Regional rates of neocortical atrophy from
normal aging to early Alzheimer disease
C.R. McDonald, PhD
L.K. McEvoy, PhD
L. Gharapetian, BS
D.J. Hagler, Jr., PhD
D. Holland, PhD
A. Koyama, BS
J.B. Brewer, MD, PhD
A.M. Dale, PhD
For the Alzheimer’s
Objective: To evaluate the spatial pattern and regional rates of neocortical atrophy from normal
aging to early Alzheimer disease (AD).
Methods: Longitudinal MRI data were analyzed using high-throughput image analysis procedures
for 472 individuals diagnosed as normal, mild cognitive impairment (MCI), or AD. Participants
were divided into 4 groups based on Clinical Dementia Rating Sum of Boxes score (CDR-SB).
Annual atrophy rates were derived by calculating percent cortical volume loss between baseline
and 12-month scans. Repeated-measures analyses of covariance were used to evaluate group
differences in atrophy rates across regions as a function of impairment. Planned comparisons
were used to evaluate the change in atrophy rates across levels of disease severity.
Results: In patients with MCI–CDR-SB 0.5–1, annual atrophy rates were greatest in medial tem-
poral, middle and inferior lateral temporal, inferior parietal, and posterior cingulate. With in-
creased impairment (MCI–CDR-SB 1.5–2.5), atrophy spread to parietal, frontal, and lateral
occipital cortex, followed by anterior cingulate cortex. Analysis of regional trajectories revealed
increasing rates of atrophy across all neocortical regions with clinical impairment. However, in-
creases in atrophy rates were greater in early disease within medial temporal cortex, whereas
increases in atrophy rates were greater at later stages in prefrontal, parietal, posterior temporal,
parietal, and cingulate cortex.
Conclusions: Atrophy is not uniform across regions, nor does it follow a linear trajectory. Knowl-
edge of the spatial pattern and rate of decline across the spectrum from normal aging to Alzhei-
mer disease can provide valuable information for detecting early disease and monitoring
treatment effects at different stages of disease progression. Neurology®2009;73:457–465
AD ? Alzheimer disease; ADNI ? Alzheimer’s Disease Neuroimaging Initiative; ANCOVA ? analysis of covariance; CDR ?
Clinical Dementia Rating; CDR-SB ? Clinical Dementia Rating Sum of Boxes score; MCI ? mild cognitive impairment;
MMSE ? Mini-Mental State Examination; PI ? Principal Investigator; RM ? repeated-measures; ROI ? region of interest;
TIV ? total intracranial volume; UCSD ? University of California, San Diego.
Whole brain atrophy rates differ among normal aging individuals and those diagnosed with mild
the spatial pattern of neocortical atrophy associated with normal vs pathologic aging is not uniform
and may depend on the degree of disease severity.4However, few longitudinal studies are available
From the Department of Psychiatry (C.R.M., C.F.-N.), Multimodal Imaging Laboratory (C.R.M., L.K.M., L.G., C.F.-N., D.J.H., D.H., A.K.,
J.B.B., A.M.D.), Department of Radiology (L.K.M., D.J.H., D.H., J.B.B., A.M.D.), and Department of Neurosciences (J.B.B., A.M.D.), University
of California, San Diego, CA.
Supported by a grant (U24 RR021382) to the Morphometry Biomedical Informatics Research Network (http://www.nbirn.net) that is funded by the
National Center for Research Resources at the National Institutes of Health, USA. Data collection and sharing for this project was funded by the Alzheimer’s
Disease Neuroimaging Initiative (ADNI; Principal Investigator: Michael Weiner; NIH grant U01 AG024904). ADNI is funded by the National Institute
on Aging, by the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Pfizer Inc.,
Wyeth Research, Bristol-Myers Squibb, Eli Lilly and Company, GlaxoSmithKline, Merck & Co. Inc., AstraZeneca AB, Novartis Pharmaceuticals
Corporation, Alzheimer’s Association, Eisai Global Clinical Development, Elan Corporation plc, Forest Laboratories, and the Institute for the Study
of Aging, with participation from the US Food and Drug Administration. Industry partnerships are coordinated through the Foundation for the
National Institutes of Health. The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated
by the Alzheimer’s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory of Neuro
Imaging at the University of California, Los Angeles.
