Nghiên cứu xây dựng hệ thống kích thích tế bào thần kinh và ứng dụng trong đánh giá đáp ứng không gian của tế bào vị trí hồi hải mã

LIST OF SYMBOLS AND ABBREVIATIONS ?? Capacitance of the membrane per unit plane cr The adjusted response number countInterVal Number of stops to adjust the parameter delayTime The min

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

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

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

10 th January, 2020

giả luận án

TA Quoc Giap

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

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

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 ………

LIST OF SYMBOLS AND ABBREVIATIONS

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

𝑑𝐷𝑀𝑇 The distance the mouse moves over a certain period of time

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

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

𝐼𝑘𝑡 Cell membrane stimulated current

M50 50 percent of the optimal

M70 70 percent of the optimal

M80 80 percent of the optimal

𝑡1 Rewarding eligible 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 – 𝑉𝑁𝑎 Transmembrane potential of Na+ channel

𝑉𝑚 – 𝑉𝐾 Transmembrane potential of K+ channel

𝑉𝑚 – 𝑉𝐿 Transmembrane potential of secondary channels

x 0, y 0 Reward coordinates of mouse before t

x s, y s The coordinates of the mice at the time t is assigned with x0,

y0 which is the original position of the mice

x t ,y t Reward coordinates of mouse at 𝑡

x z1 , y z1 The x and y coordinates of the center of the reward area 1

x z2, y z2 The x and y coordinates of the center of the reward area 2

x zt, y zt x, y coordinates of the center of the current reward area

𝑌𝑚𝑎𝑥 Maximum diameter in the vertical axis of the virtual

𝛥𝑡𝐷𝑀𝑇 System latency in DMT test

𝛥𝑡𝑁𝑃𝑇 System latency in NPT test

𝛥𝑡𝑅𝑅𝑃𝑆𝑇 System latency in RRPST test

𝛥𝑡𝑃𝐿𝑇 System latency in PLT test

𝜙𝑖 Inner membrane potential

𝜙0 Outer membrane potential

Membrane time constant

𝜃cr Correction threshold

BSR Brain stimulation reward

CCD Charge coupled device

DAC Digital analog converter

DMT Distance movement task

EBS Electrical brain stimulation

EF Extracellular field

ICSS Intracranial self – stimulation

MCI Mild cognitive impairment

MFB Medial forebrain bundle

MTLE Mesial temporal lobe epilepsy

PLT Place learning task

RND, RRPST Random task, random reward place search task SPF Spike potential field

SNR Signal to noise ratio

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

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 offline-sorter program (Plexon)……… 81

Figure 3.12 Electrical activity of neurons recorded at hippocampus……… 82

Figure 3.13 Model of evaluating the stability and latency of the system for NPT task by labchart Pro v8.1.8……… 86Figure 3.14 The illustration for pulses of the reward condition, reward delivery, and the delay time of the system……… 87Figure 3.15 The evaluation of the stability and delay of the system for the DMT, RRPST and PLT tasks……… 87Figure 3.16 Program to evaluate the stability and latency of DMT test…… 88Figure 3.17 Graph of system latency time in DMT test……… 89Figure 3.18 Program to evaluate systemic stability and latency in RRPST test……… 90Figure 3.19 Graph of system latency time in RRPST test……… 90Figure 3.20 Program to evaluate systemic stability and latency in PLT test 91Figure 3.21 Graph of system latency time in PLT test……… 92

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

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

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

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 nose-poking 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

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 self-stimulation (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

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

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

Similar to other cells in the organism, neurons are surrounded by a 7.5–10nm cell membranes The cell membrane plays a very important role in establishing the resting properties and electric activity of the cell when stimulated by regulating the movement of ions between extracellular and intracellular spaces Some ions such as HCO3-, Cl- could move to both sides through cell membrane easily due to the difference in concentration gradient But some of the ions, especially Na+ and K+ must follow selective transport mechanism to move through cell membrane This leads to a potential gradient between the two sides of the membrane and creates a potential field This field exerts force on ions across the cell membrane Therefore, the movement of membrane ions is influenced by both the electric and diffusion forces

