Nicholas J. Priebe - US grants

DESCRIPTION (provided by applicant): One strategy the brain uses to process information rapidly is the use of multiple parallel pathways to analyze different aspects of the world simultaneously. The analysis of a visual scene is thought to be segregated into three parallel pathways dedicated to the processing of color, shape, and motion. During this fellowship we will study the neuronal mechanisms that underlie the third pathway, motion selectivity, in visual cortex. Motion processing in V1 requires cortical neurons that respond selectively to the direction and speed of moving objects in the world. Direction selectivity is a neuronal response property that is created de novo in V1 neurons: it is not present in the neurons of the lateral geniculate nucleus (LGN) that provide visual input to the cortex. Unlike other purely spatial response properties such as orientation selectivity, direction selectivity requires processing in the time domain as well as the space domain: direction selective neurons must discern not only where an object is, but where it was in the previous moment. Direction selectivity is therefore thought to be created by combining inputs from LGN neurons with different receptive field positions and different temporal delays. We will investigate how the signals from the LGN are transformed and combined to give neurons in V1 their directionally selective responses. By studying and understanding direction selectivity, we will learn the rules of information processing that may apply generally to cortical processing of temporal information.

DESCRIPTION (provided by applicant): Visual cortex is the site at which dramatic transformations in neuronal receptive field properties - and thus the representation of the visual world - occur. One important transformation is the integration of inputs from the right and left eyes (binocularity), which provides the basis for the representation of the visual world in three dimensions. The excitatory input that individual cortical neurons receive from the visual thalamus is segregated into right and left eye channels. While it is clear that visual cortex is the site at which these two streams of information converge for the first time, the roles that afferent excitation, cortical inhibition and spike threshold all play in creating a three- dimensional representation - stereo vision - are as yet unknown. Using whole cell recordings in vivo, I will investigate the emergence of binocularity and the contributions of these three mechanisms. The development of stereovision is sensitive to the visual environment: disruptions early in life, such as eye misalignment (strabismus), lead to persistent stereo deficits. Early strabismus causes cortical neurons to become highly monocular in their spiking response profiles. The effect of strabismus on the inputs to the cortical neurons is unknown. I will examine whether latent inputs exist in strabismic animals, which will allow me to determine if the changes in cortical cell responses are due to an anatomical reorganization of afferents or a physiological modulation that leaves latent inputs intact and potentially recoverable. PUBLIC HEALTH RELEVANCE: Visual cortex is the site at which inputs from the right and left eyes are first integrated to provide a basis for the representation of the visual world in three dimensions (stereo vision). Proper stereo vision is disrupted by a difference in acuity between the two eyes (anisometropia) or misaligned eyes (strabismus) occurring during development. By understanding the mechanisms underlying both normal and abnormal visual function, we will gain insight into how normal vision may be restored in patients with related visual deficits.

DESCRIPTION (provided by applicant): Over the past four decades, intracellular recordings from sensory cortex of anesthetized animals have made major contributions to our understanding of cortical processing, providing a window into the synaptic inputs that shape spiking responses of individual cortical neurons. To date, however, intracellular recording has not been applied in awake, behaving primates. By combining the unique expertise from our two laboratories, we have recently developed novel techniques that allow us to conduct, on a routine basis, reliable, whole-cell intracellular recordings in primary visual cortex (V1) of awake, behaving monkeys. For the first time, we have access to both subthreshold (membrane potentials representing input) and suprathreshold (spikes representing output) responses of individual cortical neurons, while also utilizing the precise control of visual stimulation and the subject's behavioral state afforded by behaving primates. Our ability to perform intracellular recordings in awake, behaving primates opens the door to addressing two fundamental questions with respect to the circuit-level mechanisms that mediate visual perception: (1) what is the relationship between sub- and supra-threshold activity of single cortical neurons and perceptual decisions, and (2) what are the underlying mechanisms of top-down attentional modulations in sensory cortex. To address these questions, we will first study the quantitative relationship between variability in sub- and suprathreshold responses of single V1 neurons and variability in perceptual decisions of monkeys performing a demanding visual detection task (Aim 1). In Aim 2, we will examine how sub- and suprathreshold responses are altered by changing the attentional state under which the stimulus is presented. We present preliminary data demonstrating that these recordings are not only technically feasible, but are also able to provide important and unique insights into the cellular and circuit-level mechanisms that mediate cortical sensory processing.

