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{{short description|Region of the brain that processes visual information}}
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{{Infobox brain
| Name = Visual cortex
| Latin =
| Image = Brodmann areas 17 18 19.png
| Caption = View of the brain from behind. Red = Brodmann area 17 (primary visual cortex); orange = area 18; yellow = area 19
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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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The primary visual cortex (V1) is located in and around the [[calcarine fissure]] in the [[occipital lobe]]. Each hemisphere's V1 receives information directly from its ipsilateral [[lateral geniculate nucleus]] that receives signals from the contralateral visual hemifield.
[[Neuron]]s in the visual cortex fire [[action potential]]s when visual stimuli appear within their [[receptive field]]. By definition, the receptive field is the region within the entire visual field that elicits an action potential.
Furthermore, the arrangement of receptive fields in V1 is retinotopic, meaning neighboring cells in V1 have receptive fields that correspond to adjacent portions of the visual field. This spatial organization allows for a systematic representation of the visual world within V1. Additionally, recent studies have delved into the role of contextual modulation in V1, where the perception of a stimulus is influenced not only by the stimulus itself but also by the surrounding context, highlighting the intricate processing capabilities of V1 in shaping our visual experiences.<ref>{{cite journal | vauthors = Fişek M, Herrmann D, Egea-Weiss A, Cloves M, Bauer L, Lee TY, Russell LE, Häusser M | title = Cortico-cortical feedback engages active dendrites in visual cortex | journal = Nature | volume = 617 | issue = 7962 | pages = 769–776 | date = May 2023 | pmid = 37138089 | pmc = 10244179 | doi = 10.1038/s41586-023-06007-6 | bibcode = 2023Natur.617..769F }}</ref>
The visual cortex receives its blood supply primarily from the [[calcarine artery|calcarine branch]] of the [[posterior cerebral artery]].
The size of V1, V2, and V3 can vary three-fold, a difference that is partially inherited.<ref name="Benson Yoon Forenzo Engel 2022">{{cite journal |
== Psychological model of the neural processing of visual information ==
{{Main|Two-streams hypothesis}}
[[File:Ventral-dorsal streams.svg|thumb|right|300px|The [[dorsal stream]] (green) and [[ventral stream]] (purple) are shown.
=== Ventral-dorsal model ===
V1 transmits information to two primary pathways, called the ventral stream and the dorsal stream.<ref>{{cite book |title=Computer Vision, Imaging and Computer Graphics Theory and Applications |location=Berlin, Germany |
* The '''[[Two-streams hypothesis#Ventral stream|ventral stream]]''' begins with V1, goes through visual area V2, then through visual area V4, and to the [[inferior temporal cortex]] (IT cortex).
* The '''[[Two-streams hypothesis#Dorsal stream|dorsal stream]]''' begins with V1, goes through Visual area V2, then to the [[dorsomedial area]] (DM/V6) and
The what vs. where account of the ventral/dorsal pathways was first described by [[Leslie Ungerleider|Ungerleider]] and [[Mortimer Mishkin|Mishkin]].<ref
▲V1 transmits information to two primary pathways, called the ventral stream and the dorsal stream.<ref>{{cite book |title=Computer Vision, Imaging and Computer Graphics Theory and Applications |location=Berlin, Germany |first1=José |last1=Braz |first2=Julien |last2=Pettré |first3=Paul |last3=Richard |first4=Andreas |last4=Kerren |first5=Lars |last5=Linsen |first6=Sebastiano |last6=Battiato |first7=Francisco |last7=Imai |publisher=[[Springer (publisher)|Springer]] |date=February 11, 2016 |page=377 |isbn=978-3-319-29971-6 |chapter=Algorithmic Optimnizations in the HMAX Model Targeted for Efficient Object Recognition |chapter-url=https://books.google.com/books?id=hpKRCwAAQBAJ&pg=PA377 |editor-last=Bitar |editor-first=Ahmad W. |editor2-last=Mansour |editor2-first=Mohamad M. |editor3-last=Chehab |editor3-first=Ali}}</ref>
▲* The '''[[Two-streams hypothesis#Ventral stream|ventral stream]]''' begins with V1, goes through visual area V2, then through visual area V4, and to the [[inferior temporal cortex]] (IT cortex). The ventral stream, sometimes called the "What Pathway", is associated with form recognition and object representation. It is also associated with storage of [[long-term memory]].
