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A shared scale in a Student t model with four degrees of freedom raised mean 4–30 Hz SEEG joint forecast loss at 100–500 ms after five fit pulses at 82 sites in eight sessions

One shared random variance scale raised mean joint forecast loss for log power in 4 to 30 Hz at 100 to 500 ms after stimulation. The test used public SEEG data from eight people with epilepsy. At 82 sites, five early pulses fitted each forecast and 546 later pulses supplied the test data. The shared and separate scale models had the same univariate Student t distributions with four degrees of freedom. Their only difference was the joint density. The shared model raised mean loss by 0.02033 nats per shaft. The descriptive 95% person bootstrap interval for the increase was 0.00636 to 0.03547. Six of eight people had higher loss. Tests with two and thirty degrees of freedom reduced the cost and gave intervals that included zero. Pulse order controls did not show a clear departure for the main endpoint. The result is specific to the tested model and selected sessions. It does not establish independent neural responses or a clinical effect. The package preserves compact data, native voltage examples, source versions and hashes, code, fits, each pulse score, figures, and replay instructions.

joint forecast · Student t distribution · SEEG · stimulation · log power · predictive score

Admitted 1 citing publication

References

7
  1. usesA fixed model gave no clear 4–30 Hz power forecast gain from input ending 20 ms versus 500 ms before a pulse for targets at 100–500 ms after the pulse in eight SEEG sessions sci:sha256:7def033d65e62e11ff56502733ae76b99a84f7764072fd1b8d669d98536e3b22

    This work uses its complete good-pulse band powers, native voltage examples, fixed eligible contacts, source metadata, fixed source object versions and hashes, and extraction code. These inputs support a new comparison of joint Student t forecasts.

  2. usesResponse correlations gave no clear loss reduction with five fit pulses and 50% shrink at 83 SEEG sites in eight sessions sci:sha256:0bef106b1ca9c41fac09e6a5802d56ecb71132bf5c518aba74fbeecbb337ddd0

    Its metadata rule selects one eligible pair per remote shaft. Its joint Gaussian comparison supplies context for a new test of dependence through a shared random variance scale, with identical univariate Student t forecasts.

  3. usesStudent t forecasts reduced later log size loss after five fit pulses at 83 SEEG sites in eight people sci:sha256:11631e0e18f56ce0cdb8483f39c475dd71e1f1d28c64eef54f0cbe52aa374f89

    Its five-pulse Student t forecast motivates the fixed univariate mean, predictive shape, and degrees of freedom. The new test holds those margins fixed and compares joint densities. It uses band power and all later pulses rather than the earlier voltage size endpoint and final-five test set.

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

    The analysis uses processed SEEG trial arrays and metadata from OpenNeuro ds004696 version 1.0.1.

  5. supportsdoi:10.1523/JNEUROSCI.2201-22.2023

    This source study describes collection of the SEEG stimulation data and the limbic responses analyzed here.

  6. doi:10.1111/j.1751-5823.2005.tb00254.x

    Background on dependence in the tails of Student t distributions.

  7. supportsdoi:10.1198/016214506000001437

    This paper supports the use of logarithmic scoring rules to evaluate forecast densities.

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