-
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.
73
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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
74 Petersen Posner
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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
aPFC aPFC
aPFC
mCC
dlPFCdFC
dlPFCdFC
dACC/msFC
Precuneus Precuneus
Thalamus Thalamus
al/fO al/fO
IPL
IPS
TPJ(IPL/STG)
VFC(IFg/MFg)
a
b
c
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
76 Petersen Posner
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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.
www.annualreviews.org The Attention System of the Human Brain
77
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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,
78 Petersen Posner
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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
www.annualreviews.org The Attention System of the Human Brain
79
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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
80 Petersen Posner
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
Sustained
Correcttrials
Errors CueCue
start +
fixate fixate
+ stop
0.1
0.1
0
0.2
0.3
0.4
1 7
% c
hang
e
Time (MR frames)
Trial-relatedb
a
ErrorCorrect
0.1
0.1
0
0.2
0.3
0.4
1 41
% c
hang
e
Time (MR frames)
Task-related (adjusted)
Transienttask-
initiationsignal
11 3121
Sustained maintenance signal
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.
www.annualreviews.org The Attention System of the Human Brain
81
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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,
82 Petersen Posner
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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).
www.annualreviews.org The Attention System of the Human Brain
83
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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
84 Petersen Posner
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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.
www.annualreviews.org The Attention System of the Human Brain
85
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
FranciscoResaltado
-
NE35CH04-Petersen ARI 14 May 2012 11:42
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.
LITERATURE CITED
Allman JM, Watson KK, Tetreault NA, Hakeem AY. 2005. Intuition
and autism: a possible role for VonEconomo neurons. Trends Cogn.
Sci. 9:36773
Armstrong KM, Chang MH, Moore T. 2009. Selection and maintenance
of spatial information by frontal eyeeld neurons. J. Neurosci.
29:1562129
Aston-Jones G, Cohen JD. 2005. An integrative theory of locus
coeruleus-norepinephrine function: adaptivegain and optimal
performance. Annu. Rev. Neurosci. 28:40350
Bakermans-Kranenburg MJ, Van IJzendoorn MH. 2011. Differential
susceptibility to rearing environmentdepending on dopamine-related
genes: new evidence and a meta-analysis. Dev. Psychopathol.
23:3952
Bakermans-Kranenburg MJ, Van IJzendoorn MH, Pijlman FT, Mesman
J, Juffer F. 2008. Experimentalevidence for differential
susceptibility: dopamine D4 receptor polymorphism (DRD4 VNTR)
moderatesintervention effects on toddlers externalizing behavior in
a randomized controlled trial. Dev. Psychol.44:293300
Beane M, Marrocco RT. 2004. Norepinephrine and acetylcholine
mediation of the components of reexiveattention: implications for
attention decit disorders. Prog. Neurobiol. 74:16781
Beauregard M, Levesque J, Bourgouin P. 2001. Neural correlates
of conscious self-regulation of emotion.J. Neurosci. 21:RC165
Beckmann M, Johansen-Berg H, Rushworth MFS. 2009.
Connectivity-based parcellation of human cingulatecortex and its
relation to functional specialization. J. Neurosci. 29:117590
Belsky J, PluessM. 2009. Beyond diathesis stress: differential
susceptibility to environmental inuences.Psychol.Bull.
135:885908
Berger A, Tzur G, Posner MI. 2006. Infant brains detect
arithmetic errors. Proc. Natl. Acad. Sci. USA103:1264953
BotvinickMM,BraverTS, BarchDM,CarterCS,Cohen JD.
2001.Conictmonitoring and cognitive control.Psychol. Rev.
108:62452
Bush G, Luu P, Posner MI. 2000. Cognitive and emotional inuences
in anterior cingulate cortex. TrendsCogn. Sci. 4:21522
Carter CS, Krug MK. 2012. Dynamic cognitive control and
frontal-cingulate interactions. See Posner 2012b,pp. 8998
Corbetta M, Akbudak E, Conturo TE, Snyder AZ, Ollinger JM, et
al. 1998. A common network of functionalareas for attention and eye
movements. Neuron 21:76173
Corbetta M, Shulman GL. 2002. Control of goal-directed and
stimulus-driven attention in the brain. Nat.Rev. Neurosci.
3:20115
Coull JT, FrithCD, Buchel C,Nobre AC. 2000.Orienting attention
in time: behavioural and neuroanatomicaldistinction between
exogenous and endogenous shifts. Neuropsychologia 38:80819
Crottaz-Herbette S, Menon V. 2006. Where and when the anterior
cingulate cortex modulates attentionalresponse: combined fMRI and
ERP evidence. J. Cogn. Neurosci. 18:76680
Davidson MC, Marrocco RT. 2000. Local infusion of scopolamine
into intraparietal cortex slows covertorienting in rhesus monkeys.