▲* The '''[[Two-streams hypothesis#Dorsal stream|dorsal stream]]''' begins with V1, goes through Visual area V2, then to the [[dorsomedial area]] (DM/V6) and medial temporal area (MT/V5) and to the [[posterior parietal cortex]]. The dorsal stream, sometimes called the "Where Pathway" or "How Pathway", is associated with motion, representation of object locations, and control of the eyes and arms, especially when visual information is used to guide [[saccade]]s or reaching.
More recently, [[Melvyn A. Goodale|Goodale]] and Milner extended these ideas and suggested that the ventral stream is critical for visual perception whereas the dorsal stream mediates the visual control of skilled actions.<ref name="GoodaleMilner">{{cite journal |
▲The what vs. where account of the ventral/dorsal pathways was first described by [[Leslie Ungerleider|Ungerleider]] and [[Mortimer Mishkin|Mishkin]].<ref name="UngerleiderMishkin82">{{cite book|title=Analysis of Visual Behavior|chapter-url=https://archive.org/details/analysisofvisual00ingl|chapter-url-access=registration|vauthors=Ungerleider LG, Mishkin M|publisher=MIT Press|year=1982|veditors=Ingle DJ, Goodale MA, Mansfield RJ|location=Boston|pages=[https://archive.org/details/analysisofvisual00ingl/page/549 549–586]|chapter=Two Cortical Visual Systems|isbn=978-0-262-09022-3}}</ref>
Work such as
▲More recently, [[Melvyn A. Goodale|Goodale]] and Milner extended these ideas and suggested that the ventral stream is critical for visual perception whereas the dorsal stream mediates the visual control of skilled actions.<ref name="GoodaleMilner">{{cite journal|year=1992|title=Separate pathways for perception and action.|journal=Trends in Neurosciences|volume=15|issue=1|pages=20–25|doi=10.1016/0166-2236(92)90344-8|pmid=1374953|vauthors=Goodale MA, Milner AD|citeseerx=10.1.1.207.6873|s2cid=793980}}</ref> It has been shown that visual illusions such as the [[Ebbinghaus illusion]] distort judgements of a perceptual nature, but when the subject responds with an action, such as grasping, no distortion occurs.<ref name="Aglioti1995">{{cite journal|year=1995|title=Size-contrast illusions deceive the eye but not the hand.|journal=Current Biology|volume=5|issue=6|pages=679–85|doi=10.1016/S0960-9822(95)00133-3|pmid=7552179|vauthors=Aglioti S, DeSouza JF, Goodale MA|s2cid=206111613|doi-access=free}}</ref>
▲Work such as the one from Franz et al.<ref name="Franz2005">{{cite journal|year=2005|title=Illusion effects on grasping are temporally constant not dynamic.|journal=Journal of Experimental Psychology: Human Perception and Performance |volume=31|issue=6|pages=1359–78|doi=10.1037/0096-1523.31.6.1359|pmid=16366795|author=Franz VH, Scharnowski F, Gegenfurtner}}</ref> suggests that both the action and perception systems are equally fooled by such illusions. Other studies, however, provide strong support for the idea that skilled actions such as grasping are not affected by pictorial illusions<ref name="Ganel2003">{{cite journal|year=2003|title=Visual control of action but not perception requires analytical processing of object shape.|journal=Nature|volume=426|issue=6967|pages=664–7|doi=10.1038/nature02156|pmid=14668865|vauthors=Ganel T, Goodale MA|bibcode=2003Natur.426..664G|s2cid=4314969}}</ref><ref name="Ganel2008">{{cite journal|year=2008|title=A double dissociation between action and perception in the context of visual illusions: opposite effects of real and illusory size.|journal=Psychological Science|volume=19|issue=3|pages=221–5|doi=10.1111/j.1467-9280.2008.02071.x|pmid=18315792|vauthors=Ganel T, Tanzer M, Goodale MA|s2cid=15679825}}</ref> and suggest that the action/perception dissociation is a useful way to characterize the functional division of labor between the dorsal and ventral visual pathways in the cerebral cortex.<ref name="Goodale2011">{{cite journal|year=2011|title=Transforming vision into action.|journal=Vision Research |volume=51|issue=14|pages=1567–87|doi=10.1016/j.visres.2010.07.027|pmid=20691202|author=Goodale MA.|doi-access=free}}</ref>
== Primary visual cortex (V1) ==
{{More citations needed section|date=November 2016}}
[[File:visualcortex.gif|right]]
[[File:Visual cortex - low mag.jpg|thumb|right|[[Micrograph]] showing the visual cortex (pink). The [[pia mater]] and [[arachnoid mater]] including [[blood vessel]]s are seen at the top of the image.
