Neural Networks 19 (2006) 1422–1429
2006 Special Issue
Analyzing and shaping human attentional networks$
Michael I. Posnera,∗, Brad E. Sheesea, Yalc ¸in Odludas ¸a, YiYuan Tangb,a
aDepartment of Psychology, University of Oregon, Eugene, OR, USA
bInstitute of Neuroinformatics, Dailan University of Technology, China
Received 30 June 2006; accepted 1 August 2006
In this paper we outline a conception of attentional networks arising from imaging studies as connections between activated brain areas carrying
out localized mental operations. We consider both the areas of functional activation (nodes) and the structural (DTI) and functional connections
(DCM) between them in real time (EEG, frequency analysis) as important tools in analyzing the network. The efficiency of network function
involves the time course of activation of nodes and their connectivity to other areas of the network. We outline landmarks in the development of
brain networks underlying executive attention from infancy and childhood. We use individual differences in network efficiency to examine genetic
alleles that are related to performance. We consider how animal studies might be used to determine the genes that influence network development.
Finally we indicate how training may aid in enhancing attentional networks. Our goal is to show the wide range of methods that can be used to
suggest and analyze models of network function in the study of attention.
c ? 2006 Elsevier Ltd. All rights reserved.
Keywords: Alerting; DCM (Dynamic causal model for connectivity analysis); DTI (Diffusion tensor imaging); EEG frequency (electroencephalographic); fMRI
(functional magnetic resonance imaging); Executive attention; Orienting; Self-regulation
The goal of this paper is to inform people interested in neural
network models about efforts to analyze the networks of neural
areas revealed in imaging studies and to understand how genes
and experience shape their development. To do this we first
in functional imaging studies, and then examine physical and
functional connections between these areas. Next we consider
how these networks develop during infancy and early childhood
and finally what is known about how genes and experience
shape the network.
1. Networks of attention
What do we mean by an attentional network? In cellular
physiology the idea of a network involves identified neurons
$This paper is prepared for a special issue of Neural Networks on attention.
We are grateful for the help of Scott Frey, Director and members of the Lewis
Center for Neuroimaging for their help with the data and the analyses used
to illustrate DTI and fMRI connectivity in this paper. We also thank Jin Fan
for allowing us to quote in process data from his EEG research. Support was
provided by NIH Grant HD 38051 and a grant from the Dana Foundation. We
are grateful to Mary K. Rothbart for her help in developing this paper.
∗Corresponding address: 1227 University of Oregon, Department of
Psychology, 97403-1227Eugene, OR, USA. Tel.: +1 541 346 4939; fax: +1
541 346 4914.
E-mail address: firstname.lastname@example.org (M.I. Posner).
that connect to one another by synapses and through other
means of communication (Bullock et al., 2005). Connectionist
models, inspired by neural networks, have considered units
at particular levels that influence each other by direct or
reciprocal connections (O’Reilly & Munakata, 2000). Imaging
of human task performance has identified another level of
network function, which is clearly related to both the models
and the underlying cellular structure by showing that a number
of quite separate brain areas must be orchestrated in even the
simplest task. Each of these areas may be performing a different
computation, which taken together allow performance of the
task. We regard the set of activations and their connections as
the network that underlies task performance.
It is often believed that attention is a general property of
the whole brain, but neuroimaging studies have shown specific
networks of neural areas are involved in functions related to
attention (see Fig. 1). Attentional networks are special in that
networks. As illustrated in Fig. 1 three attentional functions
for which brain networks have been imaged are: alerting
which is involved in acquiring and maintaining the alert state;
orienting to sensory stimuli and executive control involved in
the resolution of conflict between neural systems and regulating
thoughts and feelings (Fan, McCandliss, Fossella, Flombaum,
0893-6080/$ - see front matter c ? 2006 Elsevier Ltd. All rights reserved.
M.I. Posner et al. / Neural Networks 19 (2006) 1422–1429
Fig. 1. This figure illustrates cortical areas involved in three attention networks.
