Cerebral Cortex August 2012;22:1813– 1823
doi:10.1093/cercor/bhr255
Advance Access publication September 23, 2011
Ab Deposition in Aging Is Associated with Increases in Brain Activation during
Successful Memory Encoding
Elizabeth C. Mormino1, Michael G. Brandel1, Cindee M. Madison1, Shawn Marks1, Suzanne L. Baker2 and William J. Jagust1,2
1
Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA and 2Life Sciences Division,
Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Address correspondence to Elizabeth C. Mormino, Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, MC#3190, Berkeley,
CA 94720, USA. Email: [email protected].
To investigate early effects of beta-amyloid (Ab) on neuronal
function, elderly normal controls (NCs, age range 58--97) were
scanned with Pittsburgh Compound-B (PIB) positron emission
tomography (a measure of Ab) as well as functional magnetic
resonance imaging (a measure of brain activation) while performing
an episodic memory--encoding task of natural scenes (also
performed by young NCs; age range 18--30). Relationships between
Ab and activation were assessed across task-positive (regions that
activate for subsequently remembered vs. forgotten scenes) and
task-negative regions (regions that deactivate for subsequently
remembered vs. forgotten scenes). Significant task-related activation was present in a distributed network spanning ventrolateral
prefrontal, lateral occipital, lateral parietal, posterior inferior
temporal cortices, and the right parahippocampal/hippocampus,
whereas deactivation was present in many default mode network
regions (posteromedial, medial prefrontal, and lateral temporoparietal cortices). Task-positive activation was higher in PIB1
compared with PIB2 subjects, and this activation was positively
correlated with memory measures in PIB1 subjects. Although task
deactivation was not impaired in PIB1 NCs, deactivation was
reduced in old versus young subjects and was correlated with
worse task memory performance among old subjects. Overall,
these results suggest that heightened activation during episodic
memory encoding is present in NC elderly subjects with high Ab.
Keywords: aging, Alzheimer’s disease, beta-amyloid, episodic memory,
fMRI, PIB-PET
Introduction
Although beta-amyloid (Ab) plaques may play a role in the
etiology of Alzheimer’s disease (AD) (Hardy and Selkoe 2002;
Walsh and Selkoe 2007), this pathology is commonly observed
in the brains of elderly normal control (NC) individuals at
postmortem examination (Bennett et al. 2006; Kok et al. 2009;
Savva et al. 2009). Similar findings have been revealed with in
vivo imaging using positron emission tomography (PET) and
Pittsburgh Compound-B (PIB), a ligand capable of quantifying
fibrillar Ab plaque burden (Morris et al. 2010; Rowe et al. 2010).
This may reflect the earliest stage in AD development, with
a possible 10-year delay between initial Ab deposition and
dementia onset (Sperling et al. 2011). This idea is supported by
subtle ‘‘AD-like’’ changes in NCs with high Ab burden, such as
brain atrophy (Dickerson et al. 2009; Mormino et al. 2009;
Storandt et al. 2009; Chetelat et al. 2010; Oh et al. 2010; Becker
et al. 2011) and cognitive decline (Morris et al. 2009;
Villemagne et al. 2011). However, some evidence suggests that
cognitive reserve processes may modify the relationship
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between Ab and detrimental downstream effects (Fotenos
et al. 2008; Kemppainen et al. 2008; Rentz et al. 2010). These
factors might enable individuals to cope with this pathology
(Stern 2006) or at least prolong the delay period between
pathological insult and cognitive impairment (Jack et al. 2010).
Many functional magnetic resonance imaging (fMRI) studies
have revealed that increased activation in aging (Cabeza et al.
2002; Rosen et al. 2002; Park and Reuter-Lorenz 2009; de
Chastelaine et al. 2011) as well as in populations at risk for
developing AD (Bookheimer et al. 2000; Dickerson et al. 2005;
Trivedi et al. 2008). These findings are often interpreted as
a compensatory response to pathology, suggesting a neural
basis of cognitive reserve processes. It is also possible that
activation increases are detrimental, reflecting reduced neural
efficiency and/or dedifferientation (Logan et al. 2002; Li et al.
2006). Distinction between beneficial versus detrimental processes is often addressed by isolating activation during
successful events as well as by examining relationships with
measures of overall memory performance.
To investigate the role of these processes during early Ab
deposition, elderly subjects underwent PIB-PET imaging as well
as fMRI during incidental encoding of outdoor scenes. A group
of younger control subjects also participated in the fMRI
experiment. The event-related fMRI design enabled isolation of
‘‘subsequent memory effects’’ or activation during successfully
encoded scenes. Additionally, deactivations (greater deactivation for subsequently remembered vs. forgotten scenes) are
typically present in the ‘‘default mode network’’ (DMN),
specifically posteromedial, medial prefrontal, and lateral temporoparietal cortices (Daselaar et al. 2004). Although previous
work has not emphasized relationships between Ab and taskpositive activation, disruption of the DMN in NCs with high Ab
burden has been reported both at rest (Hedden et al. 2009;
Sheline et al. 2009; Mormino et al. 2011) and during episodic
memory encoding (Sperling et al. 2009; Vannini et al. 2011). To
this end, the aim of the current study was to explore
relationships between Ab burden, activation, deactivation, and
cognition in elderly NC subjects.
Materials and Methods
Subject Recruitment
Fifty elderly NC subjects underwent PIB-PET imaging and fMRI for this
study, and 17 young NC subjects underwent fMRI. Eligibility requirements
for all NC subjects were no MRI contradictions, living independently in
the community, Mini-Mental State Examination (MMSE) > 26, normal
performance on cognitive tests, absence of neurological or psychiatric
illness, and lack of major medical illnesses and medications that affect
cognition. Five elderly subjects and 2 young were excluded due to
insufficient trials of high-confidence hits ( <20, N = 3), problems with
data acquisition (N = 1), excessive motion (N = 2), and memory
performance at chance levels (N = 1), resulting in a total number of 45
old and 15 young NC subjects for data analysis.
