Comparison between the movement detection systems underlying the optomotor and the landing response in the housefly

Flies evaluate movement within their visual field in order to control the course of flight and to elicit landing manoeuvres. Although the motor output of the two types of responses is quite different, both systems can be compared with respect to the underlying movement detection systems. For a quantitative comparison, both responses were measured during tethered flight under identical conditions. The stimulus was a sinusoidal periodic pattern of vertical stripes presented bilaterally in the fronto-lateral eye region of the fly. To release the landing response, the pattern was moved on either side from front to back. The latency of the response depends on the stimulus conditions and was measured by means of an infrared light-beam that was interrupted whenever the fly lifted its forelegs to assume a preprogrammed landing posture (Borst and Bahde 1986). As an optomotor stimulus the pattern moved on one side from front to back and on the other side in the opposite direction. The induced turning tendency was measured by a torque meter (Götz 1964). The response values which will be compared are the inverse latencies of the landing response and the amplitude of the yaw torque.

1. Optomotor course-control is more sensitive to pattern movement at small spatial wavelengths (10° and 20°) than the landing response (Fig. 1a and b). This suggests that elementary movement detectors (EMDs, Buchner 1976) with large detection base (the distance between interacting visual elements) contribute more strongly to the landing than to the optomotor system.
2. The optimum contrast frequencies of the different responses obtained at a comparatively high pattern contrast of about 0.6 was found to be between 1 and 10 Hz for the optomotor response, and around 20 Hz for the landing response (Fig. 2a and b). This discrepancy can be explained by the fact that the optomotor response was tested under stationary conditions (several seconds of stimulation) while for the landing response transient response characteristics of the movement detectors have to be taken into account (landing occurs under these conditions within less than 100 ms after onset of the movement stimulus). To test the landing system under more stationary conditions, the pattern contrast had to be reduced to low values. This led to latencies of several seconds. Then the optimum of the landing response is around 4 Hz. This is in the optimum range of the optomotor course-control response. The result suggests the same filter time constants for the movement detectors of both systems.
3. The dependence of both responses on the position and the size of the pattern was examined. The landing response has its optimum sensitivity more ventrally than the optomotor response (Fig. 3a and b). Both response amplitudes increase with the size of the pattern in a similar progression (Fig. 3c and d).

In first approximation, the present results are compatible with the assumption of a common set of movement detectors for both the optomotor course-control and the landing system. Movement detectors with different sampling bases and at different positions in the visual field seem to contribute with different gain to both responses. Accordingly, the control systems underlying both behaviors are likely to be independent already at the level of spatial integration of the detector output.     

Neural correlates of the optomotor response in the fly

Summary Studies of the optomotor response, the tendency to turn in response to a moving pattern, have yielded some understanding of the motion detection capabilities of the fly. We present data from extracellular microelectrode recordings from the optic lobes of the housefly, Musca domestica and the blowflies Eucalliphora lilaea and Calliphora phaenicia. Directionally selective and directionally nonselective motion sensitive units were observed in the region between the medulla and the lobula of all three species. Employing similar stimulus conditions to those used in the optomotor reaction studies, it was found that the response of the directionally selective units exhibited most of the characteristics of the optomotor response torque measurements. It is concluded that these units code the information prerequisite to the optomotor response and hence, that much data processing is achieved in the first few synaptic layers of the insect visual nervous system.     

用红外方法对蝇翅视动行为的探索

本文报告了利用红外装置对蝇翅视动行为实验研究的初步结果及其分析:1.在红外探测器探测到的信号中找到了一个能反映蝇翅拍动幅度的参数.2.双侧、单侧刺激域的宽度及刺激域的高度对视动反应发生几率在一定范围内正相关,当超过一阈值(即饱和阈值)后,即出现稳定的视动反应,它们的饱和阈值分别为60°,30°,40°刺激条纹的亮度生有类似情况.刺激条纹的运动速度在一定范围内对视动反应无影响.3.当刺激没有达到饱和时,蝇翅出现断续的典型的视动反应,即“0-1波动反应”.4.单侧条纹由前向后运动时,蝇翅出现典型反应,而条纹从后向前运动时,不出现典型的视动反应或反应很弱.双侧刺激时,条纹向前运动几乎不诱发反应;条纹向后运动诱发明显的蝇翅视动反应,且蝇翅平面的方向在拍动过程中发生变化.     

