When Does EEG Decoding Survive Electromagnetic Interference?

EEG decoders are trained in electromagnetically clean laboratories but deployed in hospitals, cockpits, and wearable settings. Structured electromagnetic interference collides with neural frequency bands, driving decoders to chance. Removing those frequencies can also erase activity that the task needs. We ask when decoding survives this shift. We introduce the Interference–Neural Confusion benchmark with four physically motivated interference families and a compact sensing-gating-calibration front end. It locates occupied frequencies in a fixed short-time Fourier representation, suppresses those bins, and withholds predictions when sensing is unreliable. For a fixed mask, the output is unchanged by interference whose transform support the mask covers; an operator-norm bound quantifies residual leakage. In subject-disjoint experiments on STEW, narrowband interference at -10 dB drops mean accuracy from 0.858 to 0.504, while gating restores 0.747, with gains on every held-out subject. For left- versus right-hand imagery in BCI Competition IV 2a, accuracy remains 0.556; band ablation points to the task information lost by gating. Prediction-set coverage on STEW rises from 0.478 to 0.854 after gating (clean: 0.915), but broadband sweeps remain largely undetected. These results connect recovery to detectable interference and the preservation of task-relevant rhythms, identifying when spectral gating can support reliable EEG decoding.