Frequency response of lift control inDrosophila

Abstract

The flight control responses of the fruitfly represent a powerful model system to explore neuromotor control mechanisms, whose system level control properties can be suitably characterized with a frequency response analysis. We characterized the lift response dynamics of tethered flying Drosophila in presence of vertically oscillating visual patterns, whose oscillation frequency we varied between 0.1 and 13 Hz. We justified these measurements by showing that the amplitude gain and phase response is invariant to the pattern oscillation amplitude and spatial frequency within a broad dynamic range. We also showed that lift responses are largely linear and time invariant (LTI), a necessary condition for a meaningful analysis of frequency responses and a remarkable characteristic given its nonlinear constituents. The flies responded to increasing oscillation frequencies with a roughly linear decrease in response gain, which dropped to background noise levels at about 6 Hz. The phase lag decreased linearly, consistent with a constant reaction delay of 75 ms. Next, we estimated the free-flight response of the fly to generate a Bode diagram of the lift response. The limitation of lift control to frequencies below 6 Hz is explained with inertial body damping, which becomes dominant at higher frequencies. Our work provides the detailed background and techniques that allow optomotor lift responses of Drosophila to be measured with comparatively simple, affordable and commercially available techniques. The identification of an LTI, pattern velocity dependent, lift control strategy is relevant to the underlying motion computation mechanisms and serves a broader understanding of insects' flight control strategies. The relevance and potential pitfalls of applying system identification techniques in tethered preparations is discussed.

Flight control of fruit flies: dynamic response to optic-flow and headwind

“…Dickinson et al, 1998;Graetzel et al, 2010;Straw et al, 2010). In this study, we measure the thrust of the flies exposed to a horizontally oscillating stimulus, as horizontal motion is more dominant and natural for flying insects.…”

Investigating Maneuverability, Stability and Control of Flapping Flight

“…Understanding roll control however, requires fast and accurate quantitative measurements of wing and body kinematics in response to controlled midair perturbation impulses -a methodology recently applied to study yaw control [32]. Crucially, these previous works typically consider only the linear response [29,[32][33][34][35][36][37][38]. Whether non-linear mechanisms come into play in natural free flight, where both large and coupled perturbations are common [1] remains unknown.…”

Vision-based flight control in the hawkmothHyles lineata

“…(a) Diagram of the virtual-reality flight simulator. Wide-field visual stimuli were provided by two modified data projectors (1,2) projecting via a system of mirrors (3,4), onto a hollow acrylic sphere coated with rear-projection paint (5). (b) The moth was tethered at the centre of the sphere to a six-component force -moment balance (6).…”

“…The feedback control systems of insects have presumably evolved in concert with their flight morphology to achieve the same ends, but physiological studies of insect flight control have been largely divorced from physical studies of insect flight dynamics. Recent efforts combining modelling approaches with measurements of motor outputs have begun to bridge this gap [1][2][3][4][5][6][7][8], but whereas the physiology of insect flight control is understood well from a mechanistic perspective, it remains poorly understood on a functional level. In this study, we characterize the optomotor response properties of hawkmoths experimentally, before relating these properties functionally to flight stabilization and control with the aid of a published model of hawkmoth flight dynamics.…”

“…Here, we measure all six components of force and moment produced in response to rotation of the entire visual field about three orthogonal axes, and use these measurements to characterize the overall response properties of the optomotor control system. Frequency domain approaches have been used successfully to characterize optomotor responses in a number of other insects [1,3,7,8,12,14], and we follow the same basic approach here. Having characterized the optomotor responses experimentally, we use a published theoretical flight dynamics model [23][24][25] to predict the natural flight dynamics of the insect (i.e.…”