Abstract
We investigate both experimentally and using a computational model how the power of the electroencephalogram (EEG) recorded in human subjects tracks the presentation of sounds with acoustic intensities that increase exponentially (looming) or remain constant (flat). We focus on the link between this EEG tracking response, behavioral reaction times and the time scale of fluctuations in the resting state, which show considerable inter-subject variability. Looming sounds are shown to generally elicit a sustained power increase in the alpha and beta frequency bands. In contrast, flat sounds only elicit a transient upsurge at frequencies ranging from 7 to 45 Hz. Likewise, reaction times (RTs) in an audio-tactile task at different latencies from sound onset also present significant differences between sound types. RTs decrease with increasing looming intensities, i.e. as the sense of urgency increases, but remain constant with stationary flat intensities. We define the reaction time variation or “gain” during looming sound presentation, and show that higher RT gains are associated with stronger correlations between EEG power responses and sound intensity. Higher RT gain further entails higher relative power differences between loom and flat in the alpha and beta bands. The full-width-at-half-maximum of the autocorrelation function of the eyes-closed resting state EEG also increases with RT gain. The effects are topographically located over the central and frontal electrodes. A computational model reveals that the increase in stimulus–response correlation in subjects with slower resting state fluctuations is expected when EEG power fluctuations at each electrode and in a given band are viewed as simple coupled low-pass filtered noise processes jointly driven by the sound intensity. The model assumes that the strength of stimulus-power coupling is proportional to RT gain in different coupling scenarios, suggesting a mechanism by which slower resting state fluctuations enhance EEG response and shorten reaction times.
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Acknowledgements
The authors would like to thank Gustavo Deco for his comments on an earlier version of the manuscript.
Funding
This work was supported by the EJLB-Michael Smith Foundation (200809EJL-194083-EJL-CECA-179644), the Canada Institute of Health Research (CIHR, 201103MOP-244752-BSB-CECA-179644), and the Canada Research Chair (CRC) (to GN). AL was supported by NSERC Canada (RGPIN-2014-06204) and the University of Ottawa Research Chair in Neurophysics. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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A. Longtin and G. Northoff are joint senior authors.
This is one of several papers published together in Brain Topography on the “Special Issue: Computational Modeling and M/EEG".
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Sancristóbal, B., Ferri, F., Longtin, A. et al. Slow Resting State Fluctuations Enhance Neuronal and Behavioral Responses to Looming Sounds. Brain Topogr 35, 121–141 (2022). https://doi.org/10.1007/s10548-021-00826-4
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DOI: https://doi.org/10.1007/s10548-021-00826-4