Jose-Manuel Alonso - US grants

Neurons within the cat visual cortex show a great variety of receptive field properties. This functional diversity emerges mainly from interactions between thalamic and corticocortical inputs whose precise circuitry is largely unknown. In this proposal, two different approaches are taken to study the circuitry underlying the responses of complex cells in layer II-III. First, cross correlations, evaluated while recording from layer II-III, layer IV and the thalamus, are used to examine the cortical and/or thalamic inputs to complex cells. Second, small reversible blockades are made in the lateral geniculate nucleus (LGN) to study the contribution of different thalamic pathways to the generation of complex receptive fields. According to a hierarchical model of connectivity, the receptive fields of complex cells originates from the convergent inputs of layer IV simple cells. A major goal of this proposal is to examine the circuitry predicted by this model and investigate the role of different types of inputs, cortical and thalamic, in the generation of complex receptive fields. The study of the connections made by cells in the visual cortex is important to understand how neural systems extract information from the outside world. Only by such detailed knowledge of the cortical circuitry can neural disorders, such as many forms of amblyopia, be understood.

DESCRIPTION (provided by applicant): The human brain needs to have access to an accurate map of visual space to interpret the images that we see. The most accurate and complete visual map is located in primary visual cortex, where all the basic stimulus properties are thought to be systematically represented, including spatial location, orientation and phase. For example, a vertical dark bar in the middle of this page can be represented in primary visual cortex by its position (point of fixation), orientation (vertical) and phase (dark flanked by light. While previous studies have made important advances in our understanding of how spatial location and orientation are mapped across the primary visual cortex, we still do not know how spatial phase is represented in this map. This is a fundamental gap in knowledge given the importance that phase has in image processing algorithms, which are regularly applied to satellite imagery, medical imaging, videophone and character recognition. Current experimental data suggest that spatial phase is randomly distributed throughout the cortex; however, computational models keep insisting that phase should be clustered in specific regions of the cortical map. Our recent results demonstrate, for the first time, the existence of pronounced clusters for spatial phase that are closely related to the mapping of stimulus orientation in cortex. In addition, we show that dark-dominated phases are better represented than light-dominated ones. The main goal of this research project is to study the organization of these newly discovered cortical maps for spatial phase with a novel approach that takes advantage of recent advances in multielectrode recording and has considerably better spatio-temporal resolution than other methods used in the past. With our multielectrode approach, we will reveal the inter- related organization of visual cortical maps for spatial position, orientation and phase the topography of dark- dominance in these maps and the rules that govern the representation of multiple stimulus dimensions within each 100 x 100 microns of cortex. We will use these measurements to build a detailed database of the multi- dimensional mapping of stimulus features across the visual cortical map and to test current computational models of functional cortical architecture and cortical development. PUBLIC HEALTH RELEVANCE: A complete understanding of how sensory maps are organized in the cerebral cortex is essential to guide future therapeutic approaches aimed at repairing or replacing cortical microcircuits. For example, the success of electrical neuronal prosthesis in the cerebral cortex not only require solving problems of tissue damage and electrode interphase but also requires a very detailed understanding of the cortical topography in which the prosthesis will be implanted. Interpreting the cortical changes that take place in visual disorders such as amblyopia and macular degeneration also requires a complete understanding of cortical map organization. Our research project is part of a maintained effort to reveal the functional organization of visual cortical maps, which will be needed to guide the treatments of insults to the visual brain in the future.

DESCRIPTION (provided by applicant): In the last 30 years, there has been an enormous progress in understanding the brain circuits involved in selective visual attention. Some current models propose that the 'attention signal' originates in high cortical areas (e.g. frontal and parietal cortex) and then is transferred in a top-down fashion to earlier stages in visual processing. This model is consistent with the existence of a rich anatomical network of feedback connections that go from higher to lower stages in the visual pathway. However, feedback connections reach stages as low in processing as the primary visual cortex (V-1 ) and the Lateral Geniculate Nucleus (LGN). Therefore, attention could potentially modulate perception by acting at the initial stages of the visual pathway. Consistent with this hypothesis, increasing evidence indicates that selective visual attention modulates the activity of V-1 and one recent anatomical study found the first evidence for attentional modulations in LGN. An important characteristic of selective visual attention is its retinotopic specificity the focus of attention can be restricted to very small regions of visual space. A remarkable specificity has been demonstrated in several cortical areas including V-1 but not in LGN. The demonstration that visual attention can modulate LGN activity is missing therefore an important piece of evidence. It is not known how retinotopically selective LGN modulations can be. In this proposal, the retinotopic specificity of LGN attentional modulations will be measured by simultaneously recording from multiple geniculate neurons while an animal performs a task that requires selective visual attention. In addition, it will be investigated whether LGN modulations are reliably transferred to V-1 by doing simultaneous recordings from LGN and V-1 cells with receptive fields aligned in visual space. A precise knowledge of the circuits involved in selective visual attention is important to understand how the brain processes visual information. The study of this circuitry will eventually lead to the prevention and treatment of serious attentional deficits that are common in many psychiatric and neurological disorders.

