Relevant bibliographies by topics / Visual Cortex

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Visual Cortex'

Author: Grafiati
Published: 4 June 2021
Last updated: 28 July 2024

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Journal articles on the topic "Visual Cortex"

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Miller, K. D. "= Visual Cortex." Science 330, no. 6007 (November 18, 2010): 1059–60. http://dx.doi.org/10.1126/science.1198857.

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Wlesel, Torsten N., and Charles D. Gilbert. "Visual cortex." Trends in Neurosciences 9 (January 1986): 509–12. http://dx.doi.org/10.1016/0166-2236(86)90161-x.

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Kaufman, K. J. "The Cerebral Cortex: Visual Cortex." Archives of Ophthalmology 104, no. 8 (August 1, 1986): 1141. http://dx.doi.org/10.1001/archopht.1986.01050200047040.

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Cowey, A. "Cerebral Cortex, Vol. 3, Visual Cortex." Neuroscience 19, no. 3 (November 1986): 1023. http://dx.doi.org/10.1016/0306-4522(86)90314-3.

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Hughes, John R. "Cerebral cortex. Vol. 3. Visual cortex." Electroencephalography and Clinical Neurophysiology 63, no. 4 (April 1986): 392. http://dx.doi.org/10.1016/0013-4694(86)90029-5.

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Taira, Masato, and Narumi Katsuyama. "Visual association cortex." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 18, no. 3 (2006): 377–82. http://dx.doi.org/10.3156/jsoft.18.3_377.

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Tusa, Ronald J. "The Visual Cortex." American Journal of EEG Technology 26, no. 3 (September 1986): 135–43. http://dx.doi.org/10.1080/00029238.1986.11080198.

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Hübener, Mark. "Mouse visual cortex." Current Opinion in Neurobiology 13, no. 4 (August 2003): 413–20. http://dx.doi.org/10.1016/s0959-4388(03)00102-8.

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Tong, Frank. "Primary visual cortex and visual awareness." Nature Reviews Neuroscience 4, no. 3 (March 2003): 219–29. http://dx.doi.org/10.1038/nrn1055.

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La Chioma, Alessandro, and Mark Hübener. "Visual Cortex: Binocular Matchmaking." Current Biology 31, no. 4 (February 2021): R197—R199. http://dx.doi.org/10.1016/j.cub.2020.12.011.

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Dissertations / Theses on the topic "Visual Cortex"

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Thulin, Nilsson Linnea. "The Role of Primary Visual Cortex in Visual Awareness." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-11623.

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Despite its great complexity, a great deal is known about the organization and information-processing properties of the visual system. However, the neural correlates of visual awareness are not yet understood. By studying patients with blindsight, the primary visual cortex (V1) has attracted a lot of attention recently. Although this brain area appears to be important for visual awareness, its exact role is still a matter of debate. Interactive models propose a direct role for V1 in generating visual awareness through recurrent processing. Hierarchal models instead propose that awareness is generated in later visual areas and that the role of V1 is limited to transmitting the necessary information to these areas. Interactive and hierarchical models make different predictions and the aim of this thesis is to review the evidence from lesions, perceptual suppression, and transcranial magnetic stimulation (TMS), along with data from internally generated visual awareness in dreams, hallucinations and imagery, this in order to see whether current evidence favor one type of model over the other. A review of the evidence suggests that feedback projections to V1 appear to be important in most cases for visual awareness to arise but it can arise even when V1 is absent.
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Hardingham, Neil Robert. "Synaptic connections in rat visual cortex." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325298.

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Fotheringhame, David K. "Temporal coding in primary visual cortex." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.339357.

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Nauhaus, Ian Michael. "Functional connectivity in primary visual cortex." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1692099811&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Peelen, Marius Vincent. "Body selectivity in human visual cortex." Thesis, Bangor University, 2006. https://research.bangor.ac.uk/portal/en/theses/body-selectivity-in-human-visual-cortex(4091f96c-dee2-42ec-9a32-c0a8cf17b288).html.

