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1
Thulin, Nilsson Linnea. "The Role of Primary Visual Cortex in Visual Awareness." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-11623.
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Despite its great complexity, a great deal is known about the organization and information-processing properties of the visual system. However, the neural correlates of visual awareness are not yet understood. By studying patients with blindsight, the primary visual cortex (V1) has attracted a lot of attention recently. Although this brain area appears to be important for visual awareness, its exact role is still a matter of debate. Interactive models propose a direct role for V1 in generating visual awareness through recurrent processing. Hierarchal models instead propose that awareness is generated in later visual areas and that the role of V1 is limited to transmitting the necessary information to these areas. Interactive and hierarchical models make different predictions and the aim of this thesis is to review the evidence from lesions, perceptual suppression, and transcranial magnetic stimulation (TMS), along with data from internally generated visual awareness in dreams, hallucinations and imagery, this in order to see whether current evidence favor one type of model over the other. A review of the evidence suggests that feedback projections to V1 appear to be important in most cases for visual awareness to arise but it can arise even when V1 is absent.
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Hardingham, Neil Robert. "Synaptic connections in rat visual cortex." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325298.
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Fotheringhame, David K. "Temporal coding in primary visual cortex." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.339357.
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Nauhaus, Ian Michael. "Functional connectivity in primary visual cortex." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1692099811&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
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Peelen, Marius Vincent. "Body selectivity in human visual cortex." Thesis, Bangor University, 2006. https://research.bangor.ac.uk/portal/en/theses/body-selectivity-in-human-visual-cortex(4091f96c-dee2-42ec-9a32-c0a8cf17b288).html.
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Perceiving other people is a seemingly effortless process. Yet within a few hundred milliseconds we are aware of who we are looking at, what this person is doing, and even what this person feels. We derive this information from the form and motion of the face and body. Faces may be particularly important for some aspects of person perception (e. g., identity recognition), whereas bodies may be more important for others (e. g., action recognition). Furthermore, information from the body is important in cases where it is not possible to perceive the details of the face, for instance when the face is occluded, or when we see someone from a distance. In most cases, however, it is likely that information from both the face and the body are perceived in parallel and are integrated at an early stage. Previous research on person perception has mostly focused on the brain mechanisms underlying face perception. Much less research has focused on the brain mechanismsu nderlying body perception,w hich is the topic of this thesis. Using functional magnetic resonance imaging (fMRI) I provide evidence for a previously unknown body-selective visual area that overlaps a face-selective area. By employing novel analysis techniques that take into account patterns of activation across voxels I show that body- and face-selective areas can be functionally dissociated. Finally, I show that, in contrast to frontal and parietal action-recognition areas, visual body-selective areasd o not contain a dynamic representationo f observeda ctions. Together, thesef indings increaseo ur understandingo f the brain mechanismsu nderlying body, face and action perception, by showing both similarities and dissimilarities in the brain structures involved in these processes.
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Romo, Phillip Alfonso. "Visual processing in the higher cortices of the mammalian visual cortex." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/27311.
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Area 18 of the cat is the focus of this thesis as it a cortical area considered both primary visual cortex due to its direct LGN projections, but also an association visual cortex and homologue of the primate area V2. Visual cortical neurones are categorised as either simple or complex based on receptive field properties within a small, central excitatory region. But when stimuli are expanded beyond the confines of the central receptive field, a silent surround region is capable of playing a modulatory role on the centre response.
Chapter 1 provides some historical background regarding the visual cortex, properties of the neuronal populations and hypothesised models associated with the construction of receptive field.
Chapter 2 expands previous work from our laboratory in area 17 of the cat into area 18. In over 75% of cells in area 18 we observed to have a suppressive surround and exhibit tuning for orientation, contrast, spatial and temporal frequencies. Previously observed ‘simplification of complex cells’ (reduced phase sensitivity) in area 17 when receptive fields were co-stimulated with optimised surround stimuli was also present in area 18.
Chapter 3 expands the understanding of binocular cell responses and the extent of matching for centre and surround receptive fields in area 18. Centre receptive fields demonstrated excellent matching for phase-sensitivities and orientation. Conversely, there was weak interocular matching of the optimal temporal frequencies, the diameters of summation areas of the excitatory responses and suppression index.
In chapter 4, consistent with findings of area 17, we have observed silent surround which can be classified as suppressive, rebound, plateau and faciliatory. Exploring the ECRF in a subregion fashion we observed uniform suppressive ECRF in addition to heterogenous subregions capable of suppression and facilitation of the centre
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Bernard, Clémence Francoise. "Otx2-glycosaminoglycan interaction to regulate visual cortex plasticity." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066228/document.
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Pendant le développement postnatal du cortex cérébral visuel, l'homéoprotéine Otx2 est transférée préférentiellement dans les interneurones inhibiteurs à parvalbumine (cellules PV), induit leur maturation et régule la période critique de plasticité pour la dominance oculaire. Pendant cette période critique, les cellules PV sont progressivement entourées par une matrice extracellulaire riche en glycosaminoglycanes (GAGs), qui pourraient être impliqués dans la capture d'Otx2. Pour étudier comment l'interaction entre Otx2 et les GAGs à la surface des cellules PV régule la période critique, nous avons analysé une lignée de souris transgéniques Otx2-AA chez lesquelles cette interaction est perturbée. Ces souris présentent une spécificité réduite de l'Otx2 cortical pour les cellules PV et un retard dans l'ouverture et la fermeture de la période critique pour la dominance oculaire. Nous avons montré que la protéine Otx2 se lie aux chaines de chondroïtine sulfates à la surface des cellules PV et qu'elle a une forte affinité pour le chondroïtine sulfate CS-E. Chez l'adulte, le cortex est maintenu à l'état non plastique par un apport continuel d'Otx2. Afin de ré-ouvrir une fenêtre de plasticité chez l'adulte, nous avons développé deux modèles pour perturber le transfert d'Otx2 : un analogue synthétique de CS-E qui se lie à Otx2 et une souris knock-in inductible pour contrôler la sécrétion d'un anticorps simple chaine contre Otx2. Ces résultats confirment et précisent le rôle in vivo de l'interaction entre Otx2 et les GAGs, à la fois pour la mise en place des périodes critiques pendant le développement postnatal et pour le maintien de l'état non plastique du cortex chez l'adulteDuring postnatal development of the visual cerebral cortex, Otx2 homeoprotein is transferred preferentially into parvalbumin inhibitory interneurons (PV-cells), induces their maturation and regulates a critical period of plasticity for binocular vision. During the critical period, PV-cells are gradually enwrapped by perineuronal nets enriched in glycosaminoglycans (GAGs), which are likely involved in the capture of Otx2. To understand how Otx2 interacts with GAGs at the surface of PV-cells for critical period regulation, we have analyzed a transgenic Otx2-AA mouse line in which the interaction between Otx2 and GAGs is disrupted. These mice show a reduced specificity of cortical Otx2 for PV-cells with concomitant delayed onset and closure of critical period for ocular dominance. We have also identified that Otx2 protein binds chondroitin sulfate chains of the perineuronal nets and that it has a high affinity for the chondroitin sulfate CS-E. We have therefore developed a sugar-ase protection assay for identifying specific glycan sequences involved in homeoprotein recognition. Throughout adulthood, the cortex receives Otx2 to maintain a consolidated, non-plastic state. To interfere with Otx2 transfer in the adult and reopen a window of plasticity, we have developed two models: a synthetic hexasaccharide analogue of CS-E that binds to Otx2 and an inducible, knock-in mouse allowing spatio-temporal control of a secreted single chain antibody against Otx2. All these results confirm and clarify the in vivo role for Otx2-GAG interaction, both in the timing of critical periods during postnatal development and in the maintenance of the non-plastic state of the cortex in the adult
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Krug, Kristine. "Ordering geniculate input into primary visual cortex." Thesis, University of Oxford, 1997. https://ora.ox.ac.uk/objects/uuid:b342ffae-4a31-4171-94a6-83cb516e83fe.
