Functional relevance of pre-supplementary motor areas for the choice to stop during Stop signal task

Neuroscience Research 70 (2011) 277–284

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Functional relevance of pre-supplementary motor areas for the choice to stop during Stop signal task Hayato Tabu a,b , Tatsuya Mima a,∗ , Toshihiko Aso a , Ryosuke Takahashi b , Hidenao Fukuyama a a b

Human Brain Research Center, Kyoto University Graduate School of Medicine, Sakyo-ku Shogo-in Kawahara-cho 54, Kyoto 606-8507, Japan Department of Neurology, Kyoto University Graduate School of Medicine, Sakyo-ku Shogo-in Kawahara-cho 54, Kyoto 606-8507, Japan

a r t i c l e

i n f o

Article history: Received 7 December 2010 Received in revised form 28 February 2011 Accepted 10 March 2011 Available online 29 March 2011 Keywords: Pre-supplementary motor area Response inhibition Stop signal task Functional MRI Prefrontal cortex

a b s t r a c t There exists an ongoing debate about the functional relevance of the pre-supplementary motor area (preSMA) and right ventrolateral prefrontal cortex (VLPFC) for response inhibition during Stop signal task, because of difficulties in segregating cognitive elements involved in stopping, such as response inhibition, attentional control and error monitoring. To further understand the precise brain representation of response inhibition, we developed a new “Double-press signal task” that requires subjects to decide pressing the button once or twice as quickly as possible according to the cue and conducted an event-related functional MRI study of the conventional Stop signal and Double-press signal tasks for 13 healthy subjects. The advantage of our experimental design is that the latter task does not contain any response inhibition and that its difficulty measured by error rate is not significantly different from that of Stop signal task. Activations of the right VLPFC and pre-SMA were observed only for Stop signal task. Moreover, voxelby-voxel analysis comparing these two tasks showed the significantly larger activation in the pre-SMA for Stop signal task, supporting the hypothesis that the pre-SMA is functionally essential for response inhibition. © 2011 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

1. Introduction The inhibition of inappropriate behaviors and internal processes is critical for daily activities in the ever-changing environment. Inaccurate response inhibition can be even lethal, for example you encounter a red light when crossing a road. Lesion studies in human patients and animals revealed the close link between this inhibitory control and the prefrontal cortex, which is regarded as the center of executive function (Aron et al., 2004, 2003b; Duncan and Owen, 2000; Iversen and Mishkin, 1970; Shallice and Burgess, 1996). Importance of response inhibition is also suggested by the fact that numerous neuro-psychiatric diseases, for example attention deficit hyperactivity disorders, often show symptom related to deficient inhibition (Aron, 2009; Aron et al., 2003a; Barkley, 1997; Morein-Zamir et al., 2008; Schachar et al., 1995; Solanto et al., 2001). Previous neuroimaging studies evaluating response inhibition showed activities in the ventro- and dorso-lateral prefrontal cortex (V/DLPFC), pre-supplementary motor area (pre-SMA) and parietal cortex (PC) (Aron and Poldrack, 2006; Bellgrove et al., 2004; Chikazoe et al., 2009; Duann et al., 2009; Garavan et al., 1999;

∗ Corresponding author. Tel.: +81 75 751 3695; fax: +81 75 751 3202. E-mail address: [email protected] (T. Mima).

Hampshire et al., 2010; Konishi et al., 1999; Leung and Cai, 2007; Li et al., 2006; Liddle et al., 2001; Menon et al., 2001; Mostofsky et al., 2003; Nakata et al., 2008; Rubia et al., 2003). However, the exact functional localization of response inhibition is still under discussion. Some reports indicated the crucial importance of the right VLPFC for inhibitory motor control (Aron and Poldrack, 2006; Garavan et al., 1999; Konishi et al., 1999; Liddle et al., 2001; van Boxtel et al., 2001). Electrical stimulation in the rostroventral corner of prefrontal cortex induced the decreased activity in the motor cortex (Sasaki et al., 1989). A lesion study of patients with frontal lobe damage suggested the essential role of the right VLPFC in response inhibition (Aron et al., 2004), which was confirmed by a virtual lesion study using transcranial magnetic stimulation (TMS) (Chambers et al., 2006). However, it is also known that the right VLPFC is associated with various tasks other than response inhibition (Duncan and Owen, 2000; Hon et al., 2006; Miller and Cohen, 2001; Shallice et al., 2008). The VLPFC plays a general role in attentional control (Dehaene et al., 1998; Duncan, 2001), particularly when the target is salient and behaviorally relevant (Bledowski et al., 2004; Corbetta et al., 2008; Corbetta and Shulman, 2002; Hampshire et al., 2010, 2007, 2008, 2009; Linden et al., 1999). Since response inhibition is disturbed by lesions in the left VLPFC (Swick et al., 2008), the left VLPFC as well as the right one may also be relevant for response inhibition.

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H. Tabu et al. / Neuroscience Research 70 (2011) 277–284