The three-dimensional optomotor torque system ofDrosophila melanogaster

Summary The well known optomotor yaw torque response in flies is part of a 3-dimensional system. Optomotor responses around the longitudinal and transversal body axes (roll and pitch) with strinkingly similar properties to the optomotor yaw response are described here forDrosophila melanogaster. Stimulated by visual motion from a striped drum rotating around an axis aligned with the measuring axis, a fly responds with torque of the same polarity as that of the rotation of the pattern. In this stimulus situation the optomotor responses for yaw, pitch and roll torque have about the same amplitudes and dynamic properties (Fig. 2). Pronounced negative responses are measured with periodic gratings of low pattern wavelengths due to geometrical interference (Fig. 3). The responses depend upon the contrast frequency rather than the angular velocity of the pattern (Fig. 4). Like the optomotor yaw response, roll and pitch responses can be elicited by small field motion in most parts of the visual field; only for motion below and behind the fly roll and pitch responses have low sensitivity.The mutantoptomotor-blind ^H31 (omb ^H31) in which the giant neurones of the lobula plate are missing or severely reduced, is impaired in all 3 optomotor torque responses (Fig. 5) whereas other visual responses like the optomotor lift/thrust response and the landing response (elicited by horizontal front-to-back motion) are not affected (Heisenberg et al. 1978).We propose that the lobula plate giant neurons mediate optomotor torque responses and that the VS-cells in particular are involved in roll and pitch but not in lift/thrust control. This hypothesis accommodates various electrophysiological and anatomical observations about these neurons in large flies.Abbreviation EMD elementary movement detector     

Neuronal representation of optic flow experienced by unilaterally blinded flies on their mean walking trajectories

Asymmetries in the optic flow on both eyes may indicate an unintended turn of an animal and evoke compensatory optomotor responses. On a straight path in an evenly structured environment, the optic flow on both eyes is balanced corresponding to a state of optomotor equilibrium. When one eye is occluded an optomotor equilibrium is expected to be reached on a curved path provided that the translatory optic flow component is cancelled by a superimposed rotation. This hypothesis is tested by analysing how the HSE cell, a constituent element of the fly's optomotor system, represents optic flow in behavioural situations. The optic flow as seen on the average trajectory of freely walking monocular flies is reconstructed. This optic flow is used as stimulus of the HSE cell in electrophysiological experiments and as input of a model of the fly's optomotor system. The responses of the HSE cell and of the model fluctuate around the resting potential. On average, they are much smaller than the responses evoked by optic flow experienced on a straight path. These results corroborate the hypothesis that the mean trajectory of monocular flies corresponds to a path of optomotor equilibrium. Accepted: 29 February 2000     

The optomotor yaw response of the desert locust, Schistocerca gregaria

Abstract The optomotor yaw response of the desert locust, Schistocerca gregaria (Forsk.), was investigated under open- and closed-loop conditions. When flying tethered in the centre of a vertically striped hollow sphere, the polarity of response of the locust was always the same as the stimulus. The response, therefore, appears suitable to stabilize body posture against passive rotations around the yaw-axis in free flight. Responses were induced by contrast frequencies up to 150 Hz with a maximum of amplitude at about 20 Hz. The characteristic curve, measured between 0.3 and 160 Hz, is widened up towards higher frequencies as compared with those of bees and flies.
Variability was the most striking feature in the locust's yaw response. The amplitude of modulation not only varied greatly between individuals but also changed with the same visual stimulus in the course of an experiment. We therefore suppose that the locust's turning behaviour is subject to gain control mechanisms and that spontaneous gain modulations are responsible for the observed variability in the stimulus-response conversion.     

Relating neuronal to behavioral performance: variability of optomotor responses in the blowfly

Behavioral responses of an animal vary even when they are elicited by the same stimulus. This variability is due to stochastic processes within the nervous system and to the changing internal states of the animal. To what extent does the variability of neuronal responses account for the overall variability at the behavioral level? To address this question we evaluate the neuronal variability at the output stage of the blowfly''s (Calliphora vicina) visual system by recording from motion-sensitive interneurons mediating head optomotor responses. By means of a simple modelling approach representing the sensory-motor transformation, we predict head movements on the basis of the recorded responses of motion-sensitive neurons and compare the variability of the predicted head movements with that of the observed ones. Large gain changes of optomotor head movements have previously been shown to go along with changes in the animals'' activity state. Our modelling approach substantiates that these gain changes are imposed downstream of the motion-sensitive neurons of the visual system. Moreover, since predicted head movements are clearly more reliable than those actually observed, we conclude that substantial variability is introduced downstream of the visual system.     