The existence of a cell membrane depends on the permeability of the necessary substances from the external environment into the cell and the excretion of metabolites and debris from within the cell The permeability or transportation of substances through the cell membrane is carried out in the forms of direct transport, phagocytosis, pinocytosis and exocytosis Direct transportation of substances through the membrane can be divided into three categories: diffusion, passive transport and active transport [1]

The resting potential of ions in a cell is described in Figure 1.2 [52] The main ions are potassium (K+), sodium (Na+), chlorine (Cl-) and calcium (Ca2+)

In particular, the electrical activity of the cell is mainly determined by K+ and

Na+ ions The activity of K+ and Na+ ions respectively determines the resting potential and the action potential of the cell membrane The potential equilibrium is obtained when the diffuse force is equal to the electric field force

of all ions For membrane with selective permeability of only one type of ion, equilibrium condition is when the electric field creates a force equal to and in opposite direction to the diffuse force The steady-state values of the membrane

potentials when there are some forms of ions in the intracellular and extracellular environments, as they cross the cell membrane, are specifically described in the Goldman - Hodgkin - Katz voltage equation[26], [61].

Figure 1.2 Concentration and potential of ions at rest

1.1.2 Resting and action potential

The membrane potential of a cell is defined as the difference in potential between the internal and external side of the membrane due to the difference between ions on either side At rest, the ions distributed on both sides of the membrane are in equilibrium and depend on two forces - diffusion and electrostatic forces The ions diffused out in the resting cell state are mainly K+,

so the diffusion force is calculated by the work needed to pass 1 mole of K+

ions across the membrane The electrostatic force at rest is calculated by the work needed to resist the repulsion of ions with the same sign and the attraction

of the opposite ions, in order to transfer a mole of K+ ions across the membrane

[1] Thus, in order to pass a mole of ions across the membrane, a total force (called electrochemical potential) is needed, which is equal to the sum of the diffuse and electrostatic forces and when the ions are in equilibrium, the two forces are equal (but opposite) In the resting state (polarized state), the resting voltage Ek, determined by the K+ ion, is calculated using the Nernst equation and usually fluctuates between -70mV and -90mV and the cell membrane is now in a polar state

K

IN

K RT E

- n: valence of ion; with K+, n = 1

- F: Faraday constant (electric charge per mole of electrons)

When the cell is excited, the membrane potential is changed by changing the permeability of the membrane with Na+ ions The Na+ channel is opened, and the Na+ ions on the outside of the membrane rush into the cell to redistribute ions on either side of the membrane: the number of positively charged ions on the inside of the membrane is greater than on the outside At this time, the membrane is polarized from the polar state to the depolarized state and the excited or action potential EA appears This potential originates from the stem cell along the axon and is conducted to other cells The operating potential value can reach 120mV but because at the starting point the membrane potential

(in the polarized state) has a value of -90mV, the actual voltage is about + 30mV

A

IN

Na RT

Figure 1.3 Direction of potential field lines around a neuron

When depolarizing neuron membrane generates action potentials, they increase the electrical conductivity of the excitation-sensitive areas of the membrane such as at the axon hillock or the soma The potential current enters the cell through these locations into the core of the cell and then out to the membrane located at nearby inactive positions and returns to the place where the potential current enters through many different ways This process forms a potential electric field around the neuron and its properties depend on the size

and shape of the cell, as well as the position and time on which the membrane’s conductivity is enhance [42], as described in Figure 1.3

The term EF (extracellular field) or SPF (spike potential field) mentions the potential field around an active neuron when producing potential pulse The membrane voltage 𝑉𝑚 of an excitable cell is defined as the potential

on the inside surface of the membrane 𝜙𝑖 compared to the outside surface potential 𝜙0:

