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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| Superior document: | Frontiers Research Topics |
|---|---|
| : | |
| Year of Publication: | 2018 |
| Language: | English |
| Series: | Frontiers Research Topics
|
| Physical Description: | 1 electronic resource (152 p.) |
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| 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. | ||
| 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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| 700 | 1 | |a Ruben Moreno-Bote |4 auth | |
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