With the aim of developing a brain-computer interface for the communication of basic mental states, a classical conditioning paradigm with affective stimuli was used, assessing the possibility to discriminate between affirmative and negative thinking in an fMRI-BCI setting. 6 Alzheimer patients and 7 healthy control subjects participated to the study. Congruent and incongruent word-pairs were respectively associated to pleasant (baby laughter) and unpleasant (scream) affective stimuli. A Support Vector Machine classifier focusing on insula, amygdala and anterior cingulate cortex was used to discriminate between the activations relative to congruent and incongruent word-pairs (eliciting respectively affirmative and negative thinking), following the conditioning process. Classification accuracy was on average 71% for Alzheimer patients, reaching 85%, and on average 69% for control subjects, reaching 83%. This study shows that it is possible to extract information on individuals' mental states by exploiting affective responses, overcoming the typical obstacles of traditional BCIs, which generally require time-consuming trainings and intact cognition. © 2013 IEEE.
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|Titolo:||Development of a binary fMRI-BCI for alzheimer patients: A semantic conditioning paradigm using affective unconditioned stimuli|
|Data di pubblicazione:||2013|
|Appartiene alla tipologia:||04b Atto di convegno in volume|