Simulating human sleep spindle MEG and EEG from ion channel and circuit level dynamics

Abstract

BackgroundAlthough they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain. MethodWe present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors. ResultsThe simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted. Comparison with Existing MethodsPrevious models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales simultaneously. ConclusionsThis multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses.

Sleep waves in a large-scale corticothalamic model constrained by activities intrinsic to neocortical networks and single thalamic neurons

“…[7][8][9][10] To further our knowledge of the mechanisms underlying these EEG rhythms, many biophysical and nonbiophysical models have been used to simulate sleep waves. [11][12][13][14][15][16][17][18][19][20][21] However, none of these models implemented the variety of neocortical neuron-specific sleep-related activities reported to occur in the isolated neocortex 22 and/or the ability of single thalamic neurons to elicit slow (< 1Hz) oscillations when isolated from the neocortex [23][24][25][26] .…”