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Ann. N.Y. Acad. Sci. ISSN 0077-8923

A N N A L S O F T H E N E W Y O R K A C A D E M Y O F S C I E N C E SIssue: The Year in Cognitive Neuroscience

Cognitive control and right ventrolateral prefrontal cortex:

reflexive reorienting, motor inhibition, and action updatingBenjamin J. Levy1 and Anthony D. Wagner1,2

1Department of Psychology and 2Neurosciences Program, Stanford University, Stanford, California

Address for correspondence: Benjamin J. Levy, Department of Psychology, Stanford University, Jordan Hall, Building 420, MC

2130, Stanford, CA 94305. [email protected]

Delineating the functional organization of the prefrontal cortex is central to advancing models of goal-directed

cognition. Considerable evidence indicates that specific forms of cognitive control are associated with distinct

subregions of the left ventrolateral prefrontal cortex (VLPFC), but less is known about functional specialization

within the right VLPFC. We report a functional MRI meta-analysis of two prominent theories of right VLPFC

function: stopping of motor responses and reflexive orienting to abrupt perceptual onsets. Along with a broader

review of right VLPFC function, extant data indicate that stopping and reflexive orienting similarly recruit the

inferior frontal junction (IFJ), suggesting thatIFJ supports the detection of behaviorally relevant stimuli. By contrast,

other right VLPFC subregions are consistently active during motor inhibition, but not reflexive reorienting tasks,

with posterior-VLPFC being active during the updating of action plans and mid-VLPFC responding to decision

uncertainty. These results highlight the rich functional heterogeneity that exists within right VLPFC.

Keywords: response inhibition; reorienting; inferior frontal gyrus; fMRI

In many situations, input from the environment issufficient to drive cognition in a bottom-up fashionresulting in the production of appropriate behav-ior. At other times, such prepotent responses arenot contextually appropriate, and we must exerttop-down control to shape cognition and achievea desired behavior. The prefrontal cortex (PFC) isthought to enable top-down control by biasing pro-cessing in other brain regions toward contextually

appropriate representations.13

Extensive evidenceindicates that PFC-mediated cognitive control en-compasses a wide range of specific operations.410

For example, upon hearing a phone ring you mustdecide whether to (a) execute the motor actionsinvolved in answering your phone, (b) resist theinappropriate urge to answer your friends phone,(c) attempt to ignore the sound as an auditory dis-traction, or (d) quickly attempt to silence your cellphone in order to minimize your embarrassment atthe talk you are attending.

The lateral PFC consists of multiple subre-gions that differ in their cytoarchitectonics and

their patterns of connectivity with posterior cor-tical sites.5,1013 Remarkable progress has beenmade in the last two decades toward understand-ing the function-to-structure mapping that consti-tutes lateral PFCs macroscopic functional organi-zation.1424 This body of research suggests that PFCis a heterogeneous structure with distinct subre-gions relating to specific cognitive control opera-tions. Progress has also been made in understanding

the broader principles of PFC organization, such asthe possibility that PFC is hierarchically organizedalong its rostro-caudal axis, with higher-order goalsencoded by more anterior regions and increasinglyspecific subgoals encoded as one moves posteriorlythrough PFC.18,2534

Importantly, for present purposes, key advanceshave arisen from an extensive literature focused onthe organization of left ventrolateral PFC (VLPFC),with extant data documenting functional distinc-tions between the anterior (Brodmanns area [BA]

47), mid- (BA 45), and posterior (BA 44) subregionsof left VLPFC.21,22,3440 By contrast, considerably

doi: 10.1111/j.1749-6632.2011.05958.x

40 Ann. N.Y. Acad. Sci. 1224 (2011) 4062 c 2011 New York Academy of Sciences.


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Levy & Wagner Cognitive control and right ventrolateral PFC

less is known about the functional organizationof right PFC, and, in particular, it remains largelyunclear whether the specific subdivisions of rightVLPFC are functionally distinct and, if so, how tocharacterize their underlying computations.

While right VLPFC function is not well un-derstood, neuroimaging studies employing variouscognitive tasks have implicated this region as a crit-ical substrate of control. At present, two prominenttheories feature right VLPFC as a key functional re-gion. From one perspective, right VLPFC is thoughtto play a critical role in motor inhibition, wherecontrol is engaged to stop or override motor re-sponses.41 Consistent with this view, neuroimagingstudies of tasks thought to require motor inhibition

typically reveal activation in right VLPFC, amongother regions.4244 In addition, patients with dam-age to the inferior extent of right PFC take longer tooverride a prepotent response compared to healthyadults or even patients with damage to other PFCsubregions.45 Based on this evidence, Aron et al.41

argued that right VLPFC plays a critical role in mo-tor inhibition.

Alternatively, Corbetta and Shulman46,47 have ad-vanced the hypothesis that there are two distinctfrontoparietal networks involved in spatial atten-

tion, with right VLPFC being a component of aright-lateralized ventral attention network that gov-erns reflexive reorienting. From this perspective,right lateral PFC, along with a region spanning righttemporoparietal junction and the inferior parietallobule, are engaged when abrupt onsets occur in theenvironment, suggesting that these regions are in-volved in reorienting attention to perceptual eventsthat occur outside the current focus of attention.While much of the research brought to bear in sup-

port of this theoretical framework has focused onactivity within lateral parietal cortex, the perfor-mance of tasks thought to tap reflexive reorientingalso typically gives rise to robust right lateral PFCac-tivation.a Nevertheless, the precise operations me-

a Both TPJ and lateral PFC are engaged during atten-

tional reorienting and analyses of resting state activity

indicate that these regions demonstrate functionally cor-

related responses,48,49 which suggests that these regions

act as part of a functional network. Importantly, though,

recent data have shown that TPJ and lateral PFC show

distinct patterns of activity across different orienting de-

Figure 1. Anatomical divisions within the ventrolateral pre-

frontal cortex (VLPFC). VLPFC, or inferior frontal gyrus, isbounded superiorly by the inferior frontal sulcus (green) and

inferiorly by the lateral sulcus (blue). Cytoarchitectonic and

connectivity patterns,1113 as well as neuroimaging dissocia-

tions within the left hemisphere,21,22,3440 suggest functional dis-

tinctions between three distinct subregions within VLPFC. The

most caudal extent (A), which we refer to as posterior-VLPFC, is

bounded by the precentral sulcus (red) and the ascendingramus

ofthelateralsulcus(orange).Thisregioncorrespondsroughlyto

theregionreferred to as pars opercularis or Brodmann area (BA

44). Rostral to theascending ramus (orange) is mid-VLPFC (B),

which corresponds roughly to pars triangularis or BA 45. The

horizontal ramus of the lateral sulcus (yellow) separates mid-

VLPFC from anterior-VLPFC (C), which roughly corresponds

toparsorbitalis or BA47. Inaddition to these three VLPFC sub-

regions, recent evidence also suggests that there may be another

distinct functionalsubregion7274 that falls at themost posterior

andsuperior regionof VLPFC,whereVLPFCintersectswith the

middle frontal gyrus dorsally and the premotor cortex caudally.