However, a recent study showed that lesions of the subthalamic nucleus (STN), a structure connected with the VLPFC and pre-SMA (Inase et al., 1999; Takada et al., 2001), did not change the response inhibition (Eagle et al., 2008). Another possible brain area responsible for response inhibition is the pre-SMA, because response inhibition is one type of response control and switching where the pre-SMA is known to play a critical role (Isoda and Hikosaka, 2007; Rushworth et al., 2002). In this perspective, response inhibition during Stop signal task can be regarded as a kind of choice reaction time task between Go and No-go. Thus, it has been hypothesized that the task switching and response inhibition might be merely different aspects of a single function (Nachev et al., 2008). Human functional magnetic resonance imaging (fMRI) studies using Go/No-go or Stop signal task often showed the brain activation including the pre-SMA (Aron and Poldrack, 2006; Cai and Leung, 2009; Leung and Cai, 2007; Nakata et al., 2008; Sharp et al., 2010; Wager et al., 2005). Patients with damage to the superior medial parts of the frontal lobes, probably including the pre-SMA, had an increased number of incorrect responses in Go/No-go task (Picton et al., 2007). In addition, TMS over the pre-SMA changed the ability to respond to the stop signals, indicating the altered inhibitory control (Chen et al., 2009). It has been suggested that the VLPFC mediates attentional control of the stop signal and the pre-SMA mediates response inhibitory control (Duann et al., 2009). Hampshire et al. (2010) recently reported also that the right VLPFC is activated during both the mental counting and simple button-press tasks using the Stop cues during Stop signal task as a target (Hampshire et al., 2010). To further understand the precise brain representation of response inhibition, we performed the event-related fMRI study of Stop signal task that requires subjects to respond immediately on Go trials and to inhibit the response on Stop trials, with special interests to the functional relevance of the VLPFC and pre-SMA. To segregate the brain areas associated with response inhibition, we utilized a new task where subjects have to decide pressing the button once or twice as quickly as possible, according to the cue (Double-press signal task), in addition to the conventional Stop signal task. This task will require the detection of a task-relevant cue and the change of motor behavior similar to Stop signal task without any obvious motor inhibition component. 2. Material and methods 2.1. Subjects Thirteen right-handed healthy young adults participated in the experiments (8 men and 5 women, mean age ± SD is 27.5 ± 5.2 years old). None of subjects had a history of neurological, psychiatric and addictive disorders according to self-report. None of subjects took caffeine and tobacco on scan days. Their handedness scores were between 0.8 and 1, which were assessed by the Edinburgh scale (Oldfield, 1971). All participants provided written informed consent according to the study protocol approved by the Kyoto University Graduate School and Faculty of Medicine Ethics Committee. 2.2. Stop signal task Stop signal task (Logan et al., 1984; Verbruggen and Logan, 2008) consisted of Go and Stop trials (Fig. 1). On each trial, after a fixation period the central fixation point was replaced by a left- or rightpointing arrow in green color (Go cue) on a computer screen. The width of green arrow signals was within ∼10◦ of eccentricity from the center. The green arrow signal remained for 900 ms. Subjects were instructed to press the non-magnetic button as soon as pos-

Go trial(75%) 900ms Fixation Go cue

Fixation

Button press

Stop/Double-press trial(25%) 900ms Fixation Go cue Stop/Double-press cue

Stop signal delay/ Double-press signal delay

Fixation

( ) Withholding button press/ Double button press

Fig. 1. Schema of Stop and Double-press signal task. In Go trials, subjects press a left or right button in response to a Go cue (duration: 900 ms), depending on the direction of the arrow. In Stop trials during Stop signal task, a Stop cue (red rectangle) replaced the Go cue at some delay (SSD). Subjects are instructed to try to inhibit pressing the button when they find the Stop cue. For Double-press signal task, the same series of visual stimuli as Stop signal task were used. In this task, the red rectangle indicates the Double-press cue where subjects are instructed to press the button twice successively instead of withholding the response. Inter-trial intervals ranged from 3 to 5 s. For both tasks, the time delay for the Stop or Double-press cue presentation (SSD or DSD) changed dynamically throughout the experiment to produce a 50% inhibition rate (see Section 2). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

sible using the right or left thumb, in response to the Go cue. The presentation order of the directions of the arrows was randomized. In 25% of trials (Stop trials), a Stop cue (a red rectangle) was presented shortly after the presentation of a Go cue. The frequency of the stop signal followed previous fMRI and TMS studies (Aron and Poldrack, 2006; Badry et al., 2009; Cai and Leung, 2009; Leung and Cai, 2007; Li et al., 2006; Rubia et al., 2003). Time difference from the onset of Go cue to that of Stop cue in Stop trials was named as the Stop signal delay (SSD). The Stop cue remained on the monitor for the rest of 900 ms period. For Stop trials, subjects were instructed to try to inhibit pressing the button. Trials were separated by a null period of 3–5 s with a fixation cross at the center of the monitor. There were 30 Stop and 90 Go trials per session. The number of leftward and rightward pointing arrows was equal. The SSD changed dynamically depending on the result of the previous Stop trial. Successful inhibition of the button press made the SSD of the next Stop trial increased by 50 ms, which made the next trial difficult. After the failure in the Stop trial, the next SSD decreased by 50 ms. The SSD started from 150 ms at the beginning. After each session, subjects were given feedback in the form of their median correct RT and SSD scores. 2.3. Double-press signal task We developed Double-press signal task using exactly the same series of visual stimuli as Stop signal task, to evaluate the brain processing of the detection of a task-relevant cue and the change of motor behavior. Double-press signal task consisted of Go and Double-press trials. The Go trial in this task was the same as the one in Stop signal task. For Double-press trials (25% of all trials), subjects were instructed to press the button twice successively instead of withholding the response, when they saw a red rectangle (Double-press cue), which appears with a short time delay from the onset of the Go cue (Double-press signal delay: DSD). The DSD changed dynamically depending on the result of the previous

H. Tabu et al. / Neuroscience Research 70 (2011) 277–284

Double-press trial in the same way as the SSD. The DSD started from 300 ms at the beginning. Behavioral performances of Double-press trials were judged by whether the subject could press the button twice before the disappearance of the red rectangle. Subjects were informed of this judgment to receive the same feedback as Stop trials. To avoid the possible contribution of inhibitory system, subjects were allowed to press the button before the appearance of Double-press cue.

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parallel to the anterior–posterior commissural (AC–PC) line. Four image volumes were discarded at the beginning of each session to allow the MR signal to reach equilibrium. In addition, magnetization-prepared rapid-acquisition gradient echo (MPRAGE) was obtained for each subject for registration purposes.

