Journal of Neuroscience MethodsNeurosciencePeer-reviewed journal article
Simulating human sleep spindle MEG and EEG from ion channel and circuit level dynamics
Burke Q. RoseniD, Giri P. KrishnaniD, Pavel ŠandaiD, Maxim Komarov, Terrence J. Sejnowski A BiD, Nikolai F. RulkoviD, István UlbertiD, Lóránd ErőssiD, Joseph R. MadseniD, Orrin DevinskyiD, Werner DoyleiD, Dániel FabóiD, Sydney S. CashiD, Maxim BazhenoviD, Eric HalgreniD
- Citations
- 10
- FWCI
- 0.30
- Field percentile
- top 41%
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.\n\nMethodWe 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.\n\nResultsThe 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.\n\nComparison 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.\n\nConclusionsThis 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.
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Thalamocortical and Intracortical Laminar Connectivity Determines Sleep Spindle Properties
Giri P. Krishnan, Burke Q. Rosen, … Maxim Bazhenov·PLoS Computational BiologyPeer-reviewed·Jun 27, 2018
- Cross-frequency slow oscillation-spindle coupling in a biophysically realistic thalamocortical neural mass model
Nikola Jajcay, Caglar Cakan, Klaus Obermayer·Frontiers in Computational NeurosciencePeer-reviewed·May 6, 2022
- Mean-field models for EEG/MEG: from oscillations to waves
Áine Byrne, James Ross, … Stephen Coombes·Brain TopographyPeer-reviewed·May 15, 2021
- Biophysical modeling of the neural origin of EEG and MEG signals
Solveig Næss, Geir Halnes, … Torbjørn V. Ness·bioRxiv·Jul 1, 2020
- What EEG doesn't see: a whole-brain MEG map of sleep spindles and slow oscillations
Anne Calvel, Keelin Greenlaw, … Emily B. J. Coffey·bioRxiv·Oct 12, 2026
- Sleep waves in a large-scale corticothalamic model constrained by activities intrinsic to neocortical networks and single thalamic neurons
Martynas Dervinis, Vincenzo Crunelli·CNS Neuroscience & TherapeuticsPeer-reviewed·Apr 18, 2023