Transcranial Magnetic and Electrical Brain Stimulation for Neurological Disorders

Front Cover
TRANSCRANIAL MAGNETIC AND ELECTRICAL BRAIN STIMULATION FOR NEUROLOGICAL DISORDERS
TRANSCRANIAL MAGNETIC AND ELECTRICAL BRAIN STIMULATION FOR NEUROLOGICAL DISORDERS
Copyright
Dedication
Contents
About the authors
Preface
Acknowledgment
1 - Foundation of electromagnetic theory
1.1 Introduction
1.2 Vector analysis
1.2.1 Vector algebra
1.2.1.1 Sum of two vectors
1.2.1.2 Subtraction of two vectors
1.2.1.3 Multiplication of two vectors
1.2.2 Scalar product of two vectors
1.2.3 Vector product of two vectors
1.2.3.1 Devision of two vectors
1.2.4 Vector gradient
1.2.5 Vector integration
1.2.6 Vector divergence
1.2.7 Vector curl
1.2.8 Vector differential operator
1.3 Further developments
1.4 Electrostatics
1.4.1 The Coulomb's law
1.4.2 The electric field
1.4.3 The Gauss's law
1.5 Solution of electrostatics problems
1.5.1 Poisson's equation
1.5.1.1 Rectangular or cartesian coordinate
1.5.1.2 Cylindrical coordinate
1.5.1.3 Spherical coordinate
1.5.2 Laplace's equation
1.6 Electrostatics energy
1.6.1 Potential energy of a group of point charges
1.6.2 Electrostatic energy of a charge distribution
1.6.3 Forces and torques
1.6.3.1 The rate of energy transfer (per unit volume) from a region of space equals the rate of work done on a charge distribution ...
