Awake alpha bursting emerges as the dynamic working state in a lateral geniculate thalamocortical cell model

Abstract

The awake thalamus is known to be able to filter primary sensory input with and without external modulation. Through the construction and analysis of a novel computational model of a lateral geniculate thalamocortical neuron, we demonstrate how the processing of sensory retinal input is influenced by the underlying thalamic dynamic state. Our model, using only currents verified against expression data from publicly available datasets, is the first to produce five experimentally established distinct dynamic firing regimes. We demonstrate that the thalamocortical cell transitions between these dynamic states in response to glutamatergic signals from the cortex or cholinergic arousal signals coming from the brainstem. We focus on signal processing in the model dynamic states associated with the awake thalamic alpha rhythm where we find that the ability of retinal inputs to generate thalamic spikes is a balance between the timing of retinal spikes, the excitability break imposed by the M-current, and the decay time of the L-type calcium current. Finally, we explore how these two currents help the thalamus process extra-retinal rhythmic inputs, showing the model produces entrainment to slower inhibitory and excitatory rhythms, as well as detailing the importance of nesting faster frequency rhythms within slow cycles for successful thalamic transmission. Our results suggest that the awake alpha rhythm is indirectly causal by acting as a marker for the interaction of these two currents. This biophysically-constrained lateral geniculate thalamocortical cell model generates predictions regarding rhythmic dynamics under different arousal states, thalamic control of retinogeniculate transmission, and the possible impacts neurological disorders, like schizophrenia, have on thalamic processing. Variations of this model could be used to explore the functions of higher order thalamic nuclei, thereby extending its use to investigating more complex cognitive processes. Author summaryThe thalamus generates multiple distinct brain rhythms, processes primary sensory inputs, and modulates its output using feedback signals. Previous computational models of the thalamus have typically focused on a subset of these three thalamic functions without drawing relationships among them. Here we present a novel computational thalamic cell model that unites these thalamic processes. We focus on the awake alpha rhythm, a well known thalamic oscillation, and show that it is a signature of a critical working state that enables the experimentally observed thalamic filtering of retinal signals. Additionally, we find this state is optimal for processing and passing non-sensory rhythmic signals. Our model generates testable predictions about which ionic currents control the transmission of external signals. It highlights the roles of two currents from our model that do not have specified functions in the awake thalamus in previous computational models. The work concludes with hypotheses about why neurological disorders that perturb the thalamus from this alpha rhythm working state lead to significant processing errors locally within the thalamus and globally within the brain.