Dissertations / Theses on the topic 'Primary Visual Cortex (area V1)'

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.

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.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-08-18T12:54:46Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Antonio Jorge Fontenele Neto.pdf: 9942923 bytes, checksum: 9de5bf466a9fc72acbc6a2a2d3a9c57c (MD5)<br>Made 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<br>CAPEs<br>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.<br>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.

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 maritime<br>In 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

Made available in DSpace on 2016-08-17T14:52:43Z (GMT). No. of bitstreams: 1 Andre Borges Cavalcante.pdf: 1739525 bytes, checksum: 2073615c7df203b086d5c76276905a35 (MD5) Previous issue date: 2008-02-25<br>Efficient 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.<br>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.

The effect of visual attention on neural signals has been extensively studied using various techniques such as macaque neurophysiology and human electro/magneto encephalogram (EEG/MEG). Depending on the technique, different neural measures are typically used for studying attention. For example, in neurophysiology experiments involving macaques, many studies have focused on the modulation in spiking activity or the change in oscillatory power at different frequency bands such as alpha (8-12 Hz) or gamma (30-80 Hz) with attention, or the change in the relationship of spikes with these oscillations. In contrast, human EEG studies, in addition to studying alpha and gamma modulation, often use flickering stimuli that produce a specific neural response called steady-state visually evoked potential (SSVEP), which is also modulated by attention. However, due to the differences in stimuli and task paradigms in such studies, it is difficult to determine the effectiveness of these various neural measures for capturing attentional modulation. To address this, we designed a task paradigm which included both static and counterphase flickering stimuli to generate all the relevant neural measures (alpha/gamma power as well as SSVEPs) under identical recording conditions, which allowed us to compare their effectiveness in studying attention. Since several reports suggest that attention modulates these neural measures through a canonical neural mechanism called normalization, in the first study of this thesis, we varied the normalization strength parametrically as a proxy for attentional modulation and tested its effect on various neural measures. We manipulated normalization strength by presenting static as well as flickering orthogonal superimposed gratings (plaids) at varying contrasts to two female monkeys while recording multiunit activity (MUA) and LFP from the primary visual cortex (area V1). We quantified the modulation in MUA, gamma (32-80 Hz), high-gamma (104-248 Hz) power, and SSVEP. Even under similar conditions, normalization strength was different for the four measures; and increased as: spikes, high-gamma, SSVEP, and gamma. However, these results could be explained using a normalization model, modified for population responses by varying the tuned normalization parameter and semi-saturation constant. In the second part of the thesis, we tested the predictions of the gamma phase coding hypothesis in the context of stimulus contrast and visual attention. The gamma phase coding hypothesis posits that the intensity of the incoming stimulus is encoded in the position of the spike relative to the gamma rhythm. Using chronically implanted microelectrode arrays in the primary visual cortex of macaques engaged in an attention task while presenting stimuli of varying contrasts, we tested whether the phase of the gamma rhythm relative to spikes varied as a function of stimulus contrast and attentional state. We analyzed spikes and LFP from different electrodes and found a weak but significant effect of attention, but not stimulus contrast, on the gamma phase relative to spikes. Although we found a significant effect of attention, we argue that a small magnitude of phase shift as well as the dependence of phase angles on gamma power and center frequency, limits the potential role of gamma in phase coding in area V1. In the third part of the thesis, we recorded EEG signals from 26 human participants while they were engaged in an attention task and analyzed alpha and gamma band powers for both static and flickering stimuli and SSVEP power for flickering stimuli. We report two main results. First, attentional modulation was comparable for SSVEP and alpha. Second, we found that non-foveal stimuli produced weak gamma despite various stimulus optimizations and therefore showed a negligible effect of attention although the same participants showed robust gamma activity for full-screen gratings. Thus, alpha and SSVEP won over gamma in capturing attentional modulation in human EEG. This result was in contrast to the findings of a comparable study in monkeys, where gamma and alpha won over SSVEPs. This study highlights the effectiveness of various neural measures in studying visual spatial attention and further implicates their usefulness in decoding behavior and attentional state in humans.<br>DBT-Wellcome Trust India Alliance (Grant IA/S/18/2/504003), Tata Trusts, DBT-IISc Partnership Programme

