Journal
HUMAN BRAIN MAPPING
Volume 42, Issue 12, Pages 3983-3992Publisher
WILEY
DOI: 10.1002/hbm.25534
Keywords
cognitive function; Connectome; fMRI; machine learning; resting‐ state; schizophrenia
Funding
- Israel Science Foundation [1603/18]
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This study using fMRI showed a strong connection between abnormal brain activity and connectivity in schizophrenia patients. Through machine-learning, accurate predictions of task-evoked brain activation in these patients were made using measures extracted from healthy controls. These findings offer novel insights into the relationship between brain connectivity and activity in schizophrenia.
What goes wrong in a schizophrenia patient's brain that makes it so different from a healthy brain? In this study, we tested the hypothesis that the abnormal brain activity in schizophrenia is tightly related to alterations in brain connectivity. Using functional magnetic resonance imaging (fMRI), we demonstrated that both resting-state functional connectivity and brain activity during the well-validated N-back task differed significantly between schizophrenia patients and healthy controls. Nevertheless, using a machine-learning approach we were able to use resting-state functional connectivity measures extracted from healthy controls to accurately predict individual variability in the task-evoked brain activation in the schizophrenia patients. The predictions were highly accurate, sensitive, and specific, offering novel insights regarding the strong coupling between brain connectivity and activity in schizophrenia. On a practical perspective, these findings may allow to generate task activity maps for clinical populations without the need to actually perform any tasks, thereby reducing patients inconvenience while saving time and money.
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