A multivariate population density model of the dLGN/PGN relay |
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Authors: | Marco A Huertas Gregory D Smith |
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Institution: | (1) Department of Applied Science, College of William and Mary, Williamsburg, VA, 23187 |
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Abstract: | Using a population density approach we study the dynamics of two interacting collections of integrate-and-fire-or-burst (IFB)
neurons representing thalamocortical (TC) cells from the dorsal lateral geniculate nucleus (dLGN) and thalamic reticular (RE)
cells from the perigeniculate nucleus (PGN). Each population of neurons is described by a multivariate probability density
function that satisfies a conservation equation with appropriately defined probability fluxes and boundary conditions. The
state variables of each neuron are the membrane potential and the inactivation gating variable of the low-threshold Ca2+ current IT. The synaptic coupling of the populations and external excitatory drive are modeled by instantaneous jumps in the membrane
potential of postsynaptic neurons. The population density model is validated by comparing its response to time-varying retinal
input to Monte Carlo simulations of the corresponding IFB network composed of 100 to 1000 cells per population. In the absence
of retinal input, the population density model exhibits rhythmic bursting similar to the 7 to 14 Hz oscillations associated
with slow wave sleep that require feedback inhibition from RE to TC cells. When the TC and RE cell potassium leakage conductances
are adjusted to represent cholingergic neuromodulation and arousal of the network, rhythmic bursting of the probability density
model may either persists or be eliminated depending on the number of excitatory (TC to RE) or inhibitory (RE to TC) connections
made by each presynaptic cell. When the probability density model is stimulated with constant retinal input (10–100 spikes/sec),
a wide range of responses are observed depending on cellular parameters and network connectivity. These include asynchronous
burst and tonic spikes, sleep spindle-like rhythmic bursting, and oscillations in population firing rate that are distinguishable
from sleep spindles due to their amplitude, frequency, or the presence of tonic spikes. In this context of dLGN/PGN network
modeling, we find the population density approach using 2,500 mesh points and resolving membrane voltage to 0.7 mV is over
30 times more efficient than 1000-cell Monte Carlo simulations.
Action Editor: David Golomb |
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Keywords: | Population density model Dorsal lateral geniculate nucleus Perigeniculate nucleus Thalamocortical relay neuron Thalamic reticular neuron Burst Tonic Vision |
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