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.<br>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 notion that learning and memory processes are highly dependent on central cholinergic neurotransmission has been widely accepted. However, studies documenting the importance of Acetylcholine (ACh) in attention have led some to suggest that attention impairments may underlie the deficits in learning and memory resulting from cholinergic disruptions. Using a visual discrimination task, I attempted to discern whether performance impairments by Scopolamine were predominantly due to the importance of muscarinic receptor integrity in attention, or memory consolidation in learning. Rats were trained in a visual discrimination task using a Y-shaped water maze apparatus. To successfully navigate to a hidden platform located in one of the two goal arms, rats learned to discriminate between 2 distinct visual cues, indicating the platform’s presence (CS+) or absence (CS-), respectively. Following task acquisition, testing continued using a combination of Regular trials (RT; both CS+ and CS- present) and Probe trials (PT; only one of the cues present). Results indicated that performance on PT was impaired due to greater task difficulty under conditions of reduced information, while Scopolamine (1 mg/kg) further impacted PT performance without affecting RTs. In a second experiment, PTs were administered with the platform present to provide reinforcement and a learning opportunity. Animals still exhibited poorer PT performance, but rapidly learned to rely on a single cue for accurate platform localization. Interestingly, this learning was not apparent under conditions of Scopolamine treatment (1 mg/kg), even though RT performance was completely unaffected. To examine experience-dependent changes in neuronal responding after visual discrimination learning, a subset of animals were anesthetised and visual evoked potentials (VEPs) in V1 and area CA1 of the hippocampus were recorded in response to CS+, CS-, and novel stimuli. In both the V1 and CA1, the VEP amplitudes elicited to familiar and novel stimuli were not significantly different. First, these experiments demonstrate the importance of the cholinergic system in sustaining visual attention and acquiring a new single-cue strategy. Furthermore, the null electrophysiology findings do not rule out the plastic response properties of the mature V1 and CA1, but remind us of the complex nature of memory encoding in the brain.<br>Thesis (Master, Psychology) -- Queen's University, 2011-09-16 13:50:24.045

<p><a></a><a>The visual system is capable of interpreting immense sensory complexity, allowing us to quickly identify behaviorally relevant stimuli in the environment. It performs this task with a hierarchical organization that works to detect, relay, and integrate visual stimulus features into an interpretable form. To understand the complexities of this system, visual neuroscientists have benefited from the many advantages of using mice as visual models. Despite their poor visual acuity, these animals possess surprisingly complex visual systems, and have been instrumental in understanding how visual features are processed in the primary visual cortex (V1). However, a growing body of literature has shown that primary sensory areas like V1 are capable of more than basic feature detection, but can express neural activity patterns related to learning, memory, categorization, and prediction. </a></p> <p>Visual experience fundamentally changes the encoding and perception of visual stimuli at many scales, and allows us to become familiar with environmental cues. However, the neural processes that govern visual familiarity are poorly understood. By exposing awake mice to repetitively presented visual stimuli over several days, we observed the emergence of low frequency oscillations in the primary visual cortex (V1). The oscillations emerged in population level responses known as visually evoked potentials (VEPs), as well as single-unit responses, and were not observed before the perceptual experience had occurred. They were also not evoked by novel visual stimuli, suggesting that they represent a new form of visual familiarity in the form of low frequency oscillations. The oscillations also required the muscarinic acetylcholine receptors (mAChRs) for their induction and expression, highlighting the importance of the cholinergic system in this learning and memory-based phenomenon. Ongoing visually evoked oscillations were also shown to increase the VEP amplitude of incoming visual stimuli if the stimuli were presented at the high excitability phase of the oscillations, demonstrating how neural activity with unique temporal dynamics can be used to influence visual processing.</p> <p>Given the necessity of perceptual experience for the strong expression of these oscillations and their dependence on the cholinergic system, it was clear we had discovered a phenomenon grounded in visual learning or memory. To further validate this, we characterized this response in a mouse model of Fragile X syndrome (FX), the most common inherited form of autism and a condition with known visual perceptual learning deficits. Using a multifaceted experimental approach, a number of neurophysiological differences were found in the oscillations displayed in FX mice. Extracellular recordings revealed shorter durations and lower power oscillatory activity in FX mice. Furthermore, we found that the frequency of peak oscillatory activity was significantly decreased in FX mice, demonstrating a unique temporal neural impairment not previously reported in FX. In collaboration with Dr. Christopher J. Quinn at Purdue, we performed functional connectivity analysis on the extracellularly recorded spikes from WT and FX mice. This analysis revealed significant impairments in functional connections from multiple layers in FX mice after the perceptual experience; some of which were validated by another graduate student (Qiuyu Wu) using Channelrhodopsin-2 assisted circuit mapping (CRACM). Together, these results shed new light on how visual stimulus familiarity is differentially encoded in FX via persistent oscillations, and allowed us to identify impairments in cross layer connectivity that may underlie these differences. </p> <p>Finally, we asked whether these oscillations are observable in other brain areas or are intrinsic to V1. Furthermore, we sought to determine if the oscillating unit populations in V1 possess uniform firing dynamics, or contribute differentially to the population level response. By performing paired recordings, we did not find prominent oscillatory activity in two visual thalamic nuclei (dLGN and LP) or a nonvisual area (RSC) connected to V1, suggesting the oscillations may not propagate with similar dynamics via cortico-thalamic connections or retrosplenial connections, <a>but may either be uniquely distributed across the visual hierarchy or predominantly</a> restricted to V1. Using K-means clustering on a large population of oscillating units in V1, we found unique temporal profiles of visually evoked responses, demonstrating distinct contributions of different unit sub-populations to the oscillation response dynamics.</p>

