To control their actions (for reviews, see e.g. Aron, 2011; Braver, 2012). For example, subjects can `OxaliplatinMedChemExpress Oxaliplatin proactively’ adjust attentional and responseselection parameters in the go task to enhance stop-signal detection and slow down responding (e.g. Aron, 2011; Verbruggen Logan, 2009b; Verbruggen, Stevens, et al.,Cognition. Author manuscript; available in PMC 2016 April 08.Author Manuscript Author Manuscript Author Manuscript Author ManuscriptVerbruggen and LoganPage2014). Furthermore, task prioritization or task bias can be a top-down strategic decision (e.g. Logan Gordon, 2001; Miller et al., 2009). For example, it may be advantageous to prioritize the stop process (and allocate more processing capacity to it) when signals are likely to be valid (see Bissett Logan, 2014). 3.5. Implications and practical guidelines for stop-signal users In the present study, we found strong dependence MG-132 site between stopping and going in selective stopping tasks, and we have argued that capacity sharing may also occur in stop-signal tasks. In other words, the present study and other recent work indicates that going and stopping tend to interact when stopping is no longer a `simple’ prepared reflex. Consequently, the independence assumptions of the independent race model will be violated. As discussed in the Introduction, the assumptions should not be taken lightly because SSRT cannot be reliably estimated when they are violated. Therefore, we propose that every stop-signal study that uses the tracking procedure and estimates SSRT should: 1. 2. 3. Report average signal espond RT, and confirm that it is statistically different from average no-signal RT for each experimental condition. Determine whether differences between conditions indicate various degrees of capacity sharing. Confirm that signal espond RT is shorter than no-signal RT for every subject for whom SSRT is estimated. SSRT should not be estimated for subjects with signal?respond RTs longer than no-signal RTs. The number of subjects excluded from the SSRT analysis should be mentioned.Author Manuscript Author Manuscript Author Manuscript Author ManuscriptThese first three guidelines focus on testing the independence assumptions. In addition, stopsignal users should always report: 1. 2. 3. The probability of responding on signal trials for each condition The average stop-signal delay for each condition Use an appropriate method, like the integration method, to estimate SSRT (Verbruggen et al., 2013).A final note concerns the interpretation of the SSRT. SSRT measures the time it takes to stop a response. However, it is important to realize that SSRT is a global concept that describes the chain of processes involved in an act of control that results in a response being withheld (Verbruggen, McLaren, et al., 2014). More specifically, SSRT captures the duration of perceptual, decisional, and (inhibitory) motor-related processes. For example, previous behavioral studies and computational work have highlighted the role of perceptual processes (see above). Our study shows that successfully stopping also depends on decisional processes, such as response selection and memory retrieval (see also e.g. Logan et al., 2014; van de Laar, van den Wildenberg, van Boxtel, van der Molen, 2010). Finally, when the decision to stop is reached, motor output or other ongoing processing has to be suppressed (e.g. via a fronto-basal-ganglia network). Thus, in simple stop-signal tasks and their many variants, SSRT reflects.To control their actions (for reviews, see e.g. Aron, 2011; Braver, 2012). For example, subjects can `proactively’ adjust attentional and responseselection parameters in the go task to enhance stop-signal detection and slow down responding (e.g. Aron, 2011; Verbruggen Logan, 2009b; Verbruggen, Stevens, et al.,Cognition. Author manuscript; available in PMC 2016 April 08.Author Manuscript Author Manuscript Author Manuscript Author ManuscriptVerbruggen and LoganPage2014). Furthermore, task prioritization or task bias can be a top-down strategic decision (e.g. Logan Gordon, 2001; Miller et al., 2009). For example, it may be advantageous to prioritize the stop process (and allocate more processing capacity to it) when signals are likely to be valid (see Bissett Logan, 2014). 3.5. Implications and practical guidelines for stop-signal users In the present study, we found strong dependence between stopping and going in selective stopping tasks, and we have argued that capacity sharing may also occur in stop-signal tasks. In other words, the present study and other recent work indicates that going and stopping tend to interact when stopping is no longer a `simple’ prepared reflex. Consequently, the independence assumptions of the independent race model will be violated. As discussed in the Introduction, the assumptions should not be taken lightly because SSRT cannot be reliably estimated when they are violated. Therefore, we propose that every stop-signal study that uses the tracking procedure and estimates SSRT should: 1. 2. 3. Report average signal espond RT, and confirm that it is statistically different from average no-signal RT for each experimental condition. Determine whether differences between conditions indicate various degrees of capacity sharing. Confirm that signal espond RT is shorter than no-signal RT for every subject for whom SSRT is estimated. SSRT should not be estimated for subjects with signal?respond RTs longer than no-signal RTs. The number of subjects excluded from the SSRT analysis should be mentioned.Author Manuscript Author Manuscript Author Manuscript Author ManuscriptThese first three guidelines focus on testing the independence assumptions. In addition, stopsignal users should always report: 1. 2. 3. The probability of responding on signal trials for each condition The average stop-signal delay for each condition Use an appropriate method, like the integration method, to estimate SSRT (Verbruggen et al., 2013).A final note concerns the interpretation of the SSRT. SSRT measures the time it takes to stop a response. However, it is important to realize that SSRT is a global concept that describes the chain of processes involved in an act of control that results in a response being withheld (Verbruggen, McLaren, et al., 2014). More specifically, SSRT captures the duration of perceptual, decisional, and (inhibitory) motor-related processes. For example, previous behavioral studies and computational work have highlighted the role of perceptual processes (see above). Our study shows that successfully stopping also depends on decisional processes, such as response selection and memory retrieval (see also e.g. Logan et al., 2014; van de Laar, van den Wildenberg, van Boxtel, van der Molen, 2010). Finally, when the decision to stop is reached, motor output or other ongoing processing has to be suppressed (e.g. via a fronto-basal-ganglia network). Thus, in simple stop-signal tasks and their many variants, SSRT reflects.