Journal
NATURE COMMUNICATIONS
Volume 9, Issue -, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41467-018-03664-4
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Funding
- National Institute of Mental Health (NIMH) [K99MH104605]
- NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation
- National Institute of Mental Health Intramural Research Program (NIH) [NCT00001360, 93-M-0170, ZIAMH002783-16]
- NIH Blueprint for Neuroscience Research (as part of the Human Connectome Project, WU-Minn Consortium) [1U54MH091657]
- McDonnell Center for Systems Neuroscience at Washington University
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Little is known about how our brains dynamically adapt for efficient functioning. Most previous work has focused on analyzing changes in co-fluctuations between a set of brain regions over several temporal segments of the data. We argue that by collapsing data in space or time, we stand to lose useful information about the brain's dynamical organization. Here we use Topological Data Analysis to reveal the overall organization of whole-brain activity maps at a single-participant level-as an interactive representation-without arbitrarily collapsing data in space or time. Using existing multitask fMRI datasets, with the known ground truth about the timing of transitions from one task-block to next, our approach tracks both within-and between-task transitions at a much faster time scale (similar to 4-9 s) than before. The individual differences in the revealed dynamical organization predict task performance. In summary, our approach distills complex brain dynamics into interactive and behaviorally relevant representations.
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