Academic literature on the topic 'Visual cortex (V1)'
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Journal articles on the topic "Visual cortex (V1)"
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Beltramo, Riccardo, and Massimo Scanziani. "A collicular visual cortex: Neocortical space for an ancient midbrain visual structure." Science 363, no. 6422 (January 3, 2019): 64–69. http://dx.doi.org/10.1126/science.aau7052.
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Visual responses in the cerebral cortex are believed to rely on the geniculate input to the primary visual cortex (V1). Indeed, V1 lesions substantially reduce visual responses throughout the cortex. Visual information enters the cortex also through the superior colliculus (SC), but the function of this input on visual responses in the cortex is less clear. SC lesions affect cortical visual responses less than V1 lesions, and no visual cortical area appears to entirely rely on SC inputs. We show that visual responses in a mouse lateral visual cortical area called the postrhinal cortex are independent of V1 and are abolished upon silencing of the SC. This area outperforms V1 in discriminating moving objects. We thus identify a collicular primary visual cortex that is independent of the geniculo-cortical pathway and is capable of motion discrimination.
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Froudarakis, Emmanouil, Paul G. Fahey, Jacob Reimer, Stelios M. Smirnakis, Edward J. Tehovnik, and Andreas S. Tolias. "The Visual Cortex in Context." Annual Review of Vision Science 5, no. 1 (September 15, 2019): 317–39. http://dx.doi.org/10.1146/annurev-vision-091517-034407.
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In this article, we review the anatomical inputs and outputs to the mouse primary visual cortex, area V1. Our survey of data from the Allen Institute Mouse Connectivity project indicates that mouse V1 is highly interconnected with both cortical and subcortical brain areas. This pattern of innervation allows for computations that depend on the state of the animal and on behavioral goals, which contrasts with simple feedforward, hierarchical models of visual processing. Thus, to have an accurate description of the function of V1 during mouse behavior, its involvement with the rest of the brain circuitry has to be considered. Finally, it remains an open question whether the primary visual cortex of higher mammals displays the same degree of sensorimotor integration in the early visual system.
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White, Brian J., Janis Y. Kan, Ron Levy, Laurent Itti, and Douglas P. Munoz. "Superior colliculus encodes visual saliency before the primary visual cortex." Proceedings of the National Academy of Sciences 114, no. 35 (August 14, 2017): 9451–56. http://dx.doi.org/10.1073/pnas.1701003114.
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Models of visual attention postulate the existence of a bottom-up saliency map that is formed early in the visual processing stream. Although studies have reported evidence of a saliency map in various cortical brain areas, determining the contribution of phylogenetically older pathways is crucial to understanding its origin. Here, we compared saliency coding from neurons in two early gateways into the visual system: the primary visual cortex (V1) and the evolutionarily older superior colliculus (SC). We found that, while the response latency to visual stimulus onset was earlier for V1 neurons than superior colliculus superficial visual-layer neurons (SCs), the saliency representation emerged earlier in SCs than in V1. Because the dominant input to the SCs arises from V1, these relative timings are consistent with the hypothesis that SCs neurons pool the inputs from multiple V1 neurons to form a feature-agnostic saliency map, which may then be relayed to other brain areas.
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Hawken, M. J., R. M. Shapley, and D. H. Grosof. "Temporal-frequency selectivity in monkey visual cortex." Visual Neuroscience 13, no. 3 (May 1996): 477–92. http://dx.doi.org/10.1017/s0952523800008154.
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AbstractWe investigated the dynamics of neurons in the striate cortex (V1) and the lateral geniculate nucleus (LGN) to study the transformation in temporal-frequency tuning between the LGN and V1. Furthermore, we compared the temporal-frequency tuning of simple with that of complex cells and direction-selective cells with nondirection-selective cells, in order to determine whether there are significant differences in temporal-frequency tuning among distinct functional classes of cells within V1. In addition, we compared the cells in the primary input layers of V1 (4a, 4cα, and 4cβ) with cells in the layers that are predominantly second and higher order (2, 3, 4b, 5, and 6). We measured temporal-frequency responses to drifting sinusoidal gratings. For LGN neurons and simple cells, we used the amplitude and phase of the fundamental response. For complex cells, the elevation of impulse rate (F0) to a drifting grating was the response measure. There is significant low-pass filtering between the LGN and the input layers of V1 accompanied by a small, 3-ms increase in visual delay. There is further low-pass filtering between V1 input layers and the second- and higher-order neurons in V1. This results in an average decrease in high cutoff temporal-frequency between the LGN and V1 output layers of about 20 Hz and an increase in average visual latency of about 12–14 ms. One of the most salient results is the increased diversity of the dynamic properties seen in V1 when compared to the cells of the lateral geniculate, possibly reflecting specialization of function among cells in V1. Simple and complex cells had distributions of temporal-frequency tuning properties that were similar to each other. Direction-selective and nondirection-selective cells had similar preferred and high cutoff temporal frequencies, but direction-selective cells were almost exclusively band-pass while nondirection-selective cells distributed equally between band-pass and low-pass categories. Integration time, a measure of visual delay, was about 10 ms longer for V1 than LGN. In V1 there was a relatively broad distribution of integration times from 40–80 ms for simple cells and 60–100 ms for complex cells while in the LGN the distribution was narrower.