The alerting network (squares) includes thalamic and cortical sites related to the
brain’s norepinephrine system. The orienting network (circles) is centered on
parietal sites (discussed below) and the executive network (triangles) includes
the anterior cingulate and other frontal areas.
&Posner,2005). Although thesites at which attention influence
can be demonstrated involve most any brain area including
primary sensory, limbic and motor cortex, as shown in Fig. 1
the sources of these activations are much more limited.
Orienting to sensory events has been the more studied of
these networks both with imaging (Corbetta & Shulman, 2002)
and cellular (Reynolds, 2004) methods. The convergence on the
set of brain areas serving as the source of the amplification of
sensory signals has been impressive (see Hillyard, Di Russo,
and Martinez (2004), for a recent review). It is widely agreed
that the frontal eye fields work in conjunction with superior
and inferior parietal areas as the cortical nodes of the orienting
network. In addition, studies have implicated some subcortical
areas including the pulvinar of the thalamus and the superior
colliculus. Most of the studies of this network have involved
visual stimuli, but the sources of the attention influences in
orienting to other modalities are much the same. Of course the
site of amplification of the sensory message is quite different
for each of the modalities.
Evidence to date suggests that both maintained alertness
during task performance (tonic) and phasic changes induced
by a warning signal involve a subcortical structure, the locus
coeruleus that is the source of the brain’s norepinephrine. A
great deal of evidence (summarized in Posner and Petersen
(1990)) indicates that the tonic state depends upon an intact
right cerebral hemisphere. Lesions in this hemisphere can
produce profound difficulty in responding to unexpected
targets. Warning signals, however, may have their influence
more strongly on the left cerebral hemisphere (Coull, Frith,
Buchel, & Nobre, 2000; Fan et al., 2005). This distinction may
reflect a more general division between the hemispheres where
rapidly acting events are left lateralized while more slowly
changing states involve right hemisphere activity.
Tasks that involve conflict between stimulus dimensions
competing for control of the output often provide activation
in the anterior cingulate gyrus and lateral prefrontal areas.
It is thought that the conflict, induced by a stimulus, is
representative of situations where different neural networks
compete for control of consciousness or output. Because of this
we have termed this the executive attention network because
it regulates the activity in other brain networks involved in
thought and emotion (Crottaz-Herbtte & Mennon, 2006; Etkin,
Egner, Peraza, Kandel, & Hirsch, 2006). This network shows a
strong development in childhood and its maturation is related
to what in developmental psychology has been called self-
Individual differences are invariably found in cognitive tasks
involving attention. The Attention Network Test (ANT) was
developed to examine individual differences in the efficiency of
the brain networks of alerting, orienting and executive attention
discussed above (Fan, McCandliss, Sommer, Raz, & Posner,
2002; Rueda, Fan, et al., 2004). The ANT uses differences in
of each network. Each trial begins with a cue (or a blank
interval, in the no-cue condition) that informs the participant
either that a target will be occurring soon, or where it will occur
or both. The target always occurs either above or below fixation
and consists of a central arrow, surrounded by flanking arrows
that can either point in the same direction (congruent) or in the
from incongruent target trials provides a measure of conflict
resolution and assesses the efficiency of the executive attention
network. Subtracting RTs obtained in the double-cue condition
from RT in the no-cue condition gives a measure of alerting due
to the presence of a warning signal. Subtracting RTs to targets
at the cued location (spatial cue condition) from trials using a
central cue gives a measure of orienting, since the spatial cue,
but not the central cue, provides valid information on where a
target will occur.
2. Network connectivity
Neural areas found active in studies of functional anatomy
to studying this connectivity uses fMRI to study the time course
of activity and the correlations between active areas. Because
of the relatively long delays between input and peak BOLD
fMRI signal, small time differences may be hard to detect.
Another approach to the examination of temporal connections
between brain areas is based on electrical or magnetic signals
since these signals can give higher temporal resolution, and can
be combined with MRI to improve the spatial localization. A
third approach to the measurement of connectivity involves the
measurement of fiber tracts that connect neural areas by use of
diffusion tensor imaging (DTI) that traces white matter tracts.
