Neuronal timescales are functionally dynamic and shaped by cortical microarchitecture
Abstract
Complex cognitive functions such as working memory and decision-making require information maintenance over seconds to years, from transient sensory stimuli to long-term contextual cues. While theoretical accounts predict the emergence of a corresponding hierarchy of neuronal timescales, direct electrophysiological evidence across the human cortex is lacking. Here, we infer neuronal timescales from invasive intracranial recordings. Timescales increase along the principal sensorimotor-to-association axis across the entire human cortex, and scale with single-unit timescales within macaques. Cortex-wide transcriptomic analysis shows direct alignment between timescales and expression of excitation- and inhibition-related genes, as well as genes specific to voltage-gated transmembrane ion transporters. Finally, neuronal timescales are functionally dynamic: prefrontal cortex timescales expand during working memory maintenance and predict individual performance, while cortex-wide timescales compress with aging. Thus, neuronal timescales follow cytoarchitectonic gradients across the human cortex, and are relevant for cognition in both short- and long-terms, bridging microcircuit physiology with macroscale dynamics and behavior.
Data availability
All raw data are previously published and taken from publicly available repositories (see Table 1), all intermediate data produced from this manuscript are available on Github, with the associated analysis and visualization code
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MNI Open iEEGMNI, https://mni-open-ieegatlas.research.mcgill.ca/.
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Human Connectome Project S1200 ReleaseHCP, https://www.humanconnectome.org/study/hcp-young-adult/document/1200-subjects-data-release.
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Neurotycho Anesthesia and Sleep TaskNeurotycho, Anesthesia and Sleep.
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Whole brain gene expressionhttp://www.meduniwien.ac.at/neuroimaging/mRNA.html.
Article and author information
Author details
Funding
Natural Sciences and Engineering Research Council of Canada (CGSD3-488052-2016)
- Richard Gao
Katzin Prize
- Richard Gao
Alexander von Humboldt-Stiftung
- Ruud L van den Brink
Alfred P. Sloan Foundation (FG-2015-66057)
- Bradley Voytek
Whitehall Foundation (2017-12-73)
- Bradley Voytek
National Science Foundation (BCS-1736028)
- Bradley Voytek
National Institutes of Health (R01GM134363-01)
- Bradley Voytek
Shiley-Marcos Alzheimer's Disease Research Center
- Bradley Voytek
Halicioglu Data Science Institute Fellowship
- Bradley Voytek
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Martin Vinck, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Germany
Publication history
- Received: July 21, 2020
- Accepted: November 22, 2020
- Accepted Manuscript published: November 23, 2020 (version 1)
- Version of Record published: December 22, 2020 (version 2)
Copyright
© 2020, Gao et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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