Electroencephalogram-Based Single-Trial Detection of Language Expectation Violations in Listening to Speech

Tanaka, Hiroki; Watanabe, H.; Maki, Hayato; Sakti, Sakriani; Nakamura, Satoshi

doi:10.3389/fncom.2019.00015

Cited by 11 publications

(7 citation statements)

References 63 publications

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“…It is likely that their higher accuracy reflects the better data quality recorded in adults, who are better able to sit still and engage with the task. More recently, Tanaka et al reported significant decoding of single-trial semantic anomalies, with an overall accuracy of 59.5% 53 . They, however, did not report individualparticipant accuracies, making it hard to compare their results to the current findings.…”

Section: Discussionmentioning

confidence: 99%

Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children

Petit

Badcock

Grootswagers

et al. 2020

Sci Rep

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In conditions such as minimally-verbal autism, standard assessments of language comprehension are often unreliable. Given the known heterogeneity within the autistic population, it is crucial to design tests of semantic comprehension that are sensitive in individuals. Recent efforts to develop neural signals of language comprehension have focused on the N400, a robust marker of lexical-semantic violation at the group level. However, homogeneity of response in individual neurotypical children has not been established. Here, we presented 20 neurotypical children with congruent and incongruent visual animations and spoken sentences while measuring their neural response using electroencephalography (EEG). Despite robust group-level responses, we found high inter-individual variability in response to lexico-semantic anomalies. To overcome this, we analysed our data using temporally and spatially unconstrained multivariate pattern analyses (MVPA), supplemented by descriptive analyses to examine the timecourse, topography, and strength of the effect. Our results show that neurotypical children exhibit heterogenous responses to lexical-semantic violation, implying that any application to heterogenous disorders such as autism spectrum disorder will require individual-subject analyses that are robust to variation in topology and timecourse of neural responses.

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Section: Discussionmentioning

confidence: 99%

Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children

Petit

Badcock

Grootswagers

et al. 2020

Sci Rep

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“…Previous works have reported single-trial classification rates in the order of 0.8 (see Reference [ 58 , 59 , 65 ]). The classification rates reported are similar to those achieved in this work.…”

Section: Discussionmentioning

confidence: 99%

“…First, the effect of stimulation condition and of the number of symbols on the single-trial classification between target and non-target responses was assessed through a five-fold cross-validation process. Although there exist a sample overlapping, this performance evaluation approach is quite acceptable to estimate the online performance of the BCI [ 58 , 59 ]. Here, all the epochs in a given dataset were randomly allocated into five sets.…”

Section: Methodsmentioning

confidence: 99%

Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions

Peguero

Mendoza-Montoya

Antelis

2020

Sensors

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The P300 paradigm is one of the most promising techniques for its robustness and reliability in Brain-Computer Interface (BCI) applications, but it is not exempt from shortcomings. The present work studied single-trial classification effectiveness in distinguishing between target and non-target responses considering two conditions of visual stimulation and the variation of the number of symbols presented to the user in a single-option visual frame. In addition, we also investigated the relationship between the classification results of target and non-target events when training and testing the machine-learning model with datasets containing different stimulation conditions and different number of symbols. To this end, we designed a P300 experimental protocol considering, as conditions of stimulation: the color highlighting or the superimposing of a cartoon face and from four to nine options. These experiments were carried out with 19 healthy subjects in 3 sessions. The results showed that the Event-Related Potentials (ERP) responses and the classification accuracy are stronger with cartoon faces as stimulus type and similar irrespective of the amount of options. In addition, the classification performance is reduced when using datasets with different type of stimulus, but it is similar when using datasets with different the number of symbols. These results have a special connotation for the design of systems, in which it is intended to elicit higher levels of evoked potentials and, at the same time, optimize training time.

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“…It is likely that their higher accuracy reflects the better data quality recorded in adults, who are better able to sit still and engage with the task. More recently, Tanaka et al (2019) reported significant decoding of single-trial semantic anomalies, with an overall accuracy of 59.5%.…”

Section: Discussionmentioning

confidence: 99%

Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children

Petit

Badcock

Grootswagers

et al. 2019

Preprint

View full text Add to dashboard Cite

In conditions such as minimally-verbal autism, standard assessments of language comprehension are often unreliable. Given the known heterogeneity within the autistic population, it is crucial to design tests of semantic comprehension that are sensitive in individuals. Recent efforts to develop neural signals of language comprehension have focused on the N400, a robust marker of lexical-semantic violation at the group level. However, homogeneity of response in individual neurotypical children has not been established. Here, we presented 20 children with congruent and incongruent visual animations and spoken sentences while measuring their neural response using EEG. Despite robust group-level responses, we found high inter-individual variability in response to lexico-semantic anomalies. To overcome this, we analysed our data using temporally and spatially unconstrained MVPA, supplemented by descriptive analyses to examine the timecourse, topography, and strength of the effect. Even neurotypical children exhibit heterogenous responses to lexical-semantic violation, implying that any application to heterogenous disorders such as ASD will require individual-subject analyses that are robust to variation in topology and timecourse of neural responses.

show abstract

Electroencephalogram-Based Single-Trial Detection of Language Expectation Violations in Listening to Speech

Cited by 11 publications

References 63 publications

Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children

Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children

Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions

Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children

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