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Abstract #2919

Accurate Brain Parcellation of Individual Marmosets Based on Awake Resting-State fMRI Data and Deep Neural Networks

Xiaoguang Tian1, Zhifeng Liang2, Afonso C Silva1, and Cirong Liu2
1Dept. of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States, 2Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China

As a prerequisite for understanding how the brain works, it has been a long-sought goal to subdivide (parcellate) the brain into a mosaic of anatomically- and functionally-defined parcels (areas). However, reaching a consensus parcellation has been hindered by inaccuracies in aligning brain areas across subjects. Here, we developed a novel cortical parcellation approach using resting-state fMRI data collected in a population of awake marmosets to accurately map the functional brain organization of individuals.

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