2.8. Imaging analysis 2.4. Experimental procedures All 13 subjects participated in Stop signal task and Double-press signal task. We compared Stop signal task with Double-press signal task. For each task, each subject performed four sessions which took approximately 40 min. To avoid fatigue, each task was performed separately on a different day, 14–28 days apart. Half of subjects performed Stop signal task first and another half performed Double-press signal task first. To achieve the stable performance, subjects were over-trained for both tasks before scanning. 2.5. EMG recording The Electromyogram (EMG) was recorded from bilateral abductor pollicis brevis (APB) muscles. Silver–silver chloride surface electrodes with shielded plates and cables were placed over the muscle. A ground electrode was placed on the ventral surface of the wrist. EMG signals were fed to a digital amplifier (SynAmps; Neuroscan, Sterling, VA, USA) through a radiofrequency filter. EMG data were band-pass filtered at 5–200 Hz and sampled at a digitization rate of 10 kHz. 2.6. Behavioral analysis Median reaction time (RT) of the correct Go trials and the average SSD or DSD were calculated from the latter 100 trials of each session for Stop or Double-press signal tasks. The number of Error trials (Go trials with pressing the button by the wrong side) was also counted. For Stop signal task, the duration of stop process was measured by Stop signal reaction time (SSRT) by subtracting SSD from RT. This calculation is based on the Logan’s race model (Aron and Poldrack, 2006; Logan et al., 1984). This model presumed that the Go and Stop processes were independent and raced. Therefore we can estimate the underlying Go process during Stop trials from the Go reaction time and calculate SSRT. Based on the visual inspection of EMG monitoring, some of the successful Stop trials were excluded because of the existence of small EMG burst that may reflect the interrupted button press movement. The percentage of successfully inhibited Stop trials was also assessed individually. For Double-press signal task, the median reaction time for the first and second response in Double-press trials was calculated. The percentage of successful Double-press trials was also assessed individually. The behavioral results were statistically compared using t-test with the threshold at the p-value of 0.05. 2.7. MRI data acquisition Whole-brain images were obtained using a Trio 3-T scanner (Siemens) with an eight-channel head coil. First, three-plane localizer images were obtained followed by 204 functional T2*-weighted echoplanar images (EPIs) for each session [slice thickness = 3 mm; 40 axial slices; repetition time (TR) = 2.5 s; echo time (TE) = 20 ms; flip angle = 90◦ ; matrix size = 64 × 64; field of view (FOV) = 192 mm × 192 mm]. A series of EPI were obtained

All images were processed with SPM5 (Wellcome Department of Imaging Neuroscience, University College London, London, UK; http://www.fil.ion.ucl.ac.uk/spm/) and Matlab (version6; MathWorks, Natick, MA). Images were realigned relative to the mean volume of each subject. The high-resolution anatomical images were coregistered with the mean functional image. All images were then normalized to the Montreal Neurological Institute (MNI) T1 template, using a 12-parameter affine registration and nonlinear transformations (Friston et al., 1995). The functional images were then resampled to 2 mm × 2 mm × 2 mm voxel size and spatially smoothed with a Gaussian kernel of 6 mm full-width at half-maximum. The data were high-pass filtered with a 128 s cutoff. For the voxel-by-voxel analysis, a design model was constructed. (1) For Stop signal task, a design was constructed using the onset times of four task conditions on both right and left sides: Go, Stop-success, Stop-failure, Go-wrong (2) for Doublepress signal task, a design model was constructed using the onset times of four task conditions on both side: Go, Double-success, Double-failure, Go-wrong. Each event vector was convolved with a canonical hemodynamic response function and used as a regressor (Friston et al., 1995). Realignment parameters in all six dimensions were also entered in the model. A higher-level analysis produced across-session contrasts of each subject for contrast images. These were then analysed at the whole-brain level, with random-effects analyses in SPM5, using one-sample t tests. Group images were then thresholded using cluster detection statistics, with a threshold of T > 3.93 and a cluster probability of p < 0.05, corrected for whole-brain multiple comparisons using Gaussian random field theory. At first, we analysed all the MRI data for Stop signal task. It is possible that ‘Stop-success’ condition would reflect an already initiated Go process with a subsequent Stop process (Aron and Poldrack, 2006). Thus, to investigate the brain representation of response inhibition, we performed the contrast ‘Stop-success vs. Go’ for right and left hands separately. Since there was no significant difference between the inhibition-related brain activation for right and left hands, we decided to pool trials irrespective of the task-performing hand for the further analysis. In addition, contrasts ‘Stop-failure vs. Go’ and ‘Stop-success vs. Stop-failure’ were also performed. For Double-press signal task, we performed the contrast ‘Double-success vs. Go’ for right and left hands separately. Because of the same reason in Stop signal task, we pooled the data irrespective of the task-performing hand. In addition, we performed the region-of-interest (ROI) analysis, based on the hypothesis that the right VLPFC and pre-SMA were relevant for response inhibition. Two brain regions were selected and defined as: (1) right VLPFC, consisting of combined pars opercularis and pars triangularis from AAL (WFU PickAtlas by Advanced Neuroscience Imaging Research Lab, Winston-Salem, NC), (2) preSMA using the SMA region from the AAL atlas (with y > 0). ROI data from each subject were extracted using Marsbar (Brett et al., 2002) (http://marsbar.sourceforge.net/). To estimate the magnitude of brain activation, the % signal changes of ROI during Go condition were subtracted from those of Stop-success or Double-success conditions.

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Fig. 2. Activations are overlaid on the image from the SPM single-subject render template and the coronal image from the SPM template (A: y = 18, B: y = 10, C: y = 14). All maps are thresholded at t = 3.93 voxel level, p < 0.05 cluster corrected for whole brain. ‘Stop-success vs. Go’ contrast in Stop signal task significantly activated the right VLPFC, right insula, right DLPFC, left VLPFC–left insula, pre-SMA and PC (A). ‘Double-success vs. Go’ contrast showed the activation of the right DLPFC, left VLPFC and PC (B). The conjunction analysis for ‘Stop-success vs. Go’ and ‘Double-success vs. Go’ contrast showed the common activation in the PC, right DLPFC and left VLPFC but not in the right VLPFC and pre-SMA (C).

Firstly, to compare Stop signal and Double-press signal tasks, a higher level analysis was created by paired-t test between the contrast ‘Stop-success vs. Go’ minus ‘Double-success vs. Go’ for each subject to estimate the specific region for response inhibition (with a height threshold of T > 3.05 and a cluster probability of p < 0.05, corrected for whole-brain). In addition, common activations across them were investigated by the conjunction analytic procedures based on a conjunction null hypothesis (Friston et al., 2005; Nichols et al., 2005). A voxel was considered conjunctively activated if it was suprathresholded in the both contrasts (with a height threshold of T > 3.93). Since we report the results in a priori regions of interest (right VLPFC and pre-SMA), we also applied ROI analysis to compare the % signal changes during these conditions. 3. Results High behavioral performance was showed on Go trials in Stop signal task (mean ± SD; accuracy, 98.3 ± 2.1%; RT 445.2 ± 54.4 ms). The inhibition rate among Stop trials was close to 50% (53.9 ± 3.8%). The SSD was 187.7 ± 57.3 ms and, the SSRT was 257.4 ± 43.2 ms. The percentage of excluded successful Stop trials due to EMG burst among total successful Stop trials was 1.9 ± 2.4%. In Double-press signal task, the reaction time of Go trials was significantly shorter than that in Stop signal task (mean ± SD; accuracy, 96.8 ± 3.3%; RT

