2020年

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Zening Fu, Yuhui Du, Jing Sui, Vince Calhoun*. Dynamic Functional Network Variability Underlying Disease Traits in Schizophrenia and Autism. Biological Psychiatry, 2020, 87(9): S118–S119.

时间:2020-06-22 10:51:22   来源:  点击:[34]

Background

Brain dynamics span multiple spatial scales, from connectivity associated with a specific region/network to whole-brain configuration, representing different neural aspects of the brain. Schizophrenia and autism spectrum disorder are among many psychiatric and neurological disorders that share overlapping features. Studying the dynamic connectivity for these two disorders from a comprehensive spatial perspective is important for clarifying their relationship in a way that captures brain dynamics, which can underlie behavioral aspects and cognitive symptoms.

Methods

A novel measure called step-wise functional network variability was introduced for characterizing how functional brain organization varies at different spatial scales. We applied this measure to two independent datasets including schizophrenia and autism to assess the degree to which these two disorders are associated with multi-levels connectivity structure (whole-brain, within/between-domain, and intrinsic networks involved connectivity). 

Results

Both diseases show increased whole-brain network variability and between cerebellar and subcortical/ sensorimotor domains, with more abnormalities observed in schizophrenia. Schizophrenic effects were mainly localized to networks of the subcortical, sensory and cerebellar domains, while autism effects were widespread across domains. Interestingly, the network variability between cerebellar and sensorimotor domains was not only correlated with the performance of reasoning-problem-solving but also with autistic symptoms as assessed by autism diagnostic observation schedule (multiple-comparison-adjusted p < 0.05).

Conclusions

Step-wise functional network variability is a promising measure for capturing connectivity dynamics at different spatial scales. The investigation of brain dynamics from a comprehensive perspective can provide previously ignored insights into brain reconfiguration, which might advance our knowledge of the mechanisms underlying mental illness.