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

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.

Stimulus-induced changes in 1/f-like background activity in EEG

“…Importantly, failing to disentangle these factors contributing to the shape of the power spectrum could lead to erroneous conclusions regarding the mechanisms generating neural signals. Specifically, in our datasets, we observed a general steepening of 1/f activity from pre-to post-event, which would normally be interpreted as a shift towards inhibitory as opposed to excitatory activity (Colombo et al, 2019;Gao et al, 2017;Lendner et al, 2020;Miskovic et al, 2019;Waschke et al, 2021). However, our subsequent analyses indicate that it would be premature to conclude that auditory stimuli lead to increased inhibition.…”

“…Notably, this possibility does not invalidate the popular account which posits that changes in the shape of 1/f activity reflect changes in the balance of excitatory and inhibitory neural inputs, regardless of the invasiveness of the recording (Gao et al, 2017;Waschke et al, 2021), given that activity elicited by an event (ERP) arguably -and trivially -also reflects a shift in the balance of excitation and inhibition in neural populations. Our findings, however, increase the explanatory power of this account by suggesting that 1/f-like scaling in the frequency domain of a signal might reflect a combination of stimulus-related and stimulus-unrelated (ongoing, background) activities that are both non-oscillatory in nature (i.e., they do not include ongoing alpha oscillations).…”

“…As such, spatial summation may act as a low-pass spatial filter similarly to time-domain averaging, resulting in a 1/f-like pattern in signals measured non-invasively. Therefore, any findings based on surface level recordings concerning the functional significance of 1/f-like activity (Wainio-Theberge et al, 2021;Waschke et al, 2021) may be capturing changes in low frequency activity, which may partly be due to the emergence of ERPs (although see control analyses in Waschke et al, 2021).…”

“…It is reasonable to assume that 1/f activity may change in response to external events, because the slope (x) and offset of 1/f activity have both been found to change as a function of neuronal activation levels in local brain activity measured by invasive recordings (Miller et al, 2009;Podvalny et al, 2015). Recently, 1/f activity has also been shown to be sensitive to the balance between excitatory and inhibitory neural activity in surface EEG recordings, which reflect activity summated over larger areas of the cortex as opposed to local activity (Waschke et al, 2021), and this balance might also change during tasks. Furthermore, M/EEG findings by Wainio-Theberge et al (2021) suggest that the parameters describing the shape of pre-stimulus and post-stimulus 1/f activity may in fact differ, although that study did not directly investigate this question.…”

Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood

“…Recent work, however, has begun to provide compelling evidence in support of the importance of the aperiodic signal. Studies have shown aperiodic activity to be modulated by task-performance ( He et al, 2010 ), level of arousal ( Lendner et al, 2020 ), and drug-induced states ( Colombo et al, 2019 , Muthukumaraswamy and Liley, 2018 , Waschke et al, 2021 ). In addition, several studies have shown features of the aperiodic signal to be altered in neurological and psychiatric disease ( Molina et al, 2020 , Ostlund et al, 2021a , Robertson et al, 2019 , Wilkinson and Nelson, 2021 ).…”