Visually guided orientation in flies: case studies in computational neuroethology

Method and software for using m-sequences to characterize parallel components of higher-order visual tracking behavior in Drosophila

A moving visual figure may contain first-order signals defined by variation in mean luminance, as well as second-order signals defined by constant mean luminance and variation in luminance envelope, or higher-order signals that cannot be estimated by taking higher moments of the luminance distribution. Separating these properties of a moving figure to experimentally probe the visual subsystems that encode them is technically challenging and has resulted in debated mechanisms of visual object detection by flies. Our prior work took a white noise systems identification approach using a commercially available electronic display system to characterize the spatial variation in the temporal dynamics of two distinct subsystems for first- and higher-order components of visual figure tracking. The method relied on the use of single pixel displacements of two visual stimuli according to two binary maximum length shift register sequences (m-sequences) and cross-correlation of each m-sequence with time-varying flight steering measurements. The resultant spatio-temporal action fields represent temporal impulse responses parameterized by the azimuthal location of the visual figure, one STAF for first-order and another for higher-order components of compound stimuli. Here we review m-sequence and reverse correlation procedures, then describe our application in detail, provide Matlab code, validate the STAFs, and demonstrate the utility and robustness of STAFs by predicting the results of other published experimental procedures. This method has demonstrated how two relatively modest innovations on classical white noise analysis—the inclusion of space as a way to organize response kernels and the use of linear decoupling to measure the response to two channels of visual information simultaneously—could substantially improve our basic understanding of visual processing in the fly.

Impact and sources of neuronal variability in the fly's motion vision pathway

Nervous systems encode information about dynamically changing sensory input by changes in neuronal activity. Neuronal activity changes, however, also arise from noise sources within and outside the nervous system or from changes of the animal's behavioral state. The resulting variability of neuronal responses in representing sensory stimuli limits the reliability with which animals can respond to stimuli and may thus even affect the chances for survival in certain situations. Relevant sources of noise arising at different stages along the motion vision pathway have been investigated from the sensory input to the initiation of behavioral reactions. Here, we concentrate on the reliability of processing visual motion information in flies. Flies rely on visual motion information to guide their locomotion. They are among the best established model systems for the processing of visual motion information allowing us to bridge the gap between behavioral performance and underlying neuronal computations. It has been possible to directly assess the consequences of noise at major stages of the fly's visual motion processing system on the reliability of neuronal signals. Responses of motion sensitive neurons and their variability have been related to optomotor movements as indicators for the overall performance of visual motion computation. We address whether and how noise already inherent in the stimulus, e.g. photon noise for the visual system, influences later processing stages and to what extent variability at the output level of the sensory system limits behavioral performance. Recent advances in circuit analysis and the progress in monitoring neuronal activity in behaving animals should now be applied to understand how the animal meets the requirements of fast and reliable manoeuvres in naturalistic situations.

Processing of horizontal optic flow in three visual interneurons of the Drosophila brain

Motion vision is essential for navigating through the environment. Due to its genetic amenability, the fruit fly Drosophila has been serving for a lengthy period as a model organism for studying optomotor behavior as elicited by large-field horizontal motion. However, the neurons underlying the control of this behavior have not been studied in Drosophila so far. Here we report the first whole cell recordings from three cells of the horizontal system (HSN, HSE, and HSS) in the lobula plate of Drosophila. All three HS cells are tuned to large-field horizontal motion in a direction-selective way; they become excited by front-to-back motion and inhibited by back-to-front motion in the ipsilateral field of view. The response properties of HS cells such as contrast and velocity dependence are in accordance with the correlation-type model of motion detection. Neurobiotin injection suggests extensive coupling among ipsilateral HS cells and additional coupling to tangential cells that have their dendrites in the contralateral hemisphere of the brain. This connectivity scheme accounts for the complex layout of their receptive fields and explains their sensitivity both to ipsilateral and to contralateral motion. Thus the main response properties of Drosophila HS cells are strikingly similar to the responses of their counterparts in the blowfly Calliphora, although we found substantial differences with respect to their dendritic structure and connectivity. This long-awaited functional characterization of HS cells in Drosophila provides the basis for the future dissection of optomotor behavior and the underlying neural circuitry by combining genetics, physiology, and behavior.

Electric imaging through active electrolocation: implication for the analysis of complex scenes

The electric sense of mormyrids is often regarded as an adaptation to conditions unfavourable for vision and in these fish it has become the dominant sense for active orientation and communication tasks. With this sense, fish can detect and distinguish the electrical properties of the close environment, measure distance, perceive the 3-D shape of objects and discriminate objects according to distance or size and shape, irrespective of conductivity, thus showing a degree of abstraction regarding the interpretation of sensory stimuli. The physical properties of images projected on the sensory surface by the fish's own discharge reveal a "Mexican hat" opposing centre-surround profile. It is likely that computation of the image amplitude to slope ratio is used to measure distance, while peak width and slope give measures of shape and contrast. Modelling has been used to explore how the images of multiple objects superimpose in a complex manner. While electric images are by nature distributed, or 'blurred', behavioural strategies orienting sensory surfaces and the neural architecture of sensory processing networks both contribute to resolving potential ambiguities. Rostral amplification is produced by current funnelling in the head and chin appendage regions, where high density electroreceptor distributions constitute foveal regions. Central magnification of electroreceptive pathways from these regions particularly favours the detection of capacitive properties intrinsic to potential living prey. Swimming movements alter the amplitude and contrast of pre-receptor object-images but image modulation is normalised by central gain-control mechanisms that maintain excitatory and inhibitory balance, removing the contrast-ambiguity introduced by self-motion in much the same way that contrast gain-control is achieved in vision.

