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

Binocular integration using stereo motion cues to drive behavior in mice

The visual system presents an opportunity to study how two signals converge to generate a novel representation of the world: depth. The slight difference in positions between the two eyes means that different images are encoded by the left and right eyes by generating disparity signals. Another way to generate depth signals is by presenting different motion signals to the two eyes. Even though the binocular visual system has been studied for a long time, the mechanisms behind binocular integration when objects move in depth are largely unknown. In this dissertation, I demonstrate a new model for studying motion-in-depth signals using mice. Mice are an attractive animal to study the binocular visual system not only because they share common visual pathway as primates and other mammals, but also because there are genetic tools that can be used to study the underlying circuitry for binocular integration during motion-in-depth cues. Thus far there have been very few studies regarding binocularity in mice. This dissertation will focus on the behavioral output during stereoscopic motion-in-depth signals in mice and investigate visual areas involved in these behaviors. In the first section, I investigate whether mice discriminate motion-in-depth signals like primates, using disparity and motion signals presented to each eye. I find that mice are able to discriminate towards and away stimuli and that the binocular neurons in the visual cortex were critical for the computation of this signal. In the second section we measured optokinetic eye movement generated by motion-in-depth stimulus. I found that vergence eye movement in mice is driven primarily by the motion signals presented in each eye. This phenomenon can be explained largely by the summation of monocular motor signals of the two eyes that happens subcortically. These two experiments both show clear behavioral output that can be only generated when presented with binocular motion-in-depth signals. I find both cortical and subcortical components of binocular integration that are responsible for the generation of these behavior outputs which demonstrates the complicated nature of binocular integration associated with motion-in-depth signals. My work in this dissertation provides the foundation for studying binocular integration in rodentsNeuroscienc

Functional Specialization of eye-specific visual pathways into higher visual cortex

The brain is able to construct a visual representation of the world by parallel processing of cortical neurons that prefer increasingly complex stimuli. One way the visual cortex has accomplished parallel processing is by creating functionally organized modules that are tuned to unique features and linking them in multiple processing stages of cortex. For example, primary visual cortex (V1) sends functionally distinct information to higher visual areas (HVAs), which are more specialized in their processing of spatiotemporal information. Inherently coupled to this process is the convergence of eye-specific inputs in visual cortex. Shifting the eye-specific tuning of neurons in primary visual cortex by monocular deprivation in early life is known to disrupt tuning for spatial frequency in adulthood. Combining space and time better characterizes the segregation of HVAs. To begin to understand if eye-specific responses could be linked to tuning properties important for the segregation of HVAs, we characterized eye-specific spatiotemporal tuning of layer 2/3 excitatory cells within the binocular zone of V1 and two HVAs grouped into the putative ventral and dorsal streams, LM and PM, using two-photon GCaMP6s imaging of awake mice. An asymmetry was found at the level of V1, such that responses driven primarily by the contralateral eye were biased towards high spatial frequencies, low speeds, cardinal directions, and were more direction selective than binocular or ipsilateral eye-driven responses. Eye-specific inputs in V1 are tuned to different speeds and also have different degrees of speed tuning, where contralateral eye inputs are more speed tuned than ipsilateral eye inputs. The proportions of eye-specific neurons of LM and PM matched the expected preferences based on eye-specific spatial frequency tuning found at the level of V1. A similar contralateral bias for distinct features, most notably, spatiotemporal tuning, was found within LM and PM, linking neurons with similar eye-specific preferences to their tuning for early feature detectors important for stream specialization. To determine if V1 sends eye-specific functionally distinct information to HVAs, we injected AAV-Syn-GCaMP6s into the binocular zone of V1 and imaged the afferents that targeted either LM or PM. We found that V1 afferents to LM and PM were distinct in their distributions for ocular dominance, suggesting that eye-specific projections from V1 to HVAs contribute to their functional specificity. To determine if the functional specialization of HVAs depend upon eye-specific developmental mechanisms, we deprived mice of visual experience through the contralateral eye (CMD) during the ocular dominance critical period and assessed eye-specific spatiotemporal tuning of V1, LM and PM in adulthood. We found that CMD diminished the functional specificity of V1, LM and PM, resulting in areas without differentiated spatiotemporal preferences. Moreover, the eye-specific functional segregation was also disrupted with CMD. Altogether, our data demonstrates that the maturation of higher visual areas is dependent on proper binocular visual experience and suggests that the functional specialization of eye-specific responses could be an efficient routing mechanism to differentiate higher visual areas

Visual Cortex

The neurosciences have experienced tremendous and wonderful progress in many areas, and the spectrum encompassing the neurosciences is expansive. Suffice it to mention a few classical fields: electrophysiology, genetics, physics, computer sciences, and more recently, social and marketing neurosciences. Of course, this large growth resulted in the production of many books. Perhaps the visual system and the visual cortex were in the vanguard because most animals do not produce their own light and offer thus the invaluable advantage of allowing investigators to conduct experiments in full control of the stimulus. In addition, the fascinating evolution of scientific techniques, the immense productivity of recent research, and the ensuing literature make it virtually impossible to publish in a single volume all worthwhile work accomplished throughout the scientific world. The days when a single individual, as Diderot, could undertake the production of an encyclopedia are gone forever. Indeed most approaches to studying the nervous system are valid and neuroscientists produce an almost astronomical number of interesting data accompanied by extremely worthy hypotheses which in turn generate new ventures in search of brain functions. Yet, it is fully justified to make an encore and to publish a book dedicated to visual cortex and beyond. Many reasons validate a book assembling chapters written by active researchers. Each has the opportunity to bind together data and explore original ideas whose fate will not fall into the hands of uncompromising reviewers of traditional journals. This book focuses on the cerebral cortex with a large emphasis on vision. Yet it offers the reader diverse approaches employed to investigate the brain, for instance, computer simulation, cellular responses, or rivalry between various targets and goal directed actions. This volume thus covers a large spectrum of research even though it is impossible to include all topics in the extremely diverse field of neurosciences

