This is a paper I wrote for school on brain impairments in attention deficit hyperactivity disorder, with a focus on neuroanatomical differences and connectivity patterns. I reviewed findings from various studies, considered their limitations, and proposed directions for future research.

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Elizabeth Lundstedt
A08924216
COGS 172
March 2013
Brain Impairments in Attention Deficit Hyperactivity Disorder
There have been a large number of studies conducted on the neurological basis of
attention deficit hyperactivity disorder (ADHD). Many of them have contradictory results about
the differences in brain morphology and connectivity between ADHD subjects and controls. This
mostly results from having small sample sizes due to the expense of extracting MRIs, as well as
inconsistent methodology, the heterogeneity of ADHD causes and symptoms, and the difficulty
in finding medication-naïve populations. However, the most consistent findings include smaller
overall brain size in ADHD children, especially in the frontal lobes, basal ganglia, and
cerebellum (Krain & Castellanos, 2006). Abnormal connectivity during rest and during cognitive
tasks compared to controls has also been demonstrated (Konrad & Eickhoff 2010).
The largest study on ADHD anatomy tested 152 children and adolescents with ADHD
and 139 controls four times over a decade (Castellanos et al. 2002). It found smaller brain size in
ADHD subjects across all regions of the brain, especially the cerebellum. Frontal and temporal
gray matter, caudate, and cerebellar volumes seemed the most diagnostic of ADHD symptom
severity according to parent and clinician ratings. Also, previously unmedicated patients with
ADHD showed smaller white matter volumes than medicated ADHD patients and controls. The
volume abnormalities persisted with age as the subjects got older, with the exception of the
caudate nucleus. The caudate nucleus was abnormally small for ADHD children but the

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differences became insignificant during adolescence when the volume decreased in both ADHD
patients and controls. Results did not differ between male and female subjects. The results
suggest that attention involves large regions of the brain, so deficits in any region are likely to
cause attention problems.
Krain & Castellanos stated in their 2006 review paper that although many brain regions
have been implicated in ADHD, the region that seems the most consistently deviant among
ADHD subjects is the cerebellum, especially the posterior-inferior cerebellar vermis. The
cerebellum is involved in both the coordination of motor movements as well as in attention-
shifting. Children with ADHD have smaller cerebellums compared to controls even after
adjusting for total brain size. MRIs of 46 right-handed boys with ADHD and 47 controls
(Berquin et al., 1998) showed that the posterior-inferior lobe of the cerebellar vermis was
especially small in ADHD subjects. The posterior-inferior cerebellar vermis is different from the
rest of the cerebellum in that it contains dopamine-transporter-like immunoreactive axons. This
is consistent with the hypothesis that ADHD symptoms result from a reduction in dopamine
relative to healthy controls. The cerebellum in turn is part of the frontal-striatal-cerebellar circuit,
which is involved in mediating response inhibition, delay aversion, and executive functioning, all
of which are impaired in ADHD subjects.
Krain & Castellanos (2006), state that frontal lobe volumes are also significantly smaller
in ADHD subjects. This is especially significant for the prefrontal cortex. Greater reductions
have been shown for the right prefrontal cortex relative to controls, resulting in decreased
asymmetry. However, asymmetry measures tend to be unreliable, so this data is not conclusive.
As for more specific subregions, deficits have been reported in the right dorsolateral PFC and the
left orbitofrontal cortex. Mostofsky et al. (2002) performed an experiment comparing the brains

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of 12 ADHD boys with age and gender matched controls. They used cortical landmarks to define
functional regions. The results showed a global volume reduction of 8.3% in the ADHD subjects,
which was only significant in the frontal lobes. Within the frontal lobes, there was a reduction in
both grey and white matter, with the white matter reduction localized to the left hemisphere. The
volume reduction occurred in the prefrontal, premotor, and deep white matter volumes. The
findings suggest that the frontal lobe is important for attention, which is to be expected because
the frontal lobe is responsible for executive function and impulse control, both of which are
necessary for sustained attention. However, due to the small sample sizes in this experiment, the
results should be taken with a grain of salt.
The basal ganglia is another region that has been implicated in ADHD. A study by
Aylward et al., (1996) was done to assess the differences in basal ganglia volumes between 10
ADHD subjects, 16 ADHD subjects who also had Tourette syndrome, and 11 normal controls.
This study was a follow-up to previous research that compared Tourette subjects with Tourette
subjects who also had ADHD, which found reduced globus pallidus volumes for the comorbid
group compared to the Tourette-only group and controls. The subjects in this study were boys
who were matched for age and handedness. They had a mean age of 11 and all were right-
handed. The ADHD group and the comorbid group were also matched for IQ. IQ data was
unavailable for the control group. Some of the boys who had Tourette’s syndrome were taking
medications, and all of the boys in the ADHD group were taking methylphenidate. The results of
the MRI scans showed that the boys who had ADHD had significantly smaller total globus
pallidus volume, especially on the left side. This remained significant even after correcting for
total brain volume. There was no difference between the group that had ADHD alone versus the
group that had ADHD along with Tourette syndrome. It is not known why the globus pallidus

