The Reorienting System of the Human Brain:
From Environment to Theory of Mind
Maurizio Corbetta,1,2,3,4,* Gaurav Patel,2,3and Gordon L. Shulman1,4,*
1Department of Neurology
2Department of Radiology
3Department of Anatomy and Neurobiology
Washington University School of Medicine, St. Louis, MO 63110, USA
4These authors have contributed equally to this work.
*Correspondence: firstname.lastname@example.org (M.C.), email@example.com (G.L.S.)
or threatening stimuli. This ‘‘reorienting’’ response involves the coordinated action of a right hemisphere
dominantventralfrontoparietal networkthatinterruptsandresetsongoingactivityandadorsal frontoparietal
network specialized for selecting and linking stimuli and responses. At rest, each network is distinct and
internally correlated, but when attention is focused, the ventral network is suppressed to prevent reorienting
from the locus coeruleus/norepinephrine system. While originally conceptualized as a system for redirecting
attention from one object to another, recent evidence suggests a more general role in switching between
networks, which may explain recent evidence of its involvement in functions such as social cognition.
To safely navigate the environment, survive, and reproduce, an-
imals and people must rapidly select sensory information that is
relevant to their goals (e.g., routes, food, mates). They must also
quickly redirect their attention and change their course of action
when faced with novel, potentially threatening, or rewarding
stimuli. The complex set of adjustments in response to novel
and unexpected stimuli is defined here as a reorienting re-
sponse. Reorienting may occur between two environmental
stimuli, such as when we orient to the siren of an ambulance
while reading a newspaper, or between an internally directed
activity and the environment, as when the same siren interrupts
a train of thought. While several autonomic and motor responses
can be triggered by novel sensory stimuli through subcortical re-
flexes that are largely automatic and unconscious (the orienting
reflex; Sokolov, 1963), more recent work indicates that this
adaptive behavior involves a complex interaction between corti-
cal systems specialized for the selection of sensory information.
A dorsal frontoparietal (or dorsal attention) network enables the
selection of sensory stimuli based on internal goals or expecta-
tions (goal-driven attention) and links them to appropriate motor
responses. A ventral frontoparietal (or ventral attention) network
detects salient and behaviorally relevant stimuli in the environ-
ment, especially when unattended (stimulus-driven attention).
These systems dynamically interact during normal perception
to determine where and what we attend to. In this paper, we re-
view evidencefromneuroimaging, neuropsychology, andneuro-
physiology on the role of these two networks, particularly the
ventral network, in the reorienting response.
The Psychology of Attention to Environmental Stimuli
Psychological theories of attention are often concerned with
simple behavioral goals, such as finding an object with particular
features (Treisman and Gelade, 1980; Wolfe, 1994) or at a partic-
ular location (Eriksen and Hoffman, 1974; Posner, 1980) and
responding to it in an appropriate manner (Hommel, 2000).
This form of selection is labeled ‘‘goal-driven’’ or ‘‘endogenous’’
toemphasize theinternal ortop-downsignalsthatguide percep-
tion through a dynamic interaction with sensory or bottom-up
information. The biased-competition model of attention, for
example, proposes that objects in a visual scene compete for
access to visual short-term memory and that the competition
is biased by top-down signals that promote access of behavior-
ally relevant objects (Desimone and Duncan, 1995). These top-
down signals, characterized as working memory (e.g., Downing,
2000; but see Woodman and Luck, 2007), long-term memory
(Moores et al., 2003), or action related (Craighero et al., 2002;
Rosenbaum, 1991), interact with sensory (bottom-up) signals
produced by objects in the visual scene, enabling the desired
object to be selectively perceived and entered into memory
at the expense of unimportant objects (Bundesen, 1990; Wolfe,
1994). For instance, Figure 1A shows a student who focuses
on his computer desktop while writing his thesis and ignores
surrounding objects and people.
Adaptive behavior, however, also requires that we respond to
objects that are outside the current focus of attention, i.e., that
do not match current settings for selecting stimuli and re-
sponses. The object we are looking for may appear with different
features than we expected or at a different location. More impor-
ent course of action. While the student looks at the computer
screen, a colleague may ask a question (Figure 1B), or while a
monkey searches for food, a predator may appear. Moreover,
we are engaged in ‘‘internally directed’’ activities that do not in-
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
us while we are considering the meaning of a sentence in the
thesis we are writing, or a monkey may quickly react to the
appearance of a predator while grooming or eating.
Reorienting to new objects may occur reflexively, based on
their high sensory salience (Jonides and Yantis, 1988), particu-
larly when we do not have a specific task to do (Pashler and
Harris, 2001),but distinctive objects attract attention more effec-
tively when they are also behaviorally relevant (Yantis and
Egeth, 1999), either because they match our current goals or
because of long-term memory associations that signal their im-
portance, as when we hear the phone ringing or the siren of an
ambulance. In fact, the degree to which a distinctive but entirely
irrelevant object can attract our attention, so-called exogenous
attention, is controversial (Folk et al., 1992; Gibson and Kelsey,
1998; Jonides, 1981; Posner and Cohen, 1984; Theeuwes and
Burger, 1998; Yantis and Egeth, 1999). In some cases, shifts of
attention to a distinctive stimulus can be part of a task goal
(Bacon and Egeth, 1994), as when someone tries to detect any
tive but irrelevant objects may share a specific feature with our
current goal, as when we notice someone wearing a red sweater
while looking for a friend with a red hat (Folk et al., 1992; Gibson
and Kelsey, 1998).
A Neuroanatomical Model of Attention: Dorsal
and Ventral Attention Networks
Several lines of evidence indicate thattwo cortico-cortical neural
systems are involved in attending to environmental stimuli
(Corbetta and Shulman, 2002). A dorsal frontoparietal network,
whose core regions include dorsal parietal cortex, particularly
intraparietal sulcus (IPS) and superior parietal lobule (SPL), and
dorsal frontal cortex along the precentral sulcus, near or at the
frontal eye field (FEF) (Figure 2A, blue areas), embodies the
top-down control mechanism proposed by biased competition
and related theories (Bundesen, 1990; Desimone and Duncan,
1995; Wolfe, 1994). The dorsal system generates and maintains
endogenous signals based on current goals and preexisting
information about likely contingencies and sends out top-down
signals that bias the processing of appropriate stimulus features
and locations in sensory cortex. This conclusion is based on ev-
(e.g., movement in a specific direction) (Corbetta et al., 2000;
Hopfinger et al., 2000; Kastner et al., 1999; Shulman et al.,
1999), by the preparation of a specific response (Astafiev et al.,
2003; Connolly et al., 2002), or by the short-term memory of a
visual scene (LaBar et al., 1999; Pessoa et al., 2002). The dorsal
it is modulated when people change their motor plan for an ob-
ject (Rushworth et al., 2001). Under some conditions, the prepa-
ratory activation of the dorsal frontoparietal network extends to
visual cortex, presumably reflecting the top-down modulation
of sensory representations (Giesbrecht et al., 2006; Hopfinger
et al., 2000; Kastner et al., 1999; Serences et al., 2004; Silver
ipatory activity may predict performance to subsequent targets
(Giesbrecht et al., 2006; Pessoa and Padmala, 2005; Sapir
et al., 2005; Sylvester et al., 2007). Finally, recent studies show
that electrical or magnetic stimulation of FEF or IPS leads to a
retinotopically specific modulation of visual areas and parallel
improvement of perception at corresponding locations of the
visual field (Moore and Armstrong, 2003; Ruff et al., 2006, 2007).
