Investigating cognitive flexibility deficit in schizophrenia using task-based whole-brain functional connectivity

Yanqing Wang; Xueping Hu; Yilu Li

doi:10.3389/fpsyt.2022.1069036

Investigating cognitive flexibility deficit in schizophrenia using task-based whole-brain functional connectivity

Front Psychiatry. 2022 Nov 21:13:1069036. doi: 10.3389/fpsyt.2022.1069036. eCollection 2022.

Authors

Yanqing Wang^{1

2}, Xueping Hu^{3

4}, Yilu Li⁵

Affiliations

¹ Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
² Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
³ School of Linguistic Science and Art, Jiangsu Normal University, Xuzhou, China.
⁴ Key Laboratory of Language and Cognitive Neuroscience of Jiangsu Province, Collaborative Innovation Center for Language Ability, Xuzhou, China.
⁵ The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.

Abstract

Background: Cognitive flexibility is a core cognitive control function supported by the brain networks of the whole-brain. Schizophrenic patients show deficits in cognitive flexibility in conditions such as task-switching. A large number of neuroimaging studies have revealed abnormalities in local brain activations associated with deficits in cognitive flexibility in schizophrenia, but the relationship between impaired cognitive flexibility and the whole-brain functional connectivity (FC) pattern is unclear.

Method: We investigated the task-based functional connectivity of the whole-brain in patients with schizophrenia and healthy controls during task-switching. Multivariate pattern analysis (MVPA) was utilized to investigate whether the FC pattern can be used as a feature to discriminate schizophrenia patients from healthy controls. Graph theory analysis was further used to quantify the degrees of integration and segregation in the whole-brain networks to interpret the different reconfiguration patterns of brain networks in schizophrenia patients and healthy controls.

Results: The results showed that the FC pattern classified schizophrenia patients and healthy controls with significant accuracy. Moreover, the altered whole-brain functional connectivity pattern was driven by a lower degree of network integration and segregation in schizophrenia, indicating that both global and local information transfers at the entire-network level were less efficient in schizophrenia patients than in healthy controls during task-switching processing.

Conclusion: These results investigated the group differences in FC profiles during task-switching and not only elucidated that FC patterns are changed in schizophrenic patients, suggesting that task-based FC could be used as a potential neuromarker to discriminate schizophrenia patients from healthy controls in cognitive flexibility but also provide increased insight into the brain network organization that may contribute to impaired cognitive flexibility.

Keywords: cognitive flexibility; functional connectivity; graph theory analysis; multivariate pattern analysis; schizophrenia.