Neuropsychological Testing
Thirty-nine old NC subjects underwent a detailed cognitive testing
battery. To reduce this data, a maximum-likelihood factor analysis with
varimax rotation was completed using data from a larger cohort of 349
cognitively normal subjects (age range = 20--96, mean age = 58.2 (22.8),
mean MMSE = 29.0 (1.5), mean education = 16.8 (2.1), 133 males) who
underwent the same test protocol. The following measures were
entered into the factor analysis: mental control, verbal paired associates,
logical memory, and visual reproductions I and II from the Wechsler
Memory Scale-Revised (Wechsler 1987), digits forward/backward and
digit symbol tests from the Wechsler Adult Intelligence Scale-Revised,
recall sum across learning trials in the California verbal learning test
(Delis et al. 2000), Boston Naming Test (Kaplan et al. 1983), Trails B
minus A (Reitan 1958), FAS phonemic fluency (Lezak 1995), and total
correct in 60 s from the Stroop Interference test (Zec 1986). This
factor analysis revealed 5 factors fulfilling Kaiser’s criterion (eigenvalues
> 1) and were labeled according to the neuropsychological tests with
the highest factor loadings (episodic memory, executive function,
working memory, visual memory, and semantic memory; Table 1).
Thompson factor scores were estimated for each subject (Burt and
Thomson 1947) and used to compare cognition to PIB uptake and fMRI
activation within old subjects. For subjects that had undergone multiple
testing sessions, cognitive test scores closest to the PET scan date were
used in the factor analysis (mean delay between PET and closest testing
session was 4.4[3.0] months). The remaining 6 old subjects underwent
a different neuropsychological battery and were excluded from the
factor analysis due to intersession incompatibilities (however, neuropsychological testing for these subjects was used to ensure normality in
these subjects).
Apolipoprotein E Genotyping
DNA from blood samples for old NC subjects was analyzed for
apolipoprotein E (APOE) polymorphisms using a standard protocol.
For statistical comparison between groups, subjects were dichotomized into carriers and noncarriers of the E4 allele. Genotyping was
unavailable for 3 old NC subjects.
PIB-PET Acquisition
PIB was synthesized at the Lawrence Berkeley National Laboratory’s
(LBNL) Biomedical Isotope Facility using a published protocol and
described in detail previously (Mathis et al. 2003; Mormino et al. 2009).
PIB-PET imaging was performed at LBNL using an ECAT EXACT HR PET
scanner (Siemens Medical Systems, Erlangen, Germany) in 3D
acquisition mode. Ten to fifteen millicurie of PIB was injected into an
antecubital vein. Dynamic acquisition frames were obtained as follows:
4 3 15, 8 3 30, 9 3 60, 2 3 180, 8 3 300, and 3 3 600 s (90 min total).
Ten-minute transmission scans for attenuation correction were
obtained for each PIB scan. Filtered backprojected reconstructions
were performed on the transmission and emission data to judge
transmission alignment with each frame of emission data. In the case of
misalignment, the transmission image was coregistered to that individual emission frame and then forward projected to create an
attenuation correction file specific to that head position. PET data were
reconstructed using an ordered subset expectation maximization
algorithm with weighted attenuation. Images were smoothed with
a 4 mm Gaussian kernel with scatter correction.
MRI Acquisition
All subjects underwent MRI scanning at LBNL on a 1.5T Magnetom
Avanto System (Siemens Medical Systems) with a 12 channel head coil
run in triple mode. A high-resolution structural T1-weighted volumetric
magnetization prepared rapid gradient echo scan (MP-RAGE, axially
acquired, time repetition [TR]/time echo [TE]/time to inversion [TI] =
2110/3.58/1100 ms, flip angle = 15, 1.00 3 1.00 mm2 in plane
resolution, 1.00 mm thickness with 50% gap) and a low-resolution
structural T1-weighted in plane to the fMRI scans were collected
(axially acquired, TR/TE = 591/10 ms, flip angle = 150, 0.90 3 0.90
mm2 in plane resolution, 3.40 mm thickness with 15% gap). For fMRI
scanning, 4 T2 -weighted gradient-echo echo planar images (EPI) were
collected (28 axially acquired slices, TR/TE = 2200/50 ms, flip angle =
90, 3.40 3 3.40 mm2 in plane resolution, 3.40 mm thickness with 15%
gap).
Episodic Memory Paradigm
Two hundred outdoor images of natural outdoor scenes were
presented for 4.4 s each, and subjects were instructed to indicate
whether water was present at any point during the image’s presentation (collected over 4 EPI scans, with 50 scenes and 185 TRs per
EPI). Zero to 5 TRs of fixation (green crosshair on black background)
were randomly intermixed between scenes to allow separation of
individual trials (average interstimulus interval = 3.46 s (3.01); Dale
1999). A postscan surprise recognition task with all stimuli presented
during encoding as well as 100 foils was used to assess performance and
sort fMRI data (there was a 15-min delay between the last stimulus
encoded and the start of the postscan memory test). For each target
and foil, subjects were asked ‘‘Have you seen this image,’’ and allowed to
respond with 1 of 4 responses: high-confidence yes, low-confidence
yes, high-confidence no, and low-confidence no. This recognition task
was self-paced, and subjects were encouraged to be as accurate as
possible. Overall task memory performance was assessed with the
discriminability index d-prime, which uses signal detection theory to
compare recognition accuracy and false-positive rates. All lowconfidence responses were discarded to calculate d-prime values.