398.3 ± 39.4 ms) (p < 0.05). The DSD was 385.1 ± 75.3 ms. The success rate of Double-press signal task was 52.6 ± 7.0%. There was no significant difference in success rates of Stop and Double-press trials (p = 0.82). For fMRI, ‘Stop-success vs. Go’ contrast in Stop signal task significantly activated the right VLPFC (MNI: 54, 14, 10 t = 5.29; cluster size 77), right insula (MNI: 36, 16, 4; t = 6.77; cluster size 177), right DLPFC (MNI: 44, 32, 36; t = 6.40; cluster size 169), left VLPFC (MNI: −30, 20, −4; t = 4.15; cluster size 177)- left insula (MNI: −38, 12, 6; t = 6.25), pre-SMA (MNI: −4, 22, 52; t = 6.17; cluster size 550) and PC (Fig. 2A). ‘Stop-failure vs. Go’ contrasts showed essentially the similar pattern of activation. ‘Stop-success vs. Stop-failure’ contrast showed no suprathreshold activation. Thus, the further analysis to investigate the brain representation of response inhibition was performed only for ‘Stop-success vs. Go’ contrast. For Double-press signal task, ‘Double-success vs. Go’ contrast showed the activation of the right DLPFC (MNI: 42, 50, 18; t = 8.77; cluster size 75), left VLPFC (MNI: −54, 12, 14; t = 6.96; cluster size 170) and PC (Fig. 2B). The conjunction analysis for ‘Stop-success vs. Go’ and ‘Doublesuccess vs. Go’ contrast showed the common activation in the PC and marginal activation in the right DLPFC (MNI: 44, 48, 18; t = 5.01; cluster size 60) and the left VLPFC (MNI: −48, 14, 0; t = 4.52; cluster size 53) but not in the right VLPFC and pre-SMA (Fig. 2C).

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Fig. 3. Activations are overlaid on the image of the SPM single-subject sagittal template. ‘Stop-success vs. Go’ minus ‘Double-success vs. Go’ in higher level analysis showed the activation in the pre-SMA.

0.04

rtVLPFC

pre-SMA

stop-suc vs. go

double-suc vs. go

0.03

0.02

0.01

0

-0.01

-0.02

Fig. 4. ROI analysis for Stop and Double-press signal tasks for the right VLPFC and pre-SMA. T-test showed significantly higher % signal change only for the pre-SMA. *p < 0.05.

To isolate the specific region associated with response inhibition, we contrasted the model of ‘Stop-success vs. Go’ minus ‘Double-success vs. Go’ in higher level analysis, which showed significant activation in the pre-SMA (MNI: −6, 28, 62; t = 6.15; cluster size 431) and PC (Fig. 3). For the ROI analysis, 2-way repeated-measure ANOVA (ROI: right VLPFC and pre-SMA, task: Stop signal and Double-press signal tasks) showed a significant main effect of Task (p = 0.04) without ROI × Task interaction (p = 0.342) (Fig. 4). Post hoc t-test with Bonferroni correction showed significantly higher % signal change only for the pre-SMA (p = 0.04) but not for the right VLPFC (p = 0.84). 4. Discussion Our study provides a new insight for ongoing debate about the function of the right VLPFC and pre-SMA during response inhibition. With newly developed ‘Double-press signal task’, we

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investigated the specific brain regions associated with response inhibition during Stop signal task. The advantage of our experimental design is that the task difficulty measured by error rate is not significantly different between two tasks which shared the same series of visual stimuli. We also used the EMG monitoring during MRI scanning, which enabled us to confirm the motor inhibition for successful Stop trials. We found similar activations of the right DLPFC, left VLPFC and parietal cortex for both Stop signal and Double-press signal tasks. However, activations of the right VLPFC and pre-SMA were only observed for Stop signal task, which were consistent with ROI analysis. Moreover, voxel-by-voxel analysis comparing these two tasks showed the significantly larger activation in the pre-SMA for Stop signal task. Extending the previous study (Hampshire et al., 2010), our findings further supports the hypothesis that the functional role of the VLPFC during motor control is not exclusively linked to response inhibition but to attentional processing. Our results are in consistent with the functional relevance of the pre-SMA for response inhibition, which was suggested by recent studies (Duann et al., 2009; Isoda and Hikosaka, 2007; Sharp et al., 2010). The present results of a neural network of the VLPFC, insula, preSMA, DLPFC and PC during response inhibition confirmed previous findings (Aron and Poldrack, 2006; Cai and Leung, 2009; Chikazoe et al., 2009; Duann et al., 2009; Garavan et al., 1999; Hampshire et al., 2010; Liddle et al., 2001; Menon et al., 2001; Nakata et al., 2008; Sharp et al., 2010; Wager et al., 2005). To investigate the inhibitory process of button pressing during Stop signal task, we analysed the ‘Stop-success vs. Go’ contrast (Aron and Poldrack, 2006). This is because, in the present study, prefrontal activations associated with a Stop cue in successful inhibition showed no significant difference from those in failed inhibition in accord with a previous report (Aron and Poldrack, 2006). This indicates that the inhibitory process was induced at the neural level, though it was not effective at the behavioral level. In other words, the inhibitory process in the brain is essentially the same for the successful and failed Stop trials. The behavioral difference might be caused by the final results of the race between the Go and inhibitory processes (Logan et al., 1984). However, conventional ‘Stop-success vs. Go’ contrast contains potential confounding factors, including attentional demands for the salient stimuli and the behavioral switching from Go to Stop, in addition to ‘pure’ motor inhibition. Hampshire et al. (2010) extensively studied brain regions related to target detection by comparing activation during response inhibition, generation of motor response and mental-counting of the target. They showed almost the same activation in the VLPFC during response inhibition and target detection, suggesting that the VLPFC plays a general role in attentional control. Our Double-press signal task is different from Hampshire’s control tasks in two aspects. At first, subjects made a response for Go cue of Double-press signal task similar to Stop signal task. For both tasks, the probability for the simple Go reaction was same at 75%. Thus, the possible prefrontal activation associated with uncertainty for the response might be minimal (Chikazoe et al., 2009). Therefore, the baseline Go trials were same for two tasks in our experimental design, which produced the matching amount of motor output load during Go trials of two tasks as a single button press. Secondly, we also matched the behavioral difficulty of two tasks measured by error rates. Thus Double-press signal task would require the similar magnitude of attention, working memory and conflict monitoring as Stop signal task in terms of task difficulty. It is likely that the comparison between ‘Stop-success vs. Go’ and ‘Double-success vs. Go’ might represent the neural activity specific to response inhibition. It is possible that the shorter Go reaction time in Double-press signal task might indicate the smaller conflict in Double-press signal task than in Stop signal task. However

