Visual cortex: Difference between revisions

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The visual information relayed to V1 is not coded in terms of spatial (or optical) imagery{{citation needed|date=July 2020}} but rather are better described as [[edge detection]].<ref>{{cite journal | vauthors = Kesserwani H | title = The Biophysics of Visual Edge Detection: A Review of Basic Principles | journal = Cureus | volume = 12 | issue = 10 | pages = e11218 | date = October 2020 | pmid = 33269147 | pmc = 7706146 | doi = 10.7759/cureus.11218 | doi-access = free }}</ref> As an example, for an image comprising half side black and half side white, the dividing line between black and white has strongest local contrast (that is, edge detection) and is encoded, while few neurons code the brightness information (black or white per se). As information is further relayed to subsequent visual areas, it is coded as increasingly non-local frequency/phase signals. Note that, at these early stages of cortical visual processing, spatial ___location of visual information is well preserved amid the local contrast encoding (edge detection).

A theoretical explanation of the computational function of the simple cells in the primary visual cortex has been presented in.<ref name=Lin13BICY>{{cite journal | vauthors = Lindeberg T | title = A computational theory of visual receptive fields | journal = Biological Cybernetics | volume = 107 | issue = 6 | pages = 589–635 | date = December 2013 | pmid = 24197240 | pmc = 3840297 | doi = 10.1007/s00422-013-0569-z }}</ref><ref name=Lin21Heliyon>{{cite journal | vauthors = Lindeberg T | title = Normative theory of visual receptive fields | journal = Heliyon | volume = 7 | issue = 1 | pages = e05897 | date = January 2021 | pmid = 33521348 | pmc = 7820928 | doi = 10.1016/j.heliyon.2021.e05897 | doi-access = free | bibcode = 2021Heliy...705897L }}</ref><ref name=Lin23Front>{{cite journal | vauthors = Lindeberg T | title = Covariance properties under natural image transformations for the generalised Gaussian derivative model for visual receptive fields | journal = Frontiers in Computational Neuroscience | volume = 17 | pages = 1189949 | date = 2023 | pmid = 37398936 | pmc = 10311448 | doi = 10.3389/fncom.2023.1189949 | doi-access = free }}</ref> It is described how receptive field shapes similar to those found by the biological receptive field measurements performed by DeAngelis et al.<ref>{{cite journal | vauthors = DeAngelis GC, Ohzawa I, Freeman RD | title = Receptive-field dynamics in the central visual pathways | journal = Trends in Neurosciences | volume = 18 | issue = 10 | pages = 451–458 | date = October 1995 | pmid = 8545912 | doi = 10.1016/0166-2236(95)94496-r | s2cid = 12827601 }}</ref><ref>{{Cite book |chapter-url=https://direct.mit.edu/books/book/5395/chapter/3948206/A-Modern-View-ofthe-Classical-Receptive-Field |chapter=A Modern View oftheof the Classical Receptive Field: Linear and Nonlinear Spatiotemporal Processing by V1 Neurons |vauthors=DeAngelis GC, Anzai A |title=The Visual Neurosciences, 2-vol. Set |date=2003-11-21 |publisher=The MIT Press |isbn=978-0-262-27012-0 |veditors=Chalupa LM, Werner JS |volume=1 |___location=Cambridge |pages=704–719 |language=en |doi=10.7551/mitpress/7131.003.0052 }}</ref> can be derived as a consequence of structural properties of the environment in combination with internal consistency requirements to guarantee consistent image representations over multiple spatial and temporal scales. It is also described how the characteristic receptive field shapes, tuned to different scales, orientations and directions in image space, allow the visual system to compute invariant responses under natural image transformations at higher levels in the visual hierarchy.<ref name=Lin13PONE>{{cite journal | vauthors = Lindeberg T | title = Invariance of visual operations at the level of receptive fields | journal = PLOS ONE | volume = 8 | issue = 7 | pages = e66990 | year = 2013 | pmid = 23894283 | pmc = 3716821 | doi = 10.1371/journal.pone.0066990 | doi-access = free | arxiv = 1210.0754 | bibcode = 2013PLoSO...866990L }}</ref><ref name=Lin21Heliyon/><ref name=Lin23Front/>

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