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Perceiving other people is a seemingly effortless process. Yet within a few hundred milliseconds we are aware of who we are looking at, what this person is doing, and even what this person feels. We derive this information from the form and motion of the face and body. Faces may be particularly important for some aspects of person perception (e. g., identity recognition), whereas bodies may be more important for others (e. g., action recognition). Furthermore, information from the body is important in cases where it is not possible to perceive the details of the face, for instance when the face is occluded, or when we see someone from a distance. In most cases, however, it is likely that information from both the face and the body are perceived in parallel and are integrated at an early stage. Previous research on person perception has mostly focused on the brain mechanisms underlying face perception. Much less research has focused on the brain mechanismsu nderlying body perception,w hich is the topic of this thesis. Using functional magnetic resonance imaging (fMRI) I provide evidence for a previously unknown body-selective visual area that overlaps a face-selective area. By employing novel analysis techniques that take into account patterns of activation across voxels I show that body- and face-selective areas can be functionally dissociated. Finally, I show that, in contrast to frontal and parietal action-recognition areas, visual body-selective areasd o not contain a dynamic representationo f observeda ctions. Together, thesef indings increaseo ur understandingo f the brain mechanismsu nderlying body, face and action perception, by showing both similarities and dissimilarities in the brain structures involved in these processes.
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Romo, Phillip Alfonso. "Visual processing in the higher cortices of the mammalian visual cortex." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/27311.

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Area 18 of the cat is the focus of this thesis as it a cortical area considered both primary visual cortex due to its direct LGN projections, but also an association visual cortex and homologue of the primate area V2. Visual cortical neurones are categorised as either simple or complex based on receptive field properties within a small, central excitatory region. But when stimuli are expanded beyond the confines of the central receptive field, a silent surround region is capable of playing a modulatory role on the centre response. Chapter 1 provides some historical background regarding the visual cortex, properties of the neuronal populations and hypothesised models associated with the construction of receptive field. Chapter 2 expands previous work from our laboratory in area 17 of the cat into area 18. In over 75% of cells in area 18 we observed to have a suppressive surround and exhibit tuning for orientation, contrast, spatial and temporal frequencies. Previously observed ‘simplification of complex cells’ (reduced phase sensitivity) in area 17 when receptive fields were co-stimulated with optimised surround stimuli was also present in area 18. Chapter 3 expands the understanding of binocular cell responses and the extent of matching for centre and surround receptive fields in area 18. Centre receptive fields demonstrated excellent matching for phase-sensitivities and orientation. Conversely, there was weak interocular matching of the optimal temporal frequencies, the diameters of summation areas of the excitatory responses and suppression index. In chapter 4, consistent with findings of area 17, we have observed silent surround which can be classified as suppressive, rebound, plateau and faciliatory. Exploring the ECRF in a subregion fashion we observed uniform suppressive ECRF in addition to heterogenous subregions capable of suppression and facilitation of the centre
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Bernard, Clémence Francoise. "Otx2-glycosaminoglycan interaction to regulate visual cortex plasticity." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066228/document.

