Time-resolved correlation of distributed brain activity tracks E-I balance and accounts for diverse scale-free phenomena

Summary: Much of systems neuroscience posits the functional importance of brain activity patterns that lack natural scales of sizes, durations, or frequencies. The field has developed prominent, and sometimes competing, explanations for the nature of this scale-free activity. Here, we reconcile thes...

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Bibliographic Details
Main Authors: Aditya Nanda, Graham W. Johnson, Yu Mu, Misha B. Ahrens, Catie Chang, Dario J. Englot, Michael Breakspear, Mikail Rubinov
Format: Article
Language:English
Published: Elsevier 2023-04-01
Series:Cell Reports
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Online Access:http://www.sciencedirect.com/science/article/pii/S2211124723002656
Description
Summary:Summary: Much of systems neuroscience posits the functional importance of brain activity patterns that lack natural scales of sizes, durations, or frequencies. The field has developed prominent, and sometimes competing, explanations for the nature of this scale-free activity. Here, we reconcile these explanations across species and modalities. First, we link estimates of excitation-inhibition (E-I) balance with time-resolved correlation of distributed brain activity. Second, we develop an unbiased method for sampling time series constrained by this time-resolved correlation. Third, we use this method to show that estimates of E-I balance account for diverse scale-free phenomena without need to attribute additional function or importance to these phenomena. Collectively, our results simplify existing explanations of scale-free brain activity and provide stringent tests on future theories that seek to transcend these explanations.
ISSN:2211-1247