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Articles 1 - 7 of 7
Full-Text Articles in Neuroscience and Neurobiology
Elucidating And Leveraging Dynamics-Function Relationships In Neural Circuits Through Modeling And Optimal Control, Sruti Mallik
Elucidating And Leveraging Dynamics-Function Relationships In Neural Circuits Through Modeling And Optimal Control, Sruti Mallik
McKelvey School of Engineering Theses & Dissertations
A fundamental research question in neuroscience pertains to understanding how neural networks through their activity encode and decode information. In this research, we build on methods from theoretical domains such as control theory, dynamical systems analysis and reinforcement learning to investigate such questions. Our objective is two-fold: first, to use methods from engineering to identify specific objectives that neural circuits might be optimizing through their spatiotemporal activity patterns, and second, to draw motivation from neuroscience to formulate new engineering principles such as synthesis of dynamical networks for decentralized control applications. We specifically take a top-down, optimization driven approach in our …
Long-Term Neural Activity Recorders Using Energy-Based Sensing, Compressive Computation And Data Logging, Darshit Mehta
Long-Term Neural Activity Recorders Using Energy-Based Sensing, Compressive Computation And Data Logging, Darshit Mehta
McKelvey School of Engineering Theses & Dissertations
Insects are ideal candidates for developing bio-robotic systems owing to their ability to thrive in almost any environment. For example, neurons in their exquisite olfactory sensory systems can be tapped to create a sensing platform for standoff chemical monitoring. However, for enabling such cyborg systems, it is vital that the neural activity of a freely behaving organism can be measured for long periods of time. The current state-of-the-art neural recording techniques are power-intensive and they either need batteries, which make them too bulky for insects, or they have to maintain a continuous telemetry link to an external power source which …
Neural Dynamics, Adaptive Computations, And Sensory Invariance In An Olfactory System, Srinath Nizampatnam
Neural Dynamics, Adaptive Computations, And Sensory Invariance In An Olfactory System, Srinath Nizampatnam
McKelvey School of Engineering Theses & Dissertations
Sensory stimuli evoke spiking activities that are patterned across neurons and time in the early processing stages of olfactory systems. What features of these spatiotemporal neural response patterns encode stimulus-specific information (i.e. ‘neural code’), and how they are translated to generate behavioral output are fundamental questions in systems neuroscience. The objective of this dissertation is to examine this issue in the locust olfactory system. In the locust antennal lobe (analogous to the vertebrate olfactory bulb), a neural circuit directly downstream to the olfactory sensory neurons, even simple stimuli evoke neural responses that are complex and dynamic. We found each odorant …
Constructing And Analyzing Neural Network Dynamics For Information Objectives And Working Memory, Elham Ghazizadeh Ahsaei
Constructing And Analyzing Neural Network Dynamics For Information Objectives And Working Memory, Elham Ghazizadeh Ahsaei
McKelvey School of Engineering Theses & Dissertations
Creation of quantitative models of neural functions and discovery of underlying principles of how neural circuits learn and compute are long-standing challenges in the field of neuroscience. In this work, we blend ideas from computational neuroscience, information and control theories with machine learning to shed light on how certain key functions are encoded through the dynamics of neural circuits. In this regard, we pursue the ‘top-down’ modeling approach of engineering neuroscience to relate brain functions to basic generative dynamical mechanisms. Our approach encapsulates two distinct paradigms in which ‘function’ is understood. In the first part of this research, we explore …
Coupled Correlates Of Attention And Consciousness, Ravi Varkki Chacko
Coupled Correlates Of Attention And Consciousness, Ravi Varkki Chacko
McKelvey School of Engineering Theses & Dissertations
Introduction: Brain Computer Interfaces (BCIs) have been shown to restore lost motor function that occurs in stroke using electrophysiological signals. However, little evidence exists for the use of BCIs to restore non-motor stroke deficits, such as the attention deficits seen in hemineglect. Attention is a cognitive function that selects objects or ideas for further neural processing, presumably to facilitate optimal behavior. Developing BCIs for attention is different from developing motor BCIs because attention networks in the brain are more distributed and associative than motor networks. For example, hemineglect patients have reduced levels of arousal, which exacerbates their attentional deficits. More …
Functional Electrical Stimulation Of Peripheral Nerve Tissue Via Regenerative Sieve Microelectrodes, Matthew Reagan Macewan
Functional Electrical Stimulation Of Peripheral Nerve Tissue Via Regenerative Sieve Microelectrodes, Matthew Reagan Macewan
McKelvey School of Engineering Theses & Dissertations
Functional electrical stimulation (FES) of peripheral nervous tissue offers a promising method for restoring motor function in patients suffering from complex neurological injuries. However, existing microelectrodes designed to stimulate peripheral nerve are unable to provide the type of stable, selective interface required to achieve near-physiologic control of peripheral motor axons and distal musculature. Regenerative sieve electrodes offer a unique alternative to such devices, achieving a highly stable, selective electrical interface with independent groups of regenerated nerve fibers integrated into the electrode. Yet, the capability of sieve electrodes to functionally recruit regenerated motor axons for the purpose of muscle activation remains …
Extrinsic And Intrinsic Control Of Integrative Processes In Neural Systems, Anirban Nandi
Extrinsic And Intrinsic Control Of Integrative Processes In Neural Systems, Anirban Nandi
McKelvey School of Engineering Theses & Dissertations
At the simplest dynamical level, neurons can be understood as integrators. That is, neurons accumulate excitation from afferent neurons until, eventually, a threshold is reached and they produce a spike. Here, we consider the control of integrative processes in neural circuits in two contexts. First, we consider the problem of extrinsic neurocontrol, or modulating the spiking activity of neural circuits using stimulation, as is desired in a wide range of neural engineering applications. From a control-theoretic standpoint, such a problem presents several interesting nuances, including discontinuity in the dynamics due to the spiking process, and the technological limitations associated with …