Trial types in an example saccadic or manual standard stop-task, and RT-derived indices.

A. Participants are given the primary task of moving their eyes or pressing a button as fast as possible to indicate the side of a peripheral target (e.g. a white circle). B-C. On a minority of trials, a stop-signal (e.g. a black circle) is presented with a variable delay (stimulus onset asynchrony, SOA) after the target. Participants are instructed to withhold their response, which they sometimes do (B) and sometimes fail to (C). D. Distributions of reaction time on signal-absent trials (RTGo, grey curve) and failed stop-trials (RTStop, black curve). The SSRT is the time delay between the signal onset and the vertical green bar (indicating the RT up to which the area under the RTGo curve equals the area under the entire RTStop curve, i.e. the RT that equalises the two grey-shaded areas). Visuomotor deadtime (T0) is the delay between the signal onset and the blue dot (where the RTStop distribution diverges from the RTGo). In practice though, T0 is estimated on RT locked on signal onset after pooling across all SOAs (see Methods). E. Hypothetical decision mechanism leading to an RT equal to (RT1 blue line) or faster than SOA + T0. The action decision activity triggered by the target has reached the threshold before the signal can interfere with it, i.e. before SOA + V (red dashed line, V = visual transmission delay for target and stop signals). These trials correspond to RTs ≤ SOA + V + M (M = motor execution delay), all unaffected by the signal. F. Trials where the activity is below the threshold by SOA + V are exposed to automatic inhibition from the signal, leading to responses getting delayed (RT2, pink full line) or cancelled (pink dashed line). Note that the above logic is agnostic to the specific profile of the accumulation process or the interference.

Stop signal reaction time correlates with visuomotor deadtime in archival (A) and novel (B) datasets.

Data points correspond to individual estimates from manual (full circles) and saccadic (empty circles) blocks. The continuous lines show the linear regression, within (red) or across (black) datasets, the dashed lines show unity for reference. A. Pooled data across seven datasets: Campbell et al., (2017)23 in black, Bompas et al., (2020)25 experiments 1–3 in magenta, Boucher et al., (2007)24 in blue, Bompas et al., (2025)22 experiment 1 in green (bright and dark green for bright and dim signals) and experiment 2 in red. B. Data from the stop-blocks in the novel experiment. R-values are provided on each panel, with their degrees of freedom within brackets. *** indicates p-values < 0.0001, n.s. indicates a p-value > 0.05 and inconclusive BF10 (between 0.33 and 3).

Trial types in an example saccadic or manual ignore trial, and RT-derived indices.

A. Example ignore trial, interleaved with go and stop trials (see Fig. 1) as part of a selective stopping task. The participant is instructed to respond to the first stimulus and ignore the second one. B. Reaction time distribution on signal-ignore trials (RTIgnore, dark green curve) shows the same initial decrease as failed signal-stop trials (both starting at the blue dot T0) but shows a later rebound. The red dot indicates the RT at which the RTStop and RTIgnore distributions diverge. TS is this RT minus the SOA. In practice though, like T0, TS is estimated on RT locked on signal onset after pooling across all SOAs. The selective stopping delay ΔT is the difference between Ts and T0. See supplementary Fig. 1 for empirical curves.

Temporal indices from the selective stopping task, from two archival datasets (A-B) and the novel data (C-D).

A. Group averages and standard errors from 14 participants in Bompas et al. (2025)22 experiment 2 (see supplementary information Fig. S7A for task description; fast and cautious blocks serve here as internal replication). B. Individual indices (empty circles and thin lines) and group averages (squares and bold line) over the 4 observers from Bompas et al. (2020)25 experiment 3 (see supplementary information Fig. S7B for task description). C-D. Group averages and standard errors for manual and saccadic indices from our novel experiment. Visuomotor deadtime indices (blue) are when the RTIgnore (T0,Ign), RTStop (T0,Stop) or pooled RTIgnore+Stop (T0) distributions first drop below the RTGo distribution. As pre-registered, they do not differ significantly (n.s.). TS is when RTStop first drops below RTIgnore, and, as pre-registered, is significantly higher than T0 (*** p < 0.001). SSRT is the stop-signal reaction time calculated from Stop and Go trials.

Individual indices from the novel experiment.

A. Same conventions as Fig. 2B in main text. B. The red line indicates where x=0. Values falling below this are non-plausible and, because they are small, probably due to noise in T0 and/or TS estimates (estimated independently).

Pearson’s correlations for within-modality and cross-modality variable pairings.

Colour scale reflects the strength of Bayes evidence for the hypothesis against the null (BF10). Asterisks reflect frequentist significance (p-values < 0.05*, < 0.01**, < 0.001***). All measures included are post participant exclusions. BF and p-values for correlations linking SSRT to T0, and SSRT to median RT (A-B) are presented as one-tailed, consistent with the confirmatory and directional nature of the hypotheses (see Methods). All other correlations are 2-tailed.

Main features of each dataset analysed in the current article and their mean values in msec for all indices of interest.

Grey cells indicate non-applicable values. T0,Stop, T0,Ignore and T0 indicate visuomotor deadtime estimated from stop trials only, ignore trials only, or all signal trials. TS is the selective stopping time. ΔT is the selective stopping delay, i.e. the time difference between T0 and TS. Median RT is estimated from separate blocks without stop signals. Novel refers to the preregistered dataset collected in the article, for which full details can be found in the Methods section.

