A Computational Analysis of Signal Fidelity in the Rostral Nucleus of the Solitary Tract

Neurons in the rostral nucleus of the solitary tract (rNST) convey taste information to both local circuits and pathways destined for forebrain structures. This nucleus is more than a simple relay, however, since rNST neurons differ in response rates and tuning curves relative to primary afferent fibers. To systematically study the impact of convergence and inhibition on firing frequency and breadth of tuning (BOT) in rNST, we constructed a mathematical model of its two major cell types: projection neurons and inhibitory neurons. First, we fit a conductance-based neuronal model to data derived from whole-cell patch clamp recordings of inhibitory and and non-inhibitory neurons in a mouse expressing VENUS under the control of the VGAT promoter. Then we used in vivo chorda tympani (CT) taste responses as afferent input to modeled neurons and assessed how the degree and type of convergence influenced model cell output frequency and BOT for comparison to in vivo gustatory responses from the rNST. Finally, we assessed how presynaptic and postsynaptic inhibition impacted model cell output. The results of our simulations demonstrated (1) increasing numbers of convergent afferents (2-10) results in a proportional increase in best-stimulus firing frequency but only a modest increase in BOT, (2) convergence of afferent input selected from the same best-stimulus class of CT afferents produced a better fit to real data from the rNST compared to convergence of randomly selected afferent input, (3) inhibition narrowed the BOT to more realistically model the in vivo rNST data.

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