A Computational Model of Stereoscopic Prey Capture in Praying Mantises”

We present a simple model which can account for the stereoscopic sensitivity of praying mantis predatory strikes. The model consists of a single “disparity sensor”: a binocular neuron sensitive to stereoscopic disparity and thus to distance from the animal. The model is based closely on the known behavioural and neurophysiological properties of mantis stereopsis. The monocular inputs to the neuron reflect temporal change and are insensitive to contrast sign, making the sensor insensitive to interocular correlation. The monocular receptive fields have a excitatory centre and inhibitory surround, making them tuned to size. The disparity sensor combines inputs from the two eyes linearly, applies a threshold and then an exponent output nonlinearity. The activity of the sensor represents the model mantis’s instantaneous probability of striking. We integrate this over the stimulus duration to obtain the expected number of strikes in response to moving targets with different stereoscopic distance, size and vertical disparity. We optimised the parameters of the model so as to bring its predictions into agreement with our empirical data on mean strike rate as a function of stimulus size and distance. The model proves capable of reproducing the relatively broad tuning to size and narrow tuning to stereoscopic distance seen in mantis striking behaviour. The model also displays realistic responses to vertical disparity. Most surprisingly, although the model has only a single centre-surround receptive field in each eye, it displays qualitatively the same interaction between size and distance as we observed in real mantids: the preferred size increases as prey distance increases beyond the preferred distance. We show that this occurs because of a stereoscopic “false match” between the leading edge of the stimulus in one eye and its trailing edge in the other; further work will be required to find whether such false matches occur in real mantises. This is the first image-computable model of insect stereopsis, and reproduces key features of both neurophysiology and striking behaviour.

Do We See Scale?

The visual system is supposed to extract distance information from the environment in order to scale the size and distance of objects in the visual scene. The purpose of this article is to challenge this account in three stages: First, I identify three shortcomings of the literature on vergence as our primary cue to near distances. Second, I present the results from two experiments that control for these shortcomings, but at the cost of eradicating vergence and accommodation as effective distance cues (average gain of y = 0.161x + 38.64). Third, I argue that if all our cues to distance are either (a) ineffective (vergence; accommodation; motion parallax), (b) merely relative (angular size; diplopia), or (c) merely cognitive (familiar size; vertical disparity), then the visual system does not appear to extract absolute distance information, and we should be open to the possibility that vision functions without scale.

The influence of vertical disparity gradient and cue conflict on EEG omega complexity in Panum’s limiting case

Using behavioral measures and ERP technique, researchers discovered at least two factors could influence the final perception of depth in Panum’s limiting case, which are the vertical disparity gradient and the degree of cue conflict between two- and three-dimensional shapes. Although certain event-related potential components have been proved to be sensitive to the different levels of these two factors, some methodological limitations existed in this technique. In this study, we proposed that the omega complexity of EEG signal may serve as an important supplement of the traditional event-related potential technique. We found that the trials with lower vertical gradient disparity have lower omega complexity (i.e., higher global functional connectivity) of the occipital region, especially that of the right-occipital hemisphere. Moreover, for occipital omega complexity, the trials with low-cue conflict have significantly larger omega complexity than those with medium- and high-cue conflict. It is also found that the electrodes located in the middle line of the occipital region (i.e., POz and Oz) are more crucial to the impact of different levels of cue conflict on omega complexity than the other electrodes located in the left- and right-occipital hemispheres. These evidences demonstrated that the EEG omega complexity could reflect distinct neural activities evoked by Panum’s limiting case configurations, with different levels of vertical disparity gradient and cue conflict. Besides, the influence of vertical disparity gradient and cue conflict on omega complexity may be regional dependent. NEW & NOTEWORTHY The EEG omega complexity could reflect distinct neural activities evoked by Panum’s limiting case configurations with different levels of vertical disparity gradient and cue conflict. The influence of vertical disparity gradient and cue conflict on omega complexity is regional dependent. The omega complexity of EEG signal can serve as an important supplement of the traditional ERP technique.

Detection of vertical disparity in three-dimensional visualizations

This paper identifies the major types of artifacts occurring in three-dimensional materials. It focuses on the analysis of vertical disparity. The vertical disparity is the artifact of the 3D images that appears both in the film material and in the computer visualizations. The research explains the causes and consequences of the vertical disparity occurrence and presents the stable algorithm of detecting mentioned anomaly. The implementation of the developed method constitutes a complete solution enabling verification of the stereoscopic material quality. The summary of the paper contains the evaluation of the algorithm in terms of correctness and stability.