drAmenjournal
DIGNITY AFTER FOOTBALL

MISSION


Dignity After Football is the organization whose purpose is to help guide and resolve the problems found in thelack of benefits, disability claims, and pension of the NFL. Educating our youth and youth sports coaches on dangers of head injuries.

 

OBJECTIVES

Currently, Congress and the government action agencies are requiring the NFL to comply with resolving the benefits and pensions program that has serious flaws in their process to support disabled and retired players.

From Dr. Daniel Amen, research published March 2011 in

The Journal of Neuropsychiatry and Clinical Neurosciences

(coming here soon on "scribd" for easy reading)


The Journal of Neuropsychiatry and Clinical Neurosciences

Impact of Playing
Professional American
Football on Long-Term
Brain Function

Daniel G. Amen, M.D.
Andrew Newberg, M.D.
Robert Thatcher, Ph.D.
Yi Jin, M.D.
Joseph Wu, M.D.
Bill Phillips, Ph.D.
David Keator, M.C.S.
Kristen Willeumier, Ph.D.

The authors recruited 100 active and former NFL
players representing 27 teams and all positions.
Players underwent a clinical history, brain
SPECT imaging, qEEG, and multiple neuropsychological
measures, including MicroCog. Relative
to a healthy comparison group, players
showed global decreased perfusion, especially in
the prefrontal, temporal lobe, parietal, occipital,
and cerebellar regions. Quantitative EEG findings
were consistent, showing elevated slow
waves in the frontal and temporal regions. Significant
decreases from normal values were found
in most neuropsychological tests. This is the first
large-scale brain-imaging study to demonstrate
significant differences consistent with a chronic
brain trauma pattern in professional football
players.
(The Journal of Neuropsychiatry and Clinical
Neurosciences 2011; 23:000–000)
There has been considerable controversy about the
impact of playing professional American football
on long-term brain function.1 At the end of 2009, the
controversy was significantly fueled by a study sponsored
by the National Football League (NFL), which
found that retired players aged 30–49 receive a dementia-
related diagnosis at a rate of 1.9% or 20 times the rate
of age-matched populations, while 6.1% of players over
the age of 50 receive a dementia-related diagnosis representing
five times the national average of 1.2%.2
To date, there have been no published functional
brain-imaging studies on active or retired NFL players,
even though brain injuries are common, and their incidence
has been associated with mild cognitive impairment3
and depression.4
Studying the brain function in a large group of living
players is important to better understand if there are
widespread persistent negative brain effects from playing
professional football and, if so, to evaluate the potential
for rehabilitation. Both brain single photon emission
computed tomography (SPECT) imaging5 and
quantitative EEG (qEEG) have substantial research in
evaluating traumatic brain injury (TBI).6 Brain SPECT
has been shown to be more sensitive than standard CT
or MRI7,8 in evaluating TBI.
Our a priori hypothesis was that that relative to a
matched healthy comparison group, active and retired
NFL players as a group would exhibit significant decreases
in regional cerebral blood flow (rCBF) in the
frontal, temporal and occipital lobe regions of the brain,
consistent with prior brain trauma, and this would result
in compromised neuropsychological functioning.
METHODS
We recruited 100 active and retired NFL players, representing
27 teams and all positions (see Table 1 for
summary). Players were recruited from retired NFL
Players Association meetings and by participants informing
other players about the study. Each player met
our inclusion criteria of being on an active NFL roster
for a minimum of 3 years. We excluded any subjects
Received March 16, 2010; revised July 5, 2010; accepted August 11,
2010. Dr. Amen and Ms. Willeumier are affiliated with Amen Clinics,
Inc., in Newport Beach, CA; Dr. Newberg is affiliated with the Department
of Radiology at the Hospital of the University of Pennsylvania
in Philadelphia; Dr. Thatcher is affiliated with the Applied
Neuroscience Research Institute; Drs. Jin and Phillips are affiliated
with NeoSync Technologies; Dr. Wu and Mr. Keator are affiliated
with the University of California at Irvine. Address correspondence to
Daniel G. Amen, M.D., Amen Clinics, Inc., 4019 Westerly Place Suite
100, Newport Beach, CA 92660; docamen@amenclinic.com (e-mail).
Copyright © 2011 American Psychiatric Publishing, Inc.
