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Dryad

Systematic characterization of wing mechanosensors that monitor airflow and wing deformations

Cite this dataset

Fabian, Joseph et al. (2022). Systematic characterization of wing mechanosensors that monitor airflow and wing deformations [Dataset]. Dryad. https://doi.org/10.5061/dryad.h18931zns

Abstract

Animal wings deform during flight in ways that can enhance lift, facilitate flight control, and mitigate damage. Monitoring the structural and aerodynamic state of the wing is challenging because deformations are passive, and the flow fields are unsteady; it requires distributed mechanosensors that respond to local airflow and strain on the wing. Without a complete map of the sensor arrays, it is impossible to model control strategies underpinned by them. Here, we present the first systematic characterization of mechanosensors on the dragonfly’s wings: morphology, distribution, and wiring. By combining a cross-species survey of sensor distribution with quantitative neuroanatomy and a high-fidelity finite element analysis, we show that the mechanosensors are well-placed to perceive features of the wing dynamics relevant to flight. This work describes the wing sensory apparatus in its entirety and advances our understanding of the sensorimotor loop that facilitates exquisite flight control in animals with highly deformable wings.

 

Methods

Data includes raw measurements of dragonfly wing mechanosensors. Values were measured from confocal microscope images using fiji.

Funding

Biotechnology and Biological Sciences Research Council, Award: BB/R002509/1

Biotechnology and Biological Sciences Research Council, Award: BB/R002657/1