DESCRIPTION (provided by applicant): Visual cortex (V1) is the site at which dramatic transformations in neuronal receptive field properties - and thus the representation of the visual world - occur. One of the major transformations is the emergence of orientation selectivity. The functional organization of orientation selectivity in V1, however, takes different forms across species. In primates and carnivores it is topographically organized across cortex but in rodents no apparent organization is observed, yet rodents still exhibit orientation selectivity. Models tha describe the emergence of orientation selectivity have relied on the functional organization found in primates to guide connectivity between neurons that share selectivity. Two different hypotheses have been proposed to explain the emergence of orientation selectivity without functional organization in rodent V1. In one hypothesis, a specific synaptic connectivity between neurons with shared orientation preference may nonetheless exist without topographic organization of cortex. Alternatively, a computational study has now demonstrated that orientation selectivity may arise from non-specific network connectivity, with the constraint that the excitatory and inhibitory inputs are balanced (balanced network model). These two hypotheses are not mutually exclusive, and evidence for both hypotheses currently exists, but the degree to which each of these hypotheses reflects the actual connectivity underlying orientation selectivity in rodent V1 is unclear. The goal of our proposal is to address the relativ contributions of the balanced network and specific cortical connectivity to the generation of V1 orientation selectivity using experimental and computational studies. The proposed research is divided into three Specific Aims that will be carried out collaboratively and will integrate theory and experiment. Aim 1: What is the nature of the LGN input into layer 4 of V1 and how does layer 4 transform this input? In species with an orientation map, the LGN neurons afferent inputs are precisely arranged. Is this also true for species without an orientation map, and how does subcortical selectivity impact cortical selectivity? Can we explain the mechanism for orientation selectivity using a balanced network? Aim 2: Is the cortical connectivity specific? If V1 operates in the balanced state, strong orientation selectivity will arise in layer 2/3, whether or not the connectivity is feature dependet. We will measure the orientation dependence of input correlations and integrate any specific connectivity into a balanced model. Aim 3: How does disturbing the balanced state affect the cortical response? Our hypothesis is that the V1 operates in balanced excitation and inhibition regime. Perturbing this balance will be investigated theoretically and experimentally. Despite decades of study as the prime example of sensory processing, how V1 transforms incoming visual information is not well understood. It is not clear for example, whether feature specific connectivity is required to perform its function. I species with an orientation map, feature specific connectivity is not easily distinguished from connectivity that is solely dependent on anatomical distance because the anatomical and functional maps are linked. The lack of an anatomical organization for orientation selectivity in rodent V1 therefore presents us with an opportunity to study circuitry in a system in which the functional selectivities of neurons are independent of their location within the cortical network. Our proposal represents an integrative collaboration between theoreticians and experimentalists that will create an environment for students and postdoctoral fellows from different background to work side-by-side, gaining access to distinct expertise and perspectives. The collaboration represents a major effort for scientists to work in partnership between France and the US. This partnership will provide students from both France and the US the opportunity to participate in science outside of their home country. The proposed computational and experimental lab work is ideal for the training of students and postdoctoral fellows with backgrounds in physics, engineering or biology. It will be an excellent opportunity for theorists t see and participate in experiments, and for experimentalists to explore a theoretical perspective.

? DESCRIPTION (provided by applicant): The system that controls smooth pursuit eye movements is one of the most accessible, promising systems for understanding how neural circuits transform sensory inputs into actions. Pursuit is a natural, ecologically- relevant behavir that allows primates to track moving objects of interest in the visual world. Now-classical analyses relating neural activity to behavior have already provided insights about the systems-level functions and computations of the pursuit circuit that perhaps exceed our understanding of all other voluntary behaviors in mammals. Despite these successes, there are large gaps in our understanding of the pursuit system. We seek a new level in understanding the circuit by measuring and manipulating the activity of large populations of identified neurons in the key sensory and prefrontal cortical areas. We intend to address how different neuronal types function during pursuit, how they implement systems-level computations within micro- and meso-circuits, and how control centers select the appropriate sensory data given cognitive factors. These questions, although stated in the context of the pursuit system, are instances of the more general problem of how population activity in large numbers of sensory neurons is parsed and converted into appropriate behaviors. The time is now ripe to take advantage of several technical and conceptual revolutions: Specifically, we propose to study the neural basis of pursuit eye movements in marmosets, in which cortical areas responsible for motion sensation and target selection are easily accessed and for which genomic toolboxes are being generated. We will investigate the functional circuitry at multiple scales using a combination of 2-photon calcium imaging and large-scale extracellular array electrophysiology, cell-type identification and optogenetic perturbation, and dynamical systems modeling.

Project Summary A fundamental goal of systems neuroscience is to describe how sensory inputs are integrated and guide an animal's behavior. To be able to integrate these inputs, early sensory systems have developed selectivities for specific stimulus features that allow them to analyze the inputs using these features as basis. A classic example is the emergence of orientation selectivity within the visual cortex (Hubel and Wiesel, 1962). Successive processing stages in the early visual system perform systematic transformations on the incoming inputs that enable them to be able to identify multiple aspects of the visual scene important for guiding an animal's behavior, including the location, shape, depth and motion of objects. While the unique feature selectivities emerging at different stages in visual processing are known to a certain extent, the nature and mechanisms of these sensory transformations less well-understood. We aim to uncover how disparate motion signals are integrated to produce a global percept of motion, and to understand the conditions in which such integration fails.

A fundamental goal of systems neuroscience is to describe how sensory inputs are integrated and guide an animal's behavior. To be able to integrate these inputs, early sensory systems have developed selectivities for specific stimulus features that allow them to analyze the inputs using these features as basis. We aim to uncover how disparate motion signals are integrated to produce a global percept of motion, and to understand the conditions in which such integration fails. Our proposal reflects the fact that adaptive behaviors in complex environments face numerous challenges, from processing noisy and uncertain visual motion information to predict future events on target trajectory contingencies and its interactions with a dynamic, cluttered environment. We propose to use dynamic inference as an efficient theoretical framework to understand how the brain integrates Prior knowledges elaborated from statistical regularities of natural environments with different sources of information across different time scales in order to extract relevant motion information from the sensory flow and predict future events or actions. The smooth pursuit system is an excellent probe of such hierarchical dynamical inferences from target motion computation to target trajectory prediction. In marmosets, we have access to populations of neurons in pivotal cortical areas along the occipito-parieto- frontal network that have been identified in non-human and human primates. We seek to uncover a unifying empirical and theoretical framework to capture inference across different time scales. RELEVANCE (See instructions): We will examine how incoming sensory signals interact with prior experiences to guide behavior, using dynamic inference as a theoretical framework. This study uses a specific tracking behavior (smooth pursuit) to shed light on the fundamental problem of how the coordinated activity of large populations of sensory neurons is parsed and converted into appropriate behaviors in the face of changing contexts, uncertainty, and noise, a process disrupted in neurological disorders such as schizophrenia.