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T1
AQ: 1
CLINICAL AND RESEARCH REPORTS
who could not cease taking psychoactive medications
(recreational or otherwise) for an appropriate washout
period prior to scanning. All participants received an
explanation of the research study and gave written informed
consent in accordance with an institutional review
board-approved protocol.
Each participant was interviewed by a physician and
completed a detailed history, including a 315-question
DSM-IV-driven questionnaire to assess overall general
and mental health. Weight and height were obtained on
all participants and body mass index (BMI) was calculated.
Brain concussion and loss of consciousness data
were acquired from each player. Subjects were asked to
recall the number of concussions they had experienced
throughout their lifetime, including those obtained
while playing high school, college, and professional
football. We used the Centers for Disease Control and
Prevention (CDC) definition9 of concussions: “conditions
of temporarily altered mental status as a result of
head trauma” that may or may not involve a loss of
consciousness. Understanding that self-report data, especially
from many years past, is potentially unreliable,
players were also asked about periods where they experienced
a distinct loss of consciousness. Past medical
records were not available for this study, which is a
limitation. Many subjects played in an era of football
where concussions were not taken as seriously as they
are today.
Three computerized neuropsychological tests were
given to each player. These tests included the MicroCog
Assessment of Cognitive Functioning,10 which contains
12 subtests that represent functioning in five core neurocognitive
domains, including attention/mental control,
memory, reasoning, spatial processing and reaction
time. The Microcog Assessment of Cognitive
Functioning scores were compared to its own standardized
sample (N810) chosen to be representative to the
U.S. population of adults between the ages of 18 and
89with regards to education, gender, and ethnicity. Because
our sample had a higher percentage of African
Americans (33%) compared with 13% in the U.S. population,
further ethnic evaluations were performed on
the MicroCog. Participants also took the Conners’ Continuous
Performance test II,11 which measures response
inhibition and attention, and is a validated screening
tool that assigns a clinical probability of having ADHD,
based on its own large normative and clinical sample
database, which did not show an effect from ethnicity.12
Participants were also given the Mild Cognitive Impairment
Screen,13 a screening tool found to be reliable in
distinguishing mild cognitive impairment from normal.
14 The effect of ethnicity on this test has been studied
and found to be essentially zero.15
Each player underwent high-resolution brain SPECT
imaging and qEEG. For SPECT, we used already-acquired
right-handed men as a comparison group
(N20, mean age50.0, range27–83, SD16.1). The
ethnic makeup of the comparison group was Caucasian
(80%), Hispanic (10%), African American (5%), and
Asian (5%). The healthy comparison subjects were
screened using clinical interviews, the same 315-question
DSM-IV driven questionnaire used in this study,
which was also filled out by a significant other, a Structured
Clinical Interview for DSM-IV (SCID), the Beck
Depression Inventory, the Mild Cognitive Impairment
Screen, and the MMPI. All scores were in the normal
TABLE 1. Demographic Characteristics
Characteristic Mean
Age 57.27 (range 25–82)
[SD12.37]
Loss of Consciousness Episodes 2.693
Characteristic n
Handedness 84 right, 16 left or
ambidextrous
Ethnicity
African American 33
Caucasian 60
Hispanic 1
Mixed 6
Positions (N100)
Quarterback 5
Running back 9
Wide receivers 5
Tight ends 8
Offensive lineman 25
Defensive lineman 12
Linebackers 17
Defensive backs 19
Reported Episodes of Loss of
Consciousness
n
0 37
1 15
2 15
35 18
5 14
Minimum/Maximum Episodes of Loss
of Consciousness
0/20
Diagnosed Depression (DSM-IV
Criteria) Currently or Under
Treatment for Depression
28
BMI n
30 51
3040 42
40 6
For number of concussions, four players report “multiple times” or
“too many to count” but could not be more specific.
PROFESSIONAL FOOTBALL AND LONG-TERM BRAIN FUNCTION
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range. Healthy comparison subjects also reported no
brain injuries or head trauma upon being asked multiple
times in multiple ways. They were not taking any
medications at the time of evaluation and had no medical