Table 1
Factor analysis factor loadings
WMS-R mental control
WMS-R verbal paired associates
WMS-R logical memory
WMS-R visual reproduction I
WMS-R visual reproduction II
WAIS-R digit span forward
WAIS-R digit span backward
WAIS-R digit symbol
CVLT 1--5 free recall
Boston naming test
Trails B minus A
FAS phonemic fluency
Stroop
Factor1/EM
Factor2/Exe
Factor3/WM
Factor4/VisMem
Factor5/SM
0.14
0.77
0.60
0.42
0.57
0.10
NA
0.47
0.67
NA
0.21
0.14
0.39
0.65
0.16
0.24
0.31
0.33
0.16
0.35
0.71
0.28
NA
20.44
0.39
0.62
0.20
NA
NA
0.12
NA
0.97
0.43
NA
0.13
NA
0.13
0.15
0.13
0.15
0.17
0.12
0.83
0.54
NA
NA
0.25
0.21
NA
0.19
NA
0.19
0.30
0.17
0.28
0.11
NA
0.11
0.33
0.13
NA
0.40
0.18
0.43
NA
Note: Factor loadings above 0.40 are bolded. NAs are indicated for loadings between 0.1 and þ0.1. Based on these loadings, factors were label as episodic memory (EM), executive function (Exe),
working memory (WM), visuospatial memory (VisMem), and semantic memory (SM). WMS-R, Wechsler Memory Scale-Revised; WAIS-R, Wechsler Adult Intelligence Scale-Revised; CVLT, California
verbal learning test; and NA, not applicable.
1814 Increased fMRI Activation and Ab in Aging
d
Mormino et al.
PIB-PET Processing
PIB-PET data were preprocessed using the SPM8 software package
(http://www.fil.ion.ucl.ac.uk/spm, last accessed 15 August 2011). Realigned PIB frames corresponding to the first 20 min of acquisition were
averaged and used to guide coregistration to the subject’s structural MRI
scan. Distribution volume ratios (DVRs) for PIB images were created
using Logan graphical analysis with frames corresponding to 35--90 min
postinjection and a gray matter masked cerebellum reference region
defined using FreeSurfer software (Logan et al. 1996; Lopresti et al. 2005).
Structural MRI Processing
MP-RAGE scans were processed as described previously (Mormino et al.
2009) using FreeSurfer version 4.5.0 (http://surfer.nmr.mgh.harvard.
edu/, last accessed 15 August 2011) to derive regions of interest (ROIs)
in each subject’s native space (Dale et al. 1999; Fischl et al. 2001, 2002;
Segonne et al. 2004). PIB index values were derived by averaging PIB
DVR values from prefrontal, cingulate, lateral temporal, and parietal ROIs.
Dichotomization into PIB+ and PIB– Groups
Older NC subjects were divided into PIB+ and PIB– groups based on
cutoff values defined using 11 young NC subjects who were scanned
with PIB-PET without evidence of PIB uptake and were therefore
presumably Ab-free (Kok et al. 2009; Braak and Del Tredici 2011).
Seven young subjects scanned with fMRI were part of this young group
(5 males, mean age = 24.5 (3.4), mean education = 16.2 (1.9)). The PIB
positive cutoff was defined as 2 standard deviations (SDs) above the
mean PIB index value across young subjects (mean = 1.04, SD = 0.02),
resulting in a value of 1.08 (Mormino et al. 2011).
fMRI Processing
fMRI data were processed using FSL version 4.1.6 (http://www.fmrib.
ox.ac.uk/fsl, last accessed 15 August 2011). Images were motion corrected,
highpass filtered (100 s), and smoothed with a 5 mm Gaussian kernel.
To define the spatial transformation from fMRI space to Montreal
Neurological Institute (MNI) template space, a multistep registration
procedure was employed. First, the mean fMRI image from each
encoding run was linearly registered to the subject’s in-plane T1
structural image using 7 degrees of freedom (df). The in-plane T1 image
was then registered to the high-resolution structural scan using 6 df.
Finally, the high-resolution structural scan was nonlinearly aligned to
the standard MNI 152 brain using FNIRT, and resulting parameters were
used to transform fMRI data.
fMRI Modeling and Higher Level Analyses
fMRI trials were classified into 4 types (high-confidence hits, lowconfidence hits, high/low-confidence misses, and nonwater response
trials), modeled by a box function with duration of 4.4 s, and convolved
with a standard gamma hemodynamic response function. These
covariates, as well as corresponding temporal derivatives and the 6
rigid body realignment motion parameters, were entered in a general
linear model predicting fMRI signal intensity. This lower level analysis
was completed separately for each encoding run (N = 4) for each
subject, then combined across runs using a fixed effects analysis within
each subject. Resulting contrast and variance maps (corresponding to
high-confidence hits vs. misses) for all young and old subjects were
carried forward into a one-sample t-test random effects model to
determine areas showing significant differences between conditions,
covarying for memory performance (task positive = higher activation in
hits vs. misses; task negative = higher deactivation in hits vs. misses;
thresholded at z >1.64 with a cluster significance of P = 0.01, corrected
for multiple comparisons).
Peak activations and deactivations were selected from this onesample t-test and used to create spherical ROIs (6 mm centered around
selected peak coordinates). Additionally, a hippocampal ROI was
defined by masking the activation map with an anatomically defined
ROI from the Harvard--Oxford subcortical atlas. Contrast values were
extracted from spherical peak ROIs as well as from the hippocampal
ROI and used to test effects of age (young vs. old) and PIB group
(within the old group, controlling for age).
Statistical Analyses
All statistical analyses and plots were completed using R version 2.11
(http://www.r-project.org/, last accessed 15 August 2011). Group
differences in demographic variables were determined with t-tests for
continuous variables and chi-squared tests for dichotomous variables.
Within the old NC group, multiple regression was used for relationships
between PIB group and cognitive measures as well as fMRI activation
(controlling for age). Within group correlations between cognitive
measures and fMRI contrast values were computed with Spearman rank
correlations (young, all old, PIB– old, and PIB+ old group separately;
Spearman rank was used to account for the small number of subjects
within groups). P < 0.05 was considered significant, and trends of
P < 0.10 were noted.
