The ability to make decisions about continuously varying sensory stimuli, requiring the combination of bottom-up stimulus-driven with top-down task-specific information, is critical for selecting appropriate behavioral responses. Several neurodegenerative disorders showed decreased performance of category decision. At present, the understanding of the mechanisms of human categorization is mainly from fMRI data, obtaining estimation of local blood flow(a proxy for local neural processing) from tens of thousands of distinct neuroanatomical locations. However, human brain is a complex functional system, the corticostriatal loops play an important role in categorization. To exploring the mechanisms of categorization is a convenient and rich domain in understanding how brain works，The current project plans to collect functional imaging data from undergraduated and graduated students during making a spatial category decision. Using multi-voxel pattern analysis(MVPA), complex network analysis approaches and information processing modeling, this project aims to explore the mechanisms of the corticostriatal loops. The measures mainly concerned include the interaction between posterior parietal cortex and prefrontal cortex during abstract encoding of category and its regulatory mechanism, topological organization of large-scale functional brain networks as well hub regions and connectivity, and effective connectivity among key regions in corticostriatal loops. In the end, this project would reveal the mechanisms of corticostriatal loops during category decision. Additionally, the results of our project will give us further understanding of related neurodegenerative disorders, providing an important basis for prevention, intervention and new treatment means of them.
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