A Multi-Scale Study of Thalamic State-Dependent Responsiveness

Abstract

ABSTRACTThe thalamus is the brain’s central relay station, orchestrating sensory processing and cognitive functions. However, how thalamic function depends on internal and external states, is not well understood. A comprehensive understanding would necessitate the integration of single cell dynamics with their collective behaviour at population level. For this we propose a biologically realistic mean-field model of the thalamus, describing the dynamics of thalamocortical relay neurons (TC) and thalamic reticular neurons (RE). With this we perform a multi-scale study of thalamic responsiveness and its dependence on cell, synaptic, and brain states. Based on existing single-cell experiments we show that: The transition between tonic and burst states of TC cells acts as a linear-nonlinear switch in the thalamic response to stimuli. In the awake state, sensory stimuli generate a linear thalamic response while cortical input to the thalamus generates a nonlinear response. And that stimulus response and information transfer are controlled by cortical input and synaptic noise, which both suppress responsiveness. In addition, synaptic noise acts as an equalizer between thalamic response at different states and diffuses state transitions between tonic-bursting and awake-sleep states. Finally, the model replicates spindles within a sleep-like state, reducing its responsiveness. This study results in new insight on the brain-state dependent function of the thalamus. In addition, the development of a novel thalamic mean-field model provides a new a tool for incorporating detailed thalamic dynamics in large scale brain simulations. This will help to bridge the gap between computational neuroscience, behavioral experiments, and the study of brain diseases.