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The '''visual cortex''' of the [[brain]] is the area of the [[cerebral cortex]] that processes [[visual perception|visual information]]. It is located in the [[occipital lobe]]. Sensory input originating from the [[eye]]s travels through the [[lateral geniculate nucleus]] in the [[thalamus]] and then reaches the visual cortex. The area of the visual cortex that receives the sensory input from the lateral geniculate nucleus is the primary visual cortex, also known as visual area 1 ([[Brodmann area#BA17,V1|V1]]), [[Brodmann area]] 17<!---don't wikilink it as long as it redirects to here--->, or the '''striate cortex'''. The [[extrastriate cortex|extrastriate]] areas consist of visual areas 2, 3, 4, and 5 (also known as V2, V3, V4, and V5, or [[Brodmann area 18]] and all [[Brodmann area 19]]).<ref>{{cite web |
Both [[cerebral hemisphere|hemispheres of the brain]] include a visual cortex; the visual cortex in the left hemisphere receives signals from the right [[visual field]], and the visual cortex in the right hemisphere receives signals from the left visual field.
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Research on V1 has also revealed the presence of orientation-selective cells, which respond preferentially to stimuli with a specific orientation, contributing to the perception of edges and contours. The discovery of these orientation-selective cells has been fundamental in shaping our understanding of how V1 processes visual information.
Furthermore, V1 exhibits plasticity, allowing it to undergo functional and structural changes in response to sensory experience. Studies have demonstrated that sensory deprivation or exposure to enriched environments can lead to alterations in the organization and responsiveness of V1 neurons
The primary visual cortex, which is defined by its function or stage in the visual system, is approximately equivalent to the striate cortex, also known as Brodmann area 17, which is defined by its anatomical ___location. The name "striate cortex" is derived from the line of Gennari, a distinctive stripe visible to the naked eye that represents [[myelin]]ated [[axons]] from the [[lateral geniculate body]] terminating in layer 4 of the [[gray matter]].▼
▲The primary visual cortex, which is defined by its function or stage in the visual system, is approximately equivalent to the striate cortex, also known as Brodmann area 17, which is defined by its anatomical ___location. The name "striate cortex" is derived from the line of Gennari, a distinctive stripe visible to the naked eye.
Additionally, the functional significance of the striate cortex extends beyond its role as the primary visual cortex. It serves as a crucial hub for the initial processing of visual information, such as the analysis of basic features like orientation, spatial frequency, and color. The integration of these features in the striate cortex forms the foundation for more complex visual processing carried out in higher-order visual areas. Recent neuroimaging studies have contributed to a deeper understanding of the dynamic interactions within the striate cortex and its connections with other visual and non-visual brain regions, shedding light on the
▲Brodmann area 17 is just one subdivision of the broader Brodmann areas, which are regions of the cerebral cortex defined based on cytoarchitectural differences. In the case of the striate cortex, the line of Gennari corresponds to a band rich in myelinated nerve fibers, providing a clear marker for the primary visual processing region.{{cn|date=October 2024}}
The primary visual cortex is divided into six functionally distinct layers, labeled 1 to 6. Layer 4, which receives most visual input from the [[lateral geniculate nucleus]] (LGN), is further divided into 4 layers, labelled 4A, 4B, 4Cα, and 4Cβ. Sublamina 4Cα receives mostly [[Magnocellular cell|magnocellular]] input from the LGN, while layer 4Cβ receives input from [[Parvocellular cell|parvocellular]] pathways.<ref>{{cite journal | vauthors = Hubel DH, Wiesel TN | title = Laminar and columnar distribution of geniculo-cortical fibers in the macaque monkey | journal = The Journal of Comparative Neurology | volume = 146 | issue = 4 | pages = 421–450 | date = December 1972 | pmid = 4117368 | doi = 10.1002/cne.901460402 | s2cid = 6478458 }}</ref><ref>{{cite book |last1=Churchland |first1=Patricia Smith |last2=Sejnowski |first2=Terrence Joseph |author1-link=Patricia Churchland |author2-link=Terry Sejnowski |title=[[The Computational Brain]] |publisher=[[MIT Press]] |___location=Cambridge, Massachusetts |year=1992 |isbn=978-0-262-53120-7 |page=149}}</ref>▼
▲Additionally, the functional significance of the striate cortex extends beyond its role as the primary visual cortex. It serves as a crucial hub for the initial processing of visual information, such as the analysis of basic features like orientation, spatial frequency, and color. The integration of these features in the striate cortex forms the foundation for more complex visual processing carried out in higher-order visual areas. Recent neuroimaging studies have contributed to a deeper understanding of the dynamic interactions within the striate cortex and its connections with other visual and non-visual brain regions, shedding light on the intricate neural circuits that underlie visual perception.<ref>{{cite journal |vauthors=Glickstein M, Rizzolatti G |title=Francesco Gennari and the structure of the cerebral cortex |journal=Trends in Neurosciences |volume=7 |issue=12 |pages=464–467 |date=1 December 1984|doi=10.1016/S0166-2236(84)80255-6 |s2cid=53168851 }}</ref> that represents [[myelin]]ated [[axons]] from the [[lateral geniculate body]] terminating in layer 4 of the [[gray matter]].
