Mean-field Modeling of Thalamocortical Dynamics and Application to EEG Analysis

Mean-field modeling of thalamocortical dynamics, and a model-driven approach to EEG analysis

Jonathan D. Victor, Jonathan D. Drover, Mary M. Conte, and Nicholas D. Schiff

Proc. Natl. Acad. Sci. USA 108, 15631-15638 (2011)

Abstract

Higher brain function depends on task-dependent information flow between cortical regions. Converging lines of evidence suggest that interactions between cortical regions and the central thalamus play a key role in establishing the dynamic patterns of functional connectivity that normally support these processes. In patients with chronic disturbances of cognitive function due to severe brain injury, dysfunction of this circuitry likely plays a crucial role in pathogenesis. However, assaying thalamocortical interactions is challenging even in healthy subjects, and more so in severely impaired patients. To approach this problem, we apply a dynamical-systems approach to motivate an analysis of the electroencephalogram (EEG). We begin with a model for a single thalamocortical module (Robinson, Rennie & Rowe, 2002; Robinson, Rennie, Wright & Bourke, 1998). When two such modules interact via shared thalamic inhibition, multistable behavior emerges; each mode is characterized by a different pattern of coherence between cortical regions. This observation suggests that changing patterns of cortical coherence is a hallmark of normal thalamocortical dynamics. In a preliminary study, we test this idea by analyzing the EEG of a patient with chronic brain injury, who has a marked improvement in behavior and frontal brain metabolism in response to zolpidem. The analysis shows that following zolpidem administration, changing patterns of coherence are identified between the frontal lobes, and between frontal and distant brain regions. These observations support the role of the central thalamus in the organization of patterns of cortical interactions, and suggest how indices of thalamocortical dynamics can be extracted from the EEG.


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