Design, Implementation and Analysis of Functional Activity and Connectivity in Patterned Neural Networks

The central theme of this dissertation deals with investigating the issues related to the functional connectivity of biological neuronal networks. In particular, low density neuronal cultures grown on predefined patterns are found to provide suitable test beds for such studies. Likewise, microelectrode array technology serves as a valuable platform for conducting experiments in which simultaneous recording and stimulation of multiple sites within a neuronal network is of interest. This dissertation begins by describing techniques in which low density neurons can be patterned on microelectrode arrays with the aim of creating engineered networks of neurons that are functionally active and highly compliant to the imposed patterns over extended periods of time. This is followed by a discussion of the instruments required for such studies. In many cases, the nature of the experiment necessitates certain technological capabilities, while in reality the available commercial instruments pose a limitation on the feasibility of experiments. Here, a few tools have been developed in order to overcome some of the technological challenges and thereby provide more freedom and creativity in designing experiments. The last and perhaps the longest section of the dissertation is devoted to experiments aimed at mapping and analyzing the apparent functional connectivity in a network of neurons. Applying electrical stimulation on a short time scale is shown to provide a means of assessing connectivity. It has also been shown to have modulatory effects on the degree of network responsiveness. The dissertation ends by briefly considering the role of long-term chronic stimulations on the functional development of in vitro neuronal networks and their patterns of activity. It draws parallels between an intact brain, which is in a state of constant flux adapting to the signals that it continually receives from the external environment and a brain-on-a-chip. The ultimate goal is to further our understanding of the former, by observing and analyzing the behavior of the latter in response to various stimulation paradigms.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Khatami, David Behnam

Contributors dc:contributor

• Wheeler, Bruce C.

• Biology, Neuroscience

Language dc:language

eng

Identifier

(MiAaPQ)AAI3347401

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/81114