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A compact multisensory representation of self-motion is sufficient for computing an external world variable.

Christina E May1, Benjamin Cellini2, Floris van Breugel2

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Flies can infer wind direction using multi-sensory integration in their navigation center (PFNs). This active sensing allows them to estimate external forces not directly measured by a single sense.

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Area of Science:

  • Neuroscience
  • Animal Behavior
  • Sensory Integration

Background:

  • Animals navigate using external forces, but direct measurement is impossible.
  • The brain's integration of multi-modal cues for force estimation is not well understood.

Purpose of the Study:

  • Investigate multi-modal self-motion cue representation in fly PFNs.
  • Determine how neural circuits encode sensory information for inferring external forces.

Main Methods:

  • Recorded neural responses to optic flow and airflow.
  • Developed computational models of sensory encoding.
  • Applied nonlinear observability analysis to neural data.

Main Results:

  • One type of PFN integrates optic flow and airflow with distinct dynamics.
  • A separate PFN type encodes airspeed.
  • PFN activity during maneuvers allows decoding of external wind direction.

Conclusions:

  • Active sensation and multisensory encoding enable inference of unmeasurable external properties.
  • Compact nervous systems can infer environmental forces through integrated sensory processing.