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The serotonergic system tracks the outcomes of actions to mediate short-term motor learning (Software)

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The serotonergic system tracks the outcomes of actions to mediate short-term motor learning (Software)

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The serotonergic system tracks the outcomes of actions to mediate short-term motor learning (Software)

This directs to a repository for the analysis algorithms used in Kawashima et al., Cell, 2016.

Folder list

  1. cell-detection -> a Matlab code set for detecting cells expressing nuclear-localized GCaMP
  2. image-registration -> a C/CUDA code set for correcting 2D translations of individual Z-plane time series.
  3. motion-estimation -> a Matlab code set for inferring 3-dimensional deformation in the time series

Each code set contains small sample data for testing. Input parameters were optimized for this sample dataset.

Abstract

To execute accurate movements, animals must continuously adapt their behavior to changes in their bodies and environments. For example, animals can learn changes in the relationship between their locomotor commands and the resulting distance moved, then adjust command strength to achieve a desired travel distance. It is largely unknown which circuits implement this form of motor learning or how. Using whole-brain neuronal imaging and circuit manipulations in larval zebrafish, we discovered that the serotonergic dorsal raphe nucleus (DRN) mediates short-term locomotor learning. Serotonergic DRN neurons respond phasically to swim-induced visual motion but little to motion that is not self-generated. During prolonged exposure to a given motosensory gain, persistent DRN activity emerges that stores the learned efficacy of motor commands and adapts future locomotor drive for tens of seconds. The DRN’s ability to track the effectiveness of motor intent may constitute a computational building block for the broader functions of the serotonergic system.

 

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Contact

Michael Perham
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