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Riesenhuber \& Poggio recently proposed a model of object recognitionin cortex which, beyond integrating general beliefs about the visualsystem in a quantitative framework, made testable predictions aboutvisual processing. In particular, they showed that invariant objectrepresentation could be obtained with a selective pooling mechanismover properly chosen afferents through a {\sc max} operation: Forinstance, at the complex cells level, pooling over a group of simplecells at the same preferred orientation and position in space but atslightly different spatial frequency would provide scale tolerance,while pooling over a group of simple cells at the same preferredorientation and spatial frequency but at slightly different positionin space would provide position tolerance. Indirect support for suchmechanisms in the visual system come from the ability of thearchitecture at the top level to replicate shape tuning as well asshift and size invariance properties of ``view-tuned cells'' (VTUs)found in inferotemporal cortex (IT), the highest area in the ventralvisual stream, thought to be crucial in mediating object recognitionin cortex. There is also now good physiological evidence that a {\scmax} operation is performed at various levels along the ventralstream. However, in the original paper by Riesenhuber \& Poggio,tuning and pooling parameters of model units in early and intermediateareas were only qualitatively inspired by physiological data. Inparticular, many studies have investigated the tuning properties ofsimple and complex cells in primary visual cortex, V1. We show thatunits in the early levels of HMAX can be tuned to produce realisticsimple and complex cell-like tuning, and that the earlier findings onthe invariance properties of model VTUs still hold in this morerealistic version of the model.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2018-01-16T18:01:47Z No. of bitstreams: 1 KatiaSimoneDeAraujoNobregaRocha_DISSERT.pdf: 15764760 bytes, checksum: 8bfb9a0320607958c4f488fa38d6706c (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2018-01-22T11:31:34Z (GMT) No. of bitstreams: 1 KatiaSimoneDeAraujoNobregaRocha_DISSERT.pdf: 15764760 bytes, checksum: 8bfb9a0320607958c4f488fa38d6706c (MD5) / Made available in DSpace on 2018-01-22T11:31:34Z (GMT). No. of bitstreams: 1 KatiaSimoneDeAraujoNobregaRocha_DISSERT.pdf: 15764760 bytes, checksum: 8bfb9a0320607958c4f488fa38d6706c (MD5) Previous issue date: 2017-08-31 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / Cortical gamma oscillations (30 - 90 Hz) have been implicated in various cognitive processes, such as perceptual binding and attention. So far, most evidence in support of this hypothesis is based on studies that used artificial and simplified stimuli, such as moving gratings and bars. Recently, experimental work using natural images led to conflicting conclusions. In a paradigm that required human subjects to maintain fixation, electrocorticogram signals (ECoG) showed gamma for grating stimuli but not for static images or pink noise (Hermes et al., 2015). On the contrary, analysis of ECoG in the early visual cortex of macaque monkeys revealed strong gamma components for free viewing of natural scenes (Brunet et al., 2015). Here, we aim to clarify these discrepancies using a paradigm that allowed direct comparisons between fixation vs. free viewing conditions, for both simplified stimuli (moving and static gratings) and natural scenes (static and moving images). Recordings of spiking activity and local field potentials (LFPs) were obtained from the central and the peripheral representations of V1. Our results show that in capuchins (N= 3 monkeys), as previously described in macaques and humans, gamma is characteristically strong when stimulus parameters, such as size, orientation, and speed are set at to optimal values. Comparisons between fixation vs. free viewing conditions and gratings vs. natural stimuli revealed that gamma is always high for optimal grating stimuli, regardless of viewing condition (N= 93 recording sites, 2 monkeys). However, gamma is surprisingly absent during free viewing of natural images and movies. Similar negative findings were also obtained when the monkeys were exposed to real-world scenes, such as objects and other animals in the laboratory. The present results suggest that strong, narrow-band, gamma responses in V1 are primarily associated with the selective activation of cell populations sharing similar response properties. Therefore, gamma may be seen as a resonance phenomenon of the underlying cortical connectivity. Overall, our results belittle the importance of gamma as a critical cortical mechanism for vision. / As oscila??es corticais gama (30 - 90 Hz) t?m sido implicadas em processos cognitivos como a liga??o perceptual e a aten??o. At? agora, a maioria das evid?ncias que servem de suporte para esta hip?tese ? baseada em e s t u d o s a p a r t i r do uso de e s t ? m u l o s s i m p l e s e artificiais, como grades e barras luminosas. Recentemente, no entanto, estudos experimentais utilizando imagens naturais levaram a conclus?es conflitantes. Em um paradigma em humanos que requeria fixa??o mantida, sinais eletrocorticogr?ficos (ECoG) mostraram gama para grades, mas n?o p a r a imagens e s t ? t i c a s ou r u ? d o r o s a (Hermes e t a l . , 2 0 1 5 ) . Contrariamente, a an?lise dos sinais ECoG no c?rtex visual de macacosreso revelou fortes componentes gama para a livre observa??o de cenas naturais (Brunet et al., 2015). Neste estudo, temos por objetivo esclarecer essas discrep?ncias utilizando-se de um paradigma que permitiu compara??es diretas entre uma condi??o de fixa??o vs. uma condi??o de observa??o livre, tanto para est?mulos simplificados (grades m?veis e e s t ? t i c a s ) q u a n t o p a r a c e n a s n a t u r a i s ( i m a g e n s e s t ? t i c a s e em movimento). Registros de potenciais de a??o e de potenciais de campo locais (LFPs) foram obtidos para a representa??o central e perif?rica de V1. Nossos resultados demonstram que em macacos-capuchinhos (N = 3), como descrito anteriormente para macacos-reso e humanos, a gama ? caracteristicamente forte, sempre que os par?metros do est?mulo, como tamanho, orienta??o e velocidade, s?o definidos para a ativa??o ?tima das c?lulas. Compara??es entre condi??es de fixa??o e de livre observa??o e grades vs. est?mulos naturais revelaram que a gama ? sempre forte para grades de orienta??o ?tima, independentemente da condi??o de visualiza??o (N = 93 s?tios de registro, 2 macacos). No entanto, a gama est? surpreendentemente ausente durante a livre visualiza??o de imagens e filmes naturais. Achados negativos semelhantes tamb?m foram obtidos quando os macacos foram expostos a cenas do mundo real, como objetos e outros animais no laborat?rio. Os presentes resultados sugerem que, no c?rtex visual prim?rio, a atividade gama ? principalmente associada ? ativa??o seletiva de popula??es neuronais que compartilham propriedades de resposta similares. Portanto, a gama pode ser vista como um fen?meno de resson?ncia da conectividade cortical subjacente. Em geral, nossos resultados minimizam a import?ncia da gama como um mecanismo cortical chave para a vis?o.

