Stephen G. Lisberger - US grants

My long-range objective is to understand the mechanisms that produce smooth eye movement appropriate to stabilize retinal images. The vestibulo-ocular reflex (VOR) stabilizes images of stationary objects by generating eye movements opposite in direction and nearly equal in amplitude to head movement. Smooth pursuit stabilizes images of small moving objects by generating slow tracking eye movements. Much of our work concerns motor learning in the VOR. Since the oculomotor system provides model in which rigorous techniques can be used to study brain function in behaving monkeys, the work will be relevant to the problem of motor learning in general. Thus, the results may have implications for people who must learn new ways to make old movements, such as individuals who have had strokes, or children born with developmental disorders. In addition, smooth eye movements involve structures near the junction of the brainstem and cerebellum (pontine angle); a complete understanding of the mechanisms of smooth eye movement would facilitate early diagnosis and treatment of tumors and diseases that commonly affect this brain region. Experiments are done in rhesus monkeys that receive liquid rewards for tracking a small, moveable target. 1) Psychophysical experiments will measure the response of the vertical pursuit system to a variety of precisely controlled retinal stimuli. The aim of this project is to determine what retinal inputs can affect pursuit and what inputs are actually used in normal tracking. 2) Single cell recordings will monitor the discharge of cells throughout the VOR pathways during eye movement and vestibular stimulation. Each cell's afferent and efferent connections will be studied using a) rapid changes in head velocity as a vestibular stimulus and b) post-spike averaging in the abducens nucleus. The aim of this project is to determine the connections of cells whose discharge suggests they participate in the VOR. 3) Neurophysiological experiments will investigate the site of neural changes underlying long-term visual modification of the VOR. Rapid changes in head velocity will estimate a cell's sensitivity to vestibular inputs. Extraocular motoneurons will be studied first, to identify in adapted monkeys the nature and magnitude of changes we are looking for. Other brain stem cells will then be studied to identify those that provide the changed inputs.

We request funds to purchase a computer system that will be used by a group of eight integrative neuroscientists for data analysis and neural modeling related to the function of the brain. The computer system, to be purchased from Digital Equipment Corporation, will be based on the reduced instruction set computing (RISC) technology. It would consist of a DECsystem 5900 file server with 6 GB of disk storage and 17 DECstation 5000 workstations. The system will be centralized by running the workstations off the file server to facilitate the sharing of data and programs for analyzing data and for neural modeling. The computer will be a central research tool for, and will reside in the shared computer rooms of, the newly-renovated W.M. Keck Foundation Center for Integrative Neuroscience at UCSF. Research projects that will use the computer system will include: 1) quantitative analysis of the synaptic mechanisms that control the processing of visual information in the retina (Copenhagen); 2) studies of the biophysics of phototransduction in rod photoreceptors (Korenbrot); 3) investigation of the site and mechanisms of motor learning in the vestibulo-ocular reflex and of sensory-motor transformations in the control of pursuit eye movements (Lisberger); 4) studies of use-dependent plasticity in the cerebral cortex of primates and development and analysis of an implantable pediatric cochlear implant (Merzenich); 5) cellular and pharmacological analysis of the integration of synaptic inputs and of long-term potentiation in cells in the hippocampus (Nicoll); 6) analysis of how inputs from cone photoreceptors combine to yield the percept of color (Schnapf); 7) quantitative analysis of the representation and encoding of complex, speech-like sounds in the auditory cortex (Schreiner); 8) investigation of the signals and mechanisms that control the development of the visual cortex in infants (Stryker).

