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Modeling the contribution of lamina 5 neuronal and network dynamics to low frequency EEG phenomena
Authors:Fadi N Karameh  Munther A Dahleh  Emery N Brown  Steve G Massaquoi
Institution:(1) Department of Electrical and Computer Engineering, American University of Beirut, Beirut, 1107-2020, Lebanon;(2) Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;(3) Department of Brain and Cognitive Sciences, MIT-Harvard Division of Health Science and Technology, Massachusetts Institute of Technology, Rm 46-6079, 77 Massachusetts Ave, Cambridge, MA 02139, USA;(4) Neuroscience Statistics Research Laboratory, Department of Anesthesia and Critical Care, Massachusetts General Hospital, 55 Fruit Street Clinics 3, Boston, MA 02114, USA;(5) MIT-Harvard Division of Health Sciences and Technology, Massachusetts Institute of Technology, Rm 32-214, 77 Massachusetts Ave, Cambridge, MA 02139, USA
Abstract:The Electroencephalogram (EEG) is an important clinical and research tool in neurophysiology. With the advent of recording techniques, new evidence is emerging on the neuronal populations and wiring in the neocortex. A main challenge is to relate the EEG generation mechanisms to the underlying circuitry of the neocortex. In this paper, we look at the principal intrinsic properties of neocortical cells in layer 5 and their network behavior in simplified simulation models to explain the emergence of several important EEG phenomena such as the alpha rhythms, slow-wave sleep oscillations, and a form of cortical seizure. The models also predict the ability of layer 5 cells to produce a resonance-like neuronal recruitment known as the augmenting response. While previous models point to deeper brain structures, such as the thalamus, as the origin of many EEG rhythms (spindles), the current model suggests that the cortical circuitry itself has intrinsic oscillatory dynamics which could account for a wide variety of EEG phenomena.Electronic Supplementary Material Supplementary material is available for this article at Sensorimotor Control Project- MIT Harvard NeuroEngineering Research Collaborative.
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