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

Abstract

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 IQ 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 (VABS). 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/Physical/Behavior); 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.(clinical-trial ID: NCT02445625—clinicaltrials.gov).

Classification of P300 Component Using a Riemannian Ensemble Approach

“…The data was provided as part of the 2019 IFMBE scientific challenge competition organized by the 15th Mediterranean Conference on Medical and Biological Engineering and Computing (Medicon 2019). The dataset represents the 8-channels EEG recordings of a feasibility clinical trial to train youngsters with Autism Spectrum Disorder (ASD) to follow the social cues [1,2]. It consists of 7 sessions divided into training and test subsets each.…”

BCIAUT-P300: A Multi-Session and Multi-Subject Benchmark Dataset on Autism for P300-Based Brain-Computer-Interfaces

“…Amaral et al (2017) developed an interventional BCI based on P300 signals that uses a virtual environment with a virtual human character and several objects of interest to train the ability of participants to follow the cues of the virtual character to the objects. That system was validated in an interventional pilot study (Amaral et al, 2018) where 15 ASD individuals underwent 7 training sessions with this system. The database resulting from that interventional study supported the 2019 IFMBE scientific challenge and is now made public to the scientific community at https:// www.kaggle.com/disbeat/bciaut-p300 (doi: 10.34740/kaggle/dsv/ 1375326).…”

“…In the scope of the XV Mediterranean Conference in 2019, the International Federation of Medical and Biological Engineering (IFMBE) launched a scientific competition based on a multi-session dataset of P300-based BCI intervention for young adults with autism spectrum disorder (ASD) ( Amaral et al, 2018 ). This intervention was aimed at the rehabilitation of joint-attention, a core developmental skill that is altered in ASD and impacts other skills like language development ( Adamson et al, 2019 ).…”

Comparative analysis of two-group supervised classification algorithms in the study of P300-based brain-computer interface

“…In [21] vibro-tactile P300 was tested on a group of disabled and healthy people. In [22] authors applied P300 paradigm in BCI to improve Social Attention in Autistic Spectrum Disorder (ASD). The BCI based on P300 may be implemented in EmotivEpoc headset, which is promising and cheap device [23].…”