ArticleFrontiers in computational neuroscience2019
Electroencephalogram-Based Single-Trial Detection of Language Expectation Violations in Listening to Speech.
Article in Frontiers in computational neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Behavioral Analysis of EEG Signals in Loss-Gain Decision-Making Experiments.Behavioural neurology · 2022Article
- Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions.Sensors (Basel, Switzerland) · 2020Article
- Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children.Scientific reports · 2020Article
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5 authors.
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Abstract
We propose an approach for the detection of language expectation violations that occur in communication. We examined semantic and syntactic violations from electroencephalogram (EEG) when participants listened to spoken sentences. Previous studies have shown that such event-related potential (ERP) components as N400 and the late positivity (P600) are evoked in the auditory where semantic and syntactic anomalies occur. We used this knowledge to detect language expectation violation from single-trial EEGs by machine learning techniques. We recorded the brain activity of 18 participants while they listened to sentences that contained semantic and syntactic anomalies and identified the significant main effects of these anomalies in the ERP components. We also found that a multilayer perceptron achieved 59.5% (semantic) and 57.7% (syntactic) accuracies.
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