The '''primary visual cortex''' is the most studied visual area in the brain. In mammals, it is located in the posterior pole of the occipital lobe and is the simplest, earliest cortical visual area. It is highly specialized for processing information about static and moving objects and is excellent in [[pattern recognition]].
Moreover, V1 is characterized by a laminar organization, with six distinct layers, each playing a unique role in visual processing. Neurons in the superficial layers (II and III) are often involved in local processing and communication within the cortex, while neurons in the deeper layers (V and VI) often send information to other brain regions involved in higher-order visual processing and decision-making.
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.
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<ref>Glickstein M., Rizzolatti G. ''Francesco Gennari and the structure of the cerebral cortex'' Trends in Neurosciences, Volume 7, Issue 12, 464–467, 1 December 1984.</ref> that represents [[myelin]]ated [[axons]] from the [[lateral geniculate body]] terminating in layer 4 of the [[gray matter]].▼
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, highlighting the dynamic nature of this critical visual processing hub.<ref>{{cite journal | vauthors = Coen P, Sit TP, Wells MJ, Carandini M, Harris KD | title = Mouse frontal cortex mediates additive multisensory decisions | journal = Neuron | volume = 111 | issue = 15 | pages = 2432–2447.e13 | date = August 2023 | pmid = 37295419 | pmc = 10957398 | doi = 10.1016/j.neuron.2023.05.008 }}</ref>
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>Hubel, D.H., Wiesel, T.N.. ''Laminar and columnar distribution of geniculo-cortical fibers in the macaque monkey.'' Journal of Comparative Neurology, Issue 146, 421–450, 1972.</ref>▼
{{Clarify|reason=unclear what "highly specialized" and "excellent" means in this sentence.|date=November 2016}}
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 |author1= Leuba G |author2= Kraftsik R |year= 1994 |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 |doi= 10.1007/BF00187293|pmid=7840422 |s2cid= 28320951 }}</ref>▼
▲The primary visual cortex, which is defined by its function or stage in the visual system, is approximately equivalent to the
It's worth noting that 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.
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 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
▲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 |
=== Function ===
{{further|Visual system}}
{{technical|date=September 2016}}
The initial stage of visual processing within the 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.
V1 has a very well-defined map (''the [[retinotopy|retinotopic]] map'') of the spatial information in vision. For example, in humans, the upper bank of the [[calcarine sulcus]] (in the occipital lobe) responds strongly to the lower half of [[visual field]] (below the center), and the lower bank of the calcarine to the upper half of visual field. In concept, this [[retinotopy|retinotopic]] mapping is a projection of the visual image from [[retina]] to V1.<ref name= kepler1604 >Johannes Kepler (1604) Paralipomena to Witelo whereby The Optical Part of Astronomy is Treated (Ad Vitellionem Paralipomena, quibus astronomiae pars optica traditvr, 1604), as cited by A.Mark Smith (2015) From Sight to Light. Kepler modeled the eye as a water-filled glass sphere, and discovered that each point of the scene taken in by the eye projects onto a point on the back of the eye (the retina).</ref> The correspondence between a given location in V1 and in the subjective visual field is very precise: even the [[Blind spot (vision)|blind spots]] of the retina are mapped into V1. In terms of evolution, this correspondence is very basic and found in most animals that possess a V1. In humans and other animals with a [[Fovea centralis|fovea]] ([[Cone cell|cones]] in the retina), a large portion of V1 is mapped to the small, central portion of visual field, a phenomenon known as [[cortical magnification]].<ref>{{cite book|last1=Barghout|first1=Lauren|title=On the Differences Between Peripheral and Foveal Pattern Masking|date=1999|publisher=Masters Thesis. U.C. Berkeley|location=Berkeley, California, U.S.A.}}</ref> Perhaps for the purpose of accurate spatial encoding, neurons in V1 have the smallest [[receptive field]] size (that is, the highest resolution) of any visual cortex microscopic regions.▼
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. This adaptability underscores the brain's capacity to reorganize in response to varying environmental demands, highlighting the dynamic nature of visual processing.
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 mathematical modeling of this function has been compared to [[Gabor transform]]s.{{Citation needed|date=May 2023}}▼
Beyond its spatial processing role, the retinotopic map in V1 establishes intricate connections with other visual areas, forming a network crucial for integrating diverse visual features and constructing a coherent visual percept. This dynamic mapping mechanism is indispensable for our ability to navigate and interpret the visual world effectively.
