Separability of motor imagery of the self from interpretation of motor intentions of others at the single trial level: an EEG study

• Autor(a) principal: Andrade, João
• Data de Publicação: 2017
• Outros Autores: Cecílio, José, Simões, Marco, Sales, Francisco, Castelo-Branco, Miguel
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10316/108262; https://doi.org/10.1186/s12984-017-0276-4
• topic: EEG; Motor imagery; Classification; Single trial; Adult; Algorithms; Autistic Disorder; Electrocorticography; Female; Healthy Volunteers; Humans; Imagination; Male; Movement; Parietal Lobe; Signal Processing, Computer-Assisted; Support Vector Machine; Temporal Lobe; Virtual Reality; Young Adult; Ego; Electroencephalography; Intention

Background: 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.