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it is at least clear that Double-press signal task does not include the response inhibition component. In addition, Sharp et al. (2010) also reported the inhibitory function of the medial frontal area including the pre-SMA by comparing the activation during response inhibition and continuing Go reaction. However, the results of our Double-press signal task is different from continuing Go task, because ours included the behavioral change responding to the Double-press cue. The direct comparison between ‘Stop-success vs. Go’ and ‘Double-success vs. Go’ revealed the small but significant activation in the pre-SMA, suggesting its relevance in response inhibition. This finding is also confirmed by the ROI analysis. When we apply the conjunction analysis of these two comparisons, the common activation areas involved the right DLPFC and left VLPFC. Thus, the dissociation between the activations associated with response inhibition and conjunction indicates the possible functional relevance of the right VLPFC in addition to the pre-SMA for response inhibition. Mostofsky et al. suggested the importance of the pre-SMA during response inhibition (Mostofsky and Simmonds, 2008) because the pre-SMA is important for behavioral switching (Isoda and Hikosaka, 2007; Nachev et al., 2008). Previous human fMRI studies using Go/No-go or Stop signal task often showed activation in the pre-SMA (Aron and Poldrack, 2006; Leung and Cai, 2007; Nakata et al., 2008; Simmonds et al., 2008; Wager et al., 2005). Moreover, one study revealed that the pre-SMA was more activated in subjects with better inhibitory performance than in subjects with poorer inhibitory performance (Li et al., 2006). A lesion study showed that SSRT was significantly longer in patients with right dorsomedial frontal damage compared with controls (Floden and Stuss, 2006). TMS study for the pre-SMA altered the inhibitory control (Chen et al., 2009). In addition, a human electrocorticogram study also supports the functional relevance of the pre-SMA in Go/No-go task (Ikeda et al., 1999). Human and monkey microstimulation studies have revealed a “negative” motor area in the anterior pre-SMA where microstimulation produces hesitation of vocal or saccadic responses (Fried et al., 1991; Isoda, 2005). Neubert et al. (2010) reported that the effect of the pre-SMA and right VLPFC on M1 were facilitatory and inhibitory, respectively by using paired-pulse transcranial magnetic stimulation and that the VLPFC’s effect was dependent on the pre-SMA. The pre-SMA receives afferent connections from association regions in frontal and parietal cortex, including the VLPFC and DLPFC. And this connection projects to nonprimary motor but not to primary motor regions (Dum and Strick, 1991; Matsuzaka et al., 1992; Rizzolatti et al., 1996). Thus, the pre-SMA may play a controlling role between cognitive association areas and motor output areas, especially during the selection of a manual response, including the selection of response inhibition. Several human fMRI studies indicated the critical role of the VLPFC during response inhibition (Aron and Poldrack, 2006; Konishi et al., 1999; Leung and Cai, 2007; Rubia et al., 2003). Moreover, lesion and TMS data also suggested that the VLPFC is important for response inhibition in humans (Aron et al., 2003b; Chambers et al., 2006). A recent EEG study showed the response in the VLPFC occurred 100–250 ms after the Stop cue, which indicates an inhibitory control rather than signal processing (Swann et al., 2009). Although we carefully planned the study to differentiate the response inhibition from the stimulus saliency and the cognitive load of the task, it is possible that the attention system and inhibitory motor control largely shares the same neural circuit and cannot be functionally separated. It has been reported that the better inhibitory performance in adults was correlated with lower intra-individual variability which was associated with sus-

tained attention (Bellgrove et al., 2004). The same results were reported in developing children (Klein et al., 2006; Simmonds et al., 2007). In that case, the right VLPFC would also play an essential role in response inhibition. One fMRI study showed the importance of functional connection between the pre-SMA and VLPFC (Duann et al., 2009). Previous MRI tractography study suggested the possible anatomical connection between the pre-SMA, subthalmic nuclei and VLPFC (Aron et al., 2007). The activation of the DLPFC during Stop and Double-press signal tasks may be associated with working memory (Baker et al., 1996; Cohen et al., 1997; Courtney et al., 1996; Levy and Goldman-Rakic, 2000). It is also possible that the DLPFC plays a more general function in the cognitive control of behavior (Courtney, 2004; Miller and Cohen, 2001) or selective attention (Decary and Richer, 1995; Deiber et al., 1996; Jueptner et al., 1997; Rubia et al., 1998; Sakai et al., 2000). Various neuro-psychiatric disorders, for example attention deficit hyperactivity disorders (Aron, 2009; Aron et al., 2003a; Barkley, 1997; Morein-Zamir et al., 2008; Schachar et al., 1995; Solanto et al., 2001), Parkinson’s disease (Gauggel et al., 2004; van den Wildenberg et al., 2006), obsessive–compulsive disorders (Chamberlain et al., 2006) and schizophrenia (Badcock et al., 2002; Rubia et al., 2001), show symptom related to deficient inhibition. In addition, response inhibition is related to social problems as drunk driving (Fillmore et al., 2008) and drug abuse (Monterosso et al., 2005). Therefore, revealing the brain mechanism of response inhibition may lead to the better understanding of these disorders. 5. Conclusions We investigated the specific brain regions relevant for response inhibition with Stop signal task and newly developed ‘Double-press signal task’. We found the significantly larger activation in the preSMA for Stop signal task compared with Double-press signal task, which supports the hypothesis that the pre-SMA is functionally relevant for response inhibition. Acknowledgements This work was partly supported by the Strategic Research Program for Brain Sciences (SRPBS) for TM from the MEXT of Japan, and Grant-in-Aid for Scientific Research (C) 21613003 for T.M. from Japan Society for the Promotion of Science. References Aron, A.R., 2009. Introducing a special issue on stopping action and cognition. Neurosci. Biobehav. Rev. 33, 611–612. Aron, A., Poldrack, R., 2006. Cortical and subcortical contributions to stop signal response inhibition: role of the subthalamic nucleus. J. Neurosci. 26, 2424–2433. Aron, A.R., Dowson, J.H., Sahakian, B.J., Robbins, T.W., 2003a. Methylphenidate improves response inhibition in adults with attention–deficit/hyperactivity disorder. Biol. Psychiatry 54, 1465–1468. Aron, A.R., Fletcher, P.C., Bullmore, E.T., Sahakian, B.J., Robbins, T.W., 2003b. Stopsignal inhibition disrupted by damage to right inferior frontal gyrus in humans. Nat. Neurosci. 6, 115–116. Aron, A., Robbins, T., Poldrack, R., 2004. Inhibition and the right inferior frontal cortex. Trends Cogn. Sci. 8, 170–177. Aron, A., Behrens, T., Smith, S., Frank, M., Poldrack, R., 2007. Triangulating a cognitive control network using diffusion-weighted magnetic resonance imaging (MRI) and functional MRI. J. Neurosci. 27, 3743–3752. Badcock, J.C., Michie, P.T., Johnson, L., Combrinck, J., 2002. Acts of control in schizophrenia: dissociating the components of inhibition. Psychol. Med. 32, 287–297. Badry, R., Mima, T., Aso, T., Nakatsuka, M., Abe, M., Fathi, D., Foly, N., Nagiub, H., Nagamine, T., Fukuyama, H., 2009. Suppression of human cortico-motoneuronal excitability during the Stop-signal task. Clin. Neurophysiol. 120, 1717–1723. Baker, S.C., Frith, C.D., Frackowiak, R.S., Dolan, R.J., 1996. Active representation of shape and spatial location in man. Cereb. Cortex 6, 612–619. Barkley, R.A., 1997. Behavioral inhibition, sustained attention, and executive functions: constructing a unifying theory of ADHD. Psychol. Bull. 121, 65–94.

