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Non-zero mean alpha oscillations revealed with computational model and empirical data

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Studenova,  Alina A.
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia;

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Villringer,  Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Clinic for Cognitive Neurology, University of Leipzig, Germany;

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Nikulin,  Vadim V.
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia;
Neurophysics Group, Department of Neurology, Charité University Medicine Berlin, Germany;
Bernstein Center for Computational Neuroscience, Berlin, Germany;

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Citation

Studenova, A. A., Villringer, A., & Nikulin, V. V. (2022). Non-zero mean alpha oscillations revealed with computational model and empirical data. PLoS Computational Biology, 18(7): e1010272. doi:10.1371/journal.pcbi.1010272.


Cite as: https://hdl.handle.net/21.11116/0000-000A-B7AD-5
Abstract
Ongoing oscillations and evoked responses are two main types of neuronal activity obtained with diverse electrophysiological recordings (EEG/MEG/iEEG/LFP). Although typically studied separately, they might in fact be closely related. One possibility to unite them is to demonstrate that neuronal oscillations have non-zero mean which predicts that stimulus- or task-triggered amplitude modulation of oscillations can contribute to the generation of evoked responses. We validated this mechanism using computational modelling and analysis of a large EEG data set. With a biophysical model, we indeed demonstrated that intracellular currents in the neuron are asymmetric and, consequently, the mean of alpha oscillations is non-zero. To understand the effect that neuronal currents exert on oscillatory mean, we varied several biophysical and morphological properties of neurons in the network, such as voltage-gated channel densities, length of dendrites, and intensity of incoming stimuli. For a very large range of model parameters, we observed evidence for non-zero mean of oscillations. Complimentary, we analysed empirical rest EEG recordings of 90 participants (50 young, 40 elderly) and, with spatio-spectral decomposition, detected at least one spatially-filtred oscillatory component of non-zero mean alpha oscillations in 93% of participants. In order to explain a complex relationship between the dynamics of amplitude-envelope and corresponding baseline shifts, we performed additional simulations with simple oscillators coupled with different time delays. We demonstrated that the extent of spatial synchronisation may obscure macroscopic estimation of alpha rhythm modulation while leaving baseline shifts unchanged. Overall, our results predict that amplitude modulation of neural oscillations should at least partially explain the generation of evoked responses. Therefore, inference about changes in evoked responses with respect to cognitive conditions, age or neuropathologies should be constructed while taking into account oscillatory neuronal dynamics.