Processing of figure and background motion in the visual system of the fly

The visual system of the fly is able to extract different types of global retinal motion patterns as may be induced on the eyes during different flight maneuvers and to use this information to control visual orientation. The mechanisms underlying these tasks were analyzed by a combination of quantitative behavioral experiments on tethered flying flies (Musca domestica) and model simulations using different conditions of oscillatory large-field motion and relative motion of different segments of the stimulus pattern. Only torque responses about the vertical axis of the animal were determined. The stimulus patterns consisted of random dot textures (Julesz patterns) which could be moved either horizontally or vertically. Horizontal rotatory large-field motion leads to compensatory optomotor turning responses, which under natural conditions would tend to stabilize the retinal image. The response amplitude depends on the oscillation frequency: It is much larger at low oscillation frequencies than at high ones. When an object and its background move relative to each other, the object may, in principle, be discriminated and then induce turning responses of the fly towards the object. However, whether the object is distinguished by the fly depends not only on the phase relationship between object and background motion but also on the oscillation frequency. At all phase relations tested, the object is detected only at high oscillation frequencies. For the patterns used here, the turning responses are only affected by motion along the horizontal axis of the eye. No influences caused by vertical motion could be detected. The experimental data can be explained best by assuming two parallel control systems with different temporal and spatial integration properties: TheLF-system which is most sensitive to coherent rotatory large-field motion and mediates compensatory optomotor responses mainly at low oscillation frequencies. In contrast, theSF-system is tuned to small-field and relative motion and thus specialized to discriminate a moving object from its background; it mediates turning responses towards objects mainly at high oscillation frequencies. The principal organization of the neural networks underlying these control systems could be derived from the characteristic features of the responses to the different stimulus conditions. The input to the model circuits responsible for the characteristic sensitivity of the SF-system to small-field and relative motion is provided by retinotopic arrays of local movement detectors. The movement detectors are integrated by a large-field element, the output cell of the network. The synapses between the detectors and the output cells have nonlinear transmission characteristics. Another type of large-field elements (pool cells) which respond to motion in front of both eyes and have characteristic direction selectivities are assumed to interact with the local movement detector channels by inhibitory synapses of the shunting type, before the movement detectors are integrated by the output cells. The properties of the LF-system can be accounted for by similar model circuits which, however, differ with respect to the transmission characteristic of the synapses between the movement detectors and the output cell; moreover, their pool cells are only monocular. This type of network, however, is not necessary to account for the functional properties of the LF-system. Instead, intrinsic properties of single neurons may be sufficient. Computer simulations of the postulated mechanisms of the SF-and LF-system reveal that these can account for the specific features of the behavioral responses under quite different conditions of coherent large-field motion and relative motion of different pattern segments.     

On the neuronal basis of figure-ground discrimination by relative motion in the visual system of the fly

A fly can discriminate an object (figure) from its background on the basis of motion information alone. This information processing task has been analysed, so far, mainly in behavioural studies but also in electrophysiological experiments (Reichardt et al., 1983). The present study represents a further attempt to bridge the gap between the behavioural and the neuronal level. It is based on behavioural and electrophysiological experiments as well as on computer simulations. The characteristic properties of figureground discrimination behaviour impose specific constraints on the spatial integration properties of the output cells of the underlying neuronal network, the heterolateral interactions in their input circuitry, as well as on the range of variability of their response. These constraints are derived partly from previous behavioural studies (Reichardt et al., 1983), partly, however, from behavioural response characteristics which have not been addressed explicitly so far. They are interpreted in terms of one of the alternative model circuits shown by Reichardt et al. (1983) to be sufficient to account for figure-ground discrimination. It will be demonstrated, however, that this can be done equally well by means of a further alternative model circuit. These constraints are used in the electrophysiological analysis for establishing visual interneurones as output elements of the neuronal network underlying figure-ground discrimination.In the behavioural experiments on figure-ground discrimination as well as on the optomotor course control the yaw torque generated by the tethered flying fly under visual stimulation was used as a measure for the strength and time course of the reaction. Therefore, it has initially been proposed that the three Horizontal Cells, which are regarded as the output elements of the neuronal network underlying the optomotor reaction (e.g. Hausen, 1981), might also control yaw torque generation in figure-ground discrimination (Reichardt et al., 1983). New behavioural data show, however, that the Horizontal Cells do not meet all the constraints imposed on the presumed output cells of the figure-ground discrimination network: (1) The Horizontal Cells are not sensitive enough to motion of small objects. (2) The heterolateral interactions within their input circuitry are not in accordance with the behavioural data (see also Reichardt et al., 1983). (3) The variability found in the time course of certain components of the yaw torque response to relative motion of figure and ground cannot be explained by their response characteristics. Hence, the Horizontal Cells cannot account for figure-ground discrimination on their own and additional output cells of the optic lobes with different functional properties are required to accomplish this task.     

