ArticleHuman brain mapping2023
EEG mismatch responses in a multimodal roving stimulus paradigm provide evidence for probabilistic inference across audition, somatosensation, and vision.
Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Evidence for early and late prediction error-associated ERP responses during probabilistic cueing.iScience · 2026Article
- Modality-general sensitivity of pupil responses to regularity violations.Cognitive, affective & behavioral neuroscience · 2026Article
- This sounds important: Electrophysiological responses reveal a dedicated learning mechanism to process salient consonant sounds in human newborns.Psychonomic bulletin & review · 2026Article
- Functional Dissociation of Mismatch Negativity From Late Discriminative Negativity Across the Adult Lifespan.The European journal of neuroscience · 2026Article
- Article
- The Somatosensory Mismatch Negativity.The European journal of neuroscience · 2025Review
- Predicted Sensory Modality Determines the Timing and Topographies of Omitted Stimulus Potentials.Psychophysiology · 2025Article
- The Neurophysiological Features of Anticipation in Schizophrenia: A Cross-Sectional Study of Event-Related Potentials.Consortium psychiatricum · 2025Article
- Model-Based Approaches to Investigating Mismatch Responses in Schizophrenia.Clinical EEG and neuroscience · 2025Review
- Functional interaction between posterior cerebellar lobes and secondary somatosensory cortex during somatosensory mismatch detection.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Somatosensory omissions reveal action-related predictive processing.Human brain mapping · 2024Article
- A multimodal cortical network of sensory expectation violation revealed by fMRI.Human brain mapping · 2023Article
- Time-resolved dynamic computational modeling of human EEG recordings reveals gradients of generative mechanisms for the MMN response.PLoS computational biology · 2023Article
- EEG mismatch responses in a multimodal roving stimulus paradigm provide evidence for probabilistic inference across audition, somatosensation, and vision.Human brain mapping · 2023Article
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4 authors.
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Abstract
The human brain is constantly subjected to a multimodal stream of probabilistic sensory inputs. Electroencephalography (EEG) signatures, such as the mismatch negativity (MMN) and the P3, can give valuable insight into neuronal probabilistic inference. Although reported for different modalities, mismatch responses have largely been studied in isolation, with a strong focus on the auditory MMN. To investigate the extent to which early and late mismatch responses across modalities represent comparable signatures of uni- and cross-modal probabilistic inference in the hierarchically structured cortex, we recorded EEG from 32 participants undergoing a novel tri-modal roving stimulus paradigm. The employed sequences consisted of high and low intensity stimuli in the auditory, somatosensory and visual modalities and were governed by unimodal transition probabilities and cross-modal conditional dependencies. We found modality specific signatures of MMN (~100-200 ms) in all three modalities, which were source localized to the respective sensory cortices and shared right lateralized prefrontal sources. Additionally, we identified a cross-modal signature of mismatch processing in the P3a time range (~300-350 ms), for which a common network with frontal dominance was found. Across modalities, the mismatch responses showed highly comparable parametric effects of stimulus train length, which were driven by standard and deviant response modulations in opposite directions. Strikingly, P3a responses across modalities were increased for mispredicted stimuli with low cross-modal conditional probability, suggesting sensitivity to multimodal (global) predictive sequence properties. Finally, model comparisons indicated that the observed single trial dynamics were best captured by Bayesian learning models tracking unimodal stimulus transitions as well as cross-modal conditional dependencies.
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