Quantum Theory of EEG with Application to the Single-Trial ERP Analysis

Abstract

The probabilistic formalism of quantum mechanics is used to quantitatively link the electroencephalogram (EEG) with the underlying microscale activity of cortical neurons. Previous approaches applied methods of classic physics to reconstruct the EEG in terms of explicit physical models of cortical neurons and the volume conductor. However, the multiplicity of cellular processes with extremely intricate mixtures of deterministic and random factors prevented the creation of consistent biophysical parameter sets. To avoid the uncertainty surrounding the physical attributes of the neuronal ensembles, we undertake here a radical departure from deterministic equations of classical physics to the probabilistic reasoning of quantum mechanics. The crucial step is the relocation of the elementary bioelectric sources from cellular to molecular level. Using a novel method of time-frequency analysis with adaptive segmentation for digital processing of empirical EEG and single trial event related potentials (ERPs), we found universal “building blocks” of these cortical processes both in the frequency and time domains. This result is qualified as a phenomenon known in statistical physics and quantum mechanics as universality. Therationale is that despite dramatic differences in the cellular machineries, the statistical factors governed by the central limit theorem produce the EEG waveform as a statistical aggregate of the synchronized activities of large ensembles of closely located cortical neurons. Using these theoretical and empirical findings the probabilistic laws that control the microscale machinery generating the EEG are deduced.