This region (D) is referred to as the inferior frontal junction

(IFJ) and is situated at the intersection of the posterior end

of the inferior frontal sulcus (green) and the precentral sulcus

(red).

diated by right VLPFC in response to abrupt onsets

remain unclear.The motor inhibition and reflexive reorientingframeworks have gained traction in the last decadeand have guided an explosion of functional imagingresearch.44,5171 The prominence of these theorieshas also motivated reverse inferences, wherein rightVLPFC activation in a given task is attributed to ei-ther engagement of motor inhibition or attentionalorienting processes. At present, however, it is un-clear whether these two frameworks implicate the

mands,50 suggesting that these regions may play distinct

functional roles during reorienting.

Ann. N.Y. Acad. Sci. 1224 (2011) 4062 c 2011 New York Academy of Sciences. 41


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Cognitive control and right ventrolateral PFC Levy & Wagner

same or distinct subregions within right lateral PFC(Fig.1),and,ataprocesslevel,itisunclearhowthesetwo frameworks relate to each other. One possibilityis that the VLPFC activity observed during one setof tasks can be explained in terms of the other pu-

tative control mechanism. For example, recent datasuggest that stopping tasks often confound motorinhibition with the need to orient to behaviorallyrelevant cues and that this orienting response maybe what drives right VLPFC engagement when stop-ping is required.70,71 Alternatively, tasks designed totarget reflexive reorienting might also involve somedemands on motor inhibition.75

Here we examine the relationship between thesetwo theories of right PFC function by performing

a meta-analysis of the functional magnetic reso-nance imaging (fMRI) literatures on motor inhi-bition and reflexive reorienting. The goal is to de-termine whether distinct PFC subregions respondsimilarly or differently to these two different typesof cognitive control tasks. The results are then con-sidered within the context of the broader empiricalliterature, as many behavioral tasks beyond those inthe meta-analysis lead to the recruitment of rightVLPFC. From the current findings and our reviewof the literature, we then provide initial conclusions

about the nature of functional heterogeneity withinright VLPFC, with the ultimate goal of sparking fu-ture empirical work that will test these emerginghypotheses about the role of right VLPFC in cogni-tive control.

Meta-analysis of motor inhibition andreflexive reorienting

Study selectionFor each domain we selected two tasks that are typ-ically used to study the putative mechanism. Theo-ries of motor inhibition rely on the Go/No-Go andStop Signal tasks as evidence for the involvement ofright VLPFC in stopping (see Fig. 2A for explana-tion of these tasks). There have already been severalmeta-analyses of these tasks,7680 providing a start-ingpool of studies that wasthen augmented throughan additional literature search. Moreover, becausewe employed somewhat different screening criteriarelative to prior meta-analyses, some studies present

in earlier reviews were excluded here. In particular,the inclusion/exclusion criteria for Go/No-Go andStop Signal studies were as follows.

Figure 2. Behavioral tasks used to study motor inhibition and

reflexive reorienting. (A) Motor inhibition is typically studied

using either the Go/No-Go or Stop Signal task. In the Go/No-

Go task, subjects see a stream of centrally presented stimuli and

must make a button-press for every stimulus except one, theno-

go stimulus (here shown as an X). Behavioral performance is

measured by the subjects ability to withhold their response on

theno-gotrials.IntheStopSignaltask,subjectsalsoseeastream

of centrallypresented stimuli andtypically mustmake a decision

about each stimulus (e.g., is the arrow pointing right or left?).

On a minority of trials a stop signal (e.g., a tone) is presented,indicating that the subject should withhold their response on

that trial. Behavioral performance is assessed by computing a

stop signal reaction time (SSRT), which provides an estimate

of how long it takes to cancel an initiated movement. In both

motor inhibition tasks, brain activity putatively associated with

motor inhibition is measured by contrasting activity during the

inhibition trials (no-go and Stop Signal) with activity during go

trials. (B) Reflexive reorienting is typically studied using either

the Posner Cueing or Oddball task. In the Posner Cueing task,

a cue orients subjects to attend to one of two spatial positions.

Then the subject is asked to make a judgment about a stimulus

when it appears (e.g., is the letter an L or an X?). On valid

trials subjects are correctly cued to the spatial position wherethe target will appear, but on infrequent invalid trials they are

instructed to attendto thewrong position.The behavioral index

of attentional engagement in this paradigm is that subjects are

typically slower to respond on invalidly cued trials than dur-

ing validly cued trials. Brain activity putatively associated with

attentional capture is assessed by contrasting activity during

invalid trials with activity during valid trials. In the Oddball

task, subjects are asked to attend to a stream of stimuli. Most

trials present the same standard stimulus, but infrequently

an oddball appears and this requires subjects to press a button

to note its occurrence. Behavioral performance is measured by

the subjects ability to detect these oddballs and brain activity

putatively associated with attentional capture is measured by

contrasting activity in response to the oddballs compared to

when the standards are presented.



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(1) Similar to earlier meta-analyses, we only in-cluded studies of healthy, young adults thatreported whole-brain group-level coordinatesin a standardized coordinate space (Talairachor MNI).

(2) We required that studies contrast activity dur-ing stopping trials (no-go or Stop Signal tri-als) with go trials, excluding studies that sim-ply contrasted stopping trials with baselineactivity.

(3) We excluded Go/No-Go studies where theidentity of the no-go stimulus was defined bythe prior trial history.81 In these studies, sub-jects had to avoid responding whenever a par-ticular stimulus repeats within the context of a

regularly alternating sequence. While this vari-ant shares many similarities with other Go/No-Go studies, it requires additional cognitive op-erations not present in the typical versions(e.g., maintaining a working memory load),which complicates the interpretation of thesecontrasts and lessens their similarity to otherGo/No-Go studies.

(4) The current meta-analysis included studiesthat used oculomotor or vocal responses, inaddition to the more prevalent manual button

responses, although these were few in number.Excluding these studies did not change any ofour conclusions.

(5) Also included areblocked designs whereblocksof intermixed go and no-go trials were con-trasted with activity during blocks of only gotrials.

These selection criteria yielded a set of 49 motorinhibition contrasts, including 32 Go/No-Go con-

trasts and 17 Stop Signal contrasts (Table 1).We performed a similar literature search for thereflexive reorienting domain. In support of the in-volvement of right PFC in attentional orienting,Corbetta and Shulman46,47 cite evidence from theOddball and Posner Cueing paradigms (see Fig. 2Bfor explanation of these tasks). There have beenprior meta-analyses of the reflexive reorienting lit-erature,113115 although those papers restricted theiranalyses to parietal cortex. The set of studies cited inthose papers were used as an initial base for the cur-

rent set, which was then augmented with a literaturesearch. The inclusion/exclusion criteria for Oddballand Posner Cueing studies were as follows.

(1) As above, we only included studies of healthy,

young adults that reported whole-brain group-level coordinates in a standardized coordinatespace.

(2) For the Posner Cueing tasks, we only included

studies that reported the direct contrast of in-validly cued trials with validly cued trials.

(3) The Oddball task was the only task where weallowed a comparison of the critical condition,oddball targets that requireda motor response,with an unmodeled baseline, since the typicalanalysis approach in these studies was to notmodel responses to the standards.

(4) In the Oddball task, we excluded contrasts thatexamined activity for oddballs that did not re-

quire a behavioral response.(5) Along with the typical oddball versus targetcontrasts, we also included two Go/No-Goparadigms that contrasted infrequent-go tri-als with frequent-go trials,68,116 as these trialswere behaviorally infrequent oddballs withinthe context of a task that nevertheless requireda response.

These selection criteria produced a set of 38reflexive reorienting contrasts, including 25 Odd-

ball contrasts and 13 Posner Cueing contrasts(Table 2).