illnesses. As part of the SPECT procedure, the
healthy comparison men also took a Conners’ Continuous
Performance test II. Only healthy comparison subjects
who scored in the normal range on the Conners’
test were used for this study. Of note, we did not have
a sufficient number of African Americans in our Normal
Control Subject database for comparison with the
NFL players. We added an additional analysis comparing
Caucasian players with Caucasian comparison subjects
to compensate for this issue.
The qEEG data were compared against a nationally
published normative database SPECT acquisition and
analysis. We used SPECT to measure rCBF in both players
and comparison subjects. Each participant received
an age/weight-appropriate dose of technetium-99m
hexamethylpropyleneamine oxime (HMPAO) intravenously.
Participants were injected in normal lighting
while they performed the Conners’ Continuous Performance
test II. The radiopharmaceutical was injected 3
minutes after starting the 15-minute test. All participants
completed the task. The individuals were then
scanned 30 minutes later using a high-resolution Picker
Prism 3000 triple-headed gamma camera with fan beam
collimators, acquiring data in 128128 matrices, yielding
120 images per scan with each image separated by
3° spanning 360°.
SPECT data were processed and attenuation correction
performed using general linear (Chang) methods.
All images were reconstructed and resliced using an
oblique reformatting program, according to anteriorposterior
commissure line so final images were similarly
aligned for analysis.
Differences in HMPAO uptake were analyzed using
SPM8 software (Wellcome Department of Cognitive
Neurology, London) implemented on the Matlab platform
(MathWorks Inc., Sherborn, Mass.). Statistical
parametric maps are spatially extended statistical processes
that are constructed to test hypotheses about
regionally specific effects in neuroimaging data. Statistical
parametric mapping combines the general linear
model and the theory of Gaussian random fields to
make statistical inferences about regional effects.16 The
images were spatially normalized using a 12 parameter
affine transformation followed by nonlinear deformations17
to minimizing the residual sum of squares between
each scan and a reference or template image
conforming to the standard space defined by the Montreal
Neurological Institute template. The original image
matrix obtained at 12812829 with voxel sizes of
2.16 mm2.16 mm6.48 mm were transformed and
resliced to a 799568 matrix with voxel sizes of 2
mm2 mm2 mm consistent with the Montreal Neurological
Institute template. Images were smoothed using
an 8 mm full width at half maximum isotropic
Gaussian kernel. The two-sample t test design was used
with analysis of covariance (ANCOVA) by subject regressors
to account for differences in subject specific
regional response to changes in global cerebral blood
flow (CBF) and age as a covariate. To test our hypotheses
regarding regionally specific condition effects, the
estimates were compared using linear contrasts. The
resulting set of voxel values for each contrast represents
a parametric mapping of the t-statistics, statistical parametric
map(t) , which were transformed into the unit
normal distribution statistical parametric map(z) and
thresholded at t8.85, p0.0001 corrected for multiple
comparisons using the family wise error rate correction
in SPM8.
qEEG Acquisition and Analysis
Quantitative EEG is the measurement of electrical patterns
at the surface of the scalp, which reflect cortical
electrical activity. All of our measurements were obtained
with the subjects’ eyes closed and were sampled
at 200 Hz, using the international 10/20 system of electrode
placement and manual and automatic artifact removal.
Test retest reliability was greater than 0.9 for all
participants.18 There are two categories of measurement
using qEEG: the first category involves amplitude or
power at different frequencies, including 3-dimenional
sources; the second category involves network measures,
such as conduction velocities (phase differences),
coupling magnitudes (coherence) and thalamo-cortical
phase shifts and phase locks.19–22 Previous qEEG studies
have shown that network measures are the most
sensitive in the evaluation of mild to severe traumatic
brain injury.23,24 Comparison to an age-matched qEEG
normative database was used for the 3-dimenional
source analyses, which were demographically balanced
with 24.2% African American clinically healthy subjects.
25,26 The effect of ethnicity for qEEG was studied
