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M V Srinivasan

Publications and source records attributed to M V Srinivasan.

At least 19 recordsLinked to original sources
PubMed2000

Honeybee navigation: nature and calibration of the "odometer".

There are two theories about how honeybees estimate the distance to food sources. One theory proposes that distance flown is estimated in terms of energy consumption. The other suggests that the cue is visual, and is derived from the extent to which the image of the world has moved on the eye during the trip. Here the two theories are tested by observing dances of bees that have flown through a short, narrow tunnel to collect a food reward. The results show that the honeybee's "odometer" is visually driven. They also provide a calibration of the dance and the odometer in visual terms.

Animals↗
PubMed1999

Honeybee memory: navigation by associative grouping and recall of visual stimuli.

Studies of navigation in bees and ants are beginning to reveal that foraging insects traveling repeatedly to a food source navigate by using a series of visual images of the environment acquired en route (Collett, 1996; Collett et al., 1993; Judd & Collett, 1998; Wehner et al., 1990, 1996). By comparing the currently viewed scene with the appropriate stored image, the insect is able to ascertain whether or not it is on the correct path and make any necessary corrections. If a bee happens to forage at more than one site, then she needs not only to memorize a separate set of images for each route that she has learned but also to retrieve the set of images that is appropriate to each route. Here we examine the bee's capacity to learn and later retrieve from memory two different sets of visual stimuli. Bees were trained to fly through a compound Y-maze where they were presented alternately with two different sequences of visual stimuli on their route to a food reward. We find that bees can indeed store two different sequences of images simultaneously. Furthermore, the trained bees are able to classify the memorized images into two groups, one pertaining to each three-stimulus set. Exposure to any of the images pertaining to one set triggers recall of all of the other images associated with that set. Associative grouping and recall of visual stimuli, demonstrated here for the first time in honeybees, provide an effective means of retrieving the appropriate navigational information from memory.

Animals↗
PubMed1999

Motion detection in insect orientation and navigation.

The visual systems of insects are exquisitely sensitive to motion. Over the past 40 years or so, motion processing in insects has been studied and characterised primarily through the optomotor response. This response, which is a turning response evoked by the apparent movement of the visual environment, serves to stabilise the insect's orientation with respect to the environment. Research over the past decade, however, is beginning to reveal the existence of a variety of other behavioural responses in insects, that use motion information in different ways. Here we review some of the recently characterised behaviours, describe the inferred properties of the underlying movement-detecting processes, and propose modified or new models to account for them.

Animals↗
PubMed1998

The spatiotemporal properties of the Craik-O'Brien-Cornsweet effect are consistent with 'filling-in'.

The Craik-O'Brien-Cornsweet effect (COCE) is an illusion in which luminance discontinuities give rise to illusory brightness. One hypothesised mechanism for the induction of illusory brightness is that the cortex constructs a brightness percept from edge information by a lateral 'filling-in' process. A requirement for the filling-in hypothesis is that ability of the illusion to form would be limited by the speed of propagation of the filling-in. The results presented here from three methods indicate that in the case of COCE gratings brightness information propagates at a fixed speed across the central visual field of about 19 degrees/s, and across visual areas V1 or V2 at 155 or 205 (+/- 20) mm/s, respectively.

Contrast Sensitivity↗
PubMed1998

The Craik-O'Brien-Cornsweet effect and brightness induction both proceed by the spreading of brightness information.

BACKGROUND: The Craik-O'Brien Cornsweet effect (COCE) is a visual illusion where the luminance of image boundaries sets the apparent brightness of enclosed regions. The COCE may be produced by the cortex constructing the observed brightness through a lateral 'filling-in' process: propagating brightness information from the edges of the enclosed regions towards their centres. Any such filling-in process would imply a speed of propagation. METHODS: Data on the propagation speed of brightness information in two different brightness induction effects are compared using a multivariate regression analysis. RESULTS/CONCLUSION: We demonstrate similar non-zero speeds for the COCE and for a brightness contrast effect.

Contrast Sensitivity↗
PubMed1997

Visual control of honeybee flight.

Recent research has uncovered a number of different visual cues which bees use for controlling and stabilising flight. Bees flying through a tunnel maintain equidistance to the flanking walls by balancing the speeds of the images of the two walls. This strategy enables them to negotiate narrow passages or to fly between obstacles. The speed of flight in the tunnel is controlled by holding constant the average image velocity as seen by the two eyes. This mechanism prevents potential collisions by ensuring that the bee slows down when it flies through a narrow passage. Bees landing on a horizontal surface hold constant the image velocity of the surface as they approach it, thus automatically ensuring that flight speed is close to zero at touchdown. The movement-sensitive mechanisms underlying these various behaviours differ qualitatively as well as quantitatively, from those that mediate the well-investigated optomotor response. Flight thus appears to be co-ordinated by a number of visuomotor systems acting in concert.

Animals↗
PubMed1997

Edge detection by landing honeybees: behavioural analysis and model simulations of the underlying mechanism.

The mechanism of edge detection in the honeybee was investigated by examining the effects of combining different kinds of visual cues that define an edge. Free-flying bees were trained to land at three different types of edges which were defined by texture and relative motion cues either in isolation or in combination with each other. Bees are able to detect and land at the three types of edges, but do so with different frequencies. In contrast to the naive expectation that edges jointly defined by two cues can be detected better than those defined by a single cue in isolation, the combination of the cues does not increase and may even decrease the detectability of an edge. When bees land at an edge the orientation of their body axis is strongly affected by the visual cues defining this edge. Model simulations were performed to test whether the experimental findings can be explained on the basis of a single edge detection mechanism sensitive to both types of visual cues. In the model, the information from both types of cues is sensed by two fields of movement detectors that receive their input signals from two adjacent patches in the visual field. The output of all detectors subserving either patch is pooled by integrating cells. The signals of the two integrating cells subserving the two adjacent patches are compared at a subtraction stage. The resulting signal is then rectified and forms the output signal of the model. The model simulations closely resemble the experimental results, thus providing evidence that edge detection by the bee could be mediated by a single mechanism.

Animals↗
PubMed1997

Long-term synaptic plasticity in the honeybee.

A monosynaptic response was recorded in vivo in the mushroom body of the bee brain, an important site for memory consolidation. Focal electrical stimulation of a major afferent input evoked an extracellular field potential that consisted of a presynaptic fiber volley and a postsynaptic response. We report a long-lasting potentiation of the synaptic response (2.6-fold increase; < or = 3.5 h). Potentiation of the response was induced by low-frequency stimulation (0.02-1.0 Hz), was input specific, and was maintained in the absence of stimulation. Paired-pulse facilitation of the response was converted to paired-pulse depression after potentiation, suggesting a presynaptic mechanism. This is the first demonstration of long-term synaptic plasticity in the insect brain.

Animals↗
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↗
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↗