@article {70195,
	title = {Structural dynamics and neural representation of wing deformation.},
	journal = {Proc Natl Acad Sci USA},
	volume = {122},
	year = {2025},
	month = {2025 Nov 18},
	pages = {e2518032122},
	abstract = {<p>Locomotor control is facilitated by mechanosensory inputs that report how the body interacts with a physical medium. Effective representation of compliant wing deformations is particularly challenging due to the many degrees of freedom. Structural configurations can constrain the stimulus space, and strategic placement of sensors can simplify computation. Here, we measured and modeled wing displacement fields and characterized spatiotemporal encoding of the wing mechanosensors. Our data show how dragonfly wing architecture prescribes deformation modes consistent across models and measurements. We found that the wing{\textquoteright}s state under normal flapping conditions is detected by the spike timing of few sensors, with additional sensors recruited under perturbation. The functional integration of wing biomechanics and sensor placement enables a straightforward solution for information transfer.</p>
},
	keywords = {Animals, Biomechanical Phenomena, Flight, Animal, Models, Biological, Odonata, Wings, Animal},
	issn = {1091-6490},
	doi = {10.1073/pnas.2518032122},
	url = {https://doi.org/10.1073/pnas.2518032122},
	author = {Yarger, Alexandra M and Maeda, Masateru and Siwanowicz, Igor and Kajiyama, Haruhiro and Walker, Simon M and Bomphrey, Richard J and Lin, Huai-Ti}
}
@article {69484,
	title = {Mechanosensory representation of wing deformations},
	journal = {bioRxiv},
	year = {2024},
	month = {2024 Jun 02},
	abstract = {<p>Efficient representation of structural deformations is crucial for monitoring the instantaneous state of biological structures. Insects{\textquoteright} ability to encode wing deformations during flight demonstrates a general morphological computing principle applicable across sensory systems in nature as well as engineered systems. To characterize how relevant features are encoded, we measured and modelled displacement and strain across dragonfly wing surfaces in tethered and free flight. Functional interpretations were supported by neuroanatomical maps, and ablation and perturbation experiments. We find that signal redundancy is reduced by non-random sensor distributions and that morphology limits the stimulus space such that sensory systems can monitor natural states with few sensors. Deviations from the natural states are detected by a flexible population of additional sensors with many distinguishable activation patterns.</p>
},
	doi = {10.1101/2024.06.02.596338},
	url = {https://www.biorxiv.org/content/early/2024/06/02/2024.06.02.596338},
	author = {Yarger, Alexandra M and Maeda, Masateru and Siwanowicz, Igor and Kajiyama, Haruhiro and Walker, Simon M and Bomphrey, Richard J and Lin, Huai-Ti}
}