J. Neurophysiol. 83:153649
86 Petersen Posner
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
Dehaene S, Changeux JP. 2011. Experimental and theoretical
approaches to conscious processing. Neuron70:20027
Dehaene S, Posner MI, Tucker DM. 1994. Localization of a neural
system for error detection and compen-sation. Psychol. Sci.
5:3035
DesimoneR,Duncan J. 1995.Neuralmechanisms of selective visual
attention.Annu. Rev. Neurosci. 18:193222Donaldson DI, Petersen SE,
Ollinger JM, Buckner RL. 2001. Dissociating state and item
components of
recognition memory using fMRI. Neuroimage 13:12942Dosenbach NUF,
Fair DA, Cohen AL, Schlaggar BL, Petersen SE. 2008. A dual-networks
architecture of
top-down control. Trends Cogn. Sci. 12:99105Dosenbach NUF, Fair
DA, Miezin FM, Cohen AL, Wenger KK, et al. 2007. Distinct brain
networks for
adaptive and stable task control in humans. Proc. Natl. Acad.
Sci. USA 104:1107378Dosenbach NUF, Visscher KM, Palmer ED, Miezin
FM, Wenger KK, et al. 2006. A core system for the
implementation of task sets. Neuron 50:799812Driver J, Eimer M,
Macaluso E, van Velzen J. 2004. Neurobiology of human spatial
attention: modulation,
generation, and integration. See Kanwisher & Duncan 2004,
pp. 267300Duncan J. 1980. The locus of interference in the
perception of simultaneous stimuli. Psychol. Rev.
87:272300EisenbergerNI, LiebermanMD,WilliamsKD. 2003.Does rejection
hurt? An FMRI study of social exclusion.
Science 302:29092Etkin A, Egner T, Peraza DM, Kandel ER, Hirsch
J. 2006. Resolving emotional conict: a role for the rostral
anterior cingulate cortex in modulating activity in the
amygdala. Neuron 51:87182Everitt BJ, Robbins TW. 1997. Central
cholinergic systems and cognition. Annu. Rev. Psychol. 48:64984Fan
J, Flombaum JI, McCandliss BD, Thomas KM, Posner MI. 2003a.
Cognitive and brain consequences of
conict. Neuroimage 18:4257Fan J, Fossella J, Sommer T, Wu Y,
Posner MI. 2003b. Mapping the genetic variation of executive
attention
onto brain activity. Proc. Natl. Acad. Sci. USA 100:740611Fan J,
Gu X, Guise KG, Liu X, Fossella J, et al. 2009. Testing the
behavioral interaction and integration of
attentional networks. Brain Cogn. 70:20920Fan J, McCandliss BD,
Fossella J, Flombaum JI, Posner MI. 2005. The activation of
attentional networks.
Neuroimage 26:47179Fan J, McCandliss BD, Sommer T, Raz A, Posner
MI. 2002. Testing the efciency and independence of
attentional networks. J. Cogn. Neurosci. 14:34047Fernandez-Duque
D, Posner MI. 1997. Relating the mechanisms of orienting and
alerting. Neuropsychologia
35:47786Fox MD, Snyder AZ, Barch DM, Gusnard DA, Raichle ME.
2005. Transient BOLD responses at block
transitions. Neuroimage 28:95666Green AE, Munafo MR, DeYoung CG,
Fossella JA, Fan J, Gray JR. 2008. Using genetic data in
cognitive
neuroscience: from growing pains to genuine insights. Nat. Rev.
Neurosci. 9:71020Gunderson LH, Holling CS. 2002. Panarchy:
Understanding Transformations in Human and Natural Systems.
Washington, DC: IslandHampton AN, ODoherty JP. 2007. Decoding
the neural substrates of reward-related decision making with
functional MRI. Proc. Natl. Acad. Sci. USA 104:137782Harter MR,
Guido W. 1980. Attention to pattern orientation: negative cortical
potentials, reaction time, and
the selection process. Electroencephalogr. Clin. Neurophysiol.
49:46175Hillyard SA, Di Russo F, Martinez A. 2004. The imaging of
visual attention. See Kanwisher & Duncan 2004,
pp. 38190Hubbard EM, Piazza M, Pinel P, Dehaene S. 2005.
Interactions between number and space in parietal cortex.
