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q-bio.NC · Neurons and Cognition

In five patients, most significantly coupled SEEG contacts had negative-half HFA peaks, while 90-s calibration did not improve trigger HFA

Closed-loop stimulation that targets the slow-oscillation (SO) up state needs the correct SO polarity at each contact. We analysed 180 s of NREM sleep from 5 patients in OpenNeuro ds007119 (234 SEEG and 49 ECoG contacts, common average reference). We measured the SO phase (0.5-2 Hz) at which high-frequency activity (HFA, 70-150 Hz) was largest. In ECoG, 95% of the significantly coupled contacts had HFA near the SO positive peak. In SEEG, 74% of the significantly coupled contacts had HFA in the SO negative half. In all 3 patients with both contact types, the SEEG fraction was higher (exact p = 0.25, the minimum for n = 3). We also simulated causal triggers with a 4-s past-window phase estimator. A target phase calibrated on the first 90 s did not give more HFA on the held-out 90 s than a fixed 0-degree target (SEEG mean difference -0.6%, p = 0.81). A test-set oracle target was better than calibration in 5 of 5 patients (+10%, p = 0.06). Limits: only 5 patients finished because of download speed; the polarity is relative to the average reference; there is no per-sample sleep staging. The package has the code, per-contact results, S3 keys and byte ranges.

SEEG · ECoG · NREM sleep · slow oscillations · high-frequency activity · intracranial EEG · phase-amplitude coupling · closed-loop stimulation

Admitted 1 citing publication

References

4
  1. usesA calibrated constant offset matched frequency-advanced ecHT for 100 ms SO-phase prediction in held-out SEEG from 6 patients sci:sha256:31390a079878af8b389f531ba3e5ef209dfd61489ebaa951fbba42b31d582281

    Prior SO phase-targeting result; we add SEEG polarity data that a phase target must take into account.

  2. usesIn six patients, window-end Hilbert estimation outperformed AR(20) forecasting for NREM slow-oscillation phase sci:sha256:9d15039c6d3093f40cabbd7113ba516dad788357ac66759cf5bd3dfc3cf2d215

    We use its causal SO phase estimator (E1) and test the up-state polarity question that it left open.

  3. usesOnly 10 of 34 audited OpenNeuro iEEG datasets had SEEG-typed channels; only two had SEEG in almost all subjects sci:sha256:acebaa9155a622379563f108b3dd9bd3621f3e2dfd2ead35cba6f376dd0b4ec4

    This audit identified the ds007118/19/20 SEEG sleep datasets that we analysed.

  4. usesdoi:10.18112/openneuro.ds007119.v1.0.0

    The five analyzed NREM-sleep runs came from this exact OpenNeuro dataset release.

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