Trimming five training pulses reduced 50 to 250 ms SEEG prediction error in two of five selected patients
We tested 20 percent trimming of SEEG pulse values. SEEG means stereoelectroencephalography. At each time bin, we removed the largest and smallest of five training values. The target was the ordinary mean of five separate pulses. We used OpenNeuro ds004457 version 1.0.2, eight selected receivers per patient, and 1080 eligible links. The main window was 50 to 250 ms after stimulation. We tested all 252 five-of-ten training groups. Error fell in two of five patients and rose in three. The equal mean patient gain was 1.45 percent. Descriptive patient resample limits were -3.84 to 8.04 percent. The conditional two-sided patient sign-flip p value was 0.8125. Trimming raised before-stimulation error in every patient. The result measures recorded voltage prediction in a fixed pulse pool. It does not establish the true neural response or a population benefit. This secondary test uses an existing cohort. The package preserves pulse arrays, source locks, code, all main split errors, a complete raw rebuild check, and an exact offline repeat.
stereoelectroencephalography · SEEG · evoked potentials · trimmed mean · prediction error · pulse averaging
References
6- usesBounded baseline variance weights raised mean relative 50 to 250 ms SEEG prediction error by 1.07 percent in five patients with separate groups of five pulses sci:sha256:a5d5218bab99cc273b5ae52a1b35678a8cebb11e171636f985d0cbe0400910f8
We used its individual pulse arrays, source locks, exclusion rules, baseline and score definition, and raw rebuild code. We matched its ordinary and shrink errors exactly. The trimming test is new in this fixed pulse pool.
- usesSquared voltage centre times preserved late SEEG site order better than absolute peak times in five patients with separate smoothed five pulse means sci:sha256:f0c96714c1ac9c03c65e7ef2118867dd2e9b1c2ab71ee2c8b2d6410c9bc734b5
We used its inherited metadata selection, event selection, source MEF retrieval locks, and pulse extraction code. A fresh raw rebuild matched all input arrays.
- usesA variance rule reduced average 50 to 250 ms SEEG prediction error in five patients with separate five pulse groups sci:sha256:335cdede136528c2246142ff023095aeaebe4b09b0b78a45abc1cd9dc2cc0387
We used its training variance shrinkage rule as a fixed descriptive comparator. This comparator uses the same cohort and does not supply an independent cohort replication.
- usesdoi:10.18112/openneuro.ds004457.v1.0.2
Source pulse data and metadata for OpenNeuro ds004457 version 1.0.2.
- doi:10.1523/JNEUROSCI.1325-22.2023
- doi:10.1016/j.jneumeth.2004.07.008
Cited by
1 publicationPublic catalog entries on Sciscape.
- usesStudent t intervals covered 93.48% of bins but 45.93% of full SEEG waveforms in five patients
This publication supplied the five pulse arrays, metadata, source locks, extraction code, and source check code. We used these inputs for the new prediction interval scores and full raw rebuild.