Training for 100 ms data age reduced mean error versus frequency advance for 2 s theta labels in seven SEEG records
A brain-computer interface can receive old voltage data. We tested phase forecasts with an exact, known data age. We used seven public SEEG rest records from OpenNeuro ds006065 version 1.0.0. All methods used the same old 500 ms buffer. The action target was 50 ms after each decision. At 100 ms data age, training for the total delay reduced mean error from 83.10 to 81.51 degrees compared with advance by early theta frequency. The mean gain was 1.59 degrees. Five of seven people improved. The descriptive person bootstrap interval was 0.007 to 3.332 degrees. The exact sign-flip p value was 0.172. The gain was absent with a shorter, 1 s phase label. Only three people improved in all four time blocks. These results give limited support for delay training beyond frequency advance. The labels use future voltage. The data age was simulated in intact voltage. The cohort was reused. No online system or stimulation effect was tested. The package contains input traces, source versions and hashes, code, models, all forecasts, figures, and checks. Fresh source extraction and a complete analysis replay matched the archived files.
theta phase forecasting · SEEG · brain-computer interface · data age · signal processing · ridge regression · offline phase reference
References
3- usesA learned linear filter reduced mean 50 ms offline theta phase error by 12.54 degrees in seven SEEG rest recordings sci:sha256:681793db790925fefcdd246f20a125cf7ec0a4d0c7ac415b89cd84c8e64b5d35
This study uses its seven longer rest input files, fixed early pair selection, peak frequencies, phase reference, and ridge helper code. The zero-age model and scores reproduce that study. The new comparison tests known input age with the same old buffer and a fixed future action target.
- usesdoi:10.18112/openneuro.ds006065.v1.0.0
The study analyzed seven rest recordings from this exact OpenNeuro release; the source manifest and full-file hashes identify the downloaded inputs.
- doi:10.1038/s41467-025-59417-7
Cited by
1 publicationPublic catalog entries on Sciscape.
- usesTraining for known 100 ms data age reduced mean phase error by 1.10 degrees compared with frequency advance for 2 s theta labels in two SEEG rest records
Used its question about known data age, its three forecast rules, its early fitting procedure, and its code. Tested the procedure in two rest records from a different public dataset. The report states the changes in native sample rate and later test duration. The package preserves the original code and its hashes.