The Attention System of the Human Brain (Posner & Petersen) (2012)

NE35CH04-Petersen ARI 14 May 2012 11:42

The Attention System of theHuman Brain: 20 Years AfterSteven E. Petersen1 and Michael I. Posner21School of Medicine, Washington University in St. Louis, St. Louis, Missouri 63110;email: [email protected] of Psychology, University of Oregon, Eugene, Oregon 97403-1227;email: [email protected]

Annu. Rev. Neurosci. 2012. 35:7389

First published online as a Review in Advance onApril 12, 2012

The Annual Review of Neuroscience is online atneuro.annualreviews.org

This articles doi:10.1146/annurev-neuro-062111-150525

Copyright c 2012 by Annual Reviews.All rights reserved

0147-006X/12/0721-0073$20.00

Keywords

alerting network, executive network, orienting network,cingulo-opercular network, frontoparietal network

Abstract

Here, we update our 1990 Annual Review of Neuroscience article, TheAttention System of the Human Brain. The framework presented inthe original article has helped to integrate behavioral, systems, cellular,and molecular approaches to common problems in attention research.Our framework has been both elaborated and expanded in subsequentyears. Research on orienting and executive functions has supported theaddition of new networks of brain regions. Developmental studies haveshown important changes in control systems between infancy and child-hood. In some cases, evidence has supported the role of specic geneticvariations, often in conjunction with experience, that account for someof the individual differences in the efciency of attentional networks.The ndings have led to increased understanding of aspects of pathol-ogy and to some new interventions.

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Contents

INTRODUCTION . . . . . . . . . . . . . . . . . . 74THE ORIGINAL NETWORKS . . . . . 74

Alerting . . . . . . . . . . . . . . . . . . . . . . . . . . . 74Orienting. . . . . . . . . . . . . . . . . . . . . . . . . . 75Executive . . . . . . . . . . . . . . . . . . . . . . . . . . 75

ELABORATIONS OF THEFRAMEWORK . . . . . . . . . . . . . . . . . . . 77Alerting . . . . . . . . . . . . . . . . . . . . . . . . . . . 77Orienting. . . . . . . . . . . . . . . . . . . . . . . . . . 78Executive Control . . . . . . . . . . . . . . . . . 79

EXTENDING THEFRAMEWORK . . . . . . . . . . . . . . . . . . . 82Self-Regulation . . . . . . . . . . . . . . . . . . . . 82Differences in Network Efciency . . 84Training . . . . . . . . . . . . . . . . . . . . . . . . . . 85Evolution. . . . . . . . . . . . . . . . . . . . . . . . . . 85

FUTURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

INTRODUCTION

Twenty years ago, when neuroimaging was inits infancy, we summarized the current stateof knowledge on attention in the 1990 volumeof the Annual Review of Neuroscience (Posner &Petersen 1990). At that time, most available ev-idence was from behavioral studies of normaladults or patientswith varying formsof brain in-jury. However, the ability to image brain activ-ity with positron emission tomography seemedtohold great promise for the physiological anal-ysis of mental processes, including attention. Inour review, wewere able to integrate ndings ofthe initial imaging studies. We never imaginedthat the growth of cognitive neuroscience overthe subsequent 20 years would make it possibleto revisit our analysis, with 4,0006,000 imag-ing papers on attention or cognitive control andnearly 3,500 citations of our original review.

The original review suggested three basicconcepts about the attention system. The rstis that the attention system is anatomically sepa-rate from processing systems, which handle in-coming stimuli, make decisions, and produceoutputs. We emphasized the sources of the at-tentional inuences, not the many processing

systems that could be affected by attention. Thesecond concept is that attention utilizes a net-work of anatomical areas. The third is that theseanatomical areas carry out different functionsthat can be specied in cognitive terms. Themost unique aspect of our original article,whichseparated it from themany excellent summariesof the attention literature appearing in theAnnual Review of Neuroscience in the years since,is the discrete anatomical basis of the attentionsystem: divided into threenetworks, each repre-senting a different set of attentional processes.We believe that these important concepts arestill operative.Here,we try to update the frame-work of our earlier Annual Review article [othersummaries are available in Posner (2012a,b)].

In this review, we outline some of the ma-jor advances related to our framework that havetaken place in the past 20 years. First, we rein-troduce the three original networks of the at-tention system.We examine the nature of thesenetworks and how the ideas related to themhave evolved. The second part of the articleexplores additions to the original conception.Two new networks are proposed with theirfunctional descriptions, and new methods forunderstanding interactions between them. Thethird part of the article indicates how the ideashave been extended to related topics, for exam-ple, in tying genetic variations to individual dif-ferences in network efciency and in examiningthe development of attention in childhood.

THE ORIGINAL NETWORKS

The three networks we described in 1990included an alerting network, which focusedon brain stem arousal systems along withright hemisphere systems related to sustainedvigilance; an orienting network focused on,among other regions, parietal cortex; and anexecutive network, which included midlinefrontal/anterior cingulate cortex. Each of thesenetworks is explored below.

Alerting

The concept of arousal goes back to the clas-sic work of Moruzzi & Magoun (1949) on the

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role of the brain stem reticular system in main-taining alertness (Figure 1, for macaque brain).As more became known of the neuromodula-tory systems of the brain stem and thalamus,it was necessary to qualify the general conceptof arousal intomore differentiated components.Within cognitive psychology, a major emphasishas been on producing andmaintaining optimalvigilance and performance during tasks; this isthe sense of alertness that we discussed in our1990 article.

One approach to the study of alerting is touse a warning signal prior to a target event toproduce a phasic change in alertness.Thewarn-ing cue leads to replacing the resting state witha new state that involves preparation for detect-ing and responding to an expected signal. If aspeeded response is required to the target, re-action time improves following a warning. Thisimprovement is not due to the buildup of moreaccurate information about the target, whichis not changed by the warning signal, but thewarning signal does change the speed of orient-ing attention and thus responding to the signal.