Below we illustrate these methods by primarily considering the
of the Attention Network Test.
The organization of anatomical areas in alerting and
orienting is not fully known, but some promising beginnings
have taken place. In alerting the source of the attention appears
in the locus coeruleus (lc). Cells in the lc have two modes
of processing. One mode is sustained and is perhaps related
M.I. Posner et al. / Neural Networks 19 (2006) 1422–1429
Fig. 2. The results of the Diffusion Tensor Imaging study of the structural
connectivity of the dorsal and ventral anterior cingulate. The colors indi-
cate the orientation of the fibers red = left–right, green = anterior–posterior,
and blue = inferior–superior. DTI images were acquired from a single sub-
ject on a 3.0 T Siemens Allegra MRI scanner. Diffusion weighting was per-
formed using b = 700 s mm−3along 60 independent orientations (Jones
et al., 1999). MR acquisition parameters were: TE/TR = 110 ms/10.9 s;
matrix = 128 × 128 on a 256 mm FOV, slice thickness = 2 mm with
no gap; 60 transverse slices covering entire brain. DTI data were ana-
lyzed on a Siemens Leonardo TM workstation NUMARIS 4 satellite con-
sole using MGH’s DTI Task Card 1.69 software written by R.P. Wang
(http://www.nmr.mhg.harvard.edu/˜rpwang/siemens/dti taskcard/new). (For in-
terpretation of the references to colour in this figure legend, the reader is re-
ferred to the web version of this article.)
to the tonic level of alertness over long time intervals. This
function is known to involve the right cerebral hemisphere more
strongly than the left (Coull et al., 2000; Sturm & Willmess,
2001). Alertness is influenced by sensory events and by the
performance may be orchestrated from the anterior cingulate
(Mottaghy et al., 2006). More phasic shifts of alerting can
result from presenting any environmental signal. However, if
the signal is likely to warn about an impending target this
shift results in a characteristic suppression of the intrinsic
brain rhythms (e.g. alpha) within a few tens of milliseconds
and a strong negative wave (contingent negative variation)
recorded from surface electrodes and that moves from a frontal
generator toward the sensory areas of the hemisphere opposite
the expected target.
According to Bush, Luu, and Posner (2000) an analysis of
a number of conflict tasks shows that the more dorsal part of
the anterior cingulate is involved in the regulation of cognitive
tasks, while the more ventral part of the cingulate is involved
in regulation of emotion. One way to examine this issue is
to image the structural connections of different parts of the
cingulate using diffusion tensor imaging. This form of imaging
uses the diffusion of water molecules in particular directions
due to the presence of myelinated fibers (Conturo et al., 1999).
Thus it provides a way of examining the physical connections
present in the brains of people. Fig. 2 shows the result of a DTI
analysis of one subject run in our experiments. Note that the
dorsal part of the ACC shows connections to cortical areas of
the parietal and frontal lobes, while the ventral part of the ACC
has strong connections to subcortical limbic areas (Abdullaev,
Fig. 3. The results of an fMRI connectivity analysis based on the correlations
between the dorsal anterior cingulate and other cortical brain areas. Dynamic
causal modeling (DCM) was used to infer the direction of influence. Each circle
contains the Brodmann area involved. All influences among regions shown by
lines are significant in the direction of the arrow.
Another step is to examine networks of neural areas related
to the ACC during task performance. To illustrate this approach
we consider a recent fMRI study, in which we ran 12 young
adults in the ANT. The data were first analyzed by statistical
parameter mapping (SPM2) (http://www.fil.ion.ucl.ac.uk/spm)
to produce the functional anatomy of different attentional
circuits shown in Fig. 1. For illustrative purposes we examined
the cortical connectivity (Horwitz, Rumsey, & Donohue,
1998; Tang et al., 2006) to and from the dorsal anterior
cingulate during performance of the conflict subtraction in the
ANT (incongruent–congruent). As expected we found strong
connectivity to parietal and frontal brain areas.
