ArticleNature communications2023
Predictive neural representations of naturalistic dynamic input.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Oxytocin Reduces Subjective Fear in Naturalistic Social Contexts via Enhancing Top-Down Middle Cingulate Amygdala Regulation and Brain-Wide Fear Representations.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Trial
- Dynamic spatiotemporal features in action recognition: a multimodal study.Communications biology · 2026Article
- Distinct perceptual and conceptual representations of natural actions along the lateral and dorsal visual streams.Communications biology · 2026Article
- What is next? Predictable visual sequences are encoded with anticipatory biases and reduced neural responses.iScience · 2026Article
- The Representational Organization of Static and Dynamic Visual Features in the Human Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Predictable motion is progressively extrapolated across temporally distinct processing stages in the human visual cortex.PLoS biology · 2025Article
- Representational shifts from feedforward to feedback rhythms index phenomenological integration in naturalistic vision.Communications biology · 2025Article
- Neural processing of naturalistic audiovisual events in space and time.Communications biology · 2025Article
- The spatiotemporal neural dynamics of action-related features underlying action recognition.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Predictive neural representations of naturalistic dynamic input.Nature communications · 2023Article
Corrections and comments
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2 authors.
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Abstract
Adaptive behavior such as social interaction requires our brain to predict unfolding external dynamics. While theories assume such dynamic prediction, empirical evidence is limited to static snapshots and indirect consequences of predictions. We present a dynamic extension to representational similarity analysis that uses temporally variable models to capture neural representations of unfolding events. We applied this approach to source-reconstructed magnetoencephalography (MEG) data of healthy human subjects and demonstrate both lagged and predictive neural representations of observed actions. Predictive representations exhibit a hierarchical pattern, such that high-level abstract stimulus features are predicted earlier in time, while low-level visual features are predicted closer in time to the actual sensory input. By quantifying the temporal forecast window of the brain, this approach allows investigating predictive processing of our dynamic world. It can be applied to other naturalistic stimuli (e.g., film, soundscapes, music, motor planning/execution, social interaction) and any biosignal with high temporal resolution.
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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.