Biology subjects

Tarawneh, G.

Publications and source records attributed to Tarawneh, G..

6 recordsLinked to original sources

bioRxiv2020

Target tracking behaviour of the praying mantis Sphrodromantis lineola (Linnaeus) is driven by looming-type motion-detectors.

We designed visual stimuli to characterise the motion-detectors that underlie target tracking behaviour in the mantis. The first was a small, moving, stripy, bug-like target, made by opening a moving, Gabor-filtered window onto an extended, moving, sinewave pattern. The mantis tracked this bug-like target, but the likelihood of tracking the bug depended only on the temporal frequency of its motion. In contrast, optomotor responses to the extended moving sinewave pattern alone depended on both spatial and temporal frequency of the pattern, as expected from classical, correlation-based motion-detectors. In another experiment, we used small moving objects that were made up of chequerboard patterns of randomly arranged dark squares, and found objects with smaller sized chequers were tracked relatively less. Response suppression like this, when the internal detail of an object increases, suggests the presence of lateral inhibition between inputs to the motion-detectors for target tracking. Finally, wide-field motion of a chequerboard background near the target, balanced so no optomotor responses were evoked, suppressed tracking proportionally both to the nearness of the background to the target and to the size its dark chequered squares. Backgrounds with smaller sized squares produced more suppression. This effect has been used as a demonstration of lateral inhibition in detectors for looming-motion and makes their response greatest to an expanding outer edge, an image produced by an approaching object. Our findings point to a new role for a looming-type motion-detector in mantis target tracking. We also discuss the suitability of several large lobula-complex neurons for this role.Summary Statement Lateral inhibition shown by motion-detectors underlying target tracking by the praying mantis Sphrodromantis lineola (Linnaeus).View Full Text

animal behavior and cognition↗

bioRxiv2018

Motion-in-depth perception and prey capture in the praying mantis

Perceiving motion-in-depth is essential to detecting approaching or receding objects, predators and prey. This can be achieved using several cues, including binocular stereoscopic cues such as changing disparity and interocular velocity differences and monocular cues such as looming. While these have been studied in detail in humans, only looming responses have been well characterized in insects and we know nothing about the role that stereo cues play and how they might interact with looming cues. We used our 3D insect cinema in a series of experiments to investigate the role of the stereo cues mentioned above, as well as looming, in the perception of motion-in-depth during predatory strikes by the praying mantis. Our results show that motion-in-depth does increase the probability of mantis strikes but only for the classic looming stimulus, an expanding luminance edge. Approach indicated by radial motion of a texture or expansion of a motion-defined edge, or by stereoscopic cues, all failed to elicit increased striking. We conclude that mantises use stereopsis to detect depth but not motion-in-depth, which is detected via looming.\n\nSummary StatementBoth stereoscopic visual cues and changing luminance cues can enable detection of approaching objects. We show that mantises use looming rather than stereo cues to detect motion-in-depth.

animal behavior and cognition↗

bioRxiv2018

The neuronal basis of insect stereopsis

A puzzle for neuroscience - and robotics - is how insects achieve surprisingly complex behaviours with such tiny brains1,2. One example is depth perception via binocular stereopsis in the praying mantis, a predatory insect. Praying mantids use stereopsis, the computation of distances from disparities between the two retinas, to trigger a raptorial strike of their forelegs3,4 when prey is within reach. The neuronal basis of this ability is entirely unknown. From behavioural evidence, one view is that the mantis brain must measure retinal disparity locally across a range of distances and eccentricities4-7, very like disparity-tuned neurons in vertebrate visual cortex8. Sceptics argue that this \"retinal disparity hypothesis\" implies far too many specialised neurons for such a tiny brain9. Here we show the first evidence that individual neurons in the praying mantis brain are indeed tuned to specific disparities and eccentricities, and thus locations in 3D-space. This disparity information is transmitted to the central brain by neurons connecting peripheral visual areas in both hemispheres, as well as by a unilateral neuron type. Like disparity-tuned cortical cells in vertebrates, the responses of these mantis neurons are consistent with linear summation of binocular inputs followed by an output nonlinearity10. Additionally, centrifugal neurons project disparity information back from the central brain to early visual areas, possibly for gain modulation or 3D spatial attention. Thus, our study not only proves the retinal disparity hypothesis for insects, it reveals feedback connections hitherto undiscovered in any animal species.

