ArticlePLoS computational biology2025
Traveling waves in the human visual cortex: An MEG-EEG model-based approach.
Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Retrospective attention reveals a decaying theta rhythm in conscious access to a preceding stimulus.iScience · 2026Article
- The alpha rhythm: from physiology to behavior.Physiological reviews · 2026Review
- Non-invasive mapping of the temporal processing hierarchy in the human visual cortex.PLoS computational biology · 2026Article
- Article
- Semantics and syntax effects on event-related fields during speech comprehension: a MEG study.Frontiers in human neuroscience · 2026Article
- Article
- Attention-induced perceptual traveling waves in binocular rivalry.Journal of vision · 2025Article
- Locally Induced Traveling Waves Generate Globally Observable Traveling Waves.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
Brain oscillations might be traveling waves propagating in cortex. Studying their propagation within single cortical areas has mostly been restricted to invasive measurements. Their investigation in healthy humans, however, requires non-invasive recordings, such as MEG or EEG. Identifying traveling waves with these techniques is challenging because source summation, volume conduction, and low signal-to-noise ratios make it difficult to localize cortical activity from sensor responses. The difficulty is compounded by the lack of a known ground truth in traveling wave experiments. Rather than source-localizing cortical responses from sensor activity, we developed a two-part model-based neuroimaging approach: (1) The putative neural sources of a propagating oscillation were modeled within primary visual cortex (V1) via retinotopic mapping from functional MRI recordings (encoding model); and (2) the modeled sources were projected onto MEG and EEG sensors to predict the resulting signal using a biophysical head model. We tested our model by comparing its predictions against the MEG-EEG signal obtained when participants viewed visual stimuli designed to elicit either fovea-to-periphery or periphery-to-fovea traveling waves or standing waves in V1, in which ground truth cortical waves could be reasonably assumed. Correlations on within-sensor phase and amplitude relations between predicted and measured data revealed good model performance. Crucially, the model predicted sensor data more accurately when the input to the model was a traveling wave going in the stimulus direction compared to when the input was a standing wave, or a traveling wave in a different direction. Furthermore, model accuracy peaked at the spatial and temporal frequency parameters of the visual stimulation. Together, our model successfully recovers traveling wave properties in cortex when they are induced by traveling waves in stimuli. This provides a sound basis for using MEG-EEG to study endogenous traveling waves in cortex and test hypotheses related with their role in cognition.
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Registered trials
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