Spatio-temporal patient-individual assessment of synchronization changes for epileptic seizure prediction

Matthias Winterhalder, Bjoern Schelter, Thomas Maiwald, Armin Brandt, Ariane Schad, Andreas Schulze-Bonhage, Jens Timmer

Research output: Contribution to journalArticle

59 Citations (Scopus)

Abstract

Objective: Abnormal synchronization of neurons plays a central role for the generation of epileptic seizures. Therefore, multivariate time series analysis techniques investigating relationships between the dynamics of different neural populations may offer advantages in predicting epileptic seizures.

Methods: We applied a phase and a lag synchronization measure to a selected subset of multicontact intracranial EEG recordings and assessed changes in synchronization with respect to seizure prediction.

Results: Patient individual results, group results, spatial aspects using focal and extra-focal electrode contacts as well as two evaluation schemes analyzing decreases and increases in synchronization were examined. Averaged sensitivity values of 60% are observed for a false prediction rate of 0.15 false predictions per hour, a seizure occurrence period of half an hour, and a prediction horizon of 10 min. For approximately half of all 21 patients, a statistically significant prediction performance is observed for at least one synchronization measure and evaluation scheme.

Conclusions: The results indicate that synchronization changes in the EEG dynamics preceding seizures can be used for seizure prediction. Nevertheless, the underlying pathogenic mechanisms differ and both decreases and increases in synchronization may precede epileptic seizures depending on the structures investigated.

Significance: The prediction method, optimized values of intervention times, as well as preferred brain structures for the EEG recordings have to be determined for each patient individually offering the chance of a better patient-individual prediction performance. (c) 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)2399-2413
Number of pages15
JournalClinical Neurophysiology
Volume117
Issue number11
Early online date26 Sep 2006
DOIs
Publication statusPublished - Nov 2006

Keywords

  • seizure prediction
  • seizure anticipation
  • phase synchronization
  • false predictions
  • prediction horizon

Cite this

Spatio-temporal patient-individual assessment of synchronization changes for epileptic seizure prediction. / Winterhalder, Matthias; Schelter, Bjoern; Maiwald, Thomas; Brandt, Armin; Schad, Ariane; Schulze-Bonhage, Andreas; Timmer, Jens.

In: Clinical Neurophysiology, Vol. 117, No. 11, 11.2006, p. 2399-2413.

Research output: Contribution to journalArticle

Winterhalder, M, Schelter, B, Maiwald, T, Brandt, A, Schad, A, Schulze-Bonhage, A & Timmer, J 2006, 'Spatio-temporal patient-individual assessment of synchronization changes for epileptic seizure prediction' Clinical Neurophysiology, vol. 117, no. 11, pp. 2399-2413. https://doi.org/10.1016/j.clinph.2006.07.312
Winterhalder, Matthias ; Schelter, Bjoern ; Maiwald, Thomas ; Brandt, Armin ; Schad, Ariane ; Schulze-Bonhage, Andreas ; Timmer, Jens. / Spatio-temporal patient-individual assessment of synchronization changes for epileptic seizure prediction. In: Clinical Neurophysiology. 2006 ; Vol. 117, No. 11. pp. 2399-2413.
@article{c159138be4014002bfe62f55f363e70a,
title = "Spatio-temporal patient-individual assessment of synchronization changes for epileptic seizure prediction",
abstract = "Objective: Abnormal synchronization of neurons plays a central role for the generation of epileptic seizures. Therefore, multivariate time series analysis techniques investigating relationships between the dynamics of different neural populations may offer advantages in predicting epileptic seizures.Methods: We applied a phase and a lag synchronization measure to a selected subset of multicontact intracranial EEG recordings and assessed changes in synchronization with respect to seizure prediction.Results: Patient individual results, group results, spatial aspects using focal and extra-focal electrode contacts as well as two evaluation schemes analyzing decreases and increases in synchronization were examined. Averaged sensitivity values of 60{\%} are observed for a false prediction rate of 0.15 false predictions per hour, a seizure occurrence period of half an hour, and a prediction horizon of 10 min. For approximately half of all 21 patients, a statistically significant prediction performance is observed for at least one synchronization measure and evaluation scheme.Conclusions: The results indicate that synchronization changes in the EEG dynamics preceding seizures can be used for seizure prediction. Nevertheless, the underlying pathogenic mechanisms differ and both decreases and increases in synchronization may precede epileptic seizures depending on the structures investigated.Significance: The prediction method, optimized values of intervention times, as well as preferred brain structures for the EEG recordings have to be determined for each patient individually offering the chance of a better patient-individual prediction performance. (c) 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.",
keywords = "seizure prediction, seizure anticipation, phase synchronization, false predictions, prediction horizon",
author = "Matthias Winterhalder and Bjoern Schelter and Thomas Maiwald and Armin Brandt and Ariane Schad and Andreas Schulze-Bonhage and Jens Timmer",
year = "2006",
month = "11",
doi = "10.1016/j.clinph.2006.07.312",
language = "English",
volume = "117",
pages = "2399--2413",
journal = "Clinical Neurophysiology",
issn = "1388-2457",
publisher = "Elsevier Ireland Ltd",
number = "11",

