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A Randomized Trial Utilizing EEG Brain Computer Interface to Improve Facial Emotion Recognition in Autistic Adults.

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Title: A Randomized Trial Utilizing EEG Brain Computer Interface to Improve Facial Emotion Recognition in Autistic Adults.
Authors: Brewe, Alexis M., Antezana, Ligia, Carlton, Corinne N., Gracanin, Denis, Richey, John A., Kim, Inyoung, White, Susan W.
Source: Journal of Autism & Developmental Disorders. Sep2025, Vol. 55 Issue 9, p3217-3230. 14p.
Subjects: Treatment of autism, Patient compliance, Research funding, Electroencephalography, Statistical sampling, Biofeedback training, Randomized controlled trials, Virtual reality, Patient satisfaction, Asperger's syndrome, Augmented reality, Face perception, User interfaces
Abstract: Purpose: Many individuals with autism spectrum disorder (ASD) experience challenges with facial emotion recognition (FER), which may exacerbate social difficulties in ASD. Few studies have examined whether FER can be experimentally manipulated and improved for autistic people. This study utilized a randomized controlled trial design to examine acceptability and preliminary clinical impact of a novel mixed reality-based neurofeedback program, FER Assistant, using EEG brain computer interface (BCI)-assisted technology to improve FER for autistic adolescents and adults. Methods: Twenty-seven autistic male participants (M age: 21.12 years; M IQ: 105.78; 85% white) were randomized to the active condition to receive FER Assistant (n = 17) or waitlist control (n = 10). FER Assistant participants received ten sessions utilizing BCI-assisted neurofeedback training in FER. All participants, regardless of randomization, completed a computerized FER task at baseline and endpoint. Results: Results partially indicated that FER Assistant was acceptable to participants. Regression analyses demonstrated that participation in FER Assistant led to group differences in FER at endpoint, compared to a waitlist control. However, analyses examining reliable change in FER indicated no reliable improvement or decline for FER Assistant participants, whereas two waitlist participants demonstrated reliable decline. Conclusion: Given the preliminary nature of this work, results collectively suggest that FER Assistant may be an acceptable intervention. Results also suggest that FER may be a potential mechanism that is amenable to intervention for autistic individuals, although additional trials using larger sample sizes are warranted. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Autism & Developmental Disorders is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: A Randomized Trial Utilizing EEG Brain Computer Interface to Improve Facial Emotion Recognition in Autistic Adults.
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  Data: <searchLink fieldCode="AR" term="%22Brewe%2C+Alexis+M%2E%22">Brewe, Alexis M.</searchLink><br /><searchLink fieldCode="AR" term="%22Antezana%2C+Ligia%22">Antezana, Ligia</searchLink><br /><searchLink fieldCode="AR" term="%22Carlton%2C+Corinne+N%2E%22">Carlton, Corinne N.</searchLink><br /><searchLink fieldCode="AR" term="%22Gracanin%2C+Denis%22">Gracanin, Denis</searchLink><br /><searchLink fieldCode="AR" term="%22Richey%2C+John+A%2E%22">Richey, John A.</searchLink><br /><searchLink fieldCode="AR" term="%22Kim%2C+Inyoung%22">Kim, Inyoung</searchLink><br /><searchLink fieldCode="AR" term="%22White%2C+Susan+W%2E%22">White, Susan W.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Autism+%26+Developmental+Disorders%22">Journal of Autism & Developmental Disorders</searchLink>. Sep2025, Vol. 55 Issue 9, p3217-3230. 14p.
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  Data: <searchLink fieldCode="DE" term="%22Treatment+of+autism%22">Treatment of autism</searchLink><br /><searchLink fieldCode="DE" term="%22Patient+compliance%22">Patient compliance</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Electroencephalography%22">Electroencephalography</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+sampling%22">Statistical sampling</searchLink><br /><searchLink fieldCode="DE" term="%22Biofeedback+training%22">Biofeedback training</searchLink><br /><searchLink fieldCode="DE" term="%22Randomized+controlled+trials%22">Randomized controlled trials</searchLink><br /><searchLink fieldCode="DE" term="%22Virtual+reality%22">Virtual reality</searchLink><br /><searchLink fieldCode="DE" term="%22Patient+satisfaction%22">Patient satisfaction</searchLink><br /><searchLink fieldCode="DE" term="%22Asperger's+syndrome%22">Asperger's syndrome</searchLink><br /><searchLink fieldCode="DE" term="%22Augmented+reality%22">Augmented reality</searchLink><br /><searchLink fieldCode="DE" term="%22Face+perception%22">Face perception</searchLink><br /><searchLink fieldCode="DE" term="%22User+interfaces%22">User interfaces</searchLink>
– Name: Abstract
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  Data: Purpose: Many individuals with autism spectrum disorder (ASD) experience challenges with facial emotion recognition (FER), which may exacerbate social difficulties in ASD. Few studies have examined whether FER can be experimentally manipulated and improved for autistic people. This study utilized a randomized controlled trial design to examine acceptability and preliminary clinical impact of a novel mixed reality-based neurofeedback program, FER Assistant, using EEG brain computer interface (BCI)-assisted technology to improve FER for autistic adolescents and adults. Methods: Twenty-seven autistic male participants (M age: 21.12 years; M IQ: 105.78; 85% white) were randomized to the active condition to receive FER Assistant (n = 17) or waitlist control (n = 10). FER Assistant participants received ten sessions utilizing BCI-assisted neurofeedback training in FER. All participants, regardless of randomization, completed a computerized FER task at baseline and endpoint. Results: Results partially indicated that FER Assistant was acceptable to participants. Regression analyses demonstrated that participation in FER Assistant led to group differences in FER at endpoint, compared to a waitlist control. However, analyses examining reliable change in FER indicated no reliable improvement or decline for FER Assistant participants, whereas two waitlist participants demonstrated reliable decline. Conclusion: Given the preliminary nature of this work, results collectively suggest that FER Assistant may be an acceptable intervention. Results also suggest that FER may be a potential mechanism that is amenable to intervention for autistic individuals, although additional trials using larger sample sizes are warranted. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Autism & Developmental Disorders is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=187434603
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        Value: 10.1007/s10803-024-06436-w
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      – Code: eng
        Text: English
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        PageCount: 14
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    Subjects:
      – SubjectFull: Treatment of autism
        Type: general
      – SubjectFull: Patient compliance
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      – SubjectFull: Research funding
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      – SubjectFull: Electroencephalography
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      – SubjectFull: Statistical sampling
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      – SubjectFull: Biofeedback training
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      – SubjectFull: Randomized controlled trials
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      – SubjectFull: Virtual reality
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      – SubjectFull: Patient satisfaction
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      – SubjectFull: Face perception
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      – SubjectFull: User interfaces
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              M: 09
              Text: Sep2025
              Type: published
              Y: 2025
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