A new paper in PLoS Computational Biology from Washington Research Foundation postdoctoral fellow Ali Weber and CNC faculty members Tom Daniel and Bing Brunton examines how insect wing structure and mechanosensory neurons together determine optimal sensing performance during flight. Insects require sensory feedback to maintain stable flight. The team noted that while the mechanical properties of insect wings have been studied extensively, we have little understanding of the forces driving the evolution of sensing strategies in wings. Optimization of sensing strategy during flight is of major interest to engineers for building efficient and lightweight aircraft.

The team created a computational model of a flapping wing that allowed them to vary mechanical properties, like wing stiffness, and neural encoding properties, such as the threshold to set off a neuron spike. They investigated how wing structure and neural encoding interact to determine the optimal placement of sensory neurons and the accuracy with which body rotations can be detected during flight.

They found a complex and nonintuitive interaction between wing stiffness and neural threshold that determines sensor placement near either the wing base or wing tip. Moreover, they show that sensors at different locations on the wing are equally robust to multiple kinds of perturbation, suggesting that a need for resilience to sensor loss or disturbance is not a primary driver of the location of these sensory neurons. This work is a first step towards understanding how wing structure drives incoming sensory information and sensing strategy.