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Neuronal Noise: Springer Series in Computational Neuroscience, cartea 8

Autor Alain Destexhe, Michelle Rudolph-Lilith
en Limba Engleză Paperback – 23 feb 2014
Neuronal Noise combines experimental, theoretical and computational results to show how noise is inherent to neuronal activity, and how noise can be important for neuronal computations.  The book covers many aspects of noise in neurons, with an emphasis on the largest source of noise: synaptic noise. It provides students and young researchers with an overview of the important methods and concepts that have emerged from research in this area. It also provides the specialist with a summary of the large body of sometimes contrasting experimental data, and different theories proposed to explore the computational power that various forms of "noise" can confer to neurons.
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Specificații

ISBN-13: 9781489990297
ISBN-10: 1489990291
Pagini: 476
Ilustrații: XVIII, 458 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.65 kg
Ediția:2012
Editura: Springer Us
Colecția Springer
Seria Springer Series in Computational Neuroscience

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

1 Introduction.- 2 Basics.- 3 Synaptic noise.- 4 Models of synaptic noise.- 5 Integrative properties in the presence of noise6 Recreating synaptic noise using dynamic-clamp.- 7 The mathematics of synaptic noise.- 8 Analyzing synaptic noise.- 9 Case studies.- 10 Conclusions and perspectives A Numerical integration of stochastic differential equations.- B Distributed Generator Algorithm.- C The Fokker-Planck formalism.- D The RT-NEURON interface for dynamic-clamp.- References.- Index.

Textul de pe ultima copertă

Neuronal Noise combines experimental, theoretical and computational results to show how noise is inherent to neuronal activity, and how noise can be important for neuronal computations.  The book covers many aspects of noise in neurons, with an emphasis on the largest source of noise: synaptic noise. It provides students and young researchers with an overview of the important methods and concepts that have emerged from research in this area. It also provides the specialist with a summary of the large body of sometimes contrasting experimental data, and different theories proposed to explore the computational power that various forms of "noise" can confer to neurons.

Caracteristici

Neuronal Noise combines experimental, theoretical and computational results to show how noise is inherent to neuronal activity The book covers many aspects of noise in neurons, with an emphasis on the largest source of noise: synaptic noise Provides students and young researchers with an overview of the important methods and concepts that have emerged from research in this area