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Tehovnik, Edward J., and Warren M. Slocum. "What Delay Fields Tell Us About Striate Cortex." Journal of Neurophysiology 98, no. 2 (August 2007): 559–76. http://dx.doi.org/10.1152/jn.00285.2007.
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It is well known that electrical activation of striate cortex (area V1) can disrupt visual behavior. Based on this knowledge, we discovered that electrical microstimulation of V1 in macaque monkeys delays saccadic eye movements when made to visual targets located in the receptive field of the stimulated neurons. This review discusses the following issues. First, the parameters that affect the delay of saccades by microstimulation of V1 are reviewed. Second, the excitability properties of the V1 elements mediating the delay are discussed. Third, the properties that determine the size and shape of the region of visual space affected by stimulation of V1 are described. This region is called a delay field. Fourth, whether the delay effect is mainly due to a disruption of the visual signal transmitted through V1 or whether it is a disturbance of the motor signal transmitted between V1 and the brain stem saccade generator is investigated. Fifth, the properties of delay fields are used to estimate the number of elements activated directly by electrical microstimulation of macaque V1. Sixth, these properties are used to make inferences about the characteristics of visual percepts induced by such stimulation. Seventh, the disruptive effects of V1 stimulation in monkeys and humans are compared. Eighth, a cortical mechanism to account for the disruptive effects of V1 stimulation is proposed. Finally, these effects are related to normal vision.
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Schira, Mark M., Alex R. Wade, and Christopher W. Tyler. "Two-Dimensional Mapping of the Central and Parafoveal Visual Field to Human Visual Cortex." Journal of Neurophysiology 97, no. 6 (June 2007): 4284–95. http://dx.doi.org/10.1152/jn.00972.2006.
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Primate visual cortex contains a set of maps of visual space. These maps are fundamental to early visual processing, yet their form is not fully understood in humans. This is especially true for the central and most important part of the visual field—the fovea. We used functional magnetic resonance imaging (fMRI) to measure the mapping geometry of human V1 and V2 down to 0.5° of eccentricity. By applying automated atlas fitting procedures to parametrize and average retinotopic measurements of eight brains, we provide a reference standard for the two-dimensional geometry of human early visual cortex of unprecedented precision and analyze this high-quality mean dataset with respect to the 2-dimensional cortical magnification morphometry. The analysis indicates that 1) area V1 has meridional isotropy in areal projection: equal areas of visual space are mapped to equal areas of cortex at any given eccentricity. 2) V1 has a systematic pattern of local anisotropies: cortical magnification varies between isopolar and isoeccentricity lines, and 3) the shape of V1 deviates systematically from the complex-log model, the fit of which is particularly poor close to the fovea. We therefore propose that human V1 be fitted by models based on an equal-area principle of its two-dimensional magnification. 4) V2 is elongated by a factor of 2 in eccentricity direction relative to V1 and has significantly more local anisotropy. We propose that V2 has systematic intrinsic curvature, but V1 is intrinsically flat.
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Watanabe, Takeo, Yuka Sasaki, Satoru Miyauchi, Benno Putz, Norio Fujimaki, Matthew Nielsen, Ryosuke Takino, and Satoshi Miyakawa. "Attention-Regulated Activity in Human Primary Visual Cortex." Journal of Neurophysiology 79, no. 4 (April 1, 1998): 2218–21. http://dx.doi.org/10.1152/jn.1998.79.4.2218.
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Watanabe, Takeo, Yuka Sasaki, Satoru Miyauchi, Benno Putz, Norio Fujimaki, Matthew Nielsen, Ryosuke Takino, and Satoshi Miyakawa. Attention-regulated activity in human primary visual cortex. J. Neurophysiol. 79: 2218–2221, 1998. Effects of attention to a local contour of a moving object on the activation of human primary visual cortex (area V1) were examined. Local cerebral oxygenation changes (an index of neuronal activity) in human area V1 were measured with functional magnetic resonance imaging (fMRI) in conditions including the following two: 1) when attention was selectively directed toward one side of a moving wedge (the attention condition) and 2) when the wedges were viewed passively (the passive condition). Activation in area V1 was found to be higher in the attention condition than in the passive condition. To our knowledge, this is the first finding that attention to motion activates as early as area V1. We suggest that attentional activation of area V1 is task dependent.
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Pereira, Catia M., Marco Aurelio M. Freire, José R. Santos, Joanilson S. Guimarães, Gabriella Dias-Florencio, Sharlene Santos, Antonio Pereira, and Sidarta Ribeiro. "Non-visual exploration of novel objects increases the levels of plasticity factors in the rat primary visual cortex." PeerJ 6 (October 23, 2018): e5678. http://dx.doi.org/10.7717/peerj.5678.
