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, because 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 noninhibitory neurons in a mouse expressing Venus under the control of the VGAT promoter. We then 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 with 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) result 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 with convergence of randomly selected afferent input, and 3) inhibition narrowed the BOT to more realistically model the in vivo rNST data. NEW & NOTEWORTHY Using a combination of in vivo and in vitro neurophysiology together with conductance-based modeling, we show how patterns of convergence and inhibition interact in the rostral (gustatory) solitary nucleus to maintain signal fidelity. Although increasing convergence led to a systematic increase in firing frequency, tuning specificity was maintained with a pattern of afferent inputs sharing the best-stimulus compared with random inputs. Tonic inhibition further enhanced response fidelity.