On the neuronal basis of figure-ground discrimination by relative motion in the visual system of the fly

It has been concluded in the preceding papers (Egelhaaf, 1985a, b) that two functional classes of output elements of the visual ganglia might be involved in figure-ground discrimination by relative motion in the fly: The Horizontal Cells which respond best to the motion of large textured patterns and the FD-cells which are most sensitive to small moving objects. In this paper it is studied by computer simulations (1) in what way the input circuitry of the FD-cells might be organized and (2) the role the FD-cells play in figure-ground discrimination. The characteristic functional properties of the FD-cells can be explained by various alternative model networks. In all models the main input to the FD-cells is formed by two retinotopic arrays of small-field elementary movement detectors, responding to either front-to-back or back-to-front motion. According to their preferred direction of motion the FD-cells are excited by one of these movement detector classes and inhibited by the other. The synaptic transmission between the movement detectors and the FD-cells is assumed to be non-linear. It is a common property of all these model circuits that the inhibition of the FD-cells induced by large-field motion is mediated by pool cells which cover altogether the entire horizontal extent of the visual field of both eyes. These pool cells affect the response of the FD-cells either by pre- or postsynaptic shunting inhibition. Depending on the FD-cell under consideration, the pool cells are directionally selective for motion or sensitive to motion in either horizontal direction. The role the FD-cells and the Horizontal Cells are likely to play in figure-ground discrimination can be demonstrated by computer simulations of a composite neuronal model consisting of the model circuits for these cell types. According to their divergent spatial integration properties they perform different tasks in figure-ground discrimination: Whereas the Horizontal Cells mainly mediate information on wide-field motion, the FD-cells are selectively tuned to efficient detection of relatively small targets. Both cell classes together appear to be sufficient to account for figure-ground discrimination as it has been shown by analysis at the behavioural level.     

On the neuronal basis of figure-ground discrimination by relative motion in the visual system of the fly

A new class of large-field tangential neurones (Figure Detection (FD-) cells) has been found and analysed in the lobula plate, the posterior part of the third visual ganglion, of the fly by combined extra-and intracellular recording as well as Lucifer Yellow injection. The FD-cells are likely to play a prominent role in figure-ground discrimination. Together with the Horizontal Cells, the output elements of the neuronal network underlying the optomotor course control reaction, they seem to be appropriate to account for the characteristic yaw torque response to relative motion. The FD-cells might thus compensate for the deficits of the Horizontal Cells with respect to figureground discrimination (see Egelhaaf, 1985a).The FD-cells are directionally selective for either front-to-back (FD 1, FD 4) or back-to-front motion (FD 2, FD 3). Their excitatory receptive fields cover part of (FD 1, FD 2, FD 3) or the entire horizontal extent (FD 4) of the visual field of one eye. Their most important common property in the context of figureground discrimination is that they are more sensitive to relatively small objects than to spatially extended patterns. Their response to a small figure is much reduced by simultaneous large-field motion in front of the ipsi-as well as the contralateral eye. This large-field inhibition is either directionally selective or bidirectional, depending on the FD-cell under consideration. The main dendritic arborization of all FD-cells resides in the lobula plate. Their axonal projections lie in either the ipsi-or contralateral posterior optic foci and, thus, in the same area as the terminals of the Horizontal Cells. The FD-cells are, therefore, appropriate candidates for output elements of the optic lobes involved in figure-ground discrimination.     