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Precise point-to-point connectivity is the basis of ordered maps of the visual field in the brain. One point in the visual field is represented at one locus in the dLGN and one locus in primary visual cortex. A fundamental problem in the development of most sensory systems is the creation of the topographic projections which underlie these maps. Mechanisms ranging from ordered ingrowth of fibres, through chemical guidance of axons to sculpting of the map from an early exuberant input have been proposed. However, we know little about how ordered maps are created beyond the first relay. What we do know is that a topological mismatch requires the exchange of neighbours in the geniculo-cortical projection and that manipulating the input to the primary relay can affect the geniculo-cortical topography. Taking advantage of the immaturity of the newborn hamsterâs visual system, I studied the generation of an ordered map in primary visual cortex during the time of target innervation in normal and manipulated animals. I also investigated the patterning of neuronal activity prior to natural eye-opening. Paired injections of retrograde fluorescent tracers into visual cortex reveal that geniculate fibres are highly disordered at the time of invasion of the cortical plate. Topography in the geniculo-cortical projection emerges out of an unordered projection to area 17 in the first postnatal week. Furthermore, I show that manipulating the peripheral input can alter the topographic map which arises out of the early scatter. Removal of one eye at birth appears to slow the process of geniculo-cortical map formation ipsilateral to the remaining eye and at the end of the second postnatal week, a double projection between thalamus and cortex has formed. If retinal activity is blocked during this time, this double projection does not emerge. The results implicate retinal activity as the signal that induces the development of a different topographic order in the geniculo-cortical projection. It is generally believed that visual experience can influence development only after eye-opening. However, the final part of my thesis shows that neurons in the developing visual cortex of the ferret can not only be visually driven at least 10 days before natural eye-opening, but are also selective for differently oriented gratings presented through the closed eye-lid. Thus, visually-driven neuronal activity could influence development much earlier than previously assumed in many developmental studies.
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Woodbury, Greg. "Modelling Emergent Properties of the Visual Cortex." University of Sydney. School of Mathematics and Statistics, 2003. http://hdl.handle.net/2123/695.
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Nicoll, A. J. "Excitatory synaptic connections in the visual cortex." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303635.
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Berman, Neil Jonathan. "Aspects of inhibition in the visual cortex." Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303871.
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Ramachandran, Suchitra. "Visual Statistical Learning in Monkey Inferotemporal Cortex." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/463.
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Despite living in noisy sensory environments, humans and non-human primates have the ability to learn regularities and patterns in the environment solely on the basis of passive exposure. This ability to learn what is statistically likely and predictable in the environment is called statistical learning. Visual statistical learning of image sequences has been demonstrated at the level of single neurons in the rhesus macaque (monkey) inferotemporal cortex (IT). Upon subjecting monkeys to extensive exposure to pairs of images presented sequentially such that the display of one image always predicted the subsequent display of another image, IT neurons showed suppressed responses to images that occurred in a predicted context, but not when the same effect, called prediction suppression, more thoroughly, we discovered that this effect depends on the conditional probability between the images presented sequentially. Further, the effect generalizes across time and space, it is domain specific, and it can be induced by training monkeys on longer sequences. These effects are long-lasting and robust: they persist at least for 20 months after initial training with no exposure to the stimuli in the interim. We have preliminary evidence for the existence of neurophysiological markers of statistical learning in areas upstream of IT in the ventral visual stream, suggesting that learning statistical regularities may be a fundamental function of sensory cortex. images occurred in an unpredicted context (Meyer & Olson, 2011). Upon investigating this effect, called prediction suppression, more thoroughly, we discovered that this effect depends on the conditional probability between the images presented sequentially. Further, the effect generalizes across time and space, it is domain specific, and it can be induced by training monkeys on longer sequences. These effects are long-lasting and robust: they persist at least for 20 months after initial training with no exposure to the stimuli in the interim. We have preliminary evidence for the existence of neurophysiological markers of statistical learning in areas upstream of IT in the ventral visual stream, suggesting that learning statistical regularities may be a fundamental function of sensory cortex.
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Lawrence, Samuel. "Global shape processing in human visual cortex." Thesis, University of York, 2016. http://etheses.whiterose.ac.uk/16448/.
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The research described in this thesis used a combination of neuroimaging, brain stimulation and psychophysical methods to explore the representation of global shape in human visual cortex. Global shape processing mechanisms integrate over local orientation information to form an abstracted representation of an object’s shape; an important processing step for accurate object recognition in the complex visual scenes of everyday life. This thesis presents evidence for a global shape processing stream in human lateral occipital cortex comprising brain areas LO1, LO2 and object-selective lateral occipital complex (LOC). First, brain responses to shape were shown to be more global and less dependent on task in LO2 compared to LO1. Second, a global shape aftereffect was used to demonstrate that global representations of object shape are formed by a series of integrative mechanisms, where each successive mechanism integrates over outputs from the preceding mechanisms to form increasingly global shape representations. Third, brain stimulation was used to determine whether area LO2 is causally important for global shape adaptation and shape discriminations, however brain stimulation had no effect on shape perceptions meaning conclusions about a causal role for LO2 in global shape processing could not be drawn. Finally, neural tuning to radial frequency, one possible dimension of a representational shape space, was modelled using Gaussian neural modelling. Tuning towards radial frequencies that are processed globally was localised to lateral occipital cortex, and shifted from local to global frequencies in LO2 and LOC. Overall, this thesis provides novel contributions to the current understanding of how the analysis of an object’s shape facilitates object recognition, and the nature and locus of global shape representations in the human brain.
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Hesam, Shariati Nastaran. "A functional model for primary visual cortex." Thesis, The University of Sydney, 2012. http://hdl.handle.net/2123/8753.
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Many neurons in mammalian primary visual cortex have properties such as sharp tuning for contour orientation, strong selectivity for motion direction, and insensitivity to stimulus polarity, that are not shared with their sub-cortical counterparts. Successful models have been developed for a number of these properties but in one case, direction selectivity, there is no consensus about underlying mechanisms. This thesis describes a model that accounts for many of the empirical observations concerning direction selectivity. The model comprises a single column of cat primary visual cortex and a series of processing stages. Each neuron in the first cortical stage receives input from a small number of on-centre and off-centre relay cells in the lateral geniculate nucleus. Consistent with recent physiological evidence, the off-centre inputs to cortex precede the on-centre inputs by a small interval (~4 ms), and it is this difference that confers direction selectivity on model neurons. I show that the resulting model successfully matches the following empirical data: the proportion of cells that are direction selective; tilted spatiotemporal receptive fields; phase advance in the response to a stationary contrast-reversing grating stepped across the receptive field. The model also accounts for several other fundamental properties. Receptive fields have elongated subregions, orientation selectivity is strong, and the distribution of orientation tuning bandwidth across neurons is similar to that seen in the laboratory. Finally, neurons in the first stage have properties corresponding to simple cells, and more complex-like cells emerge in later stages. The results therefore show that a simple feed-forward model can account for a number of the fundamental properties of primary visual cortex.
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Mohamed, Abdelhack. "Top-down Modulation in Human Visual Cortex." Kyoto University, 2019. http://hdl.handle.net/2433/242434.
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Montobbio, Noemi <1992>. "A metric model of the visual cortex." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amsdottorato.unibo.it/9101/1/montobbio_noemi_tesi.pdf.
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The purpose of this thesis is the development of a model for the geometry of the connectivity of the primary visual cortex (V1), by means of functional analysis tools on metric measure spaces. The metric structure proposed to describe the internal connections of V1 implements a notion of correlation between neurons, based on their feature selectivity: this is expressed through a connectivity kernel that is directly induced by the local feature analysis performed by the cells. Such kernel carries a geometrical structure consistent with the well-known properties of long-range horizontal connections in V1, and it is compatible with the perceptual rules synthesized by the concept of association field. Moreover, its construction can be applied to banks of filters not necessarily obtained through a group representation, and possibly only numerically known. This model is then applied to insert biologically inspired connections in deep learning algorithms, to enhance their ability to perform pattern completion in image classification tasks. The main novelty in our approach lies in its ability to recover global geometric properties of the functional architecture of V1 without imposing any parameterization or invariance, but rather by exploiting the local information naturally encoded in the behavior of single V1 neurons in presence of a visual stimulus.
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Duffy, Kevin R. "The maturation and experience-dependent plasticity of the developing visual cortex /." *McMaster only, 2001.
