Topic: corticothalamic projections

Animals thrive in a constantly changing environment and leverage the temporal structure to learn well-factorized causal representations. In contrast, traditional neural networks have no representation of these changes and suffer from forgetting. In the prefrontal-thalamic circuit, reciprocal feedback connections produce a compressed thalamic representation of the computations performed in the prefrontal cortex. In inspiration, we use a neural network with a separate latent task representation and introduce a simple algorithm that uses optimization to rapidly infer and generate representations

Planning, a prospective form of short-term memory, is a cognitive function that has been predominantly attributed to the cortex. Recent experiments, however, have concluded that the thalamus and other subcortical structures participate in this function. A comprehensive computational framework to link neural dynamics and cognition in the context of large-scale subcortical-cortical circuits is lacking. In this computational study, we elucidated the dynamical mechanisms by which the cortex, thalamus and other subcortical structures jointly contribute to planning. Recurrent circuitry in the cort