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In presenting this thesis as a partial fulfillment of the requirements for an advanced degree from Emory University, I agree that the Library of the University shall make it available for inspection and circulation in accordance with its regulations governing materials of this type. I agree that permission to copy from, or to publish, this thesis may be granted by the professor under whose direction it was prepared, or, in his absence, by the Dean of the Graduate School when such copying or publication is solely for scholarly purposes and does not involve potential financial gain. It is understood that any copying from, or publication of, this thesis that involves potential financial gain will not be allowed without written permission.





In presenting this thesis as a partial fulfillment of the requirements for an advanced
degree from Emory University, I agree that the Library of the University shall make it
available for inspection and circulation in accordance with its regulations governing
materials of this type. I agree that permission to copy from, or to publish, this thesis may
be granted by the professor under whose direction it was prepared, or, in his absence, by
the Dean of the Graduate School when such copying or publication is solely for scholarly
purposes and does not involve potential financial gain. It is understood that any copying
from, or publication of, this thesis that involves potential financial gain will not be
allowed without written permission.





_________________________________
Alexander C. Shkolnik





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Alexander C. Shkolnik
77 Kirkwood Rd
West Hartford, CT 06117



The director of this thesis is:

Dr. James Lu
Department of Mathematics and Computer Science
400 Dowman Drive
Atlanta, GA 30322



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Neurally Controlled Simulated Robot:
Applying Cultured Neurons to Handle an Approach / Avoidance Task in Real Time
and a Framework for Studying Learning in Vitro

By

Alexander C. Shkolnik
Master of Sciences


Department of Mathematics and Computer Science




_________________________
James Lu
Adviser


_________________________
Steve Potter
Committee Member


_________________________
Thomas DeMarse
Committee Member


_________________________
Phil Hutto
Committee Member


Accepted:


_________________________
Dean of the Graduate School


________________________
Date





Neurally Controlled Simulated Robot:
Applying Cultured Neurons to Handle an Approach / Avoidance Task in Real Time
and a Framework for Studying Learning in Vitro




by



Alexander C. Shkolnik


Thesis Adviser: Dr. James Lu
Mathematics and Computer Science, Emory University

Research Adviser: Dr. Steve Potter
Laboratory for Neuroengineering, Georgia Institute of Technology






An Abstract of
a thesis submitted to the Faculty of the Graduate School
of Emory University in partial fulfillment
of the requirements for the degree of
Master of Sciences


Department of Mathematics and Computer Science


2003





Abstract



Little is known about how information is encoded in the brain, and even less is
known about how computation and useful data manipulation occurs in living neural
networks. The goal of this project was to construct a simulated robot to explore data
encoding and processing in living neuronal networks. Information was encoded by
varying timings between neuronal input stimulations. Encoding information in this way
resulted in a non-linear neural response. This response, if interpreted as a computation
can be used to emulate any logic gate, and thus a Universal Turing Machine. This neural
response was used to control a simulated robot in real-time to approach an object if it was
too far away, or to avoid an object if it was too close. The animat provides a framework
for studying living neural networks at the behavioral level. Such an animat may also be
useful to study learning in living neural networks, as expressed by changes in the
animats behavior.








Neurally Controlled Simulated Robot:
Applying Cultured Neurons to Handle an Approach / Avoidance Task in Real Time
and a Framework for Studying Learning in Vitro




by



Alexander C. Shkolnik



Thesis Adviser: Dr. James Lu
Mathematics and Computer Science, Emory University

Research Adviser: Dr. Steve Potter
Laboratory for Neuroengineering, Georgia Institute of Technology







A thesis submitted to the Faculty of the Graduate School
of Emory University in partial fulfillment
of the requirements of the degree for
Master of Sciences


Department of Mathematics and Computer Science


2003


Acknowledgements


It is a pleasure to thank the many people who made this thesis possible.


In no particular order, special thanks to: my research adviser at the Georgia
Institute of Technology Laboratory for Neuroengineering, Dr. Steve Potter for giving me
the opportunity to work in his lab and for the insights I have gained under his direction;
Former post-doc in the Potter lab, now professor of biomedical engineering at University
of Florida, Dr. Thomas DeMarse for giving me training and for helping me with the
project; my Emory thesis adviser and professor in Math / CS at Emory University, Dr.
James Lu for giving me material support and direction; The faculty of the Math / CS
department at Emory University for giving me a broad education in computer science; the
faculty of the Neuroscience and Behavioral Biology department at Emory University for
giving me a broad education in neuroscience; Dr. Pat Marsteller, Dr. David Edwards and
the SURE program for exposing me to research and pushing me forward; and my parents,
Dr. Nikolay Shkolnik and Valentina Shkolnik for their support and help.
CONTENTS

Chapter









Page

1.

Introduction ............................................................................................................... 1
2.

A Brief Review of Neuroscience and Living Neural Networks................................ 3
2.1
Bottom up approach to studying the brain: Molecular and cellular
neuroscience................................................................................................ 4
2.2
Top down approach to studying the brain: psychology, psychobiology .. 11
2.3
Living Neural Networks ........................................................................... 12
3.

Neural Computation, MEAs and Animats ............................................................. 13
3.1
Information encoding and processing....................................................... 13
3.2
Multielectrode array, recording activity, learning .................................... 16
3.3
Animats and robots ................................................................................... 16
4.

Neurally Controlled Animat Problem ..................................................................... 18
5.

Effect of dual channel probing on neural activity ................................................... 22
5.1 Background............................................................................................... 22
5.2 Method ...................................................................................................... 24
5.3 Data
Analysis ............................................................................................ 26
5.4 Results....................................................................................................... 27
6.

Demonstrating the computational power of the IPI neural effect ........................... 38
6.1
Schema for emulation of digital logic gates ............................................. 38
6.2
Input mappings for emulation of a NOT gate........................................... 41
6.3
Emulation of an AND or NOR gate...........................