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Background Historically, the primary sensory areas of the cerebral cortex have been exclusively associated with the processing of a single sensory modality. Yet the presence of tactile responses in the primary visual (V1) cortex has challenged this view, leading to the notion that primary sensory areas engage in cross-modal processing, and that the associated circuitry is modifiable by such activity. To explore this notion, here we assessed whether the exploration of novel objects in the dark induces the activation of plasticity markers in the V1 cortex of rats. Methods Adult rats were allowed to freely explore for 20 min a completely dark box with four novel objects of different shapes and textures. Animals were euthanized either 1 (n = 5) or 3 h (n = 5) after exploration. A control group (n = 5) was placed for 20 min in the same environment, but without the objects. Frontal sections of the brains were submitted to immunohistochemistry to measure protein levels of egr-1 and c-fos, and phosphorylated calcium-dependent kinase (pCaKMII) in V1 cortex. Results The amount of neurons labeled with monoclonal antibodies against c-fos, egr-1 or pCaKMII increased significantly in V1 cortex after one hour of exploration in the dark. Three hours after exploration, the number of labeled neurons decreased to basal levels. Conclusions Our results suggest that non-visual exploration induces the activation of immediate-early genes in V1 cortex, which is suggestive of cross-modal processing in this area. Besides, the increase in the number of neurons labeled with pCaKMII may signal a condition promoting synaptic plasticity.
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DUFFY, KEVIN R., KATHRYN M. MURPHY, and DAVID G. JONES. "Analysis of the postnatal growth of visual cortex." Visual Neuroscience 15, no. 5 (May 1998): 831–39. http://dx.doi.org/10.1017/s0952523898155049.
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Development and growth of V1 begins during embryogenesis and continues postnatally. The growth of V1 has direct implications on the organization of features such as the retinotopic map and the pattern of visual cortical columns. We have examined the postnatal growth and two-dimensional shape of V1 in macaque monkeys, cats, and rats. The perimeter, area, and anterior–posterior length of V1 were measured from unfolded and flattened sections from neonatal and adult animals from each of these species. Although there were substantial differences in the overall amount of postnatal growth, from 18% in macaque monkeys to more than 100% in cats, in all three species the shape of V1 did not change during development. Thus, growth of the mammalian visual cortex is well described as an isotropic expansion, so the layout of the global features, such as the arrangement of ocular dominance columns and the retinotopic map, does not need to change during development. Furthermore, quantification of the shape confirms the observations that there is a similar, egg-like oval shape to the visual cortex of these mammalian species.
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Bressloff, Paul C., Jack D. Cowan, Martin Golubitsky, Peter J. Thomas, and Matthew C. Wiener. "What Geometric Visual Hallucinations Tell Us about the Visual Cortex." Neural Computation 14, no. 3 (March 1, 2002): 473–91. http://dx.doi.org/10.1162/089976602317250861.
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Many observers see geometric visual hallucinations after taking hallucinogens such as LSD, cannabis, mescaline or psilocybin; on viewing bright flickering lights; on waking up or falling asleep; in “near-death” experiences; and in many other syndromes. Klüver organized the images into four groups called form constants: (I) tunnels and funnels, (II) spirals, (III) lattices, including honeycombs and triangles, and (IV) cobwebs. In most cases, the images are seen in both eyes and move with them. We interpret this to mean that they are generated in the brain. Here, we summarize a theory of their origin in visual cortex (area V1), based on the assumption that the form of the retino–cortical map and the architecture of V1 determine their geometry. (A much longer and more detailed mathematical version has been published in Philosophical Transactions of the Royal Society B, 356 [2001].) We model V1 as the continuum limit of a lattice of interconnected hypercolumns, each comprising a number of interconnected iso-orientation columns. Based on anatomical evidence, we assume that the lateral connectivity between hypercolumns exhibits symmetries, rendering it invariant under the action of the Euclidean group E(2), composed of reflections and translations in the plane, and a (novel) shift-twist action. Using this symmetry, we show that the various patterns of activity that spontaneously emerge when V1's spatially uniform resting state becomes unstable correspond to the form constants when transformed to the visual field using the retino-cortical map. The results are sensitive to the detailed specification of the lateral connectivity and suggest that the cortical mechanisms that generate geometric visual hallucinations are closely related to those used to process edges, contours, surfaces, and textures.
Dissertations / Theses on the topic "Visual cortex (V1)"
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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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Stevens, Jean-Luc Richard. "Spatiotemporal properties of evoked neural response in the primary visual cortex." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31330.