The average number of neurons in the adult human primary visual cortex in each hemisphere has been estimated at 140 million.<ref name="Leuba-Kraftsik-1994">{{cite journal | vauthors = Leuba G, Kraftsik R | title = Changes in volume, surface estimate, three-dimensional shape and total number of neurons of the human primary visual cortex from midgestation until old age | journal = Anatomy and Embryology | volume = 190 | issue = 4 | pages = 351–366 | date = October 1994 | pmid = 7840422 | doi = 10.1007/BF00187293 | s2cid = 28320951 }}</ref> The volume of each V1 area in an adult human is about 5400mm<math>{}^3</math> on average. A study of 25 hemispheres from 15 normal individuals with average age 59 years at autopsy found a very high variation, from 4272 to 7027mm<math>{}^3</math> for the right hemisphere (mean 5692mm<math>{}^3</math>), and from 3185 to 7568mm<math>{}^3</math> for the left hemisphere (mean 5119mm<math>{}^3</math>), with 0.81 correlation between left and right hemispheres.<ref>{{cite journal |last1=Andrews |first1=Timothy J. |last2=Halpern |first2=Scott D. |last3=Purves |first3=Dale |title=Correlated Size Variations in Human Visual Cortex, Lateral Geniculate Nucleus, and Optic Tract |journal=Journal of Neuroscience |date=1997 |volume=17 |issue=8 |pages=2859–2868 |doi=10.1523/JNEUROSCI.17-08-02859.1997 |doi-access=free|pmc=6573115 }}</ref> The same study found average V1 area 2400mm<math>{}^2</math> per hemisphere, but with very high variability. (Right hemisphere mean 2477mm<math>{}^2</math>, range 1441–3221mm<math>{}^2</math>. Left hemisphere mean 2315mm<math>{}^2</math>, range 1438–3365mm<math>{}^2</math>.)
▲The primary visual cortex is divided into six functionally distinct layers, labeled 1 to 6. Layer 4, which receives most visual input from the [[lateral geniculate nucleus]] (LGN), is further divided into 4 layers, labelled 4A, 4B, 4Cα, and 4Cβ. Sublamina 4Cα receives mostly [[Magnocellular cell|magnocellular]] input from the LGN, while layer 4Cβ receives input from [[Parvocellular cell|parvocellular]] pathways.<ref>{{cite journal | vauthors = Hubel DH, Wiesel TN | title = Laminar and columnar distribution of geniculo-cortical fibers in the macaque monkey | journal = The Journal of Comparative Neurology | volume = 146 | issue = 4 | pages = 421–450 | date = December 1972 | pmid = 4117368 | doi = 10.1002/cne.901460402 | s2cid = 6478458 }}</ref>
=== Function ===
{{further|Visual system}}
{{technical|date=September 2016}}
The initial stage of visual processing within the visual cortex, known as V1, plays a fundamental role in shaping our perception of the visual world. V1 possesses a meticulously defined map, referred to as the retinotopic map, which intricately organizes spatial information from the visual field. In humans, the upper bank of the calcarine sulcus in the occipital lobe robustly responds to the lower half of the visual field, while the lower bank responds to the upper half. This retinotopic mapping conceptually represents a projection of the visual image from the retina to V1.
The importance of this retinotopic organization lies in its ability to preserve spatial relationships present in the external environment. Neighboring neurons in V1 exhibit responses to adjacent portions of the visual field, creating a systematic representation of the visual scene. This mapping extends both vertically and horizontally, ensuring the conservation of both horizontal and vertical relationships within the visual input.
