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

• Published in: eLife Vol. 10
• Main Authors: Waschke, Leonhard, Donoghue, Thomas, Fiedler, Lorenz, Smith, Sydney, Garrett, Douglas D, Voytek, Bradley, Obleser, Jonas
• Format: Journal Article
• Language: English
• Published: England eLife Science Publications, Ltd 21.10.2021; eLife Sciences Publications Ltd; eLife Sciences Publications, Ltd
• Subjects: Acoustic Stimulation; Anesthesia; Anesthetics, Intravenous - pharmacology; Approximation; Attention; Attention - physiology; Brain - physiology; EEG; Electrodes; Electroencephalography; Electrophysiological Phenomena - physiology; electrophysiology; Female; human; Humans; Investigations; Ketamine - pharmacology; Male; Neuroscience; Photic Stimulation; Propofol - pharmacology; Sensory integration; Statistics; Visual stimuli; Young Adult; electrophysiology; human; EEG; neuroscience
• ISSN: 2050-084X; 2050-084X
• DOI: 10.7554/eLife.70068

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.