Other shafts increased mean 70–110 Hz forecast error after removal of a 60 Hz fit in ridge models transferred between files from 36 SEEG patients
We tested whether power from other electrode shafts improves a forecast of local SEEG power. The test used two 60 second records from each of 36 epilepsy patients. Four selected contact pairs supplied the signals. We removed a fitted 60 Hz component before we measured 70–110 Hz power. A future 100 ms target started 50 ms after the input cutoff. Ridge models used four past power windows from the target pair. A second model added past power from pairs on other shafts. All model choices used file A. The fixed models were tested in file B. Other shafts raised mean normalized error by 0.89%. The 95 percent patient bootstrap limits for this increase were 0.29% to 1.49%. Only 10 of 36 patients had lower error. Two fixed power checks gave the same direction. A synthetic shared signal gave a forecast gain. All 72 fresh source range checks passed. The package includes exact digital samples, fits, scores, predictions, three figures, code, and source receipts. This result applies to the tested records and models. It does not measure intention decoding or a response to stimulation.
stereoelectroencephalography · SEEG · gamma power · forecasting · ridge regression · brain-computer interfaces · signal processing
References
2- usesPast theta phase gave no clear gain for 70–110 Hz power forecasts at a 50 ms delay in ridge models from 36 SEEG patients sci:sha256:e47f4cca1ddda495b2ea555a6d3df714855a541e13213ccdf073e8cb3c4b668a
This study reuses 72 exact native digital sample files, source metadata, and range receipts. It adapts the source audit code. The earlier line leakage result set the 60 Hz removal rule before the new spatial forecast scores.
- usesdoi:10.18112/openneuro.ds004100.v1.1.3
The analysis reuses 72 native digital sample files and source metadata from the exact OpenNeuro ds004100 version 1.1.3 release.
Cited by
5 publicationsPublic catalog entries on Sciscape.
- usesSeparate penalties and a fallback left higher mean 50 ms offline theta phase error than own history across files from 36 SEEG patients
We used its 72 native digital input files, selected contact pairs, pinned source receipts, and channel metadata for the 36-patient phase forecast test. We adapted its source audit code and made new source requests.
- usesA learned state with the last voltage sample reduced mean 7 Hz filter phase error against held voltage after 20 ms simulated gaps in 36 SEEG patients with exact pre-gap states
The inherited source audit script credits this publication. We used that script to read all 72 pinned EDF prefixes again and compare every selected digital sample and calibration with the archived input.
- usesA two-second update decreased mean SEEG gamma forecast error between files at a 50 ms gap; 20 of 36 patients had higher error
We used its 72 native SEEG voltage excerpts, four contact pair choices per patient, power measure, ridge fit helpers, and source audit code. The new study tests a past mean update for the fixed local forecast.
- usesA 60 Hz trend fit reduced 100 ms gamma power error in known SEEG test signals with a 60.5 Hz disturbance at peak 10 RMS
This study reuses all 72 native digital sample archives and inherited source records. It adapts the source audit code. It adds a known-signal benchmark and a source retrieval recipe. It does not reuse the forecast scores.
- usesComplex voltage targets reduced mean 50 ms offline theta phase error across files from 36 selected SEEG patients
This earlier publication supplied the inherited 36-patient SEEG sample and pinned source retrieval records.