This award provides funds to aid in the purchase of optical microscopy equipment. The equipment will be located in a central facility where it will be available to a group of neuroscientists in the Keck Center for Integrative Neuroscience. The scientists are all interested in various aspects of local circuit analysis of the mammalian central nervous system (CNS). The goal of their studies is an improved understanding of how small groups of neurons generate behavior. The instruments requested will be used for combined anatomical and physiological studies of brain function that include the use of double or triple labeling techniques. The development of new instrumentation for optical microscopy and of new methods that permit specific labeling of certain cells or certain cell constituents has been key to progress in our understanding of many aspects of cellular and developmental biology. Neuroscience has benefited greatly from these developments, since they permit the rapid and reliable identification of particular neurons or groups of neurons in the brain or at other sites that typically contain many nerve cells or similar morphology.

computer network; computer program /software; computer data analysis; computer system design /evaluation; biomedical facility; learning; neural information processing;

The long-term goal of this research is to determine the sites and mechanisms of motor learning in a voluntary movement system that depends heavily on inputs from the cerebral cortex and that uses the cortico-ponto-cerebellar pathways. Smooth pursuit eye movements meet these criteria and therefore afford a model system for revealing principles of motor learning that may generalize to learning of somatic movements. Under normal conditions, a moving target is needed to generate pursuit and the onset of target motion evokes and early eye acceleration at an amplitude related to target speed. Preliminary results have demonstrated that the eye acceleration in this early interval can be adapted to be larger or smaller if the target starts at one speed and, after 100ms, undergoes a step increase of decrease in speed. This learning takes about 30 minutes and is reversible and repeatable over the same time course. In this grant, one aim will use measurements of eye movements before and after learning to determine whether learning is also expressed in the response to a brief perturbation of target motion given during sustained pursuit. A second aim will record the expression of learning in the cerebellar cortex by following the responses of individual Purkinje cells in the floccular lobe before, during, and after learning. The third aim will use microstimulation and recording in extrastriate visual areas MT and MST. Microstimulation at an individual site before and after learning will reveal whether sites of learning are in the pathways from MT and MST to the cerebellum. Recordings will follow the responses of individual cells before, during, and after learning, to reveal whether learning can occur in the cerebral cortex. The final aim will develop a new class of pursuit model that is based on realistic visual inputs and that can reproduce the data obtained here. The results will provide insights into the normal processes of motor learning and may provide information about how to treat and reverse motor disorders, especially those that are learned through repetitive use of the same movement.

Learning is a fundamental property of the brain. In many instances, learning is a positive attribute and it allows groups of neurons to acquire selective responses. The responses of a group of neurons to a given stimulus is called a "central representation", and these exist throughout the brain for processing complex sensory stimuli, or planning and executing complex movements. In other instances, the natural learning mechanisms of the brain are co-opted by noisy or abnormal inputs, leading to disintegration of the central representations that create normal sensation and action. The cerebral cortex has been widely implicated in learning for both sensation and action, and the cellular mechanisms that allow neurons to have plasticity are well known. This Program Project has the long-term goal of understanding how these mechanisms act at a system level to create circuits of neurons that are capable of supporting normal sensation and action. A related long-term goal is to understand how abnormal inputs cause degraded representations, how those degraded representations contribute to neurological disorders, and how to reconstruct order in central representations to relieve the disorders. Four projects support interacting approaches to these long-term goals on four different behavioral systems that rely heavily on the function of the cerebral cortex. Project 1 will continue an investigation of the cortical and cerebellar sites and mechanisms of learning in smooth pursuit eye movements. Project 2 will extend previous analysis of learning to recognize and emit one's own song in the auditory forebrain of song birds. It will investigate learning in earlier auditory areas that are homologous to the different levels of processing in the hierarchy of auditory cortex of mammals. Project 3 will also how speech sounds are represented in the brains of awake primates, and will investigate how the representation is altered when individuals are trained to discriminated different sounds. Project 4 will extend a prior analysis of the sensory correlates of focal dystonia into the motor cortex, and will study a similar dystonia that can be created in the auditory system by providing noise as a primary acoustic stimulus. These studies will elucidate the brain's natural learning abilities and provide new insight into how those abilities might be used to treat neurological disorders arising from abnormal central representations of sensory or motor information.