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reduction is associated with ADHD but not Tourette syndrome, as the globus pallidus is involved
in regulating voluntary movement, which is impaired in Tourette patients. Some shortcomings of
the study are the small sample sizes, unavailability of IQ information for the control group, and
the different types of medications taken by the ADHD group and the comorbid group.
Another way to measure brain function is to use SPECT with N-Isopropyl I-123 IMP to
indicate regions of blood flow and metabolism in the brain. The experiment by Sieg et al. (1995)
used 10 ADHD patients and 6 controls who had other psychiatric disorders in their scans. Their
results demonstrated that ADHD patients had more hemispheric asymmetry in their uptake with
less activity in the left parietal and left frontal regions. These results are consistent with earlier
studies. However, this experiment was flawed for having such a small number of test subjects. It
also failed to control for age and IQ. Age and IQ were highly variable between subjects, and the
averages differed across the two groups. The ADHD group had an average age of 9 years
whereas the control group had an average age of 11.7 years, and the ADHD group had an
average IQ of 72.8 whereas the control group had an average IQ of 86.8. All of these factors
could have contributed to error in the results.
The majority of studies on brain volume reductions have not fine-tuned them to very
specific regions. Sowell et al. (2003) conducted a study in which they measured the distance
between the center of the brain and various regions of the cortical surface to determine the
relative reductions in size for ADHD subjects relative to controls. They found bilateral
reductions in size in the dorsal prefrontal cortex and the anterior temporal cortex. There were
bilateral increases in grey matter in the posterior temporal cortex and inferior parietal cortex.
Other research supports the idea that the dorsal prefrontal cortex and anterior temporal cortex are
part of an interconnected system involved in attention control, so it is not surprising that brain

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volume would show reduction in these areas for ADHD subjects relative to controls. As for the
increases in grey matter density in the posterior temporal cortex and inferior parietal cortex, that
could be a result of an incomplete pruning of synapses or a relative reduction of white matter in
those areas.
White matter connectivity plays a large role in ADHD symptoms. The review paper by
Konrad & Eickhoff (2010) goes over the connectivity differences that characterize ADHD. The
default mode network (DMN) is the network of brain regions that is involved in task-irrelevant
mental processes. It consists of the precuneus, posterior cingulate cortex, medial prefrontal
cortex, and the lateral, medial, and inferior parietal cortex. The DMN is more active during rest
than while the subject is performing tasks, although it is not suppressed entirely during tasks.
Stronger suppression occurs while the subject is performing more demanding tasks. Insufficient
suppression during such tasks has been shown to predict errors in task performance as well as
resulting in longer reaction times. In contrast, the fronto-parietal network consisting of the
dorsolateral prefrontal cortex, the intraparietal sulcus, and the supplementary motor area show
increased activation during attention-demanding tasks. Its activation is temporally anti-correlated
with activation of the DMN. Multiple studies have suggested that children with ADHD have
disrupted frontal-parietal connectivity during tasks that require attention and are less successful
at inhibiting DMN activity while performing attention-demanding tasks.
ADHD patients may also have abnormal connectivity in the default mode network. The
experiment by Uddin et al., (2008) involved taking brain scans of adults with ADHD. The results
showed abnormal connection between the precuneus and other regions of the default mode
network. However, their study seems flawed because they used different recruitment methods for
the ADHD subjects as opposed to the controls. The ADHD subjects were recruited from a