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Understanding how neurons in the primary visual cortex (V1) of primates respond to visual patterns has been a major focus of research in neuroscience for many decades. Numerous different experimental techniques have been used to provide data about how the spatiotemporal patterns of light projected from the visual environment onto the retina relate to the spatiotemporal patterns of neural activity evoked in the visual cortex, across disparate spatial and temporal scales. However, despite the variety of data sources available (or perhaps because of it), there is still no unified explanation for how the circuitry in the eye, the subcortical visual pathways, and the visual cortex responds to these patterns. This thesis outlines a research project to build computational models of V1 that incorporate observations and constraints from an unprecedented range of experimental data sources, reconciling each data source with the others into a consistent proposal for the underlying circuitry and computational mechanisms. The final mechanistic model is the first one shown to be compatible with measurements of: (1) temporal firing-rate patterns in single neurons over tens of milliseconds obtained using single-unit electrophysiology, (2) spatiotemporal patterns in membrane voltages in cortical tissues spanning several square millimeters over similar time scales, obtained using voltage-sensitive-dye imaging, and (3) spatial patterns in neural activity over several square millimeters of cortex, measured over the course of weeks of early development using optical imaging of intrinsic signals. Reconciling this data was not trivial, in part because single-unit studies suggested short, transient neural responses, while population measurements suggested gradual, sustained responses. The fundamental principles of the resulting models are (a) that the spatial and temporal patterns of neural responses are determined not only by the particular properties of a visual stimulus and the internal response properties of individual neurons, but by the collective dynamics of an entire network of interconnected neurons, (b) that these dynamics account both for the fast time course of neural responses to individual stimuli, and the gradual emergence of structure in this network via activity-dependent Hebbian modifications of synaptic connections over days, and (c) the differences between single-unit and population measurements are primarily due to extensive and wide-ranging forms of diversity in neural responses, which become crucial when trying to estimate population responses out of a series of individual measurements. The final model is the first to include all the types of diversity necessary to show how realistic single-unit responses can add up to the very different population-level evoked responses measured using voltage-sensitive-dye imaging over large cortical areas. Additional contributions from this thesis include (1) a comprehensive solution for doing exploratory yet reproducible computational research, implemented as a set of open-source tools, (2) a general-purpose metric for evaluating the biological realism of model orientation maps, and (3) a demonstration that the previous developmental model that formed the basis of the models in this thesis is the only developmental model so far that produces realistic orientation maps. These analytical results, computational models, and research tools together provide a systematic approach for understanding neural responses to visual stimuli across time scales from milliseconds to weeks and spatial scales from microns to centimeters.
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Fournier, Julien. "Adaptation of the simple or complex nature of V1 receptive fields to visual statistics." Paris 6, 2009. http://www.theses.fr/2009PA066426.
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A partir d’enregistrements intracellulaires, réalisés dans le cortex visuel primaire (V1) chez le chat anesthésié, nous avons estimé les champs récepteurs (RF) associés aux réponses, sous-liminaires et spikantes, évoquées par des bruits 2D épars(SN) ou dense(DN). Les kernels de 1er et 2nd ordre de ces RFs ont été comparés entre conditions de stimulation. Ces composantes ne sont pas redimensionnées dans les mêmes proportions lorsqu’on passe du SN au DN: le rapport Simple/Complexe du RF augmente systématiquement, du fait d’une amplification relative des composantes linéaires dans le contexte DN et des contributions non-linéaires dans la condition SN. Le RF d’une même cellule peut ainsi apparaître Simple sous une stimulation de type DN et Complexe une fois stimulé avec le SN. Toutefois, dès lors que ces filtres sont convolués avec la séquence de stimulation, les sorties linéaires et non-linéaires contribuent à la réponse globale de la cellule dans des proportions remarquablement constantes entre les conditions SN et DN. De ce fait, même si les composantes linéaires et non-linéaires du RF ne sont pas recrutées avec la même intensité dans ces deux conditions, l’organisation spatiale du même RF semble s’adapter à la statistique du stimulus de telle manière que les contributions relatives des composantes Simples et Complexes restent constantes dans la réponse globale. Cette étude apporte de nouveaux éléments suggérant la dépendance de la connectivité fonctionnelle à la statistique du stimulus et propose l’existence d’un nouveau processus d’adaptation contrôlant l’apparente Simplicité ou Complexité des champs récepteurs de V1 selon le caractère épars ou dense de la scène visuelle.
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Palmer, Chris M. "Topographic and laminar models for the development and organisation of spatial frequency and orientation in V1." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4114.
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Over the past several decades, experimental studies of the organisation of spatial frequency (SF) preference in mammalian visual cortex (V1) have reported a wide variety of conflicting results. A consensus now appears to be emerging that in the superficial layers SF is mapped continuously across the cortical surface. However, other evidence suggests that SF may differ systematically with cortical depth, at least in layer 4, where the magnocellular (M) and parvocellular (P) pathway afferents terminate in different sublaminae. It is not yet clear whether the topographic organisation for SF observed in the superficial layers is maintained throughout the input layers as well, or whether there is a switch from a laminar to a topographic organisation along the vertical dimension in V1. I present results from two alternative self-organising computational models of V1 that receive natural image inputs through multiple SF channels in the LGN, differing in whether they develop laminar or topographic organisation in layer 4. Both models lead to topographic organisation for orientation (OR) and SF preference in upper layers, consistent with current experimental evidence. The results suggest that in either case separate sub-populations of neurons are required to obtain a wide range of SF preference from Hebbian learning of natural images. These models show that a laminar organisation for SF preference can coexist with a topographic, columnar organisation for orientation, and that the columnar organisation for orientation is dependent upon inter-laminar feedback. These results help clarify and explain the wide range of SF results reported in previous studies.