Several other methods have been used tostudy tonic alertness. These include changesover the course of the day (circadian rhythm).Reaction times are usually longer in the earlymorning and decline over the course of the dayonly to rise again during the night and peak inthe early morning (Posner 1975). These mea-sures reect other diurnal changes such as bodytemperature and cortisol secretion. A long es-tablished approach to tonic alertness is to usea long and usually rather boring task to mea-sure sustained vigilance. Some of these taskshave grown out of the job of radar opera-tors looking for near-threshold changes overlong periods of time. Vigilance tasks rely heav-ily on mechanisms of the right cerebral cortex(Posner & Petersen 1990). Both classical lesiondata andmore recent imaging data conrm thattonic alertness is heavily lateralized to the righthemisphere.

Orienting

The orienting network is focused on theability to prioritize sensory input by selecting a

Alerting

Locus coeruleus:norepinephrine

Figure 1The locus coeruleus projections of the alerting system shown on a macaquebrain. The diffuse connections interact with other, more strongly localizedsystems. The alerting system also includes regions of the frontal and parietalcortices (not shown). Reproduced from Aston-Jones & Cohen (2005).

modality or location. Although the argumentsin the original review included discussion ofthe pulvinar and the superior colliculus, mostof our focus was on visual selection and on theparietal cortex as part of a posterior attentionsystem (Figure 2a). Consensus in the imagingliterature now indicates that frontal as well asposterior areas are involved in orienting. Forexample, human and animal studies have impli-cated the frontal eye elds (FEF) in this process(Corbetta et al. 1998, Thompson et al. 2005).

In addition, parietal areas have been impli-cated in related forms of processing. This pro-cessing can be concrete as in the specicationof directed motor or eye movements (Lindneret al. 2010) or more abstract as movementsacross a number line (Hubbard et al. 2005). Infact, the specicity of parietal regions in termsof sensory versus motor processing is a majorpoint of contention. Nonetheless, most wouldagree the functions of the parietal lobe are notrestricted to orienting to sensory stimuli but in-volve other related processes.

Executive

In our original article, the third major systemwas presented under the heading of target

www.annualreviews.org The Attention System of the Human Brain 75

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Dorsal attention system:top-down visuospatial

Ventral attention system:bottom-up reorienting

Frontoparietal control system:moment-to-moment task

Cingulo-opercular system:task set maintenance

Grouping of regions using resting state functional connectivity MRI

Executive control

Orienting

IPS/SPL FEF

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Figure 2(a) The dorsal and ventral orienting networks (after Corbetta & Shulman 2002). The dorsal attention network (light green) consists offrontal eye elds (FEF) and the intraparietal sulcus/superior parietal lobe (IPS/SPL). The ventral attention network (teal ) consists ofregions in the temporoparietal junction (TPJ) and the ventral frontal cortex (VFC). (b) Two networks of the executive control system.The circled region indicates the original member of the executive control system from Posner & Petersen (1990). The remainingregions come from the elaboration of the original cingulo-opercular system (black) and the addition of the frontoparietal system ( yellow)(adapted from Dosenbach et al. 2007). (c) Resting-state correlation reecting separate control systems. The gure illustrates three viewsof the brain (left, dorsal view; middle, tilted lateral view; right, medial view). These separable resting networks are consistent with thedistinctions based on functional criteria exhibited in panels a and b: dorsal attention ( green), ventral attention (teal ), cingulo-opercular(black), frontoparietal ( yellow) (adapted from Power et al. 2011).

detection. The main reason for this was notthat target detection itself is a major atten-tional process, but that the moment of targetdetection captures awareness in a very specicway. Although it is possible to monitor fortargets in many processing streams withouttoo much difculty, the moment of targetdetection produces interference across thesystem, slowing detection of another target(Duncan 1980). This set of processes is related

to the limited capacity of the attention system,and to awareness itself, and has often beencalled focal attention. One might think of focalattention as the entry to the conscious state,which may involve widespread connectionsfrom the midline cortex and the anterior cingu-late cortex (ACC) (Figure 2b) to produce theglobal work space frequently associated withconsciousness (Dehaene & Changeux 2011).We associated target detection and awareness

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of the target with the medial frontal cortex andthe adjacent ACC. This brain region has beenhighly studied by imaging experiments partlybecause of its frequent activation.

Although one of us (S.P.) has vacillated sig-nicantly on this original idea over the past20 years, it seems that the idea is still relevant.One of the reasons is that the ACC and relatedregions have been reliably activated when thereis conict [e.g., a requirement to withhold adominant response to perform a subdominantresponse (Botvinick et al. 2001)]. The argumenthas been extended to include a role for theseareas in the regulation of both cognition andemotion (Bush et al. 2000).

The most compelling argument for a focalattention explanation comes from the activityfound in the medial frontal/anterior cingulatein such diverse operations as perception ofeither physical (Rainville et al. 1997) or social(Eisenberger et al. 2003) pain, processing ofreward (Hampton & ODoherty 2007), moni-toring or resolution of conict (Botvinick et al.2001), error detection (Dehaene et al. 1994),and theory of mind (Kampe et al. 2003). Thesedifferent demands all activate this region, inmost cases in conjunction with the anteriorinsula. Some investigators advocate a separaterole for the system for each of the comparisonsabove (e.g., as part of a pain or reward system),but, as we argue below, we support a morecomprehensive view that captures more ofthe results, including focal attention and theregulation of processing networks. Since theoriginal article, this network has also takenon an even more extensive role in executivecontrol on the basis of ndings showing multi-ple top-down control signals in these regions.This more complex functional and anatomicalnetwork is discussed in the executive controlsection below.

