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Mathematical and Theoretical Neuroscience: Cell, Network and Data Analysis /

Mathematical and Theoretical Neuroscience: Cell, Network and Data Analysis /
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Field name Details
Dewey Class 519
Title Mathematical and Theoretical Neuroscience ([EBook]) : Cell, Network and Data Analysis / / edited by Giovanni Naldi, Thierry Nieus.
Added Personal Name Naldi, Giovanni editor.
Nieus, Thierry editor.
Other name(s) SpringerLink (Online service)
Publication Cham : : Springer International Publishing : : Imprint: Springer, , 2017.
Physical Details IX, 253 p. : online resource.
Series Springer INdAM Series 2281-518X ; ; 24
ISBN 9783319682976
Summary Note 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.:
Contents note 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.
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site http://dx.doi.org/10.1007/978-3-319-68297-6
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