A second system, the ventral frontoparietal network, is not ac-
tivated by expectations or task preparation but responds along
with the dorsal network when behaviorally relevant objects (or
targets) are detected (Corbetta et al., 2000). Both dorsal and
ventral networks are also activated during reorienting, with en-
hanced responses during the detection of targets that appear
at unattended locations. For example, enhanced responses
are observed when subjects are cued to expect a target at one
location but it unexpectedly appears at another (i.e., ‘‘invalid’’
targets in the Posner spatial cueing paradigm) (Arrington et al.,
2000; Corbetta et al., 2000; Kincade et al., 2005; Macaluso
et al., 2002; Vossel et al., 2006) or when a target appears infre-
quently, as in ‘‘oddball’’ paradigms (Bledowski et al., 2004;
Braver et al., 2001; Linden et al., 1999; Marois et al., 2000;
McCarthy et al., 1997; Stevens et al., 2005) (Figure 1B). Core
regions of the ventral network include temporoparietal junction
(TPJ) cortex (anatomically, TPJ is more strictly defined as the
cortex at the intersection of the posterior end of the STS, the in-
ferior parietal lobule, and the lateral occipital cortex), defined as
the posterior sector of the superior temporal sulcus (STS) and
gyrus (STG) and the ventral part of the supramarginal gyrus
(SMG) and ventral frontal cortex (VFC), including parts of middle
frontal gyrus (MFG), inferior frontal gyrus (IFG), frontal opercu-
lum, and anterior insula (Figure 2A, orange regions). An early
theory of how the two networks interact (Corbetta and Shulman,
Figure 1. Focusing Attention and
Reorienting Attention Recruit Interacting
(Left panel) Focusing attention on an object
produces sustained activations in dorsal fronto-
parietal regions in theintraparietal sulcus,superior
parietal lobule, and frontal eye fields, as well as vi-
sual regions in occipital cortex (yellow and orange
colors) but sustained deactivations in more ventral
regions in supramarginal gyrus and superior tem-
cortex (blue and green colors). (Right panel) When
an unexpected but important event evokes a
reorienting of attention, both the dorsal regions
and the formerly deactivated ventral regions are
now transiently activated.
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
of information (stimulus-driven reorienting), output from the ven-
tral network interrupts (as a ‘‘circuit breaker’’) ongoing selection
in the dorsal network, which in turn shifts attention toward the
novel object of interest.
Although both attentional networks have been most exten-
sively investigated in vision, the available evidence indicates
a supramodal function (Driver and Spence, 1998; Macaluso
et al., 2002). The ventral network (right TPJ, right IFG) registers
salient events in the environment not only in the visual but also
in the auditory and tactile modalities (Downar et al., 2000), and
similar dorsal and ventral parietal and frontal regions are modu-
lated by reorienting to invalid targets (Arrington et al., 2000;
Corbetta et al., 2000; Giessing et al., 2006; Kincade et al.,
2005; Macaluso et al., 2002; Mayer et al., 2006; Vossel et al.,
et al., 1999; Marois et al., 2000) in different modalities.
The sections below review in more detail recent work on these
networks, particularly the ventralnetwork,including: (1) thefunc-
tional-anatomical independence of each network, (2) the impor-
tance of behavioral relevance rather than sensory salience in
driving the ventral network, (3) whether the output of the ventral
network initiates a reorienting response and how the dorsal and
ventral networks interact, (4) howthe functions of theventral net-
work may generalize beyond perception and action to include
memory and social cognition, and finally (5) the emerging link
between activity in the ventral network and the output of the
locus coeruleus-norepinephrine system (LC-NE), as recently
outlined by neurocomputational theories (Aston-Jones and
Cohen, 2005; Bouret and Sara, 2005; Dayan and Yu, 2006; Yu
and Dayan, 2005).
Wedo not consider in this discussion the relationship between
cortical and subcortical regions involved in the control of atten-
tion. There is strong evidence that subcortical structures like
the superior colliculus are involved in stimulus-driven but also
goal-driven attention (Bell et al., 2004; Fecteau et al., 2004; Rafal
et al., 1988; Sapir et al., 1999). The pulvinar nucleus of the thal-
amus has been proposed as a gateway structure that funnels
top-down biases from parietal areas into visual cortex (Petersen
et al., 1987; Shipp, 2004).
The Dorsal and Ventral Attention Systems Form
Separate Functional-Anatomical Networks
A basic question is the degree to which different regions in each
putative system cohere as a functional-anatomical network. The
hypothesis of two attention networks, originally based on the
patterns of activation under different task conditions (Corbetta
and Shulman, 2002), has been strongly supported by studies of
interareal correlation of low-frequency (<0.1 Hz) fluctuations of
functional connectivity by MRI (fcMRI) (Biswal et al., 1995). Sev-
eral groups have reported a number of fcMRI networks (e.g.,
visual, auditory, somatomotor, default, attention) (Biswal et al.,
1995; Fox et al., 2005b, 2006a; Fransson, 2005; Greicius et al.,
2003; Mantini et al., 2007), which are related to the underlying
anatomical connectivity (Vincent et al., 2007) and replay at rest
the patterns of functional activation evoked by behavioral tasks
(Fox et al., 2005b, 2006a; Greicius et al., 2003; Hampson et al.,
2002; Vincent et al., 2007). In other words, brain regions that
are commonly recruited during a task are anatomically con-
nected and maintain in the resting state (in the absence of any
stimulation) a significant degree of temporal coherence in their
spontaneous activity. Furthermore, there is growing evidence
that the integrity and strength of spontaneous functional con-
nectivity are behaviorally significant (Hampson et al., 2006;
Seeley et al., 2007; He et al., 2007b). For instance, breakdown
of interhemispheric functional connectivity in posterior parietal
cortex correlates in a group of patients with post-stroke neglect
with their visuospatial deficits (He et al., 2007a; see below).
Regions that putatively belong to the dorsal and ventral atten-
tion systems, based on their consistent activation in the Posner
tively, also show significant interregional correlation at rest (Fox
et al., 2006b) or during an active task with the mean task signal
removed (He et al., 2007a) (see Figure 3). There is a remarkable
similarity between the dorsal parietal and frontal regions iden-
tified by a meta-analysis of task-evoked activation studies
(Figure 2) and those showing high resting-state correlations
(Figure 3). Similar results are found for ventral frontoparietal
regions coactivated during stimulus-driven orienting (Fox et al.,
2006a; He et al., 2007a). Moreover, the right hemispheric bias
observed in the ventral attention network in several activation
studies (Arrington et al., 2000; Corbetta et al., 2000; Downar
Figure 2. Definition of Dorsal and Ventral Networks from Activation
Data and Putative Interactions
consistently activated bycentral cues, indicating where aperipheralobject will
subsequently appear or what is the feature of an upcoming object. Regions in
orange are consistently activated when attention is reoriented to an unex-
pected but behaviorally relevant object. (Bottom panel) Model for the interac-
tion of dorsal (blue) and ventral (orange) networks during stimulus-driven reor-
ienting. Dorsal network regions FEF and IPS send top-down biases to visual
areas and via MFG to the ventral network (filtering signal), restricting ventral
activation to behaviorally important stimuli. IPS-FEF are also important for ex-
ogenous orienting. Overall, the dorsal network coordinates stimulus-response
selection. Conversely, when a salient stimulus occurs during stimulus-driven
reorienting, the ventral network sends a reorienting signal to the dorsal net-
work through MFG.
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
et al., 2000) is mirrored in fcMRI (Fox et al., 2006a; He et al.,
2007a) (compare ventral network in Figures 2 and 3).
While segregation between dorsal and ventral attention net-
works is nearly complete, spontaneous activity in right posterior
MFG correlates with both networks (Figure 3), indicating that
right MFG may contain intermixed neuronal populations respec-
tively connected withdorsal or ventral regions(Fox etal.,2006a).
This result raises the possibility that ventral and dorsal networks
do not directly interact but are principally linked through prefron-
tal cortex (Fox etal.,2006a). Thislinkis alsosupported byresults
obtained in neglect subjects showing that the functional discon-
nection of MFG with dorsal parietal cortex is responsible for
abnormal stimulus selection (see below and He et al., 2007a)
(wire diagram, Figure 2B). The functional segregation of the
two networks in the absence of a task may allow their flexible
recruitment during active behavior. For example, while dorsal
regions are active following the presentation of an instructive
cue, ventral regions are not recruited or are even suppressed
(Shulman et al., 2003; Todd et al., 2005). However, following
the presentation of a target, both ventral and dorsal regions
respond briskly (Corbetta et al., 2000; Hampshire et al., 2007;
Shulman et al., 1999, 2003). In summary, the correspondence
between activation and connectivity analyses provides strong
evidence for separate dorsal and ventral attention networks
forming distinct functional systems.
