MINISTRY OF EDUCATION AND TRAINING
MINISTRY OF NATIONAL DEFENCE
ACADEMY OF MILITARY SCIENCE AND TECHNOLOGY
TA QUOC GIAP
RESEARCH ON ESTABLISHING
THE NEURAL STIMULATION SYSTEM AND
APPLY FOR EVALUATING THE SPATIAL RESPONSE
OF HIPPOCAMPAL PLACE CELLS
DOCTOR OF ENGINEERING DISSERTATION
HANOI - 2020
MINISTRY OF EDUCATION AND TRAINING
MINISTRY OF NATIONAL DEFENCE
ACADEMY OF MILITARY SCIENCE AND TECHNOLOGY
TA QUOC GIAP
RESEARCH ON ESTABLISHING
THE NEURAL STIMULATION SYSTEM AND
APPLY FOR EVALUATING THE SPATIAL RESPONSE
OF HIPPOCAMPAL PLACE CELLS
Specialization: Electronic engineering
Code: 9 52 02 03
DOCTOR OF ENGINEERING DISSERTATION
SUPERVISORS:
1. Dr. NGUYEN LE CHIEN
2. Dr. LE KY BIEN
HA NOI - 2020
i
DECLARATION
I hereby declare that this dissertation is my original work. The data and
results presented in the dissertation are honest and have not been published in
any other work. References are fully cited.
10th January, 2020
giả luận án
TA Quoc Giap
ii
ACKNOWLEDGMENTS
First and foremost, I would like to express my deep appreciation to my
direct supervisors, Dr. NGUYEN Le Chien, Dr. LE Ky Bien and Association
Professor TRAN Hai Anh, who enthusiastically guided me during my whole
PhD time. Thank you very much for many meaningful advices and discussion
for my work. I learnt from the mentors not only techniques for fulfilling my PhD
work, but also methods for solving problems in a lab as well as in the life. Thank
you very much for revising my thesis, giving me helpful comments and advices.
My sincere appreciations must go to other teachers in the Departments for
their encouragement, knowledge sharing, supports and helps in our course and
conduct the thesis.
I would like to express my sincere thanks to the Institute of Electronics –
Academy of Military Science and Technology; Department of Physiology,
Department of Material Equipment – VietNam Military Medical University,
where I study, live and work for creating favorable conditions for me to
participate in studying and researching during my time as a PhD student.
I want to express my special thank to the leader of Academy of Military
science and technology and other collaborator centers for their support and help
for this work.
Finally, I would like to thank my family members for their love,
encouragement. And especially, I would thank my wife who have sacrificed a
lot of things for supporting me to fulfill my PhD work.
iii
TABLE OF CONTENTS
Page
LIST OF SYMBOL AND ABBREVIATION………………………………..v
LIST OF FIGURES AND TABLES…………………………………………ix
INTRODUCTION ............................................................................................. 1
CHAPTER 1
OVERVIEW ABOUT ELECTRICAL ACTIVITY OF NEURONS ............... 6
1.1. Membrane potential of neurons ................................................................. 6
1.1.1. Structure of nerve cells membrane ..................................................... 6
1.1.2. Resting and action potential ................................................................ 9
1.2. Electrical nerve stimulation and medical significance ............................ 12
1.3. The response of cell membranes to electrical stimulation ....................... 16
1.4. The recording methods of the neuronal action potential ......................... 18
1.5. Hippocampus and hippocampal place cells ............................................. 21
1.5.1. Structural characteristics ................................................................... 21
1.5.2. Function of the Hippocampus ........................................................... 21
1.6. Fundamentals of electronic circuit model of neuron ............................... 23
1.7. Related research to this dissertation ......................................................... 26
1.8. Chapter conclusion ................................................................................... 29
CHAPTER 2
EQUIVALENT ELECTRICAL CIRCUIT MODEL .........................................
