Nonlinear Forecasting And Correlation Dimension Of Brain Dynamics : A Multichannel Study Nonlinear Forecasting And Correlation Dimension Of Brain Dynamics : A Multichannel Study.

Pezard,; Martinerie,; Breton,

doi:10.1109/iembs.1992.594677

Cited by 2 publications

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Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients

Gómez

Hornero

Mediavilla

et al. 2008

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Abstract-The goal of this study was to analyze the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD) using a nonlinear forecasting measure. It is a nonparametric method to quantify the predictability of time series. Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 15 patients with probable AD and 15 elderly control subjects. Stationary epochs of 5 seconds (848 points, sample frequency of 169.55 Hz) were selected. Our results showed that AD patients' MEGs were more predictable than controls' recordings. Additionally, an accuracy of 76.7% (80.0% sensitivity; 73.3% specificity) was reached using a receiver operating characteristic curve. These preliminary results suggest the usefulness of nonlinear forecasting to gain a better understanding of dynamical processes underlying the MEG recording.

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Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients

Gómez

Hornero

Mediavilla

et al. 2008

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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On the validity of estimating EEG correlation dimension from a spatial embedding

1996

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We demonstrate by using simulations that spatial embedding of single-variable time series data does not reliably reconstruct state-space dynamics. Instead, correlation dimension estimated from spatially embedded data is largely a measure of linear cross-correlation in the data set. For actual electroencephalographic (EEG) data, we demonstrate a high negative correlation between spatial correlation dimension and the average amount of lag-zero cross-correlation between "nearest-neighbor" embedding channels (the greater the cross-correlation, the lower the dimension). We also show that the essential results obtained from spatially embedding EEG data are also obtained when one spatially embeds across a set of highly cross-correlated stochastic (second-order autoregressive) processes. Although, with appropriate surrogate data, correlation dimension estimated from spatially embedded data detects nonlinearity, its use is not recommended because correlation dimension estimated from temporally embedded data both reconstructs state-space dynamics and, with appropriate surrogate data, detects nonlinearity as well.

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Nonlinear Forecasting And Correlation Dimension Of Brain Dynamics : A Multichannel Study Nonlinear Forecasting And Correlation Dimension Of Brain Dynamics : A Multichannel Study.

Cited by 2 publications

References 0 publications

Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients

Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients

On the validity of estimating EEG correlation dimension from a spatial embedding

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