Moreover, the retinotopic map demonstrates a remarkable degree of plasticity, adapting to alterations in visual experience. Studies have revealed that changes in sensory input, such as those induced by visual training or deprivation, can lead to shifts in the retinotopic map
Beyond its spatial processing role, the retinotopic map in V1 establishes
The correspondence between specific locations in V1 and the subjective visual field is exceptionally precise, even extending to map the blind spots of the retina. Evolutionarily, this correspondence is a fundamental feature found in most animals possessing a V1. In humans and other species with a fovea (cones in the retina), a substantial portion of V1 is mapped to the small central portion of the visual
Notably, neurons in V1 have the smallest receptive field size, signifying the highest resolution, among visual cortex microscopic regions. This specialization equips V1 with the ability to capture fine details
In addition to its role in spatial processing, the retinotopic map in V1 is
The tuning properties of V1 neurons (what the neurons respond to) differ greatly over time. Early in time (40 ms and further) individual V1 neurons have strong tuning to a small set of stimuli. That is, the neuronal responses can discriminate small changes in visual [[Orientation (mental)|orientations]], [[spatial frequencies]] and [[color]]s (as in the optical system of a [[camera obscura]], but projected onto [[retina]]l cells of the eye, which are clustered in density and fineness).<ref name= kepler1604 /> Each V1 neuron propagates a signal from a retinal cell, in continuation. Furthermore, individual V1 neurons in humans and other animals with [[binocular vision]] have ocular dominance, namely tuning to one of the two eyes. In V1, and primary sensory cortex in general, neurons with similar tuning properties tend to cluster together as [[cortical column]]s. [[David Hubel]] and [[Torsten Wiesel]] proposed the classic ice-cube organization model of cortical columns for two tuning properties: [[ocular dominance columns|ocular dominance]] and orientation. However, this model cannot accommodate the color, spatial frequency and many other features to which neurons are tuned {{Citation needed|date=November 2011}}. The exact organization of all these cortical columns within V1 remains a hot topic of current research.
The receptive fields of V1 neurons<ref>{{cite journal |vauthors=DeAngelis GC, Ohzawa I, Freeman RD |date=October 1995 |title=Receptive-field dynamics in the central visual pathways |journal=Trends in Neurosciences |volume=18 |issue=10 |pages=451–458 |doi=10.1016/0166-2236(95)94496-r |pmid=8545912 |s2cid=12827601}}</ref><ref>{{Cite book |title=The Visual Neurosciences, 2-vol. Set |vauthors=DeAngelis GC, Anzai A |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 |chapter=A Modern View of the Classical Receptive Field: Linear and Nonlinear Spatiotemporal Processing by V1 Neurons |doi=10.7551/mitpress/7131.003.0052 |chapter-url=https://direct.mit.edu/books/book/5395/chapter/3948206/A-Modern-View-ofthe-Classical-Receptive-Field}}</ref> resemble Gabor functions, so the operation of the visual cortex has been compared to the [[Gabor transform]].{{Citation needed|date=May 2023}}
Later in time (after 100 ms), neurons in V1 are also sensitive to the more global organisation of the scene (Lamme & Roelfsema, 2000).<ref>{{cite thesis | vauthors = Barghout L |title=Vision: How Global Perceptual Context Changes Local Contrast Processing | degree = Ph.D. |date=2003 |publisher=Scholar's Press |isbn=978-3-639-70962-9 |url= https://www.morebooks.de/store/gb/book/vision/isbn/978-3-639-70962-9 }} Updated to include computer vision techniques</ref> These response properties probably stem from recurrent [[feedback]] processing (the influence of higher-tier cortical areas on lower-tier cortical areas) and lateral connections from [[Pyramidal cell|pyramidal neurons]].<ref name="Hupé_1998">{{cite journal | vauthors = Hupé JM, James AC, Payne BR, Lomber SG, Girard P, Bullier J | title = Cortical feedback improves discrimination between figure and background by V1, V2 and V3 neurons | journal = Nature | volume = 394 | issue = 6695 | pages = 784–7 | date = August 1998 | pmid = 9723617 | doi = 10.1038/29537 | bibcode = 1998Natur.394..784H }}</ref> While feedforward connections are mainly driving, feedback connections are mostly modulatory in their effects.