The Ventral Network Is Activated by Important
Stimuli that Reorient Attention
While reorienting to an object can be driven by salience and be-
whether an object activates the ventral network (Downar et al.,
2001). The ventral network might be considered a prime candi-
Figure 3. Functional Connectivity Defines
Separate Dorsal and Ventral Networks
(Top panel) Four dorsal frontoparietal regions from
the meta-analysis of activation studies shown in
Figure 2 were used as seeds in an FC analysis of
resting-state data. The map indicates regions
that showed significant positive correlations with
three (red) or four (yellow) of the seed regions.
The dorsal network is largely reproduced in the
resting-state FC maps. Regions that show signifi-
cant negative correlations with three (green) or
four (blue) of the seed regions are also shown
and roughly reproduce the default network, possi-
bly indicating a push-pull relationship between the
two networks. (Bottom panel) Five ventral regions
from Figure 2 were used as seeds for an FC anal-
ysis. Regions showing consistent positive correla-
tions largely reproduce the ventral network, but
negative correlations in default regions are not
observed. The black arrow indicates that posterior
MFG near the inferior frontal sulcus appears to be
connected to both networks.
date for mediating orienting to salient
but unimportant stimuli, i.e., exogenous
attention (Posner and Cohen, 1984), be-
cause under passive conditions it is
highly responsive to distinctive sensory
events in all modalities (Downar et al., 2000). But this
hypothesis has now been tested and rejected (Kincade et al.,
2005). Kincade and colleagues separated the BOLD activity pro-
duced by an uninformative but salient peripheral cue, a red
square in an array of green squares, from the activity produced
by discriminating a subsequent rotated Tor L (Figure 4A).In con-
trol conditions, subjects were presented with a neutral display of
randomly intermixed color squares or a foveal cue that oriented
attention voluntarily. Exogenous cues (the red square) did not
activate the ventral network (Figure 4A), even though perfor-
mance was better at that location, indicating that these cues
were effective in generating a shift of attention. In contrast, the
dorsal network (IPS/SPL and FEF) showed stronger activation
for exogenous than neutral cues (Figure 4A), although the stron-
gest recruitment was recorded for endogenous cues (data not
shown). Many other studies have measured activations in exog-
enous orienting paradigms that have combined activations
during the cue and target periods (Kim et al., 1999; Lepsien
and Pollmann, 2002; Mayer et al., 2006; Peelen et al., 2004;
Rosen et al., 1999). Although these studies are more difficult to
interpret, they indicate that the ventral network is not recruited
by orienting to uninformative but salient cues presented before
a target appears (see Peelen et al., 2004, for an exception). Sim-
ilarly, de Fockert and colleagues showed that uninformative but
salient distracters that attract attention did not activate the ven-
tralsystem (deFockertetal.,2004)(Figure 4B),althoughtheydid
activate the dorsal system. The overall conclusion is that exoge-
nous orienting recruits the same dorsal frontoparietal network
that is responsible for directing attention based on goals or
Conversely, the ventral network is well activated by stimuli that
are important, even if they are not very distinctive. Indovina and
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
low salience activated regions in both dorsal (FEF, precuneus)
and ventral (IFG and anterior insula) attention networks, in line
with previous results (Arrington et al., 2000; Corbetta et al.,
a target object. Serences et al. (2005) asked subjects to cate-
gorize red foveal letters interspersed among a rapid, successive
series of colored foveal letters (rapid serial visual presentation, or
RSVP) while peripheral distracter letters were occasionally pre-
sented in the target color (red) or in a nontarget color (green) (Fig-
a friend wearing a red sweater and notice people wearing red but
not green clothes (‘‘contingent’’ orienting; Folk et al., 1992). TPJ
activation was only observed for the red distracters (Figure 4D),
consistent with the hypothesis that the ventral network responds
mainly to stimuli thought to be behaviorally relevant (see also
Downar et al., 2001).
distinctive but unimportant stimuli (exogenous orienting), except
perhaps in the special case where subjects do not have an
Figure 4. Ventral Network Activity Is Restricted to Task-Relevant Stimuli
(cue and cue period in light blue). Behavioral performance was speeded when the target location matched the singleton location, even though the cue and
targetlocationswererandom. ThetimecourseoftheBOLDsignalshowninthegraphindicates thatRFEF(see‘‘A’’inthesurface-renderedbrain)showedalarger
response for exogenous than neutral cues. In contrast, SMG showed a small deactivation during the cue period, followed by a small activation when the cue
period ended (Kincade et al., 2005).
(B) Salient irrelevant distracters influence the dorsal, not ventral, system. Subjectscategorized the orientation of a line within a singleton shape (the circle). Salient
but irrelevant singleton color distracters that impaired behavioral performance activated dorsal region SPL (see ‘‘B’’ in brain) rather than TPJ (de Fockert et al.,
(C) Unattended stimuli only activate TPJ if they are task relevant, not if they are irrelevant, even though they have high sensory salience. A task-relevant unat-
tended letter activated angular gyrus and inferior frontal gyrus (see ‘‘C’’ in brain), but no responses were seen to the unattended but highly salient checkerboard.
The angular gyrus response may reflect the combined activation of dorsal (IPS/SPL) and TPJ regions (Indovina and Macaluso, 2007).
(D) Distracters onlyactivate TPJifthey sharefeatures withatarget,indicating astrongeffect of task relevance. Subjects identified redfovealletters while ignoring
irrelevant peripheral letters. Peripheral letters that matched the target color interfered with performance and activated TPJ, while non-target-colored letters had
no effect (‘‘D’’ in brain) (Serences et al., 2005).
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
ongoing task, but does underlie reorienting to environmental
stimuli based on their task relevance. An important conclusion
from these neuroimaging studies is that the psychological dis-
tinction between exogenous and endogenous orienting (Jo-
nides, 1981) may not map onto different neural systems. Rather,
a more fundamental distinction appears to be between systems
involved in orienting, both exogenous and goal-driven, i.e., the
dorsal attention system, and those involved in stimulus-driven
reorienting, i.e., the ventral and dorsal attention systems.
Preventing Activation of the Ventral Network
by Unimportant Objects
The poor response of the ventral network to distinctive but
unimportant objects when a person focuses on a task prevents
shifts of attention that could interfere with task performance.
Two studies have now shown that this poor response may be
due to suppression of the ventral network by a sustained top-
In one study, subjects saw a rapid stream of letters (RSVP)
and were instructed to look for an occasional digit (Figure 5A)
(Shulman et al., 2003). Prior to the point at which the digit was
detected, while subjects were still searching the letter displays,
the ventral network (bilateral TPJ, R MFG, and R IFG) showed
a sustained deactivation (Figure 5C, green-blue voxels). These
deactivated regions overlapped regions that showed increased
positive responses to unattended targets in a separate experi-
ment, indicating that the deactivation occurred within ventral
leagues (Shulman etal., 2003) suggested that the suppression of
Because targets still triggered a robust positive response, how-
ever, activity in the ventral network appeared to have been gated
by task relevance or filtered, with only targets passing the filter.
Stronger filtering appeared to correlate with better performance,
because the average deactivation in right TPJ was significantly
larger on trials in which the subsequent target was detected
than missed (Shulman et al., 2007) (Figure 5A).
In a second study (Todd et al., 2005), subjects remembered
interval, decided whether any of the objects were present in
a new display (Figure 5B). The larger the number of objects the
subject had to remember (the memory load), the more R TPJ
was deactivated during the retention interval. The authors sepa-
rately showed that higher memory loads resulted in poorer
detection of a novel unattended stimulus, suggesting that high
memory loads suppress activity in R TPJ and prevent stimulus-
driven reorienting (Todd et al., 2005). Together, these studies
indicate that when subjects focus on a task, signals for task
relevance (‘‘filtering’’ in Figure 2B) deactivate TPJ, preventing
reorienting to unimportant objects.
Source of Signals that Restrict Ventral
Activation to Important Objects
The source of signals for task relevance may be the dorsal net-
work (IPS, FEF), which shows strong anticipatory activity when
people expect to see an object at a particular location or with
particular features (Corbetta et al., 2000; Kastner et al., 1999).