neuroscience↗

bioRxiv2018

Apparent Motion Perception in the Praying Mantis: Psychophysics and Modelling

Apparent motion is the perception of a motion created by rapidly presenting still frames in which objects are displaced in space. Observers can reliably discriminate the direction of apparent motion when inter-frame object displacement is below a certain limit, Dmax. Earlier studies of motion perception in humans found that Dmax scales with spatial element size, interpreting the relationship between the two as linear, and that Dmax appears to be lower-bounded at around 15 arcmin. Here, we run corresponding experiments in the praying mantis Sphodromantis lineola to investigate how Dmax scales with element size. We used moving random chequerboard patterns of varying element and displacement step sizes to elicit the optomotor response, a postural stabilization mechanism that causes mantids to lean in the direction of large-field motion. Subsequently, we calculated Dmax as the displacement step size corresponding to a 50% probability of detecting an optomotor response in the same direction as the stimulus. Our main findings are that mantis Dmax appears to scale as a power-law of element size and that, in contrast to humans, it does not appear to be lower-bounded. We present two models to explain these observations: a simple high-level model based on motion energy in the Fourier domain and a more detailed one based on the Reichardt Detector. The models present complementary intuitive and physiologically-realistic accounts of how Dmax scales with element size in insects.\n\nAuthor SummaryComputer monitors, smart phone screens and other forms of digital displays present a series of still images (frames) in which objects are displaced in small steps, tricking us into perceiving smooth motion. This illusion is referred to as \"apparent motion\", and for it to work effectively the magnitude of each displacement step must be smaller than a certain limit, referred to as Dmax. Previous studies have investigated the relationship between this limit and object size in humans and found that larger objects can be displaced in larger steps without affecting motion perception. In this work, we investigated the same relationship in the praying mantis Sphodromantis lineola by presenting them with moving chequerboard patterns on a computer monitor. Even though motion perception in humans and insects are believed to be explained equally well by the same underlying model, we found that Dmax scales with object size differently in mantids. These results suggest that there may be qualitative differences in how mantids perceive apparent motion compared to humans.

neuroscience↗

bioRxiv2017

Contrast Thresholds Reveal Different Visual Masking Functions In Humans And Praying Mantises

Recently, we showed a novel property of the Hassenstein-Reichardt detector: namely, that insect motion detection can be masked by \"invisible\" noise, i.e. visual noise presented at spatial frequencies to which the animals do not respond when presented as a signal. While this study compared the effect of noise on human and insect motion perception, it used different ways of quantifying masking in two species. This was because the human studies measured contrast thresholds, which were too time-consuming to acquire in the insect given the large number of stimulus parameters examined. Here, we run longer experiments in which we obtained contrast thresholds at just two signal and two noise frequencies. We examine the increase in threshold produced by noise at either the same frequency as the signal, or a different frequency. We do this in both humans and praying mantises (Sphodromantis lineola), enabling us to compare these species directly in the same paradigm. Our results confirm our earlier finding: whereas in humans, visual noise masks much more effectively when presented at the signal spatial frequency, in insects, noise is roughly equivalently effective whether presented at the same frequency or a lower frequency. In both species, visual noise presented at a higher spatial frequency is a less effective mask.\n\nSummary StatementWe here show that despite having similar motion detection systems, insects and humans differ in the effect of low and high spatial frequency noise on their contrast thresholds.

neuroscience↗

bioRxiv2017

When invisible noise obscures the signal: the consequences of nonlinearity in motion detection

1The motion energy model is the standard account of motion detection in animals from beetles to humans. Despite this common basis, we show here that a difference in the early stages of visual processing between mammals and insects leads this model to make radically different behavioural predictions. In insects, early filtering is spatially lowpass, which makes the surprising prediction that motion detection can be impaired by \"invisible\" noise, i.e. noise at a spatial frequency that elicits no response when presented on its own as a signal. We confirm this prediction using the optomotor response of praying mantis Sphodromantis lineola. This does not occur in mammals, where spatially bandpass early filtering means that linear systems techniques, such as deriving channel sensitivity from masking functions, remain approximately valid. Counter-intuitive effects such as masking by invisible noise may occur in neural circuits wherever a nonlinearity is followed by a difference operation.

neuroscience↗