Добірка наукової літератури з теми "Visual cortex (V1)"
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Статті в журналах з теми "Visual cortex (V1)"
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.
Повний текст джерелаFroudarakis, 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.
Повний текст джерелаWhite, 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.
Повний текст джерелаHawken, 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.
Повний текст джерелаTehovnik, 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.
Повний текст джерелаSchira, 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.
Повний текст джерелаWatanabe, 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.
Повний текст джерелаPereira, 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.
Повний текст джерелаDUFFY, 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.
Повний текст джерелаBressloff, 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.
Повний текст джерелаДисертації з теми "Visual cortex (V1)"
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.
Повний текст джерелаStevens, 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.
Повний текст джерелаFournier, Julien. "Adaptation of the simple or complex nature of V1 receptive fields to visual statistics." Paris 6, 2009. http://www.theses.fr/2009PA066426.
Повний текст джерелаPalmer, 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.
Повний текст джерелаYu, 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.
Повний текст джерелаTitle from first page of PDF file (viewed January 8, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 112-124).
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.
Повний текст джерелаFONTENELE, 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.
Повний текст джерелаMade available in DSpace on 2016-08-18T12:54:46Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Antonio Jorge Fontenele Neto.pdf: 9942923 bytes, checksum: 9de5bf466a9fc72acbc6a2a2d3a9c57c (MD5) Previous issue date: 2015-08-25
CAPEs
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.
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.
Повний текст джерелаIn 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
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.
Повний текст джерелаThe 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
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.
Повний текст джерелаEfficient 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.
Книги з теми "Visual cortex (V1)"
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.
Повний текст джерелаGori, Simone. The Rotating Tilted Lines Illusion. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0066.
Повний текст джерелаЧастини книг з теми "Visual cortex (V1)"
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.
Повний текст джерелаMandal, 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.
Повний текст джерелаYan, 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.
Повний текст джерелаAlekseevsky, 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.
Повний текст джерела"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.
Повний текст джерелаLeigh, 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.
Повний текст джерелаAfef, 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.
Повний текст джерелаBakker, 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.
Повний текст джерелаGrossberg, 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.
Повний текст джерелаТези доповідей конференцій з теми "Visual cortex (V1)"
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.
Повний текст джерелаYan, 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.
Повний текст джерелаSongnian, 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.
Повний текст джерелаMoore, 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.
Повний текст джерелаPino, 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.
Повний текст джерела