AND NEURONAL ELECTRICAL STIMULATION ALGORITHMS ........ 31
2.1. Electronic model of neuron membrane and assessment of electric
stimulation parameters .................................................................................... 32
2.1.1. Electronic circuit model of neurons .................................................. 32
2.1.2. Simulation of stimulating parameters on Maeda and Makino models ....34
2.1.3. Simulation results and discussion ..................................................... 36
2.2. The system for stimulation and recording the electrical activity of neurons.. 39
2.3. Building electrical stimulation algorithm model for neurons .................. 41
iv
2.3.1. Model and algorithm of electrical stimulation of neurons with NPT
test ............................................................................................................... 41
2.3.2. Model and algorithm of electrical stimulation of neurons with spatial
response tests ............................................................................................... 47
2.4. Chapter conclusion ................................................................................... 63
CHAPTER 3
EVALUATING THE STIMULATION ALGORITHMS AND .................... ....
THE SYSTEM BY BEHAVIOURAL RESPONSES AND...............................
PRACTICAL EXERCISES ON MICE .......................................................... 64
3.1. Materials and methods ............................................................................. 64
3.2. Simulation results ..................................................................................... 67
3.2.1. Simulation of the NPT task ............................................................... 68
3.2.2. Response simulation in spatial exercises .......................................... 69
3.3. Analyze and evaluate experimental results on mice ................................ 74
3.3.1. Experimental results performed on NPT test .................................... 74
3.3.2. Experimental results performed on the spatial response tests .......... 79
3.4. The results of stimulating and recording experiments of the neuronal
electronic activity in the hippocampus on mice………………………………80
3.4.1. Unit isolation and recording………………………………………..80
3.4.2. Common characteristics of hippocampal place cells………………..82
3.5. The evaluation of the algorithms, stimulation and recording systems for the
electrical activity of neurons…………………………………………………83
3.5.1. The evaluation of algorithms………………………………………..83
3.5.2. The evaluation of stimulating and recording system for the electrical
activity of neurons ....................................................................................... 86
3.6. Chapter conclusion ................................................................................... 94
REFERENCES .............................................................................................. 100
APPENDICES …………………………………………………………………
v
LIST OF SYMBOLS AND ABBREVIATIONS
𝐶
Ions concentration
𝐶𝑚
Capacitance of the membrane per unit plane
cr
The adjusted response number
countInterVal
Number of stops to adjust the parameter
delayTime
The minimum time from when the mouse receives the
reward until the new reward area appears
deltaTime
The time it takes to count from the time the mouse receives
the prize until the new reward area appears
delta
Limits the distance the mouse moves to get the reward
𝑑𝐷𝑀𝑇
The distance the mouse moves over a certain period of time
in the DMT test
𝑑𝑅𝑅𝑃𝑆𝑇
The distance the mouse moves over a certain period of time
in the RRPST test
𝑑𝑃𝐿𝑇
The distance the mouse moves over a certain period of time
in the PLT test
𝑑𝑋
Diameter on the horizontal axis of the virtual environment
𝑑𝑌
Diameter on the vertical axis of the virtual environment
𝐸𝐴
Action potential of cell
𝐸𝐾
Resting potential of cell
𝐸̅
Electric field strength
𝐹
Faraday constant
𝑔𝑁𝑎
Conductivity of Na+ ion channels
𝑔𝐾
Conductivity of K+ ion channels
𝑔𝐿
Conductivity of secondary ion channels
Interval
Interval to stop for parameter adjustment
𝐼𝑖
Intra-axonal current
vi
𝐼𝑘𝑡
Cell membrane stimulated current
𝐼𝑜
Extra-axonal current
𝐼𝑠
Stimulation current per unit of time
K
IN
Intracellular K+ concentration
K
OUT
Extracellular K+ concentration
maxT
The maximum time of task
maxPt
The maximum number of rewards
maxwidth
Radius of mice area moving
M50
50 percent of the optimal
M70
70 percent of the optimal
M80
80 percent of the optimal
n
Valence of ions
Na
Na
OUT
Extracellular Na+ concentration
IN
Intracellular Na+ concentration
𝑅
Constant
𝑅𝑚
Membrane resistance per unit area
𝑇
Absolute temperature
𝑡
Time to stimulate
𝑡1
Rewarding eligible time
𝑡2
Reward receiving time
𝑡𝐿𝑇
Total amount of exercise time for the mouse
𝑡𝑆
Training time (also the total time of sessions)
𝑡𝐼𝑛
Rest time to adjust the value of the stimulating parameter
𝑉𝑚
Membrane potential
Pt
Number of rewards.