In the previous RSVP experiment, IPS and FEF were each one
Figure 5. TPJ Activity Is Suppressed during
(A) Subjects searched a rapid serial visual presenta-
tion (RSVP) display for a target digit. The number of
distracter frames containing only letters prior to the
target frame containing the target was varied. The
graph shows the time course of activity in dorsal
ditions in which the target appeared near the end of
the trial. In TPJ, a deactivation to the letter distracters
was followed by an activation when the digit was pre-
sented or the trial was terminated. Interestingly, the
deactivation to the letters was significantly greater
when the subsequent digit was detected than when
it was missed. Conversely, IPS and FEF showed
sustained activations during search (Shulman et al.,
(B) Subjects encoded a visual display that they had to
remember and then match to a probe display. During
the retention interval, TPJ showed a deactivation (pur-
ple disk in the surface-rendered brain) that increased
with the number of display items that had to be re-
tained (Todd et al., 2005).
(C) The statistical map shows regions with sustained
activity as subjects searched through letter distracters
in the RSVP experiment (see panel [A]), including dor-
sal attention regions IPS and FEF (red/orange in sur-
face-rendered brain) but also regions in anterior insula
and anteriorcingulatethatform aputative task-control
network (Dosenbach et al., 2006). These regions may
send top-down signals (see arrows) to the ventral
network, which showed sustained deactivations
during search (blue/green in surface-rendered brain),
restricting its input to task-relevant objects (Shulman
et al., 2003).
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
of the few regions in the brain that showed sustained activation
to distracters prior to target detection (Shulman et al., 2003) (Fig-
ures 5A and 5C). These sustained signals may have filtered the
input to the ventral network (blue arrows in Figure 5C; filtering
signal in Figure 2B).
Another possible source of top-down signals is prefrontal
cortex (Desimone and Duncan, 1995; Miller and Cohen, 2001).
Resting-state analyses suggest that R MFG may link dorsal
and ventral networks (Fox et al., 2006a), possibly funneling
top-down biases from the dorsal network onto the ventral net-
work (Figure 5C and 2B). R MFG is probably not the source be-
cause it showed sustained deactivation along with R TPJ and R
IFG (Figure 5C). However, sustained increases were observed in
anterior cingulate and anterior insula (Shulman et al., 2003),
which have been postulated to form the core of a network for
cognitive control (Dosenbach et al., 2006) (orange arrows in
Figure 5C). The influence from these cortical regions may be di-
rect through cortico-cortical interactions or indirectly via subcor-
tical loops. In the last section, we relate the pattern of activity in
TPJ, including filtering signals, to the output of the LC-NE, which
receives input from the anterior cingulate and the anterior insula
(Aston-Jones and Cohen, 2005; Ongur et al., 2003).
If prefrontal cortex is the source or the conduit of these mod-
ulations onto TPJ, then poor top-down control of stimulus-
driven reorienting should be evident after prefrontal lesions.
Chao and Knight (1995) reported that patients with unilateral
dorsolateral prefrontal cortex (DLPFC) lesions showed mark-
edly decreased performance in an auditory match-to-sample
task due to irrelevant distracter tones presented during the re-
tention interval. Loss of prefrontal inputs may have decreased
top-down control over TPJ, resulting in inappropriate reorient-
ing to distracting stimuli (see also Ro et al., 1998; Snow and
In summary, only environmental stimuli that are behaviorally
relevant trigger the ventral network. The ventral network re-
sponse is suppressed when irrelevant stimuli are presented,
sensory responses by behavioral relevance. The source of the
filtering signal may be the dorsal network or other parts of pre-
frontal cortex, either directly or indirectly via subcortical loops.
Do Signals from the Ventral Network
it is mainly activated by behaviorally important stimuli. Next, we
consider how the output from this system affects activity in other
neural systems and behavior. One possibility isthat,whenanim-
portant stimulus appears outside the current focus of attention,
fast-latency signals from the ventral network initiate reorienting
by sending a ‘‘circuit-breaking’’ or interrupt signal to dorsal
regions, which change the locus of attention (Corbetta and
attention and the eyes to sensory stimuli appearing at unex-
pected locations, with spatially selective responses to contralat-
eral stimuli and responses to movements of attention or the eyes
1997; Schluppeck et al., 2005; Sereno et al., 2001; Sweeney
et al., 1996; Sylvester et al., 2007). In contrast, group-averaged
studies of ventral regions (TPJ, VFC) have not found spatially
selective responses during reorienting (Corbetta et al., 2002;
Macaluso et al., 2002; Macaluso and Patria, 2007). Similarly,
mapping studies in individuals have only reported weak spatially
selective responses near or within the ventral network in parts of
MFG (Hagler and Sereno, 2006; Jack et al., 2007) and superior
temporal gyrus (STG) (Jack et al., 2007). The weak evidence for
spatial selectivity in the ventral network suggests that spatial re-
orienting is not mediated solely by that network but involves joint
activation of dorsal and ventral regions.
There is little evidence, however, that short-latency responses
in the ventral attention network precede those in dorsal areas
and trigger a reorienting response. Within dorsal parietal and
frontal sites, EEG- or MEG-based estimates of visual response
latency to targets for an eye movement vary between 130 and
170 ms (Evdokimidis et al., 2001; McDowell et al., 2005; Sestieri
et al., 2008). Within ventral sites in TPJ and IFG, the response to
targets is thought to be indexed by the P300 potential, with a
latency of 300–400 ms, considerably longer than the dorsal
latencies (Bledowski et al., 2004; Daffner et al., 2003; Knight
et al., 1989; Menon et al., 1997; Yamaguchi and Knight,
1991a). Unfortunately, P300 and eye movement paradigms are
difficult to compare. There have been a number of ERP/MEG
studiesofspatial reorienting, buttheresults areambiguous inre-
lation to the relative latency of dorsal and ventral parietal regions
(Luck et al., 1994; Mangun and Hillyard, 1991). Invalid targets
that follow a voluntary cue to shift attention increase a late-pos-
itive deflection (230–400 ms) at central, parietal, and occipital
sites that might correspond to P300 (Mangun and Hillyard,
1991). At temporal electrodes ipsilateral to the target (Hopfinger
and Ries, 2005), invalid targets that follow an uninformative
(exogenous) cue produce a negative-going deflection in the
range of 200–250 ms, preceding a separate P300. Although this
latter paradigm involved noninformative cues, the ERP compo-
nent was sensitive to several task-contingent factors, reflecting
top-down signals (Hopfinger and Ries, 2005).
Overall, the latency of visual responses to salient behaviorally
relevant visual stimuli is, if anything, shorter in dorsal parietal
than in ventral parietal areas, but definitive studies have not
been conducted. In awake behaving monkeys, neural responses
to visual stimuli in lateral intraparietal area (LIP), the putative ho-
molog of human IPS/SPL, show a very rapid nonselective volley
(?50 ms) followed by slower oscillations (100–200 ms) that
are modulated by spatial attention (Bisley et al., 2004). In more
ventral parietal cortex, in correspondence with area 7A, which
shows modulation by unattended stimuli (Constantinidis and
Steinmetz, 2001; Robinson et al., 1995) and salient oddball stim-
uli during simple fixation (Constantinidis and Steinmetz, 2005),
similar to the ventral attention network, average response are
communication). No direct comparison on the same task has
ally relevant and salient stimulus outside of the current focus is
probably initiated in dorsal frontoparietal cortex in conjunction
with subcortical structures (e.g., superior colliculus). Ventral
system activity during reorienting may reflect slower adjust-
ments necessary to complete or carry out a complex reorienting
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
response that involves shifts in task sets, expectations, reward
contingencies, and arousal.
Do Signals from the Ventral Network Influence
Reorienting and the Dorsal Network?
