Parameterizing neural power spectra into periodic and aperiodic components
Top Cited Papers
- 23 November 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Nature Neuroscience
- Vol. 23 (12), 1655-1665
- https://doi.org/10.1038/s41593-020-00744-x
Abstract
Electrophysiological signals exhibit both periodic and aperiodic properties. Periodic oscillations have been linked to numerous physiological, cognitive, behavioral and disease states. Emerging evidence demonstrates that the aperiodic component has putative physiological interpretations and that it dynamically changes with age, task demands and cognitive states. Electrophysiological neural activity is typically analyzed using canonically defined frequency bands, without consideration of the aperiodic (1/f-like) component. We show that standard analytic approaches can conflate periodic parameters (center frequency, power, bandwidth) with aperiodic ones (offset, exponent), compromising physiological interpretations. To overcome these limitations, we introduce an algorithm to parameterize neural power spectra as a combination of an aperiodic component and putative periodic oscillatory peaks. This algorithm requires no a priori specification of frequency bands. We validate this algorithm on simulated data, and demonstrate how it can be used in applications ranging from analyzing age-related changes in working memory to large-scale data exploration and analysis.Keywords
Funding Information
- National Science Foundation (DGE1106400, BCS-1736028)
- UC San Diego Frontiers of Innovation Scholars Program
- UC San Diego Kavli Innovative Research Grant; Frontiers for Innovation Scholars Program fellowship; Katzin Prize
- U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (R01-MH121448, R01-MH117763, Conte Center Grant P50MH109429, U19 Brain Initiative Grant U19NS107609, F32MH75317)
- Alfred P. Sloan Foundation (FG-2015-66057)
- Whitehall Foundation (2017-12-73)
- U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (R01GM134363-01)
- U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (R37NS21135)
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