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Pendant le développement postnatal du cortex cérébral visuel, l'homéoprotéine Otx2 est transférée préférentiellement dans les interneurones inhibiteurs à parvalbumine (cellules PV), induit leur maturation et régule la période critique de plasticité pour la dominance oculaire. Pendant cette période critique, les cellules PV sont progressivement entourées par une matrice extracellulaire riche en glycosaminoglycanes (GAGs), qui pourraient être impliqués dans la capture d'Otx2. Pour étudier comment l'interaction entre Otx2 et les GAGs à la surface des cellules PV régule la période critique, nous avons analysé une lignée de souris transgéniques Otx2-AA chez lesquelles cette interaction est perturbée. Ces souris présentent une spécificité réduite de l'Otx2 cortical pour les cellules PV et un retard dans l'ouverture et la fermeture de la période critique pour la dominance oculaire. Nous avons montré que la protéine Otx2 se lie aux chaines de chondroïtine sulfates à la surface des cellules PV et qu'elle a une forte affinité pour le chondroïtine sulfate CS-E. Chez l'adulte, le cortex est maintenu à l'état non plastique par un apport continuel d'Otx2. Afin de ré-ouvrir une fenêtre de plasticité chez l'adulte, nous avons développé deux modèles pour perturber le transfert d'Otx2 : un analogue synthétique de CS-E qui se lie à Otx2 et une souris knock-in inductible pour contrôler la sécrétion d'un anticorps simple chaine contre Otx2. Ces résultats confirment et précisent le rôle in vivo de l'interaction entre Otx2 et les GAGs, à la fois pour la mise en place des périodes critiques pendant le développement postnatal et pour le maintien de l'état non plastique du cortex chez l'adulte
During postnatal development of the visual cerebral cortex, Otx2 homeoprotein is transferred preferentially into parvalbumin inhibitory interneurons (PV-cells), induces their maturation and regulates a critical period of plasticity for binocular vision. During the critical period, PV-cells are gradually enwrapped by perineuronal nets enriched in glycosaminoglycans (GAGs), which are likely involved in the capture of Otx2. To understand how Otx2 interacts with GAGs at the surface of PV-cells for critical period regulation, we have analyzed a transgenic Otx2-AA mouse line in which the interaction between Otx2 and GAGs is disrupted. These mice show a reduced specificity of cortical Otx2 for PV-cells with concomitant delayed onset and closure of critical period for ocular dominance. We have also identified that Otx2 protein binds chondroitin sulfate chains of the perineuronal nets and that it has a high affinity for the chondroitin sulfate CS-E. We have therefore developed a sugar-ase protection assay for identifying specific glycan sequences involved in homeoprotein recognition. Throughout adulthood, the cortex receives Otx2 to maintain a consolidated, non-plastic state. To interfere with Otx2 transfer in the adult and reopen a window of plasticity, we have developed two models: a synthetic hexasaccharide analogue of CS-E that binds to Otx2 and an inducible, knock-in mouse allowing spatio-temporal control of a secreted single chain antibody against Otx2. All these results confirm and clarify the in vivo role for Otx2-GAG interaction, both in the timing of critical periods during postnatal development and in the maintenance of the non-plastic state of the cortex in the adult
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Krug, Kristine. "Ordering geniculate input into primary visual cortex." Thesis, University of Oxford, 1997. https://ora.ox.ac.uk/objects/uuid:b342ffae-4a31-4171-94a6-83cb516e83fe.

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Precise point-to-point connectivity is the basis of ordered maps of the visual field in the brain. One point in the visual field is represented at one locus in the dLGN and one locus in primary visual cortex. A fundamental problem in the development of most sensory systems is the creation of the topographic projections which underlie these maps. Mechanisms ranging from ordered ingrowth of fibres, through chemical guidance of axons to sculpting of the map from an early exuberant input have been proposed. However, we know little about how ordered maps are created beyond the first relay. What we do know is that a topological mismatch requires the exchange of neighbours in the geniculo-cortical projection and that manipulating the input to the primary relay can affect the geniculo-cortical topography. Taking advantage of the immaturity of the newborn hamster’s visual system, I studied the generation of an ordered map in primary visual cortex during the time of target innervation in normal and manipulated animals. I also investigated the patterning of neuronal activity prior to natural eye-opening. Paired injections of retrograde fluorescent tracers into visual cortex reveal that geniculate fibres are highly disordered at the time of invasion of the cortical plate. Topography in the geniculo-cortical projection emerges out of an unordered projection to area 17 in the first postnatal week. Furthermore, I show that manipulating the peripheral input can alter the topographic map which arises out of the early scatter. Removal of one eye at birth appears to slow the process of geniculo-cortical map formation ipsilateral to the remaining eye and at the end of the second postnatal week, a double projection between thalamus and cortex has formed. If retinal activity is blocked during this time, this double projection does not emerge. The results implicate retinal activity as the signal that induces the development of a different topographic order in the geniculo-cortical projection. It is generally believed that visual experience can influence development only after eye-opening. However, the final part of my thesis shows that neurons in the developing visual cortex of the ferret can not only be visually driven at least 10 days before natural eye-opening, but are also selective for differently oriented gratings presented through the closed eye-lid. Thus, visually-driven neuronal activity could influence development much earlier than previously assumed in many developmental studies.
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Woodbury, Greg. "Modelling Emergent Properties of the Visual Cortex." University of Sydney. School of Mathematics and Statistics, 2003. http://hdl.handle.net/2123/695.