H. Tabu et al. / Neuroscience Research 70 (2011) 277–284 Bellgrove, M.A., Hester, R., Garavan, H., 2004. The functional neuroanatomical correlates of response variability: evidence from a response inhibition task. Neuropsychologia 42, 1910–1916. Bledowski, C., Prvulovic, D., Goebel, R., Zanella, F.E., Linden, D.E., 2004. Attentional systems in target and distractor processing: a combined ERP and fMRI study. Neuroimage 22, 530–540. Brett, M., Anton, J., Valabregue, R., Poline, J., 2002. Region of interest analysis using a SPM toolbox. In: Proceedings of the 8th International Conference on Functional Mapping of the Human Brain , Sendai Japan, abstract. Cai, W., Leung, H.C., 2009. Cortical activity during manual response inhibition guided by color and orientation cues. Brain Res. 1261, 20–28. Chamberlain, S.R., Fineberg, N.A., Blackwell, A.D., Robbins, T.W., Sahakian, B.J., 2006. Motor inhibition and cognitive flexibility in obsessive–compulsive disorder and trichotillomania. Am. J. Psychiatry 163, 1282–1284. Chambers, C., Bellgrove, M., Stokes, M., Henderson, T., Garavan, H., Robertson, I., Morris, A., Mattingley, J., 2006. Executive “brake failure” following deactivation of human frontal lobe. J. Cogn. Neurosci. 18, 444–455. Chen, C.Y., Muggleton, N.G., Tzeng, O.J., Hung, D.L., Juan, C.H., 2009. Control of prepotent responses by the superior medial frontal cortex. Neuroimage 44, 537–545. Chikazoe, J., Jimura, K., Hirose, S., Yamashita, K., Miyashita, Y., Konishi, S., 2009. Preparation to inhibit a response complements response inhibition during performance of a Stop-signal task. J. Neurosci. 29, 15870–15877. Cohen, J.D., Perlstein, W.M., Braver, T.S., Nystrom, L.E., Noll, D.C., Jonides, J., Smith, E.E., 1997. Temporal dynamics of brain activation during a working memory task. Nature 386, 604–608. Corbetta, M., Shulman, G.L., 2002. Control of goal-directed and stimulus-driven attention in the brain. Nat. Rev. Neurosci. 3, 201–215. Corbetta, M., Patel, G., Shulman, G.L., 2008. The reorienting system of the human brain: from environment to theory of mind. Neuron 58, 306–324. Courtney, S.M., 2004. Attention and cognitive control as emergent properties of information representation in working memory. Cogn. Affect. Behav. Neurosci. 4, 501–516. Courtney, S.M., Ungerleider, L.G., Keil, K., Haxby, J.V., 1996. Object and spatial visual working memory activate separate neural systems in human cortex. Cereb. Cortex 6, 39–49. Decary, A., Richer, F., 1995. Response selection deficits in frontal excisions. Neuropsychologia 33, 1243–1253. Dehaene, S., Kerszberg, M., Changeux, J.P., 1998. A neuronal model of a global workspace in effortful cognitive tasks. Proc. Natl. Acad. Sci. U.S.A. 95, 14529–14534. Deiber, M.P., Ibanez, V., Sadato, N., Hallett, M., 1996. Cerebral structures participating in motor preparation in humans: a positron emission tomography study. J. Neurophysiol. 75, 233–247. Duann, J.R., Ide, J.S., Luo, X., Li, C.S., 2009. Functional connectivity delineates distinct roles of the inferior frontal cortex and presupplementary motor area in stop signal inhibition. J. Neurosci. 29, 10171–10179. Dum, R.P., Strick, P.L., 1991. The origin of corticospinal projections from the premotor areas in the frontal lobe. J. Neurosci. 11, 667–689. Duncan, J., 2001. An adaptive coding model of neural function in prefrontal cortex. Nat. Rev. Neurosci. 2, 820–829. Duncan, J., Owen, A.M., 2000. Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends Neurosci. 23, 475–483. Eagle, D.M., Baunez, C., Hutcheson, D.M., Lehmann, O., Shah, A.P., Robbins, T.W., 2008. Stop-signal reaction-time task performance: role of prefrontal cortex and subthalamic nucleus. Cereb. Cortex 18, 178–188. Fillmore, M.T., Blackburn, J.S., Harrison, E.L., 2008. Acute disinhibiting effects of alcohol as a factor in risky driving behavior. Drug Alcohol Depend. 95, 97–106. Floden, D., Stuss, D., 2006. Inhibitory control is slowed in patients with right superior medial frontal damage. J. Cogn. Neurosci. 18, 1843–1849. Fried, I., Katz, A., McCarthy, G., Sass, K.J., Williamson, P., Spencer, S.S., Spencer, D.D., 1991. Functional organization of human supplementary motor cortex studied by electrical stimulation. J. Neurosci. 11, 3656–3666. Friston, K.J., Holmes, A.P., Poline, J.B., Grasby, P.J., Williams, S.C., Frackowiak, R.S., Turner, R., 1995. Analysis of fMRI time-series revisited. Neuroimage 2, 45–53. Friston, K.J., Penny, W.D., Glaser, D.E., 2005. Conjunction revisited. Neuroimage 25, 661–667. Garavan, H., Ross, T.J., Stein, E.A., 1999. Right hemispheric dominance of inhibitory control: an event-related functional MRI study. Proc. Natl. Acad. Sci. U.S.A. 96, 8301–8306. Gauggel, S., Rieger, M., Feghoff, T.A., 2004. Inhibition of ongoing responses in patients with Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 75, 539–544. Hampshire, A., Duncan, J., Owen, A.M., 2007. Selective tuning of the blood oxygenation level-dependent response during simple target detection dissociates human frontoparietal subregions. J. Neurosci. 27, 6219–6223. Hampshire, A., Thompson, R., Duncan, J., Owen, A.M., 2008. The target selective neural response—similarity, ambiguity, and learning effects. PLoS One 3, e2520. Hampshire, A., Thompson, R., Duncan, J., Owen, A.M., 2009. Selective tuning of the right inferior frontal gyrus during target detection. Cogn. Affect. Behav. Neurosci. 9, 103–112. Hampshire, A., Chamberlain, S.R., Monti, M.M., Duncan, J., Owen, A.M., 2010. The role of the right inferior frontal gyrus: inhibition and attentional control. Neuroimage 50, 1313–1319. Hon, N., Epstein, R.A., Owen, A.M., Duncan, J., 2006. Frontoparietal activity with minimal decision and control. J. Neurosci. 26, 9805–9809.