1.7 Mx's equations
1.8 The Law of Biot and Savart
1.9 The lorentz transformation
1.10 Electric field of a moving charge
1.11 Interaction between two moving charges
1.12 Elementary applications of the Biot and Savart Law
1.12.1 Example - one
1.12.2 Example - two
1.12.3 Example - three
1.12.4 Example - four
1.12.5 The infinite filament wire application of Biot-Savart law
1.12.5.1 Example - one
1.12.5.2 Example - two
1.13 A's law
1.13.1 Example - one
1.13.2 Example - two
1.13.3 Example - three
1.13.4 Example - four
1.13.5 Example - five
1.13.6 A's law in point form
1.13.6.1 Example - one
1.14 Scalar and vector potentials
1.15 Hall effect
References
2 - All about wave equations
2.1 Introduction
2.2 The classical wave equation and separation of variables
2.3 Standing waves
2.4 Seiche wave
2.4.1 Lake seiche
2.4.2 Sea and Bay seiche
2.5 Underwater or internal waves
2.6 Maxwell's equations and electromagnetic waves
2.7 Scalar and vector potentials
2.8 Gauge transformations, Lorentz gauge, and Coulomb gauge
2.9 Infrastructure, characteristic, derivation, and properties of scalar waves
2.9.1 Derivation of the scalar waves
2.9.1.1 Near-field difficulties
2.9.1.2 Far-filed transition
2.9.1.3 Scalar wave model
2.9.1.4 Double-frequent oscillation of size
2.9.1.5 Electric and magnetic scalar wave
2.9.1.6 Scalar wave properties
2.9.1.7 Comparison of the parts of Tesla and Hertz
2.9.1.8 Noise, a scalar wave phenomenon
2.9.1.9 Neutrino radiation
2.9.1.10 Parallel instead of serial image transmission
2.9.1.11 Research of scalar wave
2.9.2 Wave energy
2.9.3 The particles or charge field expression
2.9.4 Particle energy
2.9.5 Velocity
2.9.6 The magnetic field
2.9.7 The scalar field
2.9.8 Scalar fields, from classical electromagnetism to quantum mechanics
2.9.8.1 The Aharonov-Bohm effect
2.9.8.2 The existence of potential and scalar fields and waves
2.9.8.3 Scalar field generators
2.9.8.4 The detection of scalar fields
2.9.8.5 Power transmission and the extension to nuclear fields
2.9.8.6 The conclusion
2.9.8.6.1 Scalar fields, from classical electromagnetism to quantum mechanics
2.9.8.6.2 Quantum gauge invariance
2.9.8.6.3 Quantum gauge invariance
2.9.8.6.4 The matrix of space-time
2.9.9 Our body works with scalar waves
2.9.10 Scalar wave driven by interferometer paradiagm
2.9.11 Wireless transmission of energy at a distance driven by interferometry
2.10 The quantum waves
2.11 The X-waves
2.12 The nonlinear X-waves
2.13 The bessel's waves
2.14 Generalized solution to wave equation
References
Further reading
3 - Computational neuroscience and compartmental modeling
3.1 Introduction
3.2 Fuzzy logic and neural networks
3.3 Rise of machines, artificial super-intelligence
3.4 Fundamental issues of artificial intelligence
3.5 Ethics of big and small of artificial intelligence
3.6 Brian, a neural wet computer
3.6.1 Semantics of mental states
3.7 The computational theory of mind
3.8 Artificial intelligence
3.9 What is intelligence?
3.9.1 Learning
3.9.2 Reasoning
3.9.3 Problem solving
3.9.4 Perception
3.9.5 Language understanding
3.10 The cognitive modeling approach driven by human thinking
3.11 Type of artificial intelligence
3.11.1 Type 1: reactive machines
3.11.2 Type 2: limited memory
3.11.3 Type 3: theory of mind
3.11.4 Type 4: self-awareness
3.11.5 Weak artificial intelligence or narrow artificial intelligence
3.11.6 Strong artificial intelligence or artificial general intelligence
3.12 Example of artificial intelligence technology
3.13 Artificial intelligence applications
3.14 The artificial intelligence: the road to superintelligence
3.15 The rise of artificial intelligence and its threat to humanity
3.15.1 Watson's key components include
3.16 Neurons and brain cells
3.17 Type of neurons
3.18 Neuroscience, and brains processing information
3.19 Neural networks
3.20 The classical computational theory of mind
3.21 Computational neuroscience
3.22 Embodied cognition
3.23 On the nature of cognition
3.24 Modeling neurons
3.24.1 Detailed compartmental models
3.24.2 Detailed compartmental models
3.24.3 Single and few compartment models
3.25 Equivalent circuit of a single compartment
3.26 Axonal connections, synapses, and networks
3.27 Simulation accuracy
3.27.1 Choice of numerical integration technique
3.27.2 Integration time steps
3.27.3 Accuracy of GENESIS
References
Further reading
4 - The impact of technology on mental health
4.1 Introduction
4.2 The impact of modern technology on mental health
4.2.1 The emergence of the “constant checker”
4.2.2 Digital connectivity and well-being
4.2.3 Happiness
4.2.4 Isolation
4.2.5 Depression
4.2.6 Children and familial, digital connections
4.2.7 Video gaming and aggression
4.3 Is social media ruining your social life?
4.4 Social media use and depression linked in large study
4.5 Physicians: can social media make or break your career?
4.6 Generation stress: the mental health crisis on campus
4.6.1 Things really are different
4.6.2 Challenge and response
4.6.3 Challenge and response approaches
4.7 How can we overcome loneliness?
4.8 Common disorders
4.9 Mood disorders
4.10 Early signs of depression
4.11 Treatments
4.12 Cognitive behavioral therapy
4.12.1 What is cognitive behavioral therapy
4.12.2 Background of cognitive behavioral therapy
4.13 Prevalence of any mental illness
4.13.1 Diagnostic assessment
4.13.2 Population
4.13.3 Survey nonresponse
4.13.4 Diagnostic assessment and population
4.13.5 Survey nonresponse
4.14 Electrical brain stimulation to treat neurological disorder
4.14.1 Detailed description to treat neurological disorder
4.14.2 Applications driven by treatment neurological disorder