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 field—a phenomenon termed cortical magnification. This magnification reflects an increased representation and processing capacity devoted to the central visual field, essential for detailed visual acuity and high-resolution processing.
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 |last1=Kesserwani |first1=Hassan |title=The Biophysics of Visual Edge Detection: A Review of Basic Principles |journal=Cureus |date=28 October 2020 |volume=12 |issue=10 |doi=https://doi.org/10.7759%2Fcureus.11218 |url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7706146/ |access-date=19 November 2023}}</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).▼
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 and nuances in the visual input, emphasizing its pivotal role as a critical hub in early visual processing and contributing significantly to our intricate and nuanced visual perception.<ref>{{cite journal | vauthors = Wu F, Lu Q, Kong Y, Zhang Z | title = A Comprehensive Overview of the Role of Visual Cortex Malfunction in Depressive Disorders: Opportunities and Challenges | journal = Neuroscience Bulletin | volume = 39 | issue = 9 | pages = 1426–1438 | date = September 2023 | pmid = 36995569 | pmc = 10062279 | doi = 10.1007/s12264-023-01052-7 | pmc-embargo-date = September 1, 2024 }}</ref>
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 | last1 = Lindeberg | first1 = T. | year = 2013| title = A computational theory of visual receptive fields | doi = 10.1007/s00422-013-0569-z | pmid = 24197240 | pmc = 3840297 | journal = Biological Cybernetics | volume = 107 | issue = 6| pages = 589–635 }}</ref><ref name=Lin21Heliyon>{{cite journal | last1 = Lindeberg | first1 = T. | year = 2021| title = Normative theory of visual receptive fields | doi = 10.1016/j.heliyon.2021.e05897 | journal = Heliyon | volume = 7 | issue = 1| pages = e05897:1–20 | pmid = 33521348 | pmc = 7820928 | bibcode = 2021Heliy...705897L | doi-access = free }}</ref><ref name=Lin23Front>[https://dx.doi.org/10.3389/fncom.2023.1189949 T. Lindeberg "Covariance properties under natural image transformations for the generalized Gaussian derivative model for visual receptive fields", Frontiers in Computational Neuroscience, 17:1189949, 2023.]</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 | last1 = DeAngelis | first1 = G. C. | last2 = Ohzawa | first2 = I. | last3 = Freeman | first3 = R. D. | year = 1995 | title = Receptive field dynamics in the central visual pathways | journal = Trends in Neurosciences | volume = 18 | issue = 10| pages = 451–457 | doi=10.1016/0166-2236(95)94496-r | pmid=8545912| s2cid = 12827601 }}</ref><ref>G. C. DeAngelis and A. Anzai "A modern view of the classical receptive field: linear and non-linear spatio-temporal processing by V1 neurons. In: Chalupa, L.M., Werner, J.S. (eds.) The Visual Neurosciences, vol. 1, pp. 704–719. MIT Press, Cambridge, 2004.</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 | last1 = Lindeberg | first1 = T. | year = 2013| title = Invariance of visual operations at the level of receptive fields | doi = 10.1371/journal.pone.0066990 | pmid = 23894283 | pmc = 3716821 | journal = PLOS ONE | volume = 8 | issue = 7| page = e66990 | arxiv = 1210.0754 | bibcode = 2013PLoSO...866990L | doi-access = free }}</ref><ref name=Lin21Heliyon/><ref name=Lin23Front/>▼
▲
▲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.
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 : the Official Journal of the International Neural Network Society | 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>
▲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 |
▲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 |
{{anchor|saliencyMap}}
In primates, one role of V1 might be to create a [[saliency map]] (highlights what is important) from visual inputs to guide the shifts of attention known as '''gaze shifts'''.<ref name=
According to the [[V1 Saliency Hypothesis]], V1 does this by transforming visual inputs to neural firing rates from millions of neurons, such that the visual location signaled by the highest firing neuron is the most salient location to attract gaze shift. V1's outputs are received by the [[superior colliculus]] (in the mid-brain), among other locations, which reads out the V1 activities to guide gaze shifts.
Differences in size of V1 also seem to have an effect on the [[Interindividual differences in perception|perception of illusions]].<ref name="surface_V1">{{cite journal | vauthors = Schwarzkopf DS, Song C, Rees G | title = The surface area of human V1 predicts the subjective experience of object size |
== V2 == <!--Please keep this header, as it is a redirect -->
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|Caption= The difference V-regions. More images in [[
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'''Visual area V2''', or '''secondary visual cortex''', also called '''prestriate cortex''',<ref>{{cite book | vauthors = Gazzaniga MS, Ivry
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 nuanced and detailed representation of the visual scene.
