Mathematical and Theoretical Neuroscience [electronic resource] : Cell, Network and Data Analysis / edited by Giovanni Naldi, Thierry Nieus.

Інтелектуальна відповідальність: Вид матеріалу: Текст Серія: Springer INdAM Series ; 24Публікація: Cham : Springer International Publishing : Imprint: Springer, 2017Видання: 1st ed. 2017Опис: IX, 253 p. online resourceТип вмісту:
  • text
Тип засобу:
  • computer
Тип носія:
  • online resource
ISBN:
  • 9783319682976
Тематика(и): Додаткові фізичні формати: Printed edition:: Немає назви; Printed edition:: Немає назви; Printed edition:: Немає назвиДесяткова класифікація Дьюї:
  • 519 23
Класифікація Бібліотеки Конгресу:
  • T57-57.97
Електронне місцезнаходження та доступ:
Вміст:
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.
У: Springer eBooksЗведення: 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.
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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.

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