Pinning down response inhibition in the brain — Conjunction analyses of the Stop-signal task
Introduction
Successful behavior requires continuous coordination between the initiation and inhibition of actions, the latter being particularly important when sudden changes in the situation call for an alteration, or even the cancellation, of a planned or ongoing behavior. One of the most prominent experimental paradigms designed to investigate response inhibition is the Stop-signal task (Logan, 1994, Logan et al., 1984). In this task, a Go-stimulus requiring a choice-reaction is rapidly followed, on some trials, by a Stop-stimulus that requires the subjects to withhold the response they were about to give.
Computational models have captured the dynamics of the underlying neural processes as a ‘horse race’ between Go- and Stop-processes that are believed to evolve mostly independently over time (Boucher et al., 2007, de Jong et al., 1990, Logan et al., 1984, Verbruggen and Logan, 2008). Depending on whether the Stop-process can be implemented sufficiently before the Go-process reaches a certain threshold, inhibition will either succeed, or not. One important contribution of this race model is that it provides a formal means to infer the time required for the Stop-process to catch up to the Go-process, called the Stop-signal response time (SSRT). Based on this analysis, subjects typically need around 200 ms to stop an already-initiated behavioral response (Logan and Cowan, 1984, Logan et al., 1984). Moreover, it can be derived from the model that some response inhibition should also be entailed in unsuccessful Stop-trials. Although in such trials the Stop-process loses the race against the Go-process, it will nevertheless usually be initiated and have proceeded partway.
Recent years have seen enormous interest in the Stop-signal task. This popularity speaks to the central role that inhibitory control appears to play in normal human behavior, normal cognitive development, and in a range of neurological and psychiatric conditions such as attention-deficit hyperactivity disorder (ADHD) and substance abuse (Aron, 2009, Aron et al., 2007b, Groman et al., 2009, Verbruggen and Logan, 2008, Williams et al., 1999), as well as to the merits of this paradigm for investigating inhibitory control processes. The neural mechanisms underlying response inhibition have been investigated employing a wealth of approaches, including neuropsychological, TMS, EMG, EEG, MEG, and fMRI studies in humans, as well as neurophysiological recordings in animals. Converging evidence from these different methodologies has led to the view that a predominantly right-hemisphere network of mainly three brain areas is crucial for response inhibition: inferior frontal gyrus (IFG; especially the frontal operculum extending into the insula), medial frontal areas (particularly the pre-supplementary motor area; pre-SMA), and the basal ganglia (for recent reviews see Aron et al., 2007b, Chambers et al., 2009, Verbruggen and Logan, 2008). The dominant view contends that, in response to a Stop-stimulus, a signal from the inferior and/or medial frontal cortex is sent to the basal ganglia to cancel the motor program triggered by the Go-stimulus. This input has been proposed to enter the basal ganglia either through a so-called “hyperdirect” route to the subthalamic nucleus (STN), or the “indirect” route via the striatum (consisting of the caudate nucleus and the putamen; Aron et al., 2007a, Aron and Poldrack, 2006, Eagle et al., 2008, Mink, 1996, Nambu et al., 2002, Ray et al., 2009). Interactions between the different parts of the basal ganglia and the associated STN then give rise to a signal that is sent via the thalamus to motor cortex, where the response is ultimately inhibited (Stinear et al., 2009).
While neuroimaging studies have substantially contributed to our knowledge of the neural mechanisms that support response inhibition, a consensus has not been reached as to the appropriate functional comparison that should be used to isolate processes related to response inhibition. Consequently, approaches and results differ quite substantially between studies (Verbruggen and Logan, 2008). When devising a functional contrast for the Stop-signal task, a couple of factors have to be considered (see supplementary Table S1): response inhibition is almost certainly present in both successful and unsuccessful Stop-trials1 (Garavan et al., 2002), although it seems likely to be more pronounced, or at least faster, for successful Stop-trials. Conversely, there are also operations likely to be specific for either type of Stop-trial, such as registering the positive outcome of a successful Stop-trial2 or evaluating the error in an unsuccessful one, which are not directly related to response inhibition. Finally, both types of Stop-trials differ greatly from Go-trials in such important characteristics as their sensory stimulation and the frequency with which they occur.
Two main approaches have been commonly used to identify inhibition-related brain activity in neuroimaging studies of the Stop-signal task. In one approach, activity is isolated by contrasting successful and unsuccessful Stop-trials (e.g., Duann et al., 2009, Li et al., 2006, Rubia et al., 2003, Rubia et al., 2007). In the other, Stop-trials (either all Stop-trials or successful Stop-trials alone) are compared to Go-trials (e.g., Aron and Poldrack, 2006, Pliszka et al., 2006, Ramautar et al., 2006, Rubia et al., 2001). While both approaches have advantages for extracting differential activity of interest, each one has some distinct limitations. Of concern in the first approach (comparing successful vs. unsuccessful Stop-trials) is the underlying assumption that inhibitory processes are considerably more pronounced in successful than in unsuccessful Stop-trials. Therefore, to the degree that response-inhibition-related activity is also present in unsuccessful Stop-trials, this approach is overly conservative. Additionally, successful Stop-trials might entail specific neural operations that are not directly related to response inhibition, such as registering the successful outcome of Stop-trials. Such processes might be mistaken as being directly related to response inhibition, as the employed contrast cannot differentiate between them.