4.14.3 What is claimed to treatment of neurological disorder
References
Further reading
5 - Sleep driving improvement of declarative memory
5.1 Introduction
5.2 Enhancing long-term memory
5.2.1 Explicit memory
5.2.2 Implicit memory
5.2.3 Priming memory
5.2.4 Episodic memory
5.2.5 Semantic memory
5.2.6 Procedural memory
5.2.7 BrainHQ for better memory
5.3 Different sleep stages for memory formation
5.4 Reactivation of newly formed memories during sleep
5.5 Electrophysiological signs: spindle activity, direct current potentials, and slow oscillations
5.6 Acetylcholine, a neurotransmitter regulating sleep and memory
5.7 Electrosleep—a clinical trail approach
5.8 Conclusion
References
6 - Electrical brain stimulation to treat neurological disorders
6.1 Introduction
6.2 A brief history
6.3 Recently emerging methods
6.3.1 Transcranial Direct Current Stimulation
6.3.2 Transcranial Alternating Current Stimulation
6.3.3 Transcranial Random Noise Stimulation
6.3.4 Transcranial magnetic stimulation
6.3.5 Repetitive Transcranial Magnetic Stimulation
6.3.5.1 Repetitive Transcranial Magnetic Stimulation side effects
6.3.6 Transcranial Electrical Stimulation
6.3.6.1 Advantages of transcranial electrical stimulation therapy
6.3.7 Repetitive Transcranial Electrical Stimulation
6.3.8 Magnetic Seizure Therapy
6.3.8.1 Magnetic Seizure Therapy side effects
6.3.9 Vagus Nerve Stimulation
6.3.9.1 Vagus Nerve Stimulation side effects
6.3.10 Deep Brain Stimulation
6.3.11 Deep Brain Stimulation side effects
6.3.12 Cortical Brain Stimulation
6.3.13 Electroconvulsive Therapy
6.3.13.1 Electroconvulsive Therapy side effects
6.3.14 Position Emission Tomography
6.3.14.1 Risk involved with position emission tomography
6.3.14.2 How do you prepare for a (PET) scan?
6.3.14.2.1 A few days before PET scan
6.3.14.2.2 The day before PET scan
6.3.14.2.3 Hours before PET scan
6.3.14.3 Other considerations
6.3.15 Electroencephalography
6.3.15.1 Electroencephalography risks
6.3.15.2 Electroencephalography advantages
6.3.15.3 Electroencephalography disadvantages
6.3.15.4 Electroencephalography mechanisms
6.3.15.5 Electroencephalography methods
6.3.16 Quantitative Electroencephalography
6.3.17 Magnetic resonance imaging
6.3.17.1 How magnetic resonance imaging works?
6.3.17.2 Diffusion magnetic resonance imaging
6.3.17.3 Functional magnetic resonance imaging
6.3.17.4 Magnetic resonance imaging safety
6.4 Applications
6.5 Conclusions
References
7 - Brain stimulation therapies
7.1 Introduction
7.2 A better approach to therapy
7.3 Physical and mathematical background and technical characteristic of TMS
7.3.1 Mathematical modeling of TMS
7.4 TMS procedure description and main definitions
7.5 Cortical excitability studies
7.6 Neuronal plasticity studies
7.7 Effect of electric fields on individual neurons
7.8 Interaction of network oscillations and electric fields
7.9 Computational neural models
7.10 Effects of weak electric fields on the human brain
7.11 Electric fields future directions
References
Further reading
8 - Artificial intelligence driven by machine learning & deep learning
8.1 Introduction
8.2 History of artificial intelligence
8.3 Weak artificial intelligence (WAI)
8.3.1 Technological singularity
8.4 Artificial general intelligence (AGI)
8.4.1 Existential risk from artificial general intelligence
8.5 Natural language processing (NLP)
8.5.1 How does natural language processing (NLP) work?
8.5.1.1 Named entity recognition (NER)
8.5.1.2 Natural language generation (NLG)
8.6 Cognitive science and cognitive linguistics
8.7 Big data
8.7.1 Big data history and current considerations
8.7.2 What are big data and big data analytics?
8.7.3 Why is the big data important?
8.7.4 Where the big data is used and who uses it?
8.7.4.1 Government
8.7.4.2 Education
8.7.4.3 Banking
8.7.4.4 Health care
8.7.4.5 Manufacturing
8.7.4.6 Retail
8.7.5 How does the big data works?
8.7.5.1 Streaming data
8.7.5.2 Social media data
8.7.5.3 Publicly available sources
8.8 Summary and conclusion
References
9 - Artificial Intelligence–driven mental health and depression treatment
9.1 Introduction
9.2 Depression basics
9.2.1 Major depression
9.2.2 Persistent depression disorder (dysthymia)
9.3 What are the signs and symptoms of depression?
9.4 Artificial Intelligence and Optical Character Recognition
9.5 Conclusion
References
10 - Global suicide rate among youngsters increasing significantly
10.1 Introduction
10.2 Who is at risk for suicide and why?
10.3 What are the warning signs for suicide?
10.4 The impact of modern technology on mental health?
10.5 Transcranial magnetic stimulation driving depression treatment
10.6 Transcranial alternating current stimulation
10.7 Transcranial random noise stimulation
10.8 Feasibility of artificial intelligence in suicide risk prediction and management
References
A - Proofs of integral relations
A.1 THE LAPLACIAN OF 1/|R→−R→′|=1/R
A.2 THE DIVERGENCE OF E→
A.3 THE SCALAR HELMHOLTZ INTEGRAL (STATIC)
A.4 AMPERE'S CIRCUITAL LAW (MAGNETOSTATIC)
A.5 THE VECTOR HELMHOLTZ INTEGRAL (STATIC)
A.6 THE VECTOR HELMHOLTZ INTEGRAL – GENERAL CASE
A.7 DIVERGENCE THEOREM
A.8 STOKES THEOREM
B - Schrödinger wave equation
B.1 INTRODUCTION
B.2 SCHRÖDINGER EQUATION CONCEPT
B.3 THE TIME-DEPENDENT SCHRÖDINGER EQUATION CONCEPT
B.4 TIME-INDEPENDENT SCHRÖDINGER EQUATION CONCEPT
B.5 A FREE PARTICLE INSIDE A BOX AND DENSITY OF STATE
B.6 RELATIVISTIC SPIN ZERO PARTIES: KLEIN–GORDON EQUATION
B.6.1 Antiparticles
B.6.2 Negative energy states and antiparticles
B.6.3 Neutral particles
References
Index
A
B
C
D
E
F
G
H
I
K
L
M
N
O
P
Q
R
S
T
U
V
W
X
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