Discrimination between migraine patients and normal subjects based on steady state visual evoked potentials: discriminant analysis and artificial neural network classifiers.
Fifty-one migraine patients and 19 control subjects were examined by steady state visual evoked potentials (SSVEPs) procedure. The aim of this study was to develop a discriminant analysis and an artificial neural network (NN) classifier in order to discriminate between migraneurs during attack-free periods and normal subjects. Discriminant analysis correctly classified 72.5% of migraine patients with a false positive rate of 36.8%. The NN method had a sensitivity of 100% with a false positive rate of 15%. The results of this study confirm SSVEP pattern as a marker of migraine and demonstrate that NNs could be a useful method in the statistical analysis of topographic EEG data.
de Tommaso
M
M
2nd Neurological Clinic, University of Bari, Italy.
Sciruicchio
V
V
Bellotti
R
R
Castellano
M
M
Tota
P
P
Guido
M
M
Sasanelli
G
G
Puca
F
F
D000328:Adult; D016002:Discriminant Analysis; D005074:Evoked Potentials, Visual / Q000502:physiology*; D005260:Female; D006706:Homeostasis / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D008881:Migraine Disorders / Q000150:complications / Q000175:diagnosis*; D008959:Models, Neurological; D012372:ROC Curve; D012016:Reference Values; D012678:Sensation Disorders / Q000209:etiology