Results
Group Characteristics
Group characteristics are listed in Table 2. Old subjects were
significantly more educated than young subjects who were
mainly still students (t = 2.78, P = 0.007); there was no
difference in gender between old and young groups. Young
subjects were more accurate than old subjects on the water/no
water judgment (91% vs. 85%; t = –4.18, P < 0.0001), and there
was a trend for better memory recognition accuracy (t = 1.38,
P = 0.17) and better task memory performance in young versus
old subjects (assessed with d-prime; t = 1.68, P = 0.10). There
was no difference in recognition false-positive rate between
young and old subjects. Furthermore, young subjects had faster
reaction times than old subjects for the water/no water
judgment (1388 vs. 1863 ms; t = –5.56, df = 58, P < 0.0001)
as well as during the postscan recognition judgment (1878 vs.
3174 ms; t = –5.88, df = 58, P < 0.0001).
Based on the PIB index cutoff value of 1.08, 15 old NCs were
classified as PIB+ and 30 old NCs were PIB–. There were no
significant differences for age, education, or gender between
PIB+ and PIB– groups. Fifty-three percent of PIB+ subjects were
APOE4 carriers, whereas 33% of PIB– subjects were APOE4
carriers (this difference was not significant). Controlling for
age, there were no significant relationships between PIB status
and MMSE or any factor score other than semantic memory
Table 2
Subject characteristics
N
Age
Gender
Educationþ
APOE4 carriers/noncarriers
Recognition accuracy
Recognition false-positive rate
d-prime
PIB index
MMSE
Factor score 1 (EM)
Factor score 2 (Exe)
Factor score 3 (WM)
Factor score 4 (VisMem)
Factor score 5 (SM)*
yNC
PIB oNC
PIBþ oNC
15
23.2 (3.6)
9M
15.6 (1.7)
NA
0.76 (0.25)
0.38 (0.25)
1.24 (0.79)
NA
NA
NA
NA
NA
NA
NA
30
74.9 (6.6)
11M
17.3 (2.0)
9/18
0.68 (0.19)
0.36 (0.19)
0.98 (0.51)
1.03 (0.04)
29.2 (1.1)
0.02 (0.78)
0.25 (0.79)
0.14 (0.62)
0.13 (1.08)
0.01 (0.57)
15
76.3 (7.9)
6M
17.0 (2.0)
8/7
0.66 (0.27)
0.42 (0.27)
0.81 (0.66)
1.27 (0.18)
29.1 (1.1)
0.04 (0.63)
0.29 (0.48)
0.24 (0.74)
0.17 (1.16)
0.46 (0.49)
Note: Means and SDs are reported for continuous variables. Neuropsychological factor scores
were unavailable for 6 old normal controls (oNCs) (2 PIBþ and 4 PIB) and 3 PIB oNC were
missing APOE genotyping. Significant differences between young and old subjects are denoted
with a þ (P \ 0.05). Significant differences between PIB and PIBþ oNC are denoted with a
* (P \ 0.05). yNC, young normal controls; EM, episodic memory; Exe, executive function; WM,
working memory; VisMem, visuospatial memory; SM, semantic memory; and NA, not applicable.
Cerebral Cortex August 2012, V 22 N 8 1815
(PIB– were higher than PIB+; P = 0.014). There were no
differences in water/no water accuracy, recognition accuracy
or false-positive rate, overall memory performance assessed
with d-prime, or reaction time measures between PIB+ and
PIB– subjects.
Task Activation and Deactivation Patterns in Young and
Old Subjects
One-sample t-tests of young and old subjects combined are
shown in Figure 1. Task activations (hits > misses) are found
bilaterally in ventrolateral prefrontal (bordering dorsolateral
prefrontal), lateral occipital/parietal, posterior inferior temporal, and right parahippocampal/hippocampus. Deactivations
(hits < misses) were present in bilateral medial occipital,
posteromedial, angular, medial prefrontal, superior/dorsolateral
prefrontal, and left central/postcentral cortices. To create taskpositive ROIs, the highest peak coordinate for each cluster was
selected (Table 3). Furthermore, an additional task-positive ROI
was created in the hippocampus by masking cluster 3 by the
Harvard--Oxford subcortical atlas anatomically defined hippocampus ROI, resulting in a right hippocampus ROI 92 voxels in
size (736 mm3, ‘‘RHip’’). To create task-negative ROIs (Table 4),
the highest peak for clusters 3 and 4 were selected. For clusters
5 and 6, local maximum were selected in addition to or rather
than the highest peak since the peak coordinate for these
clusters did not coincide with regions typically considered part
of the DMN. We choose to focus on DMN-typical regions due to
previous publications stressing the concordance between this
network and Ab deposition. However, follow-up voxelwise
analyses enabled examination of all regions irrespective of
criterion used to select ROIs. Specifically, for cluster 5, a local
maximum in medial prefrontal cortex (mPFC) was selected (an
area typically associated with the DMN) rather than the highest
peak for that cluster, which was in the frontal pole. For cluster
6, the peak coordinate was in medial occipital cortex, whereas
a local maximum was in precuneus (consequently, 2 ROIs were
created for this cluster, ‘‘LOcc’’ and ‘‘Precun’’). ROIs from
clusters 1 and 2 were not selected since these regions are
outside the DMN. Overall, this resulted in 5 task-positive and 5
task-negative ROIs for subsequent analyses.
