About the Book
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 87. Chapters: Artificial neural network, Action potential, Neural oscillation, Neuroinformatics, Connectome, Types of artificial neural networks, Dendritic spine, Cultured neuronal network, Connectionism, Neural coding, Biological neuron model, Cable theory, Bayesian brain, Hebbian theory, BCM theory, Soliton model, Hodgkin-Huxley model, Temporal difference learning, Theoretical neuromorphology, Blue Brain Project, Spike-triggered average, Brain-reading, Neurocybernetics, Neural backpropagation, Neuronstudio, Backpropagation through time, Linear-nonlinear-Poisson cascade model, Regulatory feedback network, AnimatLab, Parallel Constraint Satisfaction Processes, Cerebellar Model Articulation Controller, Human Connectome Project, International Neuroinformatics Coordinating Facility, Modular neural networks, Wilson-Cowan model, Artificial Intelligence System, Brian, FitzHugh-Nagumo model, Softmax activation function, NeuroElectroDynamics, Laurent Itti, Infomax, Neural Information Processing Systems, Hindmarsh-Rose model, NOMFET, Spike-triggered covariance, CARET, Fast Analog Computing with Emergent Transient States, Phase-of-firing code, Neurogrid, Diffusion Networks, Pulse computation, Spike directivity. Excerpt: In physiology, an action potential is a short-lasting event in which the electrical membrane potential of a cell rapidly rises and falls, following a consistent trajectory. Action potentials occur in several types of animal cells, called excitable cells, which include neurons, muscle cells, and endocrine cells, as well as in some plant cells. In neurons, they play a central role in cell-to-cell communication. In other types of cells, their main function is to activate intracellular processes. In muscle cells, for example, an action potential is the first step in the chain of events leading to contraction. In beta cells of t...