𝑉𝑚 – 𝑉𝑁𝑎
Transmembrane potential of Na+ channel
vii
𝑉𝑚 – 𝑉𝐾
Transmembrane potential of K+ channel
𝑉𝑚 – 𝑉𝐿
Transmembrane potential of secondary channels
𝑉′
Electric membrane charge
𝑣𝑚
̅̅̅̅
The mean of movement speed of the mouse in the open
environment
𝑋𝑚𝑎𝑥
Maximum diameter in the horizontal axis of the virtual
environment
𝑋𝑚𝑖𝑛
Minimum diameter in the horizontal axis of the virtual
environment
x0, y0
Reward coordinates of mouse before t
xs, ys
The coordinates of the mice at the time t is assigned with x0,
y0 which is the original position of the mice
xt ,yt
Reward coordinates of mouse at 𝑡
xz1, yz1
The x and y coordinates of the center of the reward area 1
xz2, yz2
The x and y coordinates of the center of the reward area 2
xzt, yzt
x, y coordinates of the center of the current reward area
𝑌𝑚𝑎𝑥
Maximum diameter in the vertical axis of the virtual
environment
𝑌𝑚𝑖𝑛
Minimum diameter in the vertical axis of the virtual
environment
𝑧1
Reward region 1
𝑧2
Reward region 2
wz
Radius of the reward area
𝛥𝑡
System latency
𝛥𝑡𝐷𝑀𝑇
System latency in DMT test
𝛥𝑡𝑁𝑃𝑇
System latency in NPT test
𝛥𝑡𝑅𝑅𝑃𝑆𝑇
System latency in RRPST test
viii
𝛥𝑡𝑃𝐿𝑇
System latency in PLT test
𝜙𝑖
Inner membrane potential
𝜙0
Outer membrane potential
Membrane time constant
𝜃0
Response threshold
𝜃cr
Correction threshold
AD
Alzheimer’s disease
BSR
Brain stimulation reward
CCD
Charge coupled device
DAC
Digital analog converter
DC
Direct current
DMT
Distance movement task
EBS
Electrical brain stimulation
EF
Extracellular field
FPS
Frames per second
HNM
Hippocampal network model
ICSS
Intracranial self – stimulation
MCI
Mild cognitive impairment
MFB
Medial forebrain bundle
MTLE
Mesial temporal lobe epilepsy
NPT
Nose – poking task
OF
Open – field
PLT
Place learning task
RND, RRPST Random task, random reward place search task
SPF
Spike potential field
SNR
Signal to noise ratio
ix
LIST OF FIGURES
page
Figure 1.1. Basic structure of nerve cell……………………………………... 7
Figure 1.2. Concentration and potential of ions at rest………………………. 9
Figure 1.3. Direction of potential field lines around a neuron…………….... 11
Figure 1.4. Changes in membrane potential under the effect of stimulation
pulses…………………………………………………………………….13
Figure 1.5. Dopamine transmission pathways of mesolimbic……………… 14
and mesocortical systems…………………………………………………… 14
Figure 1.6. Cell membrane’s response to stimulus signals………………… 16
Figure 1.7. Demonstration of extracellular potential recording technique and
the data form............................................................................................. 19
Figure 1.8. Diagram of rodent brain and the location of the hippocampus… 21
Figure 1.9. Experimental equipment for the formation of the axon cable
equation………………………………………………………………… 23
Figure 1.10. Electronic circuit model and voltage chart of neurons…………24
Figure 2.1. Electric model of neron and the theory of action potential………32
Figure 2.2. Electrical neuron model according to Maeda and Makino………34
Figure 2.3. Electric model of a neuron under the stimulation of direct
current…………………………………………………………………...35
Figure 2.4. One-dimensional stimulation pulse form with specified
parameter………………………………………………………………...36
Figure 2.5. The voltage response pattern of the model…………………….. 37
Figure 2.6. Voltage change by stimulating intensity at 80Hz……………… 38
Figure 2.7. Change in voltage by stimulation frequency, at the intensity of
70μA……………………………………………………………………..39
Figure 2.8. Model of stimulating and recording the potential of neurons….. 40
x
Figure 2.9. The integrated control pulse pattern of the system and the neuron
stimulation pulse………………………………………………………... 41
Figure 2.10. Model of system for stimulating and responding to nose-poke
behavior………………………………………………………………… 42
Figure 2.11. Flow chart of the NPT test……………………………………. 45
Figure 2.13. Stimulating algorithm flowchart for DMT test……………….. 51
Figure 2.14. The system for stimulation and recording the action potential of
neurons on mice………………………………………………………… 53
Figure 2.15. Algorithm flowchart for the RRPST test……………………... 57
Figure 2.16. Flowchart of electric stimulation algorithm for PLT test……... 61
Figure 3.2. The recording chamber for the ICSS response and………………..
