Abstract. Humans are able to perform a large variety of periodic activ-ities in different modes, for instance cyclic rehearsal of phone numbers, humming a melody sniplet over and over again. These performances are, to a certain degree, robust against perturbations, and it often suffices to present a new pattern a few times only until it can be “picked up”. From an abstract mathematical perspective, this implies that the brain, as a dynamical system, (1) hosts a very large number of cyclic attractors, such that (2) if the system is driven by external input with a cyclic motif, it can entrain to a closely corresponding attractor in a very short time. This chapter proposes a simple recurrent neural network architecture which displays these dyn...
Recurrent collaterals in the brain represent the recollection and execution of various monotonous ac...
Neurodynamical models of working memory (WM) should provide mechanisms for storing, maintaining, ret...
A new learning algorithm for the storage of static and periodic attractors in biologically inspired ...
Most theoretical studies of the computational capabilities of balanced, recurrent E/I networks assu...
The brain's ability to tell time and produce complex spatiotemporal motor patterns is critical for a...
For the last twenty years, several assumptions have been expressed in the fields of information proc...
One way to understand the brain is in terms of the computations it performs that allow an organism t...
The article calls attention to complex dynamical phenomena in artificial neural systems, which are -...
Abstract—New method for modeling nonlinear systems called the echo state networks (ESNs) has been pr...
Chaos in dynamical systems potentially provides many different dynamical states arising from a singl...
The neural net computer simulations which will be presented here are based on the acceptance of a se...
At a first glance, artificial neural networks, with engineered learning algorithms and carefully cho...
Explaining how the brain works and processes information from multiple sources is still a current to...
We propose a simple neural network model to understand the dynamics of temporal pulse coding. The mo...
One of the central questions in neuroscience is how neurons and neuron populations communicate with ...
Recurrent collaterals in the brain represent the recollection and execution of various monotonous ac...
Neurodynamical models of working memory (WM) should provide mechanisms for storing, maintaining, ret...
A new learning algorithm for the storage of static and periodic attractors in biologically inspired ...
Most theoretical studies of the computational capabilities of balanced, recurrent E/I networks assu...
The brain's ability to tell time and produce complex spatiotemporal motor patterns is critical for a...
For the last twenty years, several assumptions have been expressed in the fields of information proc...
One way to understand the brain is in terms of the computations it performs that allow an organism t...
The article calls attention to complex dynamical phenomena in artificial neural systems, which are -...
Abstract—New method for modeling nonlinear systems called the echo state networks (ESNs) has been pr...
Chaos in dynamical systems potentially provides many different dynamical states arising from a singl...
The neural net computer simulations which will be presented here are based on the acceptance of a se...
At a first glance, artificial neural networks, with engineered learning algorithms and carefully cho...
Explaining how the brain works and processes information from multiple sources is still a current to...
We propose a simple neural network model to understand the dynamics of temporal pulse coding. The mo...
One of the central questions in neuroscience is how neurons and neuron populations communicate with ...
Recurrent collaterals in the brain represent the recollection and execution of various monotonous ac...
Neurodynamical models of working memory (WM) should provide mechanisms for storing, maintaining, ret...
A new learning algorithm for the storage of static and periodic attractors in biologically inspired ...