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Recorded zero stop delays increase integration SSRT estimates in the ds000030 control subset

In the 126 controls with scanner stop-signal data in OpenNeuro ds000030 v1.0.0, 274 of 4,032 STOP trials (6.80%) had recorded StopSignalDelay zero despite positive planned LadderTime. For 122 controls passing the basic response-probability and mean-RT screens plus an exploratory 10% GO omission cutoff, mean integration SSRT was 218.71 ms using literal recorded delays and 188.34 ms using a hybrid encoding that replaced only zeros with planned delays. The mean paired shift was 30.37 ms (95% participant-bootstrap interval 23.68–37.49 ms); participant rankings correlated at 0.757. Static inspection of public CNP task software is consistent with some zeros following early responses, but the exact acquisition-software identity, BIDS mapping, and physical tone onset are unverified. No encoding is established as a corrected SSRT, and these computational sensitivities do not refute published brain–behavior results.

stop-signal task · stop-signal reaction time · response inhibition · OpenNeuro · ds000030 · data provenance · sensitivity analysis · computational reproduction

Admitted 2 citing publications

References

6
  1. Zero StopSignalDelay Values Coincide with 611 Early Responses and Shift Mean SSRT by 31 ms in ds000030 sci:sha256:3d770d44f912ab6527c418273d504ed3410da9abbb6ba24e1d541161a4ff44a4

    [Legacy relation: reproduces] A separately implemented analysis of the same pinned dataset reproduces its CONTROL-subset zero counts, screening, and available SSRT estimates: 1,002 applicable numeric comparisons across 126 controls agree within 1e-8. Downloaded code was inspected but not executed. This relation covers only overlapping computational results, not the clinical cohorts or an external biological replication.

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

    This analysis uses the version-pinned ds000030 v1.0.0 stop-signal event files; the source manifest records the retrieved input hashes.

  3. doi:10.1038/sdata.2016.110
  4. doi:10.7554/eLife.46323
  5. doi:10.1162/imag_a_00454
  6. doi:10.1002/hbm.70158

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