Fig. 6: EEG results: multivariate decoding and pattern component modelling.
From: Audiovisual adaptation is expressed in spatial and decisional codes
a Time course of the spatial encoding index (across-subjects’ mean ± SEM, n = 5 subjects, grey line and shaded area) and EEG evoked potentials (across-subjects’ mean, n = 5 subjects, averaged over central channels, see inset) for the 7 spatial locations in pre-adaptation phase (±12°, ±5°, ±2° and 0° azimuth). b Time course of the recalibration index (across-subjects’ mean ± SEM, n = 5 subjects, grey line and shaded area) and the EEG evoked potentials (across-subjects’ mean, n = 5 subjects, averaged over central channels, see inset) for sounds presented at 0° azimuth for pre-, postVA-, and postAV-adaptation phases. Clusters underlying significant effects of spatial encoding (a) and recalibration (b) (p < 0.05, one-sided, cluster corrected) are indicated by grey boxes. Areas within the dashed boxes indicate the a priori defined time window focusing on early recalibration effects13. c PCM results—Spatial and/or decisional uncertainty models as predictors for EEG activity patterns across four time windows. Across-subjects’ mean LogeBFs (±SEM, n = 5 subjects) and individual data points (circular markers) for each model. Top row: The spatial, decisional, and spatial + decisional uncertainty models without recalibration relative to a null model that allows for no similarity between activity patterns. Bottom row: The models factorially manipulate whether the spatial and/or decisional component accounts for recalibration. Loge-Bayes factors are relative to the spatial + decisional uncertainty model (without recalibration). Dash-dotted grey lines indicate the relative LogeBF for the fully flexible models as noise ceiling. S = spatial model, D = decisional uncertainty model, SR = spatial model with recalibration, DR = decisional uncertainty model with recalibration. d PCM results—BOLD-response patterns from the five ROIs as predictors for EEG activity patterns across four time windows. Across-subjects’ mean LogeBFs (±SEM, n = 5 subjects) and individual data points (circular markers) for each target model relative to the model using BOLD-response patterns in HG as predictors. HG Heschl’s gyrus, hA higher auditory cortex, IPS intraparietal sulcus, IPL inferior parietal lobule, FEF frontal eye-field. Source data are provided as a Source Data file.