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Rudiger, Philipp John Frederic. "Development and encoding of visual statistics in the primary visual cortex." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/25469.
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How do circuits in the mammalian cerebral cortex encode properties of the sensory environment in a way that can drive adaptive behavior? This question is fundamental to neuroscience, but it has been very difficult to approach directly. Various computational and theoretical models can explain a wide range of phenomena observed in the primary visual cortex (V1), including the anatomical organization of its circuits, the development of functional properties like orientation tuning, and behavioral effects like surround modulation. However, so far no model has been able to bridge these levels of description to explain how the machinery that develops directly affects behavior. Bridging these levels is important, because phenomena at any one specific level can have many possible explanations, but there are far fewer possibilities to consider once all of the available evidence is taken into account. In this thesis we integrate the information gleaned about cortical development, circuit and cell-type specific interactions, and anatomical, behavioral and electrophysiological measurements, to develop a computational model of V1 that is constrained enough to make predictions across multiple levels of description. Through a series of models incorporating increasing levels of biophysical detail and becoming increasingly better constrained, we are able to make detailed predictions for the types of mechanistic interactions required for robust development of cortical maps that have a realistic anatomical organization, and thereby gain insight into the computations performed by the primary visual cortex. The initial models focus on how existing anatomical and electrophysiological knowledge can be integrated into previously abstract models to give a well-grounded and highly constrained account of the emergence of pattern-specific tuning in the primary visual cortex. More detailed models then address the interactions between specific excitatory and inhibitory cell classes in V1, and what role each cell type may play during development and function. Finally, we demonstrate how these cell classes come together to form a circuit that gives rise not only to robust development but also the development of realistic lateral connectivity patterns. Crucially, these patterns reflect the statistics of the visual environment to which the model was exposed during development. This property allows us to explore how the model is able to capture higher-order information about the environment and use that information to optimize neural coding and aid the processing of complex visual tasks. Using this model we can make a number of very specific predictions about the mechanistic workings of the brain. Specifically, the model predicts a crucial role of parvalbumin-expressing interneurons in robust development and divisive normalization, while it implicates somatostatin immunoreactive neurons in mediating longer range and feature-selective suppression. The model also makes predictions about the role of these cell classes in efficient neural coding and under what conditions the model fails to organize. In particular, we show that a tight coupling of activity between the principal excitatory population and the parvalbumin population is central to robust and stable responses and organization, which may have implications for a variety of diseases where parvalbumin interneuron function is impaired, such as schizophrenia and autism. Further the model explains the switch from facilitatory to suppressive surround modulation effects as a simple by-product of the facilitating response function of long-range excitatory connections targeting a specialized class of inhibitory interneurons. Finally, the model allows us to make predictions about the statistics that are encoded in the extensive network of long-range intra-areal connectivity in V1, suggesting that even V1 can capture high-level statistical dependencies in the visual environment. The final model represents a comprehensive and well constrained model of the primary visual cortex, which for the first time can relate the physiological properties of individual cell classes to their role in development, learning and function. While the model is specifically tuned for V1, all mechanisms introduced are completely general, and can be used as a general cortical model, useful for studying phenomena across the visual cortex and even the cortex as a whole. This work is also highly relevant for clinical neuroscience, as the cell types studied here have been implicated in neurological disorders as wide ranging as autism, schizophrenia and Parkinson’s disease.
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de, Haas B. "Contextual modulations of visual perception and visual cortex activity in humans." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1435556/.
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Visual perception and neural processing depend on more than retinal stimulation alone. They are modulated by contextual factors like cross-modal input, the current focus of attention or previous experience. In this thesis I investigate ways in which these factors affect vision. A first series of experiments investigates how co-occurring sounds modulate vision, with an emphasis on temporal aspects of visual processing. In three behavioral experiments I find that participants are unable to ignore the duration of co-occurring sounds when giving visual duration judgments. Furthermore, prolonged sound duration goes along with improved detection sensitivity for visual stimuli and thus extends beyond duration judgments per se. I go on to test a cross-modal illusion in which the perceived number of flashes in a rapid series is affected by the number of co-occurring beeps (the sound-Induced flash illusion). Combining data from structural magnetic resonance imaging (MRI) and a behavioral experiment I find that individual proneness to this illusion is linked with less grey matter volume in early visual cortex. Finally, I test how co-occurring sounds affect the cortical representation of more natural visual stimuli. A functional MRI (fMRI) experiment investigates patterns of activation evoked by short video clips in visual areas V1-3. The trial-by-trial reliability of such patterns is reduced for videos accompanied by mismatching sounds. Turning from cross-modal effects to more intrinsic sources of contextual modulation I test how attention affects visual representations in V1-3. Using fMRI and population receptive field (pRF) mapping I find that high perceptual load at fixation renders spatial tuning for the surrounding visual field coarser and goes along with pRFs being radially repelled. In a final behavioral and fMRI experiment I find that the perception of face features is modulated by retinal stimulus location. Eye and mouth stimuli are recognized better, and evoke more discriminable patterns of activation in face sensitive patches of cortex, when they are presented at canonical locations. Taken together, these experiments underscore the importance of contextual modulation for vision, reveal some previously unknown such factors and point to possible neural mechanisms underlying them. Finally, they argue for an understanding of vision as a process using all available cues to arrive at optimal estimates for the causes of sensory events.
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De, Pasquale Roberto. "Visual discrimination learning and LTP-like changes in primary visual cortex." Doctoral thesis, Scuola Normale Superiore, 2009. http://hdl.handle.net/11384/85939.
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Brady, Mark James. "Psychophysical investigations of incomplete forms and forms with background /." Diss., ON-CAMPUS Access For University of Minnesota, Twin Cities Click on "Connect to Digital Dissertations", 1999. http://www.lib.umn.edu/articles/proquest.phtml.
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Bartolucci, Marco. "Attentional modulations in the visual cortex in the absence of visual stimulation." Thesis, Royal Holloway, University of London, 2012. http://repository.royalholloway.ac.uk/items/5594dbe3-8d95-44e6-bda6-f0b0a37bfabe/1/.
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Every day we perceive visual scenes filled with different stimuli. Visual attention allows us to select the information that is most relevant to ongoing behaviour. The aim of this thesis is to explore how top-down modulations of activity in the human visual cortex affect perception and how attention interacts with visual processing in the brain. Specifically, we investigate the role of the modulation that occurs after a cue to attend but before onset of a visual stimulus, referred to in the literature as pre-stimulus attentional modulation, using fMRI methods alongside behavioural measurements. The main focus of the first three experiments is on the interactions between pre-stimulus attentional modulation and modulation by attention of the stimulus-evoked response. Results overall suggest that pre-stimulus activity is correlated with the effects of attention on the stimulus-evoked response and that the two attentional effects may therefore reflect a single process. The aim of the fourth experiment is to study the interaction of spatial and feature-based attention, and the results suggest that when both are engaged together, visual cortical areas do not benefit in an additive way, suggesting either that one dominates or that attentional resources saturate. The fifth experiment investigates the interaction of pre-stimulus activity with the speed and accuracy of saccade movements, and the results suggest no relation between those two processes. Finally the last two experiments focus on the role of pre-stimulus attentional modulation in perceptual learning, and the results strongly suggest that attentional modulation is involved in this process. Based on the results of these experiments, the role of pre- stimulus attentional modulation in visual processing is discussed.
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CONVENTO, SILVIA. "The “multisensory” visual cortex: crossmodal shaping of visual cortical responses and perception." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/68621.
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The convergence and integration of information from the different sensory channels represents a fundamental ability of the human brain: in our daily life, multisensory cues impact our sensory system, shaping our perception of sensory events. Classical models of multisensory perception defer integration until sensory-specific information has been extensively processed. Strikingly, several anatomical studies now suggest that this view may be over-simplistic and that the substrate for multisensory integration is not constrained to the classical area of multisensory convergence; rather, it also occurs in the early stages of sensory processing, rising the intriguing hypothesis that most of the brain, including the primary sensory cortices, is essentially multisensory.
The present dissertation inquires the causal involvement of classical ‘sensory-specific’ visual areas in multisensory processing. Using a combination of behavioral, neuromodulatory, and neuropsychological evidence, I seek the behavioral and brain signatures of a causal link between visual cortical excitability and multisensory perception. In parallel, I provide a characterization of the impact of distinct crossmodal stimuli on subjective visual experience.