Relationships between Subsequent Memory Effects and Ab
in Old Subjects
Older subjects showed reduced activation compared with
young subjects across all task-positive ROIs (P < 0.01) except
the RHip ROI (P = 0.63). Controlling for age, PIB+ NCs showed
significantly increased activation compared with PIB– NCs in
RHip (P = 0.011) and LOcc (P = 0.019), while a trend was
present in ROcc (P = 0.058; Fig. 2). An average activation value
was additionally computed across all 5 task-positive ROIs and
was significantly different between PIB+ and PIB– groups
(Average Act; P = 0.012, Fig. 2). Results were similar after
Table 3
Activation clusters and peak coordinates
Cluster Cluster Z
index size
x
y
4
4
4
4
4
4
3
3
3
3
3
3
2
2
2
2
2
2
1
1
1
1
1
30
28
24
48
24
34
38
24
26
42
38
26
50
44
40
44
36
40
40
52
44
38
56
78 26 L lateral superior occipital (LOcc)
90 26 L occipital pole/lateral occipital
68 50 L lateral superior occipital
56 16 L inferior temporal
78 40 L lateral superior occipital
92 12 L lateral superior occipital
86 18 R lateral superior occipital (ROcc)
38 18 R fusiform/posterior parahippocampal gyrus
66 52 R lateral superior occipital
80 18 R lateral superior occipital
82 26 R lateral superior occipital
68 46 R lateral superior occipital
34 12 R inferior frontal gyrus/frontal pole (RIFG)
6 28 R precentral gyrus/inferior frontal gyrus
14 26 R inferior/middle frontal gyrus
36 10 R frontal pole/inferior frontal gyrus
16 26 R inferior/middle frontal gyrus
6 32 R precentral/middle frontal gyrus
8 26 L inferior frontal gyrus/precentral gyrus (LIFG)
14 38 L middle/inferior frontal gyrus
38
8 L frontal pole/inferior frontal gyrus
30 16 L inferior/middle frontal gyrus
32 18 L middle/inferior frontal gyrus
9189
8781
1893
1616
6.17
6.15
5.87
5.68
5.56
5.53
6.03
5.96
5.86
5.83
5.72
5.69
4.96
4.65
4.5
4.49
4.4
4.35
4.55
4.12
3.74
3.37
3.14
z
Location
Note: Significant task-positive clusters and corresponding local maxima from the one-sample ttest of young and old subjects. The highest peak within each cluster was selected for subsequent
ROI analyses (bolded and italicized). Additionally, cluster 3 was masked with a hippocampus
anatomical mask to define an additional task-positive ROI in the right hippocampus (‘‘RHip’’). L,
left; R, right.
Figure 1. Activation and deactivation statistical maps. Statistical maps are defined by one-sample t-tests across young and old subjects, covarying for task memory
performance. Warm colors are activations (hits [ misses), while cool colors are deactivations (hits \ misses).
1816 Increased fMRI Activation and Ab in Aging
d
Mormino et al.
Table 4
Deactivation clusters and peak coordinates
Cluster
index
Cluster
size
Z
x
y
z
Location
6
6
6
6
6
6
5
5
5
5
5
5
4
4
4
4
4
4
3
3
3
3
3
3
2
2
2
2
2
2
1
1
1
1
1
1
6157
5.55
4.98
4.69
4.51
4.28
4.27
4.43
4.12
4.03
3.87
3.65
3.56
4.55
4.25
4.2
3.87
3.73
3.62
3.47
3.42
3.39
3.38
3.36
3.31
3.91
3.51
3.35
3.26
3.15
3.15
4.06
3.65
3.63
3.39
3.33
3.29
2
2
2
12
0
4
20
26
2
22
34
30
60
50
66
58
56
58
62
62
66
62
54
60
42
32
42
46
34
28
26
24
30
22
36
28
90
88
72
90
80
82
50
54
52
42
34
36
46
26
46
30
48
40
46
40
36
26
12
36
22
28
38
32
36
44
44
56
48
58
46
56
26
30
26
28
42
40
26
20
10
22
30
28
32
12
32
26
44
0
14
38
28
8
4
24
50
62
62
56
68
52
30
28
26
22
28
20
L medial occipital pole/cuneus (LOcc)
R cuneus/occipital pole
L cuneus/precuneus
L occipital pole
Precuneus (Precun)
L cuneus/precuneus
L frontal pole
L frontal pole
Paracingulate/frontal pole (mPFC)
L frontal pole
L middle frontal gyrus/frontal pole
L middle frontal gyrus/frontal pole
R angular/supramarginal gyrus (RPar)
R middle temporal gyrus
R supramarginal/angular
R parietal operculum/supramarginal
R angular/supramarginal gyrus
R middle temporal gyrus
L supramarginal/angular (LPar)
L supramarginal
L supramarginal
L supramarginal
L temporal pole
L parietal operculum
L postcentral
L postcentral
L postcentral
L postcentral
L postcentral
L superior parietal
R frontal pole
R frontal pole
R frontal pole
R frontal pole
R frontal pole
R frontal pole
3448
3307
2831
1840
1777
Note: Significant task-negative clusters from the one-sample t-test of young and old subjects are
listed. Peaks selected for subsequent ROI analyses are bolded and italicized. L, left, R; right.
controlling for APOE status (RHip: P = 0.026; LOcc: P = 0.073;
ROcc: P = 0.082; Average Act: P = 0.044).
Relationships between Task Activation and Behavioral
Measures
To explore whether heightened activation is associated with
cognitive processes, average task activation (across the 5 taskpositive ROIs) was related to fMRI task memory performance
assessed with d-prime as well as the 5 factor scores derived
from neuropsychological data collected on a separate day from
fMRI scanning (episodic memory, executive function, working
memory, visual memory, and semantic memory). Due to the
significant association with PIB+ status within old subjects,
contrast values from the LOcc and RHip ROIs were also related
to cognitive measures within PIB+ subjects.
Across the entire old group, within PIB– subjects, and within
young subjects, there were no relationships between average
task activation and task memory performance or any factor
score. Within PIB+ subjects, there was a significant relationship
between average task activation and the visual memory factor
score (rho = 0.59, P = 0.035; Fig. 3). Furthermore, activation in
LOcc was significantly related to task memory performance
(rho = 0.66, P = 0.007), while activation in RHip was associated
with visual memory (rho = 0.60; P = 0.031) in PIB+ subjects
(Table 5 and Fig. 3). Relationships between average/regional
activation and the remaining factor scores were not significant
within PIB+ subjects.
