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q-bio.NC · Neurons and Cognition

Donor response covariance gave higher mean 16-mode SEEG forecast scores than background covariance at 86 selected sites in eight people

We tested covariance for forecasts of stimulation responses in public SEEG from eight people. The test kept 86 selected sites from OpenNeuro ds004696 version 1.0.1. Five early pulses fitted each local mean and scale. The test used 610 later pulses. Covariance came from five early pulses per site in the other seven people. The main model used 16 cosine modes over 20 to 500 ms. Mean negative log density per mode was 1.2253 for response covariance and 1.2206 for background covariance. Lower scores are better. Response covariance was worse in six people. The mean difference was +0.0047 natural log units. Descriptive person resampling limits were -0.0105 to +0.0314, with donor fits repeated. The result changed sign in a fixed 32-mode test. Response variances alone beat full response covariance on average. The package preserves voltage, fitted models, all scores, two figures, source checks, and repeat instructions. This reused cohort does not establish a general advantage or live BCI benefit.

SEEG · electrical stimulation · covariance · forecasting · brain-computer interface · stereoelectroencephalography

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References

6
  1. usesFive calibration pulses gave mean later signed template AUC of 0.939 compared with 0.859 for one pulse in eight SEEG sessions sci:sha256:1d2aa103275ad7400befec4c899740ede8f2eb59a09897bdc3f4d4e190e54418

    Keeps its first-five-pulse readout selection through the direct input. These choices define the scope of 86 selected stimulation sites.

  2. usesDonor covariance raised mean 16-mode SEEG response AUC after five local fit pulses at 86 selected sites in eight patients sci:sha256:6c4cced9dadb0e1e3eda59b7313983bcc2e732c773a7d1d9a0363f14681fece4

    Uses its common cosine space and trace-normalized donor background model as method guides. The earlier endpoint was response ranking. The present endpoint is forecast density.

  3. usesFive early response pulses gave lower mean error for later 20–500 ms sample variance in SEEG from eight people sci:sha256:bd13b330f15606f39be54c5b06b3b81bf3b6fb8af05625f53e1f1a696e45c154

    Uses its variance forecast result to choose local response variance as the common scale control. The covariance shape, selected readouts, and later-pulse endpoint differ.

  4. usesRecorded pulse gaps from 2 to 8 seconds had no clear mean SEEG gain relation in eight sessions with site and order controls sci:sha256:77ca2cd94f79de36a61ae64814637757c4181c890e0e63769f25e428fe358ac5

    Uses its exact voltage windows for 1,042 stored pulses, event maps, source pins, and retrieval code. The test keeps its 86 fixed readouts and adds a covariance forecast score.

  5. usesdoi:10.18112/openneuro.ds004696.v1.0.1

    The analysis uses processed voltage derivatives from OpenNeuro ds004696 version 1.0.1; source commits, URLs, and file hashes are preserved.

  6. doi:10.1523/JNEUROSCI.2201-22.2023

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