Review
Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses

https://doi.org/10.1016/j.neubiorev.2014.11.003Get rights and content

Highlights

  • We delineated the key regions mediating supervisory attentional control.

  • Right anterior insula plays a central role in task set monitoring.

  • Right inferior frontal junction continuously reactivates the relevant task rule.

  • Posterior dorsomedial frontal cortex mediates energization of task schemata.

Abstract

The supervisory attentional system has been proposed to mediate non-routine, goal-oriented behaviour by guiding the selection and maintenance of the goal-relevant task schema. Here, we aimed to delineate the brain regions that mediate these high-level control processes via neuroimaging meta-analysis. In particular, we investigated the core neural correlates of a wide range of tasks requiring supervisory control for the suppression of a routine action in favour of another, non-routine one. Our sample comprised n = 173 experiments employing go/no-go, stop-signal, Stroop or spatial interference tasks. Consistent convergence across all four paradigm classes was restricted to right anterior insula and inferior frontal junction, with anterior midcingulate cortex and pre-supplementary motor area being consistently involved in all but the go/no-go task. Taken together with lesion studies in patients, our findings suggest that the controlled activation and maintenance of adequate task schemata relies, across paradigms, on a right-dominant midcingulo-insular-inferior frontal core network. This also implies that the role of other prefrontal and parietal regions may be less domain-general than previously thought.

Introduction

Flexible, adaptive behaviour requires continuous balancing between the initiation and inhibition of actions, such as when a prepotent response has to be suppressed in favour of a contextually appropriate one. Cognitive control of action is particularly important in the presence of a changing environment or the up-dating of goals and intentions (cf. Boehler et al., 2010, Schachar et al., 2007, Miller and Cohen, 2001). Norman and Shallice (1986) developed a theoretical framework for the implementation of goal-directed, non-routine behaviour against competing pre-dominant, routine responding. According to this framework, automatic or routine actions are based on the activation and implementation of a task schema that represents a learned sequence of input–output rules. Schemata can be activated by triggers, such as sensory input or the outcome of other schemata (Stuss et al., 1995). During well-learned routine behaviours, competition between schemata is controlled by lateral inhibition mechanisms, termed “contention scheduling.” However, the coordination of schemata with higher-level, overarching goals requires the additional employment of a “supervisory attentional system” (SAS), which exerts top-down control by deactivating certain schemata and activating others in the service of higher-order goals (cf. Alexander and Brown, 2010). The implementation of non-routine behaviour against predominant but inadequate response tendencies specifically relies on different sub-processes of the SAS that have been anatomically localized in the frontal cortex. In particular, lesion studies revealed a crucial role of the dorsomedial frontal cortex for energization, the process of initiating and sustaining the currently relevant task schema (cf. Stuss and Alexander, 2007). This sub-process would become necessary whenever a task schema needs to be activated that is not triggered automatically by perceptual and motivational input (cf. Shallice et al., 2008b). In contrast, patients with lesions in the left lateral prefrontal cortex (PFC) show deficits in task-setting, which sets the specific stimulus–response contingencies and is specifically required in the initial stages of learning a task (Shallice et al., 2008a, Shallice et al., 2008b). Right lateral PFC, on the other hand, has been associated with monitoring processes, such as continuously checking the appropriateness of the behavioural output (Stuss, 2006, Stuss, 2011).

Frequently used tasks that require participants to suppress a predominant response in favour of an appropriate, context-dependent one comprise the Stroop, flanker, Simon, stimulus–response compatibility (SRC), and antisaccade tasks as well as stop-signal and go/no-go tasks (cf. Diamond, 2013, Nee et al., 2007, Sebastian et al., 2013). All these tasks have very often been conceptualized as paradigms that tax inhibitory action control. Poor performance in these tasks has hence been commonly explained as a prefrontally mediated deficit in inhibiting the inappropriate response. However, recent evidence points to a more general role of the PFC in these tasks, being crucial for the active maintenance of task goals as well as the activation of the appropriate behavioural alternative (Everling and Johnston, 2013, Munakata et al., 2011).