Relationships with Task Deactivation
Examination of the parameter estimates across trial types for
areas showing significantly lower activation for hits than misses
revealed that selected task-negative regions show greater
deactivation during hits than misses relative to fixation (Fig. 4).
To examine differences in parameter estimates across young
and old subjects, a repeated measures analysis of variance with
ROI and trial type (hits vs. misses) as within subject factors and
group as a between subject factor as well as the interaction
between group and trial type was conducted. This analysis
revealed main effects for both ROI (F = 35.24, P < 0.001) and
trial type (F = 22.29, P < 0.001) as well as a trend for the
interaction between group and trial type (F = 3.6149, P =
0.058). Paired t-tests contrasting parameter estimates for
average deactivation across the 5 selected ROIs in young and
old groups separately revealed greater deactivation during hits
relative to misses in both young (P < 0.001) and old groups (P
< 0.001). Between group t-tests revealed greater deactivation
in young versus old subjects during hits (P = 0.028), whereas
no difference was observed for misses between old and young
subjects (P = 0.42). Thus, the reduced deactivation between
hits and misses observed in our old group was driven by
a reduced magnitude of deactivation during hits.
Likewise, direct comparison of hits versus misses contrast
values revealed reduced deactivations in old compared with
young subjects in 2/5 examined ROIs (LOcc: P < 0.001; mPFC:
P = 0.022) and in the average value across all 5 ROIs (Average
deact: P = 0.041). There was no effect of PIB status on the
contrast between hits versus misses in individual task-negative
ROIs or on average deactivation (Fig. 5).
To ensure the null result between PIB status and task
deactivations was not a consequence of ROI selection, an
exploratory voxelwise analysis was conducted using permutation testing with FSL’s Randomize (with 5000 permutations,
http://www.fmrib.ox.ac.uk/fsl/randomise/, last accessed 15 August 2011 restricted to the voxels that were significant in the
one-sample t-test of hits < misses). Results were considered
significant at a liberal threshold of P < 0.05, k = 50 (uncorrected). This analysis failed to reveal strong evidence for an
effect of amyloid on deactivations in this cohort. At this liberal
threshold, there were a few clusters showing reduced deactivation in PIB+ compared with PIB– subjects, as well as 2
clusters showing reduced deactivation in PIB– compared with
PIB+ subjects (Table 6).
Relationships between Task Deactivation, Cognition, and
Task Activation
Although a strong effect of Ab was not found in task-negative
regions, we nevertheless sought to determine whether
deactivations relate to memory performance in our cohort.
An average task deactivation measure was calculated by
averaging across the 5 selected task-negative ROIs and was
related to task performance as well as the 5 neuropsychological
factor scores. Across all old subjects, there was a negative
relationship with task memory performance (i e., more
deactivation, better performance; rho = –0.34, P = 0.021),
however, this relationship did not reach significance when old
groups were examined separately (PIB+ only: rho = –0.36,
P = 0.182; PIB– only: rho = –0.31, P = 0.126). There were no
significant relationships between average deactivation and any
factor score or between task memory performance and
deactivation within young subjects.
Cerebral Cortex August 2012, V 22 N 8 1817
Figure 2. Task activation across groups. Mean contrast values (hits vs. misses) for each task-positive ROI as well as an average across the 5 ROIs. Error bars reflect the
standard error estimates of each mean. *Indicates significant difference between PIBþ and PIB groups (P \ 0.05, controlling for age). LOcc, left occipital; LIFG, left inferior
frontal gyrus; ROcc, right occipital; RIFG, right inferior frontal gyrus; RHip, right hippocampus; and Average Act, average activation across 5 ROIs.
Figure 3. Relationships between activation and cognitive measures. Positive relationships between fMRI contrast values and measures of memory were identified within PIBþ
subjects. Specifically, activation in LOcc was correlated with memory performance during the fMRI experiment (measured with the d-prime of high-confidence recognition
responses, left; P 5 0.007), whereas RHip and the average activation across the 5 task-positive ROIs were correlated with the visual memory factor score (middle, right; P 5
0.031 and 0.035, respectively). Values are ranked due to the small number of subjects. There were no relationships with the other factor scores or within young or PIB old
subjects.
To assess independent contributions to fMRI task memory
performance (de Chastelaine et al. 2011), multiple regression
models were conducted with average task-negative and
-positive contrast values as simultaneous predictors of task
memory performance (conducted in all old subjects as well as
within PIB+ and PIB– groups separately). These models revealed
an independent effect of deactivation on performance across
all old subjects (P = 0.038) as well as trends for dissociable
effects of deactivation and activation on task memory
performance within PIB+ subjects (P = 0.091 and P = 0.099,
1818 Increased fMRI Activation and Ab in Aging
d
Mormino et al.
respectively; such that there was a trend for reduced deactivation in task-negative regions to be independently
associated with worse performance, while there was a trend
for increased task-positive activation to be independently
associated with better performance, Table 7).
Discussion
In this study, we scanned young and old subjects with fMRI
while performing incidental scene encoding, allowing isolation
of brain regions associated with successful memory formation.
Consistent with previous studies, we identified regions
showing greater activation for successfully remembered versus
subsequently forgotten scenes bilaterally in ventrolateral prefrontal, lateral occipital/parietal, posterior inferior temporal,
and the right parahippocampal/hippocampus (task-positive
regions). Furthermore, significant deactivations (hits < misses)
were present in DMN regions (posteromedial, medial prefrontal, and lateral temporoparietal cortices) as well as in areas
outside the DMN (bilateral medial occipital cortex, superior/
dorsolateral prefrontal, and left central/postcentral gyri).