We then applied the Dynamic Casual Modeling (DCM)
method for region of interest (ROI)-based effective connectivity
analyses in the conflict task (Friston, Harrison, & Penny, 2003;
Penny, Stephan, Mechelli, & Friston, 2004). Fig. 3 shows
the results (numbers indicate Brodmann areas). Our findings
showed interregional coupling (effective connectivity) for the
conflict subtraction among the nodes of the attention system
including the dorsal ACC, the lateral ventral prefrontal lobe
(BA6, BA10), superior parietal gyrus (BA7) and temporal
parietal junction (BA22). The ACC is likely to be the core
mediation for the other brain regions in the conflict task. At the
same time, BA7 and BA22 also modulate ACC. The interaction
of the orienting and conflict network arises because following
some cues (e.g. central) a shift of orienting must take place after
the target occurs.
Another way to examine network activity during the ANT
is to use scalp EEG electrodes to record neural activity
synchronized in different frequency bands. This method can
be used to separate rapid temporal events, for example, it can
separate the cue effects from the target effects in the ANT. In
one study using the ANT (Fan et al., in preparation), a spatial
frequency gamma activity (above 30 Hz) about 200 ms after the
M.I. Posner et al. / Neural Networks 19 (2006) 1422–1429
cue presentation. When the cue brought attention to the target
location, gamma activity was found following the cue, but not
following the target. When the cue indicated the center location
so that a shift of attention was needed following the target,
the gamma activity was present following the target. These
data suggest that gamma activity is associated with orienting
of attention. It may occur 200 ms after the cue or only after the
target depending upon when attention shifts. Taken together the
fMRI, EEG and DTI methods can provide a detailed account of
the orchestration of neural networks related to attention.
3. Development of attentional networks
The goal of understanding networks is to illuminate their
role in actual human behavior. Efforts have been made
to examine how the development of attentional networks
influences infant and child behavior. Such landmarks of
development are crucial for links between genetic differences
and actual behavior. The alerting and orienting systems begin
development in early infancy and allow the infant to stay alert
and to be in contact with sensory information. However, in
this paper we concentrate on the executive network, which
has been more difficult to demonstrate even in a rudimentary
form during infancy. One effort involves anticipatory looking
paradigms such as the Visual Expectation Paradigm (Haith,
Hazan, & Goodman, 1988). In this method a repeating
predictable sequence of visual stimuli is shown to infants.
Infant eye movements are recorded and coded for evidence of
reactive looks, which occur in response to the presentation of
stimuli, and anticipatory looks, which occur in advance of the
presentation of stimuli. Reactive looks are thought to reflect
exogenous control of attention in that looks to stimuli are
in response to the stimuli itself and only require attentional
processes associated with alerting and orienting. In contrast,
anticipatory looks involve internal control of attention and may
reflect the early functioning of the executive attention network.
Anticipatory looking to more complex, ambiguous se-
quences of visual stimuli may present a method for examin-
ing more sophisticated forms of executive attention in infancy.
Working with adults, Curran and Keele (1993) showed that
while stimuli appearing in an unambiguous sequence of lo-
cations (e.g., 123123) could be learned in the absence of at-
tention, learning context-dependent sequences (e.g., 12131213)
was dependent upon higher-order attentional processes. Clo-
hessy, Posner, and Rothbart (2001) proposed that higher-order
attentional processes may be required when anticipating a stim-
ulus following Location 1 in a context-dependent sequence be-
cause there is a conflict that must be resolved between shift-
ing attention to Location 2 and Location 3. They examined an-
ticipatory looking to both unambiguous and context-dependent
sequences of visual stimuli in infancy and found anticipatory
looking during unambiguous sequences as early as 4 months.
However, anticipatory looking during context-dependent se-
quences was not seen consistently until at least 18 months of
age. These data suggest the possibility that rudimentary exec-
utive attention capacities may emerge during the first year of
life but that more advanced conflict resolution capacities are
not present until 2 years of age.
