRI) study is to identify the brain network(s) involved in gathering information under conditions of weak evidence, in people with schizophrenia experiencing delusions. fMRI activity during probabilistic reasoning in people with schizophrenia experiencing delusions (n = 29) compared to people with schizophrenia not experiencing delusions (n = 41) and healthy controls (n = 41) was observed when participants made judgments based on evidence that weakly or strongly matched (or mismatched) with the focal hypothesis. A brain network involved in visual attention was strongly elicited for conditions of weak evidence for healthy controls and patients not experiencing delusions, but this increase was absent for patients experiencing delusions. This suggests that the state associated with delusions manifests in fMRI as reduced activity in an early visual attentional process whereby weak evidence is incorrectly stamped as conclusive, manifestating as a feeling of fluency and misplaced certainty, short-circuiting the search for evidence, and providing a candidate neural process for 'seeding' delusions.
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Affiliation(s)
- Saman Fouladirad
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Linda V Chen
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Faculty of Science, University of British Columbia, Vancouver, BC, Canada
| | - Meighen Roes
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychology, University of British Columbia, Vancouver, BC, Canada
| | - Abhijit Chinchani
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Chantal Percival
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Jessica Khangura
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Hafsa Zahid
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Aly Moscovitz
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Leonardo Arreaza
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Charlotte Wun
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Nicole Sanford
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Ryan Balzan
- College of Education, Psychology & Social Work, Flinders University, Adelaide, SA, Australia
| | - Steffen Moritz
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Mahesh Menon
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Todd S Woodward
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.
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Wadden KP, Woodward TS, Metzak PD, Lavigne KM, Lakhani B, Auriat AM, Boyd LA. Compensatory motor network connectivity is associated with motor sequence learning after subcortical stroke. Behav Brain Res 2015; 286:136-45. [PMID: 25757996 DOI: 10.1016/j.bbr.2015.02.054] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2014] [Revised: 02/13/2015] [Accepted: 02/17/2015] [Indexed: 12/31/2022]
Abstract
Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behavior within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke.
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Li D, Christ SE, Cowan N. Domain-general and domain-specific functional networks in working memory. Neuroimage 2014; 102 Pt 2:646-56. [PMID: 25178986 DOI: 10.1016/j.neuroimage.2014.08.028] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2013] [Revised: 07/15/2014] [Accepted: 08/18/2014] [Indexed: 11/24/2022] Open
Abstract
Working memory (WM) is a latent cognitive structure that serves to store and manipulate a limited amount of information over a short time period. How information is maintained in WM remains a debated issue: it is unclear whether stimuli from different sensory domains are maintained under distinct mechanisms or maintained under the same mechanism. Previous neuroimaging research on this issue to date has focused on individual brain regions and has not provided a comprehensive view of the functional networks underlying multi-domain WM. To study the functional networks involved in visual and auditory WM, we applied constrained principal component analysis (CPCA) to a functional magnetic resonance imaging (fMRI) dataset acquired when participants performed a change-detection task requiring them to remember only visual, only auditory, or both visual and auditory stimuli. Analysis revealed evidence of both [1] domain-specific networks responsive to either visual or auditory WM (but not both), and [2] domain-general networks responsive to both visual and auditory WM. The domain-specific networks showed load-dependent activations during only encoding, whereas a domain-general network was sensitive to WM load across encoding, maintenance, and retrieval. The latter domain-general network likely reflected attentional processes involved in WM encoding, retrieval, and possibly maintenance as well. These results do not support the domain-specific account of WM maintenance but instead favor the domain-general theory that items from different sensory domains are maintained under the same mechanism.
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