title: Classification of fMRI patterns--a study of the language network segregation in pediatric localization related epilepsy.
abstract: This article describes a pattern classification algorithm for pediatric epilepsy using fMRI language-related activation maps. 122 fMRI datasets from a control group (64) and localization related epilepsy patients (58) provided by five children's hospitals were used. Each subject performed an auditory description decision task. Using the artificial data as training data, incremental Principal Component Analysis was used in order to generate the feature space while overcoming memory requirements of large datasets. The nearest-neighbor classifier (NNC) and the distance-based fuzzy classifier (DFC) were used to perform group separation into left dominant, right dominant, bilateral, and others. The results show no effect of age, age at seizure onset, seizure duration, or seizure etiology on group separation. Two sets of parameters were significant for group separation, the patient vs. control populations and handedness. Of the 122 real datasets, 90 subjects gave the same classification results across all the methods (three raters, LI, bootstrap LI, NNC, and DFC). For the remaining datasets, 18 cases for the IPCA-NNC and 21 cases for the IPCA-DFC agreed with the majority of the five classification results (three visual ratings and two LI results). Kappa values vary from 0.59 to 0.73 for NNC and 0.61 to 0.75 for DFC, which indicate good agreement between NNC or DFC with traditional methods. The proposed method as designed can serve as an alternative method to corroborate existing LI and visual rating classification methods and to resolve some of the cases near the boundaries in between categories.
authors: Department of Electrical and Computer Engineering, Florida International University, Miami, Florida.
authors: Jin
authors: J
authors: Wang
authors: Xiaozhen
authors: X
authors: You
authors: Wensong
authors: W
authors: Wu
authors: Magno R
authors: MR
authors: Guillen
authors: Mercedes
authors: M
authors: Cabrerizo
authors: Joseph
authors: J
authors: Sullivan
authors: Elizabeth
authors: E
authors: Donner
authors: Bruce
authors: B
authors: Bjornson
authors: William D
authors: WD
authors: Gaillard
authors: Malek
authors: M
authors: Adjouadi
mesh_terms: D000293:Adolescent; D000367:Age Factors; D017668:Age of Onset; D001921:Brain / Q000503:physiopathology*; D001931:Brain Mapping / Q000379:methods*; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D004828:Epilepsies, Partial / Q000209:etiology / Q000503:physiopathology*; D005260:Female; D007839:Functional Laterality; D017143:Fuzzy Logic; D006801:Humans; D007223:Infant; D007802:Language; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009434:Neural Pathways / Q000503:physiopathology; D025341:Principal Component Analysis; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D055815:Young Adult
keywords: PCA; distance-based fuzzy classifier; eigensystem; eigenvectors; fMRI; language networks; lateralization index; nearest neighbor classifier; visual rating system