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university ADHD program and controls were recruited through media advertisements. The types
of people who attend programs to alleviate their ADHD symptoms may not be representative of
people with ADHD, and the types of controls who get recruited would depend on the specific
media outlets that the advertisements were placed in. The paper made no mention of what those
media outlets were. Also, the ADHD subjects who were still taking medications were combined
with ADHD subjects who had ceased taking medications. Even though none of the subjects had
taken medications for 24 hours prior to the scanning, their past use of the medications may have
caused long-term changes to their brain morphology and connectivity patterns relative to the
untreated individuals.
Another experiment by Makris et al. (2007) compared the white matter tracts of adults
with childhood ADHD to healthy control subjects using MRI and fractional anisotropy (FA)
maps. Their results showed less FA in the cingulum bundle and superior longitudinal fascicle II
compared to the fornix, which was used as a control region. The cingulum bundle is one of the
principal fiber tracts connecting bilateral brain regions involved in executive function, such as
the frontal, parietal, and superior temporal lobes. The SLF II is in turn involved in connecting the
prefrontal cortex with the posterior parietal cortex. Its function may be to help subjects orient
attention to specific parts of space. The results are interesting, but the study could have been
improved if it also compared adults with childhood ADHD who still exhibited symptoms to
adults with childhood ADHD who no longer fit the diagnostic criteria.
Differences in connection efficiency have been noted in ADHD as well. Wang et al.
(2009) collected resting-state fMRI data from 19 children with ADHD and 20 healthy controls.
The results found that although both groups displayed efficient local connectivity, ADHD
subjects had relatively impaired global connectivity. They also showed impaired nodal

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efficiencies in the medial prefrontal, temporal, and occipital cortex, but increased nodal
efficiency in the inferior frontal cortex and subcortical areas. (Nodal efficiency refers to the
connections that a region has with other parts of the brain. Lower nodal efficiency for a region
would mean that region is more isolated from the rest of the brain and cut off from the rest of the
network.) The results are mostly consistent with earlier studies implicating these regions in
executive function. Executive function requires multiple brain regions, so impaired global
efficiency would result in poorer executive function. The increased nodal efficiency in the
inferior frontal cortex and subcortical areas however may be a form of compensation caused by
long-term effort by the ADHD children to inhibit their symptoms.
Konrad and Eickhoff (2010) describe some potential causes of the disorder. ADHD is
mediated by genetic and environmental factors. It is generally accepted that there are multiple
genetic factors that are responsible for the condition. The genetic basis is suggested by
correlations in white matter connectivity between ADHD children and their parents. As for
environmental factors, multiples studies have demonstrated that ADHD is the most common
disorder following brain injuries during childhood (Max, et al., 1997), especially of the basal
ganglia and thalamus (Gerring et al., 2000). Low birth weight and perinatal exposure to
teratogens have also been consistently shown to be risk factors for ADHD. Low birth weight in
particular has been linked to low FA in white matter tracts that have been implicated in ADHD
(Konrad and Eickhoff 2010). Overall, the pattern of connectivity in ADHD subjects shows
similarity to connectivity in healthy younger children, perhaps suggesting delayed brain
maturation as a basis for ADHD symptoms. Supporting this hypothesis is the observation that
ADHD symptoms frequently normalize with age.

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In conclusion, a comparison of the most consistent findings suggests that ADHD involves
a network of interconnected regions of the brain, particularly those known to be involved in
executive function and motor control. Dysfunction in any part of the network is likely to result in
ADHD symptoms. Some common limitations in these studies are small sample sizes and failure
to control for potential confounds such as age, IQ, medication history, and specific symptoms. It
would be interesting to compare neurological differences between people who possess different
subtypes of ADHD, such as the inattentive type versus the hyperactive type. That way it might
be possible to localize specific behavioral deficits to specific regions. Another problem with
many of these studies is that most of them look for correlations between brain differences and
behavior rather than testing for causation. One potential way to test for causation would be to use
TMS to induce temporary lesions in healthy subjects in regions of the brain that have been
implicated in ADHD while making them perform various attention-demanding tasks. Their
performance can then be compared to controls and analyzed. It would also be nice to see more
longitudinal studies extending from the early childhood onset of symptoms into adulthood.
Changes in brain morphology and connectivity between adults who still had the disorder can be
compared to that of adults who no longer did, and both groups can be compared to their younger
selves. Overall, there is still much to learn about the neurological mechanisms underlying ADHD
and how they cause the specific cognitive deficits that characterize it. Considering the major toll
ADHD takes on the productivity of the individuals who suffer from it, this would be a good topic
for future research to focus on. Knowing the causes and mechanisms underlying ADHD is an
important step toward developing prevention and treatment.
References

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