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Yu, Hsin-Hao. "Integration of visual information and the organization of receptive fields in V1 of the California ground squirrel." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3283974.
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Thesis (Ph. D.)--University of California, San Diego, 2007.Title from first page of PDF file (viewed January 8, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 112-124).
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Kogan, Cary. "The expression of neurofilament protein and mRNA levels in the lateral geniculate nucleus and area V1 of the developing and adult vervet monkey (Ceorcopithicus aethiops) /." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0028/MQ50807.pdf.
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FONTENELE, NETO Antonio Jorge. "Implementação de um protocolo experimental para estudo de propriedades de resposta visual de neurônios do córtex visual primário (V1) em ratos utilizando matrizes de eletrodos." Universidade Federal de Pernambuco, 2015. https://repositorio.ufpe.br/handle/123456789/17698.
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O córtex visual primário (V1) é a região do córtex cerebral responsável pela primeira etapa de processamento da informação visual capturada pela retina. Por ser uma das áreas corticais melhor compreendidas, V1 constitui um dos principais paradigmas de compreensão do processamento sensorial. Desde os anos 70 há uma extensa literatura que estuda propriedades de resposta de neurônios de V1, principalmente com eletrodos individuais e utilizando-se como modelo animal gatos e macacos. Tem-se conhecimento de onde partem seus principais inputs e quais estímulos fazem os neurônios dispararem (grades senoidais com determinadas frequências espaciais e temporais). Mais recentemente, com o uso de matrizes de eletrodos, se tornou possível a investigação de propriedades coletivas da atividade e codificação neurais, que não eram possíveis de serem desvendadas com eletrodos individuais. Além disso, no estado da arte tecnológico atual, o uso do rato como modelo animal permite o registro da atividade neural com os animais em comportamento livre (sem anestesia ou contenção). No entanto, pouco se sabe sobre especificidades das propriedades de resposta dos neurônios do córtex visual do rato. Este trabalho teve por objetivo desenvolver um aparato e um protocolo experimental no Laboratório de Neurociência de Sistemas e Computacional adequado para estudo das propriedades de resposta de neurônios de V1 de ratos usando matrizes de eletrodos. Finalmente, apresentamos resultados experimentais onde caracterizamos respostas de neurônios de V1 a diferentes estímulos visuais (Funções de Gabor ou Grades) seja em ruído denso ou rarefeito, variando as propriedades de frequências temporal e espacial de estimulação, densidades de estímulos, velocidade, etc. Concluímos que implementamos com sucesso a técnica experimental, que abre inúmeras perspectivas futuras de pesquisas nesta linha no Departamento de Física da Universidade Federal de Pernambuco.
The primary visual cortex (V1) is the cerebral cortex region responsible for the first processing step of the visual information captured by the retina. Being one of the most studied and well described cortical sensory areas, V1 is one of the main paradigms for the study of sensory processing. Since the 70s, there is a vast literature that studies properties of V1’s neurons, specially using single electrodes and using cats and monkeys as animal models. The anatomical conectivity of the visual pathway is known, from the retina to the lateral geniculate nucleus to V1, as well as the main visual stimulations that make V1 neurons fire (sinusoidal gratings with certain spatial and temporal frequencies). More recently, using multielectrode arrays, it became possible to study coletive properties of the activity and neural codification, that could not be unveiled with single electrodes. Furthermore with, the current state of the art in multielectrode recordings it is possible to record the neural activity in frelly behaving rats (without anesthesia or restraint). This represents an advantage in using the rat as animal model. However, little is known about specificities of the V1 neurons response properties in the rat. The aim of this work is to develop, in the Laboratório de Neurociência de Sistemas e Computacional, an apparatus and an experimental protocol suitable for the study of visual response properties of V1’s neurons in rats, using multielectrode array recordings. Finally, we present experimental results that characterize the response of V1’s neurons with different visual stimuli (Gabor or Grating Functions), either in dense os sparse noise modes, varying the spatial and temporal stimulation frequencies, stimulus density, speed, etc. We conclude that the experimental technique was implemented successfully. These results open important perspectives of future research on this field for the Departamento de Física at the Universidade Federal de Pernambuco.
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Bohi, Amine. "Descripteurs de Fourier inspirés de la structure du cortex visuel primaire humain : Application à la reconnaissance de navires dans le cadre de la surveillance maritime." Thesis, Toulon, 2017. http://www.theses.fr/2017TOUL0002/document.