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.<br>Source: Dissertation Abstracts International, Volume: 68-11, Section: B, page: 7161. Adviser: Janice M. Juraska. Includes bibliographical references (leaves 60-79) Available on microfilm from Pro Quest Information and Learning.

<div>The visual system is responsible for processing visual input, inferring its environmental causes, and assessing its behavioral significance that eventually relates to visual perception and guides animal behavior. There is emerging evidence that visual perception does not simply mirror the outside world but is heavily influenced by contextual information. Specifically, context might refer to the sensory, cognitive, and/or behavioral cues that help to assess the behavioral relevance of image features. One of the most famous examples of such behavior is visual or optical illusions. These illusions contain sensory cues that induce a subjective percept that is not aligned with the physical nature of the stimulation, which, in turn, suggests that a visual system is not a passive filter of the outside world but rather an active inference machine.</div><div>Such robust behavior of the visual system is achieved through intricate neural computations spanning several brain regions that allow dynamic visual processing. Despite the numerous attempts to gain insight into those computations, it has been challenging to decipher the circuit-level implementation of contextual processing due to technological limitations. These questions are of great importance not only for basic research purposes but also for gaining deeper insight into neurodevelopmental disorders that are characterized by altered sensory experiences. Recent advances in genetic engineering and neurotechnology made the mouse an attractive model to study the visual system and enabled other researchers and us to gain unprecedented cellular and circuit-level insights into neural mechanisms underlying contextual processing.</div><div>We first investigated how familiarity modifies the neural representation of stimuli in the mouse primary visual cortex (V1). Using silicon probe recordings and pupillometry, we probed neural activity in naive mice and after animals were exposed to the same stimulus over the course of several days. We have discovered that familiar stimuli evoke low-frequency oscillations in V1. Importantly, those oscillations were specific to the spatial frequency content of the familiar stimulus. To further validate our findings, we investigated how this novel form of visual learning is represented in serotonin-transporter (SERT) deficient mice. These transgenic animals have been previously found to have various neurophysiological alterations. We found that SERT-deficient animals showed longer oscillatory spiking activity and impaired cortical tuning after visual learning. Taken together, we discovered a novel phenomenon of familiarity-evoked oscillations in V1 and utilized it to reveal altered perceptual learning in SERT-deficient mice.</div><div>16</div><div>Next, we investigated how spatial context influences sensory processing. Visual illusions provide a great opportunity to investigate spatial contextual modulation in early visual areas. Leveraging behavioral training, high-density silicon probe recordings, and optogenetics, we provided evidence for an interplay of feedforward and feedback pathways during illusory processing in V1. We first designed an operant behavioral task to investigate illusory perception in mice. Kanizsa illusory contours paradigm was then adapted from primate studies to mouse V1 to elucidate neural correlates of illusory responses in V1. These experiments provided behavioral and neurophysiological evidence for illusory perception in mice. Using optogenetics, we then showed that suppression of the lateromedial area inhibits illusory responses in mouse V1. Taken together, we demonstrated illusory responses in mice and their dependence on the top-down feedback from higher-order visual areas.</div><div>Finally, we investigated how temporal context modulates neural responses by combining silicon probe recordings and a novel visual oddball paradigm that utilizes spatial frequency filtered stimuli. Our work extended prior oddball studies by investigating how adaptation and novelty processing depends on the tuning properties of neurons and their laminar position. Furthermore, given that reduced adaptation and sensory hypersensitivity are one of the hallmarks of altered sensory experiences in autism, we investigated the effects of temporal context on visual processing in V1 of a mouse model of fragile X syndrome (FX), a leading monogenetic cause of autism. We first showed that adaptation was modulated by tuning properties of neurons in both genotypes, however, it was more confined to neurons preferring the adapted feature in FX mice. Oddball responses, on the other hand, were modulated by the laminar position of the neurons in WT with the strongest novelty responses in superficial layers, however, they were uniformly distributed across the cortical column in FX animals. Lastly, we observed differential processing of omission responses in FX vs. WT mice. Overall, our findings suggest that reduced adaptation and increased oddball processing might contribute to altered perceptual experiences in FX and autism.</div>

