Signal-related contributions to stopping-interference effects in selective response inhibition

In our ability to selectively inhibit a subset of concurrent response tendencies, referred to as selective response inhibition, stopping-interference (SI) effects have been found and attributed to global inhibitory processes. In the standard stop-signal paradigm, the stop signal might not only signal stopping but also produce other effects simply by virtue of being an additional signal. Therefore, we investigated whether previously observed SI effects reflect not only selective response inhibition but also other effects caused by the appearance of the stop signal. In Experiment 1, we controlled for the possible extra influences of the stop signal and still found SI effects, allowing a more confident attribution of SI effects to global inhibitory processes. Furthermore, the extra signal affected the motor system, as revealed by a reduction in SI effects on response force after the improved control. Using the lateralized readiness potential, Experiment 2 showed that the extra signal affected relatively central motor processing. The findings thus advance our knowledge about the distinction between signal-related and motor-inhibitory effects in stop-signal tasks.

1. The probability of stop-signal trials employed in selective-stopping tasks requiring stopping one of the two hands is usually higher than that in typical stop-all tasks (e.g. Aron and Verbruggen 2008). This is because in the selective-stopping tasks, stopping has to be signalled for either the left or the right hand, and that increases the frequency of the stop-signal trial. Regarding the probability of the controlled-go trials in the present study, we thought that SI effects obtained by comparing signal-inhibit trials and no-signal go trials have been clear, and our main purpose of this study was to test whether SI effects remain when the extra signal in signal-inhibit trials is controlled by introducing a similar extra signal in the controlled-go trials. For that reason, the probability of the controlled-go trials was set to be much higher than that of the no-signal go trials. Although the low probability of no-signal-go trials might cause the participant to adapt a delay strategy in those trials, this possibility does not affect our main concern of testing SI effects by comparing signal-inhibit and controlled-go trials.

2. This pattern of result was exactly the same when the comparison was made between signal-inhibit trials and their RT-matched no-signal go trials: there was no difference between the nontarget hand RTs of the two types of trials (648.85 and 648.70 ms; F(1,19) = 1.90, p > .1). The nontarget hand PFs were larger in signal-inhibit trials than in their RT-matched no-signal go trials (337 vs. 274 cN; F(1,19) = 21.56, p < .001).

3. Regarding typical two-choice RT tasks requiring a single-hand response to the imperative stimulus, it is true that the LRP is more closely associated with the response (i.e. the RT) to the imperative stimulus. However, in our selective-stopping task, a single-hand response (as it is in signal-inhibit trials) is prepared and executed after the presentation of the X, rather than the imperative stimulus (two filled-in squares). In other words, any LRP in our selective-stopping task is in response to the X, and therefore, the presentation of the X is the critical event for time-locking in our analyses. Nonetheless, when RT-aligned averages are considered, all patterns of results and their implications remain the same. Specifically, a clear LRP in the signal-inhibit trials and a small LRP in the controlled-go trials before the response were found. Mean LRPs in the 200-ms interval right before the response were calculated. The mean LRP in signal-inhibit trials was −1.98 muV, which was significantly different from zero [F(1,15) = 134.15, p < .0001], as was expected. The mean LRP in controlled-go trials was −.44 muV, which was also significantly different from zero [F(1,15) = 9.36, p < .01], indicating the extra signal has its effects on the motor stage of the information processing.

4. In Fig. 2, a 10-point moving-average filter was used as an off-line low-pass filter to attenuate high-frequency fluctuations in LRPs. To have a consistency between descriptions about statistical results and Fig. 2, the results reported here are those after the low-pass filtering. Importantly, all patterns of results were the same even if the low-pass filtering was not used: the mean LRP in signal-inhibit trials was −2.39 muV, which was significantly different from zero [F(1,15) = 82.47, p < .0001]. The mean LRP in controlled-go trials was −.67 muV, which was also significantly different from zero [F(1,15) = 14.94, p < .01].

5. We thank Sander Los for initiating this discussion.

Authors and Affiliations

1. Institute of Cognitive Neuroscience, National Central University, Jhongli City, Taiwan

   Yao-Ting Ko

2. University of Otago, Dunedin, New Zealand

   Jeff Miller

Corresponding author

Correspondence to Yao-Ting Ko.

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