Search PubMed⌕ Search

Biomedical subjects

M V Srinivasan

Publications and source records attributed to M V Srinivasan.

At least 37 records · Page 2Linked to original sources
PubMed1996

Maze learning by honeybees.

This study examines whether honeybees can learn to fly through complex mazes, in the presence or the absence of specific visual cues. The results are summarized as follows: 1. Bees can learn to fly through a complex maze by following a trail of colored marks. 2. Bees, initially trained to follow color marks through an initial part of the maze, are immediately able to use the same sign-tracking cue to find their way through the rest of the maze, which is unfamiliar to them. 3. Bees trained to follow color marks through a particular maze can use the same cue to negotiate a novel maze. 4. Bees trained to use a particular color to negotiate a maze can immediately use a novel color to negotiate the same maze or even a novel maze. 5. After learning to negotiate a maze by following colored marks, bees can find their way through the maze even when the marks are removed, albeit at reduced levels of accuracy. Thus, the trained bees do not rely solely on sign-tracking to find their way through the maze: they also acquire a spatial memory of the maze or at least a sequence of motor commands describing the correct path through it. 6. Bees can learn to use color as a signal even when it indicates the path through the maze in a symbolic way, for example, blue indicating a turn to the right and green a turn to the left. 7. Bees can learn an unmarked maze. Performance under these conditions is poorer than when marks are provided, but is still significantly better than chance level. 8. Control experiments rule out the use of external landmarks in all of these situations.

Animals↗
PubMed1996

Visual computation of egomotion using an image interpolation technique.

A novel technique is presented for the computation of the parameters of egomotion of a mobile device, such as a robot or a mechanical arm, equipped with two visual sensors. Each sensor captures a panoramic view of the environment. We show the parameters of ego-motion can be computed by interpolating the position of the image captured by one of the sensors at the robot's present location, with respect to the images captured by the two sensors at the robot's previous location. The algorithm delivers the distance travelled and angle rotated, without the explicit measurement or integration of velocity fields. The result is obtained in a single step, without any iteration or successive approximation. Tests of the algorithm on real and synthetic images reveal an accuracy to within 5% of the actual motion. Implementation of the algorithm on a mobile robot reveals that stepwise rotation and translation can be measured to within 10% accuracy in a three-dimensional world of unknown structure. The position and orientation of the robot at the end of a 30-step trajectory can be estimated with accuracies of 5% and 5 degrees, respectively.

Algorithms↗
PubMed1995

Convergent processing in honeybee vision: multiple channels for the recognition of shape.

Advanced mammalian visual systems can recognize a familiar shape under a variety of viewing conditions. Recognition is possible whether the shape is presented in simple outline, as a random dot stereogram, or by motion contrast. We report here that bees have a similar ability: they can recognize a shape when it is learned through visual signals of one kind and subsequently viewed through another. The results reveal that (i) bees that have learned a shape defined in terms of luminance contrast can recognize the same shape when it is defined in terms of motion contrast, (ii) shapes that are delineated by motion contrast are discriminated through a channel that receives input only from the green photoreceptors, (iii) a shape learned through one class of signal is subsequently recognized via any of these other classes, and (iv) shape is memorized in a generic form regardless of whether it is initially sensed by green-contrast, blue-contrast, luminance-contrast, or motion-contrast signals.

Journal Article↗
PubMed1994

Active vision in honeybees: task-oriented suppression of an innate behaviour.

In a pattern discrimination task, bees tend to fly along the contours contained in the patterns, as revealed by an earlier study. As opposed to this, in a task involving the detection of an edge between two striped surfaces placed at two different ranges, the bees avoid contour-following, as revealed by the present study. The study shows that, in the latter task, the bees learn to suppress the otherwise innate contour-following behaviour and adopt a flight strategy that provides them with the motion parallax cues necessary to cope with this task. Thus, the animal's active behaviour determines the type of visual information to be extracted from the environment.

Animals↗
PubMed1993

'Vector white noise': a technique for mapping the motion receptive fields of direction-selective visual neurons.

A technique is described and tested for mapping the sensitivities and preferred directions of motion at different locations within the receptive fields of direction-selective motion-detecting visual neurons. The procedure is to record the responses to a number of visual stimuli, each stimulus presentation consisting of a set of short, randomly-oriented, moving bars arranged in a square grid. Each bar moves perpendicularly to its long axis. The vector describing the sensitivity and preferred direction of motion at each grid location is obtained as a sum of the unit vectors defining the directions of motion of the bars in each of the stimuli at that location, weighted by the strengths of the corresponding responses. The resulting vector field specifies the optimum flow field for the neuron. The advantage of this technique over the conventional approach of probing the receptive field sequentially at each grid location is that the parallel nature of the stimulus is sensitive to nonlinear interactions (such as shunting inhibition for mutual facilitation) between different regions of the visual field. The technique is used to determine accurately the motion receptive fields of direction-selective motion detecting neurons in the optic lobes of insects. It is potentially applicable to motion-sensitive neurons with highly structured receptive fields, such as those in the optic tectum of the pigeon or in area MST of the monkey.