and found to be essentially zero.27 None of the healthy
comparison subjects exhibited focal brain abnormalities
AMEN et al.
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and all of the healthy comparison subjects were without
a history of neurological disorders, including TBI.
RESULTS
See Table 1 for demographic characteristics, handedness,
positions played, reported number of loss of consciousness
data, incidence of depression, and BMI. See
Table 2 for neuropsychological test results. The results
of the MicroCog Assessment of Cognitive Functioning
revealed that players scored in the bottom half of the
percentile placements on all measures except spatial
processing and reaction time, which were both in the
top half of the percentile placements. This was true for
both Caucasians and African American players, although
African Americans scored lower on all measures
as a group.
Figure 1 and Figure 2 show differences between NFL
players and the healthy comparison subjects on SPECT,
using age as a nuisance covariate. No areas of increased
perfusion were seen. There were global decreases
across the whole brain, especially in the prefrontal, temporal,
parietal, and occipital lobes, anterior and posterior
cingulate gyrus, and cerebellum. The decreases
were significant at p0.0001 family wise error corrected
for multiple comparisons. The Brodmann’s areas that
showed these decreases are listed in Table 3. When we
felt Brodmann’s areas were insufficient we also used
areas defined by the Automated Anatomical Labeling
Atlas.
Because African Americans are higher in our sample
than in the general population, and also because our
healthy comparison group did not have an adequate
number of African American males, we performed another
analysis using only Caucasian players (60) versus
Caucasian comparison subjects.16 The results were essentially
the same, showing global decreases at p0.001
family wise error and no increases.
We also performed two additional analyses on our
data. First, we examined players who reported a high
number of loss of consciousness episodes (three or
more) versus players who reported no loss of consciousness
episodes. The total group size was 32 with
high loss of consciousness and 32 with no loss of consciousness.
The analysis yielded no significant differences
with family wise error multiple comparisons corrections.
Without multiple comparisons corrections at
p0.01 there were several areas of increased activity in
the lateral prefrontal cortices and areas of decreased
perfusion in the temporal, parietal and occipital lobes in
the high loss of consciousness group. In the second
additional analysis we examined players who played a
high number of professional games (200) versus those
who played a relatively low number of professional
games (50). Twenty-six players in our study played 50
or fewer games, while 10 players played 200 or more
games. Again, no significant differences survived family
wise error corrections for multiple comparisons, but
there were significant decreases in the 200 games
group compared to the 50 group without corrections
for multiple comparisons at p0.001 in the prefrontal
cortex, temporal, parietal, and occipital lobes and in the
cerebellum.
The qEEG findings were consistent with the SPECT
findings and showed significantly elevated slow waves
in the bilateral temporal regions, bilateral frontal lobes,
and reduced power at the higher frequencies. Due to
the brain-bone interface, focal deviations from healthy
comparison subjects in the frontal and temporal lobes
are a common qEEG finding in TBI patients.28,29 In
addition, changes in the conduction velocities and network
synchrony between different brain regions were
deviant from normal relative to a group of healthy comparison
subjects. A more detailed analysis of qEEG connectivity
measures is in preparation for a future publication.
TABLE 2. Neuropsychological Assessment Results of *97 Retired
Players
Conners’s Continuous Performance Test II
50% greater chance of having
ADHD based on CCPT II
81
Mild Cognitive Impairment
Screen by Age Group Abnormal/Total N %
75–82 4/4 100
65–74 8/22 36
50–65 6/52 12
25–49 1/22 4.5
MicroCog Percentile Scores Mean SD
General cognitive functioning 33.3 25.5
General cognitive proficiency 27.6 23.2
Processing speed 33.3 26.0
Processing accuracy 41.2 26.8
Attention 40.8 26.3
Reasoning 34.4 27.5
Memory 36.5 28.7
Spatial processing 68.0 21.9
Reaction time 70.2 24.5
*Due to physical ailments or advanced dementia, three players
were unable to complete the tests.