ELABORATIONS OF THEFRAMEWORK

The intervening 20 years since our originalarticle have produced a surprising amount ofsupport for the basic outlines of the framework

described above. There has also been a signi-cant amount of elaboration or evolution of theideas during that timeframe. The next threesections review some of the studies deepeningor expanding our understanding of the originalnetworks.

Alerting

Our understanding of the physiology andpharmacology underlying the alerting systemhas changed signicantly. For example, strongevidence relates the neuromodulator nore-pinephrine (NE) to the alerting system.Awarn-ing signal is accompanied by activity in the lo-cus coeruleus, the source of NE (Aston-Jones& Cohen 2005). Warning-signal effects can beblocked by drugs such as guanfacine and clono-dine, which decrease NE release (Marrocco &Davidson 1998). Drugs that increase NE re-lease can also enhance the warning-signal ef-fect. The NE pathway includes major nodes inthe frontal cortex and in parietal areas relatingto the dorsal but not the ventral visual pathways(Morrison & Foote 1986).

To examine the specicity of these effectsto the warning signal, researchers used a cueddetection task with humans, monkeys, andrats (Beane & Marrocco 2004, Marrocco &Davidson 1998) to separate information aboutwhere a target will occur (orienting) fromwhenit will occur (alerting). To accomplish this, oneof four cue conditions was presented prior toa target for a rapid response. By subtracting adouble cue condition, where the participant isinformed of when a target will occur but notwhere, from a no cue condition, they receivea specic measure of the warning inuenceof the signal. When the cue that indicatesthe targets location is subtracted from analerting cue, the difference represents effects oforienting. Results of drug studies with humansand monkeys show that NE release inuencesalerting effects, whereas drugs inuencingthe neuromodulator acetylcholine (Ach) affectorienting but not alerting. Studies have shownthat individual differences in alerting andorienting are largely uncorrelated (Fan et al.


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2002) and that orienting improves to the samedegree with a cue regardless of the level ofalertness. These results suggest a great dealof independence between these two functions(Fernandez-Duque & Posner 1997). However,these systems usually work together in mostreal-world situations, when a single event oftenprovides information on both when and wherea target will occur (Fan et al. 2009).

The changes during the time between warn-ing and target reect a suppression of ongo-ing activity thought to prepare the system fora rapid response. In the central nervous sys-tem there is a negative shift in scalp-recordedEEG, known as the contingent negative varia-tion (CNV) (Walter 1964), which often beginswith thewarning signal andmay remain presentuntil the target presentation. This negative po-tential appears to arise in part from the ante-rior cingulate and adjacent structures (Nagaiet al. 2004) and may overlap the event-relatedresponse to the warning stimulus. The negativeshiftmay remainpresent as a standingwaveoverthe parietal area of the contralateral hemisphere(Harter & Guido 1980). If the target interval ispredictable, the person may not show the CNVuntil just prior to target presentation.

An extensive imaging study (Sturm &Willmes 2001) showed that a largely commonright hemisphere and thalamic set of areas areinvolved in both phasic and tonic alerting. An-other imaging study, however, suggested thatthe warning signal effects rely more stronglyon left cerebral hemisphere mechanisms (Coullet al. 2000, Fan et al. 2005). This could rep-resent the common ndings described aboveon hemispheric differences in which right lat-eralized processes often involve slower effects(tonic), whereas left hemisphere mechanismsare more likely to be involved with higher tem-poral (phasic) or spatial frequencies (Ivry &Robertson 1997). The exact reasons for differ-ences in laterality found with tonic and phasicstudies are still unknown.

Orienting

In a series of imaging experiments us-ing cuing methodology in combination with

event-related fMRI, Corbetta & Shulman(2002) showed that two brain systems are re-lated to orienting to external stimuli as illus-trated in Figure 2a. A more dorsal system in-cluding the FEFs and the interparietal sulcusfollowed presentation of an arrow cue and wasidentied with rapid strategic control over at-tention. When the target was miscued, subjectshad to break their focus of attention on the cuedlocation and switch to the target location. Theswitch appeared to involve the temporoparietaljunction (TPJ) and the ventral frontal cortexand was identied with the interrupt signal thatallowed the switch to occur.

The dorsal system included the well-studiedparietal regions but added a small set of frontallocations as well, particularly in the FEFs.Some have argued that covert attention shiftsare slaved to the saccadic eye movement system(Rizzolatti et al. 1987), and neuroimagingstudies using fMRI have shown that covert andovert shifts of attention involve similar areas(Corbetta et al. 1998). However, single-unitphysiology studies in the macaque suggestimportant distinctions at the level of cellpopulations, with some cells in the FEFs activeduring saccades and a distinct but overlappingpopulation of cells involved in covert shifts ofattention (Schafer & Moore 2007, Thompsonet al. 2005). The cells responsible for covertshifts of attention also seem to hold the locationof cues during a delay interval (Armstrong et al.2009). The two populations of cells are mixedwithin the FEFs and, at least to date, have notbeen distinguished by fMRI. However, thephysiological data indicate that covert attentionis distinct from the motor system governingsaccades, even though they clearly interact.

As suggested by the FEF studies, it is impor-tant to be able to link the imaging and physi-ological results with other studies to providemore details on local computations. One strat-egy for doing so is to study the pharmacologyof each of the attention networks. Cholinergicsystems arising in the basal forebrain appear toplay a critical role in orienting; lesions of thebasal forebrain in monkeys interfere with ori-enting attention (Voytko et al. 1994). However,

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it appears that the site of this effect is not inthe basal forebrain per se, but instead involvesthe superior parietal lobe. Davidson & Mar-rocco (2000) made injections of scopolaminedirectly into the lateral intraparietal area ofmonkeys. This area corresponds to the humansuperior parietal lobe and contains cells inu-enced by cues about spatial location. The in-jections have a large effect on the monkeysability to shift attention to a target. Systemicinjections of scopolamine, an anticholinergic,have a smaller effect on covert orienting of at-tention than do local injections in the parietalarea. Cholinergic drugs do not affect the abil-ity of a warning signal to improve the mon-keys performance, so there appears to be a dou-ble dissociation, with NE involved mainly inthe alerting network and Ach involved in theorienting network. These observations in themonkey have been conrmed by similar studiesin the rat (Everitt & Robbins 1997). It is es-pecially signicant that comparisons in the ratstudies of cholinergic and dopaminergic mech-anisms have shown that only the former inu-ence the orienting response (Everitt & Robbins1997, Stewart et al. 2001).

The more ventral network including theTPJ (Figure 2a) seemed to be more active fol-lowing the target and was thus identied as partof a network responsive to sensory events. Itis strongly right lateralized and lesions in thisarea are central to the neglect syndrome, al-though the interaction ofTPJwithmore frontaland dorsal brain areas is also critical (Shulman& Corbetta 2012). Researchers generally agreeabout themembership of themajor nodes of theorienting network on the basis of both spatialcuing and visual search studies (Hillyard et al.2004, Wright & Ward 2008).

Perhaps more surprising is that the brainareas involved in orienting to visual stimuliseem to overlap strongly (within fMRI res-olution) with those involved with orientingto stimuli in other modalities (Driver et al.2004). Although attention operates on sensory-specic modalities according to the incomingtarget, the sources of this effect appear to becommon. There are also important synergies

between modalities. In many cases, orientingto a location will provide priority not only tothe expected modality but also to informationpresent at the same location from other modal-ities (Driver et al. 2004), indicating how closelythe sensory systems are integrated within theorienting network.

How can the sources of the orienting net-work described above inuence sensory com-putations? Anatomically, the source of the ori-enting effect lies in the network of parietal,frontal, and subcortical areas mentioned above.However, the inuence of attention is on thebottom-up signals arriving in sensory-specicareas: for vision, in the primary visual cortexand extrastriate areas moving forward towardthe temporal lobe. That this remote inuenceinvolves synchronizationbetween activity in themore dorsal attention areas and activity in themore ventral visual areas is an inuential idea(Womelsdorf et al. 2007). The synchronizationapparently leads to greater sensitivity in the vi-sual system, allowing faster responses to visualtargets and thus improved priority for process-ing targets.

In addition to synchronization, single-unitphysiology studies conducted within ventral vi-sual areas suggest that as items are added to avisual scene they tend to reduce the ring rate ofcells responding to the target stimulus. Atten-tion to a target seems to reduce the inuence ofother competing stimuli. This idea was impor-tant in the development of biased competitiontheory (Desimone & Duncan 1995). This the-ory sees attention as arising out of a winner-take-all competition within various levels ofsensory and association systems. fMRI studiesconrm that attention to a stimulus can occurprior to its arrival, changing the baseline neu-ral and blood oxygen leveldependent (BOLD)response, and that the overall BOLD activity isaffected in ways consistent with the biased com-petition theory (Desimone & Duncan 1995).

Executive Control

Our third original network has been elabo-rated considerably. As noted above, our original


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focus was on midline regions of the medialfrontal cortex and anterior cingulate. We sug-gested that activity found during the perfor-mance of tasks was related to focal attention be-cause trial-related activity in these regions wasgreater for targets than for nontargets, for con-ict more than for nonconict trials, and forerrors more than for correct trials. We arguedthat such a system might be very useful for pro-ducing top-down regulation, thus its relation-ship to executive control. This role of the ACCin top-down control was based on rather slimevidence at the time but seems to still seemsto be accurate and plays an important role intwo prominent theories of executive control inthe current literature. One theory stresses therole of the ACC in monitoring conict and inrelation to lateral frontal areas in resolving theconict (Botvinick et al. 2001, Carter & Krug2012). A different view arguing for two differenttop-down control networks is based on exten-sive studies of the specic aspects of the ACCduring task performance and correlations withother regions at rest (Figure 2b,c) (Dosenbachet al. 2006, 2007).

Support for two separate executive controlnetworks arises from studies designed to dis-cover signals related to top-down task control.Such signals might include those related to taskinstructions that are transient at the beginningof a task block (Figure 3). Transient blocktransition signals had been seen in earlier work(Donaldson et al. 2001, Fox et al. 2005, Konishiet al. 2001) with many different interpretations.A second type of activity is sustained acrossthe trials of the task, putatively related to themaintenance of task parameters/top-downcontrol (Figure 3). The third type of signal isrelated to performance feedback; an example ofsuch feedback would be systematic differencesbetween correct and incorrect trials (Figure 3).

Dosenbach et al. (2006) studied 10 differenttasks (including visual and auditory words andvisual objects as stimuli, with many differentdecision criteria, such as semantic, timing,and similarity judgments) searching for ev-idence of these signal types. Lateral frontaland parietal regions appeared to emphasize

transient signals at the beginning of blocks,whereas medial frontal/cingulate cortex andbilateral anterior insula also showed sustainedmaintenance signals across task conditions.Although these experiments identied a setof regions that could be involved in top-downtask level control, they provide no evidence ofthe relationships between regions.

Another experiment (Dosenbach et al.2007) looked for functional correlations (atrest) between regions that showed some orall of these putative control signals, with theidea that these functional connections maydene the systems-level relationships betweenthe regions. Lateral frontal and parietal re-gions that showed primarily start-cue activitycorrelated well with each other (Figure 2c).The midline and anterior insular regionsthat showed additional sustained activity alsocorrelated well with each other (Figure 2c),but these two sets of regions did not correlatestrongly with each other.

These results suggested there are two sepa-rable executive control networks. Detailed ev-idence for this view is found in Dosenbachet al. (2008). The frontoparietal network ap-pears to be distinct from the orienting net-workdiscussedpreviously,whereas the cingulo-opercular network overlaps with the originalexecutive network. If this view is correct, thereare two relatively separate executive networks.Although the best imaging evidence shows thatthe orienting and frontoparietal executive net-works are separate in adulthood, they may havea common origin in early development (seeSelf-Regulation section, below).

This breakdown of executive control intotwo separate networks is anatomically simi-lar to an inuential idea pertaining to cogni-tive control (Botvinick et al. 2001, Carter &Krug 2012). However, this cognitive controlview favors a single unied executive systemin which lateral prefrontal cortex provides top-down control signals, guided by performance-monitoring signals generated by midline struc-tures. Although the cognitive control view andthe ideas shown in Figure 2 are anatomicallysimilar, several specic functional differences

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Sustained

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Figure 3Executive control signals. The top panel shows three putative executive control signals: a task initiation signal in yellow, a task-maintenance signal in red, and activity related to correct (black) and error (blue) trials (adapted from Dosenbach et al. 2006). Regionsshowing differences in error versus correct trials are considered to be computing or receiving performance feedback. The bottom gureshows activity in the left anterior insula during a task that contains all the putative signals (plus a transient transition signal at the end ofthe block of trials). MR, magnetic resonance.

remain. In the dual network view (Dosenbachet al. 2008), the two executive systems act rel-atively independently in producing top-downcontrol. The cingulo-opercular control systemshows maintenance across trials and acts as

stable backgroundmaintenance for task perfor-mance as a whole. The frontoparietal system,in contrast, showing mostly start-cue signals, isthought to relate to task switching and initiationand to adjustments within trials in real time.


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Both the cognitive control view and the dualnetworks view explain a considerable amountof extant data, but we believe there are severalreasons to choose the latter formulation.

First, lesion studies in both humans and an-imals seem to indicate separate aspects of con-trol. Large lesions of the frontal midline oftenresult in akineticmutism inwhichpeople are ca-pable of carrying out goal-directed activities butdo not do so. On the other hand, patients withmore laterally placed lesions, including those inthe dorsolateral prefronal cortex (DLPFC) of-ten exhibit perseverations with an inability toswitch from one set to the other. In a com-pelling set of macaque experiments, Rossi et al.(2007) showed that a complete unilateral resec-tion of the DLPFC and an interruption of thecorpus callosum resulted in a unilateral inabil-ity to switch sets but an intact ability to adopt asustained set, consistent with the human lesiondata.

A second difference between the dual net-work and cognitive control views is concernedwith the directionality of relationships. Thecognitive control view requires a timing dif-ference between the midline monitoring pro-cesses and theDLPFC implementation regionswithin a trial. The two-network account is tol-erant of ordering effects because the two net-works operate separately. Two quite differentsets of data argue that cingulo-opercular in-volvement is often at the end of or after thetrial. The rst is from studies of single-unitactivity in the ACC in macaques (Ito et al.2003). During a saccade countermanding task,investigators found neurons that signaled er-rors and unexpected rewards after trial com-pletion. Second, a recent human imaging studyby Ploran et al. (2007) used a slow reveal task.During visual information processing, activ-ity progressively increased with increasing vi-sual information across several seconds in theDLPFC.This preceded late activity in theACCand anterior insula. These results are consistentwith the hypothesis that the ACC may oftenserve to monitor the consequences of actions,and they are inconsistent with a more rigiddirectionality.

The addition of two separate orienting net-works and two separate executive networksraises the possibility that additional control net-works will be elaborated in the future. How-ever, for several reasons, we do not expect thenumber of control networks to be much largerthan the number described here. The studyof many complex systems, from ecosystems toprotein-protein interactions, seems to indicatethat these systems follow a rule of hand andhave approximately ve controlling variables(ranging from three to seven) (Gunderson &Holling 2002). For example, the maintenanceof upright balanced posture appears to be con-trolled by at least three separate systems: vi-sion, the vestibular system, and kinesthetic jointsensors. These systems act relatively indepen-dently and have different spatial and temporalcharacteristics. From this perspective, the pres-ence of ve relatively separate attention net-works appears reasonable. A second argumentin favor of this view is an empirical one. Ina recent large-scale study of resting state net-works (Power et al. 2011), with effectively allthe brain represented, all the cortical networks,found by the more piecemeal approaches de-scribed above, are present.

EXTENDING THE FRAMEWORK

One of the gratifying outcomes of our originalpublication has been the many ways that theseideas inspired a large number of studies. Wereview extensions of the framework into newareas related to attention networks.

Self-Regulation

The ability to control our thoughts, feelings,and behavior in developmental psychologyis called self-regulation; with adults it isoften called self-control (see sidebar on Will,Self-Regulation, and Self-Control for furtherdenitions). Neuroimaging presents strongevidence that conict tasks such as the Stroopeffect activate common areas of the anteriorcingulate gyrus: the dorsal portion for morestrictly cognitive tasks and the ventral area foremotion-related tasks (Botvinick et al. 2001,

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WILL, SELF-REGULATION, AND SELF-CONTROL

Several names have been applied to the voluntary control of emotion and cognition. Duringchild development, these functions are often called self-regulation. This name provides aclear contrast to the regulation that occurs through the caregiver or other external sources.In adults, the same set of voluntary functions is frequently called self-control. Regulationmay also occur through nonvoluntary means, for example, by fear or by the calming aspectsof drugs or therapy. In all cases, self-control or self-regulation appears to be an ability tocontrol reexive or otherwise dominant responses to select less dominant ones.

Conict tasks: The Stroop effect involves the conict between the task of naming thecolor of ink of conicting color names (e.g., thewordGREENpresented inRED INK).TheStroop and other conict-related tasks have been used to measure the ability to select theless dominant response. Because the classic Stroop effect requires reading, other conicttasks such as spatial conict, anker conict, and pictorial conict have also been used.Imaging studies with adults suggest that the conict in these tasks have a common anatomy(Fan et al. 2003a).

Anatomy: The use of imaging has provided some evidence of a common brain networkthat is involved in all these senses of control. This network includes anterior cingulate (Bushet al. 2000) and anterior insula (Dosenbach et al. 2007; Sridharan et al. 2007, 2008) and alsoincludes areas of the prefrontal cortex when inhibition of dominant responses is a strongfeature (Fan et al. 2003a). The common involvement of the anterior cingulate in attentionand both emotion and cognitive control has provided one basis for the argument that theexecutive attention network is critical to these various functions. The brain activation ofconict-related tasks such as the Stroop has also been common to studies of attention andaspects of control.

Age: Self-regulation has been a concept used mainly in developmental psychology,whereas the terms cognitive control, self-control, and willpower are usually applied toadults. There appears to be no strict dividing line. A new nding is the important role of theorienting system in providing some of the control in infants and in young children (Posneret al. 2012, Rothbart et al. 2011). Even in adults, no doubt orienting to new sensory stimulior thoughts can be a self-control mechanism.

Future: The much broader term executive function is applied in psychology to self-control as well as the ability to solve problems, shift tasks, plan ahead, and implement goals.Although conict resolution has been studied widely with normals, the anatomy of otherfunctions remains to be thoroughly explored.

Bush et al. 2000). Although the cingulateanatomy is much more complex, the divisioninto cognitive and emotion-related areas hasbeen supported by more detailed anatomicalstudies (Beckmann et al. 2009).

Support for the voluntary exercise of self-regulation comes from studies that examine ei-ther the instruction to control affect or the con-nections involved in the exercise of that control.For example, the instruction to avoid arousal

during processing of erotic events (Beauregardet al. 2001) or to ward off emotion when look-ing at negative pictures (Ochsner et al. 2002)produces a locus of activation in midfrontaland cingulate areas. If people are required toselect an input modality, the cingulate showsfunctional connectivity to the selected sensorysystem (Crottaz-Herbette & Menon 2006) andin emotional tasks to limbic areas (Etkin et al.2006).


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Both behavioral and resting state functionaldata suggest substantial development of the ex-ecutive attention network between infancy andchildhood. A study of error detection in seven-month-old infants and adults (Berger et al.2006) shows that both ages use the anterior cin-gulate area, but the usual slowing following anerror does not seem present until about threeyears of age ( Jones et al. 2003). We recentlyproposed (Posner et al. 2012, Rothbart et al.2011) that during infancy control systems de-pend primarily on the orienting network as de-scribed previously. During later childhood andinto adulthood, the time to resolve conict cor-related with parent reports of their childs abil-ity to control his or her behavior (effortful con-trol, EC) (Posner & Rothbart 2007, Rothbartet al. 2011). The correlation between conictscores and parent reports of EC form one ba-sis for the association between self-regulationand executive attention. EC is also related tothe empathy that children show toward othersand their ability to delay an action as well as toavoid such behaviors as lying or cheating whengiven the opportunity. High levels of EC andthe ability to resolve conict are related to fewerantisocial behaviors in adolescents (Rothbart2011). These ndings show that self-regulationis a psychological function crucial for child so-cialization, and they suggest that it can also bestudied in terms of specic anatomical areas andtheir connections by examining the develop-ment of executive attention networks.

Differences in Network Efficiency

Although everyone has the attention net-works described above, there are also individualdifferences in the efciency of all brain net-works.TheAttentionNetworkTest (ANT) hasbeen used to examine the efciency of atten-tion networks (Fan et al. 2002). The task re-quires the person to press one key if the cen-tral arrow points to the left and another if itpoints to the right. Conict is introduced byhaving ankers surrounding the target point-ing in either the same (congruent) or opposite

(incongruent) direction as the target. Cues pre-sented prior to the target provide informationon where or when the target will occur. Thereare strong individual differences in each atten-tion network and there are surprisingly low cor-relations between these network scores (Fanet al. 2002), although the networks interact inmore complex tasks and in everyday life (Fanet al. 2009).

Normal functions including attention areundoubtedly inuenced by many genes incomplex interaction with epigenetic and envi-ronmental factors. Most studies have involvedvarious pathologies and have not centered oncommon human functions; hence relativelylittle is known about the full range of genesinvolved in attention networks. One strategywould be to use emerging genomic andepigenomic technologies to carry out studiesof large cohorts using various attention tasks asphenotypes to determine genes that relate toperformance differences. A more limitedapproach, based on what is known aboutattention networks, takes advantage of theassociation between different neuromodulatorsand attention networks to examine specicgenetic alleles (e.g., related to dopamine)to examine individual performance on theappropriate network (see Green et al. 2008 forreview). As one example, the ANT has beenused to examine individual differences in theefciency of executive attention. A numberof polymorphisms in dopamine and serotoningenes have been associated specically withthe scores on executive attention (Green et al.2008). This work is still just getting started,and reports are conicting. One reason for theconict may be that genetic variations are alsoinuenced by environmental factors.

Genetic modulation by environmental fac-tors is perhaps clearest for the dopamine 4 re-ceptor gene (DRD4), which has been associatedwith the executive network in adult imagingstudies (Fan et al. 2003b).Data at 1820monthsshowed that quality of parenting interactedwith the 7 repeat allele of the DRD4 geneto inuence the temperamental dimensions of

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impulsivity, high-intensity pleasure and activitylevel, and all components of sensation seeking(Sheese et al. 2007). Parenting made a strongdifference for children with the 7 repeat al-lele inmoderating sensation seeking but not forthose children without this allele. At 34 yearsof age, the DRD4 gene interaction with par-enting was related to childrens EC, suggestingthat executive attention may be the mechanismfor this interaction. One study found that onlythose children with the 7-repeat of the DRD4showed the inuence of a parent training inter-vention (Bakermans-Kranenburg et al. 2008),suggesting that the presence of the DRD47 repeat allele maymake the child more suscep-tible to environmental inuences (Bakermans-Kranenburg & Van IJzendoorn 2011, Belsky &Pluess 2009, Sheese et al. 2007). This joint in-uence of environment and genetics seems tocontinue into adulthood (Larsen et al. 2010).

Training

Because parenting and other cultural factorsinteract with genes to inuence behavior, itshould be possible to develop specic trainingmethods that can be used to inuence under-lying brain networks. Two forms of trainingmethods have been used in the literature. Oneinvolves practice of a particular attention net-work. Several such attention training studieshave shown improved executive attention func-tion and produced changes in attention-relatedbrain areas (Klingberg 2011, Rueda et al. 2005).The practice of a form of meditation has beenused to change the brain state in a way thatimproves attention, reduces stress, and also im-proves functional connectivity between the an-terior cingulate and the striatum (Tang et al.2007, 2009).

Evolution

The ACC is a phylogenetically old area of thebrain. Comparative anatomical studies pointto important differences in the evolution ofcingulate connectivity between nonhuman

primates and humans. Anatomical studies showgreat expansion of white matter, which hasincreased more in recent evolution than hasthe neocortex itself (Zilles 2005). One type ofprojection cell called a Von Economo neuron isfound only in higher apes and a few other socialspecies, but they are most common in humans.In the human brain, the Von Economo neu-rons are found only in the anterior cingulateand a related area of the anterior insula(Allman et al. 2005). This neuron is likely im-portant in communication between the cingu-late and other brain areas. The two brain areasin which Von Economo neurons are found(cingulate and anterior insula) are also shown tobe in close communication during the restingstate (Dosenbach et al. 2007). It is not clear,however, if the distribution of Von Economoneurons and the cingulo-opercular networkare overlapping or closely juxtaposed (Poweret al. 2011). Some evidence indicates that thefrequency of this type of neuron increases inhuman development between infancy and laterchildhood (Allman et al. 2005). These neuronsmay provide the rapid and efcient connectivityneeded for executive control and may helpexplain why self-regulation in adult humans canbe so much stronger than in other organisms.

FUTURE

It has been exciting for us to see the expan-sion of work on networks of attention over thepast 20 years. We now have the opportunity togo from genes to cells, networks, and behaviorand to examine how these relationships changefrom infancy to old age. In development, thenumber of active control systems increases andtheir inuence changes.

Although much has been learned, manyquestions remain unanswered. We are hopefulthat the study of attention will continue toprovide greater understanding of how controldevelops typically and in pathology (Posner2012a, Posner et al. 2011) and will providepromising leads for translating basic researchinto interventions to aid children and families.


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FranciscoResaltado


DISCLOSURE STATEMENT

The authors are not aware of any afliations, memberships, funding, or nancial holdings thatmight be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS

This article was supported in part by grant HD060563 to Georgia State University subcontractedto theUniversity ofOregon. Prof.MaryK.Rothbartmade important contributions to the researchand writing of this review. This article was also supported by NIH grants NS32797 and 61144and the McDonnell Foundation.

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NE35-FrontMatter ARI 21 May 2012 11:24

Annual Review ofNeuroscience

Volume 35, 2012Contents

The Neural Basis of EmpathyBoris C. Bernhardt and Tania Singer 1

Cellular Pathways of Hereditary Spastic ParaplegiaCraig Blackstone 25

Functional Consequences of Mutations in Postsynaptic ScaffoldingProteins and Relevance to Psychiatric DisordersJonathan T. Ting, Joao Peca, and Guoping Feng 49

The Attention System of the Human Brain: 20 Years AfterSteven E. Petersen and Michael I. Posner 73

Primary Visual Cortex: Awareness and BlindsightDavid A. Leopold 91

Evolution of Synapse Complexity and DiversityRichard D. Emes and Seth G.N. Grant 111

Social Control of the BrainRussell D. Fernald 133

Under Pressure: Cellular and Molecular Responses During Glaucoma,a Common Neurodegeneration with AxonopathyRobert W. Nickells, Gareth R. Howell, Ileana Soto, and Simon W.M. John 153

Early Events in Axon/Dendrite PolarizationPei-lin Cheng and Mu-ming Poo 181

Mechanisms of Gamma OscillationsGyorgy Buzsaki and Xiao-Jing Wang 203

The Restless Engram: Consolidations Never EndYadin Dudai 227

The Physiology of the Axon Initial SegmentKevin J. Bender and Laurence O. Trussell 249

Attractor Dynamics of Spatially Correlated Neural Activity in theLimbic SystemJames J. Knierim and Kechen Zhang 267

Neural Basis of Reinforcement Learning and Decision MakingDaeyeol Lee, Hyojung Seo, and Min Whan Jung 287

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NE35-FrontMatter ARI 21 May 2012 11:24

Critical-Period Plasticity in the Visual CortexChristiaan N. Levelt and Mark Hubener 309

What Is the Brain-Cancer Connection?Lei Cao and Matthew J. During 331

The Role of Organizers in Patterning the Nervous SystemClemens Kiecker and Andrew Lumsden 347

The Complement System: An Unexpected Role in Synaptic PruningDuring Development and DiseaseAlexander H. Stephan, Ben A. Barres, and Beth Stevens 369