By directly measuring visual cortical excitability via Transcranial Magnetic Stimulation (TMS), the first study shows facilitatory effects by spatially-specific bimodal and trimodal stimuli on visual cortical responses, which, in turn, improve visual perception. Moreover, by using Transcranial Direct Current Stimulation (tDCS), I demonstrate the role played by higher order multisensory cortices in mediating such spatially-specific crossmodal influences on visual perception, reporting the presence of regional preferences for auditory or somatosensory influences on visual responses.
In the second experiment, I further extend these findings by showing that multisensory influences on vision not only express themselves through an enhancement of visual perception, but they can also provoke phenomenological changes in conscious visual perception, namely a crossmodal illusion, when incongruent auditory cues are provided. Crossmodal illusory effects show a specific time-course, compatible with the occurrence of early visual-auditory interaction in the primary visual cortex. At complement with evidence in the healthy brain, in the third study I investigate how a well-known crossmodal illusion, the Sound-Induced Flash Illusion (SIFI), is processed by brain-damaged patients with visual field defect (with damage to the primary visual cortex, the sensory visual pathways, or both), and unilateral spatial neglect (with damage to the posterior parietal and fronto-temporal regions). Perception of the SIFI is defective in patients with visual field defects, but not in those with unilateral spatial neglect, further supporting the role of low-level visual areas in integrating multisensory cues.
Overall, this set of experiments shows a causal link between the crossmodal modulation of visual perception and the activity of the primary visual areas, which represents a key site for multisensory integration.
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Jadauji, Jahan. "Modulation of olfactory processing by visual cortex stimulation." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=106393.
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In order to view the world in a unified manner, information from the different senses must combine at some point in the sensory stream. This is known as perceptual binding and has led to the study of how various senses interact, termed multisensory integration. An intriguing example of a crossmodal interaction is the finding from various imaging studies that primary visual cortex is activated while subjects performed purely olfactory tasks. This is in line with the literature documenting a connection between vision and olfaction, but whether visual cortical activity and olfactory perception are connected causally is unknown. In this thesis I will investigate the connection between vision and olfaction using Transcranial Magnetic Stimulation (TMS). TMS is a non-invasive method of stimulating cortex via magnetic induction. The present research involved the application of TMS to early visual cortex, including V1, bilaterally in the context of experiments that test both visual and olfactory perception. In particular subjects were tested on a visual task (contrast detection) and two olfactory tasks that probe the ability to discriminate odor intensity and quality. Behavioral experiments were carried out before and after the application of either no TMS, real TMS to V1, sham TMS to V1 (replicates experimental conditions of real TMS but no current is produced in the cortex) and real TMS to primary auditory cortex. The results have revealed a significant improvement in performance on the visual task, replicating previous data. Interestingly, improvements in the ability of subjects to discriminate among odor qualities following TMS of V1 were also found, with a tendency for female subjects to show more improvement than their male counterparts. Similar improvements were not found in the ability to discriminate among odor intensities or on either olfactory task in any of the control conditions (no TMS or sham TMS or auditory cortex TMS). Implications and limitations of the present results are discussed.Afin de voir le monde d'une manière unifiée, les informations provenant des sens différents doivent combiner à un certain point dans le flux sensoriel. Ceci est connu comme la combinaison perceptuelle et a conduit à l'étude de la façon dont interagissent les différents sens, appelé intégration multisensorielle. Un exemple fascinant d'une interaction intermodale est la conclusion à partir des différents études d'imagerie que le cortex visuel primaire est activé alors que les sujets ont exécuté des tâches purement olfactif. Ceci est en accord avec la littérature documentant une connexion entre la vision et l'olfaction, mais si l'activité corticale visuelle et la perception olfactive sont connectés causalement est inconnue. Dans cette thèse, je vais étudier le lien entre la vision et l'olfaction en utilisant la stimulation magnétique transcrânienne (TMS). TMS est une méthode non invasive de stimulation du cortex via l'induction magnétique. La présente recherche concernait l'application de TMS au cortex visuel, y compris V1, bilatéralement dans le contexte des expériences qui testent à la fois la perception visuelle et olfactive. En particulier les sujets ont été testés sur une tâche visuelle (détection de contraste) et deux tâches olfactives qui sondent la capacité à discriminer l'intensité d'odeur et de qualité. Les expériences comportementales ont été réalisées avant et après l'application soit pas TMS, le TMS réelles à V1, faux TMS à V1 (réplique les conditions expérimentales de TMS réel, mais pas de courant est produit dans le cortex) et TMS réelles à cortex auditif primaire. Les résultats ont révélé une amélioration significant des performances sur la tâche visuelle, qui réplique des données précédentes. L'amélioration de la capacité des sujets à discriminer parmi les qualités d'odeurs suivantes TMS de V1 ont également été trouvés, avec une tendance pour les sujets féminins à montrer une amélioration plus que leurs homologues masculins. Des améliorations similaires n'ont pas été trouvées dans la capacité à discriminer entre les intensités d'odeur ou de chaque tâche olfactive dans l'une des conditions de contrôle (pas de TMS ou faux TMS ou le TMS du cortex auditif). Les implications et les limites des résultats actuels sont discutés.
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Gharat, Amol. "Motion-defined contour processing in early visual cortex." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=106530.
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From our daily experience it is very clear that relative motion cues can contribute to correctly identifying object boundaries and for perceiving depth. Motion-defined contours are not only generated by the motion of objects in a scene, but also by the movement of an observer's head and body. However the neural mechanism involved in detecting these contours is still unknown. To explore this mechanism, I extracellularly recorded responses of neurons in Area 18 of anesthetized and paralyzed cats while they were presented with visual stimuli. The goal of this study was to determine if neurons in Area 18 that have been previously shown to detect luminance, texture- and contrast-defined contours cue-invariantly could also detect motion-defined contours. Motion-defined contour stimuli were generated by modulating the velocity of high spatial frequency sinusoidal luminance gratings (carrier gratings) by a squarewave envelope. The carrier gratings used were outside the luminance passband of a neuron, such that presence of carrier alone within the receptive field of a neuron did not elicit a response. It was found that most of the neurons in Area 18 that responded to contrast-defined contours also respond to motion-defined contours. The orientation and direction selectivity of these neurons for motion-defined contours was similar to that of luminance gratings. A given neuron also exhibited similar selectivity for the spatial frequency of the carrier grating of contrast- and motion-defined contours. These results suggest that Area 18 is a common brain area where different second-order contours are detected in a form-cue invariant manner, through a common neural mechanism.Au quotidien, il est clair que les indices locaux de mouvement relatif contribuent à l'identification des bords des objets et à la perception de la profondeur. Les contours définis par le mouvement ne sont pas seulement générés par le mouvement des objets dans une scène, mais également par le mouvement de la tête et du corps de l'observateur. Cependant, les mécanismes neuronaux impliqués dans la détection de ces contours restent toujours inconnus. Pour étudier ces mécanismes, j'ai effectué des enregistrements électrophysologiques extracellulaires dans l'aire 18 de chats anesthésiés et paralysés pendant que des stimuli visuels leurs étaient présentés. Le but de cette étude était de déterminer si les neurones de l'aire 18 pour lesquels il a été montré qu'ils détectent indifféremment les contours définis par la luminance, la texture ou le contraste peuvent aussi détecter les contours définis par le mouvement. Les stimuli de contours définis par le mouvement étaient générés en modulant la vitesse de réseaux de luminances sinusoïdaux de haute fréquence spatiale (réseau porteur) par une enveloppe en créneau. Les réseaux porteurs utilisés étaient au-delà de la bande passante de luminance des neurones de façon à ce que la présentation du réseau porteur seul dans le champ récepteur d'un neurone ne génère pas de réponse. Il a alors été observé que la plupart des neurones de l'aire 18 qui répondent aux contours définis par le contraste répondent également aux contours définis par le mouvement. Les sélectivités à l'orientation et à la direction des contours définis par le mouvement de ces neurones étaient similaires à celles des réseaux de luminance. Un neurone donné présentait également la même sélectivité à la fréquence spatiale du réseau porteur pour les contours définis par le contraste et le mouvement. Ces résultats suggèrent que l'aire 18 est une aire d'intégration où différents contours de second-ordre sont détectés par un mécanisme commun, indépendamment de la nature des indices locaux.
