Improved detection and spatiotemporal spectral analysis of neural traveling waves

Traveling waves (TWs) are a fundamental mode of neural dynamics, yet existing detection methods are limited by sensor geometry, spatial-frequency resolution, signal amplitude, and ambiguity between propagating and standing-wave patterns. Here we introduce the Traveling Wave Index (TWINDEX), a framework for three-dimensional spatiotemporal spectral analysis of TWs across temporal frequency, spatial frequency, and propagation direction. TWINDEX generalizes to irregular sensor layouts, and quantifies wave strength as the reduction in circular phase variance produced by a candidate planar wave. This normalization yields robust behavior at both low and high spatial frequencies and suppresses coherent in-phase activity. Directional moments further separate planar from standing waves. We derive analytical links between TWINDEX, parametric planar-wave fit, and distance-phase correlation, and introduce projected distance-phase correlation (ProDPC) for sensitive single-trial planar-wave detection. Applying these methods to large-scale marmoset ECoG and human EEG, we identify alpha/low-beta TWs localized in spatial and temporal frequency, with physiologically plausible propagation speeds. Across trials and epochs, waves occur in oppositely directed propagation modes, demonstrating that alpha/beta activity is associated with both feedforward- and feedback-directed large-scale dynamics.