IEEE Transactions on Neural Systems and Rehabilitation EngineeringNeurosciencePeer-reviewed journal article
Aperiodic exponent of brain field potentials is dependent on the frequency range it is estimated
Gonzalo BoncompteiD, Vicente MedeliD, Martín IraniiD, J.-P. LachauxiD, Tomás OssandóniD
Abstract
The aperiodic component of brain field potentials, like EEG, LFP and intracortical recordings, has shown to be a valuable tool in basic neuroscience and in clinical applications. Aperiodic activity is modeled as a power law of the power spectral density, with the aperiodic exponent as the key parameter. Part of the interest in this parameter lies in its proposed role as a marker of the balance between excitatory and inhibitory cortical activity. In theory, a perfect power law would imply that the same behaviour exists across all frequencies, however recent evidence has suggested that low and high frequency ranges could present different aperiodic exponents. To elucidate this, we systematically evaluated the relation between frequency range and aperiodic parameters using human resting-state intracortical recordings from 62 patients. We employed two distinct estimation methods, Specparam and IRASA. We found that aperiodic parameters were indeed dependent on frequency range. Specifically, we found that low frequency ranges displayed, on average, lower aperiodic exponents (flatter power spectral density) than high frequency ranges. This behaviour was consistent for Specparam and IRASA estimations in all frequency ranges compatible with EEG. Given that there is currently no consensus for a single frequency range to be used in either clinical or basic neuroscience, our results show that care should be taken when comparing aperiodic exponents derived from different frequency ranges. We believe our results also encourage further research into the possible roles that aperiodic exponents estimated from different frequency ranges could have in reflecting distinct aspects of cortical systems.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 9
- FWCI
- 5.11
- Field percentile
- top 3%
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