We are currently examining how executive attention as
assessed through anticipatory looking is related to emotional
and behavioral regulation in 7–9 month old infants. Preliminary
analyses suggest that infants showing higher levels of
anticipatory looking are also more likely to regulate approach
tendencies when presented with novel toys and are also more
likely to show self-soothing behaviors when presented with
frightening stimuli. These results are consistent with findings
from childhood that show higher levels of executive attention
are broadly related to behavioral and emotional regulation (see
Rothbart and Sheese (in press), for a review).
Another approach to examining executive attention in
infancy involves the ability to detect errors (Berger, Tzur, &
Posner, 2006) examined error detection capacities in seven-
month-old infants. Using a method developed by Wynn (1992),
infants were presented with simple addition problems using a
visual display of cartoon-like characters that were either correct
(1 + 1 = 2) or incorrect (1 + 1 = 1). As in previous studies
the infants looked longer at problems with incorrect answers.
EEG analysis showed an increased frontal negativity for the
incorrect problems that closely resembled that found in adults
and is known to arise in the anterior cingulate. This finding
suggests that executive attention in infancy arises in the same
anatomy as found in adults.
Two-year-olds have sufficient verbal and motor skills that
have developed to allow for laboratory tests of executive
attention that more closely resemble adult assessments.
A spatial conflict task using a touch-sensitive screen for
responding has been used to examine conflict resolution with
children as young as 2 years of age. The spatial conflict
task developed by Gerardi-Caulton (2000) places an object’s
identity and spatial location in conflict. At 24 months, children
are generally unable to resolve this conflict and show high
levels of incorrect responding. By 30 months children show
much higher levels of correct responding but still show
delays in reaction time on incongruent trials similar to what
is found in adults. Children with better conflict resolution
in the spatial-conflict task had higher levels of anticipatory
looking and also higher parent-ratings of effortful control
(Rothbart, Ellis, Rueda, & Posner, 2003). These results show
the methodologically distinct measures of conflict resolution
do reflect a common process that can be observed by parents
in daily life.
The Child Attention Network Test (ANT-C) is a modified
version of the adult ANT for use with children as young as
4 years of age. Using the ANT-C we (Rueda, Fan, et al.,
2004) examined executive attention in children between 6 and
10 years of age and compared their performance with adults.
Results suggest that executive attention continues to develop
throughout childhood but may stabilize at near-adult levels of
performance by about eight years of age.
There is considerable evidence that the executive attention
network is of great importance in the acquisition of school
subjects such as literacy (McCandliss, Beck, Sandak, &
Perfetti, 2003), numeracy and in a wide variety of other subjects
(Posner & Rothbart, 2007).
M.I. Posner et al. / Neural Networks 19 (2006) 1422–1429
The impact of individual differences in executive attention
can be seen in different areas of social development. We
have proposed that individual differences in effortful control
reflect differences in the functioning of the executive attention
network (Posner & Rothbart, 1998; Rothbart, Derryberry,
& Posner, 1994). Consistent with this hypothesis, we have
found evidence that effortful control is related to executive
attention measures throughout childhood (Gerardi-Caulton,
2000; Rothbart et al., 2003). Effortful control, in turn, has
been related to a broad range of outcomes relevant to social
development including empathy, the regulation of negative
affect, conscience development, and theory of mind (Rothbart
& Bates, 2006).
Emotion, thought, and behavior form a cluster of temporally
associated processes in specific situations as experienced
by the child. Single and repeated life experiences will
thus shape connections between elicited emotion, conceptual
understanding of events, and use of coping strategies to deal
with these events. Several theorists have made contributions
to this approach (e.g., Epstein (1998) and Mischel and
Ayduk (2004)), but the overall framework is in keeping with
the idea of Hebbian learning through network activation.
Mischel and his colleagues have recently developed a cognitive
affective personality (CAP) theory, making use of Cognitive
Affective Units (CAUs) seen to operate within a connectionist
network (Mischel & Ayduk, 2004). In their model, CAUs are
variables encoding the features of situations, which include
environmental effects as well as self-initiated thoughts.