Meta-analytic approachSelected contrasts were submitted to activationlikelihood estimation (ALE) analyses to determinewhether there was spatial convergence in the peaksof activation across a given set of studies. First, allfoci were converted into the same coordinate system(MNI), with studies reported in Talairach space be-ing converted using Ginger ALEs Talairach to MNI

(SPM) transform.139

Second, since the foci/peaksfrom each study provide an imperfect localizationof the activated region, these foci were smoothedby a three-dimensional Gaussian function to cre-ate localization probability distributions.140 The de-gree of uncertainty associated with each peak wasdetermined by the sample size of the study,141 aslarger samples should yield more stable estimates ofactive regions. Third, the union of these probabil-ity distributions was obtained to create a mod-eled activation map for each individual contrast.

These modeled activation maps represent the like-lihood that each voxel reflects a true peak ofactivation from that study. Fourth, topographic



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Table 1. Studies included in the motor inhibition meta-analysis

First Author Year Task Task demands

Altshuler82 2005 Go/No-Go Response uncertainty

Asahi83 2004 Go/No-Go Response uncertainty

Blasi53 2006 Go/No-Go Response uncertainty

Booth84 2003 Go/No-Go Response uncertainty

Bunge85 2002 Go/No-Go Response uncertainty

Falconer86 2008 Go/No-Go Response uncertainty

Horn87 2003 Go/No-Go Response uncertainty

Kaladjiana,88 2009 Go/No-Go Response uncertainty

Kaladjian89 2009 Go/No-Go Response uncertainty

Konishi90 1998 Go/No-Go Response uncertainty

Konishi91 1999 Go/No-Go Response uncertainty

Laurens92 2005 Go/No-Go Response uncertainty

Lawrence

93

2009 Go/No-Go Response uncertainty Liddle94 2001 Go/No-Go Response uncertainty

Maguire95 2003 Go/No-Go Response uncertainty

Mazzola-Pomietto 96 2009 Go/No-Go Response uncertainty

Menon43 2001 Go/No-Go Response uncertainty

Mobbs97 2007 Go/No-Go Response uncertainty

Rubia98 2005 Go/No-Go Response uncertainty

Rubia99 2006 Go/No-Go Response uncertainty

Watanabe100 2002 Go/No-Go Response uncertainty

Brown101 2006 Go/No-Go N/A

Brown102 2008 Go/No-Go N/A

Roth103

2007 Go/No-Go N/AWager104 2005 Go/No-Go N/A

Chikazoe68 2009 Go/No-Go Response override

de Zubicaray105 2000 Go/No-Go Response override

Durston106 2002 Go/No-Go Response override

Maltby107 2005 Go/No-Go Response override

McNab62 2008 Go/No-Go Response override

Zheng65 2008 Go/No-Go Response override

Aron44 2006 Stop Signal Response override

Aron57 2007 Stop Signal Response override

Caia,66 2009 Stop Signal Response override

Chamberlain108 2009 Stop Signal Response overrideChevrier58 2007 Stop Signal Response override

Chikazoe67 2009 Stop Signal Response override

Cohen109 2010 Stop Signal Response override

Leung110 2007 Stop Signal Response override

McNab62 2008 Stop Signal Response override

Ramautar111 2006 Stop Signal Response override

Sharp71 2010 Stop Signal Response override

Vink112 2005 Stop Signal Response override

Xueb,64 2008 Stop Signal Response override

Zheng65 2008 Stop Signal Response override

aContributed two contrasts.bContributed three contrasts.

N/A: not applicable.



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Table 2. Studies included in the reflexive reorienting

meta-analysis

First Author Year Task

Arrington

75

2000 Posner cueingCorbetta117 2002 Posner cueing

Doricchi118 2010 Posner cueing

Giessing119 2006 Posner cueing

Indovina59 2007 Posner cueing

Kincade120 2005 Posner cueing

Macalusoa,121 2002 Posner cueing

Macaluso60 2007 Posner cueing

Mayer54 2006 Posner cueing

Thiel51 2004 Posner cueing

Thiel122 2005 Posner cueing

Vossel55 2006 Posner cueingBledowski123 2004 Oddball

Brazdil124 2007 Oddball

Bryant125 2005 Oddball

Chikazoe68 2009 Oddball

Clark126 2000 Oddball

Gur127 2007 Oddball

Gur128 2007 Oddball

Kiehl129 2001 Oddball

Kiehl130 2005 Oddball

Lawrence

93

2009 OddballLiddle131 2006 Oddball

Lindenb,132 1999 Oddball

Menon133 1997 Oddball

Mulert134 2004 Oddball

Muller135 2003 Oddball

Ngana,136 2003 Oddball

Stevensa,61 2000 Oddball

Wolf137 2008 Oddball

Yoshiuraa,138 1999 Oddball

a

Contributed two contrasts.bContributed four contrasts.

convergence across a set of similar contrasts wasassessed by calculating an ALE score, which reflectsthe union of probabilities across all of the studiesin a given set, for each individual voxel. In order todetermine whether this set of contrasts shows morespatial clustering than would be expected by a ran-dom distribution of a similar number of peaks, this

ALE map was tested against the null hypothesis thatthere is no convergence across the individual con-trasts.141 This was done by creating a similar union

of probabilities across the full set of studies, butwhere each modeled activation map was sampledfrom a random spatial location. Fifth, the resultingALE maps were thresholded at P < 0.05 (clustercorrected for multiple comparisons). All analyses

were performed using theGingerALEsoftware(ver-sion 2.0.4), using the standard default parameters(http://brainmap.org/ale/).

Right VLPFC convergence and divergenceWe began by first performing an ALE analysis foreach of the two primary domains: motor inhibitionand reflexive orienting.Subsequently, we considereddifferences between the regions associated with thetwo domains and within-domain task differences.

Motorinhibitionmeta-analysis. Collapsingacrossboth types of stopping tasks revealed a large clus-ter of activity within right lateral PFC that includedportions of the inferior and middle frontal gyri,extending into the frontal operculum (FO) and an-terior insula (AI; Fig. 3 and Table 3). In additionto this right PFC cluster, smaller clusters of activ-ity were observed in left PFC, including the poste-rior extent of the inferior frontal sulcus, the middlefrontal gyrus, the FO, and AI. While this suggeststhat PFC activity during stopping is not strictly lat-eralized,80 the effects were more robust on the right;the spatially extensive right VLPFC response, whichincluded portions of both pars opercularis (BA 44)

and pars triangularis (BA 45), was absent on the left.In addition to effects in lateral PFC, there were

additional regions that showed consistent across-study activation, including the medial surface ofPFC, encompassing the presupplementary motorarea (preSMA) and anterior cingulatecortex (ACC),right inferior parietal lobule, and bilateral intrapari-

etal sulcus. While these regions are not the primaryfocus of the current paper, understanding the mech-anistic role of right VLPFC will necessarily involvefuture analyses of the full networks recruited bythese tasks (a point to which we later return). In-terestingly, we also observed a subcortical region ofactivation that is consistent with the involvement ofthe right subthalamic nucleus during stopping.44

Reflexive reorienting meta-analysis. The reflexivereorienting tasks also activated regions within right

lateral PFC. In particular, consistent across-studyactivation was present in the right inferior frontaljunction (IFJ), middle frontal gyrus, and within the



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Figure 3. Meta-analysis of motor inhibition and reflexive reorienting tasks. The top two rows display the activation likelihood

estimate (ALE) maps for motor inhibition tasks, collapsing across Go/No-Go and Stop Signal tasks, and reflexive reorienting tasks,

collapsing across Posner Cueing and Oddball tasks (thresholded at P< 0.05, cluster corrected for multiple comparisons). At the

bottom is a voxel-wise map of the difference score between the two unthresholded ALE maps. This image is arbitrarily thresholded

(at 0.0125) to show voxels where there are large differences in the two ALE maps; accordingly, this map provides qualitative leverage

on possible differences between conditions but does not constitute a formal statistical comparison. On the axial slices, specific right

VLPFC subregions are labeled: anterior insula (A), posterior-VLPFC (B), mid-VLPFC (C), inferior frontal junction (D), middle

frontal gyrus (E), and presupplementary motor area (F).

