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

背外侧前额叶皮质 自闭症谱系障碍 前额叶皮质 神经科学 主成分分析 模式识别(心理学) 聚类分析 心理学 计算机科学 认知 人工智能 自闭症 发展心理学
作者
Yanling Li,Rui Li,Jiahe Gu,Hongtao Yi,Junbiao He,Fengmei Lu,Jingjing Gao
出处
期刊:Cerebral Cortex [Oxford University Press]
卷期号:34 (2) 被引量:2
标识
DOI:10.1093/cercor/bhae020
摘要

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.
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