Information Processing and Synchronization in the Thalamo-Reticular System by Beta Phase Coding in a Model of Neural Oscillators

Information in the brain is suggested to be coded by either the firing rate or the relative timing of neuronal activity. Temporal coding is particularly relevant to brain structures with strong oscillatory behavior, such as the thalamo-cortical system or the hippocampus. The thalamus has a key position in information processing in the brain: First, it is the major gateway for sensory information to the cortex. Second, thalamo-cortical pathways are reciprocated by massive feedback connections from the cortex back to the thalamus. Thalamic relay neurons are coupled to cortical neurons, as well as to the inhibitory neurons of the reticular nucleus of the thalamus and the resulting reciprocal interactions generate synchronous oscillatory patterns in the thalamo-cortical system depending on input frequencies, phase deviations, and delay time. In the present work we have studied a simple neural network model of the thalamo-reticular system based on the Wilson-Cowan model of neuronal oscillatory behavior and show how different input patterns result in several spatio-temporal patterns of synchronous activity. A main finding of the numerical simulations is that the network connectivity and the intrinsic oscillatory properties result in distinct characteristic, collective spatio-temporal behavior within the network. By varying the connectivity schemes comparable with lesioned or damaged brain regions, our results are in good agreement with experimental results. For example, it could be seen that the sensory input and the cortical feedback are essential for an information processing in the thalamo-reticular system. Suppressing the sensory input results in temporal oscillatory activity in the beta and gamma range and a strong spatial dependence of the network dynamics.

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