AI (Fig. 3 and Table 4). In addition to these rightlateral frontal regions, significant clusters were ob-served in left IFJ, ACC, and bilateral inferior parietallobule.

Differences between motor inhibition and reflex-

ive reorienting. The overall pattern of activity forthe two domains was rather similar. Both elicited

primarily right-lateralized frontoparietal responses.Within PFC, both task domains led to robust activ-ity within right IFJ. At the same time, there appearto be differences in other regions of PFC. Most no-tably, the lateral surface of right VLPFC, includingpars opercularis and pars triangularis, was robustlymodulated by thestoppingtasks,but notby reflexivereorienting tasks. This remained the case even whenmatching the number of contrasts in the two typesof comparisons at 38 by randomly subsampling themotor inhibition contrasts. While our analysis ap-

proach did not support direct statistical compar-isons between tasks,141 for visualization purposeswe also computed the raw difference scores between

the two respective ALE maps (Fig. 3). Considerationof these arbitrarily thresholded difference maps sug-gested that the right VLPFC activation likelihoodmeasures markedly differed between stopping andorienting. This direct comparison also revealed thatwhile FO/AI and middle frontal gyrus were consis-tently recruited by both tasks, these regions may bemore reliably recruited by stopping tasks.

Within-domain task differences. While the pre-ceding analyses pooled data across two tasks for eachdomain, there are important distinctions betweenthe two classes of tasks within each domain. In par-ticular, different motor inhibition tasks may not in-volve the same type of stopping.78,142144 Some stop-ping tasks require the subject to override a specificmotorresponse,suchasintheStopSignalparadigm,where a subject typically has around 200300 msto initiate their button press prior to onset of the

stop signal. By contrast, other stopping tasks do notappear to require subjects to override an alreadyinitiated response. Specifically, in many imaging



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Table 3. Frontal regions that respond during motor inhibition tasks (Go/No-Go and Stop Signal)

Anatomical label BA x y z Volume (mm3)

R anterior insula 13 40 18 0 22056

R posterior-VLPFC 44 48 16 18R middle frontal gyrus 9/46 30 40 28

R mid-VLPFC 45 48 28 18

R inferior frontal junction 6/9/44 44 14 34

R middle frontal gyrus 9/46 26 50 28



R dorsal premotor cortex 6 40 2 46


R presupplementary motor area 6 6 16 50 5496

R presupplementary motor area 6 14 16 58

R anterior cingulate 32 6 24 36L anterior insula 13 42 16 6 3624

L anterior insula 13 32 20 4

L middle frontal gyrus 9/46 36 38 24 2416

L inferior frontal junction 6/9/44 46 10 28 1088

L presupplementary motor area 6 6 2 60 520


L middle frontal gyrus/frontal pole 9/10/46 38 54 20 176

L dorsal premotor cortex 6 26 2 52 120

studies of the Go/No-Go task, there is an equal like-lihood that a trial will contain a Go or No-Go stim-ulus. In equiprobable Go/No-Go tasks, it is unclearto what degree subjects engage in response prepara-tion before the stimulus appears. To the extent thatsubjects either fail to initiate a motor response orprepare both potential motor responses, the natureof stopping in equiprobable Go/No-Go tasks islikely to be quite different from that in tasks wheresubjects must override a specific initiated action.Therefore, we divided the motor inhibition tasksinto (a) tasks where subjects had a clear expectedmotor response that they could prepare and evenbegin to initiate before the stimulus appeared (allStop Signal tasks; and any Go/No-Go task whereGo trials were more frequent and the appropriateresponse was known ahead of time), which we referto as response override tasks; and (b) tasks wherethey were unlikely to engage in differential prepara-

tion of a specific motor response before the stimu-lus appeared (Go/No-Go tasks where the trial typeswere equiprobable), which we refer to as response

uncertainty tasks (for related distinctions, see Refs.142144). Four stopping tasks were excluded fromthis analysis because they were difficult to classify.

A meta-analysis of the response override stud-ies revealed consistent activity in right IFJ, bilateralmiddle frontal gyrus, and right posterior-VLPFC(pars opercularis; Fig. 4 and Table 5). Similarly, themeta-analysis of the response uncertainty contrastsrevealed that these tasks consistently recruited bi-lateral IFJ and middle frontal gyrus, along withright VLPFC spanning both pars opercularis andpars triangularis (Fig. 4 and Table 6). Strikingly, theright mid-VLPFC (pars triangularis) effect seen inthe response uncertainty studies was absent in theresponse override studies. Qualitatively, the voxel-wise difference scores between the two ALE mapshighlighted this differential effect in mid-VLPFCduring response uncertainty tasks, and also sug-gested that although right middle frontal gyrus and

AI were recruited by both types of stopping tasks,they may be more consistently active during re-sponse override tasks (Fig. 4).



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Table 4. Frontal regions that respond during reflexive reorienting tasks (Posner cueing and Oddball)


R inferior frontal junction 6/9/44 44 14 30 9472

R anterior insula 13 36 8 6R presupplementary motor area 6 28 4 60

R inferior frontal junction/premotor cortex 6/8 50 0 38

R anterior insula 13 34 24 6

R inferior frontal junction/premotor cortex 6/8 44 2 40


R anterior-VLPFC 47 46 24 10

Anterior cingulate/presupplementary motor area 6/32 0 0 46 4712

Presupplementary motor area 6 0 12 42

Supplementary motor area 6 2 12 56

R anterior cingulate/presupplementary motor area 6/32 8 20 38

L insula 13 44 0 6 3216L anterior insula 13 36 12 4


R middle frontal gyrus 9/46 34 30 30 1680


L ventral premotor cortex 6 56 2 18 1216

L inferior frontal junction 6/9/44 48 8 32

L temporal pole/insula 38/13 48 10 10 920


R frontal pole 10 30 52 12 296

L inferior frontal junction 6/9

48 6 44 224Primary motor cortex 4 36 16 64 168

A similar comparison within the reflexive reori-enting tasks was performed, as the Posner Cueingtask and the Oddball task differ in a number ofimportant ways. For example, the Cueing task in-volves a perceptual onset at an unexpected locationin space, whereas Oddball targets appear in the cen-tral stream. Also, the onset that captures attention inthe Posner Cueing task is the alternate location, butthe actual location of the stimulus is irrelevant to thesubjects decision (judging the identity of the stim-ulus), whereas the attention-capturing onset in theOddball task is the occurrence of the oddball targetand this defines what response the subject shouldmake. Despite these differences, the ALE maps forthe two sets of studies were remarkably similar anddirect comparisons between the two tasks did notsuggest any clear differentiation. This could be dueto the low number of studies using the Posner Cue-

ing task or perhaps because these task differenceshave little impact on the exact regions recruited.There is evidence from one within-subjects compar-

ison that both the Oddball and Posner Cueing taskrecruit IFJ, but that the Oddball task more reliablyrecruits a region in the inferior frontal sulcus, ante-riortotheIFJ;145 thislatterresultwasnotobservedinthe current meta-analysis, however. Future researchcan profitably explore whether within-subjects dif-ferences are consistently observed in the functionalneuroanatomy of these tasks.