In the present study, we aimed at isolating and functionally characterizing brain regions that are essential for the coordination between the inhibition of a predominant, inappropriate response and the activation of the goal-dependent one. We used coordinate-based activation likelihood estimation (ALE) meta-analyses (Eickhoff et al., 2009, Eickhoff et al., 2012, Turkeltaub et al., 2002, Turkeltaub et al., 2012) to integrate results from a diverse range of neuroimaging studies investigating the stop-signal, go/no-go, Stroop, flanker, SRC, antisaccade, and Simon tasks. All of these paradigms require cognitive control over a predominant response tendency and the context-dependent initiation of an appropriate behavioural alternative, that is, either to initiate an alternative, non-dominant response or not respond at all.

In go/no-go and stop-signal tasks, an increased automatic tendency to initiate a particular motor response is induced through a higher frequency of go trials, as compared with inhibition (i.e. no-go or stop) trials. The resulting action bias then has to be suppressed when presented with the inhibition signal during stop or no-go trials, respectively. While in the go/no-go task participants have to withhold a prepotent but not-yet initiated motor response, the stop-signal task requires cancelling an already initiated motor response (cf. Eagle et al., 2008, Schachar et al., 2007). In the other tasks, which can be subsumed under the term “incongruency tasks”, a given stimulus dimension interferes with relevant stimulus and/or response information, thereby affecting responses to the relevant information. According to the dimensional overlap model (Kornblum et al., 1990, Kornblum and Stevens, 2002), overlap between a (irrelevant) stimulus dimension and the response dimension results in an automatic translation of the stimulus feature into a response code. During congruent trials, the automatically activated response and the required one are one and the same. In contrast, during incongruent trials, the required response differs from the automatically activated one, thereby leading to an incongruency effect reflected in increased reaction times and error rates. Interestingly, it has been shown that the use of spatial as opposed to non-spatial information may lead to larger (in-)congruency effects in the context of some tasks. For example, Zeischka et al. (2010) investigated the congruency effect in different versions of the flanker task and found increased congruency effects when using arrows as stimuli, as compared to letters or colours. One possible explanation for this finding may be that the use of spatial information produces a simultaneous shift in both (perceptual) spatial attention and (motor) response activation on the ipsilateral side (Cieslik et al., 2010, Notebaert et al., 2001, Stoffer and Yakin, 1994).

Summarizing, we investigated four subcategories of cognitive action control. Action withholding was assessed with the go/no-go task that requires participants to withhold a prepotent but not yet initiated motor response. In contrast, the stop signal task investigates inhibition of an already initiated motor response, which can hence be conceptualized as action cancellation (cf. Eagle et al., 2008, Schachar et al., 2007). Interference control, finally, was investigated by means of congruency tasks that require participants to solve interference between competing response plans, by inhibiting the prepotent response and concurrently initiating the context-appropriate one. The latter were further subdivided into (non-spatial) Stroop versus spatial interference tasks (comprising Simon, SRC, antisaccade and spatial flanker tasks).

In a first step, we tested which brain regions are consistently associated with the four paradigm classes, that is, go/no-go, stop-signal, Stroop and spatial interference tasks. In a second step, we aimed to reveal those regions that are consistently activated whenever the task context requires inhibiting the predominant response and concurrently activating the appropriate task goal for initiating the adequate behaviour. We therefore performed a conjunction analysis across the thresholded ALE maps of all four task types. As all these four paradigm classes require (i) the suppression of actions that are inappropriate in a given context (ii) and the concurrent initiation of the context-appropriate behaviour, this approach should reveal those regions that are critical for the regulatory processes mediated by the SAS.

Section snippets

Paradigms included:

For our meta-analysis, neuroimaging results on the neural correlates of seven different tasks investigating cognitive control of actions were included, namely the Stroop, flanker, Simon, SRC, antisaccade, go/no-go and stop-signal tasks.