Young subjects showed more activation in task-positive regions
and greater deactivation in task-negative regions compared
with old subjects. Within the old group, PIB+ subjects showed
increased activation in task-positive regions compared with
PIB– old NCs. Furthermore, positive relationships between
Table 5
Correlations between memory, activation, and deactivation within PIBþ subjects
ROI
Task memory
performance
Visual memory
factor score
Average activation
LOcc
RHip
Average deactivation
rho 5 0.29, P 5 0.302
rho 5 0.66, P 5 0.007
rho 5 0.22, P 5 0.428
rho 5 0.36, P 5 0.182
rho 5 0.59, P 5 0.035
rho 5 0.24, P 5 0.426
rho 5 0.60, P 5 0.031
rho 5 0.24, P 5 0.426
Note: Summary of correlations with memory measures in PIBþ subjects. Relationships were not
identified with the other factor scores (episodic memory, executive function, working memory,
and semantic memory). Trends and significant relationships are bolded (P \ 0.1).
higher task activation and better memory ability within PIB+
subjects suggest that these heightened activations are beneficial. Although we did not identify strong evidence for impaired
deactivation in PIB+ subjects, a multiple regression approach
revealed trends for dissociable effects of activation and
deactivation on performance within this group, demonstrating
that these networks may have independent contributions to
performance among PIB+ subjects (such that greater activation
was associated with better memory performance and impaired
deactivation was associated with worse memory performance).
Overall, our data suggest that heightened task-positive activation in PIB+ old subjects is beneficial to memory performance
and that these increases are not directly related to deficits in
DMN deactivation.
Heightened Task Activation in PIB+ NCs May Reflect
Compensatory Processes
The pattern of elevated activation in PIB+ NC subjects is
consistent with previous work showing elevated activation in
elderly NCs destined for episodic memory decline (Persson
et al. 2006; O’Brien et al. 2010) as well as in subjects at risk for
AD (Bookheimer et al. 2000; Dickerson et al. 2005; Trivedi et al.
2008). Our results provide direct support for previous
hypotheses that this hyperactivation may be a compensatory
response to underlying AD pathology.
The design of this experiment allowed isolation of activation
specific to successful memory. Therefore, the task-positive
increases we identified in PIB+ NCs specifically occur during
Figure 4. Trial parameter estimates for task-negative regions. Average trial parameter estimates for each task-negative ROI is plotted and reveals greater deactivation during hits
than during misses relative to fixation across all subjects. Error bars reflect the standard error estimates of each mean. Although old subjects show significantly greater
deactivation during hits than misses, the magnitude of deactivation during hits is reduced compared with young subjects. t-tests were performed within and between young and
old subjects for the average deactivation measure, and significant differences are denoted with an asterisk. O 5 old, Y 5 young.
Cerebral Cortex August 2012, V 22 N 8 1819
Figure 5. Task deactivation across groups. Average contrast values for hits versus misses are plotted for each task-negative ROI. Error bars reflect the standard error estimates
of each mean. Between group t-tests revealed reduced deactivation in old compared with young across multiple ROIs (LOcc and mPFC), but an effect of PIB status was not
identified.
Table 6
Significant clusters and peak coordinates from exploratory analysis in task-negative regions
Table 7
Multiple regression model predicting memory performance
Cluster size
Max P value
x
Less deactivation in PIBþ versus PIB
Model: memory performance ~ average activation þ average deactivation
163
91
73
53
50
Less deactivation
158
55
0.0002
56
0.001
6
0.003
0
0.002
30
0.001
60
in PIB versus PIBþ
0.001
2
0.001
56
y
z
Location
50
92
40
24
60
26
28
30
30
36
L supramarginal gyrus
R medial occipital
Posterior cingulate
L middle frontal gyrus
R lateral occipital
92
44
8
26
Medial occipital
R angular gyrus
Note: Exploratory analysis within task-negative regions failed to reveal strong evidence for an
effect of amyloid within old subjects. L, left; R, right.
successful encoding. Additionally, we identified positive relationships between memory ability and heightened task
activation within PIB+ subjects. Taken together, this pattern
implies that heightened activation within PIB+ subjects during
encoding promotes better overall memory performance that
extends beyond the specific scanning session since relationships were identified with an independent measure of visual
memory performed on a separate day.
Although the mechanism underlying this effect is unclear,
a number of potential explanations exist. One possibility is that
hyperactivity may reflect increased neuronal demand that
counteracts detrimental effects of Ab that occur at the level of
synaptic function (Selkoe 2002). Another possibility is that
PIB+ NC implement alternative processing strategies in the
context of Ab-related functional decline. It has been shown
1820 Increased fMRI Activation and Ab in Aging
d
Mormino et al.
All old, N 5 45
Average dectivation
Average activation
PIBþ, N 5 15
Average dectivation
Average activation
PIB, N 5 30
Average dectivation
Average activation
Parameter
estimate
Standard
error
P
value
20.0123
0.0084
0.0057
0.0071
0.038
0.244
20.0162
0.0190
0.0088
0.0106
0.091
0.099
0.0064
--0.0002
0.0081
0.0112
0.441
0.999
Note: Multiple regression models predicting task memory performance reveal an independent
effect of task deactivation on performance across all old subjects as well as a trend for
dissociable effects of deactivation and activation on performance within PIBþ subjects (reduced
deactivation in task-negative regions was associated with worse performance; increased taskpositive activation was associated with better performance). Significant relationships and trends
are bolded (P \ 0.1).
that heightened activation within task-positive regions is
related to deep encoding (Fletcher et al. 2003) as well as
encoding effort (Reber et al. 2002), which may represent
mechanisms implemented by PIB+ subjects during this task.
While the incidental encoding nature of our design makes it
unlikely that different encoding strategies were implemented
by PIB+ subjects, it is possible that heightened activation
reflects these mechanisms at work during online task demands.