Implications for theories of right VLPFCfunction

Overall, the present meta-analysis revealed broadsimilarity in the regions recruited by motor inhibi-tion and reflexive reorienting. Tasks thought to re-flect both constructs led to consistent activity withina right-lateralized frontoparietal network. However,despite this general correspondence, there also ap-pear to be important differences in the right lateral

PFC subregions that are consistently activated bythe two classes of tasks, a finding that provides ini-tial traction on specifying the function-to-structure



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Figure 4. Meta-analysis of two different types of motor inhibition tasks. The top row displays the ALE map for tasks that involve

response override. These Stop Signal and Go/No-Go tasks encourage subjects to prepare a specific motor response before the stop

cueappears,such that thecue triggers theneedto cancel a prepared motor action. Thesecond row displaysthe ALEmap fortasks that

involve response uncertainty. These are Go/No-Go tasks where the two trial types are equiprobable, such that subjects are unlikely

to prepare a specific motor response before the trial begins. Accordingly, to the extent that they do not prepare a response, then

there is no need to override a specific response. Instead, these tasks create a situation of high decision uncertainty. The bottom row

displays a voxel-wise map of the difference score between the two unthresholded ALE maps. This image is arbitrarily thresholded

(at 0.0125) to show voxels where there are large differences in the two ALE maps; accordingly, this map provides qualitative leverageon possible differences between conditions, but does not constitute a formal statistical comparison. On the axial slices, specific

right VLPFC subregions are labeled: anterior insula (A), posterior-VLPFC (B), mid-VLPF (C), inferior frontal junction (D), and

presupplementary motor area (E).

mapping within right VLPFC. To further this goal,we next discuss the pattern of activation observedin specific right VLPFC subregions in our meta-analysis within the context of other findings fromthe broader neuroimaging, TMS, and lesion liter-atures. Finally, we conclude by offering an initial

characterization of the mechanistic role each rightVLPFC subregion may play in cognitive control.

Inferior frontal junction (IFJ)The IFJ was active across the motor inhibition andreflexive reorienting tasks included in our meta-analysis, which suggests that this region contributesto the detection of relevant stimuli in the environ-ment. Interestingly, the response of this region waslargely bilateral, which may distinguish IFJ fromVLPFC (see sections below on VLPFC). As noted

by others,70,71 motor inhibition tasks require sub-jects to detect behaviorally relevant stop signals, anddirect within-study comparisons indicate that IFJ

is similarly recruited across orienting and stoppingcontrasts.68,70,71 The pattern of generalized recruit-ment seen in thepresent meta-analysis is also consis-tent with other work implicating IFJ across a broadrange of cognitive tasks.7274 For example, Derrfusset al.72 reported that bilateral IFJ was active dur-

ing task switching, n-back, and Stroop tasks. Thesefindings suggest that the IFJ is recruited across manyparadigms that require cognitive control.

Precisely what role the IFJ plays, though, remainsunclear. Based on the results of the current meta-analysis, one possibility is that this region respondsto the detection of infrequent stimuli, since the con-trasts analyzed here mostly involve comparisons ofinfrequent trials against frequent ones (e.g., stopsignals typically occur on only 2030% of the trialsand they are contrasted with Go trials that occur the

other 7080% of the time). The one exception in thecurrent set of analyzed studies is the response un-certainty tasks, where the No-Go and Go trials were



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Table 5. Frontal regions that respond during response override tasks



R posterior-VLPFC 44 48 16 18R presupplementary motor area 6 14 16 58 4688




L anterior insula 13 42 16 6 3320




Anterior cingulate 32 6 22 36 728


R dorsal premotor cortex 6 30 0 44 240L dorsal premotor cortex 6 26 4 52 208

equiprobable. Even under such equiprobable condi-tions, greater activity on No-Go relative to Go trialswas observed in IFJ. Moreover, in some of the tasksstudied by Derrfuss et al.,72,74 the critical contrastsdo not compare infrequent trial types with frequentones (e.g., Stroop), suggesting that this region does

not respond simply to infrequent events.An alternative interpretation of IFJ functional ac-

tivations is that they may track the detection of be-haviorally relevant stimuli, rather than rare events.This idea is consistent with the notion of a ventralattention system that responds to abrupt onsets inthe environment. Importantly, all of the tasks re-viewed here require subjects to explicitly search forsome target, so these tasks likely do not elicit purebottomup, stimulus-driven activity. Rather, IFJ re-sponses likely depend on an interaction betweenstimulus-driven processes and top-down behavioralgoals.47,52 For example, IFJ may actively maintain aspecific target (e.g., a particular feature or an ob-ject identity) and then signal a match whenever itappears in the environment.146 This kind of generalmonitoring role could explain the recruitment ofIFJ across a diverse array of goal-directed tasks.

While we have interpreted the overlapping acti-vation in IFJ as evidence that reflexive reorienting isrecruited duringstoppingtasks,it is possible that the

converse is true: reflexive reorienting tasks may in-volve response inhibition. In fact, Arrington et al.75

suggested that right lateral PFC activity during in-

validly cued trials could reflect the suppression ofinappropriate responding before attention has beenreoriented to the correct spatial location. Arguingagainst this interpretation, though, is the fact thatmost oddball tasks do not involve any form of mo-tor inhibition. To further address this possibility, we

performed a meta-analysis restricted to 21 of theoddball contrasts where we can be reasonably surethat no component of the task required subjects towithhold a responseas happens, for example, inoddball tasks where subjects press a different but-ton for the standard stimuli and must withhold thisresponse when the oddball appears.132 Importantly,even in this subset of studies, we observed robustactivity within right IFJ suggesting that this regionis recruited even when there is no need to suppressa motor response.

Greater mechanistic specificity regarding IFJfunction is clearly still needed. Given the observa-tion of IFJ activation across many cognitive controltasks, one useful next step in advancing models ofIFJ function might include a more precise charac-terization of which tasks do not activate this re-gion. For example, the monitoring role proposedabove suggests that IFJ responds when the currentstimulus matches the target feature that is currentlybeing monitored for and, therefore, should not re-

spond to task-irrelevant stimuli even when they aresurprising. In contrast to this, one recent study hasshown bilateral IFJ activity in response to the initial



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Table 6. Frontal regions that respond during response uncertainty tasks


R mid-VLPFC 45 48 28 18 6752

R anterior-VLPFC 47 42 30 8R posterior-VLPFC 44 48 14 18

R posterior-VLPFC 44 56 22 12

L inferior frontal junction 6/9/44 46 12 28 2272

L middle frontal gyrus/mid-VLPFC 9/46/45 48 30 22




R frontal pole 10 24 48 30

R inferior frontal junction/middle frontal gyrus 6/9 44 14 36 800

R inferior frontal junction 6/9/44 42 10 28

L middle frontal gyrus 9/46 36 40 26 776L middle frontal gyrus 9/46 32 48 30

R dorsal premotor cortex 6 40 2 46 352

L frontal pole 10 38 58 2 312

R frontal pole 10 24 52 12 288

L frontal pole 10 22 58 6 272


L anterior-VLPFC 47 40 32 10 176

presentations of unexpected task-irrelevant stim-uli,147 suggestingthat thisregion maycomputemorethan the occurrence of a particular target. Morebroadly, an analysis of divergent validity would likelyprovide useful constraints on the possible mech-anistic contributions IFJ provides to goal-directedbehavior.

