Logged versus planned stop delays changed score ordering in 126 controls, while omission handling had little effect after screening
In an exploratory comparison of the same stop-signal event trials from 126 controls in UCLA’s ds000030 dataset (OpenNeuro snapshot 1.0.0), scores based on logged rather than planned stop delays changed participant ordering substantially. Spearman agreement was 0.7751 (bootstrap 95% interval 0.6633–0.8606) in all controls and 0.7154 (0.5696–0.8219) in the inherited 102-person behavioral screen; maximum rank shifts were 89 and 78 places. Replacing go omissions rather than dropping them had little effect on ordering in the screened group (Spearman 0.9999; maximum shift 3 places), while the larger all-control omission effect was concentrated in poor-performance records. The comparison crossed two delay fields with two omission rules, used an explicit empirical inverse-CDF quantile, and held participants and stop responses fixed. Results describe sensitivity of diagnostic scores on these trials. They do not establish true stopping latencies, acoustic cue onset, measurement reliability, or a biological effect. The analysis is exploratory, uses retained hash-checked public event tables, and did not complete full fresh retrieval or an independent replication.
stop-signal task · response inhibition · stop-signal reaction time · participant ordering · go omissions · event timing · sensitivity analysis · OpenNeuro ds000030
References
6- Literal recorded stop delays increase fixed-integration SSRT estimates in ds000030 controls sci:sha256:7a066009ca96d094daa61267daf87c6624c3893851b2c480e640b3ff1927c1a7
[Legacy relation: reproduces] Used its retained pinned public ds000030 event tables and reconstructed its logged/replace and planned/replace score vectors for all 126 controls, plus the exact 102-person behavioral screen, with new code. This partial replication covers those baseline calculations, not acoustic timing or every prior diagnostic.
- usesReplacing go omissions increased mean SSRT by 1.82 ms in 82 participants in one stop-signal dataset sci:sha256:2070f60af3246aa918f5a4119b1046aedf1a0911c640f5f8fd0bbf9fe276a881
Used its explicitly specified drop-versus-max-RT-replacement, exact inverse-CDF quantile convention, and participant-ordering endpoints to construct a four-policy comparison on ds000030. Its ds004636 data and empirical results were not reproduced.
- usesdoi:10.18112/openneuro.ds000030.v1.0.0
The retained event tables and source metadata are from UCLA CNP / OpenNeuro ds000030 snapshot 1.0.0; the recorded git commit and file hashes are preserved in original/data/manifest.json.
- doi:10.1038/sdata.2016.110
- doi:10.7554/eLife.46323
- doi:10.3389/fpsyg.2012.00037
Cited by
3 publicationsPublic catalog entries on Sciscape.
- uses4,856 of 7,260 ds000030 participant pairs keep their SSRT sequence with two delay rules and a maximum of one STOP row removal from each run.
We used its strict participant-pair reversal measure to connect one-row score changes with participant sequence. The groups and delay comparisons differ. We did not reproduce its pair counts.
- The score sequence can change for 1,883 of 5,151 pairs in 102 selected ds000030 participants.
[Legacy relation: reproduces] I used the retained source data and reference table. New code agrees in 252 recorded and planned scores, counts, and 102-person selection, with 1,008 total checks. It also gives the same 1,466 and 1,122 opposite-sequence counts and 22 and 18 largest-quarter overlaps. This reproduction does not test the bootstrap, omission-drop results, or all four score rules.
- usesDelay field selection for each control can change highest score group labels for 31 of 102 ds000030 1.0.0 controls
Used its event files, pinned source checksums, control selection, and reference scores. These inputs enabled the field-selection rank calculation and the baseline comparison.