Stimulated human cortical waves: spatiotemporal dynamics across development

2026 · doi:10.64898/2026.01.12.699175
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This study used optical flow analysis of human iEEG data to reveal that cortical wave speed and direction are influenced by white matter tracts and associate with functional networks, varying non-linearly with age.

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The paper studied how traveling cortical neural activity waves develop and how they relate to brain anatomy and functional networks in humans, using an open-access iEEG dataset from the single-pulse stimulation CCEP paradigm. Applying a manifold-based optical flow method, the authors constructed high-temporal-resolution cortical velocity fields and used spatiotemporal mode decomposition, finding that large-scale plane waves dominate global propagation while local patterns support local computation. They reported that dominant wave directions correlate with underlying white matter fiber tract orientations, that velocity-field singularities cluster non-randomly near default mode network (DMN) hubs, and that cortical wave speed shows a nonlinear relationship with age consistent with white matter maturation and aging. The paper does not explicitly discuss any limitation in the provided text. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Traveling waves of neural activity are fundamental to cortical function, yet their spatiotemporal dynamics and structural constraints remain less understood in human brain. Conventional analyses focus on network topology and spatial geometry of neural signals, with limited emphasis on wave dynamics at high spatiotemporal resolutions. Here, we applied a manifold-based optical flow algorithm to an open-access intracranial electroencephalography (iEEG) dataset from the single-pulse stimulation cortico-cortical evoked potentials (CCEPs) paradigm, enabling direct construction of high-temporal-resolution cortical neural activity velocity fields. Spatiotemporal mode decomposition revealed a hierarchical organization: large-scale plane waves (mediating global propagation) dominate, complemented by local patterns for local computation. Dominant plane wave directions correlate with underlying white matter fibre tract orientations, indicating anatomical guidance of cortical dynamics. Velocity field singularities (sources, sinks, spirals and saddles) are non-randomly distributed, associating with default mode network (DMN) hubs. We further identified a nonlinear relationship between cortical wave speed and age, with developmental phases paralleling white matter maturation and aging. Our findings link cortical wave dynamics to anatomy, functional networks, and neurodevelopment, establishing wave speed as a potential yet important biomarker for brain function and health.
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Abstract Traveling waves of neural activity are fundamental to cortical function, yet their spatiotemporal dynamics and structural constraints remain less understood in human brain. Conventional analyses focus on network topology and spatial geometry of neural signals, with limited emphasis on wave dynamics at high spatiotemporal resolutions. Here, we applied a manifold-based optical flow algorithm to an open-access intracranial electroencephalography (iEEG) dataset from the single-pulse stimulation cortico-cortical evoked potentials (CCEPs) paradigm, enabling direct construction of high-temporal-resolution cortical neural activity velocity fields. Spatiotemporal mode decomposition revealed a hierarchical organization: large-scale plane waves (mediating global propagation) dominate, complemented by local patterns for local computation. Dominant plane wave directions correlate with underlying white matter fibre tract orientations, indicating anatomical guidance of cortical dynamics. Velocity field singularities (sources, sinks, spirals and saddles) are non-randomly distributed, associating with default mode network (DMN) hubs. We further identified a nonlinear relationship between cortical wave speed and age, with developmental phases paralleling white matter maturation and aging. Our findings link cortical wave dynamics to anatomy, functional networks, and neurodevelopment, establishing wave speed as a potential yet important biomarker for brain function and health. Competing Interest Statement The authors have declared no competing interest.

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