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Includes bibliographical references and index.

Neural anatomy -- The neuron -- Glial cells -- The brain -- Passive membranes -- Cellular electrophysiology -- Stimulating the passive membrane -- Strength-duration relationship -- The membrane at rest -- Numerical methods : the Euler method -- Active membranes -- The Hodgkin-Huxley model -- The Hodgkin-Huxley action potential -- Properties of neuronal action potentials -- Complex ionic models -- Phenomenological models -- Numerical methods : template for an active membrane -- Propagation -- Passive propagation in dendrites -- Active propagation in axons -- Pass the paper please -- Numerical methods : the finite and discrete cable -- Numerical methods : template for cable propagation -- Neural branches -- Lumped models -- Multicompartment models -- Numerical methods : matrix formulation -- Synapses -- Neurotransmitters -- The pre-synapse -- Neurotransmitter diffusion and clearance -- The post-synapse -- Synaptic summation -- Simplified models of the synapse -- The many mechanisms of diseases and drugs -- Synaptic plasticity and memory -- Networks of neurons -- Networks of neurons -- Model behavior -- Artificial neural networks -- Multi-layered networks -- Numerical methods -- Extracellular recording and stimulation -- Maxwell's equations applied to neurons -- Extracellular potential recordings -- Practical aspects of recording neural potentials -- Extracellular stimulation -- Numerical methods : computing phi-e in a cable -- The neural code -- Neural encoding -- Neural decoding -- Tuning Curves -- Applications -- Science and science fiction -- Neural imaging -- Neural stimulation -- Drug and genetic therapies -- Brain machine interface -- Growing neural tissue -- Artificial intelligence -- Conclusion.

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Quantitative Neurophysiology is supplementary text for a junior or senior level course in neuroengineering. It may also serve as an quick-start for graduate students in engineering, physics or neuroscience as well as for faculty interested in becoming familiar with the basics of quantitative neuroscience. The first chapter is a review of the structure of the neuron and anatomy of the brain. Chapters 2-6 derive the theory of active and passive membranes, electrical propagation in axons and dendrites and the dynamics of the synapse. Chapter 7 is an introduction to modeling networks of neurons and artificial neural networks. Chapter 8 and 9 address the recording and decoding of extracellular potentials. The final chapter has descriptions of a number of more advanced or new topics in neuroengineering. Throughout the text, vocabulary is introduced which will enable students to read more advanced literature and communicate with other scientists and engineers working in the neurosciences. Numerical methods are outlined so students with programming knowledge can implement the models presented in the text. Analogies are used to clarify topics and reinforce key concepts.Finally, homework and simulation problems are available at the end of each chapter.

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Title from PDF t.p. (viewed on Nov. 5, 2008).