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Context, Computation, and Continuity: Neural Mechanisms of Memory and Decision-Making

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How does the brain achieve both stability and flexibility in behavior? In this journal club, we will explore two recent studies that illuminate distinct yet interconnected neural mechanisms underlying long-term motor memory and flexible decision-making. The first paper (Kim et al., Nature, 2024) demonstrates that motor memories are encoded in a combinatorial, context-specific manner in the motor cortex of mice. Using long-term two-photon imaging, the authors show that new motor skills are acquired without overwriting old ones, as new preparatory activity patterns emerge in parallel across contexts—offering a robust mechanism for continual learning. The second paper (Pagan et al., Nature, 2024) investigates how individual variability shapes context-dependent decision-making in rats. The authors develop a behavioral paradigm and theoretical framework revealing three distinct dynamical strategies for evidence accumulation, all capable of supporting flexible behavior. Strikingly, different individuals express different combinations of these strategies, despite similar performance, highlighting substantial neural and computational diversity. Optionally, we will also discuss findings from a third study (Mishchanchuk et al., Science, 2024), which reveals how the ventral hippocampus encodes abstract contextual states critical for hidden state inference. This study complements the others by highlighting the importance of hippocampal representations in decision-making based on latent contexts. Together, these studies provide a compelling picture of how the brain balances flexibility and stability through context-specific encoding, diverse computational strategies, and abstract contextual inference—shedding light on the neural basis of learning, memory, and cognition.

This talk is part of the Computational Neuroscience series.

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