Multivariate linear discrimination of seizures

Clin Neurophysiol. 2005 Mar;116(3):545-51. doi: 10.1016/j.clinph.2004.08.023. Epub 2005 Jan 5.


Objective: To discriminate seizures from interictal dynamics based on multivariate synchrony measures, and to identify dynamics of a pre-seizure state.

Methods: A linear discriminator was constructed from two different measures of synchronization: cross-correlation and phase synchronization. We applied this discriminator to a sequence of seizures recorded from the intracranial EEG of a patient monitored over 6 days.

Results: Surprisingly, we found that this bivariate measure of synchronization was not a reliable seizure discriminator for 7 of 9 seizures. Furthermore, the method did not appear to reliably detect a pre-seizure state. An association between anti-convulsant dosage, frequency of clinical seizures, and discriminator performance was noted.

Conclusions: Using a bivariate measure of synchronization failed to reliably differentiate seizures from non-seizure periods in these data, nor did such methods show reliable detection of a synchronous pre-seizure state. The non-stationary variables of decreasing antiepileptic medication (without available serum concentration measurements), and concomitant increasing seizure frequency contributed to the difficulties in validating a seizure prediction tool on such data.

Significance: The finding that these seizures were not a simple reflection of increasing synchronization in the EEG has important implications. The non-stationary characteristics of human post-implantation intracranial EEG is an inherent limitation of pre-resection data sets.

Publication types

  • Comparative Study

MeSH terms

  • Anticonvulsants / therapeutic use
  • Cortical Synchronization
  • Discrimination, Psychological
  • Electroencephalography* / drug effects
  • Humans
  • Monitoring, Physiologic
  • Multivariate Analysis
  • Predictive Value of Tests
  • Reproducibility of Results
  • Seizures / diagnosis*
  • Seizures / drug therapy
  • Seizures / physiopathology*
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted*
  • Statistics as Topic
  • Time Factors


  • Anticonvulsants