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Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns
Andrea Maesani1, Pavan Ramdya1,2, Steeve Cruchet2
1Institute of Microengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Plos Computational Biology
|November 25, 2015
Summary
Neural activity fluctuations help control when animals start and stop moving. This research models how these fluctuations, combined with sensory input, shape complex behaviors like navigation.
Area of Science:
- Neuroscience
- Computational Biology
- Animal Behavior
Background:
- The neural basis for action timing remains unclear.
- A hypothesis suggests ongoing neural activity fluctuations in action selection circuits influence moment-to-moment behavior.
Purpose of the Study:
- To investigate how neural activity fluctuations contribute to the timing of actions.
- To model the relationship between neural dynamics, sensory input, and behavior.
Main Methods:
- High-resolution measurements of freely walking Drosophila melanogaster.
- Data-driven neural network modeling.
- Dynamical systems analysis.
Main Results:
- Fluctuation-driven network models successfully replicated Drosophila locomotor bout patterns.
- Models also reproduced complex odor-evoked walking patterns across different strains.
- Ongoing fluctuations were essential for neural activity to exceed locomotion thresholds (stochastic resonance-like effect).
- Odor stimulation shifted model equilibria, causing a decrease in locomotor frequency.
Conclusions:
- Neural activity fluctuations in action selection circuits enhance behavioral responses to sensory drive.
- Simple neural dynamics coupled with fluctuations can generate complex animal behaviors.
- This mechanism may improve navigation in complex sensory environments.
