Spatiotemporal and sensory modality attention processing with domain-specific representations in frontoparietal areas

Luyao Wang, Chunlin Li, Ziteng Han, Qiong Wu, Liwei Sun, Xu Zhang, Ritsu Go, Jinglong Wu, Tianyi Yan

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)5489-5502
Number of pages14
JournalCerebral Cortex
Issue number24
Publication statusPublished - Dec 8 2022


  • activity strength
  • fMRI
  • frontal–parietal network
  • representational similarity analysis
  • top-down attention

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience


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