Right posterior-VLPFCIn contrast to task-general recruitment of IFJ, there

was evidence for functional specialization in otherPFC regions. In particular, right posterior-VLPFC(pars opercularis) was reliably recruited duringstopping tasks, but not during reflexive reorientingtasks. This finding is consistent with the observa-tion that lesions to this right VLPFC subregion areaccompanied by stopping impairments,45 and thatTMS to this region, and not other PFC regions, dis-rupts stopping.148 Strikingly, there was no evidencethat any of the tasks studied here reliably recruitedleft posterior-VLPFC.

These findings suggest that right posterior-VLPFC is specifically involved in stopping and notin the capture of attention by behaviorally relevant

stimuli. Importantly, this dissociation between rightposterior-VLPFC and right IFJ has also been ob-served using within-subject designs.68,149 For ex-ample, Chikazoe et al.68 modified the Go/No-Gotask to include infrequent-go trials that (a) occurredat the same frequency as no-go trials (12.3%), butthat (b) still required the same response as other gotrials. As such, the infrequent-go trials did not re-quire engagement of a putative stopping process,but nevertheless were oddballs that should cap-

ture attention in a stimulus-driven fashion. Im-portantly, right IFJ responded to both types of in-frequent trials (infrequent-go and no-go), whereasright posterior-VLPFC responded to the no-go tri-als but not the infrequent-go trials (cf. Sharp etal.68 for a failure to observe this dissociation in asimilar paradigm). Similarly, Verbruggen et al.149

used TMS to target right IFJ and right posterior-VLPFC during a Stop Signal task and found evi-dence that stimulating IFJ impaired the ability todetect behaviorally relevant stimuli, whereas stim-

ulating posterior-VLPFC disrupted the ability toupdate action plans after the detection of a stopsignal.



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Collectively, the present meta-analysis as wellas related within-subject directed contrasts suggestthat right posterior-VLPFC plays a key role in stop-ping tasks that is distinct from the simple detectionof stop signals in the environment. While this find-

ing is consistent with the hypothesis that this regionplays a critical role in motor inhibition,41 it shouldbe noted that our meta-analysis suggests that ac-tivation in this region does not differ between re-sponse override and response uncertainty versionsof the stopping task, despite the fact that the formerplace greater demands on stopping (i.e., the motorplan has already been initiated and should thereforebe more difficult to stop). Moreover, Verbruggenet al.149 found that TMS-mediated disruption of

right posterior-VLPFC not only slowed stopping,but also impaired the ability to use environmentalcues to update behavior even when updating did notrequire stopping (subjects simply had to press thesame button a second time). Verbruggen et al.149

suggest that the role of right posterior-VLPFC isto update action plans after a behaviorally relevantstimulus has been detected; stopping is one instanceof the class of situations in which such updatingis required. Critically, difficulties in updating ac-tion plans would still explain why lesions to right

posterior-VLPFC impair the ability to stop.45 In-terestingly, Oddball tasks do not reliably activateposterior-VLPFC. Responding to the detection ofan oddball target clearly involves engaging an actionplan, but importantly it does not involve revising aspecific prepared plan in favor of an alternate actionplan. This newly emerging view offers a critical re-framing of the role of right posterior-VLPFC: ratherthan mediating motor inhibition, per se, this PFCsubregion may contribute to the updating of action

plans.

Right mid-VLPFCThe present meta-analysis suggests that right mid-VLPFC activity was unique to response uncertaintytasks, which are stopping tasks where the go andno-go trials are equally likely to occur. In such tasks,the moment when the stimulus appears involves ahigh degree of uncertainty, as the subject must de-cide which response is currently relevant. This dif-fers from the other tasks analyzed here, in which

subjects can formulate a specific action plan priorto stimulus onset and then wait to execute that ac-tion (or counteraction) until the critical stimulus

occurs. For example, in Stop Signal tasks subjects

can begin to initiate action, knowing that only ifthey hear the infrequent stopping tone do they needto stop the response. Thus, there is relatively littleambiguity in the Stop Signal task, even when the

task is made difficult by delaying the stop signal.Similarly in the Oddball task, the subject spendsmost of the time not responding and only needs tobe prepared to respond once an oddball appears, asituation that again involves little response ambigu-ity when the stimulus appears. In response uncer-tainty tasks, however, both responses are equiprob-able, so subjects are not able engage in the kindof differential response preparation that occurs inother tasks. This means that (a) there is no spe-

cific prepotent action plan that needs to be can-celled, and (b) there is a high degree of ambiguitywhen the stimulus occurs and the subject must de-cide which of the two responses (go or no-go) isassociated with it. It is possible that in these situa-tions, subjects engage in minimal or even no prepa-ration before the stimulus appears. However, be-cause speeded responding is generally emphasizedfor go trials, we suggest that subjects are likely toprepare both responses in parallel, leading to a sit-uation where appropriate behavior is underdeter-

mined and these multiple incompatible responsesproduce conflict, triggering the need for cognitivecontrol.150

While we have suggested that this mid-VLPFCresponse is driven by uncertainty, it is unclear whatprecise cognitive control process is triggered by un-certainty in this situation. One interpretative chal-lenge stems from the fact that, while both equiprob-able go and equiprobable no-go trials should beassociated with a high degree of uncertainty, the

contrasts that yield differential mid-VLPFC activ-ity compare no-go with go trials. This suggests thatthis region is not simply driven by uncertainty, butrather is driven by no-go trials in contexts whereuncertainty is high (i.e., there is an interaction be-tween uncertainty and some factor related to no-gotrials). One possibility relates to the framing of thetask: no-go trials are typically emphasized in thetask instructions and may, therefore, take on greatersaliency or motivational significance (see also Refs.151 and 152 for a similar discussion). Alternatively,

withholding a response may place greater demandson cognitive control than executing any particularmotor movement. It is interesting to note, in this



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context, that the Oddball task is just an inverse ver-sion of the Go/No-Go task, where the typical trialsrequire no response(rather than responding). In thestudies analyzed here, oddballs were never presentedon more than 20% of the trials, but one could try

to gain leverage on this mid-VLPFC response by us-ing an equiprobable Oddball design. If mid-VLPFCresponds to target stimuli with higher salience un-der situations with high uncertainty, then mid-VLPFC should be engaged by equiprobable oddballsmore than the standards. In contrast, if mid-VLPFCactivity reflects increased demands related to with-holding a response, one might predict that theoddballs would be associated with weaker mid-VLPFC activity. These predictions await further

examination.The recruitment of right mid-VLPFC when un-certainty is high is consistent with research impli-cating left mid-VLPFC in resolving decision-levelconflict. Badre and Wagner22 reviewed the liter-ature on the cognitive control of memory andfound that left mid-VLPFC is recruited postre-trieval under conditions in which subjects had toselect amongst multiple competing active represen-tations (see also, Thompson-Schill et al.153). Morerecently, Race et al.34 used a repetition priming

paradigm to manipulate uncertainty at three differ-ent levels of representationstimulus meaning, themapping of the stimulus to task-relevant decisioncategories, and response selectionand observedthat left mid-VLPFC activation tracked decision-level uncertainty (for related findings, see Raceet al.154). At present, it remains unclear at what stageof processing the critical uncertainty arises in theresponse uncertainty tasks described here. In par-ticular, equiprobable trials are likely associated with

uncertainty both at thedecisionlevel,where subjectsmust categorize the stimulus, and at the response-level, where subjects must determine which behav-ior is currently relevant. The extant literature onthe cognitive control of memory suggests that per-haps the critical form of uncertainty here relates todecision-level stimulus mapping, but this too awaitsfurther investigation.

