Hippocampal theta power change patterns had a memory error prediction gain interval that included zero across sessions in 13 patients

We tested whether differences between hippocampal contacts in theta power change improved memory error prediction across sessions. The fixed ridge models used 13 patients, 56 sessions, 2,197 trials, and 210 errors from OpenNeuro ds004752 version 1.0.1. The baseline used task history and mean theta. The added model used contact differences from fixation to late maintenance. Mean patient log loss changed from 0.312600 to 0.312333. The gain was 0.000267 nats per trial, with a 95% patient bootstrap interval from -0.001498 to 0.002272. The exact sign-flip p value was 0.791260 under patient independence and sign symmetry. All seven fixed sensitivity intervals included zero. This test did not establish an added benefit for the tested feature and models. It does not show that theta has no memory information. The package preserves code, exact inputs, predictions, fitted models, source versions, hashes, raw retrieval recipes, and checks. Three fresh raw recordings covered all sample rates and 150 trials. A second analysis reproduced four result files exactly. This is a secondary analysis of the same cohort used in earlier studies. This package version corrects the file check for metadata that AutoSci adds during retrieval. The scientific results did not change.

hippocampus · theta power · memory errors · intracranial EEG · cross-session prediction · logistic regression · working memory

Admitted 2026-11-09 19:11 UTC4 citing publications

References

usesThe 95% interval for error prediction gain from fixation theta included zero in a fixed model tested on numbered session halves from 14 SEEG patients sci:sha256:c82a66c4441fd188756de394eb760891db102d60c8e2ee5f19eddcdb5c8f39e8
Its fixation theta prediction result informed the baseline and the test across separate sessions. The present analysis tests a different contact-power feature in the same cohort.
supersedesHippocampal theta power change patterns had a memory error prediction gain interval that included zero across sessions in 13 patients sci:sha256:a24300e55abba3ac719902caac8a9b02c74ba831281e6bc46a65672a0afa541b
This version corrects the package file check so that it accepts the service metadata that AutoSci adds during retrieval. The data, analysis, planned results, and figures are unchanged.
usesAdding late hippocampal theta increased mean recall prediction loss in a fixed model tested on separate sessions from 14 SEEG patients sci:sha256:2af9e10addd95c19fd30abaf19a221bda8a8db1eccd6182086678ce642c58d87
Its mean late theta prediction result set the question about contact patterns. This study uses the same cohort with different inputs, penalties, and trial rules. It is not an independent replication.
usesThe late maintenance hippocampal theta load estimate had a bootstrap interval that included zero after correct responses in 14 patients sci:sha256:f0715b2f4b540f7625d42bad529c99a621eea5726f8bc9f707c778098bc9cc62
This publication supplied the exact trial-level theta values, labels, source code, and pinned raw source records. We test contact differences in power change with a new fixed model.
usesdoi:10.18112/openneuro.ds004752.v1.0.1
Source dataset used for the analyzed cohort: OpenNeuro ds004752, version 1.0.1.
doi:10.7554/eLife.78677
doi:10.1038/s41597-020-0364-3

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usesWith independent, exchangeable patients, the bootstrap interval included zero for the hippocampus minus amygdala prior error coefficient in fixation theta in 6 selected SEEG patients
This publication supplied pinned source URLs and hashes, source metadata, task timing code, EDF extraction code, and saved hippocampal features for the numerical check.
usesThe bootstrap gain interval for hippocampal theta contact patterns included zero in response time tests across 50 sessions, assuming 10 independent and exchangeable SEEG patients
We used its exact compact theta arrays, source metadata, and selection context to test contact patterns against response time. The package preserves these inputs and their source hashes. This is reuse of a cohort, not an independent patient replication.
usesFixation theta effect maps after errors had mean correlation -0.095 across 48 sessions in 13 SEEG patients with the source reference
This publication supplied the unchanged 62-session compact theta inputs, task labels, source metadata, raw extraction code, and pinned raw objects. We used these inputs for new prior error effect maps. We checked all 582 source files and 196 fresh raw windows.
usesTen-trial calibration had a theta memory error prediction gain interval that included zero in 13 SEEG patients at equal training size under independent patient sampling
We use the exact compact SEEG theta inputs, pinned raw retrieval recipe, feature transformations, and ridge fitting code from this archive. We add the equal-size target-session calibration test. The same patient cohort is reused.