Real-time support vector classification and feedback of multiple emotional brain states

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dc.contributor.authorSitaram, Ranganatha
dc.contributor.authorLee, Sangkyun
dc.contributor.authorRuiz, Sergio
dc.contributor.authorRana, Mohit
dc.contributor.authorVeit, Ralf
dc.contributor.authorBirbaumer, Niels
dc.date.accessioned2025-01-21T00:02:10Z
dc.date.available2025-01-21T00:02:10Z
dc.date.issued2011
dc.description.abstractAn important question that confronts current research in affective neuroscience as well as in the treatment of emotional disorders is whether it is possible to determine the emotional state of a person based on the measurement of brain activity alone. Here, we first show that an online support vector machine (SVM) can be built to recognize two discrete emotional states, such as happiness and disgust from fMRI signals, in healthy individuals instructed to recall emotionally salient episodes from their lives. We report the first application of real-time head motion correction, spatial smoothing and feature selection based on a new method called Effect mapping. The classifier also showed robust prediction rates in decoding three discrete emotional states (happiness, disgust and sadness) in an extended group of participants. Subjective reports ascertained that participants performed emotion imagery and that the online classifier decoded emotions and not arbitrary states of the brain. Offline whole brain classification as well as region-of-interest classification in 24 brain areas previously implicated in emotion processing revealed that the frontal cortex was critically involved in emotion induction by imagery. We also demonstrate an fMRI-BCI based on real-time classification of BOLD signals from multiple brain regions, for each repetition time (TR) of scanning, providing visual feedback of emotional states to the participant for potential applications in the clinical treatment of dysfunctional affect. (C) 2010 Elsevier Inc. All rights reserved.
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.neuroimage.2010.08.007
dc.identifier.eissn1095-9572
dc.identifier.issn1053-8119
dc.identifier.urihttps://doi.org/10.1016/j.neuroimage.2010.08.007
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/95412
dc.identifier.wosidWOS:000290081900034
dc.issue.numero2
dc.language.isoen
dc.pagina.final765
dc.pagina.inicio753
dc.revistaNeuroimage
dc.rightsacceso restringido
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleReal-time support vector classification and feedback of multiple emotional brain states
dc.typeartículo
dc.volumen56
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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