A functional model for primary visual cortex

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

A functional model for primary visual cortex

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

Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role

The lateral geniculate nucleus (LGN) has often been treated in the past as a linear filter that adds little to retinal processing of visual inputs. Here we review anatomical, neurophysiological, brain imaging, and modeling studies that have in recent years built up a much more complex view of LGN . These include effects related to nonlinear dendritic processing, cortical feedback, synchrony and oscillations across LGN populations, as well as involvement of LGN in higher level cognitive processing. Although recent studies have provided valuable insights into early visual processing including the role of LGN, a unified model of LGN responses to real-world objects has not yet been developed. In the light of recent data, we suggest that the role of LGN deserves more careful consideration in developing models of high-level visual processing

Multiplexed computations in retinal ganglion cells of a single type

In the early visual system, cells of the same type perform the same computation in different places of the visual field. How these cells code together a complex visual scene is unclear. A common assumption is that cells of a single-type extract a single-stimulus feature to form a feature map, but this has rarely been observed directly. Using large-scale recordings in the rat retina, we show that a homogeneous population of fast OFF ganglion cells simultaneously encodes two radically different features of a visual scene. Cells close to a moving object code quasilinearly for its position, while distant cells remain largely invariant to the object's position and, instead, respond nonlinearly to changes in the object's speed. We develop a quantitative model that accounts for this effect and identify a disinhibitory circuit that mediates it. Ganglion cells of a single type thus do not code for one, but two features simultaneously. This richer, flexible neural map might also be present in other sensory systems

Impact of the pulvinar on the ventral pathway of the cat visual cortex

Signals from the retina are relayed to the lateral geniculate nucleus from which they are sent to the primary visual cortex. At the cortical level, the information is transferred across several visual areas in which the complexity of the processing increases progressively. Anatomical and functional evidence demonstrate the existence of two main pathways in visual cortex processing distinct features of the visual information: the dorsal and ventral streams. Cortical areas composing the dorsal stream are implicated mostly in motion processing while those comprising the ventral stream are involved in the processing of form and colour. This classic view of the cortical functional organization is challenged by the existence of reciprocal connections of visual cortical areas with the thalamic nucleus named pulvinar. These connections allow the creation of a trans-thalamic pathway that parallels the cortico-cortical communications across the visual hierarchy. The main goal of the present thesis is twofold: first, to obtain a better comprehension of the processing of light increments and decrements in an area of the cat ventral stream (area 21a); second, to characterize the nature of the thalamo-cortical inputs from the cat lateral posterior nucleus (LP) to area 21a. In study #1, we investigated the spatiotemporal response profile of neurons from area 21a to light increments (brights) and decrements (darks) using a reverse correlation analysis of a sparse noise stimulus. Our findings showed that 21a neurons exhibited stronger responses to darks with receptive fields exhibiting larger dark subfields. However, no differences were found between the temporal dynamics of brights and darks. In comparison with the primary visual cortex, the dark preference in area 21a was found to be strongly enhanced, supporting the notion that the asymmetries between brights and darks are transmitted and amplified along the ventral stream. In study #2, we investigated the impact of the reversible pharmacological inactivation of the LP nucleus on the contrast response function (CRF) of neurons from area 21a and the primary visual cortex (area 17). The thalamic inactivation yielded distinct effects on both cortical areas. While in area 17 the LP inactivation caused a slight decrease in the response gain, in area 21a a strong increase was observed. Thus, our findings suggest that the LP exerts a modulatory influence on the cortical processing along the ventral stream with stronger impact on higher order extrastriate areas. Taken together, our findings allowed a better comprehension of the functional properties of the cat ventral stream and contributed to the current knowledge on the role of the pulvinar on the cortico-thalamo-cortical processing of visual information.Les signaux provenant de la rétine sont relayés dans le corps géniculé latéral où ils sont envoyés au cortex visuel primaire. L’information passe ensuite à travers plusieurs aires visuelles où la complexité du traitement augmente progressivement. Des données tant anatomiques que fonctionnelles ont démontré l’existence de deux voies principales qui traitent différentes propriétés de l’information visuelle : les voies dorsale et ventrale. Les aires corticales composant la voie dorsale sont impliquées principalement dans le traitement du mouvement tandis que les aires de la voie ventrale sont impliquées dans le traitement de la forme et de la couleur. Cette vision classique de l’organisation fonctionnelle du cortex est toutefois remise en question par l’existence de connections réciproques entre les aires corticales visuelles et le pulvinar, un noyau thalamique. En effet, ces connections permettent la création d’une voie trans-thalamique parallèle aux connections cortico-corticales à travers la hiérarchie visuelle. Le but principal de la présente thèse consiste en deux volets : le premier est d’obtenir une meilleure compréhension du traitement des incréments et décréments de la lumière dans une aire de la voie ventrale du chat (aire 21a); le second est de caractériser la nature des inputs thalamo-corticaux du noyau latéral postérieur (LP) à l’aire 21a chez le chat. Dans l’étude #1, nous avons investigué le profil spatiotemporel des réponses des neurones de l’aire 21a aux incréments (blancs) et décréments (noirs) de lumière en utilisant l’analyse de corrélation inverse d’un stimulus de bruit épars. Les neurones de l’aire 21a ont répondu plus fortement aux stimuli noirs, en montrant des champs récepteurs avec des sous-champs noirs plus larges. Cependant, aucune différence n’a été trouvée en ce qui concerne les dynamiques temporelles des réponses aux blancs et aux noirs. En comparaison avec le cortex visuel primaire, la préférence aux stimuli noirs dans l’aire 21a s’est avérée fortement augmentée. Ces données indiquent que les asymétries entre les réponses aux blancs et aux noirs sont transmises et amplifiées à travers la voie ventrale. Dans l’étude #2, nous avons investigué l’impact de l’inactivation pharmacologique réversible du noyau LP sur la fonction de réponse au contraste (CRF) des neurones de l’aire 21a et du cortex visuel primaire (aire 17). L’inactivation a eu différents effets dans les deux aires corticales. Alors que, dans l’aire 17, l’inactivation du LP a causé une légère réduction du gain de la réponse, une forte augmentation a été observée dans l’aire 21a. Ainsi, nos résultats suggèrent que le LP exerce une influence modulatrice dans le traitement cortical à travers la voie ventrale avec un impact plus important dans des aires extrastriées de plus haut niveau. Nos résultats ont permis d’avoir une meilleure compréhension des propriétés fonctionnelles de la voie ventrale du chat et de contribuer à enrichir les connaissances actuelles sur le rôle du pulvinar dans le traitement cortico-thalamo-cortical de l’information visuelle

