The brain in motion: How ensemble fluidity drives memory-updating and flexibility
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Updated: Nov 23, 2025

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
Published on: March 8, 2024
William Mau1, Michael E Hasselmo2, Denise J Cai1
1Neuroscience Department, Icahn School of Medicine at Mount Sinai, New York, United States.
Abstract:
While memories are often thought of as flashbacks to a previous experience, they do not simply conserve veridical representations of the past but must continually integrate new information to ensure survival in dynamic environments. Therefore, 'drift' in neural firing patterns, typically construed as disruptive 'instability' or an undesirable consequence of noise, may actually be useful for updating memories. In our view, continual modifications in memory representations reconcile classical theories of stable memory traces with neural drift. Here we review how memory representations are updated through dynamic recruitment of neuronal ensembles on the basis of excitability and functional connectivity at the time of learning. Overall, we emphasize the importance of considering memories not as static entities, but instead as flexible network states that reactivate and evolve across time and experience.
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