While the latency data from electrophysiological studies are
ambiguous on whether ventral network activity triggers dorsal
activity during reorienting, transcranial magnetic stimulation
studies (TMS) nonetheless support a key role for ventral regions
in reorienting attention and detecting targets in conjunction with
dorsal frontoparietal regions (IPS, FEF). An extensive discussion
of TMS studies of visuospatial attention is beyond the scope of
this review, but some conclusions can be drawn from the extant
literature. First, interference with regions in inferior parietal cor-
tex (TPJ, SMG, AG) disrupts visual target detection and reorient-
ing (Chambers et al., 2004a; Ellison et al., 2004; Meister et al.,
2006). Second, disruption has been demonstrated for stim-
ulation latencies ranging from 90–120 ms (Chambers et al.,
2004a) to 200–300 ms following target onset (Chambers et al.,
effects may reflect disruption of a signal that disengages atten-
tion from its current location and initiates reorienting (Chambers
et al., 2004a). Third, the regions in inferior parietal cortex that
show effects of TMS depend on the task: R TPJ during detection
of bilateral stimuli (Meister et al., 2006), angular but not supra-
marginal gyrus (SMG) during reorienting in an exogenous cueing
paradigm (Chambers et al., 2004a), SMG during reorienting in an
endogenous cueing paradigm (Chambers et al., 2004b), and
STG during visual search (Ellison et al., 2004). Fourth, a larger
set of studies has reported effects of TMS in FEF or posterior pa-
rietal cortex (PPC) on detection, search, and orienting (Fuggetta
et al., 2006; Grosbras and Paus, 2002; Muggleton et al., 2003;
O’Shea et al., 2004; Taylor et al., 2007; Thut et al., 2005). Overall,
in agreement with the imaging evidence showing that dorsal and
ventral networks are coactivated during target detection and
stimulus-driven reorienting (Corbetta et al., 2002; Giessing
et al., 2006; Kincade et al., 2005; Marois et al., 2000), TMS of
both ventral and dorsal regions affects reorienting, detection,
We have reported direct evidence for an interaction between
the two networks in fMRI studies of stroke patients with spatial
neglect. Spatial neglect is a syndrome characterized by a bias
to attend and respond to objects on the contralesional side
and is observed more frequently after right than left hemisphere
strokes (Heilman et al., 1987b; Mesulam, 1999). Lesions that
cause neglect are typically localized in ventral frontal or tem-
poroparietal cortex and underlying white matter (Husain and
Kennard, 1996; Karnath et al., 2004; Mort et al., 2003; Vallar
and Perani, 1987). We recently demonstrated that the spatial
bias of neglect depends on a physiological imbalance between
left and right dorsal parietal cortex (IPS/SPL), which is caused
bystructural and physiological abnormalities in the ventral atten-
tion network (Corbetta et al., 2005; He et al., 2007a). The inter-
hemispheric imbalance in IPS/SPL is evident both during spatial
attention tasks, with a significant relationship between left-side
neglect and hyperactivation of left parietal cortex, and in mea-
sures of functional connectivity at rest. For instance, Figure 6A
fered extensive damage to inferior frontal, perisylvian, and TPJ
cortex and showed severe left-side neglect at the acute stage.
The time series clearly show abnormal correlation of the resting
BOLD signal between left and right IPS, which is not structurally
damaged. This deficit correlates across subjects with the sever-
ity of neglect and recovers over 9 months as neglect improves
(He et al., 2007a). Interestingly, the degree of functional impair-
ment in dorsal parietal cortex correlates with the degree of im-
paired functionalconnectivityin thestructurallydamagedventral
network, hence demonstrating the interaction between the two
networks. Notably, this interaction involved right MFG and the
white matter fibers connecting this region to dorsal parietal
Figure 6. Interaction of Dorsal and Ventral
(A) The surface-rendered brains show the dam-
aged right hemisphere regions (in dark gray) of
a stroke patient with spatial neglect. The bottom
graph shows the time course of BOLD activity in
undamaged regions of IPS, with the green and
red lines indicating, respectively, the time series
for the indicated left and right IPS regions. Time
subject, for the stroke patient immediately follow-
ing the stroke, and for the same patient following
recovery. While the healthy subject and the re-
covered stroke patient show highly correlated
interhemispheric IPS activity, the same patient im-
mediately after the stroke shows activity that is
much less correlated. Therefore, damage to
ventral regions, possibly including white matter
tracts, impairs physiological interactions between
undamaged dorsal regions (He et al., 2007a).
(B) The surface-rendered brains show ventral (left)
and dorsal (right) regions that are activated when
the completion of a symphonic movement is de-
tected. The time courses indicate that ventral
activations (red lines) preceded the dorsal activa-
tions (blue lines), while a Granger Causality analy-
sis of these regions indicated that ventral activity
predicted dorsal activity (Sridharan et al., 2007).
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
cortex (He et al., 2007a), providing more support for the hypoth-
esis that right MFG links ventral and dorsal systems (Figure 2B).
Finally, a recent paper used a Granger Causality analysis to
show an influence of ventral activity on dorsal activity when
healthy subjects passively listened to a movement from a sym-
phony (Sridharan et al., 2007) (Figure 6B), consistent with an
interaction between the networks. Completion of the movement
activated both networks, but the ventral activation preceded the
dorsal activation (Sridharan et al., 2007). The authors suggested
that the ventral network activity marked an event boundary
and influenced dorsal activity during a subsequent updating of
In summary, TMS, neuroimaging, and lesion evidence support
the hypothesis that ventral and dorsal networks are both neces-
sary and interact when attention is reoriented to behaviorally
relevant environmental stimuli.
Reorienting Perceptual and Response Processes
to Environmental Stimuli
Although many of the studies that have been discussed involved
spatial reorienting to environmental stimuli, we emphasized in
the introduction that the ventral network mediates a broader
set of changes in response to an environmental stimulus. Unfor-
tunately, these broader changes involve many processes that
can be difficult to isolate. For example, an early indication that
the ventral network was recruited under circumstances other
than spatial reorienting came from studies using the oddball
paradigm, in which subjects detect a target presented infre-
quently (10%–20%, ‘‘oddball’’) in a stream of frequent ‘‘stan-
dard’’ objects. Enhanced responses to oddballs are observed
in a set of regions that includes most consistently the temporo-
parietal junction and the lateral prefrontal cortex but also dorsal
Because the oddball is usually defined by a different feature(s)
than the standard, rather than by a different location (see Marois
et al., 2000, for a comparison of the two cases), the enhance-
ment to the oddball is not related to a spatial shift of attention.
But the oddball paradigm combines a range of processes,
making the fMRI activations difficult to interpret. For example,
a spatial or feature cue in a typical visual attention task may indi-
cate what object should be attended (e.g., ‘‘attend to the red
letter’’) (Broadbent, 1971; Bundesen, 1990) but not how the ob-
ject should be categorized or responded to (e.g., ‘‘if the letter is
a vowel, press the left key’’), restricting the relevant processes to
those involved in stimulus selection (Logan and Gordon, 2001).
In the oddball paradigm, however, the oddball/standard distinc-
tion indicates what response should bemade, adding processes
involved in categorizing the oddball, selecting a response
(whether overt or covert, go or no-go) based on the current stim-
ulus-response mapping, making the response, and generating
signals related to performance monitoring.
Several other studies suggest that the ventral network marks
transitions when one behavior is interrupted or terminated and
a new behavior begins, including transitions at event boundaries
(for a general discussion of event boundaries, see Zacks et al.,
2007). A similar phenomenon appears to occur during the transi-
tion between a period of rest and a task block involving many tri-
als (task onset) or the transition from the task block to rest (task
offset). Both block onsets and offsets robustly and transiently
activate R TPJ and VFC, but also other regions, including dorsal
prefrontal cortex and the dorsal attention network (Dosenbach
et al., 2006; Fox et al., 2005a; Konishi et al., 2001) (Figure 7A).
Even within a single trial, coactivation of dorsal and ventral fron-
toparietal areas at task offset may index a readjustment or inter-
ruption of ongoing task sets (Shulman et al., 2002). Interestingly,
in this latter study, the transient signal at task transition occurred
both in dorsal frontoparietal areas that were engaged prior to the
transition, but only at the transition point in the ventral network.
One interpretation is that the ventral network signals the task
transition and/or provides a reset signal. As discussed below,
itispossible that thesecortical reset signalsare related to similar
signals identified in the LC-NE system, which putatively allows
for a shift of cortical architecture at task boundaries (Bouret
and Sara, 2005).
Overall, the above studies suggest that, whenever environ-
mental stimuli call for a change in a maintained task, ventral
(and dorsal) attention networks are modulated at the transition
point. Interestingly, the ventral network is not recruited when
people regularly switch from one task to another over short
time periods (e.g., task-switching paradigms). This form of task
control appears to involve a separate set of dorsal parietal and
frontal regions (Brass and von Cramon, 2004; Braver et al.,
2003; Kimberg et al., 2000; Rushworth et al., 2002).