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SUBPROJECT ABSTRACT NOT PROVIDED

DESCRIPTION (provided by applicant): Smooth pursuit eye movements in primates provide an accessible example of motor behavior guided by sensory inputs. Pursuit movements are controlled by cortical representations of target motion and access some of the same higher cortical regions implicated in planning and decision making. In preliminary work we have shown that pursuit behavior is variable but surprisingly precise, that the variability has a simple structure, and that it can be attributed mainly to errors in sensory estimates of target motion parameters. The surprisingly precise relationship between eye trajectories and target motion is established over time windows of 100 ms durations. Thus, pursuit gives us a remarkable situation - a genuine primate sensory-motor behavior in which the input-output relationship is computational simple, while relevant time scales are short enough that each cell can contribute at most a few spikes. Thus, in the equation in which behavior is a function of neural activity, both sides are much simpler than might have been expected. The potentially combinatorial complexity involved in a complete analysis of the neural code itself and the connection between spike trains and behavior is dramatically simplified. We propose 1) to understand the neural codes for sensory and motor signals at multiple levels of the neural circuit for pursuit, 2) to correlate the activity of single cortical, brainstem and cerebellar neurons with the trial-to-trial variability of motor output in awake, behaving animals, and 3) to bridge the gap from what we can measure (co-variation of neural and behavioral responses in single trials) to what we want to know (architecture and signal processing in the full sensory-motor circuit). The outcome of this line of research will be an understanding of how multiple cortical and sub-cortical areas work together to generate a single kind of voluntary movement. It will have direct impact on how we understand neurological disorders of movement, and on the consequences of disruptions or enhancements of correlations between neurons. Correlations and neuronal oscillations are an important feature of normal motor function, and this project will help us to understand how to understand their malfunctions and to design behavioral therapies to mitigate their disruption in epilepsy, nystagmus, and movement disorders.

DESCRIPTION (provided by applicant): Neural responses are noisy. Yet behavior is remarkably accurate and precise. How is this accomplished? Is variation in neural responses simply noise that needs to be reduced? Or is it an important signal that is used to control behavior and learning? The seven projects in this application for a Conte Center for Neuroscience Research (CCNR) will ask how neural variation is used to drive behavior, determining where noise falls on the continuum from being a detriment for brain function, neutral, or an asset. The responses of a group of neurons for a given stimulus or action is called a "central representation", and these exist throughout the brain for processing complex sensory stimuli, or planning and executing complex movements. The cerebral cortex has particularly variable neural codes, yet has been widely implicated in guiding normal performance and learning for both sensation and action. This CCNR has the long-term goal of understanding the role of variation as a component of the neural code in the cortex and related areas of the basal ganglia. A related long-term goal is to understand how abnormal variation contributes to failures of adaptation, reductions in the precision and accuracy of behavior, and ultimately to the symptoms of neuro-behavioral and neuro- psychiatric disorders. The seven projects have three center-wide specific aims. First, they will characterize the variation in specific neural codes and behaviors and divide the variation into the component that is related to behavior and one that comprises unrelated, or "residual", variation. Second, they will ask whether natural modes of neural modulation such as attention and reward, or chemical modulatory systems, alter neural variation, and thereby behavior. Third, they will investigate the relationship between changes in neural variation and behavioral learning, seeking cause-and-effect relationships. The seven projects will ask these questions on six different behaviors: smooth pursuit eye movements, reaching arm movements, bird song, spatial behavior, auditory processing, and categorization of speech sounds. They will use species including rodents, songbirds, non-human primates, and humans. The ultimate goal of the CCNR will be to understand the relationship between neural variation and normal behavior to enable creation of behavioral and chemical therapies for treating and curing neuro-behavioral disorders.

