Files in this item



application/pdfRENTERIA-THESIS-2019.pdf (6MB)Restricted Access
(no description provided)PDF


Title:Computational tools for monitoring neural connectivity using calcium imaging
Author(s):Renteria, Carlos
Advisor(s):Boppart, Stephen A.
Department / Program:Bioengineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Calcium imaging
Fiber bundle
Abstract:The development of optogenetics and calcium imaging have enabled light-activated manipulation and monitoring of neural activity that offer powerful alternatives to traditional electronic and chemical methods. Along with light-evoked activity, many technical advancements have been made that allow for facilitated optical delivery, activation, and recording of neural dynamics. These include fiber-optic cables for targeted optical delivery, genetically encoded calcium indicators (GECI) for optically measuring signaling dynamics, fiber bundles for spatially targeted delivery, and optical system design for adequate integration of these technologies. Recently, this field has grown substantially, with the goal to understand neural communication based on signals transmitted between cells that lead to brain-level function. In addition to optical and genetic advancements, equally important are methods for assessing both single-cell and network-level behavior. With high volumes of data from video-rate optical imaging and stimulation systems, comes the challenge of analyzing their trends. This is especially true for inferring network-level behavior, given the limited field-of-view inherent in optical systems. In addition, when using fiber bundles, either for in vitro or in vivo experiments, there are inherent artifacts that obscure the underlying imagery, hindering data interpretation and analysis. The goal of this thesis is twofold: to present an algorithm developed for assessing network dynamics from calcium imaging data, and an algorithm aimed at removing the pixilation artifact from fiber-bundle images. The neural connectivity algorithm could be used to reveal connectivity between neurons. Furthermore, a map of connectivity in neural cultures could be developed to showcase the network structure in neural preparations. By integrating these into optical systems, underlying network behavior can be identified and better understood, and directed electromagnetic manipulation of neural circuits can be realized. These algorithms, coupled with all-optical approaches to assess network dynamics, provide a powerful tool that when fully integrated, will allow for closed-loop optogenetic feedback mechanisms in brain cultures, slices, and retinal samples to potentially evoke known and desired responses.
Issue Date:2019-04-17
Rights Information:Copyright 2019 Carlos Renteria
Date Available in IDEALS:2019-08-23
Date Deposited:2019-05

This item appears in the following Collection(s)

Item Statistics