Stroop task: In the (standard) colour-word Stroop task (Stroop, 1935), participants are required to suppress a prepotent response, the reading of a word, in favour of a less dominant one, the naming of the ink colour in which the word is written. There are three

Meta-analysis of all included experiments

In a first step, we identified those brain regions that showed significant convergence across all 173 experiments. This main-effect revealed consistently increased activity in a bilateral frontoparietal network, consisting of anterior insula (aI) and adjacent inferior frontal gyrus (IFG), dorsolateral prefrontal cortex (DLPFC), dorsal premotor cortex (dPMC), as well as bilateral intraparietal sulcus (IPS) extending into superior parietal lobe (SPL). Moreover, convergent activity was found in

Discussion

We used coordinate-based ALE meta-analyses to analyze the neural correlates of cognitive action control in different paradigms that all require the suppression of an inappropriate action and the concurrent initiation and execution of the context-appropriate alternative. In total, 173 experiments investigating go/no-go, stop-signal, Stroop and spatial interference paradigms were included. While the main effect across all experiments, independent of task type, revealed a broad bilateral

Conclusion

In this study, we investigated the neural substrates of cognitive action control via coordinate-based ALE meta-analyses of brain activity reported for Stroop, spatial interference, stop-signal, and go/no-go tasks. Our study provides evidence for a pivotal role of the right aI and right IFJ in supervisory attentional control, because these were the only two regions consistently involved in all four paradigm classes, as revealed by a minimum conjunction analysis. Furthermore, aMCC and preSMA were

Acknowledgements

We thank all contacted authors who contributed results of relevant contrasts not explicitly reported in the original publications, and we apologize to all authors whose eligible papers we might have missed.

This study was supported by the Deutsche Forschungsgemeinschaft (DFG, EI 816/4-1; EI 816/6-1 and LA 3071/3-1.), the National Institute of Mental Health (R01-MH074457) and the European EFT program (Human Brain Project).

References (155)

  • M.W. Cole et al.

    The cognitive control network: integrated cortical regions with dissociable functions

    Neuroimage

    (2007)
  • M. Corbetta et al.

    The reorienting system of the human brain: from environment to theory of mind

    Neuron

    (2008)
  • B.E. Depue et al.

    Inhibitory control of memory etrieval and motor procssing associated with the right lateral prefrontal cortex: evidence from deficits in individuals with ADHD

    Neuopsychologia

    (2010)
  • J. Derrfuss et al.

    Cognitive control in the posterior frontolateral cortex: evidence from common activations in task coordination, interference control, and working memory

    Neuroimage

    (2004)
  • N.U. Dosenbach et al.

    A dual-networks architecture of top-down control

    Trends Cogn. Sci.

    (2008)
  • N.U.F. Dosenbach et al.

    A core system for the implementation of task sets

    Neuron

    (2006)
  • J. Duncan

    The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour

    Trends Cogn. Sci.

    (2010)
  • J. Duncan et al.

    Common regions of the human frontal lobe recruited by diverse cognitive demands

    Trends Neurosci.

    (2000)
  • S.B. Eickhoff et al.

    Activation likelihood estimation meta-analysis revisited

    Neuroimage

    (2012)
  • S.B. Eickhoff et al.

    Assignment of functional activations to probabilistic cytoarchitectonic areas revisited

    Neuroimage

    (2007)
  • S.B. Eickhoff et al.

    A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data

    Neuroimage

    (2005)
  • J.J. Geng et al.

    Re-evaluating the role of TPJ in attentional control: contextual updating?

    Neurosci. Biobehav. Rev.

    (2013)
  • C.R. Gillebert et al.

    Cytoarchitectonic mapping of attentional selection and reorienting in parietal cortex

    Neuroimage

    (2013)
  • J. Gottlieb

    From thought to action: the parietal cortex as a bridge between perception, action, and cognition

    Neuron

    (2007)
  • P.E. Hallett

    Primary and secondary saccades to goals defined by instructions

    Vision Res.