Dans le cortex visuel primaire du chat (aires 17 et 18), les neurones répondant aux orientations présentes dans l’environnement (comme le contour des objets) sont organisés en colonnes perpendiculaires à la surface du cortex. Il a précédemment été montré qu'un changement drastique des orientations présentes dans l’environnement change la réponse des neurones. Par exemple, un neurone répondant à des orientations horizontales pourra répondre, après apprentissage d'un nouvel environnement, à des orientations obliques. Nous avons voulu, dans cette thèse, suivre les changements de propriétés de populations entières de neurones suite à ce type d'apprentissage. A cet effet, nous avons utilisé la technique d'imagerie optique des signaux intrinsèques, qui permet de mesurer l'activité d'une surface de cortex en utilisant le signal BOLD (blood-oxygen-level dependent). Cette thèse s'articule sur trois axes : l'effet de l'apprentissage au niveau local, l'effet de l’apprentissage à l'échelle de l'aire cérébrale, et la modélisation de l’apprentissage. Dans la première partie, nous avons comparé les changements d’orientations des neurones en fonction du gradient d’orientation local. Ce gradient est fort quand deux neurones voisins ont des orientations très différentes, et faible quand leurs orientations sont semblables. Les résultats montrent que plus les neurones sont entourés de neurones aux orientations différentes, plus l'apprentissage change leur réponse à l’orientation. Ceci suggère que les connexions locales ont une influence déterminante sur l'ampleur de l’apprentissage. Dans la deuxième partie, nous avons comparé le changement d’orientation des neurones des aires 17 et 18 avant et après apprentissage. Les résultats ne sont pas notablement différents entre les aires 17 et 18. On peut toutefois noter que les changements d’orientations dans l’aire 18 ont des amplitudes plus variables que dans l’aire 17. Ceci peut provenir du fait que l’aire 18 reçoit des afférences plus variées que l’aire 17, notamment une afférence directe des cellules Y du CGLd (Corps Genouillé Latéral dorsal). Dans la troisième partie, nous avons modélisé l'apprentissage expérimentalement observé à l'aide de réseaux de neurones utilisant un apprentissage Hebbien (cartes auto-organisatrices). Nous avons montré que le « feedback » des aires supérieures vers le cortex visuel primaire était souhaitable pour la conservation de la sélectivité à l'orientation des neurones. De manière générale, cette thèse montre l'importance des connexions locales dans la plasticité neuronale. Notamment, elles garantissent un apprentissage homéostatique, c'est-à- dire conservant la représentativité des orientations au niveau du cortex. De manière complémentaire, elle montre également l’importance des aires supérieures dans le maintient à long terme des orientations apprises par les neurones lors de l'apprentissage.<br>In the cat primary visual cortex (areas 17 and 18), neurons responding to orientations in the environment (such as the outline of objects) are organized in columns perpendicular to the cortical surface. It was previously shown that a drastic change in orientations in the environment changes the response of neurons. For example, a neuron responding to a horizontal orientation will respond, after learning a new environment, to an oblique orientation. In this thesis, we seek to follow the changes of properties of large populations of neurons due to this type of learning. To this end, we used the intrinsic signals optical imaging technique, which measures the activity of a cortical surface using the BOLD (blood-oxygen-level dependent) signal. This thesis follows three axes: the effect of learning at the local level, the effect of learning at the visual area scale, and the modeling of learning. In the first part, we compared the changes in orientation of neurons according to the local gradient of orientation. This gradient is strong when two neighboring neurons have very different orientations, and weak when their orientations are similar. The obtained relation between the gradient and the magnitude of change in orientation shows that when neurons are increasingly surrounded by neurons with different orientations, they change their response to orientation to a greater extent. This suggests that local connections have a decisive influence on the extent of learning. In the second part, we followed the change in the orientation of neurons in the areas 17 and 18, before and after learning. The results are not significantly different between area 17 and area 18. However, it is noteworthy that orientation changes in area 18 are more variable in amplitude than in area 17. This may be because area 18 receives more diverse inputs than area 17, including a direct input from dLGN (dorsal Lateral Geniculate Nucleus) Y cells. In the third part, we modeled the experimentally observed learning with neural networks using a Hebbian learning rule (networks are self-organizing maps). We have shown that feedback from higher areas to the primary visual cortex was desirable for the neurons orientation selectivity conservation. Overall, this thesis shows the importance of local connections in neuronal plasticity. In particular, they guarantee a homeostatic learning, i.e. maintaining the representativeness of orientations in the cortex. In a complementary manner, it also shows the importance of the superior areas in the conservation of learned orientations.