nose-poking behaviors of mice………………………………………………66
Figure 3.3. The illutration of the model and the arrangement of the spatial
tasks……………………………………………………………………...66
Figure 3.5. Program interface in DMT test…………………………………. 70
Figure 3.6. Program interface in RRPST test……………………………….. 71
Figure 3.7. Program interface in PLT test…………………………………... 72
Figure 3.8. Relationship between nasal poking behavioral response and
intensity of stimulation…………………………………………………. 77
Figure 3.9. The dependence of nose-poking response on the stimulating
frequency…………………………………………..……….....................78
Figure 3.10. Experimental results are analyzed for the spatial response
tests………………………………………………………………………80
Figure 3.11. The neuron activity are recorded and isolated using an offlinesorter program (Plexon)………………………………………………… 81
Figure 3.12. Electrical activity of neurons recorded at hippocampus……… 82
xi
Figure 3.13. Model of evaluating the stability and latency of the system for NPT
task by labchart Pro v8.1.8……………………………………………… 86
Figure 3.14. The illustration for pulses of the reward condition, reward
delivery, and the delay time of the system……………………………… 87
Figure 3.15. The evaluation of the stability and delay of the system for the
DMT, RRPST and PLT tasks……………………………………………87
Figure 3.16. Program to evaluate the stability and latency of DMT test…… 88
Figure 3.17. Graph of system latency time in DMT test…………………… 89
Figure 3.18. Program to evaluate systemic stability and latency in RRPST
test………………………………………………………………………. 90
Figure 3.19. Graph of system latency time in RRPST test…………………. 90
Figure 3.20. Program to evaluate systemic stability and latency in PLT test. 91
Figure 3.21. Graph of system latency time in PLT test…………………….. 92
1
INTRODUCTION
1. The necessity of the dissertation
Biomedical engineering is an applied science field, which connects
different sciences from physics, chemistry, and biology to electrical, control,
information, micro and nano technologies in order to provide biomedical
solutions for improving human health. Neural engineering is an important
subfield of biomedical engineering, which uses engineering techniques to treat,
replace, or restore the functions of the neural system. One of the central field
of neurophysiology is the study of the mechanisms of memory and information
storage in the brain [8], [48], [73], [87 - 89]. It requires a device possessed
controllable and stable properties for studying the mechanism of memory
storing in the brain. This plays an important role in a comprehensive
understanding of physiological neural system. Therefore, the development of
systems that allow studying the physiology of the nervous system has highly
practical applications.
Based on the available but functionally limited equipments and programs,
many supportive equipment and programs is needed for the system to be
functionally competent.
In this dissertation, a neural stimulation and recording sytem is developed
for evaluating behavioral and spatial responses of mice from electrical
stimulations with proper algorithms. This system allows deeper understanding
of the working principles of neurons and the brain. In addition, this is
fundamental to study the structure and function of hippocampus, which may be
associated with some neurodegenerative diseases such as Alzheimer’s, mild
cognitive impairment, mesial temporal lobe epilepsy, and Schizophrenia [5 6], [23], [41], [68], [78].
