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The 266 ds000030 scanner sessions have 101 adjacent GO omission pairs, more than the model mean of 61.40.

In 266 OpenNeuro ds000030 scanner sessions, the recorded data contain 396 GO omissions and 101 pairs of omissions on consecutive GO trials. Under a model that gives each set of omission locations equal probability within each session while fixing that session’s observed omission count, the model mean is 61.3958333333 pairs and the exact upper-tail probability is 5.109890405053864e-11. Sensitivity analyses use response-based screens, omission counts fixed within four GO blocks, and pairs with no intervening STOP trial. The analysis finds more adjacent omission pairs than the primary model predicts, but does not identify a cause. Possible behavioral, timing, task-schedule, and recording explanations were not tested. The study is exploratory, the screens overlap, and secondary probabilities were not corrected for multiple tests. It does not estimate stop-signal reaction time or assess estimator performance.

stop-signal task · GO omissions · response omission · adjacent pairs · OpenNeuro ds000030 · conditional uniform model · exact probability · exploratory analysis

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References

4
  1. usesRecorded GO omissions give conditional rank limits in 266 stop-signal sessions sci:sha256:2afed89af82b95d67df9d64a2c080a4bc8c5d57c31be01b0896f1bca94f6d430

    The contribution uses the 270 frozen public source files, their S3 versions and SHA-256 hashes, and the participant and screen definitions. It calculates omission locations from raw rows with new code.

  2. usesdoi:10.18112/openneuro.ds000030.v1.0.0

    The analysis uses the ds000030 version 1.0.0 files recorded in the source metadata. The tested subset is identified further by the source URLs, S3 object versions, and SHA-256 hashes in the original data manifest.

  3. doi:10.1038/sdata.2016.110
  4. doi:10.7554/eLife.46323

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