<ref name="Angelucci_2003">{{cite journal | vauthors = Angelucci A, Bullier J | title = Reaching beyond the classical receptive field of V1 neurons: horizontal or feedback axons? | journal = Journal of Physiology, Paris | volume = 97 | issue = 2–3 | pages = 141–54 | date = 2003 | pmid = 14766139 | doi = 10.1016/j.jphysparis.2003.09.001 }}</ref><ref name="Bullier_2001">{{cite book | vauthors = Bullier J, Hupé JM, James AC, Girard P | title = The role of feedback connections in shaping the responses of visual cortical neurons | chapter = Chapter 13 the role of feedback connections in shaping the responses of visual cortical neurons | series = Progress in Brain Research | volume = 134 | pages = 193–204 | date = 2001 | pmid = 11702544 | doi = 10.1016/s0079-6123(01)34014-1 | isbn = 978-0-444-50586-6 }}</ref> Evidence shows that feedback originating in higher-level areas such as V4, IT, or MT, with bigger and more complex receptive fields, can modify and shape V1 responses, accounting for contextual or extra-classical receptive field effects.<ref name="Murray_2004">{{cite journal | vauthors = Murray SO, Schrater P, Kersten D | title = Perceptual grouping and the interactions between visual cortical areas | journal = Neural Networks | volume = 17 | issue = 5–6 | pages = 695–705 | date = 2004 | pmid = 15288893 | doi = 10.1016/j.neunet.2004.03.010 }}</ref><ref name="Huang_2007">{{cite journal | vauthors = Huang JY, Wang C, Dreher B | title = The effects of reversible inactivation of postero-temporal visual cortex on neuronal activities in cat's area 17 | journal = Brain Research | volume = 1138 | issue = | pages = 111–28 | date = March 2007 | pmid = 17276420 | doi = 10.1016/j.brainres.2006.12.081 }}</ref><ref name="Williams_2008">{{cite journal | vauthors = Williams MA, Baker CI, Op de Beeck HP, Shim WM, Dang S, Triantafyllou C, Kanwisher N | title = Feedback of visual object information to foveal retinotopic cortex | journal = Nature Neuroscience | volume = 11 | issue = 12 | pages = 1439–45 | date = December 2008 | pmid = 18978780 | pmc = 2789292 | doi = 10.1038/nn.2218 }}</ref>▼
▲Later in time (after 100 ms), neurons in V1 are also sensitive to the more global organisation of the scene
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).▼
▲The visual information relayed
{{anchor|saliencyMap}}
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'''Visual area V2''', or '''secondary visual cortex''', also called '''prestriate cortex''',<ref>{{cite book | vauthors = Gazzaniga MS, Ivry RB, Mangun GR | date = 2002 | title = Cognitive Neuroscience: The Biology of the Mind | edition = 2nd | publisher = W W Norton & Co Inc | isbn = 978-0-393-97777-6 }}</ref> receives strong feedforward connections from V1 (direct and via the pulvinar) and sends robust connections to V3, V4, and V5. Additionally, it plays a crucial role in the integration and processing of visual information.
The feedforward connections from V1 to V2 contribute to the hierarchical processing of visual stimuli. V2 neurons build upon the basic features detected in V1, extracting more complex visual attributes such as texture, depth, and color. This hierarchical processing is essential for the construction of a more
Furthermore, the reciprocal feedback connections from V2 to V1 play a significant role in modulating the activity of V1 neurons. This feedback loop is thought to be involved in processes such as attention, perceptual grouping, and figure-ground segregation. The dynamic interplay between V1 and V2 highlights the intricate nature of information processing within the visual system.
Moreover, V2's connections with subsequent visual areas, including V3, V4, and V5, contribute to the formation of a distributed network for visual processing. These connections enable the integration of different visual features, such as motion and form, across multiple stages of the visual hierarchy.<ref>Taylor, Katherine. and Jeanette Rodriguez.