    (1978)
  • O. Jakobs et al.

    Effects of timing and movement uncertainty implicate the temporo-parietal junction in the prediction of forthcoming motor actions

    Neuroimage

    (2009)
  • E. Koechlin et al.

    An information theoretical approach to prefrontal executive function

    Trends Cogn. Sci.

    (2007)
  • B.D. McCandliss et al.

    The visual word form area: expertise for reading in the fusiform gyrus

    Trends Cogn. Sci.

    (2003)
  • W.H. Alexander et al.

    Computational models of performance monitoring and cognitive control

    Top. Cogn. Sci.

    (2010)
  • J.A. Alvarez et al.

    Executive function and the frontal lobes: a meta-analytic review

    Neuropsychol. Rev.

    (2006)
  • K. Amunts et al.

    Broca's region revisited: cytoarchitecture and intersubject variability

    J. Comp. Neurol.

    (1999)
  • A.R. Aron et al.

    Cortical and subcortical contributions to Stop signal response inhibition: role of the subthalamic nucleus

    J. Neurosci.

    (2006)
  • A.R. Aron et al.

    Inhibition of subliminally primed responses is mediated by the caudate and thalamus: evidence from functional MRI and Huntington's disease

    Brain: J. Neurol.

    (2003)
  • A.R. Aron et al.

    Stop signal inhibition disrupted by damage to right inferior frontal gyrus in humans

    Nat. Neurosci.

    (2003)
  • D. Badre et al.

    Is the rostro-caudal axis of the frontal lobe hierarchical?

    Nat. Rev. Neurosci.

    (2009)
  • A.D. Barber et al.

    Effects of working memory demand on neural mechanisms of motor response selection and control

    J. Cogn. Neurosci.

    (2013)
  • J.F. Bates et al.

    Prefrontal connections of medial motor areas in the rhesus monkey

    J. Comp. Neurol.

    (1993)
  • T.E. Behrens et al.

    Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging

    Nat. Neurosci.

    (2003)
  • M. Brass et al.

    Decomposing components of task preparation with functional magnetic resonance imaging

    J. Cogn. Neurosci.

    (2004)
  • R.L. Buckner et al.

    The brain's default network: anatomy, function, and relevance to disease

    Ann. N.Y. Acad. Sci.

    (2008)
  • P. Capotosto et al.

    Anatomical segregation of visual selection mechanisms in human parietal cortex

    J. Neurosci.

    (2013)
  • S. Caspers et al.

    The human inferior parietal lobule in stereotaxic space

    Brain Struct. Funct.

    (2008)
  • C. Cavada et al.

    Posterior parietal cortex in rhesus monkey: II. Evidence for segregated corticocortical networks linking sensory and limbic areas with the frontal lobe

    J. Comp. Neurol.

    (1989)
  • J. Chikazoe et al.

    Functional dissociation in right inferior frontal cortex during performance of go/no-go task

    Cereb. Cortex

    (2009)
  • H.J. Choi et al.

    Cytoarchitectonic identification and probabilistic mapping of two distinct areas within the anterior ventral bank of the human intraparietal sulcus

    J. Comp. Neurol.

    (2006)
  • E.C. Cieslik et al.

    Dissociating bottom-up and top-down processes in a manual stimulus–response compatibility task

    J. Neurophysiol.

    (2010)
  • M. Corbetta et al.

    Control of goal-directed and stimulus-driven attention in the brain

    Nat. Rev. Neurosci.

    (2002)
  • S.M. Courtney

    Attention and cognitive control as emergent properties of information representation in working memory

    Cogn. Affect. Behav. Neurosci.

    (2004)
  • A.D. Craig

    The sentient self

    Brain Struct. Funct.

    (2010)
  • F. Dambacher et al.

    A network approach to response inhibition: dissociating functional connectivity of neural components involved in action restraint and action cancellation

    Eur. J. Neurosci.

    (2014)
  • Cited by (0)

    View full text