The practical exercises with their respective algorithms are first built on
animals in order to develop the electrical stimulating and recording system for
2
neurons. The built stimulation system allows the electrical activities of neurons
to be evaluated in environment and whole living organism correlations. The
electrical recording of neurons in hippocampus is fundamental to assess cells’
behavior in this place. Importantly, specific working principles of the central
nervous system will be elucidated to better understand feeling, memory, and
autonomic nervous mechanisms.
Therefore, the project “research on establishing the neural stimulation
system and apply for evaluating the spatial response on hippocampal place
cells” has a practical role in comprehensive studies of neuronal physiology.
2. Objectives
- Developing
a system for stimulating and recording the electrical activity
of neurons based on electronics engineering.
- Building mathematical algorithms of neuronal stimulation for 4 practical
exercises on mice.
3. Subjects and scope of research
In order to build an electrical stimulation system which targets the
"reward" mechanism of the central nervous system, the study and development
of a stimulating control program system with appropriate equipments
including:
- Single - channel Stimulator SEN - 3401 (Nihon Kohden, Japan).
- Digital - Analog converter (DAC) and Isolator SS - 203J (Nihon Kohden,
Japan).
- Nose - poking chamber.
- Control program is built on C++ language, version 2010 (Microsoft Inc.,
USA); data structure and data collection program is built on C# language,
version 2010 (Microsoft Inc., USA).
Recording the response potential of the hippocampal place cell when the
animal moved in given environment. Microelectrodes were placed in the
3
hippocampus of mice, and the cell potential field was recorded as animals
moved through C++ and C# - based drivers developed for research purposes,
the experimental tests are built based on the corresponding algorithm.
Equipment used in recording neuron electrical activity and programs for
recording, analyzing data and evaluating system activities and developed
algorithms, including:
- Plexon HLK2 system (Plexon Inc., USA) could record the action potential
of the hippocampal place cells and the spatial location of animals in the
open environment.
- Measure the resistance of the recording electrode: Electronic Balance
(Shimadzu Corporation, Japan).
- Programs have been developed and applied in the characteristic analysis
of hippocampal place cells activities.
4. Methodology
The thesis uses circuit theory to simulate electric stimulation parameters
by NI Multisim program version 14.0 (National Instruments Inc., Australia);
mathematical statistical theory in experimental tests on mice; biomedical
techniques in implementing research systems, especially in setting up
stimulating electrodes and electrodes for recording the electrical activity of
neurons; theory of digital signal processing in signal visualization and
mathematical model formulation of the problem. Simulation program,
algorithmic models building, experimental methods description on mice and
data results with C# programming language (Microsoft, USA). System
controlling and synchronization with C++ programming language (Microsoft,
USA). Using intensive developed software to analyze the collected data as a
basis for evaluating built algorithms and system. Moreover, these results show
characteristics of hippocampal place cells in relation to a given environment.
5. Content and structure
4
Apart from Introduction, Conclusion and References, this dissertation
contains 3 chapters as follow:
Chapter 1. OVERVIEW ABOUT ELECTRICAL ACTIVITY OF NEURONS
Chapter 1 presents an overview of the membrane potential of neuron, such
as: the structure and function of the cell, the membrane of the neuron; theory
of resting and action potentials; the function of hippocampal place cells.
In assessing the electrical activity of neuron, it is necessary to build a
system capable of evaluating the neuronal electrical activity characteristics
under the influence of stimulating factors. Chapter 1 introduces the modeling
of the response of the nervous system in relation to the "reward" mechanism
for electrical stimulation, which is the basis for simulating the electrical
stimulation and response of the cell membrane carried out in Chapter 2.
The electrical activity of the cell membrane induces changes in the
extracellular potential field. Therefore, chapter 1 also provides the technical
knowledge as well as the electrical activity recording system of neurons.
Chapter 2. EQUIVALENT ELECTRICAL CIRCUIT MODEL AND
NEURONAL ELECTRICAL STIMULATION ALGORITHMS
In chapter 2, using electronic models of neurons to examine electrical
stimulation parameters and select appropriate parameters as the basis for
building experimental stimulating parameters on animals.