The online demand of the current experiment was a basic
visual search task, where subjects indicated whether or not
water was present. A possibility is that PIB+ subjects engaged in
deeper processing during visual search of presented scenes and
that this deeper processing was beneficial for successful
memory, whereas a similar level of processing was unnecessary
for successful memory in PIB– subjects. Interestingly, the
occipital cortex and hippocampus remain relatively free of Ab
deposition throughout AD development (Braak H and Braak E
1991; Thal et al. 2002), suggesting that these regions may
compensate for amyloid-induced dysfunction in multimodal
association areas that are highly vulnerable to Ab deposition.
Heightened Task Activation May Precede Ab Deposition
It is also possible that increased activation within this network
predates Ab deposition. This direction of causality is supported by
the observation that Ab release is activity dependent (Cirrito et al.
2005) and that Ab deposition occurs in the most metabolically
active areas of the brain (Buckner et al. 2005; Vlassenko et al.
2011). Furthermore, recent evidence from a mouse model of AD
suggests that neuronal activity is predictive of the brain areas that
are subsequently vulnerable to Ab deposition (Bero et al. 2011).
Given evidence that Ab is released from the presynaptic terminal
through exocytosis during fusion of synaptic vesicles, it is possible
that hyperactivation in task-positive regions directly leads to Ab
deposition in connected multimodal association regions (Cirrito
et al. 2005). The positive relationships we identified between
heightened activation and behavioral measures suggest that this
hyperactivation is nevertheless beneficial for these individuals who
perhaps have preexisting limitations that require higher brain
activity for normal cognitive function. Thus, it is possible that this
activation pattern may confer early life advantages, although
detrimental in the long term by promoting Ab deposition. This is
consistent with the observation that carriers of the APOE4 allelle
show increased hippocampal activation during episodic memory
(EM) processing in their late 20s (Filippini et al. 2009), which is
likely before Ab deposition has begun (Kok et al. 2009).
Although we did not identify a relationship between APOE
status and activation, the older age of our subjects makes the
current study suboptimal for examining effects preceding Ab
deposition. Studies that have implicated a temporal sequence of
events by investigating young APOE carriers (presumably before
Ab deposition; Mondadori et al. 2007; Filippini et al. 2009) or
longitudinal brain activation preceding cognitive decline (presumably concomitant with Ab deposition; Persson et al. 2006;
O’Brien et al. 2010) have not converged to reveal a consistent
mechanism underlying activation increases. The combination of
amyloid imaging with fMRI will help disentangle the temporal
order of these events by directly measuring underlying
pathology rather than relying on proxy markers of AD risk.
Deactivations Are Impaired in Aging and Relate to
Memory Performance But Not Ab
In addition to isolating task-positive regions, we also investigated
task-negative regions that show more deactivation during hits
than misses. Many of the regions showing this behavior belong
to the DMN, which consistently deactivates across a variety of
externally driven cognitive tasks (Buckner et al. 2008). Tasknegative regions were also identified outside the DMN, namely
bilateral medial occipital, dorsolateral PFC, and left central gyrus.
These non-DMN deactivations may be a specific response to the
employed cognitive task. For instance, previous studies employ-
ing a subsequent memory paradigm have identified deactivations
in dorsolateral prefrontal cortex (Daselaar et al. 2004), which
may reflect reallocation of resources from this area when
organization and manipulation are not involved in online task
demands (Blumenfeld and Ranganath 2007). Consistent with
previous studies, we found reduced deactivation in old
compared with young subjects as well as a relationship between
task memory performance and deactivation within old subjects
(Morcom et al. 2003; Gutchess et al. 2005; Duverne et al. 2009;
Kukolja et al. 2009; de Chastelaine et al. 2011).
Although we identified an effect of aging on deactivations
during successful encoding, we did not find a strong relationship
between deactivation failure and PIB status. This result is
inconsistent with a recent study investigating Ab in aging
(Sperling et al. 2009). There are many factors that may
contribute to this inconsistency. One possibility is that additional
factors associated with aging contribute to deactivations,
obscuring relationships between Ab and deactivations in older
subjects. For instance, precuneus deactivation has been shown
to relate to levels of dopamine synthesis in elderly subjects
(Braskie et al. 2010), and it is likely that age-related changes in
the dopamine system are unrelated to levels of Ab. Future
studies that simultaneously measure multiple age-related brain
changes may reveal distinct contributors of impaired deactivation in aging. Differences in experimental design may also
contribute to the null finding in our study. For instance, Sperling
et al. used face-name pairs as stimuli, and subjects were
specifically instructed to encode task stimuli. It is unclear how
stimuli differences and encoding intent affects relationships
between deactivations and Ab burden in aging.
Despite the lack of relationship between PIB status and
deactivation in our elderly group, a multiple regression
approach revealed trends for dissociable effects of task positive
and negative networks on performance within PIB+ subjects.
Although the ability to address this multivariate relationship in
the current analysis was greatly limited by sample size, future
studies with more participants will be able to determine
whether these networks have independent contributions to
performance amongst high PIB subjects.
Conclusions
In this study, we show that increased activation among taskpositive regions is related to Ab burden in cognitively normal
elderly controls. Although the mechanisms underlying these
increased activations remain unclear, occurrence during successful memory encoding and positive relationships with overall
measures of memory ability suggest they are beneficial to
individuals with high Ab burden. The ability to elicit compensatory neuronal activation may allow cognitively normal elderly
individuals to cope with underlying pathology and delay the
onset of cognitive decline. It is also possible that heightened
activation has a direct causal role in Ab deposition in aged
individuals.
Funding
National Institutes of Health (AG034570, AG032814) and
Alzheimer’s Association (ZEN-08-87090).
Notes
Conflict of Interest : None declared.
Cerebral Cortex August 2012, V 22 N 8 1821
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