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T2
F1,2
T3
CONCLUSION
Omalu et al.30,31 and McKee et al.32 have reported finding
excess tau protein deposits at autopsy (called
chronic traumatic encephalopathy or CTE) in a number
of deceased retired professional football players. Ours
is the first study using multiple brain imaging methods
and neuropsychological testing to demonstrate significant
brain abnormalities in large group of living active
and retired professional football players.
On SPECT, significant decreases in regional cerebral
blood flow were seen across the whole brain, especially
in the prefrontal poles, temporal poles, occipital lobes,
anterior cingulate gyrus, and cerebellum. This pattern is
consistent with the persistent effects of traumatic brain
injuries.33 We also found significant decreases in the
posterior cingulate gyrus and hippocampus, areas implicated
in dementia.34
The Mild Cognitive Impairment Screen has been
found to be a reliable tool in distinguishing mild cognitive
impairment and dementia from normal, which is
an important issue in this population. In the general
population, the prevalence of mild cognitive impairment
or dementia under age 50 is typically small,
0.1%.35 In our sample, 4.5% of subjects in this age range
scored in the abnormal range on the Screen. The general
incidence of dementia between age 50 to 65 ranges from
0.3% to 2.2%; in our sample 12% in this age group had
FIGURE 1. Examples of Representative Horizontal, Coronal and Sagittal Slices Showing Global Brain SPECT Decreases in NFL Players
Versus Healthy Brain Subjects
Horizontal Slices (from superior to inferior)
Coronal Slices (from anterior to posterior)
Sagittal Slices (from right to left)
025 038 047 053
023 037 051 063
020 031 047 059
Blue equals areas of decreased perfusion in the NFL players versus healthy brain comparison subjects at p0.0001. Family wise error. No
increases were seen.
AMEN et al.
J Neuropsychiatry Clin Neurosci 23:1, Winter 2011 http://neuro.psychiatryonline.org 5
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abnormal Screen studies. The general incidence of dementia
at age 65 is 2.2% increasing to 6.5% at age 75. In
our sample 36% of players in this age range had an
abnormal Screen study. Over age 74 100% of players
had abnormal Screen scores.
On the Conners’ Continuous Performance test II, 80%
of the NFL group scored 50% or greater as having
“probable” ADHD. Imaging studies have shown that
an extensive brain network is activated during this task
including frontal, temporal, and occipital areas,36 all of
these areas showed significant decreases on the SPECT
scans. Some players did have childhood histories consistent
with ADHD, but at a much lower level.
Depression is associated with lower brain perfusion,
especially in the prefrontal cortices, and the group of
NFL players showed a significantly higher incidence of
depression (28%) than is found in the general population
(9.5%).37 Depression has also been associated with
brain injury.38 In addition, we found decreases in Brodmann’s
area 25, which has been reported in resistant
depression39 and suicide.40 The qEEG findings showed
focal frontal and temporal lobe deviations involving
brain regions that are vulnerable to rapid acceleration/
deceleration injuries.41,42
Other factors may be involved in these findings, including
past drug or alcohol abuse, depression, steroid abuse
and brain injuries outside of the NFL, such as from high
school or college sports or motor vehicle accidents. In
addition, a recent study showed that being overweight or
obese is associated with smaller brain volume.43 Fortyeight
percent of players had a BMI over 30, which is
associated with increased cardiovascular disease risk factors,
44 compared to 33% in the general adult population.45
It is also known that African-Americans in the United
States suffer disproportionally from disorders, such as
hypertension and diabetes, which are known to increase
risk for cardiovascular problems, including
strokes and vascular dementia. Since we had a high
African American population among our study subjects
and not an equivalent percentage of healthy comparison
subjects, we performed an additional SPECT analysis
comparing Caucasian players with Caucasian
healthy subjects and found the same basic pattern seen
for the total group comparisons.
In addition, our analysis comparing high versus low
loss of consciousness groups did not reveal further
brain decreases when subjected to multiple comparisons
corrections as hypothesized. One possible explanation
