Computational model for neural representation of multiple disparities

Watanabe, Osamu; Idesawa, Masanori

doi:10.1016/s0893-6080(02)00186-7

Cited by 6 publications

(3 citation statements)

References 41 publications

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“…Therefore, examining how the contrast polarities of paired dots modulate the responses of binocular neurons with physiological and/or computational ways, we could investigate how the binocular neurons represent transparency situations. These researches should include mathematical analysis of the response of the disparity energy model (Ohzawa, DeAngelis, & Freeman, 1990;Tsai & Victor, 2003;Watanabe & Idesawa, 2003) to the ambiguous stereograms.…”

Section: Discussionmentioning

confidence: 99%

Stereo transparency in ambiguous stereograms generated by overlapping two identical dot patterns

Watanabe¹

2009

Journal of Vision

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In binocular vision, observers can perceive transparent surfaces by fusing a stereogram composed of two overlapping patterns with different disparities. When dot patterns of two surfaces are identical, the stereogram has potential matches leading to both transparency and non-transparency (or unitary surface) perceptions. However, these two matching candidates are exclusive if the uniqueness assumption holds. This stereogram can be regarded as a random-dot version of the double-nail illusion and a stereo version of the locally paired-dot stimulus that was used to investigate the neural mechanism for motion transparency. Which surface is perceived in this ambiguous stereogram would reflect the property of the transparency detection mechanism in human stereopsis. Here we perform a parametric study to examine the perceptual property in this ambiguous stereogram. The result showed that the ability in transparency detection from this stereogram is determined by the contrast reversal ratio between overlapping patterns within small regions the width of which was about 0.4 deg. The width was similar to the receptive field sizes of neurons in striate cortex. The result suggests that the contrast reversal between two identical patterns would modulate activities of binocular neurons, and this modification gives a crucial effect on the neural representation for overlapping disparities.

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Section: Discussionmentioning

confidence: 99%

Stereo transparency in ambiguous stereograms generated by overlapping two identical dot patterns

Watanabe¹

2009

Journal of Vision

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“…Although several physiologically-based models have been proposed (Fleet et al, 1996;Grossberg, 1994;Grossberg and Howe, 2003;Lehky and Sejnowski, 1990;Lippert and Wagner, 2002;Matthews et al, 2003;McLoughlin and Grossberg, 1998;Mikaelian and Qian, 2000;Prince and Eagle, 2000;Qian, 1994Qian, , 1997Qian and Andersen, 1997;Read, 2002a,b;Tsai and Victor, 2003;Watanabe and Idesawa, 2003;Zhaoping, 2002), much work remains to be done in tying these theories more closely to the known physiology, and expanding them to provide a complete account of stereoscopic perception.…”

Section: Outstanding Questionsmentioning

confidence: 99%

Early computational processing in binocular vision and depth perception

Read

2005

Progress in Biophysics and Molecular Biology

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Stereoscopic depth perception is a fascinating ability in its own right and also a useful model of perception. In recent years, considerable progress has been made in understanding the early cortical circuitry underlying this ability. Inputs from left and right eyes are first combined in primary visual cortex (V1), where many cells are tuned for binocular disparity. Although the observation of disparity tuning in V1, combined with psychophysical evidence that stereopsis must occur early in visual processing, led to initial suggestions that V1 was the neural correlate of stereoscopic depth perception, more recent work indicates that this must occur in higher visual areas. The firing of cells in V1 appears to depend relatively simply on the visual stimuli within local receptive fields in each retina, whereas the perception of depth reflects global properties of the stimulus. However, V1 neurons appear to be specialized in a number of respects to encode ecologically relevant binocular disparities. This suggests that they carry out essential preprocessing underlying stereoscopic depth perception in higher areas. This article reviews recent progress in developing accurate models of the computations carried out by these neurons. We seem close to achieving a mathematical description of the initial stages of the brain's stereo algorithm. This is important in itself--for instance, it may enable improved stereopsis in computer vision--and paves the way for a full understanding of how depth perception arises. Stereopsis as a model of perceptionAlthough we have two eyes, we are not aware of the fact during visual perception: we perceive the world as if through a single "cyclopean eye" in the middle of our forehead. Yet at the same time, we have the remarkable ability to deduce depth from the small differences in left-and right-eye retinal images which occur because our eyes are set apart in our head. This stereoscopic ability and its counterpart, binocular single vision, have fascinated us since their existence was first fully appreciated in the nineteenth century. Recently, binocular vision has come into prominence as a tool for probing one of the fundamental questions of neuroscience: how external stimuli give rise to conscious perception.There are several reasons why stereopsis is a particularly suitable model system for this goal.1. The problem to be solved is relatively well-defined, compared to for example face or speech recognition, and its mathematical basis is thoroughly understood (Fig. 1;Hartley and Zisserman, 2000;Longuet-Higgins, 1981). 2.As a consequence of this simplicity, stereopsis can be studied in both animals and humans. Monkeys perceive stereoscopic depth much as humans do, and can be trained to report their perceptions (Bough, 1970). Thus, psychophysical studies of perception can be combined with electrophysiological studies of neuronal activity in the same animal--of critical importance in the attempt to relate perception and neuronal activity. 3.The circuitry specific to this task probably oc...

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“…To accomplish our goal, we used motion-defined transparency as a test case. The transparent motion stimulus was selected based on previous studies, which have addressed its psychophysical (Braddick, 1997; Braddick et al , 2002; Calabro and Vaina, 2006; Farell and Li, 2004; Metelli, 1974; Qian et al , 1994) and computational (Murakami, 1997; Nowlan and Sejnowski, 1995; Qian et al , 1994; Raudies and Neumann, 2011; Raudies et al , 2011; Snowden and Verstraten, 1999; Tsai and Victor, 2003; Watanabe and Idesawa, 2003) characteristics, as well as its physiological substrates. The experimental paradigm proposed here provides a solid foundation for investigating how and when unimodal, crossmodal, and bimodal cues affect visual processing at the behavioral and neuronal population levels.…”

Section: Introductionmentioning

confidence: 99%

Cross-Modal Cue Effects in Motion Processing

et al. 2019

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The everyday environment brings to our sensory systems competing inputs from different modalities. The ability to filter these multisensory inputs in order to identify and efficiently utilize useful spatial cues is necessary to detect and process the relevant information. In the present study, we investigate how feature-based attention affects the detection of motion across sensory modalities. We were interested to determine how subjects use intramodal, cross-modal auditory, and combined audiovisual motion cues to attend to specific visual motion signals. The results showed that in most cases, both the visual and the auditory cues enhance feature-based orienting to a transparent visual motion pattern presented among distractor motion patterns. Whereas previous studies have shown cross-modal effects of spatial attention, our results demonstrate a spread of cross-modal feature-based attention cues, which have been matched for the detection threshold of the visual target. These effects were very robust in comparisons of the effects of valid vs. invalid cues, as well as in comparisons between cued and uncued valid trials. The effect of intramodal visual, cross-modal auditory, and bimodal cues also increased as a function of motion-cue salience. Our results suggest that orienting to visual motion patterns among distracters can be facilitated not only by intramodal priors, but also by feature-based cross-modal information from the auditory system.

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Computational model for neural representation of multiple disparities

Cited by 6 publications

References 41 publications

Stereo transparency in ambiguous stereograms generated by overlapping two identical dot patterns

Stereo transparency in ambiguous stereograms generated by overlapping two identical dot patterns

Early computational processing in binocular vision and depth perception

Cross-Modal Cue Effects in Motion Processing

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