Spectral smoothing explains the offline gain from cross-order single-trial MEG movement decoding for non-invasive BCI
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Updated: Oct 31, 2026

Using an EEG-Based Brain-Computer Interface for Virtual Cursor Movement with BCI2000
Published on: July 29, 2009
1Seoul AI School, Seoul School of Integrated Sciences and Technologies, 504, 46 Ewhayeodae 2-gil, Seodaemun-gu, Seoul, Republic of Korea., Seodaemun-gu, Seoul, 03767, Korea (the Republic of).
Objective:
Acceleration, velocity, and position can be combined in non-invasive movement decoding, but in this dataset only acceleration is measured; velocity and position are deterministic transforms obtained by integration. We therefore tested whether cross-order decoder fusion improves estimation in position space and whether any apparent gain remains after matching the spectral consequences of those transforms. Approach. We analysed single-trial MEG recordings from nine participants (18 runs; 2,160 trials) using a deterministic five-fold split. The primary outcome was within-trial Pearson correlation in position-residual space after removing trial-invariant trajectory. Acceleration-, velocity-, and position-based routes were fused and compared with same-order bagging, decorrelation-matched controls, and a bandwidth-matched pseudo-fusion of filtered copies of the direct position decoder. We additionally tested implementation sensitivity, residual-space R², non-positive-lag and causal pipelines, artefact sensitivity, multi-task architectures, and between-run transfer. Main results. Cross-order fusion exceeded same-order bagging by +0.0389 per-trial r (95% CI [+0.0288, +0.0499]; 9/9 participants). The bandwidth-matched pseudo-fusion exceeded bagging by +0.0424 and reproduced 109.0% of the offline margin, leaving E_cross - E_spec = -0.0035 (95% CI [-0.0105, +0.0032]; upper one-sided 95% bound +0.003). A nested-cross-validated smoothed single decoder likewise matched the ensemble. On residual-space R² with a training-fitted gain, the ordering reversed (E_bag -0.099, E_cross -0.120), showing that the correlation gain did not improve amplitude fidelity. With non-positive lags only, bandwidth matching explained 79% of the margin; under a fully causal zero-look-ahead pipeline, a smaller residual persisted and its mechanism was underpowered to resolve. Between-run transfer within the same visit retained only about 18% of within-run accuracy. Significance. In the primary offline regime, cross-order fusion gains can arise from integration-induced spectral smoothing without additional cross-order neural information. A bandwidth-matched surrogate should precede mechanistic interpretation when decoder routes are linked by deterministic transforms. In the causal regime, the advantage remains available online, but its mechanism remains unresolved.
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