Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/108262
DC FieldValueLanguage
dc.contributor.authorAndrade, João-
dc.contributor.authorCecílio, José-
dc.contributor.authorSimões, Marco-
dc.contributor.authorSales, Francisco-
dc.contributor.authorCastelo-Branco, Miguel-
dc.date.accessioned2023-08-21T11:06:03Z-
dc.date.available2023-08-21T11:06:03Z-
dc.date.issued2017-06-26-
dc.identifier.issn1743-0003pt
dc.identifier.urihttps://hdl.handle.net/10316/108262-
dc.description.abstractBackground: We aimed to investigate the separability of the neural correlates of 2 types of motor imagery, self and third person (actions owned by the participant himself vs. another individual). If possible this would allow for the development of BCI interfaces to train disorders of action and intention understanding beyond simple imitation, such as autism. Methods: We used EEG recordings from 20 healthy participants, as well as electrocorticography (ECoG) in one, based on a virtual reality setup. To test feasibility of discrimination between each type of imagery at the single trial level, time-frequency and source analysis were performed and further assessed by data-driven statistical classification using Support Vector Machines. Results: The main observed differences between self-other imagery conditions in topographic maps were found in Frontal and Parieto-Occipital regions, in agreement with the presence of 2 independent non μ related contributions in the low alpha frequency range. ECOG corroborated such separability. Source analysis also showed differences near the temporo-parietal junction and single-trial average classification accuracy between both types of motor imagery was 67 ± 1%, and raised above 70% when 3 trials were used. The single-trial classification accuracy was significantly above chance level for all the participants of this study (p < 0.02). Conclusions: The observed pattern of results show that Self and Third Person MI use distinct electrophysiological mechanisms detectable at the scalp (and ECOG) at the single trial level, with separable levels of involvement of the mirror neuron system in different regions. These observations provide a promising step to develop new BCI training/rehabilitation paradigms for patients with neurodevelopmental disorders of action understanding beyond simple imitation, such as autism, who would benefit from training and anticipation of the perceived intention of others as opposed to own intentions in social contexts.pt
dc.language.isoengpt
dc.publisherSpringer Naturept
dc.relationThis work was supported by the European project BRAINTRAIN - FP7- HEALTH-2013-INNOVATION-1–602,186, Portuguese Fundação para a Ciência e a Tecnologia (FCT), Grant SFRH/BPD/96749/2013, Grant SFRH/BD/77044/ 2011, POCI-01-0145-FEDER-016428 (PAC MEDPSERSYST), FCT UID/NEU/04539/ 2013–2020/COMPETE/POCI-01-0145-FEDER-007440, BIGDATIMAGE – “From computational modelling and clinical research to the development of neuroimaging big data platforms for discovery of novel biomarker” (CENTRO-01-0145-FEDER-000016).pt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectEEGpt
dc.subjectMotor imagerypt
dc.subjectClassificationpt
dc.subjectSingle trialpt
dc.subject.meshAdultpt
dc.subject.meshAlgorithmspt
dc.subject.meshAutistic Disorderpt
dc.subject.meshElectrocorticographypt
dc.subject.meshFemalept
dc.subject.meshHealthy Volunteerspt
dc.subject.meshHumanspt
dc.subject.meshImaginationpt
dc.subject.meshMalept
dc.subject.meshMovementpt
dc.subject.meshParietal Lobept
dc.subject.meshSignal Processing, Computer-Assistedpt
dc.subject.meshSupport Vector Machinept
dc.subject.meshTemporal Lobept
dc.subject.meshVirtual Realitypt
dc.subject.meshYoung Adultpt
dc.subject.meshEgopt
dc.subject.meshElectroencephalographypt
dc.subject.meshIntentionpt
dc.titleSeparability of motor imagery of the self from interpretation of motor intentions of others at the single trial level: an EEG studypt
dc.typearticle-
degois.publication.firstPage63pt
degois.publication.issue1pt
degois.publication.titleJournal of NeuroEngineering and Rehabilitationpt
dc.peerreviewedyespt
dc.identifier.doi10.1186/s12984-017-0276-4pt
degois.publication.volume14pt
dc.date.embargo2017-06-26*
uc.date.periodoEmbargo0pt
item.grantfulltextopen-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextCom Texto completo-
crisitem.author.researchunitCISUC - Centre for Informatics and Systems of the University of Coimbra-
crisitem.author.researchunitCIBIT - Coimbra Institute for Biomedical Imaging and Translational Research-
crisitem.author.parentresearchunitFaculty of Sciences and Technology-
crisitem.author.orcid0000-0001-6078-6912-
crisitem.author.orcid0000-0002-5351-5580-
crisitem.author.orcid0000-0003-4364-6373-
Appears in Collections:I&D CISUC - Artigos em Revistas Internacionais
I&D ICNAS - Artigos em Revistas Internacionais
I&D CIBIT - Artigos em Revistas Internacionais
I&D IBILI - Artigos em Revistas Internacionais
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