Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs—locomotor bouts—matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior.Author Summary: The brain is never quiet. Even in the absence of environmental cues, neurons receive and produce an ongoing barrage of fluctuating signals. These fluctuations are well studied in the sensory periphery but their potential influence on central circuits and behavior are unknown. In particular, activity fluctuations in action selection circuits—neural populations that drive an animal’s actions from moment to moment—may strongly influence behavior. To shed light on the influence of activity fluctuations on action timing, we developed a computational approach for automatically generating neural network models that reproduce large-scale, high-resolution behavioral measurements of freely walking Drosophila melanogaster. We found that models require stochastic activity fluctuations to reproduce complex Drosophila locomotor patterns. Specific fluctuation-driven dynamics allow these models to produce short and long bouts of locomotion in the absence of sensory cues and to reduce locomotor activity after sensory stimulation. These results support a role for ongoing activity fluctuations in the timing of animal behavior and reveal how behavioral shifts can be brought about through changes in the dynamics of neural circuits. Thus, simple dynamical mechanisms may underlie complex patterns of animal behavior.