Computational mechanisms underlying thalamic regulation of prefrontal signal-to-noise ratio in decision making

Abstract

The mediodorsal (MD) thalamus is a critical partner for the prefrontal cortex (PFC) in cognitive flexibility. Accumulating evidence has shown that the MD regulates task uncertainty in decision making. However, the mechanism of this cognitive process remains unclear. Here we used a reverse-engineering approach and trained biologically-constrained computational models to delineate these mechanisms. We found that the inclusion of an MD-like feedforward module increased robustness to sensory noise, enhanced working memory and enabled rapid context switching in the recurrent PFC network performing two versions of context-dependent decision-making tasks with sensory and mapping uncertainties. Incorporating genetically identified thalamocortical pathways and interneuron cell types replicated neurophysiological findings of neuronal tuning and uncovered attractor-like population dynamics. Our model revealed key computational mechanisms of context-invariant MD in regulating cueing uncertainty and context switching. It also made experimentally testable predictions linking cognitive deficits with disrupted thalamocortical connectivity, prefrontal excitation-inhibition imbalance and dysfunctional inhibitory cell types.