This definition is independent of the cause of the potential and whether the membrane voltage is constant, periodic or non-periodic in operation Fluctuations in the membrane potential can be classified according to their properties in a variety of ways According to Bullock [15], the transmembrane potential transmissions can consist of resting and changing potentials due to activity When there is a series of stimuli to the cell membrane, a certain degree

of response potential is induced If the amplitude of the response potential is small and does not exceed the threshold, the response is not propagated (electric tone) If the response is strong enough, a nerve impulse (action potential impulse) will be produced according to the "all or none" rule

1.2 Electrical nerve stimulation and medical significance

The basic theory of cells in general and neurons in particular is the basis for assessing the stimulation and response of neurons to stimuli, in which the stimulation with an electric impulse plays an extremely important role in the intensive study of neurons

When a neuron is stimulated, the membrane potential of the cell changes After response to stimulation, the membrane potential returns to its initial resting value If the membrane stimulation is insufficient to induce a transmembrane potential that reach the threshold, the membrane will not be

activated The response of the membrane to this type of stimulation is inactivation

The model of stimulating and recording the action potential of a neuron is

illustrated in Figure 1.4a, the electrical impulse generation system Is with set parameters stimulate the neuron membrane via stimulating electrode The response potential of the cell is recorded via the electrode and the recording system With sufficient stimulation, the transmembrane potential reaches the threshold and the membrane produces a special electrical impulse called a nerve impulse This potential response follows a characteristic pulse regardless of the stimulus threshold strength Or the action potential of a cell membrane obeys the "all or none" law This respond potential is call the action potential in Figure

1.4a [10] which represents the stimulus model by the I s current and

measurement of the membrane voltage V m.

Figure 1.4 Changes in membrane potential under the effect of stimulation pulses

c

Figure 1.4c shows the pulse shape and the intensity of the stimulation pulse The change in membrane voltage is shown in Figure 1.4b under the effect

of excitation pulses with different parameters: depression-induced stimulation (1) and excitation-induced stimulation (2, 3, 4) In which the stimulating pulse (2) has not reached the stimulating threshold yet, it will only cause a passive response Stimulation pulse (3) reaches the stimulus threshold can either cause

an action potential (3b) or not (3a) With stimulation pulse (4) exceed the threshold, action potential is always created

Described in 1954 when two Canadian scientists, James Olds and Peter Milner, found that animals implanted with electro-stimulating electrodes in the septal region would quickly return to the previously stimulated area in order to receive more reinforcing stimuli Thus, electric stimulation acts as a reward through which it is possible to train the animal to press the lever appropriately designed to receive stimulation [94] Modeling a behavioral evaluation model whereby the animal learns to manipulate itself to receive stimulating impulses into its own specific brain region that this brain region is thought to belong to

in the pathway involves processing the brain's reward, involved in regulating both natural reward and BSR

Figure 1.5 Dopamine transmission pathways of mesolimbic

and mesocortical systems

Studies show that it is possible to induce ICSS in many animals ranging from fish to humans; by creating BSR into brain regions belong to the "reward" mechanism such as the medial forebrain bundle (MFB), or the dopaminergic mesolimbic brain regions such as substantia nigra, ventral tegmental area, the central nuclei of the amygdala, septal nuclei, nucleus accumbens (NAcc); or the superior area of hippocampus, locus ceruleus, nucleus caudatus, olfactory tubercle, cerebellum In addition, several other brain regions also participate in the reward system such as the middle septal nucleus and the prefrontal cortex [9], [17], [94]

Moreover, BSR has outstanding features in the study of memory and motivation that other studies which use rewards as food, sex or substances [8], [53], [70], [85] does not have such as not affected by emotions, anxiety or rewards "saturation" … [17], [32], [83], [69] BSR is the type of stimulation that directly targets the reward system of the brain ICSS-trained animals can continually perform tests to receive rewards for hours or even all day until exhaustion, or in life-threatening condition the animal will still choose BSR over food or heating in condition of very low temperatures [94] Moreover, in

a certain limit, the increment of stimulation intensity (increase dose) induces the increment of ICSS response; on the other hand, other type of reward such

as food, water, sex or substances will decrease the response and create a anxiety state or “saturation” of rewards