Disclosure: Author disclosures are provided at the end of the article.
Address correspondence and
reprint requests to Dr. Carrie R.
McDonald, Multimodal Imaging
Laboratory, Suite C101, 8950
Villa La Jolla Dr., La Jolla, CA
Copyright © 2009 by AAN Enterprises, Inc.
that describe regional atrophy rates and changes
normal aging to early AD.5-7
We examined longitudinal rates of regional
neocortical atrophy over 1 year in 137 healthy
controls and 335 individuals at different stages
of clinical impairment. Annual atrophy rates
were of interest because they have demonstrated
high sensitivity to subtle brain changes in AD
and may discriminate between diagnostic
groups better than baseline brain measures.1
Furthermore, we used cross-sectional data to es-
timate the change in atrophy rates with increas-
ing levels of disease. Change in atrophy rates
cacy of disease-modifying therapeutics.5,8We
would be observed in prefrontal and parietal re-
gions with relative sparing of posterior neocor-
tex. Conversely, we predicted that in patients
with mild MCI, atrophy rates would be greatest
in medial temporal lobe regions and would
spread to other cortical regions along a
posterior-to-anterior gradient with increasing
levels of clinical impairment. The longitudinal
and cross-sectional MRI data reported in this
study provide a qualitative and quantitative de-
piction of regional brain changes that accom-
pany normal aging and progression from
prodromal to early AD.
METHODS Alzheimer’s Disease Neuroimaging Ini-
tiative. Data used in the preparation of this article were obtained
from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) da-
tabase (www.loni.ucla.edu/ADNI). The ADNI was launched in
2003 by the National Institute on Aging, the National Institute of
Biomedical Imaging and Bioengineering, the Food and Drug Ad-
nizations, as a $60 million, 5-year public–private partnership.
ADNI’s goal is to test whether serial MRI, PET, other biologic
markers, and clinical and neuropsychological assessment can be
mination of sensitive and specific markers of very early AD progres-
sion is intended to aid researchers and clinicians to develop new
treatments and monitor their effectiveness, as well as lessen the time
and cost of clinical trials.
The principal investigator of this initiative is Michael W.
Weiner, MD, VA Medical Center and University of California,
San Francisco. ADNI is the result of efforts of many coinvestiga-
tors from a broad range of academic institutions and private
corporations. Subjects have been recruited from more than 50
sites across the United States and Canada (www.adni-info.org).
Standard protocol approvals, registrations, and patient
consents. This study was approved by an ethical standards
committee on human experimentation at each institution. Writ-
ten informed consent was obtained from all patients or autho-
rized representatives participating in the study.
Participants. ADNI eligibility criteria are described at http://
view&id?9&Itemid?43). Briefly, subjects are aged 55–90
years and have a study partner able to provide an independent
evaluation of functioning. Control subjects have a Mini-Mental
State Examination (MMSE) score between 24 and 30 (inclusive)
and a global Clinical Dementia Rating (CDR) of 0. Subjects
with MCI have MMSE scores between 24 and 30, a subjective
memory symptom, objective memory loss measured by
education-adjusted scores on Wechsler Memory Scale Logical
Memory II, a global CDR of 0.5, preserved activities of daily
living, and an absence of dementia. Subjects with mild AD have
MMSE scores between 20 and 26, have a global CDR of 0.5 or
1.0, and meet National Institute of Neurological and Communi-
cative Disorders and Stroke–Alzheimer’s Disease and Related
Disorders Association criteria for probable AD.9
In this study, MRI data were included on all ADNI subjects
for whom baseline and 12-month MRI scans were available and
had passed local quality inspection by December 2008. To esti-
mate the level of clinical impairment, the CDR Sum of Boxes
score (CDR-SB) was calculated at baseline for all participants.
This score has been described as a useful and reliable measure for
detecting subtle clinical change, ideal for use in longitudinal as-
sessments of dementia.10The CDR-SB score was used to divide
the study sample into groups reflecting degree of impairment.
