Development of a Binary fMRI-BCI for Alzheimer Patients: A semantic conditioning paradigm using affective unconditioned stimuli.
(2013) IEEE Transactions on Affective Computing — Vol. 1, p. 838-842 (2012)
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- Abstract
- 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.
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Liberati, G., Dalboni da Rocha, J., Veit, R., Kim, S., Birbaumer, N., Von Arnim, C., Jenner, A., Lulé, D., Ludolph, A., Raffone, A., Olivetti Belardinelli, M., Sitaram, R., & et al. (2013). Development of a Binary fMRI-BCI for Alzheimer Patients: A semantic conditioning paradigm using affective unconditioned stimuli. IEEE Transactions on Affective Computing, 1, 838-842. https://doi.org/10.1109/ACII.2013.157 (Original work published 2012)