The pulvinar, which is located in the posterior thalamus, establishes reciprocal connections with nearly all of the visual cortical areas and is consequently in a strategic position to influence their stimulus decoding processes. Projections from the pulvinar to the primary visual cortex (V1) are thought to be modulatory, altering the response of neurons without changing their basic receptive field properties. Here, we investigate this issue by studying V1 single unit responses to sine wave gratings during the reversible inactivation of the lateral posterior nucleus (LP) - pulvinar complex in the cat. We also studied the contrast response function of V1 neurons, before and during the inactivation of the LP-pulvinar complex. No change in the preferred orientation or direction selectivity of V1 neurons was observed during pulvinar inactivation. However, for the majority of the cells tested the response amplitude to the optimal stimulus was reduced. The contrast response function of neurons was fitted with the Naka-Rushton function and analysis of the effects of pulvinar deactivation revealed a diverse set of modulations: 35% of cells had a decrease in their peak response, 11% had an increase in their C50, 6% showed modulations of the slope factor and 22% exhibited changes in more than one parameter. Our results suggest that the pulvinar modulates activity of V1 neurons in a contrast dependent manner and provides gain control at lower levels of the visual cortical hierarchy. / Le pulvinar, localisé dans le thalamus postérieur, établit des connections réciproques avec la vaste majorité des aires visuelles corticales et il est ainsi dans une position stratégique afin d’influencer les processus de décodage de celles-ci. Les projections du pulvinar au cortex visuel primaire (V1) sont considérées comme étant des projections modulatrices, qui modifieraient les réponses neuronales sans toutefois changer les propriétés de base des champs récepteurs. Dans la présente étude, nous avons étudié les réponses des neurones de V1 suite à l’inactivation réversible du complexe noyau latéral postérieur (LP)-pulvinar chez le chat. Des courbes de réponse au contraste ont été générées par la présentation de réseaux ayant plusieurs niveaux de contraste pendant l’inactivation du LP-pulvinar. Aucun changement n’a été observé concernant l’orientation préférée ou la sélectivité à la direction des neurones de V1 lors de l’inactivation du pulvinar. Néanmoins, pour la majorité des cellules testées, l’amplitude de la réponse aux stimuli optimaux a été réduite. La fonction de Naka-Rushton a été appliquée aux courbes de réponse au contraste et l’analyse des effets de l’inactivation du pulvinar a montré une panoplie d’effets modulateurs : 35% des cellules ont présenté une réduction de leur réponse maximale, 11% ont eu une augmentation de leur C50, 6% ont montré une modulation de la pente et 22% des neurones ont présenté des changements dans plus d’un paramètre. Nos résultats suggèrent que le pulvinar module l’activité des neurones de V1 d’une façon dépendante du contraste et qu’il contrôle le gain des réponses des neurones des aires primaires du cortex visuel.