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Dans cette thèse, nous développons une approche supervisée de reconnaissance d’objets basée sur l’utilisation de nouveaux descripteurs d’images globaux inspirés du modèle du cortex visuel humain primaire V1 en tant que groupe de roto-translations semi-discrètes SE (2,N)=R² x ZN produit semi-direct entre R² et ZN. La méthode proposée est basée sur des descripteurs de Fourier généralisés et rotationnels définis sur le groupe SE (2,N), qui sont invariants aux transformations géométriques (translations, et rotations). De plus, nous montrons que ces descripteur de Fourier sont faiblement complets, dans le sens qu’ils permettent de discriminer sur un ensemble ouvert et dense L² (SE(2,N)) de fonctions à support compact, donc distinguer entre des images réelles. Ces descripteurs sont ensuite utilisés pour alimenter un classifieur de type SVM dans le cadre de la reconnaissance d’objets. Nous avons mené une séries d’expérimentations dans le but d’évaluer notre méthode sur les bases de visages RL, CVL et ORL et sur la base d’images d’objets variés COIL-100, et de comparer ses performances à celles des méthodes basées sur des descripteurs globaux et locaux. Les résultats obtenus ont montré que notre approche est en mesure de concurrencer de nombreuses techniques de reconnaissance d’objets existantes et de surpasser de nombreuse autres. Ces résultats ont également montré que notre méthode est robuste aux bruits. Enfin, nous avons employé la technique proposée pour reconnaître des navires dans un contexte de surveillance maritimeIn this thesis, we develop a supervised object recognition method using new global image descriptors inspired by the model of the human primary visual cortex V1. Mathematically speaking, the latter is modeled as the semi-discrete roto-translation group SE (2,N)=R² x ZN semi-direct product between R² and ZN. Therefore, our technique is based on generalized and rotational Fourier descriptors defined in SE (2,N) , and which are invariant to natural geometric transformations (translations, and rotations). Furthermore, we show that such Fourier descriptors are weakly complete, in the sense that they allow to distinguish over an open and dense set of compactly supported functions in L² (SE(2,N)) , hence between real-world images. These descriptors are later used in order to feed a Support Vector Machine (SVM) classifier for object recognition purposes. We have conducted a series of experiments aiming both at evaluating and comparing the performances of our method against existing both local - and global - descriptor based state of the art techniques, using the RL, the CVL, and the ORL face databases, and the COIL-100 image database (containing various types of objects). The obtained results have demonstrated that our approach was able to compete with many existing state of the art object recognition techniques, and to outperform many others. These results have also shown that our method is robust to noise. Finally, we have applied the proposed method on vessels recognition in the framework of maritime surveillance
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Maama, Mohamed. "Dynamiques de réseaux complexes, modélisation et simulations : application au cortex visuel Emergent Properties in a V1 Network of Hodgkin-Huxley Neurons." Thesis, Normandie, 2020. http://www.theses.fr/2020NORMLH07.
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L'objectif de ce travail est d'analyser théoriquement et numériquement la dynamique d'un réseau de neurones excitateurs et inhibiteurs d'équations différentielles ordinaires (ODE) de type Hodgkin-Huxley (HH) inspiré du cortex visuel primaire V1. Le modèle met l'accent sur une approche combinant un entraînement stochastique entraîné pour chaque neurone et des entrées récurrentes résultant de l'activité du réseau. Après un examen de la dynamique d'une seule équation HH, pour les cas déterministes et stochastiques, nous procédons à l'analyse du réseau. Notre analyse numérique met en évidence des propriétés émergentes telles que la synchronisation et la synchronisation partielles, les ondes d'excitabilité et les oscillations dans la fréquence de la bande gammaThe aim of this work is to analyze theoretically and numerically the dynamics of a network of excitatory and inhibitory neurons of ordinary differential equations (ODE) of Hodgkin-Huxley type (HH) inspired by the primary visual cortex V1. The model emphasizes an approach combining a driven stochastic drive for each neuron and recurrent inputs resulting from the network activity. After a review of the dynamics of a single HH equation, for both deterministic and stochastic driven case, we proceed to the analysis of the network. Our numerical analysis highlights emergent properties such as partial synchronization and synchronization, waves of excitability, and oscillations in the gamma-band frequency
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Cavalcante, André Borges. "Campos receptivos similares às wavelets de Haar são gerados a partir da codificação eficiente de imagens urbanas;V1." Universidade Federal do Maranhão, 2008. http://tedebc.ufma.br:8080/jspui/handle/tede/314.
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Previous issue date: 2008-02-25Efficient coding of natural images yields filters similar to the Gabor-like receptive fields of simple cells of primary visual cortex. However, natural and man-made images have different statistical proprieties. Here we show that a simple theoretical analysis of power spectra in a sparse model suggests that natural and man-made images would need specific filters for each group. Indeed, when applying sparse coding to man-made scenes, we found both Gabor and Haar wavelet-like filters. Furthermore, we found that man-made images when projected on those filters yielded smaller mean squared error than when projected on Gabor-like filters only. Thus, as natural and man-made images require different filters to be efficiently represented, these results suggest that besides Gabor, the primary visual cortex should also have cells with Haar-like receptive fields.