4. Genes and experience build networks
As more is known about the developmental progression of
executive attention as discussed above, there is an increased
possibility of accounting for both the general development
of the network and individual differences by examining how
genes and experience interact to shape the executive attention
network. Some progress made in that direction is discussed
To determine genes that might be related to building
an attentional network we used the Attention Network Test
(ANT) to examine individual differences in the efficiency of
executive attention. We first used the ANT to assess attention in
monozygotic and dizygotic same-sex twins (Fan, Wu, Fossella,
& Posner, 2001). We found strong heritability of the executive
network. These data supported a search for genes in executive
We then used the association of the executive network
with the neuromodulator dopamine as a way of searching
for candidate genes that might relate to the efficiency of
the network (Fossella et al., 2002). To do this, 200 persons
performed the ANT and were genotyped to examine frequent
polymorphisms in genes related to dopamine. We found
significant association of two genes, the dopamine D4 receptor
(DRD4) gene and monoamine oxidase a (MAOA) gene,
with executive attention. We then conducted a neuroimaging
experiment in which persons with different alleles of these two
genes were compared while they performed the ANT (Fan,
Fossella, Sommer, & Posner, 2003). Groups with different
alleles of these genes showed differences in the ability to
resolve conflict as measured by the ANT and also produced
significantly different activations in the anterior cingulate, a
major node of the executive attention network.
Recent studies have extended these observations. In two
different studies employing conflict related tasks other than
the ANT, alleles of the catechol-o-methyl transferase (COMT)
gene were related to the ability to resolve conflict (Blasi et al.,
2005; Diamond, Briand, Fossella, & Gehlbach, 2004). A study
using the child ANT showed a significant relation between
the dopamine transporter (DAT1) and executive attention
as measured by the ANT (Rueda, Rothbart, McCandliss,
Saccamanno, & Posner, 2005). In addition, research has
suggested that genes related to serotonin transmission also
influence executive attention (Canli et al., 2005; Reuter, Ott,
Vaidl, & Henning, in press).
The relation of genetic factors to the functioning of the
executive attention system does not mean that the system
cannot be influenced by experience. Several training-oriented
programs have been successful in improving attention in
patients suffering from different pathologies. For example,
the use of Attention Process Training (APT) has led to
specific improvements in executive attention in patients with
specific brain injury (Sohlberg, McLaughlin, Pavese, Heidrich,
& Posner, 2000) as well as in children with Attention Deficit
Hyperactivity Disorder (ADHD) (Kerns, Esso, & Thompson,
1999). Work with ADHD children has also shown that working
memory training can improve attention (Klingberg, Forssberg,
& Westerberg, 2002; Olesen, Westerberg, & Klingberg, 2004).
With normal adults, training with video-games produced better
performance on a range of visual attention tasks (Green &
To examine the role of experience on the executive attention
network we have developed and tested a five-day training
intervention that uses computerized exercises. We tested the
effect of training during the period of major development of
executive attention, which takes place between 4 and 7 years of
age according to our previous results (Rueda, Fan, et al., 2004).
We hoped to observe an improvement in conflict resolution as
measured by the ANT in trained children, along with changes
in the underlying network and generalization to other aspects
of cognition. EEG data showed clear evidence of improvement
in network efficiency in resolving conflict following training
(Rueda et al., 2005). The N2 component of the scalp recorded
ERP has been shown to arise in the anterior cingulate and is
related to the resolution of conflict (Rueda, Posner, et al., 2004;
van Veen & Carter, 2002). We found N2 differences between
olds, that resembled differences found in adults. In the four-
year-olds training seemed to influence more anterior electrodes
related to emotional control areas of the cingulate (Bush et al.,
2000). These data suggest that training altered the network for
the resolution of conflict in the direction of being more like
what is found in adults.