The diploma thesis deals with measuring pressure in microfluidic systems. The theoretical part of the work is devoted to microfluidics, pressure in liquids, pressure measurement, distribution of pressure sensors, and their specifications. Then follows the hardware and software solution of the measuring system for measuring the pressure in the microfluidic system using microprocessor technology. The practical part covers the hardware and software implementation of the measuring system.

<p>The primary visual cortex (V1) is a center in the visual pathway that receives the converging information and sends diverging information to multiple visual areas. It is essential for the normal functioning of the visual system. While processing the input from the outside world, it is also continually modified by the sensory experience. This thesis is dedicated to studying the plasticity in the visual cortex that is associated with experience and brain damage recovery. In this thesis, we discovered that the visual experience induces 5 Hz oscillations that recruit inhibition in V1, sharpening the feature selectivity. We have also demonstrated that gene therapy to convert astrocytes into neurons induces neuronal circuit plasticity and functional recovery in mouse V1 following ischemia.</p>

No description available.

Dans le domaine des neurosciences computationnelles, l'hypothèse a été émise que le système visuel, depuis la rétine et jusqu'au cortex visuel primaire au moins, ajuste continuellement un modèle probabiliste avec des variables latentes, à son flux de perceptions. Ni le modèle exact, ni la méthode exacte utilisée pour l'ajustement ne sont connus, mais les algorithmes existants qui permettent l'ajustement de tels modèles ont besoin de faire une estimation conditionnelle des variables latentes. Cela nous peut nous aider à comprendre pourquoi le système visuel pourrait ajuster un tel modèle; si le modèle est approprié, ces estimé conditionnels peuvent aussi former une excellente représentation, qui permettent d'analyser le contenu sémantique des images perçues. Le travail présenté ici utilise la performance en classification d'images (discrimination entre des types d'objets communs) comme base pour comparer des modèles du système visuel, et des algorithmes pour ajuster ces modèles (vus comme des densités de probabilité) à des images. Cette thèse (a) montre que des modèles basés sur les cellules complexes de l'aire visuelle V1 généralisent mieux à partir d'exemples d'entraînement étiquetés que les réseaux de neurones conventionnels, dont les unités cachées sont plus semblables aux cellules simples de V1; (b) présente une nouvelle interprétation des modèles du système visuels basés sur des cellules complexes, comme distributions de probabilités, ainsi que de nouveaux algorithmes pour les ajuster à des données; et (c) montre que ces modèles forment des représentations qui sont meilleures pour la classification d'images, après avoir été entraînés comme des modèles de probabilités. Deux innovations techniques additionnelles, qui ont rendu ce travail possible, sont également décrites : un algorithme de recherche aléatoire pour sélectionner des hyper-paramètres, et un compilateur pour des expressions mathématiques matricielles, qui peut optimiser ces expressions pour processeur central (CPU) et graphique (GPU). / Computational neuroscientists have hypothesized that the visual system from the retina to at least primary visual cortex is continuously fitting a latent variable probability model to its stream of perceptions. It is not known exactly which probability model, nor exactly how the fitting takes place, but known algorithms for fitting such models require conditional estimates of the latent variables. This gives us a strong hint as to why the visual system might be fitting such a model; in the right kind of model those conditional estimates can also serve as excellent features for analyzing the semantic content of images perceived. The work presented here uses image classification performance (accurate discrimination between common classes of objects) as a basis for comparing visual system models, and algorithms for fitting those models as probability densities to images. This dissertation (a) finds that models based on visual area V1's complex cells generalize better from labeled training examples than conventional neural networks whose hidden units are more like V1's simple cells, (b) presents novel interpretations for complex-cell-based visual system models as probability distributions and novel algorithms for fitting them to data, and (c) demonstrates that these models form better features for image classification after they are first trained as probability models. Visual system models based on complex cells achieve some of the best results to date on the CIFAR-10 image classification benchmark, and samples from their probability distributions indicate that they have learnt to capture important aspects of natural images. Two auxiliary technical innovations that made this work possible are also described: a random search algorithm for selecting hyper-parameters, and an optimizing compiler for matrix-valued mathematical expressions which can target both CPU and GPU devices.