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|last1=von der Heydt|first1=R|last2=Peterhans|first2=E|last3=Baumgartner|first3=G|title=Illusory contours and cortical neuron responses|journal=Science|date=1984|volume=224|issue=4654|pages=1260–62|doi=10.1126/science.6539501|pmid=6539501|bibcode=1984Sci...224.1260V}}</ref><ref name="A. Anzai, X. Peng 2007"/> [[binocular disparity]],<ref name="stereoscopic edges">{{cite journal|last1=von der Heydt|first1=R|last2=Zhou|first2=H|last3=Friedman|first3=H. S|title=Representation of stereoscopic edges in monkey visual cortex|journal=Vision Research|date=2000|volume=40|issue=15|pages=1955–67|doi=10.1016/s0042-6989(00)00044-4|pmid=10828464|s2cid=10269181|doi-access=free}}</ref> and whether the stimulus is part of the figure or the ground.<ref>{{cite journal|last1=Qiu|first1=F. T|last2=von der Heydt|first2=R|title=Figure and ground in the visual cortex: V2 combines stereoscopic cues with Gestalt rules|journal=Neuron|date=2005|volume=47|issue=1|pages=155–66|doi=10.1016/j.neuron.2005.05.028|pmid=15996555|pmc=1564069}}</ref><ref>{{cite journal|last1=Maruko, I; et alt.|title=Postnatal Development of Disparity Sensitivity in Visual Area 2 (V2) of Macaque Monkeys|journal=Journal of Neurophysiology|date=2008|volume=100|issue=5|pages=2486–2495|doi=10.1152/jn.90397.2008|pmid=18753321|pmc=2585398}}</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.▼
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.
It is argued that the entire ventral visual-to-hippocampal stream is important for visual memory.<ref>{{cite journal|last1=Bussey|first1=T J|last2=Saksida|first2=L. M|author-link2=Lisa Saksida|date=2007|title=Memory, perception, and the ventral visual-perirhinal-hippocampal stream: thinking outside of the boxes|journal=Hippocampus|volume=17|issue=9|pages=898–908|doi=10.1002/hipo.20320|pmid=17636546|s2cid=13271331}}</ref> This theory, unlike the dominant one, predicts that object-recognition memory (ORM) alterations could result from the manipulation in V2, an area that is highly interconnected within the ventral stream of visual cortices. In the monkey brain, this area receives strong feedforward connections from the primary visual cortex (V1) and sends strong projections to other secondary visual cortices (V3, V4, and V5).<ref>{{cite journal|last1=Stepniewska|first1=I|last2=Kaas|first2=J. H.|title=Topographic patterns of V2 cortical connections in macaque monkeys|journal=The Journal of Comparative Neurology|date=1996|volume=371|issue=1|pages=129–152|doi=10.1002/(SICI)1096-9861(19960715)371:1<129::AID-CNE8>3.0.CO;2-5|pmid=8835723|s2cid=8500842}}</ref><ref>{{cite journal|last1=Gattas|first1=R|last2=Sousa|first2=A. P|last3=Mishkin|first3=M|last4=Ungerleider|first4=L. G.|title=Cortical projections of area V2 in the macaque|journal=Cerebral Cortex|date=1997|volume=7|issue=2|pages=110–129|doi=10.1093/cercor/7.2.110|pmid=9087820|doi-access=free}}</ref> Most of the neurons of this area in primates are tuned to simple visual characteristics such as orientation, spatial frequency, size, color, and shape.<ref name="A. Anzai, X. Peng 2007">{{cite journal|last1=Anzai|first1=A|last2=Peng|first2=X|last3=Van Essen|first3=D. C|title=Neurons in monkey visual area V2 encode combinations of orientations|journal=Nature Neuroscience|date=2007|volume=10|issue=10|pages=1313–21|pmid=17873872|doi=10.1038/nn1975|s2cid=6796448}}</ref><ref>{{cite journal|last1=Hegdé|first1=Jay|last2=Van Essen|first2=D. C|title=Selectivity for Complex Shapes in Primate Visual Area V2|journal=The Journal of Neuroscience|date=2000|volume=20|issue=5|pages=RC61|doi=10.1523/JNEUROSCI.20-05-j0001.2000|pmid=10684908|pmc=6772904|doi-access=free}}</ref><ref>{{cite journal|last1=Hegdé|first1=Jay|last2=Van Essen|first2=D. C|title=Temporal dynamics of shape analysis in Macaque visual area V2|journal= Journal of Neurophysiology|date=2004|volume=92|issue=5|pages=3030–3042|doi=10.1152/jn.00822.2003|pmid=15201315|s2cid=6428310}}</ref> Anatomical studies implicate layer 3 of area V2 in visual-information processing. In contrast to layer 3, layer 6 of the visual cortex is composed of many types of neurons, and their response to visual stimuli is more complex.▼
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. “Visual Discrimination.” StatPearls, StatPearls Publishing, 19 September 2022</ref>
In one study, the Layer 6 cells of the V2 cortex were found to play a very important role in the storage of Object Recognition Memory as well as the conversion of short-term object memories into long-term memories.<ref>{{cite journal|last1=López-Aranda et alt.|title=Role of Layer 6 of V2 Visual Cortex in Object Recognition Memory|journal=Science|date=2009|volume=325|issue=5936|pages=87–89|doi=10.1126/science.1170869|pmid=19574389|bibcode=2009Sci...325...87L|s2cid=23990759}}</ref>▼
▲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]].
