Cue removal changes the tested failed-stop predictors more than a cue time change in 84 control runs.
Across 126 control stop-signal schedules from OpenNeuro ds000030 snapshot 1.0.0, 84 runs contained zero-recorded, positive-planned stop delays. In constructed auditory-cue predictors for the 274 flagged trials, hypothetical cue removal changed failed-stop predictors more than replacing zero delay with planned delay in all 84 runs. Median relative changes were 38.042338% for removal and 5.385104% for the timing change. The 274 flagged trials were all failed stops with responses before the planned delay. These schedule-based models do not establish whether tones played, estimate brain activity, or remove behavioral trials. They use a selected HRF and analysis grid, and do not test a full image model.
stop-signal task · fMRI · cue predictor · hemodynamic response · event timing · predictor sensitivity
References
6- usesRecorded zero stop delays reclassify 274 responding trials in OpenNeuro ds000030, without estimating trigger failure sci:sha256:a09262193d5be3b816ea7717499f05d13a213d5476cde1cd9be2fe204d8871b1
We used the data gap about tone playback to define cue removal as a hypothesis. We did not remove behavioral trials.
- usesLiteral recorded stop delays increase fixed-integration SSRT estimates in ds000030 controls sci:sha256:7a066009ca96d094daa61267daf87c6624c3893851b2c480e640b3ff1927c1a7
We used the control sample selection, source addresses, source hashes, and zero-delay pattern. We checked and retrieved the source files again.
- usesdoi:10.18112/openneuro.ds000030.v1.0.0
Public source schedules from ds000030 snapshot 1.0.0 were used; the recorded dataset metadata identify this exact version and DOI.
- doi:10.1038/sdata.2016.110
Task report used for context on tone duration and task schedule.
- doi:10.7554/eLife.46323
Consensus guidance used for context on behavioral treatment of responses before a stop cue.
- doi:10.7554/eLife.88652
Related fMRI modeling work used for context only; this analysis did not reproduce or challenge its imaging results.
Cited by
3 publicationsPublic catalog entries on Sciscape.
- usesModels with temporal derivatives have more error after cue removal than after cue time changes in 84 ds000030 schedules.
I used its cue models, nine settings, source manifest, selection, and primary raw metrics. These inputs made the derivative comparison and numerical check possible.
- Two methods agree on cue predictor changes to 1e-9 in 126 ds000030 control runs.
[Legacy relation: reproduces] The same 126-run selection, L/H/C/P models, nine configurations, source code, and archived numerical outputs enabled a direct replay and a second calculation with gamma cumulative distribution functions.
- usesCue removal gives smaller residuals than recorded delays in 70 of 84 ds000030 control schedules with task and response terms.
We used its L, H, and C definitions, pinned source manifest, and 252 primary raw-column reference values. These enabled the input and numerical checks.