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Multimodal Connectivity-Based Individual Parcellation and Analysis for Humans and Rhesus Monkeys.

Yue CuiChengyi LiYuheng LuLiang MaLuqi ChengLong CaoShan YuTianzi Jiang
Published in: IEEE transactions on medical imaging (2024)
Individual brains vary greatly in morphology, connectivity and organization. Individualized brain parcellation is capable of precisely localizing subject-specific functional regions. However, most individualization approaches have examined single modalities of data and have not generalized to nonhuman primates. The present study proposed a novel multimodal connectivity-based individual parcellation (MCIP) method, which optimizes within-region homogeneity, spatial continuity and similarity to a reference atlas with the fusion of personal functional and anatomical connectivity. Comprehensive evaluation demonstrated that MCIP outperformed state-of-the-art multimodal individualization methods in terms of functional and anatomical homogeneity, predictability of cognitive measures, heritability, reproducibility and generalizability across species. Comparative investigation showed a higher topographic variability in humans than that in macaques. Therefore, MCIP provides improved accurate and reliable mapping of brain functional regions over existing methods at an individual level across species, and could facilitate comparative and translational neuroscience research.
Keyphrases
  • resting state
  • functional connectivity
  • white matter
  • high resolution
  • pain management
  • multiple sclerosis
  • high density
  • artificial intelligence
  • finite element