Age does not increase rate of forgetting over
weeks—Neuroanatomical volumes and visual
memory across the adult life-span
ANDERS M. FJELL,1KRISTINE B. WALHOVD,1IVAR REINVANG,1,2ARVID LUNDERVOLD,3
ANDERS M. DALE,4,5,6BRIAN T. QUINN,4NIKOS MAKRIS,7and BRUCE FISCHL4
1Institute of Psychology, University of Oslo, Oslo, Norway
2Department of Psychosomatic Medicine, Rikshospitalet University Hospital, Oslo, Norway
3Department of Physiology & Locus on Neuroscience, University of Bergen, Bergen, Norway
4MGH-NMR Center, Massachusetts General Hospital, Harvard University, Cambridge, Massachusetts
5MR Center, Norwegian University of Science and Technology, Trondheim, Norway
6Departments of Neurosciences and Radiology, University of California, San Diego
7Center for Morphometric Analysis, Massachusetts General Hospital, Harvard University, Cambridge, Massachusetts
(Received December 9, 2003; Revised April 15, 2004; Accepted June 23, 2004)
The aim of the study was to investigate whether age affects visual memory retention across extended time intervals.
In addition, we wanted to study how memory capabilities across different time intervals are related to the volume of
different neuroanatomical structures (right hippocampus, right cortex, right white matter). One test of recognition
(CVMT) and one test of recall (Rey-Osterrieth Complex Figure Test) were administered, giving measures of
immediate recognition0recall, 20–30 min recognition0recall, and recognition0recall at a mean of 75 days.
Volumetric measures of right hemisphere hippocampus, cortex, and white matter were obtained through an
automated labelling procedure of MRI recordings. Results did not demonstrate a steeper rate of forgetting for older
participants when the retention intervals were increased, indicating that older people have spared ability to retain
information in the long-term store. Differences in neuroanatomical volumes could explain up to 36% of the variance
in memory performance, but were not significantly related to rates of forgetting. Cortical volume and hippocampal
volume were in some cases independent as predictors of memory function. Generally, cortical volume was a better
predictor of recognition memory than hippocampal volume, while the 2 structures did not differ in their predictive
power of recall abilities. While neuroanatomical volumetric differences can explain some of the differences in
memory functioning between younger and older persons, the hippocampus does not seem to be unique in this
respect. (JINS, 2005, 11, 2–15.)
Keywords: Visual memory, Hippocampus, Cortex, MRI
Reduction of memory capabilities is generally found with
increasing age in cognitively healthy individuals (e.g. Small
et al., 1999; Tombaugh & Hubley, 2001). Especially, there
is a decrement in the ability to acquire new information
(Trahan & Larrabee, 1992). In addition, studies have exam-
ined forgetting in older persons. However, neither for visu-
ally nor for verbally presented material are differential rates
of forgetting between younger and older participants estab-
lished.With the exception ofTombaugh and Hubley (2001),
most studies of age effects on memory use retention inter-
vals between learning and delay of 30 min or less. This fits
well with the major neuropsychological tests of memory
function, where long time memory is defined as memory
across 20–30 min. However, present knowledge and theory
indicate that memory consolidation takes place over a sig-
nificantly longer time period of several days (Riedel &
Micheau, 2001), and perhaps up to several weeks (e.g., Haist
et al., 2001; Rempel-Clower et al., 1996). Thus, it is possi-
may be caused by less efficient memory consolidation, even
though this is not captured by neuropsychological tests. In
the present study, we focus on age-dependent differences in
Reprint requests to: Anders M. Fjell, Institute of Psychology, Uni-
versity of Oslo, P. B. 1094 Blindern, 0317 Oslo, Norway. E-mail:
Journal of the International Neuropsychological Society (2005), 11, 2–15.
Copyright © 2005 INS. Published by Cambridge University Press. Printed in the USA.
memory across weeks, and we relate these differences to
Forgetting Through the Life-Span
When comparing rates of forgetting among groups, initial
learning level has to be taken into account. Using saving
scores in terms of percentages of what was initially learned
or ANOVA procedures are the most common strategies to
overcome this problem. When acquisition differences are
controlled for in this way, age differences in forgetting rates
are usually not found (e.g., Cullum et al., 1990; Geffen
et al., 1990;Trahan & Larrabee, 1992;Youngjohn & Crook,
1993). An alternative method is to ensure comparable lev-
els of acquisition by increasing the level of learning for
the group with the lowest performance, for example, by
increased inspection time or increased number of repeti-
tions during learning (e.g., Huppert & Piercy, 1979). By
this procedure, Huppert and Kopelman (1989) found
increased forgetting with increased age. However, other
researchers have failed to replicate this (Rybarczyk et al.,
1987; Spikman et al., 1995). Even though the procedure has
have argued that equal performance at 10 min does not
mean equal learning, and Wickelgren (1975) has indicated
that an increase of stimulus duration may produce other
sources of variation.