From highest to lowest, our initial sample included 151 individ-
uals with a CDR-SB ? 0 (normal controls), 105 with a CDR-SB
0.5–1.0, 126 with a CDR-SB 1.5–2.5, and 104 with a CDR-SB
?2.5 (mild AD). Because we wished to compare atrophy rates in
normal aging with those across different patient groups, individ-
uals in the normal group who progressed to a CDR-SB of 0.5 or
group demographics are presented in table 1. Information on
CDR-SB progression of individual participants over the course of 1
year is included in table e-1 on the Neurology®Web site at www.
neurology.org. Groups did not differ in age [F(3,471) ? 1.9, p ?
0.05] or sex distribution [?2(3) ? 0.28, p ? 0.05]. The groups did
CDR-SB ? 0 obtained a higher level of education relative to those
with a CDR-SB ?2.5.
Procedures. Dual 3-dimensional T1-weighted volumes were
downloaded from the public ADNI database (http://www.
loni.ucla.edu/ADNI/Data/index.shtml). All image processing
and analyses occurred at the Multimodal Imaging Laboratory,
University of California, San Diego. Images were corrected for
gradient nonlinearities11and intensity nonuniformity12using
methods developed within the NIH/National Center for
Research Resources–sponsored Morphometry Biomedical In-
formatics Research Network (http://www.nbirn.net/). The
T1-weighted images were aligned, averaged to improve signal-
to-noise ratio, and resampled to isotropic 1-mm voxels. Methods
based on FreeSurfer 3.02 software were used to obtain cortical
gray matter volume and thickness measures in distinct regions of
interest (ROIs).13-18Baseline volumetric data were corrected for
differences in head size by regressing the estimated total intracra-
nial volume (TIV) from the data.19
Longitudinal analysis. For each subject, dual 3-dimensional
follow-up structural scans were rigid-body aligned, averaged, and
affine aligned to the subject’s baseline. A deformation field was
calculated from nonlinear registration according to Holland et
Neurology 73 August 11, 2009
al.20in a manner related to that of Ashburner and Friston21and
Christensen et al.22and then used to align scans at the subvoxel
level. The follow-up aligned image undergoes skull stripping and
subcortical segmentation, with labels applied from the baseline
scan. For cortical reconstruction, surface coordinates for the
white and pial boundaries were derived from the baseline images
and mapped onto the follow-up images using the deformation
field. Parcellation and labeling17from the baseline image was
then applied to the follow-up image. This results in a 1:1 corre-
spondence between each vertex in the base image and in the
12-month image. This method produces an estimate of the an-
nual percent cortical volume loss at each vertex and within each
ROI. Atrophy rates in this study were defined as the percent
cortical volume loss over the course of 1 year. These atrophy
rates represent the within-subject change over time and are inde-
pendent of group differences in baseline measurements (e.g.,
Statistical analyses. To examine whether the rate of neocor-
tical loss varies across regions as a function of degree of im-
pairment, a repeated-measures (RM) analysis of covariance
(ANCOVA) was performed with CDR-SB group as a
between-subject variable and hemisphere (left vs right) and
rate of lobar atrophy (lateral temporal, medial temporal, pari-
etal, frontal, cingulate, occipital, and primary sensory) as
within-subjects variables. Age and sex were entered as covariates
in each model. The primary analyses of interest were 1) whether
there was a main effect of CDR-SB group, indicating that atro-
phy rate varies with level of impairment, and 2) whether there
was an interaction between CDR-SB group and region or hemi-
sphere, indicating different spatial patterns of atrophy across lev-
els of impairment. When significant group effects were observed
for a lobar region, univariate analyses were performed within
smaller ROIs using a threshold of p ? 0.001. Because of evi-
dence that whole brain atrophy rates do not appear constant over
the course of disease,5changes in regional atrophy rates were
evaluated by performing independent t tests on the difference in
atrophy rates (i.e., slope of the lines) between the normal control
group and MCI patients with CDR-SB 0.5–1 vs the difference
in atrophy rates between MCI patients with CDR-SB 1.5–2.5
and early AD. Greater atrophy rates early relative to late in dis-
ease were defined as a steeper slope between the normal and
MCI–CDR-SB 0.5–1 groups, whereas greater atrophy rates later
relative to early in disease defined as a steeper slope between the
MCI–CDR-SB 1.5–2.5 and early AD groups.