Animals↗
PubMed1993

Behavioural evidence for parallel information processing in the visual system of insects.

Many flying insects display remarkable visual agility in capturing prey or pursuing a potential mate. They are capable of detecting, recognising, tracking and capturing a rapidly moving object on the wing. These manoeuvres are usually completed in a couple of seconds. The interval of time between the absorption of light quanta by the photoreceptors and the generation of an appropriate behavioural response is very short, encompassing only a few tens of milliseconds. In this time the visual nervous system has abstracted the essential features of the object, and recognized it (where appropriate), or measured its movement and computed an interception course. As an elementary unit of computation, we know that a neuron in the nervous system is considerably slower than, say, a flip-flop in the CPU of a modern computer. However, it is evident from the visual performance of an insect that the nervous system as a whole processes optical information much faster than a modern computer does. Rapid processing of visual information by animals therefore has to be attributed to the structure and the modus operandi of the nervous system.

Animals↗
PubMed1991

Camouflage by edge enhancement in animal coloration patterns and its implications for visual mechanisms.

Animal camouflage patterns may exploit, and thus give an insight into, visual processing mechanisms. In one common type of camouflage the borders of the coloured patterns are enhanced by high contrast lines. This type of camouflage is seen on many frogs and we use it as the basis for speculating about vision in a small, frog-eating snake. It is argued that a simple categorization of intensity profiles, such as that invoked by a mechanism that detects phase-congruence, occurs at an early stage of snake vision. We show that edge-detectors using a phase-congruence strategy will be unable to distinguish between 'natural' step-edges and the enhanced border profiles commonly seen on cryptic animals, and that the camouflage will be effective over a wide range of spatial scales.

Adaptation, Physiological↗
PubMed1991

A visually evoked escape response of the housefly.

Flies (Musca domestica) avoid danger by initiating a rapid jump followed by flight. To identify the visual cues that trigger the escape response in the housefly, we measured the timing and probability of escapes when the fly was presented with a variety of visual stimuli created by moving targets toward it. Our results show that an escape response is triggered by an approaching dark disk, but not by a receding dark disk. On the other hand, a bright disk elicits escape only when it recedes. A disk with black and white rings is less effective at eliciting escape than is a dark solid disk of the same size. This indicates that the darkening contrast produced by an approaching stimulus is a more crucial parameter than expansion cues contained in the optical flow. Escape is also triggered by a horizontally moving dark edge, but not by a moving bright edge or by a grating. An examination of several visual parameters reveals that the darkening contrast, measured from the onset of stimulation to the start of escape is nearly constant for a variety of stimuli that trigger escape reliably. Thus darkening contrast, coupled with motion may be crucial in eliciting the visually evoked escape response. Other visual parameters such as time-to-contact or target angular velocity seem to be relatively unimportant to the timing of escapes.

Animals↗
PubMed1991

Range perception through apparent image speed in freely flying honeybees.

When negotiating a narrow gap, honeybees tend to fly through the middle of the gap, balancing the distances to the boundary on either side. To investigate the basis of this "centering response," bees were trained to fly through a tunnel on their way to a feeding site and back, while their flight trajectories were filmed from above. The wall on either side carried a visual pattern. When the patterns were stationary vertical gratings, bees tended to fly through the middle of the tunnel, i.e. along its longitudinal axis. However, when one of the gratings was in motion, bees flying in the same direction as the moving grating tended to fly closer to it, while bees flying in the opposite direction tended to fly closer to the stationary grating. This demonstrates, directly and unequivocally, that flying bees estimate the distances of surfaces in terms of the apparent motion of their images. A series of further experiments revealed that the distance to the gratings is gauged in terms of their apparent angular speeds, and that the visual system of the bee is capable of measuring angular speed largely independently of the spatial period, intensity profile, or contrast of the grating. Thus, the motion-sensitive mechanisms mediating range perception appear to be qualitatively different from those that mediate the well-known optomotor response in insects, or those involved in motion detection and ocular tracking in man.

Animals↗
PubMed1990

Generalized gradient schemes for the measurement of two-dimensional image motion.

This paper describes a procedure for recovering the global velocity of an image by incorporating spatial filtering, and optionally, temporal filtering, into a scheme that employs a generalized version of the gradient algorithm of motion detection. Motion within a patch is analysed by six parallel channels, each incorporating a different spatiotemporal filter. Advantageous features of this scheme are: (a) global velocity is derived directly, without first computing local velocity at a number of image locations; (b) the filters compute first derivatives rather than second derivatives, making the scheme potentially more resistant to noise than certain other schemes; (c) two of the six filters can be chosen almost completely arbitrarily, and can therefore be tailored to maximize signal reliability, and (d) the measurement of velocity can be made as local or as global as desired by altering the size of the patch that is viewed by the filters. An analogous scheme is derived for the measurement of rotation as well as expansion or contraction of the image.