is that the decreased perfusion is a result of the
repetitive hits to the head, rather than single-episode
traumas. Also, the lack of additional results in our comparison
of high versus low games played suggests that
by the time players enter into professional football,
where they have usually already played for 8 years or
more at a high level, they may have already experienced
some problems in function. Screening players
upon entering the NFL may be an important step to
understanding this problem further.
There are a number of limitations to our study. The
sample may not be representative of all players, as subjects
needed to be able to travel to the study location and
have social contact that allowed them to learn about and
participate in the study. Players who were homeless, demented,
or of low income may have had a more difficult
time participating. Also, it is possible that players who
were more concerned about their memory or mood issues
were more inclined to volunteer. In addition, we were
FIGURE 2. 3D Surface Showing Global Brain SPECT Decreases
in NFL Players Versus Healthy Brain Subjects
Blue equals areas of decreased perfusion in the NFL players
versus HBS at p0.0001. Family wise error. No increases were
seen.
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unable to obtain the complete medical records on many of
our participants. The information on concussions and loss
of consciousness was based on player or family recall,
which may be subject to error.
The results of this study suggest that playing professional
football is associated with a significantly higher risk
for persistent brain damage. Further imaging studies, particularly
longitudinal in nature, and neuropsychological
assessments using larger, randomly selected groups, with
ethnic-matched normals is warranted, as well as studies to
evaluate prevention and rehabilitation strategies.
The authors wish to thank Anthony Davis, Marvin Smith,
Reggie Berry, Dave Pear, Robert Lee and all the retired
players for their assistance. In addition, we are grateful to
Christine Kraus, Ph.D., Steve Stockdale, Ph.D., William
Shankle, M.D., and Manuel Trujillo, M.D., for their consultation.
This study was approved and supervised by an institutional
review board, Alpha IRB.
Players were recruited with the help of the Los Angeles
Chapter of the Retired NFL Players Association, The Summit,
and Dave Pear’s Blog. No author reports a conflict of
interest or financial disclosure.
TABLE 3. Significant Areas of Decreased Perfusion in NFL Players Versus Healthy Comparison Subjects*
Brodmann/AAL Areas Cluster Size Location Z
BA9/46 Dorsal Lateral PFC Lt 1414 44 46 26 Inf
BA9/46 Dorsal Lateral PFC Rt 1019 50 28 18 7.81
BA10 Anterior PFC Lt 1211 14 48 24 Inf
BA10 Anterior PFC Rt 1204 14 58 4 7.67
BA11/12 Orbital PFC Lt 384 6 22 28 Inf
BA11/12 Orbital PFC Rt 206 8 22 28 Inf
BA44/45 Broca’s Area Lt 349 54 4 18 Inf
BA44/45 Broca’s Area Rt 233 48 24 10 Inf
BA47 Inferior Frontal Gyrus Lt 333 14 26 20 Inf
BA47 Inferior Frontal Gyrus Rt 484 14 22 30 Inf
BA24/32 Ant. Cingulate Lt 1099 8 40 6 7.33
BA24/32 Ant. Cingulate Rt 983 10 44 12 7.60
BA25 Subgenual Cingulate Lt 115 12 26 20 7.70
BA25 Subgenual Cingulate Rt 100 12 22 20 7.77
BA23/31 Posterior Cingulate Lt 301 14 54 12 6.73
BA23/31 Posterior Cingulate Rt 207 12 50 24 7.01
BA13/14 Insular Cortex Lt 498 40 16 8 6.65
BA13/14 Insular Cortex Rt 1114 26 22 14 7.18
Lentiform Left 463 22 4 12 6.26
Putamen Right 468 22 6 12 6.17
Olfactory Cortex Left 184 18 4 18 6.65
Olfactory Cortex Right 204 10 18 18 7.60
Amygdala Left 220 20 2 26 7.67
Amygdala Right 244 32 2 30 7.80
Hippocampus Left 321 20 4 26 7.63
Hippocampus Right 350 26 4 28 7.09
BA34/35/36 Parahippocampal Lt 591 20 6 30 7.80
BA34/35/36 Parahippocampal Rt 676 18 8 32 Inf
BA38 Temporal Pole Lt 1327 44 8 32 7.69
BA38 Temporal Pole Rt 1227 52 2 18 Inf
BA20/21/22 Sup/Mid/Inf Temp Lt 4543 56 46 22 Inf
BA20/21/22 Sup/Mid/Inf Temp Rt 4376 60 30 10 Inf
BA37 Fusiform Gyrus Lt 1314 40 68 18 6.96
BA37 Fusiform Gyrus Rt 1326 30 66 12 7.35
BA5/7 Parietal Lt 1373 48 54 36 Inf
BA5/7 Parietal Rt 282 50 52 38 Inf
BA39/40 Angular/Supramarginal Lt 1902 48 56 32 Inf
BA39/40 Angular/Supramarginal Rt 1679 58 32 32 7.69
BA17/18/19 Occipital Lobe Lt 1592 36 82 8 Inf
BA17/18/19 Occipital Lobe Rt 923 32 82 16 6.83
Calcarine/Cuneus/Lingual Lt 1148 14 54 12 6.73
Calcarine/Cuneus/Lingual Rt 1546 20 56 4 7.44
Cerebellum Left 2820 22 34 44 Inf
Cerebellum Right 3221 14 42 44 Inf
*SPM8. Corrected for multiple comparisons at p0.0001.
AMEN et al.
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