Joseph D Viviano1, Robert W Buchanan2, Navona Calarco1, James M Gold2, George Foussias3, Nikhil Bhagwat4, Laura Stefanik1, Colin Hawco5, Pamela DeRosse6, Miklos Argyelan6, Jessica Turner7, Sofia Chavez8, Peter Kochunov2, Peter Kingsley6, Xiangzhi Zhou6, Anil K Malhotra6, Aristotle N Voineskos9. 1. Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario. 2. Department of Psychiatry, Maryland Psychiatric Research Center, Catonsville, Maryland. 3. Department of Psychiatry, University of Toronto, Toronto, Ontario. 4. Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario; Computational Brain Anatomy Laboratory, Brain Imaging Center, Douglas Mental Health University Institute, Verdun, Quebec, Canada. 5. Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario; Department of Psychiatry, University of Toronto, Toronto, Ontario. 6. Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York. 7. Department of Psychology, Georgia State University, Atlanta, Georgia. 8. Department of Psychiatry, University of Toronto, Toronto, Ontario; MRI Unit, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario. 9. Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario; Department of Psychiatry, University of Toronto, Toronto, Ontario. Electronic address: aristotle.voineskos@camh.ca.
Abstract
BACKGROUND: Deficits in neurocognition and social cognition are drivers of reduced functioning in schizophrenia spectrum disorders, with potentially shared neurobiological underpinnings. Many studies have sought to identify brain-based biomarkers of these clinical variables using a priori dichotomies (e.g., good vs. poor cognition, deficit vs. nondeficit syndrome). METHODS: We evaluated a fully data-driven approach to do the same by building and validating a brain connectivity-based biomarker of social cognitive and neurocognitive performance in a sample using resting-state and task-based functional magnetic resonance imaging (n = 74 healthy control participants, n = 114 persons with schizophrenia spectrum disorder, 188 total). We used canonical correlation analysis followed by clustering to identify a functional connectivity signature of normal and poor social cognitive and neurocognitive performance. RESULTS: Persons with poor social cognitive and neurocognitive performance were differentiated from those with normal performance by greater resting-state connectivity in the mirror neuron and mentalizing systems. We validated our findings by showing that poor performers also scored lower on functional outcome measures not included in the original analysis and by demonstrating neuroanatomical differences between the normal and poorly performing groups. We used a support vector machine classifier to demonstrate that functional connectivity alone is enough to distinguish normal and poorly performing participants, and we replicated our findings in an independent sample (n = 75). CONCLUSIONS: A brief functional magnetic resonance imaging scan may ultimately be useful in future studies aimed at characterizing long-term illness trajectories and treatments that target specific brain circuitry in those with impaired cognition and function.
BACKGROUND:Deficits in neurocognition and social cognition are drivers of reduced functioning in schizophrenia spectrum disorders, with potentially shared neurobiological underpinnings. Many studies have sought to identify brain-based biomarkers of these clinical variables using a priori dichotomies (e.g., good vs. poor cognition, deficit vs. nondeficit syndrome). METHODS: We evaluated a fully data-driven approach to do the same by building and validating a brain connectivity-based biomarker of social cognitive and neurocognitive performance in a sample using resting-state and task-based functional magnetic resonance imaging (n = 74 healthy control participants, n = 114 persons with schizophrenia spectrum disorder, 188 total). We used canonical correlation analysis followed by clustering to identify a functional connectivity signature of normal and poor social cognitive and neurocognitive performance. RESULTS:Persons with poor social cognitive and neurocognitive performance were differentiated from those with normal performance by greater resting-state connectivity in the mirror neuron and mentalizing systems. We validated our findings by showing that poor performers also scored lower on functional outcome measures not included in the original analysis and by demonstrating neuroanatomical differences between the normal and poorly performing groups. We used a support vector machine classifier to demonstrate that functional connectivity alone is enough to distinguish normal and poorly performing participants, and we replicated our findings in an independent sample (n = 75). CONCLUSIONS: A brief functional magnetic resonance imaging scan may ultimately be useful in future studies aimed at characterizing long-term illness trajectories and treatments that target specific brain circuitry in those with impaired cognition and function.
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Authors: Colin Hawco; Erin W Dickie; Gabrielle Herman; Jessica A Turner; Miklos Argyelan; Anil K Malhotra; Robert W Buchanan; Aristotle N Voineskos Journal: Sci Data Date: 2022-06-14 Impact factor: 8.501
Authors: Lindsay D Oliver; Colin Hawco; Philipp Homan; Junghee Lee; Michael F Green; James M Gold; Pamela DeRosse; Miklos Argyelan; Anil K Malhotra; Robert W Buchanan; Aristotle N Voineskos Journal: Biol Psychiatry Cogn Neurosci Neuroimaging Date: 2020-12-05
Authors: Matthew Ainsworth; Jérôme Sallet; Olivier Joly; Diana Kyriazis; Nikolaus Kriegeskorte; John Duncan; Urs Schüffelgen; Matthew Fs Rushworth; Andrew H Bell Journal: J Neurosci Date: 2021-06-04 Impact factor: 6.167