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Nicoll, A. J. "Excitatory synaptic connections in the visual cortex." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303635.

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Books on the topic "Visual Cortex"

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A, Portocello Thomas, and Velloti Rudolph B, eds. Visual cortex: New research. New York: Nova Science Publishers, 2008.

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Peters, Alan, and Kathleen S. Rockland, eds. Primary Visual Cortex in Primates. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4757-9628-5.

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Rose, David, 1946 Jan. 13- and Dobson Vernon G, eds. Models of the visual cortex. Chichester: Wiley, 1985.

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1929-, Peters Alan, and Rockland, Kathleen Linda Skiba, 1947-, eds. Primary visual cortex in primates. New York: Plenum Press, 1994.

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1929-, Peters Alan, ed. The cat primary visual cortex. San Diego: Academic Press, 2002.

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Harris, Jessica M. Visual cortex: Anatomy, functions, and injuries. Hauppauge, N.Y: Nova Science Publishers, 2011.

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Rockland, Kathleen Linda Skiba, 1947-, Kass Jon H, and Peters Alan 1929-, eds. Extrastriate cortex in primates. New York: Plenum Press, 1997.

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Balázs, Gulyás, Ottoson David 1918-, and Roland Per E, eds. Functional organisation of the human visual cortex. Oxford [England]: Pergamon Press, 1993.

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Hubel, David H. Eye, brain, and vision. New York: Scientific American Library, 1988.

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Alan, Covey, Heywood Charles A, Milner A. D, and Blakemore Colin, eds. The roots of visual awareness: A festschrift in honour of Alan Cowey. Amsterdam: Elsevier, 2004.

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Book chapters on the topic "Visual Cortex"

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Felton, Warren L. "Visual Cortex." In Encyclopedia of Clinical Neuropsychology, 3611–12. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_377.

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Felton, Warren L. "Visual Cortex." In Encyclopedia of Clinical Neuropsychology, 1–2. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_377-2.

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Cynader, Max. "Visual Cortex." In Sensory System I, 76–79. Boston, MA: Birkhäuser Boston, 1988. http://dx.doi.org/10.1007/978-1-4899-6647-6_37.

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Liu, Xuyang, Jia Ma, and Ningli Wang. "Visual Cortex." In Advances in Visual Science and Eye Diseases, 33–36. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2502-1_7.

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Offit, Paul A., Anne Snow, Thomas Fernandez, Laurie Cardona, Elena L. Grigorenko, Carolyn A. Doyle, Christopher J. McDougle, et al. "Visual Cortex." In Encyclopedia of Autism Spectrum Disorders, 3290. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1698-3_591.

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Wyk, Brent Vander. "Visual Cortex." In Encyclopedia of Autism Spectrum Disorders, 5105. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-91280-6_591.

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Felton, Warren L. "Visual Cortex." In Encyclopedia of Clinical Neuropsychology, 2627–28. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-79948-3_377.

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Wong-Riley, Margaret T. T. "Primate Visual Cortex." In Cerebral Cortex, 141–200. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4757-9628-5_4.

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Whitwell, Robert L. "Visual Association Cortex." In Encyclopedia of Evolutionary Psychological Science, 1–5. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-16999-6_2769-1.

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Whitwell, Robert L. "Visual Association Cortex." In Encyclopedia of Evolutionary Psychological Science, 1–5. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-16999-6_2769-2.

