Philip N. Sabes - US grants

[unreadable] DESCRIPTION (provided by applicant): The mechanisms of sensorimotor adaptation will be studied, focusing on the rapid recalibration of visually guided reaching after exposure to altered visual feedback. This research will use a combination of human psychophysical experiments and computational modeling to gain a detailed understanding of how sensory feedback drives recalibration of the visuomotor map. A virtual reality based psychophysical apparatus will be used to introduce spatial perturbations to the visual feedback of the arm in a manner analogous to the classic "prism adaptation" experiments. A range of psychophysical measurements will be used to quantify the adaptive response at intermediate stages along the transformation from vision to movement including eye-body and body-arm calibration as well as a learned corrective response. This research will focus on three specific aims: (1) A study of the temporal dynamics of visuomotor adaptation. The trial-by-trial statistics of both the motor output and the sensory feedback will be collected and will be used to test several classes of computational models for the "learning rules" that specify how sensory feedback from each single tidal effects the visuomotor map and, consequently, the next movement. (2) A study of spatial generalization in reach adaptation. The effect that feedback from reaches to one target location has on subsequent movements to other target locations will be determined. These patterns of spatial generalization will be used to model the adaptive degrees of freedom of the visuomotor map and to test compositional models of the sequence of transformations from vision and movement. (3) A study of the "credit assignment" problem in reach adaptation: given that error corrective sensory feedback can drive adaptation at multiple stages of the visuomotor pathway, how does the brain determine which loci of adaptation should respond to the feedback from a given movement? Manipulations of the timing of the sensory feedback, the feedback signals that are available, and the extent and shape of the visual perturbations will all be performed, and the distribution of adaptive responses across the visuomotor pathway will be measured. These data will be used to model the rules by which credit assignment is accomplished. The long-term goals of this work are to gain a more quantitative understanding of sensorimotor integration in limb movements and to identify the behavioral and neural bases of reach adaptation, as a model for sensorimotor plasticity in the central nervous system. [unreadable] [unreadable]

stimulus /response

DESCRIPTION (provided by applicant): While great advances have been made in understanding the mechanisms of learning in the single synapse or cell, a large gap remains between this understanding and our knowledge of learning at the behavioral level. We know that the activity of large-scale neuronal circuits gives rise to behavior, yet we have little knowledge of what changes in those circuits during learning or how sensory feedback drives these changes. The biggest impediment to answering these questions is the inability to quantitatively measure large-scale circuit properties (e.g. connectivity between brain areas) or to precisely manipulate the activity patterns across these circuits. Optogenetics offers the potential to bridge this gap by allowing the direct control of neural activation in targeted cell types on the millisecond timescale. The development of these tools is progressing most rapidly in mouse, due to the relative ease of genetic manipulations in that species. In contrast, behavioral and circuit-level studies of learning are most practical and have been most successful in "non-genetic" species. Within our team, we have expertise in studying both the behavioral and neural bases of learning in rat, songbird, and nonhuman primate. We propose to develop the optogenetic tools and experimental techniques required to study the circuit-level mechanisms of learning in these species and to apply these to two specific scientific aims: Aim 1: Determine the functional connectivity of learning-related circuitry and how it is altered by experience. It is widely presumed that learning relies on the ability of instructive signals to drive functional modifications of connectivity in the circuits that underlie behavior. However, the tools for measuring functional connectivity in vivo have been limited. We will overcome this limitation using temporally and/or spatially precise optical activation of neurons within a circuit. Functional connectivity will be measured by recording optical-stimulation-triggered changes in activity in downstream neurons. We will assess how functional connectivity is dynamically altered by learning and by factors that may contribute crucially to learning. Connectivity changes will serve as a mechanistic index of the nature and sites of the plasticity that give rise to behavioral change. Aim 2: Test the causal contributions of patterned activity to learning in vivo. Prior research has generated specific and testable hypotheses about how and where patterned activity drives learning. Yet support for these hypotheses has derived primarily from correlative observations of activity during learning rather than causal tests of the proposed mechanisms. We will use optogenetics to causally test the contributions of patterned activity to learning. We will test the sufficiency of instructive signals by imposing precisely controlled patterns of activity at defined loci in a circuit and test their necessity by eliminating the putative signals for learning. PROJECT NARRATIVE This project is aimed at revolutionizing the study of the mechanisms of learning within large neural circuits in the brain by directly measuring large-scale properties of these circuits and precisely manipulating circuit activity. To accomplish this, we will make use of, and continue to develop, advanced new techniques that permit the control of specific population of neurons using optical stimulation (light). The knowledge and tools that we gain from these studies are likely to find broad application in the search for treatments of neurological disorders.

DESCRIPTION (provided by applicant): The ability to learn from experience is perhaps the most fundamental feature of higher brain function. Even simple behaviors such as goal-directed reaching exhibit rapid and robust adaptation in response to changes in sensory feedback. These forms of learning have been extensively characterized at the behavioral level, and a variety of models have been developed to provide an intuitive understanding of these phenomena. Yet despite this progress, very little is known about how the underlying neural circuits change with learning or how sensory feedback drives these changes. This proposal addresses these questions, focusing on the rapid learning that occurs in response to shifted visual feedback of the arm ("visual-shift adaptation"). It has been shown that when visual feedback of the arm is displaced from the true position, for example with displacing prisms, compensatory shifts are observed in visual localization (where things "look" to be) and proprioceptive localization (where the arm "feels" to be). These shifts bring the two senses back into alignment. In order to uncover the physiological mechanism behind this process, this work will investigate how vision and proprioception are normally integrated in the brain ("sensory integration") and how that process changes with visual-shift adaptation ("sensory recalibration"). This will be accomplished by recording neural activity in several arm-movement related areas in cerebral cortex as animals make sensory guided reaching movements with shifted or unshifted visual feedback of the arm. The activity of large neuronal populations will be simultaneously recorded, permitting direct comparison to existing neural models of sensory integration and recalibration. Aim 1 is to study the cortical mechanism of sensory integration. Quantitative measurements will be made of the visual and proprioceptive contributions to the neural computations that underlie reach planning. Specifically, the relative weighting of visual feedback is inferred from the effect that various visual feedback shifts, included on randomly interleaved trials, have on the population activity. These experiments are designed i) to test whether cortical areas weight sensory inputs, ii) to identify which cortical areas change their weighting with behavior, and iii) to test whether this weighting is consistent with predictions from statistical theory. Aim 2 is to study the cortical mechanism of sensory recalibration. Quantitative measurements will be made of the changes that occur to visual and proprioceptive signals in cortex during extended exposure to a constant visual shift, a situation that drives sensory recalibration. These experiments are designed to determine i) whether the changes in the sensory coding in a given cortical area can be explained by the misalignment of sensory inputs to that area and ii) whether these changes are consistent with predictions from statistical theory. PUBLIC HEALTH RELEVANCE: This project is aimed at discovering new mechanisms of learning in the neural circuits for eye-hand coordination in the cerebral cortex. This work will give us a deeper understanding of how sensory of our movements drives rapid changes in our brains. In addition to its scientific impact, this work has two potential medical applications: i) to aid in the development of sensory prosthetic devices for motor control, and ii) to aid in the development of new, principled therapies for sensory and sensory-motor deficits following stroke.