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Rest 70–150 Hz power distinguished gray and white matter SEEG pairs in eight subjects; a ds006519 threshold transferred with 0.68 balanced accuracy

In eight subjects from OpenNeuro ds004473, gray-matter (GM) stereo-EEG (SEEG) bipolar pairs had higher 70–150 Hz rest log power than white-matter (WM) pairs in all subjects (median AUC 0.75; exact one-sided sign-flip p = 0.0039). A threshold fixed on ds006519 (z = −0.387) transferred without refitting and gave median balanced accuracy 0.68 in ds004473 (8/8 above 0.5; p = 0.0039). The top 25% of pairs by power had a median 26 percentage-point increase in GM over the subject base rate (7/8; p = 0.0078). Within WM, power decreased with distance from cortex (median Spearman rho = −0.30; 8/8; p = 0.0039). A two-feature logistic model ranked pairs (median AUC 0.71) but its probability >0.5 rule did not transfer (median balanced accuracy 0.50), consistent with a GM base-rate change from 93% in ds006519 to 28–58% in ds004473. The result supports a rapid tissue check, not replacement of imaging: balanced accuracy was modest, labels came from a single midpoint voxel, and higher WM power near cortex may reflect volume conduction, contact impedance, or bipolar reference geometry. The analysis used 60 half-second windows (30 s) between trials, eight subjects, differing tissue-label methods and frequency bands across datasets, and no correction for secondary tests. The exact ds004473 release used for the archived features is not established; its source URL and file hashes are retained.

stereo-EEG · SEEG · gray matter · white matter · bipolar pairs · high-gamma power · tissue classification · brain-computer interfaces · transfer · OpenNeuro

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References

5
  1. usesIn offline SEEG data, sensorimotor pairs improved key-press decoding in 2 of 3 subjects with sensorimotor coverage sci:sha256:5e89c8255391507454ce1a75302346955f39256ad0f545e6afa79b22ad47d746

    Origin of the ds004473 band-power features, bipolar pairs and FreeSurfer midpoint labels.

  2. usesEight-subject SEEG comparison found similar key-press decoding AUC for white- and gray-matter pairs sci:sha256:bc1a5a778c1c224d101bf92918fa468400b184eb9e9a55dcd3bdb414f4345789

    Uses its copied ds004473 feature files (rest windows, midpoint labels, distance to cortex) and its tissue definition unchanged.

  3. supportsIn 7 SEEG subjects, white-matter channels had 2–3× less broadband power than gray-matter channels, but the 1/f exponent did not separate them sci:sha256:561670f549ba1a156d21db5a4bb1bfbf0f846f2c6b7d8ff9fffe8ad986ffde75

    Replicates its GM > WM rest high-gamma power effect in a different dataset, lab, task and label method (8 of 8 subjects), and shows that its threshold transfers without refit.

  4. usesIn 7 SEEG subjects, white-matter channels had 2–3× less broadband power than gray-matter channels, but the 1/f exponent did not separate them sci:sha256:561670f549ba1a156d21db5a4bb1bfbf0f846f2c6b7d8ff9fffe8ad986ffde75

    Uses its ds006519 channel_features.csv to fix the transfer threshold and the 2-feature model.

  5. usesdoi:10.18112/openneuro.ds006519.v1.0.0

    The ds006519 channel features set the transfer threshold and train the two-feature logistic model.

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