Abstract
Animals rely on sensory feedback to generate accurate, reliable movements. In many flying insects, strain-sensitive neurons on the wings provide rapid feedback that is critical for stable flight control. While the impacts of wing structure on aerodynamic performance have been widely studied, the impacts of wing structure on sensing are largely unexplored. In this paper, we show how the structural properties of the wing and encoding by mechanosensory neurons interact to jointly determine optimal sensing strategies and performance. Specifically, we examine how neural sensors can be placed effectively on a flapping wing to detect body rotation about different axes, using a computational wing model with varying flexural stiffness. A small set of mechanosensors, conveying strain information at key locations with a single action potential per wingbeat, enable accurate detection of body rotation. Optimal sensor locations are concentrated at either the wing base or the wing tip, and they transition sharply as a function of both wing stiffness and neural threshold. Moreover, the sensing strategy and performance is robust to both external disturbances and sensor loss. Typically, only five sensors are needed to achieve near-peak accuracy, with a single sensor often providing accuracy well above chance. Our results show that small-amplitude, dynamic signals can be extracted efficiently with spatially and temporally sparse sensors in the context of flight. The demonstrated interaction of wing structure and neural encoding properties points to the importance of understanding each in the context of their joint evolution.
Highlights
The physical structure of an animal’s body transforms the incoming sensory information and can either facilitate or constrain sensing capacity
While much is known about how wing structure affects aerodynamic performance, the effects of wing structure on sensing remain unexplored
Using a computational model of a flapping wing, we examine how sensing strategies depend on wing stiffness and sensor properties
Summary
The physical structure of an animal’s body transforms the incoming sensory information and can either facilitate or constrain sensing capacity. Body parts in many systems serve to preprocess sensory inputs in ways that are beneficial for the organism, extracting relevant features and reducing downstream computational burdens. In systems that rely on mechanosensation in particular, there is a large body of work pointing to the importance of structure in preprocessing sensory inputs (reviewed in [3]). There may be structural limits that constrain the numbers and locations of sensory receptors. The physical properties of non-neural structures play an important role in determining how stimuli are experienced and transduced by sensory receptors embedded in the body
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