Les neurones du cortex visuel primaire (aire 17) du chat adulte répondent de manière sélective à différentes propriétés d’une image comme l’orientation, le contraste ou la fréquence spatiale. Cette sélectivité se manifeste par une réponse sous forme de potentiels d’action dans les neurones visuels lors de la présentation d’une barre lumineuse de forme allongée dans les champs récepteurs de ces neurones. La fréquence spatiale (FS) se mesure en cycles par degré (cyc./deg.) et se définit par la quantité de barres lumineuses claires et sombres présentées à une distance précise des yeux. Par ailleurs, jusqu’à récemment, l’organisation corticale chez l’adulte était considérée immuable suite à la période critique post-natale. Or, lors de l'imposition d'un stimulus non préféré, nous avons observé un phénomène d'entrainement sous forme d'un déplacement de la courbe de sélectivité à la suite de l'imposition d'une FS non-préférée différente de la fréquence spatiale optimale du neurone. Une deuxième adaptation à la même FS non-préférée induit une réponse neuronale différente par rapport à la première imposition. Ce phénomène de "gain cortical" avait déjà été observé dans le cortex visuel primaire pour ce qui est de la sélectivité à l'orientation des barres lumineuses, mais non pour la fréquence spatiale. Une telle plasticité à court terme pourrait être le corrélat neuronal d'une modulation de la pondération relative du poids des afférences synaptiques.<br>Primary visual cortex neurons in adult cat are selective to different image properties as orientation, contrast and spatial frequency. This selectivity is characterized by action potentials as electrical activity from the visual neurons. This response occurs during the presentation of a luminous bar in the receptive fields of the neurons. Spatial frequency is the amount of luminous bars in a grating presented from a precise distance from the eyes and is measured in cycles per degree. Furthermore, it was establish until recently that cortical organisation in the adult remains inflexible following the critical period after birth. However, our results have revealed that spatial frequency selectivity is able to change after an imposition of a non-preferred spatial frequency, also called adapter. Following cortical activity recordings, there is a shift of the spatial frequency tuning curves in the direction of the adapter. A second adaptation at the same non-preferred spatial frequency produced a different neural response from the first adaptation. This “short-term plasticity” was already observed in the primary visual cortex for orientation selective neurons but not yet for spatial frequency. The results presented in this study suggest that such plasticity is possible and that visual neurons regulate their electrical responses through modulation of the weights of their synaptic afferences.