Noise-activated transitions between coexisting attractors are investigated in a chaotic spiking network. At low noise level, attractor hopping consists of discrete bifurcation events that conserve the memory of initial conditions. When the escape probability becomes comparable to the intra-basin hopping probability, the lifetime of attractors is given by a detailed balance where the less coherent attractors act as a sink for the more coherent ones. In this regime, the escape probability follows an activation law allowing us to assign pseudo-activation energies to limit cycle attractors. These pseudo-energies introduce a useful metric for evaluating the resilience of biological rhythms to perturbations
A paradox in neuroscience is the large number of oscillations of small neural networks compared with...
We investigate a model for neural activity that generates long range temporal correlations, 1/ f noi...
The brain exhibits temporally complex patterns of activity with features similar to those of chaotic...
This is the author accepted manuscript. The final version is available from the Society for Industri...
We consider the stochastic dynamics of escape in an excitable system, the FitzHugh-Nagumo (FHN) neur...
The taxonomy of collective states in models of neuronal networks must grow in tandem with relevant m...
Systems of globally coupled phase oscillators can have robust attractors that are heteroclinic netwo...
Oscillations arise in many real-world systems and are associated with both functional and dysfunctio...
The authors acknowledge financial support from H2020-MSCA-ITN-2015 project COSMOS 642563. We thank A...
This is the final version of the article. Available from American Physical Society via the DOI in th...
We demonstrate a noisy resonance phenomenon in a winner-takes-all neural network. We derive an expre...
The paper demonstrates the possibility to control the collective behavior of a large network of exci...
Neural computations underlying cognitive functions require calibration of the strength of excitatory...
The computational abilities of recurrent networks of neurons with a linear activation function above...
Copyright © by Society for Industrial and Applied Mathematics. Unauthorized reproduction of this art...
A paradox in neuroscience is the large number of oscillations of small neural networks compared with...
We investigate a model for neural activity that generates long range temporal correlations, 1/ f noi...
The brain exhibits temporally complex patterns of activity with features similar to those of chaotic...
This is the author accepted manuscript. The final version is available from the Society for Industri...
We consider the stochastic dynamics of escape in an excitable system, the FitzHugh-Nagumo (FHN) neur...
The taxonomy of collective states in models of neuronal networks must grow in tandem with relevant m...
Systems of globally coupled phase oscillators can have robust attractors that are heteroclinic netwo...
Oscillations arise in many real-world systems and are associated with both functional and dysfunctio...
The authors acknowledge financial support from H2020-MSCA-ITN-2015 project COSMOS 642563. We thank A...
This is the final version of the article. Available from American Physical Society via the DOI in th...
We demonstrate a noisy resonance phenomenon in a winner-takes-all neural network. We derive an expre...
The paper demonstrates the possibility to control the collective behavior of a large network of exci...
Neural computations underlying cognitive functions require calibration of the strength of excitatory...
The computational abilities of recurrent networks of neurons with a linear activation function above...
Copyright © by Society for Industrial and Applied Mathematics. Unauthorized reproduction of this art...
A paradox in neuroscience is the large number of oscillations of small neural networks compared with...
We investigate a model for neural activity that generates long range temporal correlations, 1/ f noi...
The brain exhibits temporally complex patterns of activity with features similar to those of chaotic...