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Conference papers on the topic "Visual Cortex"

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Csapo, Adam B., Andras Roka, and Peter Baranyi. "Visual Cortex Inspired Vertex and Corner Detection." In 2006 IEEE International Conference on Mechatronics. IEEE, 2006. http://dx.doi.org/10.1109/icmech.2006.252586.

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Gilbert, Charles. "Color processing in visual cortex." In Advances in Color Vision. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/acv.1992.fc1.

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Wavelength specific cells in visual cortex are grouped together into compartments that are interdigitated between other compartments specializing in form, movement and depth. The first evidence for a functional organization of color based on cortical area came from the work of Semir Zeki, who described an area prestriate cortex, known as area V4, that was enriched for color specific cells. Other cortical areas also contained wavelength selective cells, but the precise distribution of these cells eluded investigators for a number of years until the discovery by Margaret Wong- Riley that in area VI the enzyme cytochrome oxidase (CO) was distributed in a regular series of patches, as seen in tangential sections through the superficial cortical layers. Using CO histochemistry, David Hubei and Margaret Livingstone found that wavelength selective cells were located within these patches or "blobs", with broadband, orientation selective cells being found predominantly outside them. This lent support to the idea that color, as represented by wavelength selective cells, and form, as represented by orientation selective cells, were analyzed by separate, parallel pathways in the visual system. This left open, however, the question of how information about form and color might be attributed to a particular object, the so called "binding" problem, and also about how boundaries made by different colors could provide information about form. In fact, the existence of cells selective both for wavelength and for orientation had been known from a number of studies, and Ts'o and Gilbert found that such cells tended to lie at the boundaries of the CO blobs. With regard to the color selectivity found within the blobs, they found that cells sharing similar color opponency were grouped into columns, and that individual blobs specialized in either red-green or blue-yellow opponency.
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Maunsell, John H. R. "Motion processing in visual cortex." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1989. http://dx.doi.org/10.1364/oam.1989.tuj2.

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Many lines of anatomical and physiological evidence have shown that the visual system contains a distinct pathway that is responsible for most motion analysis. In primates this pathway originates in the retinal ganglion cells that send their axons to the magnocellular layers of the lateral geniculate nucleus (LGN). The outputs from the magnocellular LGN layers directly provide the primary excitatory drive to structures like layer 4B in striate cortex and the middle temporal area (MT) in extrastriate cortex. Both of these structures contain a high proportion of neurons that are selective for the direction of stimulus motion. Later stages of motion processing in parietal cortex appear to contribute to analyzing more complex types of movement such as rotation or looming.
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Movshon, J. Anthony. "Organization of primate visual cortex." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1989. http://dx.doi.org/10.1364/oam.1989.tuj1.

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The monkey's visual cortex contains more than two dozen separate areas, comprising in all about half the cerebral cortex. Each area provides a representation of the visual scene, and the existence of these multiple representations suggests that different areas may be specialized for the analysis of different aspects of the visual world. This tutorial reviews experimental evidence on functional specialization in the cortex and considers the validity and utility of this mosiac conception of cortical function.
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Cowan, Jack D., and Paul C. Bressloff. "Visual cortex and the Retinex algorithm." In Electronic Imaging 2002, edited by Bernice E. Rogowitz and Thrasyvoulos N. Pappas. SPIE, 2002. http://dx.doi.org/10.1117/12.469524.

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Andersen, Richard A. "Visual motion processing in primate cortex." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/oam.1987.mt1.