Nat. Rev. Neurosci. 6:43548Ito S, Stuphorn V, Brown JW, Schall
JD. 2003. Performance monitoring by the anterior cingulate
cortex
during saccade countermanding. Science 302:12022Ivry R,
Robertson LC. 1997. Two Sides of Perception. Cambridge, MA: MIT
PressJones L, Rothbart MK, Posner MI. 2003. Development of
inhibitory control in preschool children. Dev. Sci.
6:498504
www.annualreviews.org The Attention System of the Human Brain
87
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
Kampe KK, Frith CD, Frith U. 2003. Hey John: signals conveying
communicative intention toward theself activate brain regions
associated with mentalizing, regardless of modality. J. Neurosci.
23:525863
Kanwisher N, Duncan J, eds. 2004. Attention and Performance XX:
Functional Brain Imaging of Visual Cognition.Oxford, UK: Oxford
Univ. Press
Klingberg T. 2012. Training working memory and attention. See
Posner 2012b, pp. 47586Konishi S,DonaldsonDI, BucknerRL.
2001.Transient activation during block transition.Neuroimage
13:364
74Larsen H, van der Zwaluw CS, Overbeek G, Granic I, Franke B,
Engels RC. 2010. A variable-number-of-
tandem-repeats polymorphism in the dopamine D4 receptor gene
affects social adaptation of alcohol use:investigation of a
gene-environment interaction. Psychol. Sci. 21:106468
Lindner A, Iyer A, Kagan I, Andersen RA. 2010. Human posterior
parietal cortex plans where to reach andwhat to avoid. J. Neurosci.
30:1171525
Marrocco RT, Davidson MC. 1998. Neurochemistry of attention. In
The Attentive Brain, ed. R Parasuraman,pp. 3550. Cambridge, MA: MIT
Press
Morrison JH, Foote SL. 1986. Noradrenergic and serotoninergic
innervation of cortical, thalamic and tectalvisual structures in
Old and New World monkeys. J. Comp. Neurol. 243:11728
Moruzzi G, Magoun HW. 1949. Brainstem reticular formation and
activation of the EEG. Electroencephalogr.Clin. Neurophysiol.
1:45573
Nagai Y, Critchley HD, Featherstone E, Fenwick PB, Trimble MR,
Dolan RJ. 2004. Brain activity relatingto the contingent negative
variation: an fMRI investigation. Neuroimage 21:123241
Ochsner KN, Bunge SA, Gross JJ, Gabrieli JD. 2002. Rethinking
feelings: an FMRI study of the cognitiveregulation of emotion. J.
Cogn. Neurosci. 14:121529
Ploran EJ, Nelson SM, Velanova K, Donaldson DI, Petersen SE,
Wheeler ME. 2007. Evidence accumulationand the moment of
recognition: dissociating perceptual recognition processes using
fMRI. J. Neurosci.27:1191224
Posner MI. 1975. Psychobiology of attention. In Handbook of
Psychobiology, ed. M Gazzaniga, C Blakemore,pp. 44180. New York:
Academic
Posner MI. 2012a. Attention in the Social World. New York:
Oxford Univ. PressPosner MI. 2012b. Cognitive Neuroscience of
Attention. New York: GuilfordPosner MI, Petersen SE. 1990. The
attention system of the human brain. Annu. Rev. Neurosci.
13:2542PosnerMI, RothbartMK. 2007. Research on attention networks
as amodel for the integration of psychological
science. Annu. Rev. Psychol. 58:123Posner MI, Rothbart MK,
Sheese BE, Voelker P. 2012. Control networks and neuromodulators of
early
development. Dev. Psychol. In pressPower JD, Cohen AL, Nelson
SM, Vogel AC, Church JA, et al. 2011. Functional network
organization in the
human brain. Neuron 72:66578Rainville P, Duncan GH, Price DD,
Carrier B, Bushnell MC. 1997. Pain affect encoded in human
anterior
cingulate but not somatosensory cortex. Science
277:96871Rizzolatti G, Riggio L, Dascola I, Umilta C. 1987.
Reorienting attention across the horizontal and vertical
meridians: evidence in favor of a premotor theory of attention.
Neuropsychologia 25:3140Rossi AF, Bichot NP, Desimone R,
Ungerleider LG. 2007. Top down attentional decits in macaques
with
lesions of lateral prefrontal cortex. J. Neurosci.
27:1130614Rothbart MK. 2011. Becoming Who We Are. New York:
GuilfordRothbart MK, Sheese BE, Rueda MR, Posner MI. 2011.
Developing mechanisms of self-regulation in early
life. Emot. Rev. 3:20713Rueda MR, Rothbart MK, McCandliss BD,
Saccomanno L, Posner MI. 2005. Training, maturation, and
genetic inuences on the development of executive attention.