Animals↗
PubMed1990

Neural gradient models for the measurement of image velocity.

Although gradient schemes for detecting the motion of images and measuring their velocities are commonly used in computer vision, and although there is increasing evidence to support the existence of such schemes in biological vision, little attention has been directed to suggesting how such computations might be realized by neural hardware. This paper proposes two simple models, consisting of physiologically realistic networks of neurons, that approximate the gradient scheme. Computer simulations demonstrate that the models measure the speed of an object or pattern independently of its structural properties.

Computer Simulation↗
PubMed1990

Visual tracking of moving targets by freely flying honeybees.

The ability of freely-flying honeybees to track moving targets was examined by training them to collect a reward on a target, and then videotaping their approach to the target while it was in motion. Training experiments were carried out with several groups of bees, using various colors for the target and the background. Computer-aided frame-by-frame analysis of video recordings was used to plot the instantaneous positions of the target, as well as the position and orientation of the approaching bee in three dimensions. The results show that bees are perfectly capable of tracking moving targets and landing on them. When the distance of the target is greater than 15 cm, approaching bees correct for angular deviations of the target from the midline, both in the horizontal and in the vertical plane. In either plane, the input variables that are important to the tracking system seem to be (1) the angular bearing of the target with respect to the midline, and (2) the angular velocity of the target with respect to the eye. The tracking control system tends to orient the bee such that the target is located frontally, at an angle of ca. 35 deg below the bee's long axis. The chromatic properties of tracking behavior were investigated by employing combinations of colors for the target and background such that the boundary between the target and the background presented a contrast that was visible either only to the green-sensitive receptors of the bee's eye, or only to the blue-sensitive receptors.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1990

Shift of edge-taxis to scototaxis depends on mean luminance and is predicted by a matched filter theory on the responses of fly lamina LMC cells.

The strength of the flanking inhibitory regions of the receptive fields of fly lamina cells (LMC) decreases as the mean luminance is lowered. Simultaneously, the biphasic temporal flash (impulse) response of the lamina cells becomes monophasic on lowering luminance. For a moving-edge stimulus at high mean luminance, this implies that the spatial integration by the lamina cell yields a temporal waveform which is congruent to the waveform of the temporal impulse response of the lamina cell. In other words, the temporal waveform generated by the moving edge is matched to the temporal waveform most preferred by the lamina cell. The edge is the stimulus causing the largest amplitude response at high (above 1 cd/m2) levels of luminance. On lowering luminance, the now monophasic nature of the spatial and temporal impulse responses of the lamina gives a preference not for the edges but for the center of a uniform region. We describe this theory and its behavioral corroboration in walking flies (Lucilia cuprina).

Animals↗
PubMed1990

What causes edge fixation in walking flies?

The orientation of freely walking flies (female Lucilia cuprina) to lines and stripes in a circular arena is described. The following observations were made. 1. The flies walked straight towards a dark line using the frontal eye region, but a pale line on a dark background was only weakly attractive. 2. In bright conditions flies walked in a curved line towards a black-white edge, the path being convex towards the dark side of the border. The curves indicated that the flies were heading for a point about 5-10 degrees to the dark side of the edge. 3. In dim conditions the edge of a dark region was not especially attractive and flies headed towards any point in the dark area. These observations can be accounted for by assuming that the fly walks towards the darkest region in its visual field (scototaxis). In bright conditions the edges of a dark region become more attractive than its centre. This change could be explained if lateral inhibition creates a 'Mach-band' effect, making the edges appear darker than the centre. Thus, fixation behaviour in walking Lucilia females seems to be a simple taxis.

Animals↗
PubMed1987

Bi-partitioning and boundary detection in natural scenes.

We propose a strategy for early vision which tailors visual channels to the object-oriented characteristics of natural scenes. This strategy involves essentially two types of channel, one for encoding the locally dominant edges which form the boundaries of 'objects', and another for 'filling in' the regions within them. The selection of contrasts which characterize object boundaries rather than textural detail can be enhanced by making an estimate local of contrast, and setting a threshold accordingly. This procedure and other aspects of the model were first suggested by observations of insect visual cells.

Animals↗
PubMed1983

The impulse response of a movement-detecting neuron and its interpretation.

When a visual pattern undergoes a brief displacement, the response of the neuron depends primarily upon the size of the displacement. One measures a tradeoff between velocity and duration of motion, analogous to the reciprocal relationship between intensity and duration in the perception of a brief flash of light (Bloch's law). Characterizing the movement detector by its "impulse response" could be useful in predicting the response to arbitrary motions.

Animals↗