Classification of event-related potentials associated with response errors in actors and observers based on autoregressive modeling

dc.contributor.author	Βάσιος, Χρήστος	el
dc.contributor.author	Βεντούρας, Ερρίκος Μ.	el
dc.contributor.author	Ματσόπουλος, Γεώργιος Κ.	el
dc.contributor.author	Καρανάσιου, Ειρήνη Σ.	el
dc.contributor.author	Ασβεστάς, Παντελής Α.	el
dc.date.accessioned	2015-02-06T09:09:22Z
dc.date.available	2015-02-06T09:09:22Z
dc.date.issued	2015-02-06
dc.identifier.uri	http://hdl.handle.net/11400/5725
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://benthamopen.com/	en
dc.subject	Electrical activity
dc.subject	Brain
dc.subject	Ηλεκτρική δραστηριότητα
dc.subject	Εγκέφαλος
dc.title	Classification of event-related potentials associated with response errors in actors and observers based on autoregressive modeling	en
heal.type	journalArticle
heal.generalDescription	Open access journal	en
heal.classification	Medicine
heal.classification	Biomedical engineering
heal.classification	Ιατρική
heal.classification	Βιοϊατρική τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85014237
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Βιοϊατρική τεχνολογία
heal.contributorName	Ουζούνογλου, Νικόλαος Κ.	el
heal.contributorName	Van Schie, Hein T.	en
heal.contributorName	de Bruijn, Ellen R.A.	en
heal.identifier.secondary	doi: 10.2174/1874431100903010032
heal.language	en
heal.access	free
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2009
heal.bibliographicCitation	Vasios, C., Ventouras, E., Matsopoulos, G., Karanasiou, I., Asvestas, P., et al. (2009). Classification of event-related potentials associated with response errors in actors and observers based on autoregressive modeling. The Open Medical Informatics Journal. vol. 3. pp. 32-43. Bentham Open. Available from: http://www.ncbi.nlm.nih.gov [Accessed 15/05/2009]	en
heal.abstract	Event-Related Potentials (ERPs) provide non-invasive measurements of the electrical activity on the scalp related to the processing of stimuli and preparation of responses by the brain. In this paper an ERP-signal classification method is proposed for discriminating between ERPs of correct and incorrect responses of actors and of observers seeing an actor making such responses. The classification method targeted signals containing error-related negativity (ERN) and error positivity (Pe) components, which are typically associated with error processing in the human brain. Feature extraction consisted of Multivariate Autoregressive modeling combined with the Simulated Annealing technique. The resulting information was subsequently classified by means of an Artificial Neural Network (ANN) using back-propagation algorithm under the “leave-one-out cross-validation” scenario and the Fuzzy C-Means (FCM) algorithm. The ANN consisted of a multi-layer perceptron (MLP). The approach yielded classification rates of up to 85%, both for the actors’ correct and incorrect responses and the corresponding ERPs of the observers. The electrodes needed for such classifications were situated mainly at central and frontal areas. Results provide indications that the classification of the ERN is achievable. Furthermore, the availability of the Pe signals, in addition to the ERN, improves the classification, and this is more pronounced for observers’ signals. The proposed ERP-signal classification method provides a promising tool to study error detection and observational-learning mechanisms in performance monitoring and joint-action research, in both healthy and patient populations.	en
heal.publisher	Bentham Open	en
heal.journalName	The Open Medical Informatics Journal	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true