FULL TITLE:
Mapping the human brain's cortical-subcortical functional network organization
SPECIES:
Human
DESCRIPTION:
Additional files, code, and documentation can be found at https://github.com/ColeLab/ColeAnticevicNetPartition.
ABSTRACT:
Understanding complex systems such as the human brain requires characterization of the system's architecture across multiple levels of organization - from neurons, to local circuits, to brain regions, and ultimately large-scale brain networks. Here we focus on characterizing the human brain's large-scale network organization, as it provides an overall framework for the organization of all other levels. We developed a highly principled approach to identify cortical network communities at the level of functional systems, calibrating our community detection algorithm using extremely well-established sensory and motor systems as guides. Building on previous network partitions, we replicated and expanded upon well-known and recently-identified networks, including several higher-order cognitive networks such as a left-lateralized language network. We expanded these cortical networks to subcortex, revealing 358 highly-organized subcortical parcels that take part in forming whole-brain functional networks. Notably, the identified subcortical parcels are similar in number to a recent estimate of the number of cortical parcels (360). This whole-brain network atlas - released as an open resource for the neuroscience community - places all brain structures across both cortex and subcortex into a single large-scale functional framework, with the potential to facilitate a variety of studies investigating large-scale functional networks in health and disease.
PUBLICATION:
NeuroImage
- DOI:
10.1016/j.neuroimage.2018.10.006
- PMID:
30291974
- Jie Lisa Ji
- Marjolein Spronk
- Kaustubh Kulkarni
- Grega Repovš
- Alan Anticevic
- Michael W Cole
- Yale University
- Department of Psychology, University of Ljubljana, 1000, Ljubljana, Slovenia
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, 07102, USA