Journal of Neuroscience Methods 171 (2008) 110–117 Contents lists available at ScienceDirect Journal of Neuroscience Methods journal homepage: www.elsevier.com/locate/jneumeth TrackFly: Virtual reality for a behavioral system analysis in free-flying fruit flies Steven N. Fry a,b,∗ , Nicola Rohrseitz b , Andrew D. Straw c , Michael H. Dickinson c a Institute of Robotics and Intelligent Systems, ETH Z¨ urich, Switzerland b Institute of Neuroinformatics, ETH/University of Z¨ urich, Switzerland c California Institute of Technology, Pasadena CA, USA article info Article history: Received 25 January 2008 Received in revised form 22 February 2008 Accepted 26 February 2008 Keywords: Virtual reality Tracking Insects Drosophila Vision Behavior Flight Control abstract Modern neuroscience and the interest in biomimetic control design demand increasingly sophisticated experimental techniques that can be applied in freely moving animals under realistic behavioral condi- tions. To explore sensorimotor flight control mechanisms in free-flying fruit flies (Drosophila melanogaster), we equipped a wind tunnel with a Virtual Reality (VR) display system based on standard digital hardware and a 3D path tracking system. We demonstrate the experimental power of this approach by example of a ‘one-parameter open loop’ testing paradigm. It provided (1) a straightforward measure of transient responses in presence of open loop visual stimulation; (2) high data throughput and standardized mea- surement conditions from process automation; and (3) simplified data analysis due to well-defined testing conditions. Being based on standard hardware and software techniques, our methods provide an affordable, easy to replicate and general solution for a broad range of behavioral applications in freely moving animals. Particular relevance for advanced behavioral research tools originates from the need to perform detailed behavioral analyses in genetically modified organisms and animal models for disease research. © 2008 Elsevier B.V. All rights reserved. 1. Introduction A detailed understanding of how animals control their move- ments in a complex natural environment is likewise relevant to neuroscientists exploring neuromotor control mechanisms and engineers attempting to implement biological control principles in microrobots, such as micro air vehicles (MAVs). The reflexive flight control mechanisms of insects are experimentally highly amenable and therefore serve as powerful model systems to explore neuro- motor control mechanisms (e.g. Frye and Dickinson, 2001). Here we describe methods developed for a detailed behavioral system analysis in freely flying fruit flies (Drosophila melanogaster Meigen). Based on Virtual Reality (VR) display techniques imple- mented in standard digital hardware, we designed an automated ‘one-parameter open loop’ testing paradigm that allowed us to quantify the open loop transfer properties of the fly’s visual ground speed response. The ability to perform meaningful behavioral analyses with a high throughput meets the demands for an interdis- ciplinary research effort on neuromotor control strategies based on ∗ Corresponding author at: Institute of Neuroinformatics, ETH Z ¨ urich, Winterthur- erstrasse 190, CH-8057 Z¨ urich, Switzerland. Tel.: +41 44 635 30 45; fax: +41 44 635 30 53. E-mail address: steven@ini.ch (S.N. Fry). advanced genetic tools and concepts derived from control systems engineering. 1.1. Open loop stimulation in tethered insects The mechanisms underlying visuomotor flight control, like most other behaviors, are highly complex. This complexity can be approached with a reductionist approach, in which the animal is considered as a system of interconnected control loops, which can be analyzed using standard control system analysis techniques. In this approach, various sensory modalities are considered as inputs to the system, which after a sensorimotor transduction process lead to the motor output. As a result of the interaction with the physical environment, this leads to appropriate behavior and con- sequently generates sensory feedback, closing the feedback control loop (Fig. 1). In the past, visuomotor flight control mechanisms of flies and other insects have been explored extensively under restricted experimental conditions. As a classic approach, input–output relationships of identified neuromotor control loops have been measured from rigidly tethered insects, in which sensory stimuli can be delivered precisely and the resulting motor output measured with comparatively simple tools. As a result, it has been possible to characterize sensorimotor systems from their transfer properties, allowing structure–function relationships to be inferred. In the bio- 0165-0270/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.jneumeth.2008.02.016