Parameters affecting ICSS such as frequency, intensity of stimulation or duration of a single or cluster of stimulation pulse can be easily controlled and customized according to the purpose and model of the research; in which the most common are the first two parameters through which the stimulus threshold and the maximum response level are determined In this study, electrodes are implanted in the posterioral lateral hypothalamic area, under the influence of

the dopaminergic system (figure 1.5) BSR stimulation pulses are cathode positive pulses and vary in intensity or frequency

1.3 The response of cell membranes to electrical stimulation

When a stimulating pulse with set values depolarizes the membrane at rest

or exceeds the threshold voltage, the membrane responds with an action potential Described in Figure 1.4b in item 3b and section 4 "action potential responses" corresponding to stimuli that reached threshold 3b and beyond threshold 4 The response is characterized by a rapid increase in initial transmembrane potential, to positive peak potential, and then slowly recover to resting potential This phase reaction determines the action potential

Figure 1.6 Cell membrane’s response to stimulus signals

The response of the cell membrane to stimuli of varying intensity (a) follow the intensity-time curve (b) The minimum level of stimulus induced

response is called the rheobase threshold The minimum time required for a stimulating pulse is twice the intensity of the baseline to initiate the depolarization process called chronaxy [10]

Quantitative analysis of the characteristics of the action potentials was investigated by Hodgkin et al [38] on the large squid axon fiber - a species of nerve fiber with a large diameter (about 0.5mm), which is sufficient for plugging the two electrodes into the intracellular space In addition, the development of feedback control device called voltage clamp, which can keep the transmembrane voltage at any value The action potential is a very fast changing resting potential at the membrane, from polarization to polarization, polarity reversal and repolarization

There are questions to ask when studying cell membrane performance Should an electric stimulating cell be activated depending on which parameters: intensity, frequency of electrical impulse and duration of stimulation? Can the membrane voltage be reached by a short, strong stimulus or a long, weak stimulus? The curve illustrates the relationship between intensity and time in Figure 1.6 The smallest current to initiate activation is called the rheobase or current threshold Theoretically, the baseline threshold takes an infinite amount

of time to trigger activation

The time required to stimulate the cell with twice the current baseline threshold is called the chronaxy The changing and adaptive process of the cell which is repeated or continuous stimulated indicates an increase in cellular excitation so there is a decrease in the threshold The latency represents a delay between two events The time between applying a stimulus pulse and starting the activation is important parameters in the study

Once stimulation has begun, the membrane is not sensitive to new stimuli, regardless of the magnitude of the stimulus intensity This stage is called the

absolute allergy stage Near the end of the stimulating pulse, the cell can be activated, but with only a stronger stimulus than usual, this stage is called the relative inert phase The activation process involves current, potential, conductivity, density, and ionic current When activated in nerve cells, electrical impulses are called nerve impulses The bioelectric measurement focuses on the potential difference across the cell membrane so the electrical measurement of the action pulse is called the action potential - describing the electrical response of the membrane during activation In biomagnetic measurements, electric current is the source of the magnetic field Therefore, the term active current is corresponding to the source of the biomagnetic signal during the action pulse (Figure 1.6)

- The source of the action impulse is the nerve corresponding to it and being called a nerve impulse

- The electrical signal measured from the action pulse can be a potential or a current, the corresponding recording is called an active potential or an active current