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Jeong, Su Keun. "Flexible visual information representation in human parietal cortex." Thesis, Harvard University, 2014. http://nrs.harvard.edu/urn-3:HUL.InstRepos:13068539.
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In many everyday activities, we must visually process multiple objects embedded in complex real world scenes. Our visual system can flexibly extract behaviorally relevant visual information from such scenes, even though it has a severely limited processing capacity. This dissertation proposes that human superior intra-parietal sulcus (IPS) plays a central role in this flexible visual information processing. In Chapter 1, using functional magnetic resonance imaging (fMRI) with univariate analysis, I found that distractor processing in superior IPS was attenuated when target locations were known in advance. In Chapter 2, using multi-voxel pattern analysis (MVPA), I showed that superior IPS encoded object shapes, but only when such information was required by task. In Chapter 3, I showed that, given a set of perceptually distinct, but semantically grouped visual inputs, superior IPS could represent abstract object identity. The neural similarity of identities in superior IPS significantly correlated with perceived similarity between identities, confirming the representation in this region indeed reflected identity. Taken together, these results suggest that human superior IPS encodes a wide range of visual information, from simple features to abstract identities, in a task-dependent manner, enabling flexible goal-directed visual information processing in the human brain.Psychology
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Mineault, Patrick. "Parametric modelling of visual cortex at multiple scales." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=123020.
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The visual system is confronted with the daunting task of extracting behaviourally relevant visual information from noisy and ambiguous patterns of luminance falling on the retina. It solves this problem through a hierarchical architecture, in which the visual stimulus is iteratively re-encoded into ever more abstract representations which can drive behaviour. This thesis explores the question of how the computations performed by neurons in the visual hierarchy create behaviourally relevant representations. This question requires probing the visual system at multiple scales: computation is the role of single neurons and ensembles of neurons; representation is the function of multiple neurons within an area; hierarchical processing is an emergent process which involves multiple areas; and behaviour is defined at the full scale of the system, the psychophysical observer. To study visual processing at multiple scales, I propose to develop and apply parametric modelling methods in the context of systems identification. Systems identification seeks to establish the deterministic relationship between the input and the output of a system. Systems identification has proven particularly useful in the study of visual processing, where the input to the system can be easily controlled via sensory stimulation.Parametric modeling, built on the theory of Generalized Linear Models (GLMs), furnishes a common framework to analyze signals with different statistical properties which occur in the analysis of neural systems: spike trains, multi-unit activity, local field potentials and psychophysical decisions.In Chapter 2, I develop the parametric modeling framework which is used throughout this thesis in the context of psychophysical classification images. Results show that parametric modeling can infer a psychophysical observer's decision process with fewer trials than previously proposed methods. This allows the exploration of more complex, and potentially more informative, models of decision processes while retaining statistical tractability.In Chapter 3, I extend and apply this framework to the analysis of visual representations at the level of neuronal ensembles in area V4. The results show that it is possible to infer, from multi-unit activity and local field potential (LFP) signals, the representation of visual space at a fine-grained scale over several millimeters of cortex. Analysis of the estimated visual representations reveals that LFPs reflect both local sources of input and global biases in visual representation. These results resolve a persistent puzzle in the literature regarding the spatial reach of the local field potential.In Chapter 4, I extend and apply the same framework to the analysis of single-neuron responses in area MST of the dorsal visual stream. Results reveal that MST responses can be explained by the integration of their afferent input from area MT, provided that this integration is nonlinear. Estimated models reveal long suspected, but previously unconfirmed receptive field organization in MST neurons that allow them to respond to complex optic flow patterns. This receptive field organization and nonlinear integration allows more accurate estimation of the velocity of approaching objects from the population of MST neurons, thus revealing their possible functional role in vergence control and object motion estimation.Put together, these results demonstrate that with powerful statistical methods, it is possible to infer the nature of visual representations at multiple scales. In the discussion, I show how these results may be expanded to gain a better understanding of hierarchical visual processing at large.Le système visuel est confronté à la difficile tâche d'extraire de l'information utile au comportement à partir de motifs complexes et ambigus détectés par la rétine. Il résout ce problème grâce à une architecture hiérarchique, dans laquelle le stimulus visuel est itérativement ré-encodé dans une représentation abstraite. Ce mémoire explore la question suivante : comment les computations performées par des neurones de la hiérarchie visuelle créent-elles des représentations permettant des comportements complexes?Cette question nécessite l'étude du système visuel à plusieurs échelles : la computation est le rôle de neurones et d'ensembles de neurones; la représentation est une fonction des neurones dans une aire du cerveau; la hiérarchie émerge de la communication entre de multiples aires du cerveau; et le comportement est défini à l'échelle du système visuel complet, l'observateur psychophysique.Afin d'étudier le système visuel à de multiple échelles, je développe et applique des méthodes de modélisation paramétrique dans le cadre de l'identification de système. Celle-ci a pour but d'établir la relation déterministe entre l'entrée d'un système et sa sortie. L'identification de système est particulièrement utile dans l'étude de la vision, où l'entrée du système peut être facilement contrôlée par stimulation sensorielle.La modélisation paramétrique, bâtie sur la théorie des modèles linéaires généralisés, offre un paradigme commun pour analyser des signaux ayant des propriétés statistiques disparates, souvent rencontrés dans l'étude du système nerveux: les potentiels d'action, l'activité d'ensemble de neurones, et les décisions psychophysiques.Dans le 2ème chapitre, je développe le paradigme d'analyse par modélisation paramétrique qui sera utilisé tout au long de ce mémoire dans le contexte des images de classification psychophysiques. Je démontre qu'il est possible d'inférer, grâce à ces méthodes, le processus décisionnel d'un observateur psychophysique avec moins de données que ce qui était précédemment possible. Cette avancée permet l'exploration de modèles psychophysiques plus complexes, et potentiellement plus informatifs sur le processus décisionnel de l'observateur.Dans le 3ème chapitre, j'applique ce paradigme à l'analyse des représentations visuelles au niveau d'ensembles neuronaux dans l'aire V4 du système visuel. Les résultats démontrent qu'il est possible, à partir de l'activité des champs de potentiel locaux (CPL), d'inférer la représentation corticale de l'espace visuel sur une échelle de plusieurs millimètres. Je démontre ainsi que les CPL reflètent à la fois des sources synaptiques locales et des biais globaux dans la représentation visuelle. Ces résultats résolvent une controverse dans la littérature concernant l'intégration spatiale des CPL.Dans le 4ème chapitre, j'applique ce même paradigme dans l'analyse de neurones dans l'aire MST du système visuel dorsal. Je révèle que les réponses dans MST peuvent être expliquées par l'intégration de sources afférentes provenant de l'aire MT; cependant, cette intégration se révèle nonlinéaire. Cette analyse révèle des propriétés longtemps soupçonnées mais jusqu'ici non confirmées des champs réceptifs des neurones dans MST; celles-ci leur permettent de communiquer de l'information sur les motifs de flux optique complexes. Cette organisation des champs réceptifs et l'intégration nonlinéaire permet d'extraire plus facilement la vélocité d'objets s'approchant de l'observateur à partir des réponses de la population de neurones dans MST, révélant un rôle insoupçonné de ces neurones dans l'estimation de la vélocité des objets.Pris ensemble, ces résultats démontrent qu'à l'aide de méthodes statistiques puissantes, il est possible d'inférer la nature des représentations visuelles à de multiples échelles. Dans la discussion, je démontre comment généraliser ces résultats afin d'obtenir une meilleure compréhension des computations hiérarchiques dans le système visuel.
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Coggan, David. "The neural representation of objects in visual cortex." Thesis, University of York, 2019. http://etheses.whiterose.ac.uk/22899/.