The auditory cortex exhibits a broad range of response modes spanning from phasic, single spike or binary responses to tonic, multi-spike, sustained random firing sequences per stimulus. The goal of this project is to determine the character of response variability of different types of auditory cortical neurons in the awaken squirrel monkey. This will allow us to assess the potential role and influence of variability on neuronal encoding, and its impact on behavioral performance and to compare the results to other response modalities. To achieve this, it is necessary to obtain simultaneous estimates of neural and behavioral performance in the awaken animal. Response variability will be assessed under three conditions, in the passive listening animal to serve as a baseline, in the animal actively involved in a behavioral sound discrimination task to assess attention effects, and in animals that are highly trained to assess the effects of learning on the expression of response variability. In conjunction with the other projects, these studies will contribute to establishing general rules, across sensory and motor systems, of the nature and role of response variability in the generation of behavior.

Smooth pursuit eye movements are a well-understood behavior with a known neural substrate. Pursuit is generated when a target moves smoothly. It depends on a traditional cortical-cerebellar circuit with inputs from sensory cortex, processing in parietal sensory-motor areas, and motor commands from a frontal motor area. Outputs from the cerebral cortex interact with cerebro-cerebellar circuits and cerebro-basal ganglia circuits to generate motor commands. Much is known about the mean responses of neurons in these areas and how they contribute to the generation of the average pursuit movement. However, the analysis of variation in neural codes and pursuit behavior opens a new vista. The sensory input for pursuit is highly variable, yet the behavior itself is remarkably precise. The presence and ease of quantifying variation in the neural signals and the behavior offers the opportunity to ask where neural variation falls on the continuum from being a negative, neutral, or positive component of the neural generation of behavior. This project will focus on the frontal pursuit area (FPA), near the saccadic frontal eye fields and will ask 3 questions that are tightly linked to the aims of the Conte Center for Neuroscience Research. First, it will ask how much the neural code in the FPA varies and what fractions of the variance are 1) related to the behavior and 2) "residual", unrelated to the behavior. How do these fractions vary over the different phases of a pursuit movement? Second, it will use differential reward and penalty to modulate the distribution of behavioral variation and explore how that variation is effected by changes in the neural variation in the FPA. Third, it will explore neural variation in the FPA during the instructional period for visually-guided learning in pursuit, and during the subsequent expression of learning. The research in this project will contribute to the overall goals of the CCNR by providing an exemplar behavior where narrowly defined, quantitative questions can be answered about the specific roles of neural variation in a tightly controlled and well-understood behavior. In addition, an understanding of how the frontal cortex controls pursuit may help us to understand why schizophrenics have such profound deficits in smooth pursuit eye movements.

Response variability is a fact of the brain. There can be dramatic differences in the responses of[unreadable] any given neuron, to any given stimulus, at different moments in time. Different neurons in any[unreadable] cortical area contributing to the representation of any given stimulus or action commonly have[unreadable] substantially different responses. Variations in distributed local, system, and brain-wide responses[unreadable] representing any given stimulus in any given behavioral context can differ radically in different[unreadable] individuals. At the same time, the brain operates with the maintenance of perceptual constancy,[unreadable] cognitive reliability, and learned-behavior stereotypy. How do we account for the robust behavioral[unreadable] representations of inputs and actions in the face of the marked response variability of their[unreadable] neurological representations? This project will address 3 issues. First, it will determine the basic[unreadable] consequences, for neurological response variability, of exposing neonatal rats across the critical[unreadable] period with stereotyped vs naturally variable complex acoustic (speech-like) stimulus sets. Second,[unreadable] it will determine whether or not and how systematically varying the modulatory inputs enabling[unreadable] learning-induced plasticity in adult brains contribute to distributed neuronal response variability and[unreadable] coordination, and to behavioral response variability, in an auditory stimulus recognition task. Third,[unreadable] it will investigate the relationships between variation in neuronal responses in the primary auditory[unreadable] cortex (A-1) and in "secondary" auditory cortical fields (PVAF; AAF; PAF;PPVAF), as a function of[unreadable] stimulus repertoire complexity, in trained adult rats. The long-term goal of this project is to[unreadable] determine how a neurological strategy of learning-driven abstraction and coordination can lead to[unreadable] new insights into how we can potentially revise learning strategies to improve their effectiveness[unreadable] and reliability for neuro-behaviorally impaired human populations.

