The effects of long-range coupling on neural activity in the crayfish swimmeret system
Mathematical Biosciences Institute, The Ohio State University
(April 3, 2014 10:20 AM - 11:15 AM)
During forward swimming of crayfish, four pairs of limbs called swimmerets swing rhythmically through power and return strokes. Neighboring limbs move in a back to front metachronal wave with a delay of approximately 25% of the period. Interestingly, this posterior to anterior progression is maintained over the entire range of behaviorally relevant stroke frequencies. Previous work has modeled the neural circuitry coordinating this motion as a chain of nearest neighbor coupled oscillators, and it was shown that the architecture of this circuitry could provide a robust mechanism for this behavior. However, this study ignored the presence of weaker longer range coupling between oscillators, and how the coupling affects this mechanism is unknown.
In this talk, I will discuss the role of the long range coupling in the swimmeret system. An analytical argument using a phase model suggests that the presence of long range coupling speeds up the metachronal wave when the connection strength is sufficiently weak. Numerical simulations show that this effect extends to larger connection strengths. Further, we confirm these predictions in a more detailed conductance-based neuronal model. Finally, we verify the validity of the model by comparing results from the phase model to experiments that probe the effects of long range coupling.
Combined with results from a computational fluid dynamics model, our findings indicate that the long range coupling might exist to ensure that the crayfish’s limb movement during forward swimming is in an optimally efficient regime.