RESULTS Continuous surface maps of cortical vol-
ume loss as a function of disease severity demonstrate
that cortical atrophy over 12 months is minimal in
the normal control group (figure 1). In MCI patients
with CDR-SB 0.5–1, cortical loss appears most
prominent in medial and lateral temporal and infe-
rior parietal cortex, spreading to widespread frontal
regions as impairment increases to early AD.
ROI analysis. The RM ANCOVA for lobar regions
revealed a main effect of region [F(6, 1,892) ?
15.4, p ? 0.001], a main effect of group
[F(3,466) ? 45.4, p ? 0.001], and a region-by-
group interaction [F(18, 1,892) ? 23.4, p ?
0.001]. There was no main effect of hemisphere
[F(1,466) ? 3.0, p ? 0.067], nor was there a
group-by-hemisphere interaction [F(3,466) ?
1.6, p ? 0.181]. Therefore, follow-up analyses
were collapsed across right and left hemisphere
values. Univariate ANCOVAs revealed group dif-
ferences across all lobar regions. Follow-up compari-
sons were performed within each ROI between
normal controls and each patient group (table 2).
Atrophy rates in all ROIs for the 4 groups can be seen
in figure 2.
Normal vs MCI–CDR-SB 0.5–1. Relative to normal
controls, MCI patients with CDR-SB 0.5–1 showed
Table 1Demographic characteristics of the control and patient groups
(CDR-S ? 0)
(CDR-SB ? 0.5–1.0)
(CDR-SB ? 1.5–2.5)
No. of participants
137105 126 104
76.1 (5.1) 75.9 (6.7)74.7 (6.9)74.3 (8.0)
76:61, 56.0% male62:43, 58.0% male74:52, 55.7% male58:46, 55.8% male
16.2 (2.9) 15.8 (2.9)15.9 (2.9) 15.1 (3.0)
29.1 (1.1) 27.5 (1.8)26.7 (1.8)23.0 (2.2)
% of total
28% 37%48% 49%
% of total
Group means are provided, with standard deviations in parentheses.
CDR-SB ? Clinical Dementia Rating Sum of Boxes score; MCI ? mild cognitive impairment; AD ? Alzheimer disease;
MMSE ? Mini-Mental State Examination.
Neurology 73August 11, 2009
a greater rate of atrophy across all medial temporal
lobe regions, inferior and middle temporal gyri, infe-
rior parietal lobule, precuneus, and posterior cingu-
late. Atrophy rates were not increased in frontal,
occipital, or sensory regions relative to controls.
Normal vs MCI–CDR-SB 1.5–2.5. In addition to the
regions described above, MCI patients with
CDR-SB 1.5–2.5 showed an increased rate of atro-
phy within the superior temporal gyrus, as well as
lateral orbitofrontal, rostral and caudal middle fron-
tal, frontal operculum, and superior frontal gyrus
compared with controls. In addition, atrophy in all
parietal regions and the lingual and lateral occipital
regions progressed at a faster rate.
Normal vs early AD. Relative to normal controls,
those with mild AD showed a faster rate of atrophy
across all temporal, frontal, cingulate, and occipital
regions. Greater atrophy rates were also seen within
precentral and postcentral gyri with relative sparing
of pericalcarine regions.
Changes in regional atrophy rates across levels of dis-
ease severity. Although atrophy rates increased
throughout the neocortex with increasing disease se-
verity (table 2), the rate of increase across levels of
impairment was not constant within all regions. As
shown in figure 3, increases in atrophy rates were
greater between controls and those with MCI–
CDR-SB 0.5–1 within medial temporal lobe regions
(t 471 ? 2.01, p ? 0.05), including entorhinal (t
471 ? 4.69, p ? 0.01) and fusiform (t 471 ? 2.67,
p ? 0.01) cortex. This effect did not reach signifi-
cance in parahippocampal cortex (t 471 ? 0.95, p ?
