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Intracranial high-gamma activity showed weak, non-significant error decoding before confidence reports in five patients

We tested whether intracranial 70–150 Hz high-gamma activity (HGA), measured before a confidence scale appeared, distinguished error from correct trials and added information to confidence or behavior. Using the authors’ HGA derivatives from OpenNeuro ds006253, we analyzed five of 22 patients with a within-patient shrinkage LDA and repeated stratified five-fold cross-validation. Patients were selected by file size because the full HGA set was about 17 GB; the other 17 patients were not analyzed. Median error-decoding AUC was 0.576. Four of five patients had AUC above 0.5, but none was significant in patient-level permutation tests; the group sign-flip test gave p = 0.094. Adding HGA changed mean AUC by +0.0004 for confidence (p = 0.469) and −0.004 for behavior (p = 0.875); neither result supported added error information. Confidence carried more error information than HGA (mean HGA-minus-confidence AUC = −0.096; two-sided p = 0.063). The left/right choice control was above chance in all five patients (median AUC 0.542; p = 0.031), with a small effect. These offline results indicate low sensitivity for the sampled electrodes and linear features. They do not show that the brain lacks an error signal: electrode coverage varied, channels were not selected by anatomy, only five patients were analyzed, and there was no closed-loop test. The analysis used 100 permutations per patient, and exploratory time courses were not corrected for multiple comparisons.

intracranial EEG · high-gamma activity · error decoding · confidence · decision-making · SEEG · linear discriminant analysis · AUC

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References

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  1. usesOnly 10 of 34 audited OpenNeuro iEEG datasets had SEEG-typed channels; only two had SEEG in almost all subjects sci:sha256:acebaa9155a622379563f108b3dd9bd3621f3e2dfd2ead35cba6f376dd0b4ec4

    This audit identified ds006253 as an OpenNeuro dataset with SEEG in almost all subjects and no sci publication. We selected the dataset because of it.

  2. doi:10.1101/2024.03.23.586414

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