The short retention intervals usually employed in studies
of age and forgetting make it premature to conclude that
storage and forgetting do not contribute to differences in
memory capabilities across the adult life-span. The term
memory consolidation is central here, taken to mean the
processes where encoded information is stored and mem-
ory traces established in the brain in such a form that it is
potentially retrievable after longer time periods (weeks,
months, and years). These consolidatory processes proba-
bly work over days and weeks (Haist et al., 2001; Riedel
and Micheau, 2001). Thus, differences in memory consoli-
dation or storage between younger and older adults may be
evident when considerably longer intervals are employed
between learning and retention than in most previous stud-
ies. Tombaugh and Hubley’s (2001) study of verbal mem-
ory is one of the rare studies where longer retention intervals
are used. They investigated performance in three different
verbal learning tasks at different retention intervals, from
20 min and up to 62 days, in three age groups (from 20–80
years). All groups showed equal rates of forgetting after
20 min, but increasing age was associated with faster rates
of forgetting. This increase in forgetting seemed to happen
during Day 1, and did not seem to increase further across
longer delay intervals. This effect was reduced or elimi-
nated when prompted-recall instead of free recall proce-
dures was used. The authors speculate that much of the
problems older people experience in recalling information
are due to retrieval deficits, and that decline in the function-
ality of frontally based mechanisms may partly explain the
results. In addition, the authors argue that as time from the
initial learning increases, older adults may also fail to retain
as much verbal information as do younger participants
because of deterioration in long term storage. Which meth-
ods of testing memory that are chosen may be important in
such studies, since recall and recognition procedures tap
partly different memory components (Brown and Aggle-
In the present study, focus is on visual recall and visual
recognition memory, using procedures that utilize visually
complex material that is difficult to encode verbally. Thus,
processes quite different from those involved in the Tom-
baugh and Hubley (2001) study will be involved. Studies
suggest that visually presented information is processed in
other parts of the brain than verbally presented material,
and the associative networks involved when semantically
meaningful stimuli are processed are quite different from
those involved when meaningless information is processed.
Recent results indicate that various neurocognitive pro-
and that the distribution of such activity changes with age
(Albert & Moss, 1988; Brown & Jaffe, 1975; Cabeza, 2002).
Daselaar et al. (2003) have demonstrated differential acti-
vation of the medial temporal lobe system in younger and
older adults during semantic memory tasks. Thus, when
nonsemantic material is used instead of semantic, sig-
nificant differences in neurocognitive processing can be
expected. Thus, it is not evident that Tombaugh and Hub-
ley’s (2001) demonstration of age-related differences in the
rate of forgetting over long retention intervals are general-
izable to other types of memory (e.g., for visual non-
semantic material). In the present study, this will be explored
for recognition and recall memory separately. Recognition
tests are known to reduce or eliminate performance differ-
Raz et al., 1998), probably because recognition places less
demand on retrieval processes, which are known to be vul-
nerable to age (Parkin, 1993).Tombaugh and Hubley (2001)
made a similar finding when they found that prompts elim-
inated or reduced the age-associated effects. Since we have
a smaller number of participants than Tombaugh and Hub-
ley, we are not able to divide the sample in groups accord-
ing to different retention intervals.Therefore, only one long
mean retention interval will be employed (see Methods
The Neuroanatomy of Memory
Structures within the temporal lobe, including the hippo-
campus, are central in memory performance in humans.
This has been shown in patient studies (e.g., Milner, 1968,
1972; Scoville & Milner, 1957), experimental animal stud-
ies (e.g.,Alvarez et al., 1995; Zola et al., 2000), and studies
using functional scanning methods (e.g., Monk et al., 2002).
Evidence suggests that a hippocampal–neocortical dia-
logue strengthens the memory trace over time, rendering
hippocampus irrelevant at the end of the process (Buzsaki,
1996; Ward et al., 1999). Further, it is known that brain
Neuroanatomy and visual memory across weeks
regions underlying human long-term memory performance
are engaged differentially according to the nature of the
material being encoded. For instance, type of processing in
terms of spatial versus associative, influences the extent to
which hippocampus is involved (Brown &Aggleton, 2001).
Also, it is demonstrated that visual, non-nameable stimuli
involve right, but not left, medial temporal lobe (deToledo-
Morrell et al., 2000; Kelley et al., 1998; Martin et al., 1997;
Milner 1968, 1972; Monk et al., 2002).
