ArticleFrontiers in computational neuroscience2015
Computational modeling of the neural representation of object shape in the primate ventral visual system.
Article in Frontiers in computational neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Hierarchical feature binding in a spiking neural network model of the primate ventral visual pathway.PLoS computational biology · 2026Article
- Learning a Model of Shape Selectivity in V4 Cells Reveals Shape Encoding Mechanisms in the Brain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- The Strasbourg Visual Scale: A Novel Method to Assess Visual Hallucinations.Frontiers in psychiatry · 2021Article
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Authors and funding
5 authors.
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Abstract
Neurons in successive stages of the primate ventral visual pathway encode the spatial structure of visual objects. In this paper, we investigate through computer simulation how these cell firing properties may develop through unsupervised visually-guided learning. Individual neurons in the model are shown to exploit statistical regularity and temporal continuity of the visual inputs during training to learn firing properties that are similar to neurons in V4 and TEO. Neurons in V4 encode the conformation of boundary contour elements at a particular position within an object regardless of the location of the object on the retina, while neurons in TEO integrate information from multiple boundary contour elements. This representation goes beyond mere object recognition, in which neurons simply respond to the presence of a whole object, but provides an essential foundation from which the brain is subsequently able to recognize the whole object.
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