283

Ikeda, A., Yazawa, S., Kunieda, T., Ohara, S., Terada, K., Mikuni, N., Nagamine, T., Taki, W., Kimura, J., Shibasaki, H., 1999. Cognitive motor control in human pre-supplementary motor area studied by subdural recording of discrimination/selection-related potentials. Brain 122 (Pt 5), 915–931. Inase, M., Tokuno, H., Nambu, A., Akazawa, T., Takada, M., 1999. Corticostriatal and corticosubthalamic input zones from the presupplementary motor area in the macaque monkey: comparison with the input zones from the supplementary motor area. Brain Res. 833, 191–201. Isoda, M., 2005. Context-dependent stimulation effects on saccade initiation in the presupplementary motor area of the monkey. J. Neurophysiol. 93, 3016–3022. Isoda, M., Hikosaka, O., 2007. Switching from automatic to controlled action by monkey medial frontal cortex. Nat. Neurosci. 10, 240–248. Iversen, S.D., Mishkin, M., 1970. Perseverative interference in monkeys following selective lesions of the inferior prefrontal convexity. Exp. Brain Res. 11, 376–386. Jueptner, M., Stephan, K.M., Frith, C.D., Brooks, D.J., Frackowiak, R.S., Passingham, R.E., 1997. Anatomy of motor learning. I. Frontal cortex and attention to action. J. Neurophysiol. 77, 1313–1324. Klein, C., Wendling, K., Huettner, P., Ruder, H., Peper, M., 2006. Intra-subject variability in attention–deficit hyperactivity disorder. Biol. Psychiatry 60, 1088–1097. Konishi, S., Nakajima, K., Uchida, I., Kikyo, H., Kameyama, M., Miyashita, Y., 1999. Common inhibitory mechanism in human inferior prefrontal cortex revealed by event-related functional MRI. Brain 122 (Pt 5), 981–991. Leung, H.C., Cai, W., 2007. Common and differential ventrolateral prefrontal activity during inhibition of hand and eye movements. J. Neurosci. 27, 9893–9900. Levy, R., Goldman-Rakic, P.S., 2000. Segregation of working memory functions within the dorsolateral prefrontal cortex. Exp. Brain Res. 133, 23–32. Li, C.S., Huang, C., Constable, R.T., Sinha, R., 2006. Imaging response inhibition in a stop-signal task: neural correlates independent of signal monitoring and postresponse processing. J. Neurosci. 26, 186–192. Liddle, P., Kiehl, K., Smith, A., 2001. Event-related fMRI study of response inhibition. Hum. Brain Mapp. 12, 100–109. Linden, D.E., Prvulovic, D., Formisano, E., Vollinger, M., Zanella, F.E., Goebel, R., Dierks, T., 1999. The functional neuroanatomy of target detection: an fMRI study of visual and auditory oddball tasks. Cereb. Cortex 9, 815–823. Logan, G.D., Cowan, W.B., Davis, K.A., 1984. On the ability to inhibit simple and choice reaction time responses: a model and a method. J. Exp. Psychol. Hum. Percept. Perform. 10, 276–291. Matsuzaka, Y., Aizawa, H., Tanji, J., 1992. A motor area rostral to the supplementary motor area (presupplementary motor area) in the monkey: neuronal activity during a learned motor task. J. Neurophysiol. 68, 653–662. Menon, V., Adleman, N.E., White, C.D., Glover, G.H., Reiss, A.L., 2001. Error-related brain activation during a Go/NoGo response inhibition task. Hum. Brain Mapp. 12, 131–143. Miller, E.K., Cohen, J.D., 2001. An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202. Monterosso, J.R., Aron, A.R., Cordova, X., Xu, J., London, E.D., 2005. Deficits in response inhibition associated with chronic methamphetamine abuse. Drug Alcohol Depend. 79, 273–277. Morein-Zamir, S., Hommersen, P., Johnston, C., Kingstone, A., 2008. Novel measures of response performance and inhibition in children with ADHD. J. Abnorm. Child Psychol. 36, 1199–1210. Mostofsky, S., Simmonds, D., 2008. Response inhibition and response selection: two sides of the same coin. J. Cogn. Neurosci. 20, 751–761. Mostofsky, S.H., Schafer, J.G., Abrams, M.T., Goldberg, M.C., Flower, A.A., Boyce, A., Courtney, S.M., Calhoun, V.D., Kraut, M.A., Denckla, M.B., Pekar, J.J., 2003. fMRI evidence that the neural basis of response inhibition is task-dependent. Brain Res. Cogn. Brain Res. 17, 419–430. Nachev, P., Kennard, C., Husain, M., 2008. Functional role of the supplementary and pre-supplementary motor areas. Nat. Rev. Neurosci. 9, 856–869. Nakata, H., Sakamoto, K., Ferretti, A., Gianni Perrucci, M., Del Gratta, C., Kakigi, R., Luca Romani, G., 2008. Somato-motor inhibitory processing in humans: an eventrelated functional MRI study. Neuroimage 39, 1858–1866. Neubert, F.X., Mars, R.B., Buch, E.R., Olivier, E., Rushworth, M.F., 2010. Cortical and subcortical interactions during action reprogramming and their related white matter pathways. Proc. Natl. Acad. Sci. U.S.A. 107, 13240–13245. Nichols, T., Brett, M., Andersson, J., Wager, T., Poline, J.B., 2005. Valid conjunction inference with the minimum statistic. Neuroimage 25, 653–660. Oldfield, R.C., 1971. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9, 97–113. Picton, T.W., Stuss, D.T., Alexander, M.P., Shallice, T., Binns, M.A., Gillingham, S., 2007. Effects of focal frontal lesions on response inhibition. Cereb. Cortex 17, 826–838. Rizzolatti, G., Luppino, G., Matelli, M., 1996. The classic supplementary motor area is formed by two independent areas. Adv. Neurol. 70, 45–56. Rubia, K., Overmeyer, S., Taylor, E., Brammer, M., Williams, S., Simmons, A., Andrew, C., Bullmore, E., 1998. Prefrontal involvement in “temporal bridging” and timing movement. Neuropsychologia 36, 1283–1293. Rubia, K., Russell, T., Bullmore, E.T., Soni, W., Brammer, M.J., Simmons, A., Taylor, E., Andrew, C., Giampietro, V., Sharma, T., 2001. An fMRI study of reduced left prefrontal activation in schizophrenia during normal inhibitory function. Schizophr. Res. 52, 47–55. Rubia, K., Smith, A.B., Brammer, M.J., Taylor, E., 2003. Right inferior prefrontal cortex mediates response inhibition while mesial prefrontal cortex is responsible for error detection. Neuroimage 20, 351–358.

