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A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Eye Movement Monitoring of Memory
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Representational drift as the consequence of ongoing memory storage.

Federico Devalle1, Licheng Zou1, Gloria Cecchini1

  • 1Centre de Recerca Matemàtica, Campus de Bellaterra, Edifici C, 08193, Bellaterra, Barcelona, Spain.

Scientific Reports
|July 30, 2025
PubMed
Summary
This summary is machine-generated.

New memory storage causes existing memories to fade, a process called representational drift. This study shows synaptic turnover in neural networks explains this memory overwriting, a common phenomenon in learning.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Memory Research

Background:

  • Biologically constrained synaptic plasticity is crucial for memory formation.
  • Theoretical studies show new memory storage can overwrite existing memories.
  • Representational drift (RD) is the decorrelation of neural activity patterns over time during memory storage.

Purpose of the Study:

  • To test the hypothesis that representational drift is an inevitable consequence of ongoing memory storage.
  • To investigate the role of synaptic turnover in neuronal representational drift.

Main Methods:

  • Developed a network model incorporating synaptic turnover.
  • Fitted the model to long-term chronic calcium imaging data from mouse hippocampus.
  • Analyzed the model's ability to replicate observed RD statistics.

Main Results:

  • Synaptic turnover in model inputs successfully accounted for the observed statistics of representational drift.
  • This mechanism provided a parsimonious explanation for diverse experimental findings on experience-dependent drift.
  • The model demonstrated how ongoing memory encoding leads to representational drift.

Conclusions:

  • Representational drift is an expected outcome of ongoing memory storage in neuronal circuits.
  • Synaptic turnover is a key mechanism driving representational drift.
  • This finding has broad implications for understanding learning and memory across different neural systems.