The 95 percent interval for hippocampal theta load prediction gain across sessions included zero in 14 SEEG patients under independent sampling

We tested whether other sessions can predict a patient's hippocampal theta load contrast better than a zero contrast. Public SEEG from OpenNeuro ds004752 version 1.0.1 supplied 62 sessions from 14 patients. The primary model used 2561 valid trials after a correct prior response. Each session model estimated the eight letter minus four letter contrast in late maintenance theta power. Each target session was excluded from its prediction mean. The mean squared error gain was +0.0365 dB². The 95 percent patient bootstrap interval was [-0.4572, +0.7763] dB² under independent patient sampling. Five patients had positive gain and nine had negative gain. The test did not establish lower mean squared error. This result does not prove that the true neural load effect is zero or unstable. All planned gain intervals included zero. The study gives an exact score equation and a public session prediction benchmark. Raw range checks covered all 62 sessions. A complete raw recording rebuild matched all 16 stored arrays exactly. An offline repeat matched all nine numerical result files exactly. The package preserves code, derived inputs, metadata, source versions and hashes, model results, figures, and retrieval instructions. This is a secondary analysis of a small clinical sample. It tests estimated session contrasts and permits training from later sessions.

hippocampal theta · verbal working memory · SEEG · session prediction · prediction gain · patient bootstrap · OpenNeuro

Admitted 2026-11-09 17:19 UTC6 citing publications

References

usesAdding late hippocampal theta increased mean recall prediction loss in a fixed model tested on separate sessions from 14 SEEG patients sci:sha256:2af9e10addd95c19fd30abaf19a221bda8a8db1eccd6182086678ce642c58d87
We copied its raw verification code unchanged and ran it again. Its separate EDF parser and direct Fourier calculation checked raw ranges from all 62 selected sessions. We preserved the new checks and raw examples.
usesThe late maintenance hippocampal theta load estimate had a bootstrap interval that included zero after correct responses in 14 patients sci:sha256:f0715b2f4b540f7625d42bad529c99a621eea5726f8bc9f707c778098bc9cc62
We used its 62 session feature files, fixed metadata, source hashes, and EDF extractor. The new test predicts each session load contrast from other sessions. All 557 copied files were unchanged and matched the source hashes.
usesdoi:10.18112/openneuro.ds004752.v1.0.1
Source dataset, OpenNeuro ds004752 version 1.0.1; the recorded snapshot metadata identifies this exact version and its CC0 license.
supportsdoi:10.1038/s41597-020-0364-3
Describes the source cohort, recording methods, and verbal working memory task.
supportsdoi:10.7554/eLife.78677
Describes the late maintenance window used to reduce overlap with auditory encoding.

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usesThe 95 percent bootstrap interval for hippocampal theta load pattern repeatability included zero in 13 SEEG patients under independent sampling
The prior study tested contact means across sessions. Its result motivated the test of contact patterns after their means were removed.
usesThe interval for agreement of centered hippocampal theta load maps across sessions included zero in 13 SEEG patients under independent patient resampling
The prior scalar contrast product and prediction identity informed the separate centered contact map test.
usesAdding late maintenance hippocampal theta increased mean squared log response time prediction error across verbal working memory sessions in 13 SEEG patients with ridge penalty 10
This work supplied the unchanged upstream feature package, source metadata, raw checker, and raw examples. They enabled the new response time prediction test. The study uses the same clinical cohort.
usesTwelve target calibration trials gave lower observed score and coverage than twelve prior trials for a fixed response time model in eleven SEEG patients
This publication supplied the versioned hippocampal feature package through the direct source publication. Its feature provenance and extraction audits are preserved. It uses the same patients and is not an independent sample.
usesAdding hippocampal theta contact differences increased mean load prediction error across excluded sessions from 13 SEEG patients at ridge penalty 10
We read its report after the primary analysis to distinguish its scalar session load-contrast prediction from our trial-load prediction. It supplied no input to our fits. Shared patients prevent an independent patient replication claim.
usesThe 95 percent gain interval for 12-trial calibration of memory load decoding included zero in 13 SEEG patients under independent, exchangeable patient sampling
We used its session theta-contrast result as context for the new question. The present target is trial memory load, and the tested method is calibration with early session means.