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Identification and control of neural circuit dynamics for natural and surrogate inputs in-vivo

A principal goal of neural engineering is to control the activation of neural circuits across space and time. The ability to control neural circuits with surrogate inputs is needed for the development of clinical neural prostheses and the experimental interrogation of connectivity between brain regions. Electrical stimulation provides a clinically viable method for activating neural tissue and the emergence of optogenetic stimulation has redefined the limitations on stimulating neural tissue experimentally. However, it remains poorly understood how these tools activate complex neural circuits.

The goal of this proposed project was to gain a greater understanding of how to control the activity of neural circuits in-vivo using a combination of experimental and computational approaches. Voltage sensitive dye imaging was used to observe the spatiotemporal activity within the rodent somatosensory cortex in response to systematically varied patterns of sensory, electrical, and optogenetic stimulation. First, the cortical response to simple patterns of sensory and artificial stimuli was characterized and modeled, revealing distinct neural response properties due to the differing synchrony with which the neural circuit was engaged. Then, we specifically designed artificial stimuli to improve the functional relevance of the resulting downstream neural responses. Finally, through direct optogenetic modulation of thalamic state, we demonstrate control of the nonlinear propagation of neural activity within the thalamocortical circuit.

The combined experimental and computational approach described in this thesis provides a comprehensive description of the nonlinear dynamics of the thalamocortical circuit to surrogate stimuli. Together, the characterization, modeling, and overall control of downstream neural activity stands to inform the development of central nervous system sensory prostheses, and more generally provides the initial tools and framework for the control of neural activity in-vivo.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/53405
Date08 June 2015
CreatorsMillard, Daniel C.
ContributorsStanley, Garrett B.
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Languageen_US
Detected LanguageEnglish
TypeDissertation
Formatapplication/pdf

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