Schizophrenia is a complex brain disorder characterized by severe social dysfunctions. Similar but attenuated format of social dysfunction has also been found in individuals with subclinical features such as social anhedonia. Dr. Raymond Chan’s team from the Neuropsychology and Applied Cognitive Neuroscience (NACN) Laboratory, the CAS Key Laboratory of Mental Health, Institute of Psychology has recently shown that both patients with schizophrenia and individuals with social anhedonia exhibited alteration in social brain network and diminished correlation with real-world social network size characteristics. However, these previous findings were done at the regions of interest approach that may not be able to address the complex relationship between brain functional connectivity and real-life social behavioural adequately. Moreover, it is still not clearly known whether the social brain network characteristics could predict real-world social network. To further clarify these issues, Dr. Chan’s team has conducted two studies to specifically examine the association between social brain network and real-life social network size in schizophrenia patients using a hub-connected functional connectivity approach, and to examine the prediction of the identified social brain connectivity in individuals with social anhedonia.

In the first study, Dr. Chan’s team first recruited 49 patients with schizophrenia and 27 healthy controls to undertake the resting-state brain imaging scan and completed a checklist to measure social network size. Their findings showed that the left temporal lobe was the only hub of social brain network, and its connected functional connectivity strength was higher than the remaining functional connectivity in patients with schizophrenia and healthy controls. They also found that patients with schizophrenia exhibited the lower association between the hub-connected functional connectivity with the real-world social network size characteristics. More importantly, Dr. Chan’s team further recruited 30 patients with schizophrenia and 28 healthy controls to follow the same procedure and data analysis, and they did replicate the same findings in this independent sample

In the second study, Dr. Chan’s team recruited 22 pairs of participants with high and low levels of social anhedonia. All the participants undertook the resting-state brain imaging scan and completed a checklist to measure social network size at baseline and then completed the set of checklist 21 months later. Their findings showed that social brain network characteristics could predict the change of real-world social networks in both participants with high and low levels of social anhedonia. Notably, their results also showed a different pattern exhibited by the two groups. The topological characteristics of the social brain network predicted real-world social network change in participants with high level of social anhedonia, whereas the functional connectivity within the social brain network predicted real-world social network change in participants with low level of social anhedonia. Their findings also showed that the functional connectivity component centered at the right orbital inferior frontal gyrus could best predict social network change for the entire sample.

Taken together, these two series of study suggest that brain regions centred at the left temporal lobe appear to be the hub region of the social brain network supporting complex social behaviour. The hub-connected connectivity, compared with non-hub connected functional connectivity of social brain network in patients with schizophrenia, affects their relationship with real-life social function. The follow-up study in individuals with social anhedonia further suggest that such social brain network characteristics could predict the longitudinal change of real-world social network in individuals with high level of social anhedonia, particularly the inferior orbital frontal gyrus functional connectivity. These findings may have an important implication to guide the development of non-pharmacological interventions for social function deficits in patients with schizophrenia spectrum disorders.

This study was supported by the National Key Research and Development Programme, the Beijing Municipal Science & Technology Commission Grant, the Beijing Training Project for the Leading Talents in Science & Technology, and the CAS Key Laboratory of Mental Health, Institute of Psychology.

These two studies are now available online from European Archives of Psychiatry and Clinical Neuroscience, and Psychiatry Research Neuroimaging respectively on Oct 9 and Sep 9, 2021.

 -        Zhang, Y. J.#, Li, Y.#, Wang, Y. M., Wang, S. K., Pu, C. C., Zhou, S. Z., Ma, Y. T., Wang, Y., Lui, S. S. Y., Yu, X., Chan, R. C. K.* (in press). Hub-connected functional connectivity within social brain network weakens the association with real-life social network in schizophrenia patients. European Archives of Psychiatry and Clinical Neuroscience.
-        Zhang, Y. J., Cai, X. L., Hu, H. X., Zhang, R. T., Wang, Y., Lui, S. S. Y., Cheung, E. F. C., Chan, R. C. K.* (2021). Social brain network predicts real-world social network in individuals with social anhedonia. Psychiatry Research Neuroimaging, 317, 111390. 

Related Publication
-        Zhang, Y. J.#, Pu, C. C.#, Wang, Y. M., Zhang, R. T., Cai, X. L., Zhou, S. Z., Ma, Y. T., Wang, Y., Cheung, E. F. C., Lui, S. S. Y., Yu, X.*, Chan R. C. K.* (2021). Social brain network correlates with real-life social network in individuals with schizophrenia and social anhedonia. Schizophrenia Research, 232, 77-84.

LIU Chen
Institute of Psychology
Chinese Academy of Sciences
Beijing 100101, China.
E-mail: liuc@psych.ac.cn