DESCRIPTION (provided by applicant): The long-term goal of this proposal is to provide the scientific community with a new array of ultra-thin electrodes that can be chronically implanted in a primate brain and be used to study networks of neurons over long periods of time. This new array provides excellent recording isolation, excellent recording stability, minimum tissue damage (neurons can be isolated within the same piece of tissue for years) and the ability to sample neighboring cells of different types and somata sizes. The array has multiple, closely-spaced, ultra-thin electrodes that can be independently moved with chronically implanted miniature microdrives. While the array has been successfully used for recording in small animal brains, it requires significant enhancements to allow it to fulfill its potential in the primate brain. The first aim of this proposal is to make the electronic and mechanical parts of these arrays resistant to the large accelerations and forces that they will have to bear while being chronically implanted in a primate brain over long periods of time. The second aim is to provide the array with chronic micromotors that will allow moving the electrodes remotely. The third aim is to increase the number of electrodes without compromising the ability to move the electrodes independently. When these arrays are successfully adapted to the primate brain, they will dramatically increase the scientific productivity that can be achieved during daily recording sessions. At the same time, they will allow each primate to be used more efficiently and fulfill two important goals in animal research: to reduce the number of animals used in each research project and refine their use (it is possible to record from a small piece of tissue over a period of several years).The array developed in this proposal will provide the scientific community with a new, powerful tool to study brain circuitry. A detailed knowledge of this circuitry is essential for the development of treatments for the different neurological and psychiatric disorders that affect the human brain.

As we move through our visual environment, the pattern of light that enters our eyes is strongly shaped by the properties of objects within the environment, their motion relative to each other, and our own motion relative to the external world. This collaborative project will quantify motion within natural scenes, record activity from populations of neurons in the early visual pathway in response to the motion, and develop models of motion representation across neuronal populations. The primary goals of the work are to fully characterize the biological representation of motion in natural scenes in the early stages of visual processing that sets the stage for cortical computation critical for visual perception, and to unify the biological findings with computational models of motion from the computer vision community.

The perception of visual motion is critical for both biological and computer vision systems. Motion reveals structure of the world including the relative and absolute depths of objects, surface boundaries between objects and information about ego-motion and the independent motion of other objects. The effects of visual motion on the relationship between spatially localized and global properties of the natural visual scene, and how this is represented by the early visual pathway of the brain, are largely unknown.

This project addresses the computation of local and global properties of natural visual scenes by both distributed neural systems and computer vision algorithms using a novel set of complex naturalistic stimuli in which ground truth properties of the scene are known, and all aspects of the scene, including its reflectance, surface properties, lighting and motion are under investigator control. A unified probabilistic modeling framework will be adopted, that ties together the computational and biological models of properties of the natural scene. Neural activity will be recorded from a large population of densely sampled single neurons from the visual thalamus. From the perspective of the computer vision community, an important challenge exists in inferring the motion of the external environment (or "optical flow") from sequences of 2D images. From the perspective of the neuroscience community, quantifying the distributed neural representation of luminance and motion in the early visual pathway will be a critical step in understanding how scene information is extracted and prepared for processing in higher visual centers. A team of investigators with experience in computer science, engineering, and neuroscience will develop a theoretical foundation and rich set of methods for the representation and recovery of local luminance, local motion boundaries and global motion by brains and machines.

