Neural Network Learning in Humans

Giselher Schalow
Private Researcher, Switzerland

Series: Neuroscience Research Progress
BISAC: MED057000



Volume 10

Issue 1

Volume 2

Volume 3

Special issue: Resilience in breaking the cycle of children’s environmental health disparities
Edited by I Leslie Rubin, Robert J Geller, Abby Mutic, Benjamin A Gitterman, Nathan Mutic, Wayne Garfinkel, Claire D Coles, Kurt Martinuzzi, and Joav Merrick


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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.
(Imprint: Nova Biomedical)


Chapter I: Theory of Neural Network Learning

Chapter II: Rate of Neuronal Network Learning in the Healthy and Injured Human CNS

Chapter III: Neural Network Learning in Coma Patients

Chapter IV: Learning to Improve Health in Aging and Cancer Treatment

Chapter V: Learning to Improve Higher Mental Functions and to Reduce Depression and Anxiousness Patterns



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