1.4 The recording methods of the neuronal action potential

Neuroelectrophysiology has been studied from the eighteenth century through the report of Gavani on frog's thigh muscles during electrical stimulation Neuronal potential recording techniques has been in development since 1940, originating from Renshaw et al's report on recording the action potentials of cortical and hippocampal neurons that helped to understand the operating characteristics of structures in the the central nervous system [80] This technique has been applied in many research directions such as using extracellular microelectrodes to determine the potential characteristics of a neuron, thereby solving the fundamental problem that is the excitement property of neurons [31], [71] and till recently the research on the response of neurons in relation to behavior and stimulating factors in awakened and moving

animals [66] or determine connections between neurons in different regions of the brain At the same time, technology and equipment have also been improved to allow for a more accurate and convenient examination and analysis

of neuron activity [42]

Currently used extracellular potential recording techniques include two basic methods: (a) using micropipettes containing the appropriate electrolytes and connecting the input amplifier with the Ag/AgCl electrode or platinum wire; (b) Use highly conductive metal electrodes with micron-sized head and insulated body In which, the micropipette electrode is usually a glass electrode and is used in the acute recording of cell potentials for the brain regions proximal to the cortex as shown in Figure 1.7 [20]

Figure 1.7 Demonstration of extracellular potential recording technique

and the data form

Left: glass pipette electrode, filled with AgCl and attached with silver wire and approaching a neuron The amplifier amplifies the input potential from the extracellular potential field Upper right: Action potential is identified on the

signal noise when the electrode is close enough to the cell Lower right: From the moment of the pulse, a histogram (not show) or a raster can be developed

for neuron response to stimulation

Single metal microelectrode (monotrode) is widely used, developed increasingly sophisticated and described through scientific publications [40], [95] for electrodes made of glass-coated tungsten, stainless steel or platinum/iridium alloy Recent developments include extracellular potential recording techniques using dual microelectrodes (steriotrode) or quadruplex microelectrodes (tetrode)

Recording extracellular potentials using metal microelectrodes has many advantages, such as having little resistance, therefore the signal is low in noise, or relatively durable and easy to experiment in large quantity [42] A remarkable feature in the use of metal electrodes is that it could continuously record the behavior of a cell when the animal is awake, functioning normally or during tests [93] These behaviour characteristics may include impulse thresholds, latency times, pulse frequency (spontaneous or stimulated) or activities characteristics by the time [20]

On the other hand, in the study of neurophysiology, especially the mechanism of memory, the informative entry to the brain is thought to be encoded and stored in the form of synaptic connection levels in the neuron network [46] A classic report on the influence of environmental properties through activity related to the location of hippocampal pyramidal cells [24] has suggested the hypothesis that the map of the environment is encoded through the synaptic connection between pyramidal cells in the hippocampus Thus, recording the activity of the hippocampal pyramidal cells in relation to spatial stimuli can help elucidate the hippocampus's memory mechanism for the characteristics of the environment in which animals live

1.5 Hippocampus and hippocampal place cells

1.5.1 Structural characteristics

In humans and primates, Hippocampus (HPC) is a structure of the temporal lobes in the sagittal (a) and coronal (b) [69] diagrams depicted in Figure 1.8 Hippocampus is the main component and along with other structures of the midbrain and cortex such as the olfactory cortex, mammillary body, septum to form the Limbic system Studies show that HPC has a role

in storing information, converting short-term memory to form long-term memory and the ability to navigate in space [74]

Figure 1.8 Diagram of rodent brain and the location of the hippocampus

1.5.2 The function of the Hippocampus

The human hippocampus plays an important role in the process of memory and learning, in humans and in primates is important for segmented memory [25], [36], [59], [79] In mice, hippocampal injuries or interventions caused many disabilities in learning and spatial tests [33], [86], [90], [92] At the same time, recording of the hippocampal neuron potential also shows that the pyramidal cells in this region emit pulses in connection with a certain place (place - field) when the animal is moving in a specific environment Because the activity characteristics of the hippocampal pyramidal cells is in relation with

a

place, these cells are called place cells [73], [75], [93] The place - field area is affected by internal and external signals [48], [54 - 56], [67], [91], [97] or in certain information contexts [28], [34], [62] The above affirms the important role of the hippocampus in spatial memory [54 - 55], [93]