We also found a significantly greater improvement in
intelligence in the trained group compared to the control
M.I. Posner et al. / Neural Networks 19 (2006) 1422–1429
children. This finding suggested that training effects had
generalized to a measure of cognitive processing that is far
removed from the training exercises. We did not observe
changes in temperament over the course of the training, but
this was expected, due to the short time elapsing between
Not all children need or benefit from attention training. This
may be why variability is so high in children’s performance. In
some of our studies, children with the most initial difficulty in
resolving conflict showed the greatest overall improvement due
to training. Our research has also suggested a genetic marker
of initial differences in attention among the children. We were
able to genotype most of the 6-year-old children participating
in our training study. Children were divided into two groups
according to their particular form of a genetic polymorphism in
the 3?untranslated region of the dopamine transporter (DAT1);
those carrying the pure long form and those carrying the mixed
short/long form of the gene. Since our sample was small, we
combined 6-year-olds who had attention training with those in
the control condition. Although there were only seven children
in the pure long allele group and eight in the mixed long/short
group, we found a significantly greater efficiency in conflict
scores for the pure long allele group.
Several features of our data supported the relation between
the DAT1 polymorphism and individual differences in the
efficiency of executive attention. Children in the two groups
differed in their conflict scores on the ANT as well as in the
effortful control scores obtained from the Children’s Behavior
Questionnaire (Rothbart, Ahadi, Hershey, & Fisher, 2001). In
particular, the short/long mixed group showed higher conflict
scores and lower effortful control than those in the pure long
group. The two groups also differed in their EEG data. In the
first session, children with the pure long allele showed the effect
of flankers in the expected direction (larger N2 for incongruent
trials), whereas children in the mixed alleles group did not show
this effect. The larger N2 for incongruent trials was also found
for trained children of 6 years of age and adults. Thus the
presence of the pure long allele is associated with more mature
executive attention. The DAT1 gene has also been associated
with attention deficit hyperactivity disorder (ADHD). However,
the exact relation between executive attention efficiency in
normals and the presence of attention deficits in ADHD is not
clear (Swanson et al., 2000).
Our findings are preliminary, because of the small number of
children in a longitudinal study from 7 months to 4 years of age.
We hope to replicate our current results and explore other genes
that might influence the development of attentional networks.
We also hope to explore the origin in infancy of the executive
attention network that we have measured in childhood.
Given the wide range of individual differences in the
efficiency of attention, it is expected that attention training
could be especially beneficial for those children with poorer
initial efficiency. These could be children with pathologies
that involve attentional networks, children with genetic
backgrounds associated with poorer attentional performance, or
children raised in different degrees of deprivation.
Genes do not directly produce attention. What they do is
code for different proteins that influence the efficiency with
which modulators such as dopamine are produced and/or bind
to their receptors. These modulators are in turn related to
individual difference in the efficiency of the attention networks.
There is a great deal in common among humans in the anatomy
of high level networks, and this must have a basis within the
human genome. The same genes that are related to individual
differences in attention are also likely to be important in the
development of the attentional networks that are common to
all humans. Some of these networks are also common to non-
human animals. By examining these networks in animals it
should be possible to understand the role of genes in shaping
Can animals perform the same tasks we have developed
for humans? The answer is clearly yes. Monkeys have been
trained to shift attention to cues and to carry out conflict tasks
like those in the ANT. More recently rodents have also been
trained in attention shifting tasks (Beane & Marrocco, 2004).
These tasks make it possible to examine the role that genes
play in carrying out the same attentional operations as have
been studied in humans. It has also been reported that areas of
the frontal midline corresponding to the anterior cingulate are
(Han, O’Tuathaigh, & Koch, 2004). Since trace and delayed
conditioning are both very simple tasks and the two are quite
similar they could be used to assay operation of rodent brain
areas that may be related to executive attention in humans.
An important need in this effort is the development of
methods to manipulate relevant genes in specific anatomical
locations that are important nodes of a particular network.
Usually genes are expressed at multiple locations, so that
changes (e.g. knock out studies) are not specific to one brain
area. However, using subtractive genomics, a method currently
being developed (Dumas et al., 2005), it should become
possible to determine the specific operations performed by
genes at particular places in different attentional networks.
We believe that this kind of genetic analysis of network
development will create a productive link between genes and
both normal and pathological psychological function.
Abdullaev, Y. Connectivity of the anterior cingulate. Unpublished study,
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Beane, M., & Marrocco, R. (2004). Cholinergic and noradrenergic inputs to the
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