Reorienting from ‘Internally Directed’ Processes
to Environmental Objects
Stimulus-driven reorienting has mainly been discussed in the
context of changing the control of behavior from one environ-
mental input to another, but similar reorienting mechanisms
may also be involved in shifting from a broad range of ‘‘internally
directed’’ processes in order to deal with environmental events,
aswheninterrupting memory retrieval (‘‘did I lock the cardoor?’’)
to respond to a sudden stimulus (‘‘is that my cell phone ring-
ing?’’). We hypothesize that the ventral attention network may
play a central role in this function.
Important aspects of internally directed processing, such
as introspection, self-referential thoughts, or projecting oneself
into a situation (e.g., envisioning or planning one’s future or
remembering one’s past as in episodic memory) are thought to
involve the so-called ‘‘default’’ network (Raichle et al., 2001).
This network of cortical regions is strongly deactivated during
a wide range of demanding cognitive tasks relative to a passive
resting or viewing state (Binder et al., 1999; Mazoyer et al., 2001;
Shulman et al., 1997). It has been proposed that these regions
mediate a number of ‘‘default’’ processes to which the brain re-
turns in the absence of a task (Raichle et al., 2001). A similar set
of regions show high temporal correlation in resting-state fcMRI
(Fox et al., 2005b; Greicius et al., 2003).
Some authors have proposed that default and dorsal attention
networks represent two fundamental axes of functional organi-
zation in the brain, with the dorsal attention network controlling
environmentally directed processes (e.g., perception and action)
and the default network controlling internally directed processes
(e.g., memory, introspection) (Fox et al., 2005b; Golland et al.,
2007). This hypothesis is based on the observation that goal-
directed tasks activate the dorsal attention network and
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
deactivate the default network. Moreover, several fcMRI studies
have reported that default activity is negatively correlated with
the dorsal network (see top panel of Figure 3; (Fox et al.,
2006a; Fransson, 2005; but see Golland et al., 2007; Nir et al.,
2006).Finally, during naturalvision, theposterior part of the brain
is entirely occupied either by regions that are positively corre-
lated with the dorsal attention network or the default network
(Golland et al., 2007; Nir et al., 2006).
The hypothesis that the ventral network may function as a sys-
tem to switch (reorient) between internally and externally di-
rected activities is based on two sets of observations. First, the
ventral network is largely segregated in terms of functional con-
nectivity from both dorsal attention and default networks (see
of the ventral network from both dorsal and default networks
may allow a flexible interaction during externally or internally
directed behavior. Second, although both ventral attention and
default systems may deactivate during goal-oriented behavior,
the deactivations depend on different factors. During a percep-
tual task, in which subjects monitored an RSVP stream for a
single target (Shulman et al., 2003), the TPJ component of the
ventral network was deactivated only while subjects searched
the stream for the target (Figure 5A), but the angular gyrus com-
ponent of the default network was deactivated as long as the
RSVP stream remained on the screen. In other words, TPJ was
deactivated by the attentional component, while the angular
gyrus was deactivated by the sensory component of the task.
Moreover, the presentation of the attended target activated
Figure 7. Common Activation of TPJ during Reorienting, Task Transitions, and Social Cognition
(A) Regions in green show transient activity at the transition between a rest period and the onset of an extended block of trials (see time course in inset, indicating
that both onsets and offsets are often observed). ‘‘Start cue’’ activity is observed within some ventral and dorsal regions, indicating the involvement of both
networks in task transitions (Dosenbach et al., 2006).
(B) A meta-analysis of activations across studies measuring reorienting and various aspects of social cognition. Largely similar TPJ activity is observed across
paradigms, with perhaps a more posterior extension of activity in the social cognition paradigms (Decety and Lamm, 2007).
(C)Awithin-subjectcomparisonofreorientingand ToMparadigmsrevealedthatbothactivated verysimilarTPJregions (Mitchell, 2007).Thebargraphshowsthe
magnitude of the TPJ activation in the two paradigms. A large deactivation was observed in the control ‘‘false-photograph’’ condition with a significantly smaller
deactivation in the experimental ToM ‘‘false-beliefs’’ condition. The reorienting paradigm yielded event-related activations that were larger during trials with
invalid than valid cues. The blue and orange regions are taken from the meta-analysis of the dorsal and ventral networks in Figure 2.
(D) Gaze perception activates superior temporal regions. The graph shows the time course of activity when another person makes or averts eye contact with the
observer. Mutual gaze enhances the activation (Pelphrey et al., 2004).
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
TPJ but not angular gyrus (see Golland et al., 2007, for a differ-
ent dissociation between anterior and posterior portions of IPL).
In contrast, when subjects searched their episodic memory
for an item (an internally directed task), both sets of regions
were still deactivated, but only the angular gyrus was then ac-
tivated by a positive match in memory (Shannon and Buckner,
2004; Wheeler and Buckner, 2004). The similarity of response
profile when looking for a target in the environment or in mem-
ory raises the possibility that the ventral attention network plays
a similar role in both processes. In both cases, filtering of the
ventral attention network is necessary to protect the system
from involuntarily reorienting to environmental stimuli when re-
sources are allocated to perceptual, memory, or self-referential
Reorienting during Theory of Mind Cognition
An intriguing development of the last few years is that activation
of right TPJ, the posterior core of the ventral attention network,
has been reported during ‘‘theory of mind’’ (ToM) cognition,
i.e., reasoning about other people’s mental states (Fletcher
et al., 1995; Gallagher and Frith, 2003). ToM cognition involves
a close interaction between perceptual processes and those
involved in self-projection (Buckner and Carroll, 2007). Subjects
may judge the intentions of a person they are viewing in a movie
or judge a person’s intentions based on a written description.
A recent study reported that ToM activations, measured by
comparing responses to false-belief stories and control stories
involving outdated photographs, colocalized with activations
from reorienting to invalid targets in a Posner cueing task (Mitch-
between activations during attentional reorienting and social
cognition in R TPJ from a recent meta-analysis (Decety and
Lamm, 2007), although there was a tendency for the social
into the default system proper.
Colocalization of activations from ToM and reorienting para-
digms does not necessarily imply a common process. First,
the colocalization, while impressive, is only approximate. In
addition to the fact that fMRI activity averages over large cell
populations, there may be a slightly more posterior distribution
for ToM activations. To our knowledge, the VFC component of
the ventral attention network has not been reported in studies
of social cognition. Instead, social cognition paradigms often
activate, in addition to TPJ, foci in posterior cingulate and medial
prefrontal cortex that belong to the default network, which we
argued above is distinct from the ventral attention network. Per-
haps a slightly more posterior location for the TPJ focus in some
ToM paradigms reflects connectivity with these default regions.
Second, colocalization may mask subtle but systematic differ-
ences in the voxelwise distributions of the activations (Downing
et al., 2007). Demonstrating that two voxelwise patterns or distri-
patterns occur in the same cortical tissue. Although in principle
the two distributions could reflect completely unrelated func-
tions that are juxtaposed, i.e., a specialized ToM module (Saxe
and Powell, 2006) and a node within a reorienting network
(Corbetta and Shulman, 2002), the close anatomical correspon-
dence may suggest a less arbitrary relationship.
If activations from reorienting and ToM are not completely
unrelated, why might they be linked? First, colocalization might
reflect factors that are poorly controlled in either or both para-
digms. For example, ToM paradigms generally involve blocks
or trials in which subjects comprehend animations, movie se-
quences, or stories over an extended period. The cognitive or
working memory loads of the experimental and control stories
in these ToM paradigms have not been explicitly controlled. In
several studies, the selective activation of right TPJ during
ToM conditions as compared to control conditions actually
reflected a lesser deactivation (e.g., Figure 7C from Mitchell,
2007). Because greater memory loads produce stronger TPJ de-
activations (Todd et al., 2005), differential TPJ activity in experi-
mental and control conditions of ToM paradigms could reflect
overall differences in memory load or task complexity. The con-
across very different paradigms, however, suggests that any
single methodological factor may not explain the colocalization.
Second, colocalization might reflect cognitive processes that
are present in both paradigms. For example, both reorienting
and ToM paradigms often involve breaches of expectation
(e.g., invalid cues [Arrington et al., 2000; Corbetta et al., 2000;
Macaluso et al., 2002] or false-belief stories [Gallagher and Frith,
2003; Vogeley et al., 2001]), which appear to modulate the ven-
tral network. Decety and Lamm (2007) suggest that many as-
pects of social cognition involve a comparison of ‘‘internal pre-
dictions with actual external events,’’ explaining the ubiquitous
presence of R TPJ activity. However, some ToM studies have
included controls for this factor (Saxe et al., 2004), and some
ToM and reorienting studies have not involved manipulations
of expectation (Saxe and Powell, 2006; Serences et al., 2005).
