4.6 Article

A Feasibility Clinical Trial to Improve Social Attention in Autistic Spectrum Disorder (ASD) Using a Brain Computer Interface

Journal

FRONTIERS IN NEUROSCIENCE
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fnins.2018.00477

Keywords

autism; clinical trial; brain-computer interface; EEG; virtual reality; social attention

Categories

Funding

  1. FTC-Portuguese national funding agency for science, research, and technology [POCI-01-0145-FEDER-016428, POCI 030852, FCT-UID/4539/2013-COMPETE, POCI-01-0145-FEDER-007440, SFRH/BD/78982/2011, SFRH/BD/77044/2011, SFRH/BD/102779/2014, SFRH/BPD/101641/2014]
  2. FTC-Portuguese national funding agency for science, research, and technology [PAC-MEDPERSYST]
  3. FTC-Portuguese national funding agency for science, research, and technology [COMPETE 2020]
  4. FTC-Portuguese national funding agency for science, research, and technology [BIGDATIMAGE]
  5. FTC-Portuguese national funding agency for science, research, and technology [Centro 2020 FEDER] [CENTRO-01-0145-FEDER-000016]
  6. FTC-Portuguese national funding agency for science, research, and technology [COMPETE]
  7. FLAD Life Sciences
  8. BRAINTRAIN Project-Taking imaging into the therapeutic domain: Self-regulation of brain systems for mental disorders [FP7-HEALTH-2013-INNOVATION-1-602186 20]
  9. Fundação para a Ciência e a Tecnologia [SFRH/BD/102779/2014, SFRH/BD/78982/2011, SFRH/BPD/101641/2014, SFRH/BD/77044/2011] Funding Source: FCT

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Deficits in the interpretation of others' intentions from gaze-direction or other social attention cues are well-recognized in ASD. Here we investigated whether an EEG brain computer interface (BCI) can be used to train social cognition skills in ASD patients. We performed a single-arm feasibility clinical trial and enrolled 15 participants (mean age 22y 2m) with high-functioning ASD (mean full-scale 10 103). Participants were submitted to a BCI training paradigm using a virtual reality interface over seven sessions spread over 4 months. The first four sessions occurred weekly, and the remainder monthly. In each session, the subject was asked to identify objects of interest based on the gaze direction of an avatar. Attentional responses were extracted from the EEG P300 component. A final follow-up assessment was performed 6-months after the last session. To analyze responses to joint attention cues participants were assessed pre and post intervention and in the follow-up, using an ecologic Joint-attention task. We used eye-tracking to identify the number of social attention items that a patient could accurately identify from an avatar's action cues (e.g., looking, pointing at). As secondary outcome measures we used the Autism Treatment Evaluation Checklist (ATEC) and the Vineland Adaptive Behavior Scale (NABS). Neuropsychological measures related to mood and depression were also assessed. In sum, we observed a decrease in total ATEC and rated autism symptoms (Sociability; Sensory/Cognitive Awareness; Health/PhysicaVBehavior); an evident improvement in Adapted Behavior Composite and in the DLS subarea from VABS; a decrease in Depression (from POMS) and in mood disturbance/depression (BDI). BCI online performance and tolerance were stable along the intervention. Average P300 amplitude and alpha power were also preserved across sessions. We have demonstrated the feasibility of BCI in this kind of intervention in ASD. Participants engage successfully and consistently in the task. Although the primary outcome (rate of automatic responses to joint attention cues) did not show changes, most secondary neuropsychological outcome measures showed improvement, yielding promise for a future efficacy trial.

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