▲It is argued that the entire ventral visual-to-hippocampal stream is important for visual memory.<ref>{{cite journal |
▲In one study, the Layer 6 cells of the V2 cortex were found to play a very important role in the storage of Object Recognition Memory as well as the conversion of short-term object memories into long-term memories.<ref>{{cite journal |
== Third visual cortex, including area V3 ==
[[File:Visual field maps.jpg|thumb|left|A visual field map of the primary visual cortex and the numerous extrastriate areas.
The term '''third visual complex''' refers to the region of cortex located immediately in front of V2, which includes the region named '''visual area V3''' in humans. The "complex" nomenclature is justified by the fact that some controversy still exists regarding the exact extent of area V3, with some researchers proposing that the cortex located in front of V2 may include two or three functional subdivisions. For example, David Van Essen and others (1986) have proposed the existence of a "dorsal V3" in the upper part of the cerebral hemisphere, which is distinct from the "ventral V3" (or ventral posterior area, VP) located in the lower part of the brain. Dorsal and ventral V3 have distinct connections with other parts of the brain, appear different in sections stained with a variety of methods, and contain neurons that respond to different combinations of visual stimulus (for example, colour-selective neurons are more common in the ventral V3). Additional subdivisions, including V3A and V3B have also been reported in humans. These subdivisions are located near dorsal V3, but do not adjoin V2.
Dorsal V3 is normally considered to be part of the dorsal stream, receiving inputs from V2 and from the primary visual area and projecting to the posterior [[parietal cortex]]. It may be anatomically located in [[Brodmann area 19]]. Braddick using fMRI has suggested that area V3/V3A may play a role in the processing of [[global motion]]<ref name="Braddick2001">{{cite journal |
Ventral V3 (VP), has much weaker connections from the primary visual area, and stronger connections with the [[inferior temporal cortex]]. While earlier studies proposed that VP contained a representation of only the upper part of the visual field (above the point of fixation), more recent work indicates that this area is more extensive than previously appreciated, and like other visual areas it may contain a complete visual representation. The revised, more extensive VP is referred to as the ventrolateral posterior area (VLP) by Rosa and Tweedale.<ref>{{cite journal |
== V4 ==
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[[File:Fusiform gyrus animation.gif|thumb|The fusiform gyrus is the hypothetical location of V4α, a secondary area for colour processing. More: [[Colour centre]]]]
'''Visual area V4''' is one of the visual areas in the [[extrastriate]] visual cortex. In [[Rhesus macaque|macaques]], it is located anterior to V2 and posterior to [[Inferior temporal gyrus|posterior inferotemporal area (PIT)]]. It comprises at least four regions (left and right V4d, left and right V4v), and some groups report that it contains rostral and caudal subdivisions as well. It is unknown whether the human V4 is as expansive as that of the macaque [[homology (biology)|homologue]] which is a subject of debate.<ref
V4 is the third cortical area in the [[Two-streams hypothesis#Ventral stream|ventral stream]], receiving strong feedforward input from V2 and sending strong connections to the [[Inferior temporal gyrus|PIT]].
V4 is the first area in the [[Two-streams hypothesis#Ventral stream|ventral stream]] to show strong attentional modulation.
Like V2, V4 is tuned for orientation, spatial frequency, and color.
The firing properties of V4 were first described by [[Semir Zeki]] in the late 1970s, who also named the area.
