Abstract

Previous work from our lab has demonstrated how the connectivity of brain circuits constrains the repertoire of activity patterns that those circuits can display. Specifically, we have shown that the principal components of spontaneous neural activity are uniquely determined by the underlying circuit connections, and that although the principal components do not uniquely resolve the circuit structure, they do reveal important features about it. Expanding upon this framework on a larger scale of neural dynamics, we have analyzed EEG data recorded with the standard 10–20 electrode system from 41 neurologically normal children and adolescents during stage 2, non-REM sleep. We show that the principal components of EEG spindles, or sigma waves (10–16 Hz), reveal non-propagating, standing waves in the form of spherical harmonics. We mathematically demonstrate that standing EEG waves exist when the spatial covariance and the Laplacian operator on the head's surface commute. This in turn implies that the covariance between two EEG channels decreases as the inverse of their relative distance; a relationship that we corroborate with empirical data. Using volume conduction theory, we then demonstrate that superficial current sources are more synchronized at larger distances, and determine the characteristic length of large-scale neural synchronization as 1.31 times the head radius, on average. Moreover, consistent with the hypothesis that EEG spindles are driven by thalamo-cortical rather than cortico-cortical loops, we also show that 8 additional patients with hypoplasia or complete agenesis of the corpus callosum, i.e., with deficient or no connectivity between cortical hemispheres, similarly exhibit standing EEG waves in the form of spherical harmonics. We conclude that spherical harmonics are a hallmark of spontaneous, large-scale synchronization of neural activity in the brain, which are associated with unconscious, light sleep. The analogy with spherical harmonics in quantum mechanics suggests that the variances (eigenvalues) of the principal components follow a Boltzmann distribution, or equivalently, that standing waves are in a sort of “thermodynamic” equilibrium during non-REM sleep. By extension, we speculate that consciousness emerges as the brain dynamics deviate from such equilibrium.

Highlights

  • Modern philosophy and science attribute the most significant aspects of the human mind, such as consciousness, to neural activity in the brain (Tononi and Edelman, 1998; McFadden, 2002; Rees et al, 2002; Libet, 2004; Lamme, 2006; Melloni et al, 2007; Fingelkurts et al, 2013)

  • 14 (34%) were male and 27 (66%) were female, with ages ranging from 9 months to 18 years; of the subjects with agenesis or hypoplasia of the corpus callosum, 3 (37%) were male and 5 (63%) were female, with ages ranging from 3 months to 14 years

  • Electrodes were referenced to a ground electrode placed on the center of the forehead (Fpz) and all analyses were performed on EEG waveforms referenced to this common electrode

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Summary

Introduction

Modern philosophy and science attribute the most significant aspects of the human mind, such as consciousness, to neural activity in the brain (Tononi and Edelman, 1998; McFadden, 2002; Rees et al, 2002; Libet, 2004; Lamme, 2006; Melloni et al, 2007; Fingelkurts et al, 2013). Spatiotemporal EEG and MEG patterns are sensitive enough to allow for an effective discrimination between certain cognitive states such as alertness and drowsiness (Sing and Russo, 2007), and even phenotypes such as schizophrenia (Van Der Stelt and Belger, 2007), amnesia (Babiloni et al, 2010), dyslexia (Babiloni et al, 2012), and autism (García Domínguez et al, 2013; Pérez Velázquez and Galán, 2013) This suggests that despite their apparently random nature, spontaneous patterns of brain activity are well-structured both in space and time (Galán, 2008; Fingelkurts et al, 2010)

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