Thalamocortical Interactions for Flexible Cognition

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• Rui Xia; Daniel Kornai
• Tuesday 21 October 2025, 13:15-12:45
• CBL Seminar Room, Engineering Department, 4th floor Baker building.

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There has been an emerging view that the thalamus act as a central hub for coordinating distributed cortical computations, shaping how the brain flexibly transitions between cognitive states. In this journal club, we will begin by providing an overview [1] of the thalamus as a central regulator of large-scale brain dynamics, influencing cognitive processes such as attention, awareness, and adaptive behavior. Building on this framework, we present an experimental study (Lam, et al) [2] that examines how the mediodorsal thalamus (MD) contributes to uncertainty-guided decision-making. Using recordings from tree shrews performing a hierarchical decision task with rule reversals, the study finds that distinct MD populations encode cueing and rule uncertainty separately. This representation enables the thalamus to drive prefrontal reconfiguration following behavioral errors, supporting adaptive switching through a trans-thalamic pathway linking cingulate and prefrontal cortex. Complementing these findings, Zheng et al [3] presents a circuit-level model of the PFC –MD loop that implements rapid, online context inference via Hebbian plasticity. They show how incorporation of biological properties of thalamocortical circuits can alleviates catastrophic forgetting and enable transfer of knowledge to novel contexts. Together, these perspectives converge on a view of the thalamus as an active computational hub supporting flexible cognition through dynamic interactions with prefrontal circuits.

[1] Shine, J. M. (2021). The thalamus integrates the macrosystems of the brain to facilitate complex, adaptive brain network dynamics. Progress in neurobiology, 199, 101951. [2] Lam, N. H., Mukherjee, A., Wimmer, R. D., Nassar, M. R., Chen, Z. S., & Halassa, M. M. (2025). Prefrontal transthalamic uncertainty processing drives flexible switching. Nature, 637(8044), 127-136. [3] Zheng, W. L., Wu, Z., Hummos, A., Yang, G. R., & Halassa, M. M. (2024). Rapid context inference in a thalamocortical model using recurrent neural networks. Nature Communications, 15(1), 8275.

This talk is part of the Computational Neuroscience series.

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