title: A population-based model of the nonlinear dynamics of the thalamocortical feedback network displays intrinsic oscillations in the spindling (7-14 Hz) range.
abstract: The thalamocortical network is modelled using the Wilson-Cowan equations for neuronal population activity. We show that this population model with biologically derived parameters possesses intrinsic nonlinear oscillatory dynamics, and that the frequency of oscillation lies within the spindle range. Spindle oscillations are an early sleep oscillation characterized by high-frequency bursts of action potentials followed by a period of quiescence, at a frequency of 7-14 Hz. Spindles are generally regarded as being generated by intrathalamic circuitry, as decorticated thalamic slices and the isolated thalamic reticular nucleus exhibit spindles. However, the role of cortical feedback has been shown to regulate and synchronize the oscillation. Previous modelling studies have mainly used conductance-based models and hence the mechanism relied upon the inclusion of ionic currents, particularly the T-type calcium current. Here we demonstrate that spindle-frequency oscillatory activity can also arise from the nonlinear dynamics of the thalamocortical circuit, and we use bifurcation analysis to examine the robustness of this oscillation in terms of the functional range of the parameters used in the model. The results suggest that the thalamocortical circuit has intrinsic nonlinear population dynamics which are capable of providing robust support for oscillatory activity within the frequency range of spindle oscillations.
authors.affiliation: Centre for Theoretical and Computational Neuroscience, University of Plymouth, A223 Portland Square, Drake Circus, Plymouth PL4 8AA, UK. nada.yousif@plymouth.ac.uk
authors.forename: Nada A B
authors.initials: NA
authors.lastname: Yousif
authors.forename: Michael
authors.initials: M
authors.lastname: Denham
mesh_terms: D000818:Animals; D001683:Biological Clocks / Q000502:physiology*; D002540:Cerebral Cortex / Q000502:physiology*; D005246:Feedback / Q000502:physiology; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000502:physiology*; D017711:Nonlinear Dynamics; D013788:Thalamus / Q000502:physiology*; D013997:Time Factors