BCI Training for Social Cognition and Error Monitoring in ASD

Improving Social Cognition and Error Monitoring in Autism Spectrum Disorder Through a Brain Computer Interface Based on Reinforcement Learning

Social cognition seems to develop atypically in autism, particularly in processes such as faces perception, joint attention and social information processing. In this sense, and using an Emotional Paradigm of Facial Expressions (EFP) with a Brain-Computer Interface (BCI) based on Electroencephalography (EEG), the investigators intend to evaluate its effectiveness as a medical device in Autism Spectrum Disorder (ASD), namely: improving 1) social skills and 2) reducing generalized anxiety, 3) improve error monitoring, and consequently verify 4) an increase in motivation. To this end, the investigators will test a gamified intervention (EFP), using personalized feedback in real time. In this gamified interface, there is an artificial agent that learns rules through Reinforcement Learning using the evoked potentials from the participant as they observe the agent's right or wrong actions. The hypothesis is that this approach allows, during the gamified task (EFP), not only the agent/interface to learn, but also the participant through operant conditioning and implicit scrutiny of errors, which makes it particularly interesting for disorders in which error monitoring processes are compromised, as in ASD.

Inclusion Criteria:

• Participant is able and willing to give written informed consent/assent
• Previous diagnosis of Autism Spectrum Disorder by a qualified clinician according to gold-standard instruments
• Aged between 16 and 55 years old
• Normal or corrected-to-normal vision

Exclusion Criteria:

• Global Intelligence Quotient <70
• Dermatological diseases of the scalp
• Concurrent neurofeedback therapy
• Concomitant medication without a stable dosage for at least 4 weeks
• History of seizures and/or epilepsy