Brain and Classical Neural Networks

Abstract

Brain and Classical Neural Networks gives a modern review of classical neurodynamics, including brain physiology, biological and artificial neural networks, synchronization, spike neural nets and wavelet resonance, motor control and learning. It includes the following sections:

• 2.1 Human Brain

  This section presents the basics of Basics of Brain Physiology necessary for comprehensive reading of the book.

• 2.2 Biological versus Artificial Neural Networks

  This section reviews standard models of artificial neural networks and contrasts them with biophysical models of neural ensembles.

• 2.3 Synchronization in Neurodynamics

  This section elaborates on the important concept of synchronization in coupled chaotic oscillators, neural dynamical systems, and Kuramoto-type models, using methods based on Lyapunov exponents.

• 2.4 Spike Neural Networks and Wavelet Resonance

  This section presents wavelet-based neural-ensemble dynamics in general and in epileptic spikes in particular.

• 2.5 Human Motor Control and Learning

  This section presents basics of human neuro-motor control, memory, and motor learning and cerebellar muscular synergy.