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Neuroimaging studies have shown that different categories of object evoke different neural responses in the ventral visual pathway. This has been interpreted to suggest that these regions represent high-level conceptual or semantic properties of the stimulus, such as its category. However, images from different categories differ in low-level visual properties. Therefore, the extent to which category-specific neural responses indicate high-level or low-level representations is unclear. This thesis investigates the extent to which low-level properties of objects are important in the neural response of ventral visual pathway. The first study uses a data-driven approach to select clusters of objects based on the similarity of their low-level visual properties. These visually defined clusters did not correspond to typical object categories, but still evoked distinct patterns of response in the ventral stream. The second and third studies show category-specific patterns of response in the ventral stream to scrambled objects that are not recognizable, but nevertheless retain many of their low-level visual properties. The fourth study reveals that the bias toward natural object images found in the ventral stream begins to emerge in early visual areas. The final chapter shows that category-specific patterns of EEG response can be also explained by low-level image properties. Taken together, these results demonstrate the importance of low-level visual properties in the neural representation of objects. These findings suggest that the category-selectivity observed in high-level visual regions can be explained by a distributed organization based around more basic properties of the stimulus.
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Cadieu, Charles Fredrick. "Modeling shape representation in visual cortex area V4." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/30367.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 85-89).
Visual processing in biological systems is classically described as a hierarchy of increasingly sophisticated representations, originating in primary visual cortex (V1), progressing through intermediate area V4, and ascending to inferotemporal cortex. The computational mechanisms that produce representations in intermediate area V4 have remained a mystery. In this thesis I show that the standard model, a quantitative model which extends the classical description of visual processing, provides a computational mechanism capable of reproducing and predicting the responses of neurons in area V4 with a translation invariant combination of V1 responses. Using techniques I have developed, model neurons accurately predict the responses of 8 V4 neurons to within-class stimuli, such as closed contours and gratings, and achieve an average correlation coefficient of 0.77 between predicted responses and measured V4 responses. Furthermore, model neurons fit to a V4 neuron's grating stimulus response, can qualitatively predict the V4 neuron's 2-spot reverse correlation map. These results successfully demonstrate the first attempt to bridge V1 and V4 experimental data, by describing how representation in V4 could emerge from the nonlinear combination of V1 neural responses.
by Charles Fredrick Cadieu.
M.Eng.
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Pisauro, M. A. "Imaging haemodynamic activity in the mouse visual cortex." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1452981/.
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Neurovascular coupling, the relationship between neural and haemodynamic activity, is not a fixed property of the brain. Physiological, behavioural and cognitive factors can strongly modulate the degree to which haemodynamic responses to perceptual stimuli reflect co-localized neural responses. Moreover, a significant part of the haemodynamic activity is not directly coupled with the spiking activity. Here we show how anaesthesia can influence the relationship between haemodynamic and neural activity and how the former can be expressed as the sum of two components: one which is well coupled with neuronal responses and the other which seem to be independent of them and which correlates with alertness. We used wide-field optical imaging of intrinsic signals in mouse primary visual cortex (V1). Haemodynamic responses could be used to obtain clear maps of retinotopy in both anaesthetized and awake mice. However, when the mice were awake, responses were four times larger and twice as fast compared to when they were anaesthetized. By measuring neural responses we could establish that the effects of anaesthesia on haemodynamic responses were due to changes in neurovascular coupling. By activating V1 via optogenetics, we replicated the effects of anaesthesia in terms of delay of the response but not of amplitude. We then asked whether haemodynamic activity can all be explained in terms of local neural activity. By imposing a precise spatiotemporal pattern of neural responses in visual cortex we were able to distinguish two component of the haemodynamic activity: one reflects responses to visual stimuli, and is local to the retinotopic region activated by the stimuli. The second correlates strongly with pupil diameter, which reflects a measure of arousal, and is shared simultaneously by large regions of cortex.
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Freeborn, Robert Bruce. "A neural death model of the visual cortex." Thesis, University of Sussex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.394270.
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Michel, Vincent. "Understanding the visual cortex by using classification techniques." Paris 11, 2010. http://www.theses.fr/2010PA112202.
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Dans cette thèse, nous présentons différentes méthodes d'apprentissage statistique pouvant être utilisées pour comprendre le code neuronal des fonctions cognitives, en se basant sur des données d'Imagerie par Résonance Magnétique fonctionnelle (lRMf). Nous nous intéressons principalement à l'étude de la localisation spatiale des entités impliquées dans le codage, et leur influence respective dans le processus cognitif, en nous focalisant sur l'étude du cortex visuel. Après avoir introduit les notions de codage neuronal et d'imagerie fonctionnelle, nous étudions les limites de l'approche classique d'analyse des données d'IRMf, et les différents avantages apportés par une méthode d'analyse récente, l'inférence inverse. Enfin, nous détaillons les méthodes d'apprentissage statistique utilisées dans le cadre de l'inférence inverse, et nous les évaluons sur un jeu de données réelles. Dans une seconde partie, nous décrivons les trois principales contributions de cette thèse. Tout d'abord, nous introduisons une approche Bayésienne pour la régularisation parcimonieuse, généralisant au sein d'un même modèle différentes régularisations Bayésiennes. Ensuite nous proposons un algorithme de coalescence supervisé qui tient compte de l'information spatiale contenue dans les images fonctionnelles, et qui semble être bien adaptée au cas de l'inférence entre sujets. Finalement, nous proposons d'inclure l'information spatiale au sein d'un modèle de régularisation, qui peut être utilisé dans un cadre de prédiction, et permet d'extraire des ensembles connexes de voxels prédictifs. Cette approche est bien adaptée à l'étude de la localisation spatiale du codage neuronalLn this thesis, we present different approaches for statistical learning that can be used for studying the neural code of cognitive functions, based on brain functional Magnetic Resonance Imaging (fMRI) data. Ln particular, we study the spatial organization of the neural code, i. E. The spatial localization and the respective weights of the different entities implied in the neural coding. Ln this thesis, we focus on the visual cortex. Ln the first part of this thesis, we introduce the notions of functional architecture, neural coding and functional imaging. Then, we study the limits of the classical approach for the characterization of the neural code fram fMRI images, and the advantages of a recent method of analysis, namely inverse inference. Finally, we detail the statistical learning approaches used for inverse inference, and we evaluate them on real data. Ln a second part, we describe the three main contributions of this thesis. First, we introduce a Bayesian framework for sparse regularization, that generalizes two reference approaches. Then, we propose a supervised clustering method, that takes into account the spatial structure of the images. The resulting weighted maps are easily interpretable, and this approach seems particularly interesting in the case of inter-subjects inference. The last contribution of this thesis aims at including the spatial information into the regularization framework. This regularization is th us used in both regression and classification settings, and extracts clusters of predictive voxels. This approach is well suited for the decoding problem addressed in this thesis
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Bedford, James L. "Neuro-electromagnetic imaging of the human visual cortex." Thesis, Aston University, 1995. http://publications.aston.ac.uk/14604/.
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Methods of solving the neuro-electromagnetic inverse problem are examined and developed, with specific reference to the human visual cortex. The anatomy, physiology and function of the human visual system are first reviewed. Mechanisms by which the visual cortex gives rise to external electric and magnetic fields are then discussed, and the forward problem is described mathematically for the case of an isotropic, piecewise homogeneous volume conductor, and then for an anisotropic, cocentric, spherical volume conductor. Methods of solving the inverse problem are reviewed, before a new technique is presented. This technique combines prior anatomical information gained from stereotaxic studies, with a probabilistic distributed-source algorithm to yield accurate, realistic inverse solutions. The solution accuracy is enhanced by using both visual evoked electric and magnetic responses simultaneously. The numerical algorithm is then modified to perform equivalent current dipole fitting and minimum norm estimation, and these three techniques are implemented on a transputer array for fast computation. Due to the linear nature of the techniques, they can be executed on up to 22 transputers with close to linear speedup. The latter part of the thesis describes the application of the inverse methods to the analysis of visual evoked electric and magnetic responses. The CIIm peak of the pattern onset evoked magnetic response is deduced to be a product of current flowing away from the surface areas 17, 18 and 19, while the pattern reversal P100m response originates in the same areas, but from oppositely directed current. Cortical retinotopy is examined using sectorial stimuli.
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Saenz, Melissa. "Global effects of attention in human visual cortex /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2002. http://wwwlib.umi.com/cr/ucsd/fullcit?p3071014.