As was the case with posterior-VLPFC, thepresently observed mid-VLPFC response during re-sponse uncertainty tasks was clearly lateralized and

was not seen in the left hemisphere. Interestingly,the homologous left VLPFC regions are robustly

modulated by other cognitive control tasks, partic-

ularly when linguistic stimuli are used.22,34 By con-trast, in the stopping and attention tasks reviewedhere, verbal aspects of the stimuli are not criticalto performance. Collectively, these similarities anddifferences between left and right mid-VLPFC sug-

gest (a) that the difference in the types of mate-rials being processed (verbal vs. nonverbal) affectsthe laterality of the mid-VLPFC response, but (b)thatthe mid-VLPFCresponsenevertheless maysub-serve the same basic function of resolving decisionuncertainty regardless of stimulus type. This inter-pretation predicts that other tasks that measure de-cision uncertainty should also lead to mid-VLPFCrecruitment.

An alternative, although not mutually exclusive,

interpretation of the present meta-analytic find-ings is that the pattern of VLPFC activity duringstopping tasks reflects a rostro-caudal hierarchicalgradient of control.18,2534 According to this view,more anterior regions of PFC encode more abstracthigher-order goals, which typically bridge longerspans of time, whereas more posterior regions ofPFC encode progressively more specific subgoals,with the most posterior regions in premotor cor-tex instantiating specific action plans. In the cur-rent context, response override tasks involve a type

of stopping that occurs late in information pro-cessing and is targeted at already prepared actionplans, which may explain why these tasks reliablyrecruit the most posterior extent of VLPFC. Re-sponse uncertainty tasks, on the other hand, involvea more abstract form of control that involves select-ing from among multiple viable action plans andtherefore drives activity in the more rostral rightmid-VLPFC region. Seen in this light, the currentdata resemble similar functional gradients that have

been observed along the rostro-caudal axis of leftPFC.18,2534

Right AI/FOAcross all of the reviewed tasks, there was some ev-idence for recruitment of the most ventral portionof lateral frontal cortex. When activations are ob-served in group-level maps near this area, it is oftendifficult to discern whether the clusters correspondto activity within the FO of VLPFC or the imme-diately adjacent AI. Nevertheless, in the reflexive

reorienting tasks, the present meta-analyses suggestthat the most ventral lateral frontal activations wererelatively restricted and appear to fall within AI.



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By contrast, the region recruited by stopping tasksclearly extended from AI into FO.

It appears clear that the AI is consistently en-gaged during both reflexive reorienting and motorinhibition tasks,70 though right AI was more consis-

tently activated by stopping and particularly by theresponse override tasks. The broader literature onthe insula implicates this region in the processingof emotions and pain, as well as during situationsrequiring cognitive control.155 It has been suggestedthat the broad role of the AI, in conjunction withthe dorsal anterior cingulate, is in the processing ofsaliency, regardless of whether that saliency is emo-tional or cognitive.156158 This putative salience net-work is thought to respond to relevant stimuli in the

environment and activate sympathetic responses,such as increasing heart rate and dilating the pupils,in order to better prepare the subject to respond tothe salient event. It is not thought, however, to di-rectly exert control itself (although, see Dosenbachet al.159).

Recent lesion evidence suggests that AI may playsome critical functional role during motor inhibi-tion tasks. In particular, based on a meta-analysisof the imaging literature as well as new lesion data,Swick et al.80 argued that left frontal regions are

also involved in stopping. They observed that pa-tients with left frontal lesions, which included dam-age to both VLPFC and AI, made more errors in aGo/No-Go task, especially when no-go trials wereinfrequent. One possibility is that this impairmenton the Go/No-Go task was due to damage to left AIas this region, and not left VLPFC, was implicatedin stopping in the present meta-analysis and in thatby Swick et al.80 This interpretation would also beconsistent with the observation that left PFC lesions

do not disrupt stopping.

45

At the same time, it isunclear why damage to this left-lateralized regiondisrupts performance on the Go/No-Go task, andit could be for reasons that do not relate directly tomotor inhibition (e.g., these regions might supportrule maintenance or modulated arousal in responseto the salience of the stop cues). Further imagingand lesion data are needed to understand whetherleft and right AI play a fundamental role in motorinhibition.

Interactions with medial PFCA full understanding of lateral PFC functioning re-quires a broader understanding of thenetworks sup-

porting specific forms of cognitive control. Whilethe lateral frontal regions discussed above are theprimary focus of this paper, they are not the onlyregions consistently activated by motor inhibitionand reflexive reorienting tasks (Fig. 3). In partic-

ular, both task domains led to consistent across-study recruitment of medial prefrontal regions, al-though there was relatively little overlap in theprecise regions recruited. Stopping tasks tendedto activate the preSMA and ACC, whereas re-flexive reorienting activations were more posteriorand did not extend as far dorsally into preSMA.In addition, the stopping activations tended tobe right lateralized, while the reflexive reorient-ing activations tended to be centered around the

midline.Medial PFC activity in Oddball and Go/No-Gotasks has been argued to track the infrequency ofthe stimuli, putatively reflecting the heightened con-flict present whenever an infrequent response, ofany type, is required.160 Consistent with this view,we did not find evidence for the recruitment ofACC duringequiprobable Go/No-Go tasks, whereastasks that contrasted infrequent with frequent stim-uli led to robust ACC activation (although thesecontrasts yielded different ACC regions depend-

ing on the task context, whereas Braver et al.160found a common ACC region that responded toinfrequency in both Oddball and Go/No-Go tasks).While the specific ACC region recruited may dif-fer, the general recruitment of ACC across thesetasks is consistent with several competing accountsof ACC functioning,150,161163 all of which predictthat response competition should occur due to theinfrequency of the desired response. It is worthnoting, though, that the equiprobable Go/No-Go

tasks, which we have interpreted as reflecting de-cision uncertainty, do not reliably activate ACC,even though such tasks should involve responsecompetition.

In the present meta-analysis, activation withinpreSMA appeared to be specific to the responseoverride variants of stopping tasks. This finding isconsistent with observations that preSMA is moreactive during correct stop signal trials than duringgo trials where an infrequent behaviorally irrelevantcue is presented,68,71 suggesting that preSMA is in-

volved in stopping rather than attentional capture(cf., Hampshire et al.70 failed to find a differentia-

tion within preSMA for orienting and stopping in



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a similar designb). There is also lesion evidence tosuggest that damage to preSMA can lead to impairedstopping performance,164166 suggesting that, alongwith right posterior-VLPFC, this region may play acritical role in stopping tasks. Anatomically, Aron

et al.57 showed that preSMA is connected to rightposterior-VLPFC and to the subthalamic nucleus(STN), both of which also showed consistent across-study activity here that was specific to the stoppingtasks. These findings support the hypothesis thatthese regions interact as a network to support stop-ping performance,57 with the present and other datasuggesting a broader role of right posterior-VLPFCin action updating.