Vocal learning by songbirds provides a model for studying general mechanisms of sensorimotor learning with particular relevance to human speech learning. For both songbirds and humans, hearing the sounds of others, and auditory feedback of oneself, plays a central role in vocal learning. Our previous work suggests that a basal ganglia-forebrain pathway participates in processing auditory feedback and in driving experience-dependent changes to vocalizations. Moreover, these experiments suggest that variability introduced from basal ganglia circuitry to song motor structures and behavior may play a crucial role in enabling song plasticity. Here, we propose to further test this idea by combining behavioral and neural approaches to study contributions of variability to song production and plasticity. We will use chronic recordings from basal ganglia circuitry and song motor structures in singing birds to characterize normal levels of behavioral and neural variation as well as to examine neuron-neuron and neuron-behavior co-variation (Aim 1). We will then use feedback manipulations in adult birds to drive adaptive changes in song and study the relationship between behavioral variability and the capacity for plasticity (Aim 2). Finally, we will monitor and manipulate activity (via chronic recordings and lesions) during conditions of adaptive plasticity to investigate mechanisms underlying the generation of neural variability and their requirement for behavioral change (Aim 3). Songbirds provide a system where the influence of performance-based feedback on a well-defined and quantifiable behavior potentially can be understood at a mechanistic level. Such an understanding will provide basic insight into normal learning processes and contribute to our ability to prevent and correct disabilities that arise from dysfunction of these processes.

This research core provides veterinary nurse support for the Conte Center for Neuroscience[unreadable] Research (CCNR), operates a survival surgery, and manages regulatory compliance for the CCNR.[unreadable] It comprises 75% time for two veterinary nurses. The surgical component of the core provides and[unreadable] operates a survival surgery that is used for all of our surgical procedures on non-human primates,[unreadable] as well as some smaller animals. The veterinary nursing component of the core manages all[unreadable] animal welfare and health issues for all species used in the research of the CCNR. This includes[unreadable] environmental enrichment for non-human primates, daily health checks for all species, and serving[unreadable] as the interface between the UCSF veterinarians and the animal husbandry technicians. The[unreadable] regulatory component involves assisting in the preparation of animal protocols for approval by the[unreadable] IACUC, managing the pre- and post-surgical documentation that is required by the IACUC, and[unreadable] conducting regular inspections of the laboratories to ensure that we are in compliance in the event[unreadable] of an unannounced inspection from the IACUC or the USDA.

In songbirds, a discrete neural circuit is devoted to the learning and production of a stereotyped vocal motor behavior, song, providing a useful model for studying brain mechanisms of behavior, with strong relevance to human speech learning. In particular, a specialized 'cortical'-basal ganglia circuit known as the anterior forebrain pathway (AFP) is crucial for song learning and plasticity throughout life. Recent evidence from our lab and others has revealed that the AFP provides a source of variability potentially important for learning to the motor circuit. In addition, we have found that the outflow nucleus of the AFP, 'LMAN', switches from bursty, highly variable firing when birds sing alone, to more reproducible firing when birds sing to a female, suggesting that social cues could be important in the control of variability. The two social states of LMAN activity are associated with high and low variability song, respectively. Here we propose to further investigate the function of AFP variability by examining and then manipulating the circuit and neurotransmitter mechanisms that give rise to it. We will record chronically from cells in the basal ganglia inputs to LMAN as well as from LMAN neurons, to study where the social context-dependent variability of firing emerges and how it travels across this circuit. We will also measure how correlated LMAN firing is across neurons, to assess how variability may be 'read out'to the motor pathways, and how it relates to behavior (Aim 1). We will then alter the levels of the neuromodulators norepinephrine (NE) and dopamine (DA) both in adults (Aim 2) and in juveniles in late sensorimotor learning (Aim 3), and examine the effects on AFP activity and on song, to test the hypothesis that these neurotransmitters regulate neural and consequently behavioral variability. The song system provides a tractable model for studying the mechanisms by which social and other environmental cues act on the nervous system and ultimately affect behavioral output, both normally and in disease. Understanding these mechanisms has the potential to provide insights into the many neuropsychiatric disorders that have their locus in cortical-basal ganglia circuits.