Another possibility along these lines is that TPJ activity during
ToM tasks reflects signals linked to shifts in eye gaze or for per-
ception or imagery of gaze. Several studies have shown that
posterior STS is activated during the perception of gaze shifts
(Allison et al., 2000; Pelphrey et al., 2003, 2004). Within a social
context, activation from viewing-gaze shifts are larger when
away from the viewer (averted gaze) (Figure 7D). This error signal
may reflect a mismatch between our expectation and the ob-
served direction of another person’s gaze (similar to an invalidly
cued target) or an error signal in the inferred state of mind of the
other person (a ToM signal). In general, strong evolutionary rea-
social mechanisms for conspecific interactions in old and new
world monkeys to mechanisms to infer others’ intention or
ToM in higher apes and humans (Tomasello et al., 2001).
Gaze-related activations in STS, however, may not colocalize
with those for reorienting or ToM (these functions have not
been assessed within the same experiment) (see Gobbini et al.,
2007, for a recent meta-analysis).
a simulation or judgment of the other person’s mind or viewpoint
and processing of perceptual evidence from their own viewpoint
that supports the simulation or judgment. Interestingly, recent
evidence indicates that disruption of TPJ activity either by sei-
zure activity or electrical stimulation can engender a number of
hallucinatory misperceptions that involve a mismatch between
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
the perception of the surrounding environment and one’s own
body. For example, subjects may feel as if they see their body
from the outside or as if the perception of their own body is not
aligned with the body’s visual representation and surrounding
in body self-perception can be manipulated experimentally
(Lenggenhager et al., 2007) and produce right TPJ activity
(Arzy et al., 2006). These findings have been interpreted by con-
sidering TPJ cortex a site of multimodal integration of visuospa-
tial, vestibular, and body-related signals and that the alignment
of these signals generates and maintains one’s own sense of
body or bodily self (Blanke and Arzy, 2005). While the relation-
ship between reorienting signals in the ventral attention network
and sense of body remains to be explored, an intriguing hypo-
thesis is that similar environmental and bodily representations
and their comparison may be co-opted for ToM interactions
and that attention signals in TPJ may be important to switch be-
tween internal, bodily, or self-perspective and external, environ-
mental, or other’s viewpoint, a key ingredient of ToM.
The Role of Expectation in Reorienting
Many of the conditions that activate the ventral network involve
violating an expectation. For example, because people prepare
for expected objects, an unexpected target object is often an
unattended object, evoking ‘‘stimulus-driven reorienting.’’ Simi-
larly, event boundaries, which appear to activate the ventral
network, may be determined by monitoring whether the sensory
input departs from a current model of ongoing behavior (Zacks
et al., 2007). Discrepancies or breaches of expectation indicate
that a new behavior has occurred, marking an event boundary
and requiring the model to be updated. But activations to unex-
pected stimuli may also reflect processes that are either entirely
separate from reorienting or modulate reorienting. Important
objects that violate an expectation may also increase arousal,
dishabituate neuronal responses in sensory and associative
areas in paradigms in which expectations are driven by stimulus
frequency (e.g., oddball paradigms), or produce error signals
that drive learning, reward, or affective mechanisms. While, in
some cases, violations of expectation may be an essential fea-
ture of the process that drives ventral network activation, it will
also be important in future work to explicitly manipulate stimu-
lus-driven reorienting independently from expectation.
Several neuromodulators have been linked to the detection of
unexpected events, including dopamine and norepinephrine
(NE) (Dayan and Yu, 2006). Although dopaminergic responses
to unexpected stimuli are often discussed in the context of
reward (Schultz, 1998; Schultz et al., 1997) some authors have
proposed that they more generally facilitate a shift of attention
to unexpected and behaviorally important stimuli (Horvitz,
2000;Redgrave et al.,1999; Zinket al.,2003).This putative func-
tion is very similar to that proposed for the ventral attention
network, but there is no evidence of a significant dopaminergic
projection to TPJ. In contrast, there is evidence in monkey for
a strong noradrenergic innervation of inferior parietal cortex
and superior temporal gyrus, possible homologs of human TPJ
(Foote and Morrison, 1987; Morrison and Foote, 1986). There-
fore, we next consider the functional relationship between the
ventral attention network and activity in the locus coeruleus
(LC), the primary source of NE.
Links between Ventral Attention Network and Locus
TheLC-NEsystemisamonoaminergic neuromodulatory system
that originates from a small nucleus in the dorsal pons, the locus
coeruleus, projecting diffusely to the brainstem, cerebellum,
diencephalon, and neocortex. Several neurocomputational
theories of the LC-NE system activity (Aston-Jones and Cohen,
2005; Bouret and Sara, 2005; Dayan and Yu, 2006; Yu and
Dayan, 2005) bear striking resemblance to some of the ideas
put forward in this review regarding the role of the ventral atten-
LC neurons exhibit both tonic and phasic activity modes.
Tonic activity is low in an unaroused state that facilitates sleep
and disengagement from the environment (Aston-Jones and
Bloom, 1981; Rajkowski et al., 1994), moderate when the organ-
ism is engaged in a focused task of high utility and filters out
is not committed to a task, is exploring the environment, and
there is uncertainty concerning the proper relationship between
stimuli and responses (Aston-Jones et al., 1997) (i.e., unex-
pected uncertainty). Although these transitions in tonic firing of
LC neurons occur over seconds or minutes, decrements of tonic
LC activity have been observed on a shorter timescale in the
period between a warning cue instructing the onset of a trial
and a rewarded target stimulus (Bouret and Sara, 2005). As-
ton-Jones and Cohen have proposed that LC-NE tonic signals
enable transitions between behavioral states (sleep, focused
alert, exploratory) and that the decrement of tonic activity from
an exploratory state to a specific task state reflects the higher
utility associated with the detection of upcoming target stimuli.
Accordingly, transitions between different tonic levels are en-
abled by cortical inputs from prefrontal regions (anterior cin-
gulate, orbitofrontal cortex) that heavily project to LC and are
sensitive to task context and reward information.
The second component of LC discharge is the phasic re-
sponse observed to target stimuli, which is most strongly gener-
ated in the moderate tonic task-focused mode. Interestingly,
phasic responses of LC neurons share many similarities with
viously discussed in relation to the timing of the response in the
ventral attention network (Aston-Jones and Cohen, 2005; Nieu-
wenhuis et al., 2005). Two different yet related theories have
been proposed to explain the putative function of the LC phasic
response to targets. According to Aston-Jones and Cohen, the
phasic response enhances the gain of neural responses in the
complex neural matrix involving sensory, decision, and motor
regions and therefore speeds up behavioral responses. Impor-
tantly, the LC phasic response is thought to be triggered by pre-
frontal inputs only after the sensory evidence for a target has ex-
ceeded a decision threshold in the relevant cortical network, i.e.,
it is a relatively late postdecision signal that restricts LC activity
sistent with the relatively late P300 response to target detection.
Alternatively, the phasic signal has been conceptualized as an
‘‘interrupt’’ signal (Dayan and Yu, 2006) or as a ‘‘network reset’’
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
signal (Bouret and Sara, 2005) that allows the flexible configura-
tion of a target network once a target is detected. Bouret and
Sara note that this interpretation is consistent with the role that
norepinephrine plays in much simpler organisms. For instance,
in the stomatogastric nervous system of crustacea, synchro-
nized activity from a small number of neuromodulatory cells
can construct ex novo a functional network from neurons other-
wise belonging to a different functional network (Marder and
Thirumalai, 2002; Meyrand et al., 1994; Simmers et al., 1995).