Making connections in the fly visual system

Understanding the molecular mechanisms that regulate formation of precise patterns of neuronal connections within the central nervous system remains a challenging problem in neurobiology. Genetic studies in worms and flies and molecular studies in vertebrate systems have led to an increasingly sophisticated understanding of how growth cones navigate toward their targets and form topographic maps. Considerably less is known about how growth cones recognize their cellular targets and form synapses with them. Here, we review connection formation in the fly visual system, the methodological approaches used to study it, and recent progress in uncovering the molecular basis of connection specificity.     

Responses of visual interneurons in the fly optic lobe during stimulation by motion in depth

Summary A high-order wide-field neuron in the optic lobe of the fly,Phormia terraenovae (Calliphoridae), has been investigated by stimulation with simple or multiple black stripes on a white background moving sinusoidally towards and away from the head. The variation in spike frequency in correlation with the optical stimulation provides evidence that the unit detects angular velocity as well as more complex features of the stimulus. It responds preferentially to movement towards the head. Spike frequency turned out to be a two-valued function of relative angular velocity across the eye. A simple formula predicts the highly reliable responses to visual stimuli in different parts of the visual field.The author wants to thank Professor G. A. Horridge for his valuable support and clarifying discussions and to Dr. M. Srinivasan for his comments. The project has been supported by grants from the Swedish Council for Natural Science Research.     

Figure-ground discrimination by relative movement in the visual system of the fly

The visual system of the fly performs various computations on photoreceptor outputs. The detection and measurement of movement is based on simple nonlinear multiplication-like interactions between adjacent pairs and groups of photoreceptors. The position of a small contrasted object against a uniform background is measured, at least in part, by (formally) 1-input nonlinear flicker detectors. A fly can also detect and discriminate a figure that moves relative to a ground texture. This computation of relative movement relies on a more complex algorithm, one which detects discontinuities in the movement field. The experiments described in this paper indicate that the outputs of neighbouring movement detectors interact in a multiplication-like fashion and then in turn inhibit locally the flicker detectors. The following main characteristic properties (partly a direct consequence of the algorithm's structure) have been established experimentally: a) Coherent motion of figure and ground inhibit the position detectors whereas incoherent motion fails to produce inhibition near the edges of the moving figure (provided the textures of figure and ground are similar). b) The movement detectors underlying this particular computation are direction-insensitive at input frequencies (at the photoreceptor level) above 2.3 Hz. They become increasingly direction-sensitive for lower input frequencies. c) At higher input frequencies the fly cannot discriminate an object against a texture oscillating at the same frequency and amplitude at 0° and 180° phase, whereas 90° or 270° phase shift between figure and ground oscillations yields maximum discrimination. d) Under conditions of coherent movement, strong spatial incoherence is detected by the same mechanism. The algorithm underlying the relative movement computation is further discussed as an example of a coherence measuring process, operating on the outputs of an array of movement detectors. Possible neural correlates are also mentioned.     

Head-centred motion perception in the ageing visual system

Stationary objects appear to move in the opposite direction to a pursuit eye movement (Filehne illusion) and moving objects appear slower when pursued (Aubert-Fleischl phenomenon). Both illusions imply that extra-retinal, eye-velocity signals lead to lower estimates of speed than corresponding retinal motion signals. Intriguingly, the velocity (i.e. speed and direction) of the Filehne illusion depends on the age of the observer, especially for brief display durations (Wertheim and Bekkering, 1992). This suggests relative signal size changes as the visual system matures. To test the signal-size hypothesis, we compared the Filehne illusion and Aubert-Fleischl phenomenon in young and old observers using short and long display durations. The trends in the Filehne data were similar to those reported by Wertheim and Bekkering. However, we found no evidence for an effect of age or duration in the Aubert-Fleischl phenomenon. The differences between the two illusions could not be reconciled on the basis of actual eye movements made. The findings suggest a more complicated explanation of the combined influence of age and duration on head-centred motion perception than that described by the signal-size hypothesis.     