Besides, chapter 2 also proposes 4 models and 4 algorithms to apply in the
tests related to brain stimulation reward (BSR) from suitable parameters
(frequency, amplitude) simulated and verified through experiments in building
model, algorithm for intracranial self-stimulation (ICSS) with response to nosepoking through NPT test. Algorithms and drivers are applied to develop
reward-seeking exercise test in an open field, thereby assessing the potential
activity related to spatial memory of hippocampal place cells.
5
Chapter 3. EVALUATING THE STIMULATION ALGORITHMS AND THE
SYSTEM
BY
BEHAVIOURAL
RESPONSES
AND
PRACTICAL
EXERCISES ON MICE
This chapter presents the simulation results before the experiments and the
experimental results on the system through exercises performed on mice, using
the stimulation models and algorithms proposed in Chapter 2. Utilizing
evaluation methods and analyzing the obtained results is the basis for
evaluating the stimulation algorithm model and the system for stimulation and
recording the electrical activity of the built neuron.
6. Scientific and practical signification
From the understanding of electrical activity of neurons, the thesis has
investigated the frequency and amplitude parameters of stimulation pulses
through modeling electronic circuit of neurons. This is the basis for assessing
the response of neurons to DC stimulation parameters through intracranial selfstimulation (ICSS). From there, to suggest the suitable stimulation parameters
for the study subject.
From the signification and widely role of electrical stimulation in
medicine, the dissertation has proposed the construction of a system for
stimulation and recording the electrical activity of neurons along with 4
algorithms of electrical stimulation of neurons in 4 experimental tests on
animals. In addition to the proposed research facilities, these four tests help to
assess the spatial response of the "reward" system in the brain and neurons in a
given environment. These results contribute to the electrical function
evaluation of neurons, which is the basis for assessing the physiological activity
of the central nervous system.
The thesis also addresses the need to synchronously built and develop the
system and program to stimulate and record neuronal electrical activity to solve
the current problem in functional research of the central nervous system.
6
CHAPTER 1
OVERVIEW ABOUT ELECTRICAL ACTIVITY OF NEURONS
The study of characteristics, especially the electrical properties of cell
membranes and the effect of electrical stimulating parameters on neurons
serves as a basis for building an algorithmic model and a neuron stimulation
system. The successful combination of a neuronal stimulation system with the
recording of electrical activity of neurons into a complete system is important
to evaluate the activity of each neuron in relation to the environment and the
whole organism. Research in building neuron stimulation system and recording
the electrical activity of hippocampal nerve cells will help medical researchers
to evaluate the operational characteristics of the hippocampal place cells under
the influence of several stimuli in the environment.
1.1. Membrane potential of neurons
1.1.1. Structure of nerve cells membrane
Neurons are analogous to other cells, which have structural components
of cell membranes, nuclei and organelles. The electrical activity of normal cells
as well as neurons is highly related to the structure and characteristics of the
cell membrane [1].
Nerve cells (also called neurons) are composed of three main components,
the cell body, dendrites and axons, which are visualized in Figure 1.1 [10].
The cell body (also called the soma) is the largest part of the neuron,
containing the nucleus and the majority of the cytoplasm (the physical space
between the nucleus and the cell membrane). Most of the cellular metabolism
takes place here, including the production of Adenosine Triphosphate (ATP)
and the synthesis of proteins. The neuron body processes and makes decisions
about the flow of information going to and from here.
7
Dendrite are short tentacles that develop from the cell body. This is where
the signal pulse from other nerve cells is transmitted (afferent signals). The
action of these impulses may cause excitation or inhibition at the receiving
neuron. A nerve cell in the brain cortex can receive afferent impulses from tens
or even hundreds of thousands of neurons.
Figure 1.1. Basic structure of nerve cell.
Axon is the only long extension that develops from the cell body. Axons
carry the processed signal pulse from the cell body to another cell such as
neuron or myocyte, adenocyte, ... The diameter of the axon in a mammal in the
range of 1 - 20µm. In some animals, the axon can be several meters long. The
axon may be wrapped by an insulating layer called a myelin sheath, made by
Schwann cells. The myelin sheath is not seamless but is divided into segments.
Between Schwann cells are the nodes of Ranvier. The structural characteristics
of the Myelin sheath and the nodes of Ranvier have a great influence on the
speed of impulse conduction on nerve fibers.
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