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

Abstract

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.

Word Detection in Individual Subjects Is Difficult to Probe With Fast Periodic Visual Stimulation

“…Promisingly, time-unconstrained multivariate decodingwhich allows detection of effects with different topology and timecourse in each subject-elicited a higher detection rate (16/18 subjects) than traditional ERP analyses in this N400 study (9/18 subjects; Petit et al, 2020a). Such multivariate approaches can theoretically increase sensitivity to time-or locationvarying effects by allowing a classifier to learn which channels and timepoints best differentiate experimental conditions in each subject, without increasing multiple comparisons.…”

“…Recent work highlights between-subject lexical processing variability as key challenge for robust detection. Two studies ( Petit et al, 2020a , b ) used spoken-word stimuli in a traditional N400 ERP design to measure receptive language in children. Responses in individual children varied in their time-course and topography.…”

Exploring the Representations of Individual Entities in the Brain Combining EEG and Distributional Semantics

“…We took a time-resolved decoding approach (Grootswagers et al, 2017 ) for our classification, training and testing separately on each time point. We tested statistical significance at each time point using threshold-free cluster enhancement (TFCE), a permutation-based, non-parametric test of statistical significance proposed in Smith and Nichols ( 2009 ) and then widely adopted in the neuroscientific literature (Helwig, 2019 ), also for classification of EEG signals (Grootswagers et al, 2019 ; Kaiser et al, 2020 ; Petit et al, 2020 ). The main advantages of this procedure are its sensitivity, due to the fact that it can take into account the fact that brain signals are clustered both in space and in time; its avoidance of parametric test assumptions (Mensen and Khatami, 2013 ); and finally, the fact that it inherently counters the multiple comparisons problem (the inflated risk of finding false positives) that arises from testing so many data points (in our case, time points; for details on the general procedure, see Mensen and Khatami, 2013 ).…”

Cognitive-Motor Dissociation Following Pediatric Brain Injury

“… 31 , 33 The N400 has been shown to be preserved (albeit at reduced amplitude) in the group mean data from adults in VS/UWS and MCS. This has previously been presented as unreliable on an individual-patient basis in DoC 34 because of its low negative predictive value. However, when present, it is predictive of positive outcomes.…”