D ISCUSSION

The aims of this experiment were primarily to confirm whether or not physiologically distinct M1 inputs could be accessed with different TMS pulse parameters and whether these inputs were indeed differentially modulated during the SST when proactive inhibition was active.

3.4.1 Validation that physiologically distinct motor cortex inputs can be accessed and their modulation during response preparation

According to Hannah et al. movement preparation differentially modulated inputs into the motor cortex (87). As we wanted to examine whether these inputs were modulated during response initiation and inhibition, we first sought out to validate their results. To this end, we performed the same experiment reported in their original paper. We found that different motor cortex inputs were indeed modulated differentially by movement preparation; AP30 inputs were significantly modulated at time of the imperative stimulus compared to PA120 inputs. This differential modulation supports the notion that they access different inputs into the motor cortex. As another line of evidence to support this, we assessed the latencies of TMS evoked MEPs during this the time of the imperative stimulus. It is well known that AP inputs into the motor cortex display longer latencies than PA inputs when stimulated with monophasic TMS (85,91). It has also recently been found that by modulating the pulse width of TMS, these inputs can be better selected (91).

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We confirmed that this was also true in our experiment, as all participants had MEPs with longer latencies when evoked with AP30 TMS. Our results from this study validated the use of AP30 and PA120 TMS to access physiologically distinct motor cortex inputs.

3.4.2 Corticospinal outputs when stopping might be required

Assessing CSE during the SST and Go-only tasks, it is clear that CSE rises later when stopping might be required, presumably due to the influence of proactive inhibition.

However, the response-locked analysis showed that most of this difference was due to the difference in reaction times between the two tasks. Indeed, the rise in excitability prior to movement onset was the same for PA and AP inputs. Because of this, the remaining chapters use only one direction of TMS pulse. More detailed analysis of this data is continued in the next chapter.

Interestingly, we noticed that PA inputs were suppressed during early time points when stopping might be required in the SST relative to their counterparts in the Go-only task.

We interpreted this as suppression as a reflection of the requirement to stop, something we confirmed in the next analysis. Because the task was designed pseudorandomly, such that one stop trial was presented in every four trials (one stop, three go), which were then randomised themselves and concatenated, the probability of stopping on a particular trial dynamically changed. With this in mind, we predicted that subjects also dynamically change their ‘stopping expectation’. Figure 3.5C shows the probability of successfully stopping on a stop trial, depending on when it came after a stop trial. Hence, 0 refers to STOP-STOP, 1 refers to STOP-GO-STOP, 2 refers to STOP-GO-GO-STOP and so on.

It shows that the probability of successfully inhibiting increases with more go trials after a stop trial, presumably because the expectation of a stop trial occurring increases.

However, the reaction time on subsequent go trials after a stop trial does not significantly change in line with this change in ‘stopping expectancy’. One caveat of designing the experiment in this way was that the stopping expectancy could be learnt, which could potentially confound measures of response inhibition. However, we observed that

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subjects successfully inhibited their responses on approximately 50% of stop trials, showing that the staircase procedure was correctly followed.

Different M1 inputs are accessed (PA120 or AP30 TMS), at one of three time points: at the cue, 50 ms or 100 ms after the cue. If we assume that any changes in expectation of stopping and decision making are reflected early on in these time-points, then we can use these MEPs to investigate M1 inputs during this period, which may reflect the upcoming probability of a stop trial occurring. Indeed, CSE significantly differs with that at baseline from 200 ms in the SST and reaction times are 103.24 ms slower when stopping may be required between the SST and Go-only task. This suggests that preparatory steps, including decision making of a movement, occur over 100 ms after the go cue has been presented. Figure 3.5A shows the excitability probed with PA120 TMS on go trials as a function of when they occurred after stop trials. Here, the numbers correspond to the number of the go trial after stop trial: 1 = STOP-GO, 2 = STOP-GO-GO and so forth. It shows that CSE is largest on the go trial straight after a stop trial, presumably because the expectation of stopping is lowest on the trial after a stop trial. Consequently, CSE may be higher to set the motor state in a heightened one, primed to make a fast response. This lies in agreement with lower probability of stopping on the corresponding trial. As the number of go trials increases, the probability of successful stopping increases, whilst CSE decreases. However, this relationship exists for PA120 MEPs only; this pattern is not exhibited in AP30 MEPs. A relationship between CSE and reaction times has previously been shown to be under the influence of cognitive preprocessing pertaining to uncertainty and surprise (95). In the SST, it is possible that what we have measured is a manifestation of the uncertainty of a stop signal occurring, which manifests as proactive inhibition.

Many authors have shown that the expectation of movement is reflected in M1 excitability in the preparatory period prior to movement (116,118–120). By analogy we suggest that the SST-Go-only difference observed here reflects a similar phenomenon (94–96,181–

183). In this task, the effector being called into action is always the right index finger.

Therefore, one can assume that motor preparation, from an effector selection perspective,

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is equal in the Go-only and SST. Interestingly, we see that AP inputs are suppressed with respect to baseline in both tasks and regardless of the go trial they occurred on. These results support earlier findings that AP suppression is a necessary component of movement preparation, irrespective of stopping requirements and does not reflect proactive inhibition. Hence what is probably being assayed in these early time points, in AP30 MEPs, is probably movement preparation. PA inputs, on the other hand, seem to track behaviour regarding reaction times and stopping probability; they are suppressed when stopping might be required, in a dose-dependent fashion. In all, these results seem to point to two simultaneous processes occurring: AP suppression reflecting putative movement preparation, which is overlain by suppression of PA inputs regarding the possibility of stopping.

Despite being differentially modulated during response preparation and inhibition, we do not believe that these are the exclusive pathways mediating these processes. Our interpretation is more conservative, that response preparation and inhibition can act via different inputs (response inhibition is not merely less response initiation) and that our data strengthen the hypothesis that PA and AP inputs into M1 are physiologically and behaviourally distinct (86,87,90,184).