The phylogenetic stability of norepinephrine systems from crus-
taceans to humans is a powerful argument for stability of func-
tion. The Aston-Jones/Cohen theory of the phasic LC-NE signal
is not necessarily inconsistent with this idea, because the
authors note that the phasic signal effectively reconfigures the
following a decision phase but does not capture the ‘‘network
We propose a functional relationship between signals of the
LC/NE system and activity in the ventral attention network,
both in relation to behavioral transitions (tonic signals) and target
detection (phasic response). The decrease in tonic LC activity
during the transition from an exploratory state to a task-focused
state may parallel the deactivation of TPJ, relative to rest, when
subjects engage in a demanding task (Shulman et al., 2003;
Todd et al., 2005) (Figure 8). The Aston-Jones/Cohen theory
maintains that a decrease in the tonic level of LC activity
promotes engagement on the current task and filtering of
distracters, similar to the hypothesis that the ventral attention
network is deactivated under demanding conditions, reflecting
a top-down ‘‘filtering’’ signal that restricts the network response
to a narrow range of task-relevant stimuli (targets or contingent
distracters). Conversely, the hypothesized broad sensitivity to
environmental stimuli during the high tonic activity/exploratory
LC mode in the Aston-Jones/Cohen model may correspond to
the ability of any salient stimulus to activate TPJ during passive
viewing or no-task states (Downar et al., 2000). We reviewed
evidence above that the sources of top-down filtering signals
into the ventral network are either the dorsal network through
prefrontal cortex (Figures 5C and 2B) or prefrontal regions (ante-
rior cingulate, frontal operculum; Figure 5C) directly or indirectly
through their projection via LC. On the output side, LC-NE neu-
rons densely projects to inferior parietal cortex and superior
temporal gyrus, possible homologs of human TPJ (Foote and
Morrison, 1987; Morrison and Foote, 1986). Therefore, as shown
in Figure 8, the deactivation of the ventral attention network
during focused attention may be partly caused by a decrement
of tonic activity in the LC/NE system.
There is also a striking similarity between the target-related
response in the ventral network, P300 potentials, and the phasic
response in the LC (Table 1). All three (ventral network, P300, LC
neurons) show enhanced responses to behaviorally relevant
stimuli (targets) in multiple modalities, relative to distracters,
and an enhanced response to low-frequency targets. Detection
of unattended targets (i.e., ‘‘invalid’’ targets in the Posner cueing
paradigm) enhancesboth TPJactivityandtheamplitudeofalate
positive potential that may correspond to P300 (Mangun and
Hillyard, 1991), while stimuli of high emotional valence modulate
P300 and LC activity. On the response output side, TPJ activity,
P300, and LC activity are relatively independent of response
parameters (Astafiev et al., 2006; Clayton et al., 2004; McCarthy
and Donchin, 1981). Finally, both P300 and LC activity can be
anatomically linked to TPJ. Lesions of different parts of the
ventral attention network affect different components of P300,
with TPJ damage decreasing both target- and novel-evoked
P300 components and prefrontal lesions affecting the novelty
response (Yamaguchi and Knight, 1991b; Verleger et al., 1994;
Daffner et al., 2000). A recent study showed that oddball target
responses in TPJ and prefrontal cortex were abolished by
propranolol, a b-adrenergic blocker drug (Strange and Dolan,
These physiological similarities point to similar functions. The
hypothesis that the ventral attention network is involved in reor-
ienting from one task state to another, either in the environment
or between internally and externally directed activities, is very
Figure 8. Relationship between Activity in
TPJ and Locus Coeruleus/Noradrenergic
The surface-rendered brains show fMRI BOLD
activations and deactivations relative to when
subjects are fixating in an otherwise blank field
(i.e., the baseline, left panel), when searching
through letter distracters of an RSVP display (mid-
dle panel, ventral network is deactivated, dorsal
network is activated), and when detecting a digit
target in the display (right panel, both networks
are activated along with other regions) (Shulman
et al., 2003). The bottom panel shows spiking ac-
tivity in monkey locus coeruleus neurons during
analogous periods: an inattentive period in which
a task is poorly performed and tonic activity is
high, an attentive period in which the task is
performed well and tonic activity is decreased,
and target detection, which produces a phasic
increase in activity (Usher et al., 1999). The inset
trace shows event-related potentials recorded
from the scalp of a human when a target is de-
tected in a completely separate experiment, with
the large positive deflection indicating the P300.
Neuron 58, May 8, 2008 ª2008 Elsevier Inc.
close to the network-reset hypothesis of Bouret and Sarah. A
network reset or interrupt hypothesis captures the sensitivity of
the ventral attention network to task transitions or unexpected
events that may require the dorsal network to be reconfigured
(as in Figures 6B and 7A). Under these conditions, activity in
the dorsal network reflects the reconfiguration of task processes
(stimulus and motor representations) in response to the new
contingency, while activity in the ventral network facilitates
rather than initiates this reset or reconfiguration process. We
have already discussed that activity in the ventral network, as
indexed by the P300, may not be sufficiently fast to initiate a
reorienting response. A similar argument applies to the LC-NE
system, which has a relatively long latency to a stimulus
(?100–150 ms) and a slow transmission of its output to the cor-
tex (?50–100 ms). In the context of a nonlinear dynamic system,
the highly synchronized LC-NE activation of the ventral network
may allow the dorsal network to switch to or settle into another
state more appropriate for the new environmental situation
(Serences and Yantis, 2006).
While the adaptive-gain theory of Aston-Jones and Cohen is
concerned with the role of LC/NE activity in categorization and
responding to attended targets, an interrupt/reset/reorienting
framework includes other situations discussed above, such as
stimulus-driven shifts of attention, transitions between rest and
an extended task period, and detection of event boundaries.
The disruption of a reset signal may impair shifting between
objects or events in the environment and thus underlie nonlater-
alized attentional impairments after damage of ventral frontal
and temporoparietal cortex (Husain and Rorden, 2003), such
as poorer detection or identification of targets in both visual
fields (Duncan et al., 1999; He et al., 2007a; Peers et al., 2005),
problems with vigilance (Heilman et al., 1987b; Robertson,
2001; Wilkins et al., 1987), and an extended ‘‘attentional blink’’
(Husain et al., 1997; Shapiro et al., 2002). Moreveor, impaired
interactions between the ventral and dorsal attention network
(Corbetta et al., 2005; He et al., 2007a) produce activity imbal-
ances in parietal spatial maps that result in a tonic attentional
bias toward the ipsilesional field. Transient increases in vigilance
improve spatial attention and perception (Robertson, 2001;
Robertson et al., 1998), presumably through an augmentation
of LC-NE output that leads to a more normal interaction between
the two networks.
This review of the function of the ventral attention network
suggests several novel avenues for future investigation. It is im-
portant to know the timing of the activation of ventral and dorsal
networks on timescales that are closer to the underlying neural
signals and whether temporal codes such as synchronization
and coherence link widely separate neuronal populations during
selection and behavioral reorienting. The recent combination
of fMRI and EEG/MEG methods, as well as the integration of
TMS/fMRI and EEG, should provide important information on
timing and causal interactions between areas. Also, the evolu-
tionary precursors of the ventral attention network and its right
hemisphere lateralization could be uncovered by neuroimaging
and single-unit studies of primates. An ongoing and critical issue
is the relationship between different attentional functions and
neuromodulatory systems, especially noradrenaline, acetylcho-
line, and dopamine, for which there is already strong evidence
of a role in attention and learning. Finally, further exploration
into human pathologies, both focal (e.g., stroke) and nonfocal
(e.g., traumatic brain injuries, attention-deficit disorders), using
cognitive neuroscience models of attention, may lead to a better
theory of these debilitating conditions.
This work was supported by the J.S. McDonnell Foundation, the National
Institute of Neurological Disorders and Stroke (R01 NS48013), the National
Union (MEXC-CT-2004-006783). We thank Jan De Fockert, Emiliano Maca-
luso, John Serences, Rene ´ Marois, Vinod Menon, Devarajan Sridharan, Nikos
Dosenbach, Steve Petersen, Jean Decety, Jason Mitchell, Kevin A. Pelphrey,
and Gary Aston-Jones for generously providing illustration of their results. We
would like also to thank James Bisley, Christos Constantidinis, Ron Mangun,
and Joe Hopfinger for helpful discussions.
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Table 1. Ventral Attention Network/P300/LC Activity
InputsTPJ/VFC P300LC Phasic
Target > passive+++
(visual, auditory, tactile)
Stimulus probability (low > high)+++
Orienting to unattended
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Orienting to contingent
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