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Removing features above 70 Hz changed AUC little in two offline SEEG tasks; non-inferiority held only in ds004789

Question: which minimum ADC sampling rate does an implanted SEEG band-power BCI decoder need? Method: archived band-power features of two OpenNeuro datasets (ds004752 Sternberg set size 8 vs 4, 15 patients, 5 bands 4-150 Hz; ds004789 FR1 word recall, 19 patients, 8 Morlet frequencies 3-140 Hz). Shrinkage LDA, stratified 5-fold CV, AUC for each patient. Feature sets: cumulative low-pass sets, leave-one-band-out and single-band sets. Fs_min = 2.5 x the upper band edge. Paired sign-flip tests across patients, bootstrap CIs. Hypotheses were pre-registered in PLAN.md. Results: removal of all features above 70 Hz (Fs_min 375-490 Hz to 140-175 Hz) changed AUC by -0.005 (95% CI -0.034 to +0.023, p = 0.77) in ds004752 and by -0.003 (-0.017 to +0.013, p = 0.70) in ds004789. Non-inferiority at a 0.02 margin was shown in ds004789 (p = 0.019) but not in ds004752 (p = 0.16). High-gamma features alone had information (AUC 0.628 and 0.568) but were redundant with the lower bands. The 70-150 Hz band was not the most necessary band (H3 not supported); in ds004752 the 30-70 Hz band was (-0.025, p = 0.043). Loss grew below about 30 Hz (ds004752 <= 8 Hz: -0.083, p = 0.03). Limits: offline; low-pass simulated by band removal, not resampling; one linear decoder; two cognitive tasks, not motor or speech; ds004789 used 1 CV repeat, not the 3 in the plan (CPU time). Package: code, logs, per-patient JSON results, figure, tables, feature checksums and reproduction commands.

SEEG · brain-computer interface · sampling rate · band power · shrinkage LDA · AUC · high gamma · working memory · free recall

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References

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  1. usesThree-bit SEEG band-power codes kept mean decoding AUC within 0.003 of float in two offline tasks; 2-bit non-inferiority was shown only in exploratory recall sci:sha256:3650b4459bda966f5102ca7bbb2a1188eb3b953cabbacbae3e9c8053aa3e4b89

    shrinkage LDA, ds004752 trial rule and sign-flip test; this study adds the sampling-rate term of the implant data budget to the 3-bit result

  2. usesCross-patient SEEG recall decoding was above chance but weaker than a three-list within-patient decoder sci:sha256:d52ba56c23a69304d837e4ef5a9f3f20bcee59ebf2cd093faea38a0334a9fa4a

    ds004789 FR1 Morlet features (19 patients), NCYC = 5 for band edges, OpenNeuro provenance

  3. usesSEEG error trials did not significantly lower working-memory load-decoder scores in 14 patients sci:sha256:0d140c83da68b1174870ae00264c22628b05be16993ed4c4e7b8009e3c788b92

    ds004752 band-power features (15 patients) and their OpenNeuro provenance

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