ArticlePsychophysiology2024
Using multivariate pattern analysis to increase effect sizes for event-related potential analyses.
Article in Psychophysiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Evaluating the effects of regularization and cross-validation parameters on the performance of SVM-based decoding of EEG data.Cortex; a journal devoted to the study of the nervous system and behavior · 2026Article
- Neural Markers of Interocular Grouping During Binocular Rivalry With MEG.Human brain mapping · 2026Article
- Evaluating the effects of regularization and cross-validation parameters on the performance of SVM-based decoding of EEG data.bioRxiv : the preprint server for biology · 2026Article
- Experience-dependent Changes in the Visual Processing of Letters: Evidence from Electroencephalography Decoding.Journal of cognitive neuroscience · 2026Article
- Population-Level Activity Dissociates Preparatory Overt from Covert Attention.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Assessing the impact of artifact correction and artifact rejection on the performance of SVM- and LDA-based decoding of EEG signals.NeuroImage · 2025Article
- How EEG preprocessing shapes decoding performance.Communications biology · 2025Article
- Assessing the impact of artifact correction and artifact rejection on the performance of SVM-based decoding of EEG signals.bioRxiv : the preprint server for biology · 2025Article
- Decoding in the Fourth Dimension: Classification of Temporal Patterns and Their Generalization Across Locations.Human brain mapping · 2025Article
- Decoding event-related potentials: single-dose energy dietary supplement acts on earlier brain processes than we thought.Frontiers in neuroinformatics · 2025Article
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Abstract
Multivariate pattern analysis (MVPA) approaches can be applied to the topographic distribution of event-related potential (ERP) signals to "decode" subtly different stimulus classes, such as different faces or different orientations. These approaches are extremely sensitive, and it seems possible that they could also be used to increase effect sizes and statistical power in traditional paradigms that ask whether an ERP component differs in amplitude across conditions. To assess this possibility, we leveraged the open-source ERP CORE data set and compared the effect sizes resulting from conventional univariate analyses of mean amplitude with two MVPA approaches (support vector machine decoding and the cross-validated Mahalanobis distance, both of which are easy to compute using open-source software). We assessed these approaches across seven widely studied ERP components (N170, N400, N2pc, P3b, lateral readiness potential, error related negativity, and mismatch negativity). Across all components, we found that multivariate approaches yielded effect sizes that were as large or larger than the effect sizes produced by univariate approaches. These results indicate that researchers could obtain larger effect sizes, and therefore greater statistical power, by using multivariate analysis of topographic voltage patterns instead of traditional univariate analyses in many ERP studies.
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