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Algorithmic dissection of optic flow memory in larval zebrafish.

Ryosuke Tanaka1, Ruben Portugues2

  • 1Institute of Neuroscience, Technical University of Munich, Biedersteiner Str. 29, 80802 Munich, Germany.

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|September 17, 2025
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Summary

Larval zebrafish visual stabilization depends on past optic flow history. External optic flow, not self-generated, influences future behavior, suggesting sensory filtering over path integration memory.

Keywords:
calcium imaginginferior oliveneural integratoroptomotor responseworking memoryzebrafish

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Sensory Processing

Background:

  • Visual stabilization in larval zebrafish is a model for working memory and decision-making.
  • The underlying algorithmic mechanisms of this history-dependent behavior are not well understood.

Purpose of the Study:

  • To investigate the algorithmic basis of history-dependent visual stabilization in larval zebrafish.
  • To determine the role of self-generated versus externally generated optic flow.
  • To elucidate the neural circuits involved in integrating optic flow over time.

Main Methods:

  • Behavioral experiments using externally and self-generated optic flow paradigms.
  • Reverse correlation and delay-based analyses to probe temporal integration.
  • Quantitative modeling of optic flow integration.
  • Whole-brain light-sheet and two-photon calcium imaging of neural activity.

Main Results:

  • Only externally generated optic flow influences future stabilization, indicating sensory low-pass filtering.
  • Multiple timescales of optic flow integration were identified, with memory decreasing in dynamic environments.
  • Optic-flow-selective neurons with motor efference copy signatures were found.
  • Inferior olive neurons were shown to integrate forward and backward flow separately.

Conclusions:

  • The study refines the understanding of history dependence in visual stabilization.
  • Findings suggest sensory filtering and multiple integration timescales are key.
  • Neural correlates for optic flow integration and its history dependence were identified, offering insights into circuit implementation.