Unified developmental model of maps, complex cells and surround modulation in the primary visual cortex

For human and animal vision, the perception of local visual features can depend on the spatial arrangement of the surrounding visual stimuli. In the earliest stages of visual processing this phenomenon is called surround modulation, where the response of visually selective neurons is influenced by the response of neighboring neurons. Surround modulation has been implicated in numerous important perceptual phenomena, such as contour integration and figure-ground segregation. In cats, one of the major potential neural substrates for surround modulation are lateral connections between cortical neurons in layer 2/3, which typically contains ”complex” cells that appear to combine responses from ”simple” cells in layer 4C. Interestingly, these lateral connections have also been implicated in the development of functional maps in primary visual cortex, such as smooth, well-organized maps for the preference of oriented lines. Together, this evidence suggests a common underlying substrate the lateral interactions in layer 2/3—as the driving force behind development of orientation maps for both simple and complex cells, and at the same time expression of surround modulation in adult animals. However, previously these phenomena have been studied largely in isolation, and we are not aware of a computational model that can account for all of them simultaneously and show how they are related. In this thesis we resolve this problem by building a single, unified computational model that can explain the development of orientation maps, the development of simple and complex cells, and surround modulation. First we build a simple, single-layer model of orientation map development based on ALISSOM, which has more realistic single cell properties (such as contrast gain control and contrast invariant orientation tuning) than its predecessor. Then we extend this model by adding layer 2/3, and show how the model can explain development of orientation maps of both simple and complex cells. As the last step towards a developmental model of surround modulation, we replace Mexican-hat-like lateral connectivity in layer 2/3 of the model with a more realistic configuration based on long-range excitation and short-range inhibitory cells, extending a simpler model by Judith Law. The resulting unified model of V1 explains how orientation maps of simple and complex cells can develop, while individual neurons in the developed model express realistic orientation tuning and various surround modulation properties. In doing so, we not only offer a consistent explanation behind all these phenomena, but also create a very rich model of V1 in which the interactions between various V1 properties can be studied. The model allows us to formulate several novel predictions that relate the variation of single cell properties to their location in the orientation preference maps in V1, and we show how these predictions can be tested experimentally. Overall, this model represents a synthesis of a wide body of experimental evidence, forming a compact hypothesis for much of the development and behavior of neurons in the visual cortex

