ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2023
EEG Decoding Reveals Neural Predictions for Naturalistic Material Behaviors.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Material discrimination relies on context-dependent active sensing strategies.Journal of vision · 2026Article
- Vocal Emotion Perception and Musicality-Insights from EEG Decoding.Sensors (Basel, Switzerland) · 2025Article
- Neural representation of consciously seen and unseen information.Scientific reports · 2025Article
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Authors and funding
3 authors.
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Abstract
Material properties, such as softness or stickiness, determine how an object can be used. Based on our real-life experience, we form strong expectations about how objects should behave under force, given their typical material properties. Such expectations have been shown to modulate perceptual processes, but we currently do not know how expectation influences the temporal dynamics of the cortical visual analysis for objects and their materials. Here, we tracked the neural representations of expected and unexpected material behaviors using time-resolved EEG decoding in a violation-of-expectation paradigm, where objects fell to the ground and deformed in expected or unexpected ways. Participants were 25 men and women. Our study yielded three key results: First, both objects and materials were represented rapidly and in a temporally sustained fashion. Second, objects exhibiting unexpected material behaviors were more successfully decoded than objects exhibiting expected behaviors within 190 ms after the impact, which might indicate additional processing demands when expectations are unmet. Third, general signals of expectation fulfillment that generalize across specific objects and materials were found within the first 150 ms after the impact. Together, our results provide new insights into the temporal neural processing cascade that underlies the analysis of real-world material behaviors. They reveal a sequence of predictions, with cortical signals progressing from a general signature of expectation fulfillment toward increased processing of unexpected material behaviors.
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