Epilepsies as Dynamical Diseases of Brain Systems: Basic Models of the Transition Between Normal and Epileptic Activity

@article{DaSilva2003EpilepsiesAD,
  title={Epilepsies as Dynamical Diseases of Brain Systems: Basic Models of the Transition Between Normal and Epileptic Activity},
  author={Fernando Lopes Da Silva and Wouter Blanes and Stiliyan N Kalitzin and Jaime Parra and Piotr Suffczynski and Demetrios N. Velis},
  journal={Epilepsia},
  year={2003},
  volume={44}
}
Summary:  Purpose: The occurrence of abnormal dynamics in a physiological system can become manifest as a sudden qualitative change in the behavior of characteristic physiologic variables. We assume that this is what happens in the brain with regard to epilepsy. We consider that neuronal networks involved in epilepsy possess multistable dynamics (i.e., they may display several dynamic states). To illustrate this concept, we may assume, for simplicity, that at least two states are possible: an… Expand
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References

SHOWING 1-10 OF 76 REFERENCES
Dynamics of local neuronal networks: control parameters and state bifurcations in epileptogenesis.
TLDR
Evidence is presented that local neuronal networks (LNNs) are functionally organized in such a way that they behave as dynamic non-linear systems that can exhibit multiple types of attractor and can present bifurcations between different attractors, depending on control parameters. Expand
The epileptic process as nonlinear deterministic dynamics in a stochastic environment: an evaluation on mesial temporal lobe epilepsy
TLDR
This analysis framework was extended by introducing a new measure xi, designed to discriminate between nonlinear deterministic and linear stochastic dynamics, which allowed to retrospectively determine the side of the epileptogenic zone in full agreement with results of the presurgical workup. Expand
Epileptic seizures can be anticipated by non-linear analysis
TLDR
It is demonstrated that in most cases, seizure onset could be anticipated well in advance (between 2–6 minutes beforehand), and that all subjects seemed to share a similar 'route' towards seizure. Expand
Spatio-temporal dynamics of the primary epileptogenic area in temporal lobe epilepsy characterized by neuronal complexity loss.
  • K. Lehnertz, C. Elger
  • Psychology, Medicine
  • Electroencephalography and clinical neurophysiology
  • 1995
TLDR
To test whether a relationship exists between spatio-temporal alterations of neuronal complexity and spatial extent and temporal dynamics of the epileptogenic area, a moving-window correlation dimension analysis was applied to intracranially recorded electrocorticograms of 20 patients with unilateral temporal lobe epilepsy. Expand
Time dependencies in the occurrences of epileptic seizures
TLDR
The analysis of patient recorded time series of the occurrence of epileptic seizures shows that the epileptic process is not consistent with the rules of a homogeneous Poisson process or generally with a random (IID) process. Expand
Phase space topography and the Lyapunov exponent of electrocorticograms in partial seizures
TLDR
Electrocorticograms from 16 of 68 chronically implanted subdural electrodes, placed over the right temporal cortex in a patient with a right medial temporal focus, were analyzed and a methodology for detecting prominent spikes in the ECoG was developed. Expand
Characterization of state transitions in spatially distributed, chaotic, nonlinear, dynamical systems in cerebral cortex
  • W. Freeman
  • Physics, Medicine
  • Integrative physiological and behavioral science : the official journal of the Pavlovian Society
  • 1994
TLDR
Spatial phase gradients in the EEG are useful for identifying EEG segments in a sequence of state transitions in response to sensory input, and give strong reason to postulate that the mechanism for the construction of these sequences of patterns is a dynamical system operating in a chaotic domain. Expand
High‐frequency oscillations in human brain
TLDR
Two similar types of high‐frequency field oscillations recorded from the entorhinal cortex and hippocampus of patients with mesial temporal lobe epilepsy are described, which are found in the epileptogenic region and may reflect pathological hypersynchronous population spikes of bursting pyramidal cells. Expand
Cellular mechanisms of a synchronized oscillation in the thalamus.
TLDR
Reduction of gamma-aminobutyric acidA (GABAA) receptor-mediated inhibition markedly enhanced GABAB inhibitory postsynaptic potentials in relay cells and subsequently generated a slowed and rhythmic population activity resembling that which occurs during an absence seizure. Expand
Inhibition-based rhythms: experimental and mathematical observations on network dynamics.
TLDR
This review will provide the reader with a brief outline of the basic properties of inhibition-based oscillations in the CNS by combining research from laboratory models, large-scale neuronal network simulations, and mathematical analysis. Expand
...
1
2
3
4
5
...