Parcellation of individual brains: From group level atlas to precise mapping.

Journal: Neuroscience and biobehavioral reviews
Published Date:

Abstract

Individual brains vary greatly in morphology, connectivity, and organization. Group-level brain parcellations, which do not account for individual variations in brain parcels, are increasingly limited in their applicability, especially given the rapid development of precision medicine. Accurate individual-level brain functional mapping is pivotal for comprehending variations in brain functions and behaviors, the early and precise identification of brain abnormalities, and personalized treatments for neuropsychiatric disorders. Recent advances in neuroimaging and machine learning techniques have led to a surge in studies on the parcellation of individual brains. In this paper, we present an overview of recent advances in the methodologies of individual brain parcellation, including optimization- and learning-based methods. We then introduce comprehensive evaluation metrics to validate individual functional regions, and discuss how individual brain mapping advances neuroscience research and clinical medicine. Finally, major challenges and future directions of individual brain parcellation are summarized. In conclusion, we provide a comprehensive overview of individual brain parcellation methods, validations, and applications, highlighting current challenges and the urgent need for integrated platforms that encompass datasets, methods, and validations.

Authors

  • Chengyi Li
    Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China; Key Laboratory of Brian Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, Beijing, China.
  • Shan Yu
    Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190 Beijing, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 100190 Beijing, China; University of Chinese Academy of Sciences, 100049 Beijing, China. Electronic address: shan.yu@nlpr.ia.ac.cn.
  • Yue Cui
    National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China.