Modality-specific tracking of attention and sensory statistics in the human electrophysiological spectral exponent

Author:

Waschke Leonhard12ORCID,Donoghue Thomas3ORCID,Fiedler Lorenz4ORCID,Smith Sydney5,Garrett Douglas D12ORCID,Voytek Bradley3567ORCID,Obleser Jonas89ORCID

Affiliation:

1. Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Max Planck Institute for Human Development

2. Center for Lifespan Psychology, Max Planck Institute for Human Development

3. Department of Cognitive Science, University of California, San Diego

4. Eriksholm Research Centre, Oticon A/S

5. Neurosciences Graduate Program, University of California, San Diego

6. Halıcıoglu Data Science Institute, University of California, San Diego

7. Kavli Institute for Brain and Mind, University of California, San Diego

8. Department of Psychology, University of Lübeck

9. Center of Brain, Behavior, and Metabolism, University of Lübeck

Abstract

A hallmark of electrophysiological brain activity is its 1/f-like spectrum – power decreases with increasing frequency. The steepness of this ‘roll-off’ is approximated by the spectral exponent, which in invasively recorded neural populations reflects the balance of excitatory to inhibitory neural activity (E:I balance). Here, we first establish that the spectral exponent of non-invasive electroencephalography (EEG) recordings is highly sensitive to general (i.e., anaesthesia-driven) changes in E:I balance. Building on the EEG spectral exponent as a viable marker of E:I, we then demonstrate its sensitivity to the focus of selective attention in an EEG experiment during which participants detected targets in simultaneous audio-visual noise. In addition to these endogenous changes in E:I balance, EEG spectral exponents over auditory and visual sensory cortices also tracked auditory and visual stimulus spectral exponents, respectively. Individuals’ degree of this selective stimulus–brain coupling in spectral exponents predicted behavioural performance. Our results highlight the rich information contained in 1/f-like neural activity, providing a window into diverse neural processes previously thought to be inaccessible in non-invasive human recordings.

Funder

Deutsche Forschungsgemeinschaft

H2020 European Research Council

Max Planck UCL Centre for Computational Psychiatry and Ageing Research

Whitehall Foundation

National Science Foundation

National Institute of General Medical Sciences

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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