Figure 1Annual atrophy rates as a function of degree of clinical impairment
Annual atrophy rates as a function of degree of clinical impairment (i.e., baseline Clinical Dementia Rating Sum of Boxes
score [CDR-SB]). Mean atrophy rates are represented as a percent change in neocortical volume and mapped onto the
lateral (left), ventral (middle), and medial (right) pial surface of the left hemisphere. These data demonstrate that atrophy
rates are most prominent in posterior brain regions early in the course of disease, spreading to anterior regions as the level
of impairment increases, with relative sparing of sensorimotor regions. MCI ? mild cognitive impairment; AD ? Alzheimer
Neurology 73August 11, 2009
0.05), hippocampus (t 471 ? 0.96, p ? 0.05), or the
temporal pole (t 471 ? 1.17, p ? 0.05). Conversely,
increases in atrophy rates were greater between those
with MCI–CDR-SB 1.5–2.5 and early AD within
frontal (t 471 ? 2.17, p ? 0.05), parietal (t 471 ?
3.34, p ? 0.01), anterior cingulate (t 471 ? 3.5, p ?
0.01), and posterior cingulate (t 473 ? 3.10, p ?
0.01) cortex. No differences in early vs late changes
in atrophy rates were observed in the occipital (t
471 ? 0.87, p ? 0.05), lateral temporal (t 471 ?
1.69, p ? 0.05), or hippocampal (t 471 ? 0.229,
p ? 0.05) regions. Whereas occipital regions showed
minimal change across groups, atrophy rates within
the lateral temporal lobe and hippocampus appeared
constant across levels of disease severity.
DISCUSSION Longitudinal MRI analysis from our
large cohort of normal controls, individuals with
MCI, and individuals with AD provides strong evi-
dence that neocortical atrophy rates are not uniform
Table 2One-year atrophy rates in the control and patient groups
(CDR-SB ? 0)
(CDR-SB ? 0.5–1.0)
(CDR-SB ? 1.5–2.5)
0.10 (0.70)0.11 (0.79)0.01 (0.81)
0.09 (0.62)0.10 (0.70)
Rates are provided as percentages, with standard deviations in parentheses.
Group mean is significantly different from the control mean at *p ? 0.001, †p ? 0.0001, ‡p ? 0.00001.
CDR-SB ? Clinical Dementia Rating Sum of Boxes score; MCI ? mild cognitive impairment; AD ? Alzheimer disease.
Neurology 73August 11, 2009
across the cortical mantle, nor are changes in atrophy
rates constant in many regions with increased level of
clinical impairment. We demonstrate a pattern of at-
rophy in MCI–CDR-SB 0.5–1 that begins in medial
and inferolateral temporal, inferior parietal, and pos-
terior cingulate and spreads to encompass superior
parietal, widespread prefrontal, and lateral occipital
cortex with progression to MCI–CDR-SB 1.5–2.5.
In patients with mild AD, atrophy rates are greater in
all cortical regions with the exception of primary vi-
sual and auditory cortex relative to age-matched con-
trols. These data support our primary hypothesis and
are consistent with previous findings that atrophy in
MCI and AD progresses along a posterior-to-anterior
gradient with relative sparing of sensory regions.4,23,24
However, regional atrophy rates do not always
progress in a linear manner. Whereas increases in at-
rophy rates were greatest between controls and those
with MCI–CDR-SB 0.5–1 within most medial tem-
poral regions and plateaued slightly between those
with MCI–CDR-SB 1.5–2.5 and early AD, increases
in atrophy rates within the hippocampus and lateral
temporal neocortex did not differ across levels of im-
pairment. Conversely, increases in atrophy rates
within most prefrontal, parietal, and anterior cingu-
late regions were modest between controls and pa-
tients with MCI–CDR-SB 0.5–1, but the degree of
increase was greater as disease severity increased.