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Recent anatomical experiments in macaque monkeys have identified the presumed cortical pathway for motion processing. Using a combination of psychophysical, recording, and lesion techniques our laboratory has begun to investigate the types of motion processing that occur at each cortical level in this pathway. Our psychophysical experiments show that monkeys and humans have similar thresholds for perceiving shear motion and 2- and 3-D structures from motion. These experiments also show that the monkey and human nervous systems integrate motion information across both space and time to form neural representations of 3-D surfaces. Restricted ibotenic acid-induced cortical lesions to the middle temporal area (area MT) of macaque monkeys produced increased thresholds for the perception of both shear motion and structure from motion. These deficits were restricted to that part of the visual field that corresponded to the locus of the lesion within the retinotopic representation in area MT. The deficits appeared to be specific to motion perception since contrast sensitivity thresholds were not affected by the lesions. Interestingly the shear motion thresholds recovered in 3–4 days. This result suggests that either there has been a reorganization of the retinotopic map within regions of area MT that were not damaged or parallel motion pathways have been recruited or strengthened during the recovery period.
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Günthner, Max F., Santiago A. Cadena, George H. Denfield, Edgar Y. Walker, Leon A. Gatys, Andreas S. Tolias, Matthias Bethge, and Alexander S. Ecker. "Learning Divisive Normalization in Primary Visual Cortex." In 2019 Conference on Cognitive Computational Neuroscience. Brentwood, Tennessee, USA: Cognitive Computational Neuroscience, 2019. http://dx.doi.org/10.32470/ccn.2019.1211-0.

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Cevikbas, Can, and Tulay Yildirim. "Simplified Visual Cortex Model for Pattern Recognition." In 2018 Innovations in Intelligent Systems and Applications Conference (ASYU). IEEE, 2018. http://dx.doi.org/10.1109/asyu.2018.8554013.

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Zhang, Shouyu, Song Gao, Xiaojian Kang, and Shanglian Bao. "Diffusion characteristic analysis in human visual cortex." In 2013 IEEE International Conference on Medical Imaging Physics and Engineering (ICMIPE). IEEE, 2013. http://dx.doi.org/10.1109/icmipe.2013.6864514.

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Du, Xing, Weiguo Gong, and Weihong Li. "Feature extraction inspired by visual cortex mechanisms." In Second International Conference on Digital Image Processing. SPIE, 2010. http://dx.doi.org/10.1117/12.852798.

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Reports on the topic "Visual Cortex"

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Intrator, Nathan, Mark F. Bear, Leon N. Cooper, and Michael A. Paradiso. Theory of Synaptic Plasticity in Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, December 1992. http://dx.doi.org/10.21236/ada260052.

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Intrator, Nathan, Mark F. Bear, Leon N. Cooper, and Michael A. Paradiso. Theory of Synaptic Plasticity in Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada260322.

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Serre, Thomas, Lior Wolf, and Tomaso Poggio. Object Recognition with Features Inspired by Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada454604.

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Sajda, Paul, and Leif H. Finkel. Computer Simulations of Object Discrimination by Visual Cortex,. Fort Belvoir, VA: Defense Technical Information Center, January 1992. http://dx.doi.org/10.21236/ada253345.

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Neve, Rachael L., and Mark F. Bear. Visual Experience Regulates Gene Expression in the Developing Striate Cortex. Fort Belvoir, VA: Defense Technical Information Center, December 1989. http://dx.doi.org/10.21236/ada216149.

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Poggio, Tomaso, and Stephen Smale. Hierarchical Kernel Machines: The Mathematics of Learning Inspired by Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, February 2013. http://dx.doi.org/10.21236/ada580529.

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Cooper, Leon N. Synaptic Plasticity in Visual Cortex. From Synaptic Properties to Membranes and Receptors. Fort Belvoir, VA: Defense Technical Information Center, October 1995. http://dx.doi.org/10.21236/ada304169.

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Artun, Omer B., Harel Z. Shouval, and Leon N. Cooper. The Effect of Dynamic Synapses on Spatio-temporal Receptive Fields in Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, December 1997. http://dx.doi.org/10.21236/ada333497.

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Sajda, Paul, and Leif H. Finkel. A Neural Network Model of Object Segmentation and Feature Binding in Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, January 1990. http://dx.doi.org/10.21236/ada248100.

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Makous, Walter, John Maunsell, and Tatiana Pasternak. New Insights on Visual Cortex. Abstracts. Center for Visual Science Symposium (16th) Held in Rochester, New York on June 16-18, 1988. Fort Belvoir, VA: Defense Technical Information Center, June 1988. http://dx.doi.org/10.21236/ada199826.

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