Ideal binocular disparity detectors learned using independent subspace analysis on binocular natural image pairs

This work was funded by the Biotechnology and Biological Sciences Research Council (BBSRC) grant [BB/K018973/1].An influential theory of mammalian vision, known as the efficient coding hypothesis, holds that early stages in the visual cortex attempts to form an efficient coding of ecologically valid stimuli. Although numerous authors have successfully modelled some aspects of early vision mathematically, closer inspection has found substantial discrepancies between the predictions of some of these models and observations of neurons in the visual cortex. In particular analysis of linear-non-linear models of simple-cells using Independent Component Analysis has found a strong bias towards features on the horoptor. In order to investigate the link between the information content of binocular images, mathematical models of complex cells and physiological recordings, we applied Independent Subspace Analysis to binocular image patches in order to learn a set of complex-cell-like models. We found that these complex-cell-like models exhibited a wide range of binocular disparity-discriminability, although only a minority exhibited high binocular discrimination scores. However, in common with the linear-non-linear model case we found that feature detection was limited to the horoptor suggesting that current mathematical models are limited in their ability to explain the functionality of the visual cortex.Publisher PDFPeer reviewe

Development of an Integrated Model of Primary Visual Cortex

Network-level models of visual processing have potentially important insights for applications such as computer vision and robotics. Primary visual cortex is a key stage of visual processing with involvement in many circuits proposed for these applications including motion tracking, object recognition, and control of eye movements. However, no model of V1 to date has captured the complete set of observed behaviour in a large-scale model. Linear kernel methods with threshold and divisive non-linearities can reproduce classical receptive field behaviour, but not the full range of non-classical behaviours. The stabilized supralinear network (SSN) provides a simple scheme of lateral interactions that produce a wealth of observed V1 behaviour not previously captured with linear kernel methods. However, the SSN is restricted in stimulus selectivity and is not pixel-computable, limiting its utility for real-world applications. Integrating a linear kernel model with the SSN resulted in a model that is pixel-computable and produces a wide range of classical and non-classical behaviour. With further development this network model will be usable in visual processing circuits. The SSN was also expanded to use binocular stimuli. Using an optimization procedure, SSN parameters were found that produce interocular transfer of suppression in excitatory units, but not inhibitory ones. The lack of interocular transfer in inhibitory units may indicate that an alternate inhibition-stabilization scheme is more biophysically realistic. Mammalian visual perception is enabled not only by neural processing but also by precise eye movements, which allow for efficient scanning of the environment. This thesis describes the requirements for a robot that can orient cameras with the same dynamics as macaque monkey eyes as well as a camera system that reproduces macaque visual acuity

Genetic determination and layout rules of visual cortical architecture

The functional architecture of the primary visual cortex is set up by neurons that preferentially respond to visual stimuli with contours of a specific orientation in visual space. In primates and placental carnivores, orientation preference is arranged into continuous and roughly repetitive (iso-) orientation domains. Exceptions are pinwheels that are surrounded by all orientation preferences. The configuration of pinwheels adheres to quantitative species-invariant statistics, the common design. This common design most likely evolved independently at least twice in the course of the past 65 million years, which might indicate a functionally advantageous trait. The possible acquisition of environment-dependent functional traits by genes, the Baldwin effect, makes it conceivable that visual cortical architecture is partially or redundantly encoded by genetic information. In this conception, genetic mechanisms support the emergence of visual cortical architecture or even establish it under unfavorable environments. In this dissertation, I examine the capability of genetic mechanisms for encoding visual cortical architecture and mathematically dissect the pinwheel configuration under measurement noise as well as in different geometries. First, I theoretically explore possible roles of genetic mechanisms in visual cortical development that were previously excluded from theoretical research, mostly because the information capacity of the genome appeared too small to contain a blueprint for wiring up the cortex. For the first time, I provide a biologically plausible scheme for quantitatively encoding functional visual cortical architecture by genetic information that circumvents the alleged information bottleneck. Key ingredients for this mechanism are active transport and trans-neuronal signaling as well as joined dynamics of morphogens and connectome. This theory provides predictions for experimental tests and thus may help to clarify the relative importance of genes and environments on complex human traits. Second, I disentangle the link between orientation domain ensembles and the species-invariant pinwheel statistics of the common design. This examination highlights informative measures of pinwheel configurations for model benchmarking. Third, I mathematically investigate the susceptibility of the pinwheel configuration to measurement noise. The results give rise to an extrapolation method of pinwheel densities to the zero noise limit and provide an approximated analytical expression for confidence regions of pinwheel centers. Thus, the work facilitates high-precision measurements and enhances benchmarking for devising more accurate models of visual cortical development. Finally, I shed light on genuine three-dimensional properties of functional visual cortical architectures. I devise maximum entropy models of three-dimensional functional visual cortical architectures in different geometries. This theory enables the examination of possible evolutionary transitions between different functional architectures for which intermediate organizations might still exist

Modeling orientation and ocular dominance columns in the visual cortex

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Physics, 1997.Includes bibliographical references (leaves 126-132).by Darren Michael Pierre.M.S