Dataset Information

Adaptive Neuromorphic Circuit for Stereoscopic Disparity Using Ocular Dominance Map.

ABSTRACT: Stereopsis or depth perception is a critical aspect of information processing in the brain and is computed from the positional shift or disparity between the images seen by the two eyes. Various algorithms and their hardware implementation that compute disparity in real time have been proposed; however, most of them compute disparity through complex mathematical calculations that are difficult to realize in hardware and are biologically unrealistic. The brain presumably uses simpler methods to extract depth information from the environment and hence newer methodologies that could perform stereopsis with brain like elegance need to be explored. This paper proposes an innovative aVLSI design that leverages the columnar organization of ocular dominance in the brain and uses time-staggered Winner Take All (ts-WTA) to adaptively create disparity tuned cells. Physiological findings support the presence of disparity cells in the visual cortex and show that these cells surface as a result of binocular stimulation received after birth. Therefore, creating in hardware cells that can learn different disparities with experience not only is novel but also is biologically more realistic. These disparity cells, when allowed to interact diffusively on a larger scale, can be used to adaptively create stable topological disparity maps in silicon.

SUBMITTER: Sharma S

PROVIDER: S-EPMC4868909 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Adaptive Neuromorphic Circuit for Stereoscopic Disparity Using Ocular Dominance Map.

Sharma Sheena S Gupta Priti P Markan C M CM

Neuroscience journal 20160503

Stereopsis or depth perception is a critical aspect of information processing in the brain and is computed from the positional shift or disparity between the images seen by the two eyes. Various algorithms and their hardware implementation that compute disparity in real time have been proposed; however, most of them compute disparity through complex mathematical calculations that are difficult to realize in hardware and are biologically unrealistic. The brain presumably uses simpler methods to e ...[more]

PMID: 27243029

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Project description:In invertebrate predators such as the praying mantis and vertebrate predators such as wild cats the ability to detect small differences in inter-ocular retinal disparities is a critical means for accurately determining the depth of moving objects such as prey. In mammals, the first neurons along the visual pathway that encode binocular disparities are found in the visual cortex. However, a precise functional architecture for binocular disparity has never been demonstrated in any species, and coarse maps for disparity have been found in only one primate species. Moreover, the dominant approach for assaying the developmental plasticity of binocular cortical neurons used monocular tests of ocular dominance to infer binocular function. The few studies that examined the relationship between ocular dominance and binocular disparity of individual cells used single-unit recordings and have provided conflicting results regarding whether ocular dominance can predict the selectivity or sensitivity to binocular disparity. We used two-photon calcium imaging to sample the response to monocular and binocular visual stimuli from nearly every adjacent neuron in a small region of the cat visual cortex, area 18. Here we show that local circuits for ocular dominance always have smooth and graded transitions from one apparently monocular functional domain to an adjacent binocular region. Most unexpectedly, we discovered a new map in the cat visual cortex that had a precise functional micro-architecture for binocular disparity selectivity. At the level of single cells, ocular dominance was unrelated to binocular disparity selectivity or sensitivity. When the local maps for ocular dominance and binocular disparity both had measurable gradients at a given cortical site, the two gradient directions were orthogonal to each other. Together, these results indicate that, from the perspective of the spiking activity of individual neurons, ocular dominance cannot predict binocular disparity tuning. However, the precise local arrangement of ocular dominance and binocular disparity maps provide new clues regarding how monocular and binocular depth cues may be combined and decoded.

Dataset Information

Adaptive Neuromorphic Circuit for Stereoscopic Disparity Using Ocular Dominance Map.

Publications

Adaptive Neuromorphic Circuit for Stereoscopic Disparity Using Ocular Dominance Map.

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