Developing a computational theory for the cognitive thalamus
The thalamus is the major input to the cortex and interactions between the two structures are critical for sensation, action and cognition. In addition to its known function in relaying sensory input, recent studies have shown a separate role for the thalamus in regulating task-related cortical dynamics. Specifically, experiments in animals, including humans, have shown that both the pulvinar and mediodorsal thalamus regulate functional connectivity within and across the cortical areas they innervate, making them indispensable for tasks involving attention and working memory. Ongoing experiments across several laboratories are identifying the mechanisms responsible for these thalamic functions, yet a theoretical foundation for why the brain contains a thalamus in the first place is lacking. Specifically, although state-of-the-art machine learning models that solve computationally-challenging tasks have drawn inspiration from the structure of the mammalian neocortex, they have not yet incorporated a thalamus-like architecture. This may be a missed opportunity since the associative parts of the thalamus (which we refer to as the cognitive thalamus), have experienced evolutionary expansion equivalent to their cortical counterparts.
Mar 30–Aug 16, 2019
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Department of Brain & Cognitive Sciences
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