Proc. Natl. Acad. Sci. USA 102:1493136Schafer RJ, Moore T. 2007.
Attention governs action in the primate frontal eye eld. Neuron
56:54151Sheese BE, Voelker PM, Rothbart MK, Posner MI. 2007.
Parenting quality interacts with genetic variation
in dopamine receptor D4 to inuence temperament in early
childhood. Dev. Psychopathol. 19:103946Shulman GL, Corbetta M.
2012. Two attentional networks: identication and function within a
larger cog-
nitive architecture. See Posner 2012b, pp. 11327
88 Petersen Posner
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
NE35CH04-Petersen ARI 14 May 2012 11:42
Sridharan D, Levitin DJ, Chafe CH, Berger J, Menon V. 2007.
Neural dynamics of event segmentation inmusic: converging evidence
for dissociable ventral and dorsal networks. Neuron 55:52132
Sridharan D, Levitin DJ, Menon V. 2008. A critical role for the
right fronto-insular cortex in switchingbetween central-executive
and default-mode networks. Proc. Natl. Acad. Sci. USA
105:1256974
Stewart C, Burke S, Marrocco R. 2001. Cholinergic modulation of
covert attention in the rat. Psychopharma-cology 155:21018
Sturm W, Willmes K. 2001. On the functional neuroanatomy of
intrinsic and phasic alertness. Neuroimage14:S7684
Tang YY, Ma Y, Fan Y, Feng H, Wang J, et al. 2009. Central and
autonomic nervous system interaction isaltered by short-term
meditation. Proc. Natl. Acad. Sci. USA 106:886570
Tang YY, Ma Y, Wang J, Fan Y, Feng S, et al. 2007. Short-term
meditation training improves attention andself-regulation. Proc.
Natl. Acad. Sci. USA 104:1715256
Thompson KG, Biscoe KL, Sato TR. 2005. Neuronal basis of covert
spatial attention in the frontal eye eld.J. Neurosci. 25:947987
Voytko ML, Olton DS, Richardson RT, Gorman LK, Tobin JR, Price
DL. 1994. Basal forebrain lesions inmonkeys disrupt attention but
not learning and memory. J. Neurosci. 14:16786
Walter G. 1964. The convergence and interaction of visual,
auditory, and tactile responses in human non-specic cortex. Ann. N.
Y. Acad. Sci. 112:32061
Womelsdorf T, Schoffelen JM, Oostenveld R, Singer W, Desimone R,
et al. 2007. Modulation of neuronalinteractions through neuronal
synchronization. Science 316:160912
Wright RD, Ward LM. 2008. Orienting of Attention. Oxford/New
York: Oxford Univ. PressZilles K. 2005. Evolution of the human
brain and comparative cyto- and receptor architecture. In
FromMonkey
Brain to Human Brain, ed. S Dehaene, J-R Duhamel, MD Hauser, G
Rizzolatti, pp. 4156. Cambridge,MA: MIT Press/Bradford Books
www.annualreviews.org The Attention System of the Human Brain
89
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
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
vii
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
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
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
-
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
Stephen M. Stigler, University of ChicagoThe Annual Review of
Statistics and Its Application aims to inform statisticians and
quantitative methodologists, as well as all scientists and users of
statistics about major methodological advances and the
computational tools that allow for their implementation. It will
include developments in the field of statistics, including
theoretical statistical underpinnings of new methodology, as well
as developments in specific application domains such as
biostatistics and bioinformatics, economics, machine learning,
psychology, sociology, and aspects of the physical sciences.
Complimentary online access to the first volume will be
available until January 2015.
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
Brain Imaging Analysis, F. DuBois BowmanStatistics and Climate,
Peter GuttorpClimate Simulators and Climate Projections,
Jonathan Rougier, Michael GoldsteinProbabilistic Forecasting,
Tilmann Gneiting,
Matthias KatzfussBayesian Computational Tools, Christian P.
RobertBayesian Computation Via Markov Chain Monte Carlo,
Radu V. Craiu, Jeffrey S. Rosenthal
Build, Compute, Critique, Repeat: Data Analysis with Latent
Variable Models, David M. Blei
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.
Ann
u. R
ev. N
euro
sci.
2012
.35:
73-8
9. D
ownl
oade
d fro
m w
ww
.annu
alre
view
s.org
A
cces
s pro
vide
d by
Uni
vers
idad
de
Talc
a on
03/
27/1
5. F
or p
erso
nal u
se o
nly.
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
ar: logo: