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Optimization of Embedding Parameters for Prediction of Seizure Onset with Mutual Information

In: Nonlinear Dynamics and Statistics

Author

Listed:
  • Alfonso M. Albano
  • Christopher J. Cellucci
  • Richard N. Harner
  • Paul E. Rapp

Abstract

Normal neurological function is characterized by a high volume of information transferred between different parts of the central nervous system. An imperfect, but nonetheless useful, assessment of this spatially distributed transfer process can be obtained by examining multichannel EEG records that are measured with an array of scalp electrodes. A nonlinear quantitative measure of the transfer can be obtained by calculating the pairwise mutual information of each electrode pair. The average mutual information of two time series is the amount of information of one that can be predicted by measuring the other. As suggested in our previous work, a reduction in information transfer, as estimated by this metric, can occur prior to clinically discernible seizure onset. In the case of the focal seizure examined here, this reduction first occurred in the area of the brain that was subsequently shown to contain the epileptogenic focus. Thus, the calculation contains two clinically valuable elements: a prediction of seizure onset and a preliminary localization of the epileptogenic focus. We predict that in the case of seizures that are generalized at onset, the initiation of a seizure will be preceded by a near-simultaneous reduction in cross-channel average mutual information for several electrode pairs.

Suggested Citation

  • Alfonso M. Albano & Christopher J. Cellucci & Richard N. Harner & Paul E. Rapp, 2001. "Optimization of Embedding Parameters for Prediction of Seizure Onset with Mutual Information," Springer Books, in: Alistair I. Mees (ed.), Nonlinear Dynamics and Statistics, chapter 0, pages 435-451, Springer.
  • Handle: RePEc:spr:sprchp:978-1-4612-0177-9_18
    DOI: 10.1007/978-1-4612-0177-9_18
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