Recent work has shown that V4 exhibits long-term plasticity,<ref>{{cite journal |
== Middle temporal visual area (V5) ==<!-- This section is linked from [[V5]] -->
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
=== Connections ===
MT is connected to a wide array of cortical and subcortical brain areas.
A standard view is that V1 provides the "most important" input to MT.<ref name="BornBradley" /> Nonetheless, several studies have demonstrated that neurons in MT are capable of responding to visual information, often in a direction-selective manner, even after V1 has been destroyed or inactivated.<ref>{{cite journal |
▲MT is connected to a wide array of cortical and subcortical brain areas. Its input comes from visual cortical areas V1, V2 and dorsal V3 ([[dorsomedial area]]),<ref name="FellemanVanEssen">{{cite journal |vauthors=Felleman D, Van Essen D | title = Distributed hierarchical processing in the primate cerebral cortex | journal = [[Cerebral Cortex]] | volume = 1 | issue = 1 | pages = 1–47 | year = 1991| pmid = 1822724 | doi = 10.1093/cercor/1.1.1-a| doi-access = free }}</ref><ref name="UngerleiderDesimone">{{cite journal |vauthors=Ungerleider L, Desimone R | title = Cortical connections of visual area MT in the macaque | journal = Journal of Comparative Neurology | volume = 248 | issue = 2 | pages = 190–222 | year = 1986 | pmid = 3722458 | doi = 10.1002/cne.902480204| s2cid = 1876622 | url = https://zenodo.org/record/1229147 }}</ref> the [[koniocellular]] regions of the [[LGN]],<ref name="Sincich">{{cite journal |vauthors=Sincich L, Park K, Wohlgemuth M, Horton J | title = Bypassing V1: a direct geniculate input to area MT | journal = Nature Neuroscience | volume = 7 | issue = 10 | pages = 1123–8 | year = 2004 | pmid = 15378066 | doi = 10.1038/nn1318| s2cid = 13419990 }}</ref> and the [[pulvinar nuclei|inferior pulvinar]].<ref>{{cite journal |vauthors=Warner CE, Goldshmit Y, Bourne JA | title = Retinal afferents synapse with relay cells targeting the middle temporal area in the pulvinar and lateral geniculate nuclei | journal = Frontiers in Neuroanatomy | volume = 4 | page = 8 | year = 2010 | pmid = 20179789 | doi = 10.3389/neuro.05.008.2010 | pmc=2826187| doi-access = free }}</ref> The pattern of projections to MT changes somewhat between the representations of the foveal and peripheral visual fields, with the latter receiving inputs from areas located in the midline cortex and [[retrosplenial region]].<ref name="PalmerRosa2006">{{cite journal |vauthors=Palmer SM, Rosa MG | year=2006 | title=A distinct anatomical network of cortical areas for analysis of motion in far peripheral vision | journal=European Journal of Neuroscience | volume=24 |pages=2389–405 | doi=10.1111/j.1460-9568.2006.05113.x | pmid=17042793 | issue=8| s2cid=21562682 }}</ref>
▲A standard view is that V1 provides the "most important" input to MT.<ref name="BornBradley" /> Nonetheless, several studies have demonstrated that neurons in MT are capable of responding to visual information, often in a direction-selective manner, even after V1 has been destroyed or inactivated.<ref>{{cite journal | last1 = Rodman | first1 = HR | last2 = Gross | first2 = CG | last3 = Albright | first3 = TD |name-list-style=vanc | year = 1989 | title = Afferent basis of visual response properties in area MT of the macaque. I. Effects of striate cortex removal | journal = Journal of Neuroscience | volume = 9 | issue = 6| pages = 2033–50 | pmid = 2723765 | pmc = 6569731 | doi = 10.1523/JNEUROSCI.09-06-02033.1989 }}</ref> Moreover, research by [[Semir Zeki]] and collaborators has suggested that certain types of visual information may reach MT before it even reaches V1.
MT sends its major output to areas located in the cortex immediately surrounding it, including areas FST, [[Medial superior temporal area|MST]], and V4t (middle temporal crescent). Other projections of MT target the eye movement-related areas of the frontal and parietal lobes (frontal eye field and lateral intraparietal area).
