AbstractA new nonlinear dynamical analysis is applied to complex behavior from neuronal systems. The conceptual foundation of this analysis is the abstraction of observed neuronal activities into a dynamical landscape characterized by a hierarchy of “unstable periodic orbits” (UPOs). UPOs are rigorously identified in data sets representative of three different levels of organization in mammalian brain. An analysis based on UPOs affords a novel alternative method of decoding, predicting, and controlling these neuronal systems
The field of neural network modelling has grown up on the premise that the massively parallel distri...
The extreme complexity of the brain naturally requires mathematical modeling approaches on a large v...
Networks of dynamical systems are common models for many problems in physics, engineering, chemistry...
AbstractA new nonlinear dynamical analysis is applied to complex behavior from neuronal systems. The...
Although nonlinear dynamics have been mastered by physicists and mathematicians for a long time (as ...
With many areas of science reaching across their boundaries and becoming more and more interdiscipli...
As we strive to understand the mechanisms underlying neural computation, mathematical models are inc...
The developments in nonlinear dynamics and the theory of chaos have considerably altered our percept...
The article calls attention to complex dynamical phenomena in artificial neural systems, which are -...
We investigate the phase space dynamics of local systems of biological neurons in order to deduce th...
Many complex and interesting phenomena in nature are due to nonlinear phenomena. The theory of nonli...
We investigate the phase space dynamics of local systems of biological neurons in order to deduce th...
We begin with a brief review of the abstract dynamical system that models systems of biological neur...
81 pages, 91 figures, review paperInternational audienceThis paper presents an overview of some tech...
Abstract In-depth understanding of the generic mech-anisms of transitions between distinct patterns ...
The field of neural network modelling has grown up on the premise that the massively parallel distri...
The extreme complexity of the brain naturally requires mathematical modeling approaches on a large v...
Networks of dynamical systems are common models for many problems in physics, engineering, chemistry...
AbstractA new nonlinear dynamical analysis is applied to complex behavior from neuronal systems. The...
Although nonlinear dynamics have been mastered by physicists and mathematicians for a long time (as ...
With many areas of science reaching across their boundaries and becoming more and more interdiscipli...
As we strive to understand the mechanisms underlying neural computation, mathematical models are inc...
The developments in nonlinear dynamics and the theory of chaos have considerably altered our percept...
The article calls attention to complex dynamical phenomena in artificial neural systems, which are -...
We investigate the phase space dynamics of local systems of biological neurons in order to deduce th...
Many complex and interesting phenomena in nature are due to nonlinear phenomena. The theory of nonli...
We investigate the phase space dynamics of local systems of biological neurons in order to deduce th...
We begin with a brief review of the abstract dynamical system that models systems of biological neur...
81 pages, 91 figures, review paperInternational audienceThis paper presents an overview of some tech...
Abstract In-depth understanding of the generic mech-anisms of transitions between distinct patterns ...
The field of neural network modelling has grown up on the premise that the massively parallel distri...
The extreme complexity of the brain naturally requires mathematical modeling approaches on a large v...
Networks of dynamical systems are common models for many problems in physics, engineering, chemistry...