Decompositions of Behavioral Modulations and Run Shapes in Drosophila Larvae
ORAL
Abstract
With its small size and limited motor tool set, the Drosophila larva is a good system for studying how animals alter their behavior to reach optimal conditions. We aim to distinguish behavioral modulations caused by the physical effects of temperature from those due to sensory input and to decompose curved runs (bouts of forward crawling) into run-shape eigenvectors.
To decouple the causes of behavioral modulation, we use temperature-insensitive mutants and 3 different spatiotemporal stimulus environments; PID controllers maintain the different spatial and temporal gradients. Many larvae are recorded during free navigation and computer vision software segments trajectories into alternating sequences of runs and turns, analogous to classic 2D random walks. The turn rate is the dominant characteristic of diffusive processes and larvae primarily achieve navigation by modulating it. Monte-Carlo simulations allow for comparison with experimental data and for analysis of otherwise unfeasible experiments.
Our results suggest that larvae exhibit different average speeds due to physical changes, and exhibit different turn rates because of both physical changes and sensory input. Computational methods are currently being explored for use in decomposing runs into run-shape eigenvectors.
To decouple the causes of behavioral modulation, we use temperature-insensitive mutants and 3 different spatiotemporal stimulus environments; PID controllers maintain the different spatial and temporal gradients. Many larvae are recorded during free navigation and computer vision software segments trajectories into alternating sequences of runs and turns, analogous to classic 2D random walks. The turn rate is the dominant characteristic of diffusive processes and larvae primarily achieve navigation by modulating it. Monte-Carlo simulations allow for comparison with experimental data and for analysis of otherwise unfeasible experiments.
Our results suggest that larvae exhibit different average speeds due to physical changes, and exhibit different turn rates because of both physical changes and sensory input. Computational methods are currently being explored for use in decomposing runs into run-shape eigenvectors.
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Presenters
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Joseph Shomar
Physics, University of Miami, University of Miami
Authors
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Joseph Shomar
Physics, University of Miami, University of Miami
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Anggie Ferrer
Physics, University of Miami, University of Miami
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Joshua Forer
Physics, University of Miami, University of Miami
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Tom Zhang
University of Miami
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Mason Klein
University of Miami, Physics, University of Miami