Right VLPFC: beyond stopping andattention

While our focus in this review was to specifically ad-dress two dominant accounts of right VLPFC func-tion, it is important to emphasize that activation ofright VLPFC subregions has been observed duringthe performance of many tasks beyond those de-scribed here. For instance, neuroimaging studies ofepisodic memory encoding and retrieval often re-port that activation in VLPFC is strongly lateralized

based on the type of stimuli being processed.

167175

Verbal stimuli often lead to robust activation in leftVLPFC, whereas visuospatial stimuli often result inactivation in right VLPFC. Interestingly, in situa-tions where visual stimuli are easy to verbally re-code (e.g., nameable famous faces or pictures ofcommon objects), bilateral VLPFC activations areobserved, suggesting that subjects engage both ver-bal and nonverbal processing mechanisms for these

b

While Hampshire et al.70

failed to find differentiationwithin preSMA for stopping and reorienting, interpre-

tation of this outcome is complicated by a number of

methodological factors. In particular, the orienting and

stopping tasks were compared to different baselines, the

orienting task involved a working memory component

that was absent from the stopping task, and the orient-

ing task always preceded the stopping task during scan-

ning.68,71 It is difficult to know which, if any, of these

factors explain the divergence from other studies. It is

also worth nothing that while Hampshire etal.70 reported

a right VLPFC region that did not differentiate between

orienting and stopping, this effect appears to fall ventralto the posterior-VLPFC region observed implicated in

stopping by the present meta-analysis.

Figure 5. Encoding visuospatial information activates simi-

lar VLPFC regions as motor inhibition. Here the activations

from the motor inhibition meta-analysis are replotted in red,

and overlaid in blue is an ALE meta-analysis of three episodic

memory encoding studies.168,171,174 Each of these latter studies

contrasted encodingphases with difficult-to-verbalize visuospa-

tial stimuli (e.g., textures) to ones with verbal stimuli. While

several other studies reported similar patterns both at encod-

ing169,172,175 and during retrieval,168,169 many of these studies did

not report peak coordinates. This sample was too small to jus-

tifya formal meta-analytic treatment;nevertheless, theapparent

overlap suggests that similar right VLPFC regions are engaged

during motor inhibition and during nonverbal episodic encod-

ing tasks.This overlap would appear difficult to explain in termsof either motor inhibition or reflexive reorienting.

types of stimuli.167,175 There is also some evidencefor a similar material-specificity effect during work-ing memory tasks, particularly when the tasks in-volve simple maintenance.176 Importantly, these re-gions clearly overlap with the VLPFC responsesobserved here, particularly for the stopping tasks(Fig. 5).

Right VLPFC has also been implicated as a keyregion in the mirror neuron system.177,178 Mirrorneurons are cells that respond both to the executionof an action and to observing someone else per-forming thesame action.179 Theseneurons were firstobserved in the primate premotor and parietal cor-tices,180 but this work has inspired functional neu-roimaging studies of humans investigating whichbrain regions show these type of responses; thehuman neuroimaging literature has also extendedthese earlier studies to examine the role of mirror

neurons in imitation, empathy, and social cogni-tion generally. Importantly, these imaging studieshave implicated bilateral VLPFC, along with other



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regions, in actionobservation,execution, and imita-tion. A meta-analysis of this literature revealed thatthis lateral PFC response includes right IFJ alongwith posterior and mid-VLPFC regions that over-lap with those observed here.178

These two examples provide an important,broader context for theorizing about what functionsare subserved by right VLPFC. If a common VLPFCregion is observed within-subjects to be engagedacross these domains, it is unclear how the putativemechanisms discussed in the present review couldexplain those activations in the episodic encodingand mirror neuron literatures. Encoding of non-verbal stimuli and action imitation, for example,both likely involve orienting to behaviorally relevant

stimuli as they appear in the environment, but inneither case is it obvious that thecontrasts employedin those studies reflect the capture of attention. Fur-thermore, drawing on such an interpretation to ex-plain these other effects leads to the prediction thatthe VLPFC regions implicated in orienting shouldbe active whenever subjects encounter any type ofbehaviorally relevant stimuli. It is perhaps even lessclear how the encoding and mirror neuron VLPFCdata could be explained by a stopping mechanism,as neither encoding nor imitation involves the inhi-

bition of a motor response. On the other hand, anaction updating account of posterior-VLPFC mayoffer insight into why this region may also be in-volved in action representationin themirror neuronsystem.

While the foregoing analysis suggests that theoverlap in fMRI activations implies shared popula-tions of neurons across tasks, it is also possible thatthere is intra-voxel functional heterogeneity. Thisissue could be explored by direct within-study com-

parisons thatuse repetition suppression strategies

181

to test whether the same populations of neurons areengaged by both tasks. Even if the same neuronsare engaged by two classes of tasks (e.g., inhibitionand encoding), though, the specific computationsperformed may fundamentally differ based on theother regions they interact with as part of largernetworks.182 If either of these possibilities were sup-ported it would of coursechallengetheoretical viewsthat proffer single function-to-structure mappings.To advance theories of right VLPFC function, we

need to directly test whether the same populationsof neurons are engaged across domains, and, if so,

we must consider the broad array of tasks that par-

ticular VLPFC subregions support, being careful to

consider mechanisms that could account for thiskind of diversity.

Movingforward, thecurrent results provide someinitial traction on the pattern of functional special-

ization within right VLPFC. In particular, we ob-served that the IFJ responds generally to the onsetof behaviorally relevant stimuli, suggesting that thisregion reflects an interaction between top-down be-havioral goals and bottom-up capture by the rele-vant stimulus.47,52 In contrast, posterior-VLPFC ap-pears to respond when we must update a preparedaction plan in order to engage an alternative re-sponse, with stoppingbeingone such instance wherethis happens. Right mid-VLPFC shows yet another

pattern of activity, as it was engaged by stoppingspecifically under situations with high uncertainty,suggesting an analogous role to the function of leftmid-VLPFC.2234 Interestingly, though, we did notsee clear evidence across any of the tasks for the in-volvement of right anterior-VLPFC, suggesting thatthe critical functions performed by this region weresimply not captured by the cognitive mechanismsstudied here.

As the above summary describes, rich functionalheterogeneity exists within right VLPFC, which

means that care should be taken when describingpatterns of PFC activity in terms of the underly-ing anatomy. Importantly, future work will need tocarefully test our proffered hypotheses about func-tional specialization,usingwithin-subjects manipu-lations; we areencouraged that this work has alreadybegun.68,149 New research projects will also need toexpand on these mechanistic accounts to see if theycan accommodate findings of right VLPFC activa-tion within other behavioral paradigms. Such work

promises to advance understanding of the function-to-structure mapping of right VLPFC, which willultimately lead to a more complete theory of howthe PFC implements control over cognition andbehavior.

Acknowledgments

This work was funded by the NIMH (5R01-MH080309 and F32-079648). We would also liketo thank Nora Lindstrom for assistance with com-

piling the coordinate database for the meta-analysisand Ben Hutchinson, Melina Uncapher, and ChelanWeaver for helpful discussions.



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Conflicts of interest

The authors declare no conflicts of interest.

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