Neural network learning in humans / Giselher Schalow, Dr. Med. Habil., Dr. Rer. Nat., Dipl. Ing.

Format:

Book

Author/Creator:

Schalow, Giselher, author.

Series:

Neuroscience research progress.

Neuroscience research progress

Language:

English

Subjects (All):

Neural networks (Neurobiology).

Nervous system.

Psychology.

Movement therapy.

Learning--Physiological aspects.

Learning.

Physical Description:

1 online resource (339 p.)

Place of Publication:

New York : Nova Biomedical, [2015]

Summary:

Based on human neurophysiology, it has been shown that the human brain and spinal cord can partly be repaired by movement-based learning. It seems that even to a very limited extent, new nerve cells can be built anew in the human central nervous system. Neural network learning starts with the knowledge of basic human neural network functions and their communication with the outside world. Neural network functions can only be explored thoroughly if it is partly known what impulse patterns run into and out of the networks. Even though the gained knowledge is rudimentary, it has immediate consequences for learning and the repair of the human central nervous system. This book discusses the theory of neural network learning. It provides research on neural network learning rates in healthy patients and patients with central nervous system injuries; neural network learning for coma patients; improving health in geriatric and cancer patients; and improving mental functions in patients with depression and anxiety.

Contents:

NEURAL NETWORK LEARNING IN HUMANS ; NEURAL NETWORK LEARNING IN HUMANS ; Contents; Preface; Chapter I Theory of Neural Network Learning; Abstract; 1. Introduction to Neural Network Learning; 1.1. From Repair to Learning; 1.2. Tools and Strategy to Study Human Neural Network learning; 2. Anatomy of the Spinal Cord and Cauda Equina Nerve Roots; 2.1. Anatomy of the Cauda Equina: A Site Where CNS Functioning Can Be Measured; 3. Recording of Single-Nerve Fiber Action Potentials (Electrophysiology); 3.1. Principle of Recording Single Afferent and Efferent Nerve Fiber Action Potentials

3.2. Recording of Single-nerve Fiber Action Potentials from Nerve Roots and Splitting of the Multiunit Recording into Natural Impulse Patterns of Several Single Afferent and Efferent Fibers4. Classification of Peripheral Human Nerve Fibers (Electrophysiology Combined with Morphometry); 4.1. Classification of Human Peripheral Nerve Fibers by the Group Conduction Velocity and the Group Nerve Fiber Diameter; 4.2. The Neuron Microenvironment Influences Neural Network Functioning; 5. Self-organization of Neuronal Networks of the Human Central Nervous System

5.1. Self-Organization of Premotor Spinal Network Oscillators5.2. Phase and Frequency Coordination among Neuron Firing for Human CNS Self-Organization; 5.3. Relative Phase and Frequency Coordination between the Firings of ( and (-Motoneurons and Secondary Muscle Spindle Afferents Recorded with the Single-nerve Fiber Action Potential Recording Method; 6. Surface Electromyography to Record Motor Programs, Oscillatory Firing, and Phase and Frequency Coordination among Motor Units (Electrophysiology); 6.1. Recording of Single-Motor Units; 6.2. Oscillatory Firing of Motoneurons and Motor Units

6.3. Motor Program Generation, Oscillatory Firing and Coordination Among (1-Motor Units (FF-type)6.4. Firing Frequency Increases with Increasing Load; 6.5. Motor Program Development; 6.6. Phase and Frequency Coordination between the Firing of the Motor Units; 6.7. Phase and Frequency Coordination's between (1-Motor Unit Firing of Different Muscles and Different Arms; 7. Similar Efferent Impulse Patterns Obtained with the Two Electrophysiological Methods Single-nerve Fiber Action Potential Recording Method and Single-Motor Unit sEMG

8. Integrative Physiology: System Theory of Pattern Formation8.1. The System Theory of Pattern Formation for Understanding Neuronal Network Organization and Learning; 8.2. Learning Implications for Treatment Derived from the Equations of Motion of the Collective Variables (Formula 2); 8.3. Geographical Landscape of Attractors; 8.4. Equation of Motion, Potential Function and Attractor Layout for the Movement 'Jumping on Springboard'; 8.5. Including the Variability of Phase and Frequency Coordination among Neuron Firing into the Equation of Motion of the Collective Variables

8.6. Geographical Landscape of Attractors

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on online resource; title from PDF title page (ebrary, viewed May 9, 2016).

ISBN:

1-63482-573-X