As illustrated above, patient studies and functional neuro-
imaging studies have established the importance of hippo-
campus in human memory. However, it is not evident which
role structural aspects of a neuroanatomical volume (e.g.,
volume) play. A plausible assertion is that the volumes of
different neuroanatomical structures are a function of the
number of neurons and the complexity of the interconnec-
tions between them. Some evidence for this view exists;
for example, it has been demonstrated that hippocampal
volume is proportional to neuronal number (Kuzniecky &
Jackson, 1995), and that larger brains generally contain
more neurons (Pakkenberg & Gundersen, 1997). Further,
it is shown that the volumes of different neuroanatomical
structures are reduced in normal aging (e.g., Courchesne
et al., 2000, Hackert et al., 2002), and that cognitive abil-
ities such as memory decline with age (Lezak, 1995). How-
ever, even though some studies have identified negative
relationships between neuronal number and age in certain
brain regions (Simic et al., 1997), it seems clear that age-
related decreases in the number of neurons in the healthy
human brain cannot account for the observed reductions in
neuroanatomical volumes (Courchesne et al., 2000). Fur-
ther, contrary to the hypothesis that neuronal death in aging
causes age-related changes in cognitive function, studies
of memory in aged rats have suggested that age-related
cognitive decline can occur in the absence of significant
neuron death in any major, cytoarchitectonically defined
component of the hippocampal system (Rapp et al., 2002).
Thus, alterations in connectivity and other changes are
more likely causative factors. Other studies indicate that
the same probably is true for cerebral cortex also. Terry
et al. (1987) found age-related decrements in brain weight,
thickness of certain cortical regions, and a shrinkage of
large neurons, but concluded that neuronal density was
relatively unchanged. Peters et al. (1998), in a review paper,
conclude that, for the human cerebral cortex, there is no
strong evidence to support the concept that significant num-
bers of neurons are lost during normal aging. Discrepant
results exist (e.g., Pakkenberg & Gundersen, 1997; Regeur
et al., 1994), and Peters et al. keep the possibility open
that regional losses of neurons from one architectonic area
or cortical layer with age are possible. However, there is
presently no strong case that (1) the often-observed reduc-
tions in neuroanatomical volumes in normal aging are
caused by neuron deaths, or that (2) if neuron death in
aging actually occurs in specific regions in the human
brain, this causes the cognitive changes that inevitably
come with increasing age.
Even though reductions in the volume of different brain
areas with age probably have other causes than reduction in
neuronal number, it may still be reasonable to expect a
positive relationship between the volume of different brain
regions and cognitive function throughout the life-span, for
example, due to differences in number of interconnections
between neurons in a given brain region. However, a rela-
tionship between the size of hippocampus and memory per-
formance in healthy samples has not been easy to establish.
While dozens of studies link atrophy in hippocampus and
the medial temporal lobe to dementias as Alzheimer’s dis-
ease, and hippocampal volume is related to memory func-
tion within such patient groups (Barber et al., 2001; Cahn
et al., 1998; deLeon et al., 1996, 1997; Deweer et al., 1995;
Fox et al., 1996; Heun et al., 1997; Jack et al., 1997; Mega
et al., 2002; Mori et al., 1997; O’Brien et al., 1997; Small
et al., 1999), it is not evident how and if individual differ-
ences in hippocampal structure contribute to individual dif-
ferences in memory abilities in healthy persons. Only a few
studies have linked hippocampal volume to memory perfor-
mance in nonpathological samples. In these studies, the rela-
tionship between hippocampal volume and psychometric
memory performance has been difficult to establish, even
when life-span samples are used (Chantôme et al., 1999;
Köhler et al., 1998; Petersen et al., 2000; Raz et al., 1998;
Tisserand et al., 2000;Ylikoski et al., 2000), although some
studies find the expected relationships (e.g., Golomb et al.,
1994). The largest study conducted to date is Hackert et al.
(2002), who found that hippocampal head size was related
to memory test performance in 60–95 year-olds, even when
controlling for age, sex, education, and midsagittal area as
proxy for intracranial volume.
Evidently, previous research has not been able to estab-
lish any robust relationship between hippocampal volume
and memory performance. One reason for this may be that
previous studies have used short retention intervals, 1-hr or
most often less, between the learning trials and the memory
test.As argued above, the hippocampus may be involved in
memory consolidation over a prolonged time. Dupont et al.
