Spatiotemporal and sensory modality attention processing with domain-specific representations in frontoparietal areas. (8th February 2022)

• Record Type: Journal Article
• Authors: Wang, Luyao; Li, Chunlin; Han, Ziteng; Wu, Qiong; Sun, Liwei; Zhang, Xu; Go, Ritsu; Wu, Jinglong; Yan, Tianyi
• Is Part Of: Cerebral cortex. Volume 32:Number 24(2022)
• Page Start: 5489
• Page End: 5502
• Publication Date: 2022-02-08
• Subjects: top-down attention -- activity strength -- representational similarity analysis -- frontal–parietal network -- fMRI; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhac029
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: The frontoparietal network (FPN), including bilateral frontal eye field, inferior parietal sulcus, and supplementary motor area, has been linked to attention processing, including spatiotemporal and sensory modality domains. However, it is unclear whether FPN encodes representations of these domains that are generalizable across subdomains. We decomposed multivariate patterns of functional magnetic resonance imaging activity from 20 participants into domain-specific components and identified latent multivariate representations that generalized across subdomains. The 30 experimental conditions were organized into unimodal–bimodal and spatial–temporal models. We found that brain areas in the FPN, form the primary network that modulated during attention across domains. However, the activation patterns of areas within the FPN were reorganized according to the specific attentional demand, especially when pay attention to different sensory, suggesting distinct regional neural representations associated with specific attentional processes within FPN. In addition, there were also other domain-specific areas outside the FPN, such as the dorsolateral prefrontal cortex. Our conclusion is that, according to the results of the analysis of representation similarity, 2 types of activated brain regions, related to attention domain detailed information processing and general information processing, can be revealed.