Therefore, although atrophy rates increased through-
out the neocortex with disease severity, the rate of
increase differed across regions and level of clinical
impairment. A few longitudinal studies have shown
acceleration in whole brain, ventricular, and hip-
pocampal atrophy rates with disease progression.5-7
Our cross-sectional findings are in line with other
studies suggesting that hippocampal atrophy rates in-
crease linearly with level of disease severity.25Such
discrepancies in the literature may reflect method-
Figure 2 Annual neocortical atrophy rates in regions of interest
Graphs depicting annual neocortical atrophy rates (percent volume change) in regions of interest in the normal control, mild cognitive impairment (MCI)–
Clinical Dementia Rating Sum of Boxes score (CDR-SB) 0.5–1, MCI–CDR-SB 1.5–2.5, and early Alzheimer disease (AD) groups.
Neurology 73 August 11, 2009
ologic differences in hippocampal measurements,
variability in MRI scanning intervals, and/or differ-
ences in study design and patient cohorts (i.e., accel-
eration of hippocampal atrophy rates has been shown
in familial AD).7Nevertheless, our findings extend
the literature by revealing that observed increases in
atrophy rates vary by neocortical region and level of
Understanding the different spatial patterns and
regional trajectories of neocortical loss that accom-
pany various stages of disease can provide critical in-
formation for early detection of disease, as well as
response to treatment. Whereas atrophy rates within
medial temporal lobe regions seem to be the earliest
indicator of mild disease, atrophy rates within ante-
rior and posterior association cortex may help to de-
termine treatment efficacy with respect to slowing
disease progression and cognitive decline. Such lon-
gitudinal data will be particularly important for stud-
ies of disease-modifying treatments because each
subject serves as his or her own control, allowing dis-
ease progression to be assessed directly through re-
peat evaluations. When monitoring response to
treatment, our data suggest that the cortical areas tar-
geted will depend on where patients reside along the
disease spectrum. Slowing of entorhinal atrophy rates
in patients with mild impairment may represent a
true treatment effect, whereas later in the disease it
may reflect the natural course of disease progression.
Similarly, a steady rate of decline in prefrontal re-
gions in patients with greater impairment may reflect
a strong response to treatment because increases in
atrophy rates would be expected with conversion to
early AD. These patterns should be carefully consid-
ered in studies that select MRI biomarkers as primary
or secondary outcome measures because overlooking
the natural history of disease progression could result
in overestimation or underestimation of treatment
effects. High-throughput image analysis procedures,
such as the ones used in this study, would be particu-
larly useful and cost-effective in large-scale clinical
trials designed to measure treatment effects in hun-
dreds of individuals, within multiple regions of inter-
est, and over several time points.
Despite support for our hypothesis of the spatial
distribution of changes observed in our patient
groups, the pattern of atrophy in our control group
did not support our hypothesis of greater atrophy
rates in prefrontal and parietal regions relative to pos-
terior association cortex. Rather, we found 1-year at-
rophy rates to be relatively small and of similar
magnitude across frontal, parietal, and temporal lobe
regions. Although these data initially appear at odds
with existing literature, they are commensurate with
other studies showing minimal, diffuse cortical atro-
phy over a 1- to 2-year period in healthy individuals
aged 59–85 years.4,26,27Therefore, it is possible that
with a longer time interval, the predicted anterior-to-
posterior gradient of atrophy frequently observed in
normal aging would have emerged. Additional in-
sights into patterns of normal age-related atrophy
will be critical to the interpretation of pathologic pat-
terns of aging.
Despite the potential clinical value of our find-
ings, there are limitations of this study that should be
noted. First, longitudinal follow-up was limited to 1
year. Therefore, our longitudinal data were supple-
mented with cross-sectional analysis to investigate
the change in atrophy rates across levels of clinical
Figure 3 Corticalsurfacemapsrepresentingthe
mentia Rating Sum of Boxes score [CDR-SB] 0.5–1 ? normal)
in the course of disease projected onto the left pial surface.
Positive values (red) represent cortical regions showing
early ? late increases in atrophy rates (i.e., areas in which the
difference in atrophy rates between controls and patients
with MCI–CDR-SB 0.5–1 was greater than that between pa-
ative values (blue) represent cortical areas showing late ?
early increases in atrophy rates (i.e., areas in which the differ-
ence in atrophy rates between patients with MCI–CDR-SB
tients with MCI–CDR-SB 0.5–1). Areas showing no difference
Neurology 73August 11, 2009
impairment. Longitudinal studies that follow the
same individuals for 5 to 10 years will provide a more
definitive analysis of the pattern of atrophy (i.e., re-
gional acceleration) associated with disease progres-
sion. Long-term follow-up is particularly important
for individuals diagnosed with MCI because of the
heterogeneity within MCI and the uncertainty as to
what this group truly represents. Second, we do not
currently have histologic verification of disease.