Regional specialization for an optomotor response in the honeybee compound eye

ABSTRACT. The optomotor head-turning response of the honeybee ( Apis mellifera ) to a horizontally moving stripe pattern was analysed after occlusion of specific regions of the compound eye. The dorsal half of the eye and the medial region appear to be irrelevant to this behavioural reflex. Occlusion of the ventrolateral portion of the eye, however, even with the remainder of the eye unoccluded, rendered the optomotor system blind. The optomotor response was found to be mediated by an area roughly equal to one-fifth of the total eye surface with some redundancy in the system, since occlusion of at least half of the zone did not significantly impair the response. These results support the hypothesis of physically separate visual subsystems in the bee eye which are adapted for different functions.     

Visual signals in an optomotor reflex: systems and information theoretic analysis

Compensatory optomotor reflexes were examined in crayfish (Procambarus clarkii) with oscillating sine wave gratings and step displacements of a single stripe. A capacitance transducer was used to measure the rotation of the eyestalk about its longitudinal axis. System studies reveal a spatial frequency response independent of velocity and stimulus amplitude and linear contrast sensitivity similar to that of neurons in the visual pathway. The reflex operates at low temporal frequencies (<0.002 Hz to 0.5 Hz) and exhibits a low-pass temporal frequency response with cut-off frequency of 0.1 Hz. Eyestalk rotation increases as a saturable function of the angular stimulus displacement. When compared to the oscillatory response, transient responses are faster, and they exhibit a lower gain for large stimulus displacements. These differences may reflect system nonlinearity and/or the presence of at least two classes of afferents in the visual pathway. Our metric for information transmission is the Kullback-Leibler (K-L) distance, which is inversely proportional to the probability of an error in distinguishing two stimuli. K-L distances are related to differences in responsiveness for variations in spatial frequency, contrast, and angular displacement. The results are interpreted in terms of the neural filters that shape the system response and the constraints that the K-L distances place on information transmission in the afferent visual pathway.     

Direction-sensitive partitioning of the honeybee optomotor system

ABSTRACT. The horizontal motion-detecting system controlling optomotor head-turning behaviour in honeybees, Apis mellifera , was found to be partitioned into two separate subsystems. Each subsystem is direction-specific such that visual stimulation in the preferred direction elicited a high level of responses that correcly followed the movement, whereas stimulation in the non-preferred direction resulted in response levels comparable to or lower than those for blinded controls. The results indicate that medial eye regions are specialized for the detection of posterior-to-anterior movements and lateral regions are specialized for detecting anterior-to-posterior motion. A model suggesting possible neural correlates for this functional subdivision of the optomotor response is proposed.     

Stimulus detection after interruption of the feedforward response in a backward masking paradigm

In backward masking, a target stimulus is rendered invisible by the presentation of a second stimulus, the mask. When the mask is effective, neural responses to the target are suppressed. Nevertheless, weak target responses sometimes may produce a behavioural response. It remains unclear whether the reduced target response is a purely feedforward response or that it includes recurrent activity. Using a feedforward neural network of biological plausible spiking neurons, we tested whether a transient spike burst is sufficient for face categorization. After training the network, the system achieved face/non-face categorization for sets of grayscale images. In a backward masking paradigm, the transient burst response was cut off thereby reducing the feedforward target response. Despite the suppressed feedforward responses stimulus classification remained robust. Thus according to our model data stimulus detection is possible with purely, suppressed feedforward responses.     

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.     