}

TY - JOUR

T1 - Spatio-temporal patient-individual assessment of synchronization changes for epileptic seizure prediction

AU - Winterhalder, Matthias

AU - Schelter, Bjoern

AU - Maiwald, Thomas

AU - Brandt, Armin

AU - Schad, Ariane

AU - Schulze-Bonhage, Andreas

AU - Timmer, Jens

PY - 2006/11

Y1 - 2006/11

N2 - Objective: Abnormal synchronization of neurons plays a central role for the generation of epileptic seizures. Therefore, multivariate time series analysis techniques investigating relationships between the dynamics of different neural populations may offer advantages in predicting epileptic seizures.Methods: We applied a phase and a lag synchronization measure to a selected subset of multicontact intracranial EEG recordings and assessed changes in synchronization with respect to seizure prediction.Results: Patient individual results, group results, spatial aspects using focal and extra-focal electrode contacts as well as two evaluation schemes analyzing decreases and increases in synchronization were examined. Averaged sensitivity values of 60% are observed for a false prediction rate of 0.15 false predictions per hour, a seizure occurrence period of half an hour, and a prediction horizon of 10 min. For approximately half of all 21 patients, a statistically significant prediction performance is observed for at least one synchronization measure and evaluation scheme.Conclusions: The results indicate that synchronization changes in the EEG dynamics preceding seizures can be used for seizure prediction. Nevertheless, the underlying pathogenic mechanisms differ and both decreases and increases in synchronization may precede epileptic seizures depending on the structures investigated.Significance: The prediction method, optimized values of intervention times, as well as preferred brain structures for the EEG recordings have to be determined for each patient individually offering the chance of a better patient-individual prediction performance. (c) 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

AB - Objective: Abnormal synchronization of neurons plays a central role for the generation of epileptic seizures. Therefore, multivariate time series analysis techniques investigating relationships between the dynamics of different neural populations may offer advantages in predicting epileptic seizures.Methods: We applied a phase and a lag synchronization measure to a selected subset of multicontact intracranial EEG recordings and assessed changes in synchronization with respect to seizure prediction.Results: Patient individual results, group results, spatial aspects using focal and extra-focal electrode contacts as well as two evaluation schemes analyzing decreases and increases in synchronization were examined. Averaged sensitivity values of 60% are observed for a false prediction rate of 0.15 false predictions per hour, a seizure occurrence period of half an hour, and a prediction horizon of 10 min. For approximately half of all 21 patients, a statistically significant prediction performance is observed for at least one synchronization measure and evaluation scheme.Conclusions: The results indicate that synchronization changes in the EEG dynamics preceding seizures can be used for seizure prediction. Nevertheless, the underlying pathogenic mechanisms differ and both decreases and increases in synchronization may precede epileptic seizures depending on the structures investigated.Significance: The prediction method, optimized values of intervention times, as well as preferred brain structures for the EEG recordings have to be determined for each patient individually offering the chance of a better patient-individual prediction performance. (c) 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

KW - seizure prediction

KW - seizure anticipation

KW - phase synchronization

KW - false predictions

KW - prediction horizon

U2 - 10.1016/j.clinph.2006.07.312

DO - 10.1016/j.clinph.2006.07.312

M3 - Article

VL - 117

SP - 2399

EP - 2413

JO - Clinical Neurophysiology

JF - Clinical Neurophysiology

SN - 1388-2457

IS - 11

ER -