Wing structure and neural encoding jointly determine sensing strategies in insect flight

Area of Science:

• Biomechanics
• Neuroethology
• Insect flight dynamics

Background:

• Animals use sensory feedback for accurate movement generation.
• Mechanosensory neurons on insect wings provide critical flight control feedback.
• The impact of wing structure on sensory feedback remains underexplored.

Purpose of the Study:

• To investigate the interplay between wing structural properties and mechanosensory neuron encoding.
• To determine optimal strategies for sensor placement on flapping wings for detecting body rotation.
• To understand how wing stiffness and neural thresholds influence sensing performance.

Main Methods:

• Utilized a computational wing model with variable flexural stiffness.
• Simulated the placement of mechanosensors to detect body rotation about different axes.
• Analyzed the impact of sensor location, wing stiffness, and neural thresholds on sensing accuracy.

Main Results:

• A small set of mechanosensors at key locations (wing base or tip) enable accurate body rotation detection.
• Optimal sensor placement shifts based on wing stiffness and neural thresholds.
• Sensing strategy is robust to external disturbances and sensor loss, with few sensors achieving high accuracy.

Conclusions:

• Wing structure and neural encoding jointly determine effective flight sensing strategies.
• Spatially and temporally sparse sensors can efficiently extract dynamic flight signals.
• Understanding the co-evolution of wing structure and neural sensing is crucial for flight control research.