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Mathematical and theoretical neurosc...

Naldi, Giovanni.

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Mathematical and theoretical neuroscience = cell, network and data analysis /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mathematical and theoretical neuroscience/ edited by Giovanni Naldi, Thierry Nieus.
其他題名:	cell, network and data analysis /
其他作者:	Naldi, Giovanni.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	ix, 253 p. :ill., digital ;24 cm.
內容註:	1 Simulating cortical Local Field Potentials and Thalamus dynamic regimes with integrate-and-fire neurons -- 2 Computational modeling as a means to defining neuronal spike pattern behaviors -- 3 Chemotactic guidance of growth cones: a hybrid computational model -- 4 Mathematical Modeling of Cerebellar Granular Layer Neurons and Network Activity: Information Estimation, Population Behaviour and Robotic Abstractions -- 5 Bifurcation analysis of a sparse neural network with cubic topology -- 6 Simultaneous jumps in interacting particle systems: from neuronal networks to a general framework -- 7 Neural fields: Localised states with piece-wise constant interactions -- 8 Mathematical models of visual perception based on cortical architectures -- 9 Mathematical models of visual perception for the analysis of Geometrical optical illusions -- 10 Exergaming for autonomous rehabilitation -- 11 E-infrastructures for neuroscientists: the GAAIN and neuGRID examples -- 12 Nonlinear Time series Analysis -- 13 Measures of spike train synchrony and Directionality -- 14 Space-by-time tensor decomposition of single-trial analysis of neural signals -- 15 Inverse Modeling for MEG/EEG data.
Contained By:	Springer eBooks
標題:	Neurosciences - Mathematical models. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-68297-6
ISBN:	9783319682976

Mathematical and theoretical neuroscience = cell, network and data analysis /
Mathematical and theoretical neurosciencecell, network and data analysis /[electronic resource] :edited by Giovanni Naldi, Thierry Nieus. - Cham :Springer International Publishing :2017. - ix, 253 p. :ill., digital ;24 cm. - Springer INdAM series,v.242281-518X ;. - Springer INdAM series ;v.24..

1 Simulating cortical Local Field Potentials and Thalamus dynamic regimes with integrate-and-fire neurons -- 2 Computational modeling as a means to defining neuronal spike pattern behaviors -- 3 Chemotactic guidance of growth cones: a hybrid computational model -- 4 Mathematical Modeling of Cerebellar Granular Layer Neurons and Network Activity: Information Estimation, Population Behaviour and Robotic Abstractions -- 5 Bifurcation analysis of a sparse neural network with cubic topology -- 6 Simultaneous jumps in interacting particle systems: from neuronal networks to a general framework -- 7 Neural fields: Localised states with piece-wise constant interactions -- 8 Mathematical models of visual perception based on cortical architectures -- 9 Mathematical models of visual perception for the analysis of Geometrical optical illusions -- 10 Exergaming for autonomous rehabilitation -- 11 E-infrastructures for neuroscientists: the GAAIN and neuGRID examples -- 12 Nonlinear Time series Analysis -- 13 Measures of spike train synchrony and Directionality -- 14 Space-by-time tensor decomposition of single-trial analysis of neural signals -- 15 Inverse Modeling for MEG/EEG data.

This volume gathers contributions from theoretical, experimental and computational researchers who are working on various topics in theoretical/computational/mathematical neuroscience. The focus is on mathematical modeling, analytical and numerical topics, and statistical analysis in neuroscience with applications. The following subjects are considered: mathematical modelling in Neuroscience, analytical and numerical topics; statistical analysis in Neuroscience; Neural Networks; Theoretical Neuroscience. The book is addressed to researchers involved in mathematical models applied to neuroscience.

ISBN: 9783319682976

Standard No.: 10.1007/978-3-319-68297-6doiSubjects--Topical Terms:

610833
Neurosciences
--Mathematical models.

LC Class. No.: QP357.5

Dewey Class. No.: 612.8

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