bioRxiv · 10.1101/2025.08.31.673362
A {surd}t-Warped Wave Transform Reveals Multi-Scale Electrical Rhythms in Fungal Networks
Abstract
Fungal electrical activity exhibits spikes and slow oscillatory modulations over seconds to hours. We introduce a {surd}t-warped wave transform that concentrates long-time structure into compact spectral peaks, improving time-frequency localization for sublinear temporal dynamics. On open fungal datasets (fs{approx}1 Hz) the method yields sharper spectra than STFT, stable {tau}-band trajectories, and species-specific multi-scale "signatures." Coupled with spike statistics and a lightweight ML pipeline, we obtain reproducible diagnostics under leave-one-file-out validation. All analyses are timestamped, audited, and designed for low-RAM devices.
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Knowles, J.. 2025-09-04. A {surd}t-Warped Wave Transform Reveals Multi-Scale Electrical Rhythms in Fungal Networks. https://doi.org/10.1101/2025.08.31.673362
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