Distinct frontal systems for response inhibition, attentional capture, and error processing

Division of Experimental Medicine, Imperial College London, London W12 0NN, United Kingdom.
Proceedings of the National Academy of Sciences (Impact Factor: 9.81). 03/2010; 107(13):6106-11. DOI: 10.1073/pnas.1000175107
Source: PubMed

ABSTRACT Stopping an action in response to an unexpected event requires both that the event is attended to, and that the action is inhibited. Previous neuroimaging investigations of stopping have failed to adequately separate these cognitive elements. Here we used a version of the widely used Stop Signal Task that controls for the attentional capture of stop signals. This allowed us to fractionate the contributions of frontal regions, including the right inferior frontal gyrus and medial frontal cortex, to attentional capture, response inhibition, and error processing. A ventral attentional system, including the right inferior frontal gyrus, has been shown to respond to unexpected stimuli. In line with this evidence, we reasoned that lateral frontal regions support attentional capture, whereas medial frontal regions, including the presupplementary motor area (pre-SMA), actually inhibit the ongoing action. We tested this hypothesis by contrasting the brain networks associated with the presentation of unexpected stimuli against those associated with outright stopping. Functional MRI images were obtained in 26 healthy volunteers. Successful stopping was associated with activation of the right inferior frontal gyrus, as well as the pre-SMA. However, only activation of the pre-SMA differentiated stopping from a high-level baseline that controlled for attentional capture. As expected, unsuccessful attempts at stopping activated the anterior cingulate cortex. In keeping with work in nonhuman primates these findings demonstrate that successful motor inhibition is specifically associated with pre-SMA activation.

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Available from: Xavier De Boissezon, Oct 17, 2014
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    • "A few studies with the stop task have attempted to control for attentional capture in healthy adult populations with different results. Sharp et al. (2010) added infrequent continue signals to the stop task to control for attentional capture. Brain activation for the control and successful inhibition conditions overlapped in the rIFG, with only activation in the pre-SMA being uniquely associated with inhibition. "
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    ABSTRACT: The stop-signal task has been used extensively to investigate the neural correlates of inhibition deficits in children with ADHD. However, previous findings of atypical brain activation during the stop-signal task in children with ADHD may be confounded with attentional processes, precluding strong conclusions on the nature of these deficits. In addition, there are recent concerns on the construct validity of the SSRT metric. The aim of this study was to control for confounding factors and improve the specificity of the stop-signal task to investigate inhibition mechanisms in children with ADHD. FMRI was used to measure inhibition related brain activation in 17 typically developing children (TD) and 21 children with ADHD, using a highly controlled version of the stop-signal task. Successful inhibition trials were contrasted with control trials that were comparable in frequency, visual presentation and absence of motor response. We found reduced brain activation in children with ADHD in key inhibition areas, including the right inferior frontal gyrus/insula, and anterior cingulate/dorsal medial prefrontal cortex. Using a more stringent controlled design, this study replicated and specified previous findings of atypical brain activation in ADHD during motor response inhibition. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
    Psychiatry Research: Neuroimaging 07/2015; DOI:10.1016/j.pscychresns.2015.07.007 · 2.83 Impact Factor
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    • "Moreover, we have previously shown that repetitive transcranial magnetic stimulation over the rIFG induces faster response inhibition (Zandbelt et al., 2013a), providing additional evidence in support of the notion that this region is involved in the detection of a salient stop-signal (i.e. the automatic stopping of the white bar moving ). Our finding is also in line with previous studies revealing the importance of the rIFG for the detection of task-relevant stimuli (Duann et al., 2009; Hampshire et al., 2010; Sharp et al., 2010). Furthermore, the rIFG and rIPC are known for their role in working memory needed for flexible adjustments of actions based on context (Nee & Brown, 2013). "
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    ABSTRACT: The subjective belief of what will happen plays an important role across many cognitive domains, including response inhibition. However, tasks that study inhibition do not distinguish between the processing of objective contextual cues indicating stop-signal probability and the subjective expectation that a stop-signal will or will not occur. Here we investigated the effects of stop-signal probability and the expectation of a stop-signal on proactive inhibition. Twenty participants performed a modified stop-signal anticipation task while being scanned with functional magnetic resonance imaging. At the beginning of each trial, the stop-signal probability was indicated by a cue (0% or > 0%), and participants had to indicate whether they expected a stop-signal to occur (yes/no/don't know). Participants slowed down responding on trials with a > 0% stop-signal probability, but this proactive response slowing was even greater when they expected a stop-signal to occur. Analyses were performed in brain regions previously associated with proactive inhibition. Activation in the striatum, supplementary motor area and left dorsal premotor cortex during the cue period was increased when participants expected a stop-signal to occur. In contrast, activation in the right inferior frontal gyrus and right inferior parietal cortex activity during the stimulus-response period was related to the processing of contextual cues signalling objective stop-signal probability, regardless of expectation. These data show that proactive inhibition depends on both the processing of objective contextual task information and the subjective expectation of stop-signals. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
    European Journal of Neuroscience 04/2015; 41(8). DOI:10.1111/ejn.12879 · 3.67 Impact Factor
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    • "Clinical studies have put this component forward as a strong candidate for cortical area responsible for cognitive control [72], [73]. This area was also implicated in maintaining attention [67], [74]–[76]. Further, some studies have identified bilateral inferior frontal junction (IFJ) in the detection of visual motion whereas color detection preferentially engaged right IFJ [18], [77]. Other studies also identified hemispheric differences in IFJ activity using visual stimuli in that different fronto-parietal regions were found to be involved in attention to motion versus color features [78], [79]. "
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    ABSTRACT: Memory encoding engages multiple concurrent and sequential processes. While the individual processes involved in successful encoding have been examined in many studies, a sequence of events and the importance of modules associated with memory encoding has not been established. For this reason, we sought to perform a comprehensive examination of the network for memory encoding using data driven methods and to determine the directionality of the information flow in order to build a viable model of visual memory encoding. Forty healthy controls ages 19-59 performed a visual scene encoding task. FMRI data were preprocessed using SPM8 and then processed using independent component analysis (ICA) with the reliability of the identified components confirmed using ICASSO as implemented in GIFT. The directionality of the information flow was examined using Granger causality analyses (GCA). All participants performed the fMRI task well above the chance level (>90% correct on both active and control conditions) and the post-fMRI testing recall revealed correct memory encoding at 86.33±5.83%. ICA identified involvement of components of five different networks in the process of memory encoding, and the GCA allowed for the directionality of the information flow to be assessed, from visual cortex via ventral stream to the attention network and then to the default mode network (DMN). Two additional networks involved in this process were the cerebellar and the auditory-insular network. This study provides evidence that successful visual memory encoding is dependent on multiple modules that are part of other networks that are only indirectly related to the main process. This model may help to identify the node(s) of the network that are affected by a specific disease processes and explain the presence of memory encoding difficulties in patients in whom focal or global network dysfunction exists.
    PLoS ONE 10/2014; 9(10):e107761. DOI:10.1371/journal.pone.0107761 · 3.23 Impact Factor
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