Visual afferences to flight steering muscles controlling optomotor responses of the fly

Summary In tethered flying house-flies (Musca domestica) visually induced turning reactions were monitored under open-loop conditions simultaneously with the spike activity of four types of steering muscles (M.b1, M.b2, M.I1, M.III1). Specific behavioral response components are attributed to the activity of particular muscles. Compensatory optomotor turning reactions to large-field image displacements mainly occur when the stimulus pattern oscillates at low frequencies. In contrast, turning responses towards objects are preferentially induced by motion of relatively small stimuli at high oscillation frequencies. The different steering muscles seem to be functionally specialized in that they contribute to the control of these behavioral responses in different ways. The muscles I1, III1 and b2 are preferentially active during small-field motion at high oscillation frequencies. They are much less active during small-field motion at low oscillation frequencies and large-field motion at all oscillation frequencies which were tested. M.b2 is most extreme in this respect. These steering muscles thus mediate mainly turns towards objects. In contrast, M.b1 responds best during large-field motion at low oscillation frequencies and, thus, is appropriate to control compensatory optomotor responses. However, the activity of this muscle is also strongly modulated during small-field motion at high oscillation frequencies and, therefore, may be involved also in the control of turns towards objects. These functional specializations of the different steering muscles in mediating different behavioral response components are related to the properties of two parallel visual pathways that are selectively tuned to large-field and small-field motion, respectively.Abbreviations FD (cell) figure detection (cell) - HS (cell) horizontal (cell)     

Dynamic properties of two control systems underlying visually guided turning in house-flies

Summary The compensatory optomotor turning reaction as well as the turning response towards objects play an important role in visual orientation. On the basis of behavioural experiments under precisely defined stimulus conditions it is concluded that in female house-flies these motion-dependent responses are mediated by two parallel control systems with different dynamic and spatial integration properties. One of them (large-field system) is most sensitive to the motion of large textured patterns and controls the yaw torque mainly at low oscillation frequencies (below 0.1 Hz) of the stimulus panorama. In contrast, the other control system (small-field system) is tuned to the detection of relatively small moving patterns and shows its strongest responses at high oscillation frequencies (between 1 and 4 Hz), i.e. in a frequency range where the large-field system contributes to the turning response with only a relatively small gain.In free flight, house-flies do not curve smoothly but in sequences of rapid turns which induce retinal large-field motion of continually changing sign (Wagner 1986b). The dynamic properties of the large-field system might thus be interpreted as a simple strategy to almost eliminate the unwanted optomotor yaw torque induced by active self-motion. In contrast, the small-field system might still be operational under these conditions.     

Are the large monopolar cells of the insect lamina on the optomotor pathway?

Evidence is presented here from experiments on the visual system of the fly that questions participation of the large monopolar cells (LMCs) in the optomotor response.

The orientation of flies towards visual patterns: On the search for the underlying functional interactions

The average optomotor response of insects to a given visual stimulus (measured in open-loop conditions) can be decomposed into a direction sensitive and a direction insensitive component. This decomposition is conceptual and always possible. The direction sensitive optomotor response represents the “classical” optomotor reflex, already studied in previous investigations; the direction insensitive optomotor response is strictly connected to the orientation and tracking behaviour (see the work of Reichardt and coworkers). Thus a characterization of the direction insensitive response is useful in clarifying the nervous mechanisms underlying the orientation behaviour. For this reason we study in this paper the direction insensitive optomotor (torque) response of fixed flying fliesMusca domestica. Periodic gratings, either moving or flickering, represent our main stimulus, since the dependence of the fly response on the spatial wavelength can unravel the presence and properties of the underlying lateral interactions. In this connection an extension of the Volterra series formalism to multi-input (nervous) networks is first outlined in order to connect our (behavioural) input-output data with the interactive structure of the network. A number of results concerning, for instance, the response of such networks to flickered and moving gratings are derived; they are not restricted to our behavioural results and may be relevant in other fields of neuroscience. These theoretical considerations provide the logical framework of our experimental investigation. The main results are:

1. the direction insensitive optomotor response depends on the spatial frequency of a moving grating, implying the existence of (nonlinear) lateral interactions,
2. its wavelength dependence changes with age, unlike the direction sensitive response,
3. both the direction insensitive response and the (closed loop) orientation behaviour are present only in the lower part of the eye; on the other hand the direction sensitive response is present in every part of the two eyes.

Furthermore the attraction towards a flickered periodic grating shows, as theoretically expected, a wavelength-dependence similar to that of the direction insensitive response, again present only in the lower part of the eye. The interactions which affect the orientation response are selective with respect to the spatiotemporal mapping of the pattern onto the receptor array. It is conjectured that these interactions are the basic mechanisms underlying spontaneous pattern discrimination in flies. Their possible organization is further discussed in terms of our formalism. Moreover our data suggest that two specific nervous circuitries correspond to our conceptual decomposition of the optomotor response.     