Besides many other functions, it seems that the main function of the hippocampus is providing the brain's neuronal material that reflects the external physical environment [25], [59] Based on this ability of the hippocampal place cell, it is thought to be the basis for studying or performing spatial cognitive exercises [19], [24], [25], [47], [48], [63], [81] In addition, many studies also suggest that an important function of hippocampal pyramidal cells is the ability

to remember the order of events [5], [76]

In mice, hippocampal pyramidal cells generate pulses at specific locations

in the environment and are influenced by environmental factors For a given environment, place cells have different place-field regions, and these response areas can be influenced by reference points located near or far from the animal's position or even by other intrinsic factors

Therefore, hippocampal place cells in the brain have been discovered to help explain why we remember where we've been and can find our way back

to where we were before Maguire et al [60] compared the size of hippocampus

of taxi drivers (who need to memorize many streets, roads and places) and bus drivers (less space memorized) in the city of London (UK) and reported certain differences in the size of the hippocampus between the two groups From there,

it further clarifies the function of the hippocampus related to spatial memory The hippocampus is regarded as the most studied sub-cortical region in both humans and animals mainly due to its role and function in cognitive learning and memory When injured, hippocampal dysfunction symptoms are manifested as impairments in memory, attention, emotions, spatial navigation

and executive function Diseases that cause degeneration or damage to hippocampal neurons can be seen in Alzheimer's disease (AD) [23], [5], [77], [82]; Mild Cognitive Impairment (MCI) [41]; Mesial Temporal Lobe Epilepsy (MTLE) [68]; Schizophrenia [78]… In terms of neural networks, the hippocampus is located in a central position, which acts as a bridge to many other brain regions involved in many cognitive processes It is suggested that the metabolic needs of various centers make hippocampus vulnerable in many neurological conditions [22], [35] Using hippocampus as the center, thereby creating a hippocampal network model (HNM) that can be applied in the study

of nervous system disorders [51], [64]

This dissertation focuses on researching to build a system to verify and from which can clarify the role of hippocampal place cells in memory and learning through testing the effects of stimulating factors, especially the influence of spatial factors on experimental animals

1.6 Fundamentals of electronic circuit model of neuron

To further study and understand the activity of membrane potential on electric stimulation, scientists have modeled the conducting system as an electronic circuit model

Figure 1.9 Experimental equipment for the formation of the axon cable equation

Supposely, the axon is immersed in an electrolyte of a certain concentration (similar to the extracellular medium) and the stimulation pulse is introduced through a pair of electrodes, one electrode determines the external axon in the extracellular medium and one determines the inner axon as illustrated in Figure

1.9 [10] The total stimulating current (I i) around the axis of the axon decreases with distance from the inner axis through the membrane to the return of the outer axon current Note that the direction of positive currents is to the right with 𝐼𝑖and 𝐼0 in case the conservation of current required 𝐼0 = −𝐼𝑖 At the same time, assuming both inside and outside of the axon, the voltage does not change with respect to the direction of the nerve and this system represents a symmetry axis Axon radius is much smaller than axon length

In this model, each section represents the transverse component of the inner axon with the boundary of the extracellular solution chosen shorter than the total axon length The membrane modeled as a scattered resistor and capacitor in parallel is shown in Figure 1.10a The intracellular and extracellular paths both have resistances, which is the basis for describing experiments on axons

Figure 1.10 Electronic circuit model and voltage chart of neurons

Stimulation on living cells with a sufficiently large electrical impulse will

cause a response that changes the membrane potential When the stimulating parameter reaches a certain threshold, the action potential of the cell will be generated After this response, the membrane potential will gradually return to its initial resting potential value If the excitation pulse is not large enough, the cell will not be activated The response of the membrane to this kind of stimulus

is passive If the stimulating impulse is strong enough, the membrane potential reaches a threshold and the membrane produces a characteristic electrical impulse called a nerve impulse