ABSTRACT: Neuronal mechanisms of selective attention in early vision The mechanisms of selective attention have been intensively investigated over the past two decades. As a consequence, there is now a better understanding of the network of brain areas that are involved in visual attention and the responses of individual neurons to attentional shifts. Current models of attention are also one step closer to providing a general framework of attentional circuits that could have direct clinical significance. However, a major limitation of current models is the lack of cellular specificity. Most current models treat each cell within a given cortical area as if it was taken from a random sample of neurons that simply differ in the spatial location of their receptive fields and their selectivity for line orientation and direction of movement. The existence of different cell types with possible different functions is completely neglected. Neurons in different layers, neurons making local and long-range connections and, until very recently, inhibitory and excitatory neurons are all treated equally by models. The main goal of this proposal is to provide the biological data on cell selectivity that is needed to build more realistic and clinically relevant models of visual attention. We aim to characterize the different cell types that are involved in attentional networks in area V1. We also aim to identify populations of neurons with different functions in attention: those involved in enhancing vision at the focus of attention and those involved in suppressing distraction in surrounding areas. We will use state-of-the-art technology to densely sample individual neurons and populations of neurons through the cortical depths of area V1. Our novel technology allows us to study the properties of a given population of neurons for days or months, if necessary. We aim to take advantage of this technology to provide a detailed characterization of attention circuits at different cortical depths of area V1 and identify the task parameters that make attentional modulations strongest.

DESCRIPTION (provided by applicant): The human brain needs to have access to an accurate map of visual space to interpret the images that we see. The most accurate and complete visual map is located in primary visual cortex, where all the basic stimulus properties are thought to be systematically represented, including spatial location, orientation and phase. For example, a vertical dark bar in the middle of this page can be represented in primary visual cortex by its position (point of fixation), orientation (vertical) and phase (dark flanked by light. While previous studies have made important advances in our understanding of how spatial location and orientation are mapped across the primary visual cortex, we still do not know how spatial phase is represented in this map. This is a fundamental gap in knowledge given the importance that phase has in image processing algorithms, which are regularly applied to satellite imagery, medical imaging, videophone and character recognition. Current experimental data suggest that spatial phase is randomly distributed throughout the cortex; however, computational models keep insisting that phase should be clustered in specific regions of the cortical map. Our recent results demonstrate, for the first time, the existence of pronounced clusters for spatial phase that are closely related to the mapping of stimulus orientation in cortex. In addition, we show that dark-dominated phases are better represented than light-dominated ones. The main goal of this research project is to study the organization of these newly discovered cortical maps for spatial phase with a novel approach that takes advantage of recent advances in multielectrode recording and has considerably better spatio-temporal resolution than other methods used in the past. With our multielectrode approach, we will reveal the inter- related organization of visual cortical maps for spatial position, orientation and phase the topography of dark- dominance in these maps and the rules that govern the representation of multiple stimulus dimensions within each 100 x 100 microns of cortex. We will use these measurements to build a detailed database of the multi- dimensional mapping of stimulus features across the visual cortical map and to test current computational models of functional cortical architecture and cortical development.

PROJECT SUMMARY Visual information is transferred from the eye to the brain through ON and OFF pathways that signal the presence of light and dark features in visual scenes. ON and OFF pathways are present in all animals with image-forming visual-systems including flies and primates, however, we still have a poor understanding of how they interact in visual processing. While neuroscience textbooks describe ON and OFF pathways as sharing equal cortical space, recent work has demonstrated that the OFF pathway greatly dominates cortical responses. We hypothesize that this cortical OFF dominance originates from a difference in the contrast response function between ON and OFF pathways that we recently discovered. Because contrast saturation is more pronounced within the ON pathway, light stimuli are spatially distorted and less effective at driving cortical responses than dark stimuli, which causes the cortex to be OFF dominated. Because of this greater spatial distortion for lights, we predict that ON/OFF differences in contrast saturation will have major implications not only in cortical function but also in human visual perception and visual disease. Therefore, this proposal uses the differences in ON/OFF contrast saturation as a conceptual framework to predict and investigate how cortical OFF dominance changes under different stimulation conditions and the implications of these changes for the perception of lights and darks. Our conceptual framework predicts that cortical OFF dominance will increase when the image is out of focus either because of normal changes in lens accommodation (e.g. blurred background when fixating a target at close distance) or visual disease (e.g. amblyopia, myopia). In turn, cortical OFF dominance will decrease when seeing high spatial frequencies with high mean luminance, which are common outdoors. To test our predictions and investigate the dynamics of ON and OFF cortical function, we will measure the responses of cortical single neurons to dark and light targets under a large variety of stimulus conditions (e.g. different contrasts, spatial frequency, mean luminance, luminance distribution). We will then use the same stimulus conditions to measure changes in light/dark visual acuity and visual salience in humans. To fully characterize cortical responses of single neurons to multiple stimulus dimensions, we will use an innovative multielectrode array that we have been developing over the past years to record from well-isolated single neurons for prolonged periods of time. This novel technical approach allows us to obtain an unprecedented characterization of the stimulus space that modulates ON/OFF signaling by testing a large combination of stimulus conditions that could not be fully explored with previous methods.