On the existence of 'fast' and 'slow' directionally sensitive motion detector neurons in insects.

In a fly, butterfly, locust and dragonfly we examined the responses of a variety of directional motion-sensitive neurons which run from the brain down the ventral cord. The stimulus was a sinusoidally modulated moving pattern of regular stripes presented at a range of velocities in random order for either 0.1 s or 2.0 s. The response was measured as the total number of spikes to each stimulus. The neurons fall into two groups, 'fast' and 'slow'. The responses of the fast type rise progressively to a peak contrast frequency at 15-20 Hz for all four insects, and decline at higher contrast frequencies. The responses of slow neurons rise rapidly to a peak at 1-10 Hz and then decline more slowly across the range where the fast neurons are at their peak. The existence of two groups of neurons with overlapping response ranges to different velocities of the same pattern, presented in exactly the same way, provides the insect with a means of measuring angular velocity irrespective of contrast, spatial frequency or intensity. As an input mechanism it is proposed that there are two types of unit motion detector, fast and slow, the latter being the main input to the optomotor system. It is also argued that even these inputs are not sufficient to provide a mechanism for the whole repertoire of normal insect vision.     

Reflex pressure response to the electric stimulation of different parts of the rat stomach

The role of the autonomic nervous system in the pressor response to the electrical stimulation of different gastric zones has been studied in rats. The stimulus was applied before and after the following interventions: bilateral vagotomy, ganglionic blockade, alpha-adrenergic receptor blockade and beta-adrenergic receptor blockade. After the ganglionic blockade no pressor responses to the electrical stimulus were observed. After the alpha-adrenergic blockade a lower pressor response was observed. A hypertensive response can be induced by mechanical, chemical or electrical stimulation of gastric receptors. It is concluded that the pressor reflex following the application of an electrical stimulus on different zones of the digestive tract is mediated by the sympathetic nervous system and that the efferent pathways are mainly alpha-adrenergic ones.     

Nonlinear kernels of the human ERG

In this paper we examine the use of a symmetric binary random stimulus for eliciting the ERG, and for calculating the first-order and second-order kernels of a nonlinear functional expansion of the response. We show that if the stimulus is represented in a non-dimensional form, then the units in which all kernels are measured are the same as the units used to measure the response, microvolts in the case of the ERG: further, contributions from all kernels to the response can be added without scale factors. We present the first-order and second-order kernels measured for a population of 15 normal subjects in a clinical setting. The measurements were made at various levels of adaptation ranging from photopic to scotopic conditions. The second-order kernels illustrate the processes of rapid adaptation (<100 ms) in the retina.This research was supported in part by Grants No. EY01526, EY01774, EY01775, and RR07003 from the National Institutes of Health     

Memory-dependent adjustment of vocal response latencies in a territorial songbird

Vocal interactions in songbirds can be used as a model system to investigate the interplay of intrinsic singing programmes (e.g. influences from vocal memories) and external variables (e.g. social factors). When characterizing vocal interactions between territorial rivals two aspects are important: (1) the timing of songs in relation to the conspecific’s singing and (2) the use of a song pattern that matches the rival’s song. Responses in both domains can be used to address a territorial rival. This study is the first to investigate the relation of the timing of vocal responses to (1) the vocal memory of a responding subject and (2) the selection of the song pattern that the subject uses as a response. To this end, we conducted interactive playback experiments with adult nightingales (Luscinia megarhynchos) that had been hand-reared and tutored in the laboratory. We analysed the subjects’ vocal response latencies towards broadcast playback stimuli that they either had in their own vocal repertoire (songs shared with playback) or that they had not heard before (unknown songs). Likewise, we compared vocal response latencies between responses that matched the stimulus song and those that did not. Our findings showed that the latency of singing in response to the playback was shorter for shared versus unknown song stimuli when subjects overlapped the playback stimuli with their own song. Moreover birds tended to overlap faster when vocally matching the stimulus song rather than when replying with a non-matching song type. We conclude that memory of song patterns influenced response latencies and discuss possible mechanisms.