Therefore, it is possible that some subjects have dis-
orders other than AD, or have comorbid pathology
that was notdetectedwithourinvivomeasures.Taken
together, these data provide additional insight into the
complex patterns and rates of neocortical atrophy that
information may aid in the selection of biomarkers for
future clinical trials designed to evaluate the effect of
Statistical analysis was performed by Carrie McDonald, PhD. Dr. Mc-
Donald is a clinical neuropsychologist and an Assistant Professor of Psy-
chiatry at the University of California, San Diego. She has doctoral level
training in multivariate statistics and structural equation modeling.
Data used in the preparation of this article were obtained from the Alzhei-
mer’s Disease Neuroimaging Initiative (ADNI) database (www.loni.
ucla.edu/ADNI). As such, the investigators within the ADNI contributed
to the design and implementation of ADNI and/or provided data but did
not participate in analysis or writing of this report. Complete listing of
ADNI investigators available at http://www.loni.ucla.edu/ADNI/Data/
ADNI_Authorship_List.pdf. The authors thank Robin Jennings, Michele
Perry, Chris Pung, and Elaine Wu for downloading and preprocessing the
Dr. McDonald receives research support from the NIH [NS056091
(Principal Investigator [PI])]. Dr. McEvoy receives research support from
the NIH [K01 AG029218 (PI), R01AG031224 (Coinvestigator), and
U24 RR021382 (Coinvestigator)], from the HIV Neurobehavioral Re-
search Center, University of California, San Diego (UCSD) (PI), and
from the Stein Institute for Research on Aging, UCSD (PI). An imme-
diate family member serves as President of and holds stock and stock
options in Cortechs Labs, Inc. and receives research support from the
NIH [5R43NS061023 (PI) and 1R43NS061023 (PI)]. Ms. Gharape-
tian reports no disclosures. Dr. Fennema-Notestine receives research
support from the NIH [U24 RR21382 (Coinvestigator), U24
RR021992 (Coinvestigator), U24 RR019701 (Coinvestigator), P30
MH062512 (Coinvestigator), N01 MH22005 (Coinvestigator, PI Im-
aging Core), R01 MH079752 (Coinvestigator), R01 AG031224
(Coinvestigator), R01 AG024506 (Coinvestigator)], and from the De-
partment of Veterans Affairs (Medical Research Service grant).
Dr. Hagler receives research support from the NIH [MH079146-01A2
(PI), 2R01 NS018741-23A1 (Coinvestigator), U54 NS056883-01
(Coinvestigator), and 5K01MH079146-02 (PI)] and has applied for a
patent for an automated method for labeling white matter fibers from
MRI (2008, details pending). Dr. Holland receives research support
from the NIH [7R01AG022381-03 (Programmer Analyst) and
1U01AG024904-02 (Programmer Analyst)]. Mr. Koyama reports no
disclosures. Dr. Brewer receives research support from the NIH [K23
NS050305 (PI)]. Dr. Dale receives research support from the NIH
[2P50NS022343-21A2 (Coinvestigator), 1R01AG031224 (PI),
1U01AG024904-02 (Subcontract PI), 5 U24 RR021382-04 (Subcon-
tract PI), 1R01MH079752-01 (Coinvestigator), 2 RO1 NS18741-
23A1 (Coinvestigator), and 1P50MH081755-01 (Coinvestigator)];
receives funding to his laboratory from General Electric Medical Sys-
tems as part of a Master Research Agreement with UCSD; and is a
founder of, holds equity in, and serves on the scientific advisory board
for CorTechs Labs, Inc. The terms of this arrangement have been
reviewed and approved by UCSD in accordance with its conflict of
Received February 6, 2009. Accepted in final form May 1, 2009.
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