Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/4766
Title: Cubic least-squares minimum-distance classifier for discriminating one-month abstinent heroin addicts from healthy controls using the P600 component of ERP signals
Authors: Καλατζής, Ιωάννης
Πήλιουρας, Νικόλαος
Βεντούρας, Ερρίκος Μ.
Παπαγεωργίου, Χαράλαμπος
Λιάππας, Ιωάννης Α.
Contributors: Νικολάου, Χρυσούλα
Ραμπαβίλας, Ανδρέας Ν.
Κάβουρας, Διονύσης Α.
Item type: Conference publication
Conference Item Type: Full Paper
Keywords: Heroin addicts;Pattern recognition systems--Congresses;Ηρωινομανής;Αναγνώριση προτύπων
Subjects: Medicine
Pharmacognosy
Ιατρική
Φαρμακογνωσία
Issue Date: 26-Jan-2015
2004
Abstract: The aim of this study was to investigate whether brain information storage and processing in one-month abstinent heroin addicts differ from healthy controls, as reflected by the P600 component of Event-related potential (ERP) signals elicited during a working memory test, as well to search deeper into the P600 signals by extracting new features and, by employing powerful classification procedures, to develop a pattern recognition system for discriminating drug users from controls. Sixteen one-month abstinent heroin addicts and twenty normal controls were examined. All subjects were evaluated by a computerized version of the digit span subtest of the Wechsler Adult Intelligence Scale. EEG activity was recorded from 15 scalp electrodes (leads). From the P600 component of each signal nineteen waveform-features were calculated. The cubic least-square minimum-distance classifier was developed and it was fed with features from all leads. The system was evaluated by means of the exhaustive search and leave-one-out methods. Highest single-lead precision (86.1%) was found at the P3, C5 and F3 leads at left. When leads were grouped into compartments, highest accuracies were achieved at the temporo-central region (88.9%). These findings may be indicative that one-month abstinent heroin addicts present deficits in working memory processes, as reflected by the P600 component.
Description: Proceedings of the 1st International Conference “From Scientific Computing to Computational Engineering” (1ST IC-SCCE) (CD-ROM).
Language: English
Citation: Kalatzis, I., Piliouras, N., Ventouras, E., Papageorgiou, C., Liappas, I., et al. (2004). Cubic least-squares minimum-distance classifier for discriminating one-month abstinent heroin addicts from healthy controls using the P600 component of ERP signals, In the 1st International Conference “From Scientific Computing to Computational Engineering”. University of Patras: Athens, 8th-10th September 2004.
Conference: The aim of this study was to investigate whether brain information storage and processing in one-month abstinent heroin addicts differ from healthy controls, as reflected by the P600 component of Event-related potential (ERP) signals elicited during a working memory test, as well to search deeper into the P600 signals by extracting new features and, by employing powerful classification procedures, to develop a pattern recognition system for discriminating drug users from controls. Sixteen one-month abstinent heroin addicts and twenty normal controls were examined. All subjects were evaluated by a computerized version of the digit span subtest of the Wechsler Adult Intelligence Scale. EEG activity was recorded from 15 scalp electrodes (leads). From the P600 component of each signal nineteen waveform-features were calculated. The cubic least-square minimum-distance classifier was developed and it was fed with features from all leads. The system was evaluated by means of the exhaustive search and leave-one-out methods. Highest single-lead precision (86.1%) was found at the P3, C5 and F3 leads at left. When leads were grouped into compartments, highest accuracies were achieved at the temporo-central region (88.9%). These findings may be indicative that one-month abstinent heroin addicts present deficits in working memory processes, as reflected by the P600 component.
Access scheme: Embargo
License: Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες
URI: http://hdl.handle.net/11400/4766
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