D

Daniel Deitch

Weizmann Institute of Science

Publishes on Neuroscience and Neuropharmacology Research, Neuroinflammation and Neurodegeneration Mechanisms, Memory and Neural Mechanisms. 6 papers and 569 citations.

6Publications
569Total Citations

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Top publicationsby citations

Organization of hippocampal CA3 into correlated cell assemblies supports a stable spatial code
Liron Sheintuch, Nitzan Geva, Daniel Deitch et al.|Cell Reports|2023
Cited by 43Open Access

Hippocampal subfield CA3 is thought to stably store memories in assemblies of recurrently connected cells functioning as a collective. However, the collective hippocampal coding properties that are unique to CA3 and how such properties facilitate the stability or precision of the neural code remain unclear. Here, we performed large-scale Ca2+ imaging in hippocampal CA1 and CA3 of freely behaving mice that repeatedly explored the same, initially novel environments over weeks. CA3 place cells have more precise and more stable tuning and show a higher statistical dependence with their peers compared with CA1 place cells, uncovering a cell assembly organization in CA3. Surprisingly, although tuning precision and long-term stability are correlated, cells with stronger peer dependence exhibit higher stability but not higher precision. Overall, our results expose the three-way relationship between tuning precision, long-term stability, and peer dependence, suggesting that a cell assembly organization underlies long-term storage of information in the hippocampus.

Representational drift in the mouse visual cortex
Daniel Deitch, Alon Rubin, Yaniv Ziv|bioRxiv (Cold Spring Harbor Laboratory)|2020
Cited by 24Open Access

Abstract Neuronal representations in the hippocampus and related structures gradually change over time despite no changes in the environment or behavior. The extent to which such ‘representational drift’ occurs in sensory cortical areas and whether the hierarchy of information flow across areas affects neural-code stability have remained elusive. Here, we address these questions by analyzing large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies. We found representational drift over timescales spanning minutes to days across multiple visual areas. The drift was driven mostly by changes in individual cells’ activity rates, while their tuning changed to a lesser extent. Despite these changes, the structure of relationships between the population activity patterns remained stable and stereotypic, allowing robust maintenance of information over time. Such population-level organization may underlie stable visual perception in the face of continuous changes in neuronal responses.