A codificação eficiente de imagens naturais gera filtros similares às wavelets de Gabor que relembram os campos receptivos de células simples do córtex visual primário. No entanto, imagens naturais e urbanas tem características estatísticas diferentes. Será mostrado que uma simples análise do espectro de potência em um modelo eficiente sugere que imagens naturais e urbanas requerem filtros específicos para cada grupo. De fato, aplicando codificação eficiente à imagens urbanas, encontramos filtros similares às wavelets de Gabor e de Haar. Além disso, observou-se que imagens urbanas quando projetadas nesses filtros geraram um menor erro médio quadrático do que quando projetadas somente em filtros de similares a Gabor. Desta forma, como imagens naturais e urbanas requerem filtros diferentes para serem representadas de forma eficiente, estes resultados sugerem que além de Gabor, o córtex visual primário também deve possuir células com campos receptivos similares às wavelets de Haar.
Books on the topic "Visual cortex (V1)"
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Chirimuuta, Mazviita, and Ian Gold. The Embedded Neuron, the Enactive Field? Edited by John Bickle. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780195304787.003.0010.
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This article examines the concept of the receptive field (RF) of visual neurons. It introduces the concept of visual RFs by discussing the classical picture of primary visual cortex (V1) physiology and discusses the psychophysics and computational vision of contrast discrimination to place the visual neurophysiology in context. It evaluates some recent data which questioned the classical conception of the RF and considers some options available for absorbing these data into visual theory.
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Gori, Simone. The Rotating Tilted Lines Illusion. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0066.
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This chapter describes the Rotating-Tilted-Lines illusion , which is a new motion illusion that arises in a circular pattern composed by black, radial lines tilted to the right and presented on a white background. When one approaches the stimulus pattern, the radial lines appear to rotate in the counterclockwise direction, whereas when one recedes from it, they appear to rotate clockwise. It is the simplest pattern able to elicit illusory rotatory motion in presence of physical radial expansion. This surprising misperception of motion seems to be a result of the competition between two motion processing units in the primary visual cortex (V1, V5)
Book chapters on the topic "Visual cortex (V1)"
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Pino, Robinson E., and Michael Moore. "A Columnar V1/V2 Visual Cortex Model and Emulation." In Advances in Neuromorphic Memristor Science and Applications, 269–90. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4491-2_14.
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Mandal, Atanendu Sekhar. "Contextual Effects in the Visual Cortex Area 1 (V1) and Camouflage Perception." In Perception and Machine Intelligence, 35–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27387-2_5.
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Yan, Tianyi, Fengzhe Jin, and Jinglong Wu. "Correlated Size Variations Measured in Human Visual Cortex V1/V2/V3 with Functional MRI." In Brain Informatics, 36–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04954-5_14.
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Alekseevsky, Dmitri. "Conformal Model of Hypercolumns in V1 Cortex and the Möbius Group. Application to the Visual Stability Problem." In Lecture Notes in Computer Science, 65–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80209-7_8.
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"Retinotopic Areas: V1, V2, V4." In Visual Cortex and Deep Networks. The MIT Press, 2016. http://dx.doi.org/10.7551/mitpress/10177.003.0005.
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Leigh, R. John, and David S. Zee. "The Neural Basis for Conjugate Eye Movements." In The Neurology of Eye Movements, 386–473. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199969289.003.0007.
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This chapter draws on a range of studies of macaque and humans to forge an anatomical scheme for the control of gaze. At each stage, this scheme is used to predict effects of focal lesions on the control of gaze, with video examples. Contributions include the abducens nucleus, medial longitudinal fasciculus (MLF), and paramedian pontine reticular formation (PPRF) to horizontal gaze; the rostral interstitial nucleus of the medial longitudinal fasciculus (RIMLF), interstitial nucleus of Cajal, and posterior commissure to vertical gaze; cerebellar flocculus, paraflocculus, dorsal vermis, fastigial nucleus, and inferior olive to adaptive optimization of gaze. Cortical control of gaze by structures including primary visual cortex (V1), middle temporal visual area (MT, V5), medial superior temporal visual area (MST), posterior parietal cortex, frontal eye fields, supplementary eye fields, dorsolateral prefrontal cortex, cingulate cortex, descending pathways, thalamus, pulvinar, caudate, substantia nigra pars reticulata, subthalamic nucleus, and superior colliculus are each discussed.
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Afef, Ouelhazi, Rudy Lussiez, and Molotchnikoff Stephane. "Cortical Plasticity under Ketamine: From Synapse to Map." In Sensory Nervous System - Computational Neuroimaging Investigations of Topographical Organization in Human Sensory Cortex [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.104787.
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Sensory systems need to process signals in a highly dynamic way to efficiently respond to variations in the animal’s environment. For instance, several studies showed that the visual system is subject to neuroplasticity since the neurons’ firing changes according to stimulus properties. This dynamic information processing might be supported by a network reorganization. Since antidepressants influence neurotransmission, they can be used to explore synaptic plasticity sustaining cortical map reorganization. To this goal, we investigated in the primary visual cortex (V1 of mouse and cat), the impact of ketamine on neuroplasticity through changes in neuronal orientation selectivity and the functional connectivity between V1 cells, using cross correlation analyses. We found that ketamine affects cortical orientation selectivity and alters the functional connectivity within an assembly. These data clearly highlight the role of the antidepressant drugs in inducing or modeling short-term plasticity in V1 which suggests that cortical processing is optimized and adapted to the properties of the stimulus.
