Nonlinear dynamical analysis of EEG and MEG: review of an emerging field
CJ Stam - Clinical neurophysiology, 2005 - Elsevier
Many complex and interesting phenomena in nature are due to nonlinear phenomena. The
theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a …
theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a …
[HTML][HTML] Is there chaos in the brain? II. Experimental evidence and related models
H Korn, P Faure - Comptes rendus biologies, 2003 - Elsevier
The search for chaotic patterns has occupied numerous investigators in neuroscience, as in
many other fields of science. Their results and main conclusions are reviewed in the light of …
many other fields of science. Their results and main conclusions are reviewed in the light of …
Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study
Background Seizure prediction would be clinically useful in patients with epilepsy and could
improve safety, increase independence, and allow acute treatment. We did a multicentre …
improve safety, increase independence, and allow acute treatment. We did a multicentre …
Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state
We compare dynamical properties of brain electrical activity from different recording regions
and from different physiological and pathological brain states. Using the nonlinear prediction …
and from different physiological and pathological brain states. Using the nonlinear prediction …
Application of entropy measures on intrinsic mode functions for the automated identification of focal electroencephalogram signals
The brain is a complex structure made up of interconnected neurons, and its electrical
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
Practical implementation of nonlinear time series methods: The TISEAN package
R Hegger, H Kantz, T Schreiber - Chaos: An Interdisciplinary Journal of …, 1999 - pubs.aip.org
We describe the implementation of methods of nonlinear time series analysis which are
based on the paradigm of deterministic chaos. A variety of algorithms for data …
based on the paradigm of deterministic chaos. A variety of algorithms for data …
Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients
To derive tests for randomness, nonlinear-independence, and stationarity, we combine
surrogates with a nonlinear prediction error, a nonlinear interdependence measure, and …
surrogates with a nonlinear prediction error, a nonlinear interdependence measure, and …
Wavelet entropy: a new tool for analysis of short duration brain electrical signals
Since traditional electrical brain signal analysis is mostly qualitative, the development of new
quantitative methods is crucial for restricting the subjectivity in the study of brain signals …
quantitative methods is crucial for restricting the subjectivity in the study of brain signals …
Entropies for detection of epilepsy in EEG
N Kannathal, ML Choo, UR Acharya… - Computer methods and …, 2005 - Elsevier
The electroencephalogram (EEG) is a representative signal containing information about the
condition of the brain. The shape of the wave may contain useful information about the state …
condition of the brain. The shape of the wave may contain useful information about the state …
Epileptic seizure prediction and control
LD Iasemidis - IEEE Transactions on Biomedical Engineering, 2003 - ieeexplore.ieee.org
Epileptic seizures are manifestations of epilepsy, a serious brain dynamical disorder second
only to strokes. Of the world's/spl sim/50 million people with epilepsy, fully 1/3 have seizures …
only to strokes. Of the world's/spl sim/50 million people with epilepsy, fully 1/3 have seizures …