In terms of anatomy, V2 is split into four quadrants, a [[Dorsum (biology)|dorsal]] and [[ventral]] representation in the left and the right [[cerebral hemisphere|hemispheres]]. Together, these four regions provide a complete map of the visual world. V2 has many properties in common with V1: Cells are tuned to simple properties such as orientation, spatial frequency, and color. The responses of many V2 neurons are also modulated by more complex properties, such as the orientation of [[illusory contours]],<ref name="illusory contours">{{cite journal | vauthors = von der Heydt R, Peterhans E, Baumgartner G | title = Illusory contours and cortical neuron responses | journal = Science | volume = 224 | issue = 4654 | pages = 1260–1262 | date = June 1984 | pmid = 6539501 | doi = 10.1126/science.6539501 | bibcode = 1984Sci...224.1260V }}</ref><ref name="A. Anzai, X. Peng 2007"/> [[binocular disparity]],<ref name="stereoscopic edges">{{cite journal | vauthors = von der Heydt R, Zhou H, Friedman HS | title = Representation of stereoscopic edges in monkey visual cortex | journal = Vision Research | volume = 40 | issue = 15 | pages = 1955–1967 | date = 2000 | pmid = 10828464 | doi = 10.1016/s0042-6989(00)00044-4 | s2cid = 10269181 | doi-access = free }}</ref> and whether the stimulus is part of the figure or the ground.<ref>{{cite journal | vauthors = Qiu FT, von der Heydt R | title = Figure and ground in the visual cortex: v2 combines stereoscopic cues with gestalt rules | journal = Neuron | volume = 47 | issue = 1 | pages = 155–166 | date = July 2005 | pmid = 15996555 | pmc = 1564069 | doi = 10.1016/j.neuron.2005.05.028 }}</ref><ref>{{cite journal | vauthors = Maruko I, Zhang B, Tao X, Tong J, Smith EL, Chino YM | title = Postnatal development of disparity sensitivity in visual area 2 (v2) of macaque monkeys | journal = Journal of Neurophysiology | volume = 100 | issue = 5 | pages = 2486–2495 | date = November 2008 | pmid = 18753321 | pmc = 2585398 | doi = 10.1152/jn.90397.2008 }}</ref> Recent research has shown that V2 cells show a small amount of attentional modulation (more than V1, less than V4), are tuned for moderately complex patterns, and may be driven by multiple orientations at different subregions within a single receptive field.
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Recent work has shown that V4 exhibits long-term plasticity,<ref>{{cite journal | vauthors = Schmid MC, Schmiedt JT, Peters AJ, Saunders RC, Maier A, Leopold DA | title = Motion-sensitive responses in visual area V4 in the absence of primary visual cortex | journal = The Journal of Neuroscience | volume = 33 | issue = 48 | pages = 18740–18745 | date = November 2013 | pmid = 24285880 | pmc = 3841445 | doi = 10.1523/JNEUROSCI.3923-13.2013 | doi-access = free }}</ref> encodes stimulus salience, is gated by signals coming from the [[frontal eye fields]],<ref>{{cite journal | vauthors = Moore T, Armstrong KM | title = Selective gating of visual signals by microstimulation of frontal cortex | journal = Nature | volume = 421 | issue = 6921 | pages = 370–373 | date = January 2003 | pmid = 12540901 | doi = 10.1038/nature01341 | s2cid = 4405385 | bibcode = 2003Natur.421..370M | author-link1 = Tirin Moore }}</ref> and shows changes in the spatial profile of its receptive fields with attention.{{citation needed|date=March 2016}} In addition, it has recently been shown that activation of area V4 in humans (area V4h) is observed during the perception and retention of the color of objects, but not their shape.<ref>{{cite conference | vauthors = Kozlovskiy S, Rogachev A |title=How Areas of Ventral Visual Stream Interact When We Memorize Color and Shape Information |date=2021 |book-title=Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics. Intercognsci 2020 |series=Advances in Intelligent Systems and Computing |volume=1358 |pages=95–100 | veditors = Velichkovsky BM, Balaban PM, Ushakov VL |place=Cham |publisher=Springer International Publishing |language=en |doi=10.1007/978-3-030-71637-0_10 |isbn=978-3-030-71636-3 }}</ref><ref>{{Cite journal | vauthors = Kozlovskiy S, Rogachev A |date=October 2021 |title=Ventral Visual Cortex Areas and Processing of Color and Shape in Visual Working Memory |journal=International Journal of Psychophysiology |language=en |volume=168 |issue=Supplement |pages=S155–S156 |doi=10.1016/j.ijpsycho.2021.07.437|s2cid=239648133 }}</ref>
== Middle temporal visual area (V5) <span class="anchor" id="V5"></span> ==<!--
The '''middle temporal visual area''' ('''MT''' or '''V5''') is a region of extrastriate visual cortex. In several species of both [[New World monkey]]s and [[Old World monkey]]s the MT area contains a high concentration of direction-selective neurons.<ref name="BornBradley" /> The MT in primates is thought to play a major role in the [[motion perception|perception of motion]], the integration of local motion signals into global percepts, and the guidance of some [[Eye movement (sensory)|eye movements]].<ref name="BornBradley">{{cite journal | vauthors = Born RT, Bradley DC | title = Structure and function of visual area MT | journal = Annual Review of Neuroscience | volume = 28 | pages = 157–189 | year = 2005 | pmid = 16022593 | doi = 10.1146/annurev.neuro.26.041002.131052 }}</ref>
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