Metastable Dynamics of Neural Ensembles

A classical view of neural computation is that it can be characterized in terms of convergence to attractor states or sequential transitions among states in a noisy background. After over three decades, is this still a valid model of how brain dynamics implements cognition? This book provides a comp...

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Bibliographic Details
Main Author: Emili Balaguer-Ballester (auth)
Other Authors: Ruben Moreno-Bote (auth), Gustavo Deco (auth), Daniel Durstewitz (auth)
Format: Book Chapter
Published: Frontiers Media SA 2018
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Online Access:Get Fullteks
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042 |a dc 
100 1 |a Emili Balaguer-Ballester  |4 auth 
700 1 |a Ruben Moreno-Bote  |4 auth 
700 1 |a Gustavo Deco  |4 auth 
700 1 |a Daniel Durstewitz  |4 auth 
245 1 0 |a Metastable Dynamics of Neural Ensembles 
260 |b Frontiers Media SA  |c 2018 
300 |a 1 electronic resource (152 p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a A classical view of neural computation is that it can be characterized in terms of convergence to attractor states or sequential transitions among states in a noisy background. After over three decades, is this still a valid model of how brain dynamics implements cognition? This book provides a comprehensive collection of recent theoretical and experimental contributions addressing the question of stable versus transient neural population dynamics from complementary angles. These studies showcase recent efforts for designing a framework that encompasses the multiple facets of metastability in neural responses, one of the most exciting topics currently in systems and computational neuroscience. 
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546 |a English 
653 |a Attractor Dynamics 
653 |a Trial-to-trial Variability 
653 |a Transient Dynamics 
653 |a Neural Noise 
653 |a Metastability 
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