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Bakker, Marleen, Hinke N. Halbertsma, Nicolás Gravel, Remco Renken, Frans W. Cornelissen, and Barbara Nordhjem. "Early Visual Areas are Activated during Object Recognition in Emerging Images." In Sensory Nervous System - Computational Neuroimaging Investigations of Topographical Organization in Human Sensory Cortex [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.105756.
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Human observers can reliably segment visual input and recognise objects. However, the underlying processes happen so quickly that they normally cannot be captured with fMRI. We used Emerging Images (EI), which contains a hidden object and extends the process of recognition, to investigate the involvement of early visual areas (V1, V2 and V3) and lateral occipital complex (LOC) in object recognition. The early visual areas were located with a retinotopy scan and the LOC with a localiser. The participants (N=8) then viewed an EI, followed by the hidden object’s silhouette (disambiguation), and then, the EI was repeated. BOLD responses before and after disambiguation were compared. The retinotopy parameters were used to back-project the BOLD response onto the visual field, creating spatially detailed maps of the activity change. V1 and V2 (but not V3) showed stronger response after disambiguation, while there was no difference in the LOC. The back-projections revealed no distinct pattern or changes in activity on object location, indicating that the activity in V1 and V2 is not specific for voxels corresponding to the object location. We found no difference before and after disambiguation in the LOC, which may be repetition suppression counteracting the effect of recognition.
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Grossberg, Stephen. "How Prefrontal Cortex Works." In Conscious Mind, Resonant Brain, 517–38. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190070557.003.0014.
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This chapter describes a unified theory of how the prefrontal cortex interacts with multiple brain regions to carry out the higher cognitive, emotional, and decision-making processes that define human intelligence, while also controlling actions to achieve valued goals. This predictive Adaptive Resonance Theory, or pART, model builds upon the foundation in earlier chapters. Prefrontal functions are often called executive functions. Executive functions regulate flexible and adaptive behaviors, notably in novel situations, while suppressing actions that are no longer appropriate, notably reflexive responses to current sensory inputs. Working memory is particularly involved in contextually appropriate behaviors. Prefrontal properties of desirability, availability, credit assignment, category learning, and feature-based attention are explained. These properties arise through interactions of orbitofrontal, ventrolateral prefrontal, and dorsolateral prefrontal cortices with inferotemporal cortex, perirhinal cortex, parahippocampal cortices; ventral bank of the principal sulcus, ventral prearcuate gyrus, frontal eye fields, hippocampus, amygdala, basal ganglia, hypothalamus, and visual cortical areas V1, V2, V3A, V4, MT, MST, LIP, and PPC. Model explanations include how the value of visual objects and events is computed, which objects and events cause desired consequences and which may be ignored as predictively irrelevant, and how to plan and act to realize these consequences, including how to selectively filter expected vs. unexpected events, leading to movements towards, and conscious perception of, expected events. Modeled processes include reinforcement learning and incentive motivational learning; object and spatial working memory dynamics; and category learning, including the learning of object categories, value categories, object-value categories, and sequence categories, or list chunks.
Conference papers on the topic "Visual cortex (V1)"
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Xu, Yuelei, Xulei Zhang, Chao Lv, Shiping Ma, Shuai Li, Peng Xin, Mingming Zhu, and Hongqiang Ma. "Feature extraction inspired by V1 in visual cortex." In Ninth International Conference on Graphic and Image Processing, edited by Hui Yu and Junyu Dong. SPIE, 2018. http://dx.doi.org/10.1117/12.2302951.
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Yan, Tian-yi, Feng-zhe Jin, and Jing-long Wu. "Visual field representation and location of visual area V1 in human visual cortex by functional MRI." In 2009 ICME International Conference on Complex Medical Engineering - CME 2009. IEEE, 2009. http://dx.doi.org/10.1109/iccme.2009.4906645.
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Songnian, Zhao, Zou Qi, Jin Zhen, Xiong Xiaoyun, Yao Guozheng, Yao Li, and Liu Yijun. "A Computational Model that Realizes a Sparse Representation of the Primary Visual Cortex V1." In 2009 WRI World Congress on Software Engineering. IEEE, 2009. http://dx.doi.org/10.1109/wcse.2009.40.
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Moore, Michael J., Richard Linderman, Morgan Bishop, and Robinson Pino. "A columnar primary visual cortex (V1) model emulation using a PS3 Cell-BE array." In 2010 International Joint Conference on Neural Networks (IJCNN). IEEE, 2010. http://dx.doi.org/10.1109/ijcnn.2010.5596903.
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Pino, Robinson E., Michael Moore, Jason Rogers, and Qing Wu. "A columnar V1/V2 visual cortex model and emulation using a PS3 cell-BE array." In 2011 International Joint Conference on Neural Networks (IJCNN 2011 - San Jose). IEEE, 2011. http://dx.doi.org/10.1109/ijcnn.2011.6033425.
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