284

H. Tabu et al. / Neuroscience Research 70 (2011) 277–284

Rushworth, M.F., Hadland, K.A., Paus, T., Sipila, P.K., 2002. Role of the human medial frontal cortex in task switching: a combined fMRI and TMS study. J. Neurophysiol. 87, 2577–2592. Sakai, K., Hikosaka, O., Takino, R., Miyauchi, S., Nielsen, M., Tamada, T., 2000. What and when: parallel and convergent processing in motor control. J. Neurosci. 20, 2691–2700. Sasaki, K., Gemba, H., Tsujimoto, T., 1989. Suppression of visually initiated hand movement by stimulation of the prefrontal cortex in the monkey. Brain Res. 495, 100–107. Schachar, R., Tannock, R., Marriott, M., Logan, G., 1995. Deficient inhibitory control in attention deficit hyperactivity disorder. J. Abnorm. Child Psychol. 23, 411–437. Shallice, T., Burgess, P., 1996. The domain of supervisory processes and temporal organization of behaviour. Philos. Trans. R. Soc. Lond. B Biol. Sci. 351, 1405–1411, discussion 1411–1402. Shallice, T., Stuss, D.T., Picton, T.W., Alexander, M.P., Gillingham, S., 2008. Mapping task switching in frontal cortex through neuropsychological group studies. Front. Neurosci. 2, 79–85. Sharp, D.J., Bonnelle, V., De Boissezon, X., Beckmann, C.F., James, S.G., Patel, M.C., Mehta, M.A., 2010. Distinct frontal systems for response inhibition, attentional capture, and error processing. Proc. Natl. Acad. Sci. U.S.A. 107, 6106–6111. Simmonds, D.J., Fotedar, S.G., Suskauer, S.J., Pekar, J.J., Denckla, M.B., Mostofsky, S.H., 2007. Functional brain correlates of response time variability in children. Neuropsychologia 45, 2147–2157. Simmonds, D., Pekar, J., Mostofsky, S., 2008. Meta-analysis of Go/No-go tasks demonstrating that fMRI activation associated with response inhibition is taskdependent. Neuropsychologia 46, 224–232.

Solanto, M.V., Abikoff, H., Sonuga-Barke, E., Schachar, R., Logan, G.D., Wigal, T., Hechtman, L., Hinshaw, S., Turkel, E., 2001. The ecological validity of delay aversion and response inhibition as measures of impulsivity in AD/HD: a supplement to the NIMH multimodal treatment study of AD/HD. J. Abnorm. Child Psychol. 29, 215–228. Swann, N., Tandon, N., Canolty, R., Ellmore, T.M., McEvoy, L.K., Dreyer, S., DiSano, M., Aron, A.R., 2009. Intracranial EEG reveals a time- and frequency-specific role for the right inferior frontal gyrus and primary motor cortex in stopping initiated responses. J. Neurosci. 29, 12675–12685. Swick, D., Ashley, V., Turken, A.U., 2008. Left inferior frontal gyrus is critical for response inhibition. BMC Neurosci. 9, 102. Takada, M., Tokuno, H., Hamada, I., Inase, M., Ito, Y., Imanishi, M., Hasegawa, N., Akazawa, T., Hatanaka, N., Nambu, A., 2001. Organization of inputs from cingulate motor areas to basal ganglia in macaque monkey. Eur. J. Neurosci. 14, 1633–1650. van Boxtel, G.J., van der Molen, M.W., Jennings, J.R., Brunia, C.H., 2001. A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm. Biol. Psychol. 58, 229–262. van den Wildenberg, W.P., van Boxtel, G.J., van der Molen, M.W., Bosch, D.A., Speelman, J.D., Brunia, C.H., 2006. Stimulation of the subthalamic region facilitates the selection and inhibition of motor responses in Parkinson’s disease. J. Cogn. Neurosci. 18, 626–636. Verbruggen, F., Logan, G.D., 2008. Response inhibition in the stop-signal paradigm. Trends Cogn. Sci. 12, 418–424. Wager, T.D., Sylvester, C.Y., Lacey, S.C., Nee, D.E., Franklin, M., Jonides, J., 2005. Common and unique components of response inhibition revealed by fMRI. Neuroimage 27, 323–340.