Maxim Volgushev - US grants

DESCRIPTION (provided by applicant): Every neuron in the neocortex receives thousands of synapses from thousands of other neurons. Activation of only a portion of them, dozens to hundreds, may evoke cell firing and under certain conditions induce plasticity. Input-specific associative plasticity is believed to be the synaptic mechanism of learning and memory. However, just as new learning always takes place on a background of existing memories, so synaptic plasticity is always induced on a background of existing distribution of synaptic weights. To understand how neurons achieve new learning while preserving existing information, we need to know, how the induction of plasticity at a specific group of synapses interacts with the existing pattern of synaptic weights. It is crucial, therefore, to understand the rules that govern heterosynaptic plasticity i.e. changes at synapses which were not active during plasticity induction. Our proposal is aimed at this question. Using in vitro slices of rodent neocortex, we will record excitatory postsynaptic potentials in major types of neocortical neurons: pyramids from layer 2/3 and 5, spiny cells from layer 4 and inhibitory interneurons. We will study plastic changes, induced in these cells by intracellular tetanization - bursts of short depolarizing pulses that evoke in vivo-like firing patterns in the postsynaptic neuron without presynaptic activity. We will ask, how heterosynaptic plasticity is induced at different types of synapses (Aim 1), how it interacts with plasticity induced by temporal coincidence (pairing) or afferent tetanization, and why it leads to mixed effects: potentiation, depression or no change (Aim 2). We will implement the rules derived in the above experiments in detailed models of major types of neocortical neurons. With these models we will examine changes of synaptic weights and their distribution during patterns of input activity typical for neurons in vivo and during multiple applications of plasticity induction protocols (Aim 3). This combined experimental and theoretical approach will allow us to achieve the long-term goal of the proposal: to understand how single neurons combine the ability for learning new while retaining existing memory traces, and how heterosynaptic plasticity helps to resolve this dilemma. This new knowledge will stimulate research and understanding of mechanisms of disorders that affect learning new and remembering previously learned information by humans. The National Center for Learning Disabilities estimates that five percent of the United States population or fifteen million people are affected by learning disorders. Three million school students receive special help because of learning disabilities. Research of learning disorders and development of new therapies will improve the quality of life of the affected people and bring economic benefits from healthcare. PUBLIC HEALTH RELEVANCE: The National Center for Learning Disabilities estimates that five percent of the United States population, or fifteen million people are affected by learning disorders. The goal of this project is to understand how neurons achieve new learning while preserving the old memories. This new knowledge will stimulate research and understanding of mechanisms of disorders of learning and remembering in humans and development of new diagnostic tools and therapies.

DESCRIPTION (provided by applicant): Every neuron in the neocortex receives thousands of synapses from thousands of other neurons. Activation of only a portion of them, dozens to hundreds, may evoke cell firing and under certain conditions induce plasticity. Input-specific associative plasticity is believed to be the synaptic mechanism of learning and memory. However, just as new learning always takes place on a background of existing memories, so synaptic plasticity is always induced on a background of existing distribution of synaptic weights. To understand how neurons achieve new learning while preserving existing information, we need to know, how the induction of plasticity at a specific group of synapses interacts with the existing pattern of synaptic weights. It is crucial, therefore, to understand the rules that govern heterosynaptic plasticity i.e. changes at synapses which were not active during plasticity induction. Our proposal is aimed at this question. Using in vitro slices of rodent neocortex, we will record excitatory postsynaptic potentials in major types of neocortical neurons: pyramids from layer 2/3 and 5, spiny cells from layer 4 and inhibitory interneurons. We will study plastic changes, induced in these cells by intracellular tetanization - bursts of short depolarizing pulses that evoke in vivo-like firing patterns in the postsynaptic neuron without presynaptic activity. We will ask, how heterosynaptic plasticity is induced at different types of synapses (Aim 1), how it interacts with plasticity induced by temporal coincidence (pairing) or afferent tetanization, and why it leads to mixed effects: potentiation, depression or no change (Aim 2). We will implement the rules derived in the above experiments in detailed models of major types of neocortical neurons. With these models we will examine changes of synaptic weights and their distribution during patterns of input activity typical for neurons in vivo and during multiple applications of plasticity induction protocols (Aim 3). This combined experimental and theoretical approach will allow us to achieve the long-term goal of the proposal: to understand how single neurons combine the ability for learning new while retaining existing memory traces, and how heterosynaptic plasticity helps to resolve this dilemma. This new knowledge will stimulate research and understanding of mechanisms of disorders that affect learning new and remembering previously learned information by humans. The National Center for Learning Disabilities estimates that five percent of the United States population or fifteen million people are affected by learning disorders. Three million school students receive special help because of learning disabilities. Research of learning disorders and development of new therapies will improve the quality of life of the affected people and bring economic benefits from healthcare.

Understanding how visual information is processed during natural behavior is a fundamental problem of neuroscience. Despite recent insights from research in alert head-fixed subjects, it remains largely unknown how visual processing is affected by active behavior: self-motion and active selection of visual targets for serving on-going behavior. Proposed research aims to establish a unique experimental paradigm of active vision in freely moving cats during natural locomotion, while testing a specific hypothesis that visual processing is shaped by the needs of on-going behavior. This new paradigm builds on complementary strength of visual and motor physiology, and allows to study vision under conditions in which it is naturally used: during coordinated and coherent motor activity, sensory feedback, allocation of attention and dynamically changing visual input. Cats readily walk in environments that impose different demands on accuracy of stepping and vision: from simple flat surfaces (low demand) to stepping on elevated objects (high demand). Using this robust and repetitive natural behavior we will measure (i) visual input, (ii) neuronal activity, and (iii) behavioral output. We will take footage from a head-fixed camera and record the eye position, gaze trajectory, and biomechanics of head and body. Using these measurements, we will calculate visual input in retinotopic and body-centric coordinates. While cat is walking, we will record activity of neurons in primary visual (a.17 and a.18) and multisensory parietal (a.5b) cortical areas. We will use reverse-correlation to reconstruct receptive fields of neurons in retinotopic and body-centric coordinates. To measure behavioral output, we will use state-of-the-art 3-dimensional analysis of biomechanics of head, body and limbs, and the accuracy of steps. To determine how the needs of locomotion shape visual processing we will use environments with different demands on accuracy of stepping and visual information: from low demand (walking on flat surface) to high demand (stepping on elevated platforms). Our overarching hypothesis maintains that processing in visual cortex is task-dependent: higher demands on accuracy of stepping lead to an increasing precision of space representation in visual system. Our Specific Aim is to understand how demands of locomotion task shape visual input and processing of visual information. We hypothesize that higher demands on precision of visual information for locomotion will be met by increasing both precision of visual input by more frequent fixations on locations for future foot placement, and precision of visual processing by increasing the strength of visual responses and decreasing the size of visual receptive fields. We will ask: (1a) How the visual input, determined by the pattern of gaze behavior, changes during locomotion in diverse environments; and (1b) How visual responses and receptive fields change during locomotion in environments with different demands on vision. Obtained results will provide (i) rigorous testing and validation of the new experimental paradigm for research into active vision; and (ii) tests for our hypothesis, that during locomotion in environments with higher requirements on accuracy of stepping and higher demand on visual information, visual responses will be stronger and receptive fields smaller than during locomotion in low-demand environments. This new knowledge will aid the development of new rehabilitation strategies for patients with deficits in using vision during locomotion.