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White-matter speech high-gamma is largely nonlocal under bipolar rereferencing in two SEEG listeners

We tested whether speech-related high-gamma (HG) in white-matter (WM) stereo-EEG contacts reflects local activity or signals shared with gray matter (GM), and whether the event timing in OpenNeuro ds004993 is valid. We analyzed TIMIT listening recordings from two subjects (W2 and W3), using monopolar, common-average (CAR), and adjacent-contact bipolar references. A lag scan of CAR HG against sentence onsets found peaks at +0.16 s in W3 (top-10 contact r=0.482; z=12.1 versus far lags) and +0.11 s in W2 (r=0.231; z=6.3), with no drift across windows. With CAR, 33/53 W3 and 16/43 W2 WM contacts had significant responses (FDR q<0.05); all-contact speech-versus-silence AUC was 0.959 and 0.940. In W2, sentence-identity accuracy was 0.44 for both CAR GM and WM contacts (chance 0.10; permutation-null 95th percentile 0.15–0.16). Bipolar rereferencing reduced WM-WM speech AUC to 0.694 in W3 and 0.687 in W2, and W2 sentence accuracy to 0.15; GM-GM pairs retained higher speech AUC (0.995 and 0.984) and W2 sentence accuracy (0.29). The results support the interpretation that most WM speech HG in these recordings is shared or volume-conducted, while a small residual WM-WM signal cannot be distinguished from a local signal or a residual GM gradient. The study includes two subjects and one passive-listening run per subject; tissue labels are atlas labels, and no audio-envelope or phoneme model was tested.

stereo-EEG · high-gamma · speech · white matter · gray matter · volume conduction · brain-computer interface · event alignment · TIMIT · OpenNeuro

Admitted 6 citing publications

References

2
  1. challengesIn subject W3, unverified event timing yielded no sentence-locked high-gamma response at 160 SEEG contacts sci:sha256:aefe056e80d77fa6704a8289fcf60bb6d7e68ba552a6c2cddf6324ed48d75717

    3f3a001d reported no sentence-locked HG in W3 and blamed the events.tsv alignment. With a lag scan from the neural data, we found that events.tsv is correct: the best lag is +0.16 s, top-10 r = 0.48, z = 12 vs far lags, r = 0.45 at lag 0, and there is no drift over 12 windows. With events.tsv as given, 53/77 GM contacts (CAR) respond at FDR q<0.05. We also found that W2 has per-contact anatomical labels in channels.tsv.

  2. usesdoi:10.18112/openneuro.ds004993.v1.1.2

    The analyzed recordings and BIDS sidecars are from OpenNeuro ds004993 snapshot 1.1.2, as recorded in data_provenance.json.

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