Illustration of example trial sequences when target and ignore signal are white and stop signal is black.

A. Go trial. B. Stop trial. C. Ignore trial. All trial types have a total length of 2000 msec (trial end is 500 msec after the fixation cross is removed).

Additional outcome measures from the novel dataset.

Group average and standard deviation within brackets for each trial type for the novel data, before participant exclusions. Go, Ignore and Stop trials correspond to the three trial types during the selective stop task. Speeded Go are from separate blocks with no signals. Primary accuracy: percentage of all valid responses that were directed to the target (for stop trials, this applies only to failed stop trials).

Number of participants contributing to indices of interest in the novel data after all exclusions.

Reaction time distributions pooled across all participants.

Each index is estimated from RT locked on signal onset, after pooling across the 5 SOAs and 37 participants, separately for the manual (left) and saccadic blocks (right). Same conventions as Fig. 1D and 3B from main paper. Index calculation uses the same algorithm as individual estimates, but without Gaussian smoothing.

Individual outcome measures from the novel selective stop-task.

Red reflects participants who were excluded from SSRT and/or ΔT analyses due to meeting exclusion criteria or with ambiguous T0 or TS. Pale blue are participants included in both SSRT and ΔT analyses (manual N = 35, saccadic N = 24). Bold blue is the group-level means calculated using participants plotted in pale blue.

Individual stopping accuracy across SOAs.

Same conventions as in Fig. 2.

Stop signal reaction time against speeded reaction time for archival (A) and novel data (B).

Median RTs are calculated from no-signal trials in ignore blocks for Campbell et al. (2017) (black circles) and Bompas et al., (2020) experiments 1–3 (magenta), and from go-only blocks for Bompas et al., (2025) experiment 1 (RT to bright and dim stimuli shown as bright and dark green circles) and the novel data. Data points correspond to individuals. The continuous lines show the linear regression, the dashed lines show unity for reference. R-values are provided on each panel, with their degrees of freedom within brackets. * indicates p-values < 0.05 and *** indicates p-values < 0.0001. The grey dotted line indicates the linear regression when manual and saccadic responses are pooled.

Effect of trial number on T0 estimates.

Mean, standard deviation (SD) and standard error (SE) are based on 100 independent bootstrapping of the novel dataset. Each repetition involved subsampling without replacement 250, 100 or 50 stop-signal trials (NPooledTrials/T0) and twice more go trials, and extracting a T0. Trials were obtained from various combinations of number of participants (NPooledParticipants) and number of trials per participant (NTrials/Participant). NPooledParticipants of 1 means data were not pooled across participants. Stop trials were drawn across the 5 SOAs in equal proportion. For instance, each repetition contributing to the left-most values were obtained by randomly selecting 25 participants out of 37, then randomly selecting and pooling 10 stoptrials (2 trials at each SOA) out of 500, and 20 go trials out of 1000 from each selected participant. Analyses were run separately for manual (blue) and saccadic (red) data. Original mean T0 (straight horizontal lines) are the mean over all 37 participants, using all 500 stop-trials and 1000 go trials, serving here as ground truth. Reducing the number of trials available per estimate (NPooledTrials/T0) leads to a clear increase in the mean and variability of these estimates. Different strategies for achieving a given number of trials (combinations of NPooledParticipants and NTrials/Participant) had no visible impact.

Pooling participants is a sound way to obtain enough trials to support RT distributional analyses.

Each panel shows a different index (T0, TS, ΔT and SSRT). Each index on each repetition is estimated from 500 stop, 500 ignore and 1000 go trials, obtained by randomly selecting and pooling NTrials stop, NTrials ignore and 2*NTrials go, from NPooledParticipants. Rightmost values (500 x 1) show the mean, standard error (SE) and standard deviation (SD) across all 37 participants, estimated using all available trials from each participant (same values as presented in the main article). For all other sampling levels (15 x 33 to 250 x 2), mean, SE and SD are based on 100 independent repetitions of randomly selecting trials and participants without replacement (same principle and convention as Fig. 5). T0 and SSRT were extractedfrom stop and go trials only. TS and ΔT were extracted based on all trial types.

Example trials from the two archival selective stopping datasets from main paper Table 1 and Fig. 4.

A. Two examples for each of the three trial types involved in Bompas et al. (2024) experiment 2. Each block used a different triplet of letters (here O, Q and G), with two letters serving as targets (here O and Q), and the third serving as stop-signal (here G). Ignore trials presented the same target letter again at the alternative position, following a delay. Text in brackets shows the instruction associated with each trial type and were not visible to participants. B. Three trial types involved in Bompas et al. (2020) experiment 3. The colour of peripheral targets (black or white small disk) varied across blocks, followed by a signal (larger central disk) on 50% of trials. Ignore signals had the same polarity as the target, stop signals had the opposite polarity.

Lack of correlation between ΔT, SSRT and selective stopping accuracy.

Dashed lines show the identity whilst solid lines are regression lines. Pearson R-values are provided on each panel, with their degrees of freedom within brackets. ϕindicates a p-value > 0.05 and BF10 < 0.33 (evidence for the null). n.s. indicates a p-value > 0.05 and inconclusive BF10 (between 0.33 and 3).