? DESCRIPTION (provided by applicant): The cerebellum is critical for learning of motor skills. Since the 60's and 70's, the field has been working within the framework of the cerebellar learning theory: climbing fiber inputs to the cerebellum signal errors in movements; the conjunction of climbing fiber inputs and parallel fiber activity leads to depression of the synapse from active parallel fibers onto Purkinje cell dendrites; this long-term depression (LTD) causes changes in the simple-spike firing of Purkinje cells on subsequent movements; and the change in cerebellar output causes gradual improvements in motor performance and eliminates motor errors. Subsequent behavioral and neural studies suggest that learning is mediated by multiple plasticity mechanisms at several brain sites. The present proposal uses the smooth pursuit eye movements of awake, behaving monkeys to understand how a full neural circuit single organizes motor skill learning. The proposal first will describe the time course of development of multiple components of behavioral learning, especially a component that requires repetition of learning stimuli to consolidate. Next, the proposed experiments will study neural correlates of the different components of learning in three different areas in the cerebellar circuit for pursuit eye movements; Purkinje cells in the floccular complex, their target neurons (FTNs) in the vestibular nucleus, and Purkinje cells related to pursuit in the oculomotor vermis. The floccular complex already has been implicated in a single-trial component of learning, and the proposed research will ask whether consolidated learning also is represented there. Recordings from the other areas will allow quantitative conclusions about the extent to which neural learning is localized in the floccular complex, and whether multiple components of learning evolve over different time courses at different sites in the circuit. Motor skill learning is an essential mechanism for allowing humans to relearn old movements after strokes, and for maintaining excellent motor function as the nervous system ages. An understanding of the neural circuit mechanisms of motor learning should facilitate clinical approaches in motor disorders and stroke.

Abstract The cerebellum is critical for learning and executing coordinated, well-timed movements. The cerebellar cortex seems to have a particular role in learning to time movements. Since the 1960's and 70's, we have known the architecture of the cerebellar microcircuit, but most analyses of cerebellar function during behavior have focused on Purkinje cells. Here, we propose to investigate the cerebellar cortex at an entirely new level by asking how the full cerebellar microcircuit ? mossy fiber, granule cells, Golgi cells, molecular layer interneurons, and Purkinje cells ? performs neural computations during motor behavior and motor learning. We strive to ?crack? the circuit by identifying all elements, recording their electrical activity during movement and learning, and reconstructing a neural circuit model that reproduces the biological data. We will use three established learning systems that all can learn predictive timing: classical conditioning of the eyelid response (mice), predictive timing of forelimb movements (mice), and direction learning in smooth pursuit eye movements (monkeys). Our proposal has six key features. First, optogenetics (in mice) will link the discharge of different cerebellar interneurons during movement and learning to their molecular cell types. Second, a machine-learning clustering analysis (in mice and monkeys) will find analogies among the cell populations recorded in our three preparations and will classify neurons according to their putative cell types based on recordings of many parameters of non-Purkinje cells during movement and motor learning. Third, multi- contact electrodes will allow us to record simultaneously from multiple neighboring single neurons and compute spike-timing cross-correlograms (CCGs) to identify the sign of connections; we also will look for changes in CCGs that provide evidence of specific sites of plasticity during learning. Fourth, gCAMP imaging of the granule cell layer will reveal the temporal structure of inputs to the cerebellar microcircuit, and determine whether those inputs are modified in relation to motor learning. Fifth, a model neural network with realistic cerebellar architecture will reveal a single set of model parameters that will transform the measured inputs to the cerebellum in our three movement systems to the measured responses of all neurons in the cerebellar cortex. Sixth, the model will elucidate how mechanisms of synaptic and cellular plasticity at different sites in the cerebellar microcircuit work together to cause motor learning.