title: Identification of diagnostic evoked response potential segments in Alzheimer's disease.
abstract: Evoked response potentials (ERPs) to brief flashes of light were analyzed for constituent features that could be used to distinguish individuals with Alzheimer's disease (AD, n = 15) from matched control subjects (n = 17). Statistical k nearest-neighbor methods distinguished AD from control with a maximum sensitivity of 29% and false alarm rate of 12%. The comparable sensitivity/false-alarm values for a statistical projection pursuit method and an extended projection pursuit method, which selectively identify discriminative features for classification, were 75%/18% and 100%/6%, respectively. The results demonstrate that combinations of selected ERP time segments across different electrodes contain signal features that discriminate AD from control subjects with high sensitivity and specificity.
mesh_terms: D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000503:physiopathology; D001931:Brain Mapping; D016000:Cluster Analysis; D004569:Electroencephalography / Q000379:methods*; D005074:Evoked Potentials, Visual / Q000502:physiology; D005188:False Negative Reactions; D005189:False Positive Reactions; D006801:Humans; D010775:Photic Stimulation; D011237:Predictive Value of Tests; D012372:ROC Curve; D011930:Reaction Time; D012016:Reference Values; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted