ArticlePLoS computational biology2021
Neural surprise in somatosensory Bayesian learning.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- This sounds important: Electrophysiological responses reveal a dedicated learning mechanism to process salient consonant sounds in human newborns.Psychonomic bulletin & review · 2026Article
- Validating electrical stimulation through the somatosensory system: a perspective on mismatch negativity and auditory prostheses.Frontiers in human neuroscience · 2026Article
- The Somatosensory Mismatch Negativity.The European journal of neuroscience · 2025Review
- Perceptual experience in somatosensory temporal discrimination is indexed by a mid-latency fronto-central ERP difference.Scientific reports · 2025Article
- Evaluating cardiac noise correction approaches for non-invasive electrophysiology of the human spinal cord.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Functional interaction between posterior cerebellar lobes and secondary somatosensory cortex during somatosensory mismatch detection.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Model-Based Approaches to Investigating Mismatch Responses in Schizophrenia.Clinical EEG and neuroscience · 2025Review
- Dorsal Anterior Cingulate Cortex Coordinates Contextual Mental Imagery for Single-Beat Manipulation during Rhythmic Sensorimotor Synchronization.Brain sciences · 2024Article
- Somatosensory omissions reveal action-related predictive processing.Human brain mapping · 2024Article
- Fast adaptation to rule switching using neuronal surprise.PLoS computational biology · 2024Article
- Time-resolved dynamic computational modeling of human EEG recordings reveals gradients of generative mechanisms for the MMN response.PLoS computational biology · 2023Article
- A multimodal cortical network of sensory expectation violation revealed by fMRI.Human brain mapping · 2023Article
- Bayesian Surprise Predicts Human Event Segmentation in Story Listening.Cognitive science · 2023Article
- EEG mismatch responses in a multimodal roving stimulus paradigm provide evidence for probabilistic inference across audition, somatosensation, and vision.Human brain mapping · 2023Article
- Semantic surprise predicts the N400 brain potential.Neuroimage. Reports · 2023Article
- Active inference and the two-step task.Scientific reports · 2022Article
- Spatiotemporal Signatures of Surprise Captured by Magnetoencephalography.Frontiers in systems neuroscience · 2022Article
- Article
- Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making.PLoS computational biology · 2021Article
- Human Belief State-Based Exploration and Exploitation in an Information-Selective Symmetric Reversal Bandit Task.Computational brain & behavior · 2021Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tracking statistical regularities of the environment is important for shaping human behavior and perception. Evidence suggests that the brain learns environmental dependencies using Bayesian principles. However, much remains unknown about the employed algorithms, for somesthesis in particular. Here, we describe the cortical dynamics of the somatosensory learning system to investigate both the form of the generative model as well as its neural surprise signatures. Specifically, we recorded EEG data from 40 participants subjected to a somatosensory roving-stimulus paradigm and performed single-trial modeling across peri-stimulus time in both sensor and source space. Our Bayesian model selection procedure indicates that evoked potentials are best described by a non-hierarchical learning model that tracks transitions between observations using leaky integration. From around 70ms post-stimulus onset, secondary somatosensory cortices are found to represent confidence-corrected surprise as a measure of model inadequacy. Indications of Bayesian surprise encoding, reflecting model updating, are found in primary somatosensory cortex from around 140ms. This dissociation is compatible with the idea that early surprise signals may control subsequent model update rates. In sum, our findings support the hypothesis that early somatosensory processing reflects Bayesian perceptual learning and contribute to an understanding of its underlying mechanisms.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.