If 𝐼𝑠 is the excitation current per unit area, from the circuit theory applied

to parallel RC circuits shown in Figure 1.10b [10], we have:

In which:

- V': membrane charge [mV]

- I s : stimulation currents per unit of time [μA/cm2]

- R m : membrane resistance per unit area [kΩ.cm2]

- t: stimulation time [ms]

- τ: membrane time constant = R m C m [ms]

- C m : membrane capacitance per unit plane [μF/cm2]

In prolonged studies in live animals, usually using about 70 - 80% of the threshold value should satisfy the requirements [88] but in case exceeding the threshold, the response is also non-linear and can even cause the death of animals Potential time, the immobile threshold are relative concepts In a typical state, a timing chart may be based on an average of a specific number

of experiments In this case, the threshold (rheobase) and the valence (chronaxie) are measured experimentally by the stimulus response Generally, the faster the physiological system's expectations are met, the smaller the chronaxie value [10]

In the study of electrical stimulation of nerve cells, the parameters of electrical stimulation signals are very important: first, make sure not to cause damage to the stimulating object and it is also important to receive information Needs study of neurons The relationship between parameters of electric impulsive stimulus, for each given intensity, there is the corresponding frequency interval or duration of suitable stimulus announced in the study [81]; The relationship between intensity and duration of excitation in nerve stimulation: the greater the intensity (certain value), the smaller the stimulus time and vice versa [13 - 14], [39]

1.7 Related research to this dissertation

a) International research

In 1780, when Galvin stimulated the frog's sciatic nerve, muscle twitching occurred in the frog's thigh Since then, electric stimulation has been widely used in physiological research The development of science and technology has motivated human to study intensively the body in general and neurophysiological activity in particular [29], [52] Electrical Brain Stimulation (EBS) is used as a tool to elucidate central nervous system function Until recently, there have been many scientists studying the problems in stimulating neurons Among these are the great contributions to the principles, experiments and applications of neuro-electrical stimulation published by Rattay [29] In order to better understand the mechanism of electrical activity

of neurons, the scientists modeled the neuron as an electronic circuit and the neurotransmission as the electrical signal transmission in the circuit Laying the groundwork for electronic circuitry model of neurons are Hodgkin AL and Huxley AF [38], describe the action potential pulse using linear differential equations given by FitzHugh [27], [43] is an additional and evolving step for the neuron electronic model of Hodgkin and Huxley After that, many scientists

studied electronic circuit modeling for neurons by making various electronic circuit models to evaluate the stimulation of neurons as well as describe the respond by operating pulse form with the value of potential close to reality [57], [58] In parallel with the study of parameters affecting electrical stimulation of nerve cells [13 - 14], [39], neuronal potential recording technology has been developed since the 1940s Originating from the recording of the action potential of a single neuron has helped to understand the operating characteristics of central nervous system structures Later on, this technique was applied in many research directions such as using extracellular microelectrodes to locate potential characteristics of a neuron in in-vitro research, thereby helping to solve the fundamental problem which is the excitability of dendrites of neurons [31], [71] Recently, researchs focus on the response of neurons in relation to awakening and motor behaviors, or identifying connections between neurons in different centers [66] At the same time, technology and equipment have also been improved to allow for more accurate and convenient nerve cell survey and analysis [42] The technique to record the activity of nerve cell voltage has also been studied and published by many scientists [20], [31], [42], [71] The system that stimulates and records nerve cell activity as well as the animal's behavioral response to stimulation has also been studied and tested Numerous studies of stimulus and recording systems in response to the act of pressing the lever and receiving rewards were also reported [17], [32]; or the spatial response of the hippocampal place cell

in the maze [3], [75], [84] In animals, hippocampal lesions or dopamine receptor deficiencies will affect the animal's ability to remember with spatial response [86 - 90]

Moreover, depending on the purpose of the research, scientists use devices for stimulating and recording the electrical activity of neurons as well as