From Synaptic Interactions to Collective Dynamics in Random Neuronal Networks Models: Critical Role of Eigenvectors and Transient Behavior | Citedby Results | Neural Computation | MIT Press

Skip to Main Content

Skip Nav Destination

From Synaptic Interactions to Collective Dynamics in Random Neuronal Networks Models: Critical Role of Eigenvectors and Transient Behavior

Neural Computation (2020) 32 (2): 395–423.

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

Different eigenvalue distributions encode the same temporal tasks in recurrent neural networks

Cecilia Jarne

Cognitive Neurodynamics (2023) 17 (1): 257.

Eigenfunction non-orthogonality factors and the shape of CPA-like dips in a single-channel reflection from lossy chaotic cavities

Yan V Fyodorov
Mohammed Osman

Journal of Physics A: Mathematical and Theoretical (2022) 55 (22): 224013.

Network structural origin of instabilities in large complex systems

Chao Duan
Takashi Nishikawa
Deniz Eroglu
Adilson E. Motter

Science Advances (2022) 8 (28)

Real spectra of large real asymmetric random matrices

Wojciech Tarnowski

Physical Review E (2022) 105 (1)

Condition Numbers for Real Eigenvalues in the Real Elliptic Gaussian Ensemble

Yan V. Fyodorov
Wojciech Tarnowski

Annales Henri Poincaré (2021) 22 (1): 309.

Universal transient behavior in large dynamical systems on networks

Wojciech Tarnowski
Izaak Neri
Pierpaolo Vivo

Physical Review Research (2020) 2 (2)

Edge of Chaos and Avalanches in Neural Networks with Heavy-Tailed Synaptic Weight Distribution

Łukasz Kuśmierz
Shun Ogawa
Taro Toyoizumi

Physical Review Letters (2020) 125 (2)