Brain Plasticity Through the Life Span: Learning to Learn and ActionVideo GamesDaphne Bavelier, C. Shawn Green, Alexandre Pouget, and Paul Schrater 391

The Pathophysiology of Fragile X (and What It Teaches Us aboutSynapses)Asha L. Bhakar, Gul Dolen, and Mark F. Bear 417

Central and Peripheral Circadian Clocks in MammalsJennifer A. Mohawk, Carla B. Green, and Joseph S. Takahashi 445

Decision-Related Activity in Sensory Neurons: Correlations AmongNeurons and with BehaviorHendrikje Nienborg, Marlene R. Cohen, and Bruce G. Cumming 463

Compressed Sensing, Sparsity, and Dimensionality in NeuronalInformation Processing and Data AnalysisSurya Ganguli and Haim Sompolinsky 485

The Auditory Hair Cell Ribbon Synapse: From Assembly to FunctionSaaid Saeddine, Aziz El-Amraoui, and Christine Petit 509

Multiple Functions of Endocannabinoid Signaling in the BrainIstvan Katona and Tamas F. Freund 529

Circuits for Skilled Reaching and GraspingBror Alstermark and Tadashi Isa 559

Indexes

Cumulative Index of Contributing Authors, Volumes 2635 579

Cumulative Index of Chapter Titles, Volumes 2635 583

Errata

An online log of corrections to Annual Review of Neuroscience articles may be found athttp://neuro.annualreviews.org/

viii Contents

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AnnuAl Reviewsits about time. Your time. its time well spent.

AnnuAl Reviews | Connect with Our expertsTel: 800.523.8635 (us/can) | Tel: 650.493.4400 | Fax: 650.424.0910 | Email: [email protected]

New From Annual Reviews:Annual Review of Statistics and Its ApplicationVolume 1 Online January 2014 http://statistics.annualreviews.org

Editor: Stephen E. Fienberg, Carnegie Mellon UniversityAssociate Editors: Nancy Reid, University of Toronto

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table of contents:What Is Statistics? Stephen E. FienbergA Systematic Statistical Approach to Evaluating Evidence

from Observational Studies, David Madigan, Paul E. Stang, Jesse A. Berlin, Martijn Schuemie, J. Marc Overhage, Marc A. Suchard, Bill Dumouchel, Abraham G. Hartzema, Patrick B. Ryan

The Role of Statistics in the Discovery of a Higgs Boson, David A. van Dyk

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Structured Regularizers for High-Dimensional Problems: Statistical and Computational Issues, Martin J. Wainwright

High-Dimensional Statistics with a View Toward Applications in Biology, Peter Bhlmann, Markus Kalisch, Lukas Meier

Next-Generation Statistical Genetics: Modeling, Penalization, and Optimization in High-Dimensional Data, Kenneth Lange, Jeanette C. Papp, Janet S. Sinsheimer, Eric M. Sobel

Breaking Bad: Two Decades of Life-Course Data Analysis in Criminology, Developmental Psychology, and Beyond, Elena A. Erosheva, Ross L. Matsueda, Donatello Telesca

Event History Analysis, Niels KeidingStatisticalEvaluationofForensicDNAProfileEvidence,

Christopher D. Steele, David J. BaldingUsing League Table Rankings in Public Policy Formation:

Statistical Issues, Harvey GoldsteinStatistical Ecology, Ruth KingEstimating the Number of Species in Microbial Diversity

Studies, John Bunge, Amy Willis, Fiona WalshDynamic Treatment Regimes, Bibhas Chakraborty,

Susan A. MurphyStatistics and Related Topics in Single-Molecule Biophysics,

Hong Qian, S.C. KouStatistics and Quantitative Risk Management for Banking

and Insurance, Paul Embrechts, Marius Hofert

Access this and all other Annual Reviews journals via your institution at www.annualreviews.org.

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Annual Reviews OnlineSearch Annual ReviewsAnnual Review of NeuroscienceOnlineMost Downloaded Neuroscience Reviews Most Cited Neuroscience Reviews Annual Review of Neuroscience Errata View Current Editorial Committee

All Articles in the Annual Review of Neuroscience, Vol. 35The Neural Basis of EmpathyCellular Pathways of Hereditary Spastic ParaplegiaFunctional Consequences of Mutations in Postsynaptic Scaffolding Proteins and Relevance to Psychiatric DisordersThe Attention System of the Human Brain: 20 Years AfterPrimary Visual Cortex: Awareness and BlindsightEvolution of Synapse Complexity and DiversitySocial Control of the BrainUnder Pressure: Cellular and Molecular Responses During Glaucoma, a Common Neurodegeneration with AxonopathyEarly Events in Axon/Dendrite PolarizationMechanisms of Gamma OscillationsThe Restless Engram: Consolidations Never EndThe Physiology of the Axon Initial SegmentAttractor Dynamics of Spatially Correlated Neural Activity in the Limbic SystemNeural Basis of Reinforcement Learning and Decision MakingCritical-Period Plasticity in the Visual CortexWhat Is the Brain-Cancer Connection?The Role of Organizers in Patterning the Nervous SystemThe Complement System: An Unexpected Role in Synaptic Pruning During Development and DiseaseBrain Plasticity Through the Life Span: Learning to Learn and Action Video GamesThe Pathophysiology of Fragile X (and What It Teaches Us about Synapses)Central and Peripheral Circadian Clocks in MammalsDecision-Related Activity in Sensory Neurons: Correlations Among Neurons and with BehaviorCompressed Sensing, Sparsity, and Dimensionality in Neuronal Information Processing and Data AnalysisThe Auditory Hair Cell Ribbon Synapse: From Assembly to FunctionMultiple Functions of Endocannabinoid Signaling in the BrainCircuits for Skilled Reaching and Grasping

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The Attention System of the Human Brain (Posner & Petersen) (2012)

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