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Watson, David M. "The neural representation of scenes in visual cortex." Thesis, University of York, 2016. http://etheses.whiterose.ac.uk/12961/.
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Recent neuroimaging studies have identified a number of regions in the human brain that respond preferentially to visual scenes. These regions are thought to underpin our ability to perceive and interact with our local visual environment. However, the precise stimulus dimensions underlying the function of scene-selective regions remain controversial. Some accounts have proposed an organisation based on relatively high-level semantic or categorical properties of the stimulus. However, other accounts have suggested that lower-level visual features of the stimulus may offer a more parsimonious explanation. This thesis presents a series of fMRI experiments employing multivariate pattern analyses (MVPA) in order to test the role of low-level visual properties in the function of scene-selective regions. The first empirical chapter presents two experiments showing that patterns of neural response to different scene categories can be predicted by a model of the visual properties of scenes (GIST). The second empirical chapter demonstrates that direct manipulations of the spatial frequency content of the image significantly influence the patterns of response, with effects often being comparable to or greater than those of scene category. The third empirical chapter demonstrates that distinct patterns of response can be found to different scene categories even when images are Fourier phase scrambled such that low-level visual features are preserved, but perception of the categories is impaired. The fourth and final empirical chapter presents an experiment using a data-driven method to select clusters of scenes objectively based on their visual properties. These visually defined clusters did not correspond to typical scene categories, but nevertheless elicited distinct patterns of neural response. Taken together, these results support the importance of low-level visual features in the functional organisation of scene-selective regions. Scene-selective responses may arise from the combined sensitivity to multiple visual features that are themselves predictive of scene content.
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Ajina, Sara. "Changes in connectivity, structure and function following damage to the primary visual cortex." Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:2e274261-c71a-4ad1-82cf-2fe6bbdbf673.
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Residual vision, or blindsight, following damage to the primary visual cortex was first identified almost a century ago. However, the mechanism and pathways underlying this ability, as well as the extent of visual function, remain unclear and are a continuing source of speculation. The work presented here goes some way to try to address these questions, investigating 18 patients with V1 damage and homonymous visual field loss acquired in adulthood. Six experimental chapters explore the extent and potential for visual function after V1 damage, and apply novel neuroimaging paradigms and techniques to try to uncover the mechanisms and pathways that might be involved. A combination of psychophysics, functional and structural MRI was used to investigate responses to blind field stimulation in the dorsal and ventral streams. In addition, diffusion MRI tractography was performed and related to psychophysical performance, so that the three main pathways implicated in blindsight could be evaluated. Lastly, a small rehabilitation study was carried out to assess the effect of training in the blind hemifield, and to investigate whether there is any transfer of learning between the dorsal and ventral visual streams. The results from this work reinforce the suggestion that blindsight may be more common than was first thought, and may extend across a number of characteristics involving both visual streams. It is also suggested that visual function need not be completely unconscious, but that certain salient stimuli can elicit both non-visual and crude visual experience. The use of parametric functional imaging paradigms has enabled a number of properties of non-striate inputs to the extrastriate cortex to be revealed. Together with tractography, this points to an important role for the ipsilateral lateral geniculate nucleus in blindsight function. It is hoped that future work will build upon this, and that it may be possible to target these residual pathways in the rehabilitation of patients with V1 damage.
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Ip, Ifan Betina. "Effects of visual attention on stereoscopic depth perception in the human visual cortex." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.543544.
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Liu, Xiaochen. "Modelling Functional Maps and Associated Visual Gamma Activities in the Primary Visual Cortex." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/28536.
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The mammalian primary visual cortex (V1) has been extensively studied over the last decades to probe the neural mechanisms behind visual perception of elementary visual features such as edges, direction of motion, and colour. Numerous experiments have visualized the ordered arrangement of various functional maps in V1 and measured the neural activity patterns associated with them. However, only a few studies have quantitatively modelled the influences of the spatial structure of the functional maps on the neural activities. Moreover, the experimental maps usually show a great degree of irregularity and contain a large number of neurons, which makes them difficult to describe in analytic forms and computationally inefficient to integrate into quantitative neural models of large scale brain dynamics.
The present work approximates the functional maps of V1 in a compact analytic representation that complies with the main characteristics of the experimental maps, and integrates such map structure into the established neural field model with interacting neural populations to reproduce oscillatory neural activities in V1.
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Zumbroich, Thomas J. "The organization and development of the lateral suprasylvian visual areas of the cat visual cortex." Thesis, University of Oxford, 1986. http://ora.ox.ac.uk/objects/uuid:5ba54462-21db-4207-b591-e79c26cb06ab.
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Leinweber, Marcus. "Development of orientation preference maps in ferret visual cortex." Diss., lmu, 2010. http://nbn-resolving.de/urn:nbn:de:bvb:19-135685.
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Spacek, Martin A. "Characterizing patches of primary visual cortex with minimal bias." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/53975.
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The brain is highly complex, and studying it requires simplifying experiments, analyses, and theories. New techniques can capture more of the brain's complexity while reducing biases in our understanding of how it works. This thesis describes experiments in primary visual cortex of anesthetized cat, using high-density silicon multisite electrodes to simultaneously record from as many neurons as possible across all cortical layers, thereby characterizing local cortical populations with minimal bias. Recordings were maintained for many hours at a time, and included both spontaneous and stimulus-evoked periods, with a wide variety of naturalistic and artificial visual stimuli. A new "divide-and-conquer" spike sorting method translated correlated multisite voltages into action potentials of spatially localized, isolated neurons. This method tracked neurons over periods of many hours despite drift, and distinguished neurons with firing rates < 0.05 Hz. Neuron physiology was reasonably normal and mostly agreed with accepted principles of visual cortex, but there were exceptions. Surprisingly, firing rates across the population followed a lognormal distribution, and 82% of neurons had mean firing rates < 1 Hz. Also surprisingly, orientation tuning strength across the population was inversely correlated with log firing rate. Finally, there was evidence for neural shift work: over long durations, as some neurons became silent, others became active. To break down analyses by cell type, neurons were classified by their temporal spike shape and receptive field. Responses to repeated natural scene movie clips consisted of unique patterns of remarkably sparse, temporally precise (20 ms wide), reliable events. Mean pairwise correlations between neurons, as measured between trial-averaged responses to natural scene movies, were weakly positive. Correlations between simple and complex cells were lower — and between complex cells were higher — than expected, challenging the hierarchical model of complex cells. Cortical state was classified according to the local field potential, revealing greater natural scene movie response precision, sparseness, and reliability during the synchronized than desynchronized cortical state, contrary to reports in rodents. The open-ended, inclusive, high-dimensional experiments and analyses described here make few assumptions, potentially leading to more insightful theories of brain function than hypothesis-driven research alone.Medicine, Faculty of
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Jia, Wei-Guo. "Calcium-related signal transduction systems in developing visual cortex." Thesis, University of British Columbia, 1991. http://hdl.handle.net/2429/30927.
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Neuronal connections in cat visual cortex are highly susceptible to visual experience at early postnatal age and thus serve as a useful model of neural plasticity. The biochemical mechanisms underlying this cortical plasticity remain unclear. In this thesis, the development of several elements in calcium-related signal transduction systems, including the type-1 muscarinic and alpha-1 adrenoceptor systems as examples of cell surface receptors and protein kinase C. calcium/calmodulin dependent kinase II and inositol 1,4,5 phosphotate receptors as second messenger targets, were investigated using the methods of immunocytochemistry and autoradiography. The results show that each receptor develops with its own time-table and laminar distribution; the various elements all culminate and display the maximal colocalization during the critical period; and, only at this age, the cortical levels of the receptors and kinases are dependent on subcortical afferents. The results suggest that cell surface receptors and their second messenger targets develop in specific temporal and spatial patterns, which may be both genetically and environmentally determined, and this specific sequence of development of the molecules for signal transduction results in a series of modifications in the morphology and physiology of the developing cortex leading to its maturation.Medicine, Faculty of
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Sammons, Rosanna Penelope. "Mechanisms of homeostatic plasticity in the mouse visual cortex." Thesis, King's College London (University of London), 2016. https://kclpure.kcl.ac.uk/portal/en/theses/mechanisms-of-homeostatic-plasticity-in-the-mouse-visual-cortex(9740e4f1-b25c-4e9e-8905-c3547e552ff3).html.