A comparative study of cortical computations in the mammalian visual cortex

textA common feature of all mammals is the cerebral cortex, which is essential for higher-order functions and processing information to generate motor actions. While cortical circuits exhibit a striking uniformity in anatomical organization, it is unknown whether these circuits preform similar computations across mammalian species. In this dissertation I compare the emergence of two computations in the primary visual cortex (V1) of carnivores and rodents. A cortical computation is a transformation in neural representation, such that the spiking output of a cortical neuron exhibits a selectivity not present in the inputs from upstream neurons. Here I explore two computations: orientation selectivity, the preference of neurons for oriented edges in the visual world, and binocularity, the integration of signals from the two eyes. In the first section, I compare the emergence of orientation selectivity in the early visual pathway of mouse and cat. Recordings from thalamic relay cells and V1 neurons in both species reveal orientation selectivity in mouse V1 is not emergent, and could be inherited subcortically. In a second set of experiments, I measure orientation selectivity and the organization of V1 orientation preference in a grasshopper mouse with predatory behavior, compared to the scavenger lab mouse. Here I find the same functional properties. In the second section, I focus on the integration of ocular inputs in V1 of mouse and cat. I first compare disparity selectivity in cats, where convergence of ocular inputs has long been established, with mice, where ocular integration had not previously been investigated. Similar to cats, mouse V1 neurons were sensitive to binocular disparity, albeit to a lesser degree, and could be described by a linear feed-forward model. I next explore the disruption of binocular disparity tuning in both animals. In cats, strabismus induced during development causes increased monocularity in V1 and a loss of disparity selectivity. In mice, monocular deprivation causes increased ocular input, which also manifests as decreased disparity selectivity. Finally, I explore how excitatory and inhibitory neurons in mouse V1 integrate binocular signals. Paravalbumin-expressing inhibitory interneurons are more binocular but less disparity tuned than surrounding cortical neurons, providing a canonical mechanism explaining loss of disparity selectivity in both carnivores and rodents.Neuroscienc

Development and encoding of visual statistics in the primary visual cortex

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

Temporal information processing across primary visual cortical layers in normal and red light reared tree shrews.

Visual neuroscience research has benefitted from decades of efforts of comparative studies of different species, since exploring and understanding the diversity of functional properties of visual system in different species has helped us identify both general organization rules and unique traits of certain species. In this study, spatio-temporal receptive fields (STRFs), together with some other functional properties (etc. stimulus preference to different visual stimuli, orientation tuning, temporal frequency tuning and the F1/F0 ratio of responses to sine-wave grating stimuli), of primary visual cortex (V1) cells were measured in normally reared and red-light reared tree shrews (Tupaia), a species considered the closest non-primate relative to human being. All data were sampled in anesthetized animals using extracellular recording techniques. In the current study, a diversity of STRFs structures were found in tree shrew V1, and the STRFs found were classified into two categories, Type I receptive fields (RFs) that had spatially discontinuous on- and off-regions, or had spatio-temporal inseparable RFs, and Type II RFs that had spatially overlapped circular or elliptical on- and off- regions, and spatio-temporal separable RFs. Spatial and temporal profile analysis indicated this Type I and Type II classification did not correspond to simple and complex RF types previously described in primates and carnivores. It was also found in the current study that the linear prediction based on STRFs did not predict temporal frequency tuning, orientation tuning or the F1/F0 ratio very well in tree shrew V1. In tree shrew V1, both low-pass and band-pass cells for temporal frequency were found, and the proportion of cells with different types of tuning curves also differed across layers, resulting in a low-pass filter between layer II/II and layer IV. Last but not least, it was found in this study that red light rearing after birth changes the population stimulus preference in layer IV in tree shrew V1