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Cited by 34EEG and Brain-Computer InterfacesAutism Spectrum Disorder ResearchEmotion and Mood Recognition

Trial by trial EEG based BCI for distress versus non distress classification in individuals with ASD

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Eldeeb, Safaa, Susam, Busra T., Akcakaya, Murat, Conner, Caitlin M., White, Susan W., Mazefsky, Carla A.·2021·Scientific Reports
DOI 10.1038/s41598-021-85362-8PMC PMC7971030
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Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is often accompanied by impaired emotion regulation (ER). There has been increasing emphasis on developing evidence-based approaches to improve ER in ASD. Electroencephalography (EEG) has shown success in reducing ASD symptoms when used in neurofeedback-based interventions. Also, certain EEG components are associated with ER. Our overarching goal is to develop a technology that will use EEG to monitor real-time changes in ER and perform intervention based on these changes. As a first step, an EEG-based brain computer interface that is based on an Affective Posner task was developed to identify patterns associated with ER on a single trial basis, and EEG data collected from 21 individuals with ASD. Accordingly, our aim in this study is to investigate EEG features that could differentiate between distress and non-distress conditions. Specifically, we investigate if the EEG time-locked to the visual feedback presentation could be used to classify between WIN (non-distress) and LOSE (distress) conditions in a game with deception. Results showed that the extracted EEG features could differentiate between WIN and LOSE conditions (average accuracy of 81%), LOSE and rest-EEG conditions (average accuracy 94.8%), and WIN and rest-EEG conditions (average accuracy 94.9%).

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  • There has been little research on distress tolerance, behavioral activation, and depressive and anxiety symptoms in autistic adolescents to guide diagnostic practices and treatment planning.

    “To our knowledge, there has been little research on distress tolerance, behavioral activation, and depressive and anxiety symptoms in autistic adolescents to guide diagnostic practices and treatment planning.”

    From The relationship between distress tolerance and behavioral activation on anxiety and depression symptomatology in autistic youth: Leveraging self and caregiver perspectives (2024) · cites this paper as Eldeeb et al., 2021

    The Introduction discusses emotion-regulation difficulties in autistic people and their relevance to treatment, while the Discussion mentions distress-tolerance training. Neither passage says that research on distress tolerance, behavioral activation, and depressive and anxiety symptoms in autistic adolescents is scarce or links such a gap to diagnostic and treatment planning. Searches for those terms and for the claimed research gap found no supporting passage in our copy. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

  • Few studies have specifically examined the broad construct of distress tolerance or behavioral activation in autism.

    “Despite an increasing focus on ER in autistic individuals (Cai et al., 2018), few studies have specifically examined the broad construct of DT or BA in autism (Eldeeb et al., 2021; Schwartzman et al., 2023)”

    From The relationship between distress tolerance and behavioral activation on anxiety and depression symptomatology in autistic youth: Leveraging self and caregiver perspectives (2024) · cites this paper as Eldeeb et al., 2021

    The Introduction discusses emotion regulation in autism, and the Discussion mentions distress tolerance as a goal for a future intervention. Neither section assesses how many studies have examined the broad constructs of distress tolerance or behavioral activation. Searches for those terms and for statements that such studies are scarce did not establish the claim. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

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Authors
Eldeeb, S., Susam, B. T., Akcakaya, M., Conner, C. M., White, S. W., & Mazefsky, C. A.
Affiliations
  • University of Pittsburgh (US)
  • University of Alabama (US)
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2021-03-16
Volume
11
Issue
1
Pages
6000-6000
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-021-85362-8
PMC
PMC7971030
OpenAlex
W3139427875
Cited by
34
References
53
Citations by year
2026: 3 · 2025: 7 · 2024: 4 · 2023: 12 · 2022: 8
FWCI
3.15
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Science Foundation (1844885)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
Keywords
autism spectrum disorder, emotion regulation, distress detection, EEG-based brain-computer interface, single-trial EEG classification, neurofeedback, real-time emotion monitoring
MeSH terms
Clinical Decision-Making, Autism Spectrum Disorder, Data Analysis, Adolescent, Algorithms, Child, Disease Susceptibility, Electroencephalography, Emotions, Evoked Potentials, Humans, Sensitivity and Specificity, Reproducibility of Results, Biomarkers, Disease Management, Young Adult, Brain-Computer Interfaces, Symptom Assessment

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