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During development, newly established cortical circuits are undergoing a period of experience dependent refinement. Visual deprivation during this time leads to the induction of plasticity mechanisms, including homeostatic plasticity measures. These are a distinct set of plasticity mechanisms thought to play a role in maintaining stability within networks, and preventing large perturbations in overall activity levels. Homeostatic plasticity mechanisms can be divided into synaptic and intrinsic mechanisms. While details of individual mechanisms are reasonably well understood, details of how these different mechanisms are linked to one another are much less clear. In this thesis, I investigate the relationship between structural and functional forms of synaptic and intrinsic plasticity in layer 2/3 neurons in the monocular visual cortex, before and after induction of plasticity via monocular enucleation. I find that while axon initial segment (AIS) plasticity takes place following deprivation, in both pyramidal neurons, and a subset of inhibitory neurons, it does not correlate with functional measures of excitability. However, in control conditions, I do find a relationship between the synaptic inputs of a neuron, and its intrinsic excitability. Following deprivation, this relationship is altered. Specifically, I find that the activity status of the neuron affects the level of intrinsic excitability, and to some extent, the synaptic input to the cell. Putatively inactive neurons show increased excitability, and trend towards stronger synaptic input in comparison to their active counterparts. These differences between active and inactive cells may reflect the engagement of homeostatic mechanisms in inactive cells, in order to restore their activity levels.
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Koski, Lisa Marie. "The role of frontal cortex in visual selective attention." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0017/NQ55350.pdf.
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Thomson, J. Ross. "Models of pattern formation on the primate visual cortex." Thesis, McGill University, 1989. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=55635.
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Palmer, Joanne Eryl. "Functioning of the visual cortex in patients with migraine." Thesis, Lancaster University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369653.
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McKay, Sarah Maree. "The nature of the first responses in visual cortex." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.403576.
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Ranson, Adam. "Development and plasticity of the mouse primary visual cortex." Thesis, Cardiff University, 2011. http://orca.cf.ac.uk/54216/.
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A strain difference was observed in juvenile OD plasticity between C57BL/6J and C57BL/6JOlaHsd mice whereby open eye 'homeostatic' potentiation was completely absent in the C57BL/6JOlaHsd strain. This was accompanied by an absence of dark exposure induced synaptic scaling as measured
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Burgess, C. P. "Measuring correlates of perceptual decisions in mouse visual cortex." Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1473920/.
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The activity of sensory cortex is determined not only by afferent sensory stimuli, but also by behavioural context factors such as movement, anticipation, attention, and reward. To investigate such factors, I developed a visual psychophysical task in head-fixed mice and combined it with two-photon calcium imaging to measure activity in primary visual cortex (V1). I trained mice to report the position of a grating by turning a wheel with their forepaws. I found that a crucial element in helping mice learn the task was enabling them to control the position of the stimulus: the grating would initially appear to their left or to their right, and their wheel turns would translate it. They were rewarded for bringing it to the centre. Mice typically learned the task in 2-3 weeks, producing high-quality psychometric functions of stimulus contrast, with 75% accuracy at contrasts as low as 8%. In the same mice, I injected a virus in V1 to express GCaMP6, so I could perform two-photon calcium imaging of neural populations while the mice performed the task. Calcium imaging in V1 revealed strong responses evoked by contralateral stimuli, modulated by stimulus contrast. I obtained measures of contrast sensitivity from population responses and found them to be higher than the corresponding psychophysical measures. I did not find significant correlations between perceptual decisions and stimulus-independent V1 activity. I also observed small but significant increases in calcium activity during pre-stimulus periods and the amplitude of this activity was predictive of subsequent psychophysical performance on those trials. Finally, I discovered that the basic task was adaptable and the stimulus control principle was generalizable. I demonstrate this by presenting multiple variants of the task including one using auditory stimuli and another probing the effects of dopamine stimulation.
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Rikhye, Rajeev V. (Rajeev Vijay). "The mechanisms of reliable coding in mouse visual cortex." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107559.
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Thesis: Ph. D. in Neuroscience, Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2016.Cataloged from PDF version of thesis. Page 262 blank.
Includes bibliographical references.
As we interact with the environment, our senses are constantly bombarded with information. Neurons in the visual cortex have to transform these complex inputs into robust and parsimonious neural codes that effectively guide behavior. The ability of neurons to efficiently convey information is, however, limited by intrinsic and shared variability. Despite this limitation, neurons in primary visual cortex (V1) are able to respond with high fidelity to relevant stimuli. My thesis proposes that high fidelity encoding can be achieved by dynamically increasing trial-to-trial response reliability. In particular, in this thesis, I use the mouse primary visual cortex (V1) as a model to understand how reliable coding arises, and why it is important for visual perception. Using a combination of novel experimental and computational techniques, my thesis identifies three main factors that can modulate intrinsic variability. My first goal was to understand the extrinsic, stimulus-dependent, factors responsible for reliably coding (Chapter 3). Natural scenes contain unique statistical properties that could be leveraged by the visual cortex for efficient coding. Thus, the first aim is to elucidate how image statistics modulate reliable coding in V1. To this end, I developed a novel noise masking procedure that allowed us to specifically perturb the spectral content of natural movies without altering the edges. Using high-speed twophoton calcium imaging in mice, I discovered that movies with stronger spatial correlations are more reliably processed by V1 neurons than movies lacking these correlations. In particular, perturbing spatial correlations in the movie dynamically altered the structure of interneuronal correlations. Movies with more naturalistic correlations typically recruited large neuronal ensembles that were weakly noise correlated. Using computational modeling, I discovered that these ensembles were able reduce shared noise through divisive normalization. Together, these findings demonstrate that natural scene statistics dynamically recruit neuronal ensembles to ensure reliable coding. Microcircuits of inhibitory interneurons lie at the heart of all cortical computations. It has been proposed that these interneurons are responsible for reliable spiking by controlling the temporal window over which synaptic inputs are integrated. However, no study has yet conclusively investigated the role of different interneuron subtypes. Thus, my second goal was to establish how natural scenes are reliably encoded by dissecting the inhibitory mechanisms underlying reliable coding (Chapter 4). Specifically, I investigated the role of somatostatin-expressing dendrite targeting interneurons (SST) and parvalbumin-expressing soma targeting interneurons (PV), which are known to provide distinct forms of inhibition onto pyramidal neurons. Using a novel combination of dual-color calcium imaging and optogenetic manipulation, I have discovered that the SST->PV inhibitory circuit plays a crucial role in modulating pyramidal cell reliability. In particular, by transiently suppressing PV neurons, SST neurons are able to route inhibition rapidly from the soma to the dendrites. Strong dendritic inhibition allows noisy inputs to be filtered out by the dendrites, while weaker somatic inhibition allows these inputs to be integrated to produce reliable spikes. In agreement with these results, I found that selectively deleting MeCP2 from these interneurons resulted in unreliable visual processing and other circuit-specific deficits, which are commonly observed in Rett Syndrome (Chapter 5). These results underscore the importance of intact inhibitory microcircuits in reliable processing. Finally, my goal was to determine why reliable coding is necessary for visual processing (Chapter 6). To this end, I trained head-fixed mice to perform a natural movie discrimination task. Mice were able to learn how to discriminate between two movies after a short training period. By perturbing the amplitude spectrum of these movies, I discovered that mice used structural information in the phase spectrum to discriminate between the different movies. This suggests that mice also use similar strategies as higher mammals for scene recognition. Inspired by this result, we trained mice on a harder target categorization task, where mice had to identify the movies from an ensemble that were more similar to the target movie to gain a water reward. We developed this movie ensemble by blending together the phase spectrum of a target and non-target movie at different fractions. Optically activating SST neurons in V1 improved the ability of mice to correctly identify "target-like" movies. This increase in behavioral performance correlated well with an increase in V1 coding reliability. Thus, reliable codes are a prerequisite for accurate visual perception. Taken together, this work bridges the gap between cells, circuits and behavior, and provides mechanistic insight into how complex visual stimuli are encoded with high fidelity in the visual cortex.
by Rajeev V. Rikhye.
Ph. D. in Neuroscience