The second approach (comparing Stop-trials and Go-trials) is also limited in that some processes are likely to be present in Stop-trials and absent in Go-trials that are also not directly related to response inhibition (see supplemental Table S1). Most prominently, there are differences in visual stimulation in these two conditions (i.e., there is no Stop-stimulus in Go-trials), which thereby render interpretations of visually responsive areas rather problematic. Importantly, some of these areas might actually play an integral role in response inhibition and deserve investigation. A good example is the parietal cortex, where large swaths of activity have been very often associated with motor control tasks (e.g., Aron and Poldrack, 2006, Coxon et al., 2009, Garavan et al., 2002, Jaffard et al., 2008, Menon et al., 2001). Despite being identified in motor control experiments so regularly, it is not clear whether some parietal regions indeed subserve a function that is directly related to response inhibition (Bunge et al., 2002, Chambers et al., 2009, Coxon et al., 2009, Wager et al., 2005), or whether its functions might be restricted to the attentive processing of the relevant stimuli. In order to make distinctions between such processes, it is crucial to separate out effects arising from the inherent differences in sensory stimulation between Stop- and Go-trials.
To summarize, it appears that both approaches that have been commonly used thus far have some limitations. Comparing successful and unsuccessful Stop-trials is potentially overly conservative, whereas comparing Stop-trials and Go-trials has limited specificity. The present study attempts to find a compromise between these two extremes by utilizing conjunction analyses of fMRI responses to isolate cognitive/neural operations that are shared between successful and unsuccessful Stop-trials, as compared to trials in which there is no response inhibition. This strategy should account for specificity issues arising from processes that are exclusive to either Stop-trial type, in that it excludes activity that is only present in one condition. However, as detailed above, there are also factors that are common to both Stop-trial types beyond those directly related to response inhibition. As noted above, the most prominent of these factors is the processing of the Stop-stimulus that makes activity differences between Stop-trials and Go-trials in sensory areas hard to interpret. Accordingly, in order to allow investigation of hemodynamic responses in areas that respond to sensory stimulation, the present study included a sensory control condition that was matched in visual stimulation to the Stop-trials but did not require response inhibition. This approach should thus be more specific than the comparison between Stop-trials and Go-trials, while at the same time it is likely to be less restrictive than the comparison of successful and unsuccessful Stop-trials, depending on how much more pronounced response-inhibition activity is in successful than in unsuccessful Stop-trials.
Section snippets
Participants
Eighteen subjects participated in this study, two of which were excluded due to technical problems. One additional subject was excluded due to particularly poor behavioral performance. Of the 15 remaining participants, nine were female and the mean age was 22.9 years. All subjects had correct or corrected-to-normal visual acuity, and none of them reported a history of psychiatric or neurological disorders. All were paid for participation and gave written informed consent before the experiment in
Behavioral results
An overview of the main behavioral parameters is provided in Table 1. Subjects performed very accurately under both task regimes, with similar accuracy in the three conditions that require responses (i.e., Go-trials in both the SR and SI task blocks and “Stop”-trials in SI-blocks; F(1.5,21.4) = 2.2, p = 0.15). Response times (RTs) were the slowest on Stop-relevant Go-trials, as compared to unsuccessful Stop-trials from the same blocks and Go- and Stop-trials from the Stop-irrelevant blocks (overall
Discussion
The present fMRI study investigated neural processes underlying response inhibition during the Stop-signal task in human subjects. We have argued that some of the heterogeneity between results from preceding fMRI studies may have arisen from the use of different functional contrasts and that these prior approaches may have either lacked some specificity or were overly conservative concerning response-inhibition-related brain activity. Here we have suggested using conjunction analyses of both
Summary and conclusions
We have argued that earlier approaches aimed at identifying activity that is related to response inhibition in fMRI studies were limited in that they have tended to be overly conservative or relatively unspecific. We have demonstrated that employing conjunctions of successful and unsuccessful Stop-trials respectively against a reference condition can provide a viable compromise that engenders a reasonable degree of specificity without being overly conservative. The most drastic increase in
Acknowledgments
This research was supported by NIH grants RO1-MH060415 and R01-NS051048 to M.G.W. and funds of the Deutsche Forschungsgemeinschaft (BO 3345/1-1) to C.N.B.
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