Crossmodal visual input for odor tracking during fly flight

Flies generate robust and high-performance olfactory and visual behaviors. Adult fruit flies can distinguish small differences in odor concentration across antennae separated by less than 1 mm [1], and a single olfactory sensory neuron is sufficient for near-normal gradient tracking in larvae [2]. During flight a male housefly chasing a female executes a corrective turn within 40 ms after a course deviation by its target [3]. The challenges imposed by flying apparently benefit from the tight integration of unimodal sensory cues. Crossmodal interactions reduce the discrimination threshold for unimodal memory retrieval by enhancing stimulus salience [4], and dynamic crossmodal processing is required for odor search during free flight because animals fail to locate an odor source in the absence of rich visual feedback [5]. The visual requirements for odor localization are unknown. We tethered a hungry fly in a magnetic field, allowing it to yaw freely, presented odor plumes, and examined how visual cues influence odor tracking. We show that flies are unable to use a small-field object or landmark to assist plume tracking, whereas odor activates wide-field optomotor course control to enable accurate orientation toward an attractive food odor.

Active sensing: Pre-receptor mechanisms and behavior in electric fish

Weakly electric fish perceive their actively generated electrical field with cutaneous electroreceptors. This active sensory system is used both for orientation and for communication. In a recent paper1 we focussed on how anatomical adaptations (pre-receptor mechanisms), biophysical constraints and behavior all contribute to active electrolocation, i.e., the fishes' unique ability to determine and distinguish the electrical properties of objects based on the modulation of a self-generated carrier signal, the so-called electric organ discharge.

Dynamic properties of large-field and small-field optomotor flight responses in Drosophila

Optomotor flight control in houseflies shows bandwidth fractionation such that steering responses to an oscillating large-field rotating panorama peak at low frequency, whereas responses to small-field objects peak at high frequency. In fruit flies, steady-state large-field translation generates steering responses that are three times larger than large-field rotation. Here, we examine the optomotor steering reactions to dynamically oscillating visual stimuli consisting of large-field rotation, large-field expansion, and small-field motion. The results show that, like in larger flies, large-field optomotor steering responses peak at low frequency, whereas small-field responses persist under high frequency conditions. However, in fruit flies large-field expansion elicits higher magnitude and tighter phase-locked optomotor responses than rotation throughout the frequency spectrum, which may suggest a further segregation within the large-field pathway. An analysis of wing beat frequency and amplitude reveals that mechanical power output during flight varies according to the spatial organization and motion dynamics of the visual scene. These results suggest that, like in larger flies, the optomotor control system is organized into parallel large-field and small-field pathways, and extends previous analyses to quantify expansion-sensitivity for steering reflexes and flight power output across the frequency spectrum.

Courtship dances in the flies of the genus Lispe (Diptera: Muscidae): from the fly's viewpoint

Two predatory fly species, Lispe consanguinea Loew, 1858 and L. tentaculata DeGeer, 1776, inhabit the supralittoral zone at the shore of a fresh-water reservoir. Both species look alike and possess similar "badges," reflective concave silvery scales on the face. Flies occupy different lek habitats. Males of the first species patrol the bare wet sand on the beach just above the surf. Males of the second species reside on the more textured heaps of algae and stones. Courtship and aggressive behaviour of males was video-recorded and analysed frame by frame. Visual stimuli provided by the conspecific partner were computed in the body-fixed space of a fly observer. Males of L. consanguinea perform long pedestrian dances of pendulating circular arcs (frequency 2 s(-1), median radius 2.5 cm, linear velocity 0.130 m/s). Right and left side runs are equally probable. Circular runs are interrupted by standby intervals of average duration 0.35 s. The female views the male as a target covering 2 by 2 ommatidia, moving abruptly with the angular velocity over 200 degrees/s in a horizontal direction down the path of about 50 degrees till the next standpoint. Dancing is evenly distributed around the female. On the contrary, the male fixates the image of the female within the narrow front sector (median +/-10 degrees); the target in his view has 6-7 times less angular velocity and angular span of oscillations, and its image in profile overlays 6-8 by 2 ommatidia. If the female walks, the male combines tracking with voluntary circular dances. Rival males circle about one another at a distance shorter than 15 mm, but not in close contact. Males of L. tentaculata are capable of similar circular courting dances, but do so rarely. Usually they try to mount any partner immediately. In the latter species, male combat consists of fierce wrestling. Flies of both species often walk sideward and observe the partner not in front but at the side.