A special class of nonlinear interactions in the visual system of the fly

Flies can detect a small object in front of a randomly contrasted background if the object undergoes small motions. The effect was investigated in fixed flying flies under open-loop conditions. The results suggest that nonlinear inhibitory interactions underly this elementary case of figure-ground discrimination.     

The fundamental mechanism of motion detection in the insect visual system

The basic principle of motion detection by fibers of the optic lobes of flies were studied with a pair of small spots and a variety of paired intensity variations. These show that the process of correlation of adjacent field regions to detect motion is confined to a small area. The presence of small field units with small field adjacent inhibition in the system was detected. The optimum spot spacing for maximum reactions corresponded to the facet spacings. Selective motion detection responses from minimum information consisting of evaluating the difference between the spot intensities and the rate of change of the trailing spot relative to the motion direction was shown. However, additional properties best determined by white-noise experiments designed from this study were found.     

The perception of visual motion.

Recent developments have led to a greater insight into the complex processes of perception of visual motion. A better understanding of the neuronal circuitry involved and advances in electrophysiological techniques have allowed researchers to alter the perception of an animal with a stimulating electrode. In addition, studies have further elucidated the processes by which signals are combined and compared, allowing a greater understanding of the effects of selective brain damage.     

Reception of images by the visual system in the imaginary plane in front of and behind the real plane

It was shown that our visual system and brain are able to initiate the appearance of images of pictures in an imaginary plane simultaneously behind and before their real plane and continuously watch their independent displacement.     

Dissection of the peripheral motion channel in the visual system of Drosophila melanogaster

In the eye, visual information is segregated into modalities such as color and motion, these being transferred to the central brain through separate channels. Here, we genetically dissect the achromatic motion channel in the fly Drosophila melanogaster at the level of the first relay station in the brain, the lamina, where it is split into four parallel pathways (L1-L3, amc/T1). The functional relevance of this divergence is little understood. We now show that the two most prominent pathways, L1 and L2, together are necessary and largely sufficient for motion-dependent behavior. At high pattern contrast, the two pathways are redundant. At intermediate contrast, they mediate motion stimuli of opposite polarity, L2 front-to-back, L1 back-to-front motion. At low contrast, L1 and L2 depend upon each other for motion processing. Of the two minor pathways, amc/T1 specifically enhances the L1 pathway at intermediate contrast. L3 appears not to contribute to motion but to orientation behavior.     

Low-level visual processing of biological motion.

Biological motion displays depict a moving human figure by means of just a few isolated points of light attached to the major joints of the body. Naive observers readily interpret the moving pattern of dots as representing a human figure, despite the complete absence of form cues. This paper reports a series of experiments which investigated the visual processes underlying the phenomenon. Results suggest that (i) the effect relies upon responses in low-level motion-detecting processes, which operate over short temporal and spatial intervals and respond to local modulations in image intensity; and (ii) the effect does not involve hierarchical visual analysis of motion components, nor does it require the presence of dots which move in rigid relation to each other. Instead, movements of the extremities are crucial. Data are inconsistent with current theoretical treatments.     

Maximally efficient prediction in the early fly visual system may support evasive flight maneuvers

The visual system must make predictions to compensate for inherent delays in its processing. Yet little is known, mechanistically, about how prediction aids natural behaviors. Here, we show that despite a 20-30ms intrinsic processing delay, the vertical motion sensitive (VS) network of the blowfly achieves maximally efficient prediction. This prediction enables the fly to fine-tune its complex, yet brief, evasive flight maneuvers according to its initial ego-rotation at the time of detection of the visual threat. Combining a rich database of behavioral recordings with detailed compartmental modeling of the VS network, we further show that the VS network has axonal gap junctions that are critical for optimal prediction. During evasive maneuvers, a VS subpopulation that directly innervates the neck motor center can convey predictive information about the fly’s future ego-rotation, potentially crucial for ongoing flight control. These results suggest a novel sensory-motor pathway that links sensory prediction to behavior.