Enhanced group-level dorsolateral prefrontal cortex subregion parcellation through functional connectivity-based distance-constrained spectral clustering with application to autism spectrum disorder

Author:

Li Yanling1,Li Rui1,Gu Jiahe1,Yi Hongtao1,He Junbiao1,Lu Fengmei23,Gao Jingjing4

Affiliation:

1. School of Electrical Engineering and Electronic Information, Xihua University , 9999 Hongguang Avenue, Pixian District, Chengdu City, Sichuan Province, Chengdu 610039 , China

2. The Clinical Hospital of Chengdu Brain Science Institute , School of Life Science and Technology, , 2006 Xiyuan Avenue, High-tech Zone (West Zone), Chengdu City, Sichuan Province, Chengdu 610054 , China

3. University of Electronic Science and Technology of China , School of Life Science and Technology, , 2006 Xiyuan Avenue, High-tech Zone (West Zone), Chengdu City, Sichuan Province, Chengdu 610054 , China

4. School of Information and Communication Engineering, University of Electronic Science and Technology of China , 2006 Xiyuan Avenue, High-tech Zone (West Zone), Chengdu City, Sichuan Province, Chengdu 611731 , China

Abstract

Abstract The dorsolateral prefrontal cortex (DLPFC) assumes a central role in cognitive and behavioral control, emerging as a crucial target region for interventions in autism spectrum disorder neuroregulation. Consequently, we endeavor to unravel the functional subregions within the DLPFC to shed light on the intricate functions of the brain. We introduce a distance-constrained spectral clustering (SC-DW) methodology that leverages functional connection to identify distinctive functional subregions within the DLPFC. Furthermore, we verify the relationship between the functional characteristics of these subregions and their clinical implications. Our methodology begins with principal component analysis to extract the salient features. Subsequently, we construct an adjacency matrix, which is constrained by the spatial properties of the brain, by linearly combining the distance matrix and a similarity matrix. The quality of spectral clustering is further optimized through multiple cluster evaluation coefficient. The results from SC-DW revealed four uniform and contiguous subregions within the bilateral DLPFC. Notably, we observe a substantial positive correlation between the functional characteristics of the third and fourth subregions in the left DLPFC with clinical manifestations. These findings underscore the unique insights offered by our proposed methodology in the realms of brain subregion delineation and therapeutic targeting.

Funder

Autism Brain Imaging Data Exchange

National Natural Science Foundation of China

Sichuan Province Science and Technology Support Program

Medico-Engineering Cooperation Funds from University of Electronic Science and Technology of China

National Key Research and Development Program of China

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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