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The brain's memory function involves patterns of neural population spiking activity, shaped by experience and recurring over time. These neural population patterns are typically studied with respect to the three stages of acquisition, retention, and retrieval. Despite intensive investigation, the relationship between the features of population activity and the properties, computations, and codes for memory remains elusive. In this perspective, we synthesize recent advances in the study of memory from the viewpoint of brain network physiology, aiming for a comprehensive mapping between the properties and computations of memory and the features of population-activity codes. We propose that brain memory circuits implement trade-offs between conflicting demands on population codes. We anticipate that an important challenge for both discovery and translational neuroscience of memory is to study these trade-offs, delineating a safe zone in the population-activity space where neuronal circuits operate efficiently.
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Dupret et al. (2025) studied this question.
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