=== Function ===
The first studies of the [[electrophysiological]] properties of neurons in MT showed that a large portion of the cells are [[neuronal tuning|tuned]] to the speed and direction of moving visual stimuli.<ref name="DubnerZeki">{{cite journal | vauthors = Dubner R, Zeki SM | title = Response properties and receptive fields of cells in an anatomically defined region of the superior temporal sulcus in the monkey | journal = Brain Research | volume = 35 | issue = 2 | pages = 528–532 | date = December 1971 | pmid = 5002708 | doi = 10.1016/0006-8993(71)90494-X }}.</ref><ref name="MaunsellVanEssen">{{cite journal | vauthors = Maunsell JH, Van Essen DC | title = Functional properties of neurons in middle temporal visual area of the macaque monkey. I. Selectivity for stimulus direction, speed, and orientation | journal = Journal of Neurophysiology | volume = 49 | issue = 5 | pages = 1127–1147 | date = May 1983 | pmid = 6864242 | doi = 10.1152/jn.1983.49.5.1127 | s2cid = 8708245 }}</ref>
However, since neurons in V1 are also tuned to the direction and speed of motion, these early results left open the question of precisely what MT could do that V1 could not. Much work has been carried out on this region, as it appears to integrate local visual motion signals into the global motion of complex objects.<ref name="Movshon">Movshon, J.A., Adelson, E.H., Gizzi, M.S., & Newsome, W.T. (1985). The analysis of moving visual patterns. In: C. Chagas, R. Gattass, & C. Gross (Eds.), Pattern recognition mechanisms (pp. 117–151), Rome: Vatican Press.</ref>
For example, ''lesion'' to the V5 leads to deficits in perceiving motion and processing of complex stimuli. It contains many neurons selective for the motion of complex visual features (line ends, corners). ''Microstimulation'' of a neuron located in the V5 affects the perception of motion. For example, if one finds a neuron with preference for upward motion in a monkey's V5 and stimulates it with an electrode, then the monkey becomes more likely to report 'upward' motion when presented with stimuli containing 'left' and 'right' as well as 'upward' components.<ref name="BrittenVanWezel">{{cite journal | vauthors = Britten KH, van Wezel RJ | title = Electrical microstimulation of cortical area MST biases heading perception in monkeys |
There is still much controversy over the exact form of the computations carried out in area MT<ref name="Wilson">{{cite journal |
=== Functional organization ===
MT was shown to be organized in direction columns.<ref name="Albright">{{cite journal |
==V6==
<!-- [[Dorsomedial area]] redirects to this section -->
The '''dorsomedial area''' (DM) also known as '''V6''', appears to respond to visual stimuli associated with self-motion<ref>{{cite journal |
There are similarities between the visual area V5 and V6 of the [[common marmoset]]. Both areas receive direct connections from the [[primary visual cortex]].<ref name= humanV6 />{{rp|7971}} And both have a high [[myelin]] content, a characteristic that is usually present in brain structures involved in fast transmission of information.<ref name="pitzalis2012">{{cite journal |
For many years, it was considered that DM only existed in [[New World monkeys]]. However, more recent research has suggested that DM also exists in [[Old World monkeys]] and humans.<ref name= humanV6 />{{rp|7972}} V6 is also sometimes referred to as the parieto-occipital area (PO), although the correspondence is not exact.<ref>{{cite journal | vauthors = Galletti C,
===Properties===
Neurons in area DM/V6 of [[night monkey]]s and [[common marmoset]]s have unique response properties, including an extremely sharp selectivity for the orientation of visual contours, and preference for long, uninterrupted lines covering large parts of the visual field.<ref>{{cite journal
However, in comparison with area MT, a much smaller proportion of DM cells shows selectivity for the direction of motion of visual patterns.<ref name="fmritools.com">{{Cite web | vauthors = Ducreux D |title=Calcarine (Visual) Cortex |website=Connectopedia Knowledge Database |url=http://www.fmritools.com/kdb/grey-matter/occipital-lobe/calcarine-visual-cortex/index.html
Recently, an area responsive to wide-angle flow fields has been identified in the human and is thought to be a homologue of macaque area V6.<ref>{{cite journal |
===Pathways===
[[File:Neural pathway diagram.svg|thumb]]
The connections and response properties of cells in DM/
== See also ==
* [[Cortical area]]
* [[Cortical blindness]]
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* [[Complex cell]]
== References ==
{{Reflist|30em}}
== External links ==
{{Commons category|Visual cortex}}
* {{cite web |title=The Primary Visual Cortex by Matthew Schmolesky |url=http://webvision.med.utah.edu/VisualCortex.html |publisher=[[University of Utah]]|archive-url=https://web.archive.org/web/20041229070957/http://webvision.med.utah.edu/VisualCortex.html
*
* {{BrainInfo|ancil|415}} – striate area 17
* {{BrainInfo|ancil|699}} – Brodmann area 17 in guenon
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