(2002), in a recent fMRI study of immediate recall as well
as recall after 24 hr, found significant hippocampal activa-
tion during recall only after the 24-hr delay. The short-
interval studies may not capture the time lag where the
hippocampus exerts some of its most important contribu-
tion to human memory performance. Supporting this view
is a study by Walhovd et al. (2004). Using a retention inter-
val of several weeks, a positive relationship between hippo-
campal volume and the free recall score on the California
Verbal Learning Test was found. This relationship did not
exist independently of age when a 30-min retention interval
was used. One aim of the present study is to relate long-
term visual memory function to neuroanatomical volumet-
ric measures. If the hippocampus is involved in long-term
memory consolidation, it is important to investigate whether
memory over weeks is more strongly related to hippocam-
pal volume than memory over 20–30 min. Furthermore,
current hypotheses about the nature of hippocampal pro-
A.M. Fjell et al.
cessing indicate that stronger relations should be found for
visual material involving spatial material and using recall.
Also, it is of interest whether a relationship between hippo-
campal volume and memory performance is of a linear or
nonlinear nature. If nonlinear relationships exist between
neuroanatomical volumes and neuropsychological func-
tion, this implies that volumetric differences cannot in a
straightforward way be related to differences in cognitive
performance. Since the right hemisphere is established as
the most important for visual, non-nameable stimuli, we
will restrict our focus to the right hemisphere. The visual
recognition test employed in the present study, The Contin-
uous Visual Memory Test (CVMT), has been shown to be
more vulnerable to right than left hemisphere pathology
(Trahan et al., 1990). The recall test, the Rey-Osterrieth
Complex Figure Test, may be more dependent upon left
hemisphere structures in addition to the right, but it has
been established that especially right hemisphere injuries
affect both visual reconstructive aspects and the visual recall
aspects of the test (Taylor, 1979). However, as background
information, some analyses will be performed for left as
well as right hemisphere.
Specifically, two main questions are asked: (1) Are lon-
ger retention intervals more detrimental for the visual mem-
ory performance of older people than younger? and (2) Can
variations in hippocampal, cortical, and0or white matter
volume explain variations in visual memory performance?
In addition to direct answers to these questions, supplemen-
tary statistical analyses will be provided when appropriate.
Participants were recruited by newspaper adverts or because
they were participants in an longitudinal research project in
Oslo on cognitive aging (see Walhovd & Fjell, 2003, for
more details). The original sample consisted of 84 partici-
pants, aged 21–88 years, screened for general health prob-
(e.g., hypothyroidism, stroke, diabetes, drinking or drug
problems, medications, etc.), psychiatric disorders (e.g.,
depression), or cognitive dysfunction (e.g., dementia). For
these purposes we used a self-report inventory about phys-
ical and mental health, Beck Depression Inventory (Beck,
1987), Wechsler Abbreviated Scale of Intelligence (WASI;
Wechsler, 1999), and the Mini Mental Status Exam (Fol-
stein et al., 1975). Participants were required to have a MMS
score of at least 26, a Beck score of maximum 15 and an IQ
score of at least 85. Eleven persons were excluded before,
during, or after the examination, due to failure to satisfy the
inclusion criteria. Of these, 70 returned the extended mem-
ory tests, of which we had full MRI recordings available for
46.Thus, for analyses involving MRI, the sample size is 46,
while for all other analyses the sample size is 70. All par-
ticipants underwent a broad neuropsychological examina-
tion, a 2-hr neurophysiological examination (EEG and ERP,
which will not be reported here), and an MRI scan, usually
on three different occasions within about two weeks. For
some analyses, the sample was divided into three different
age groups; 20–30 years, 31–60 years, and 61–90 years.
Correlation analyses between Beck Depression score, MMS
score, age, education, gender, and IQ showed significant
relationships between Beck Depression score and age (r 5
.48, p , .05), MMS score and age (r 5 2.40, p , .05),
MMS score and IQ (r5.24, p , .05), and education and IQ
(r 5 .45, p , .05), while the other 11 correlations were
nonsignificant. These relationships were as expected. The
significant relationship between depression score and age
is due to the fact that a large part of the Beck Depression
Inventory consists of questions regarding sleep pattern, eat-
ing pattern, sexual function etc., functions that are known
to change and decline with advanced age. All in all, we are
reasonably sure that possible age effects on the variables of
interest are not due to systematic differences in sample char-
acteristics at different ages, or that the oldest in the sample
are showing indications of degenerative disease processes.
Further sample characteristics are reported in Table 1.
The CVMT (Trahan & Larrabee, 1985) consists of 112
abstract drawings, which are shown sequentially to the par-
ticipant, each for 2 s. The task is to decide which pictures
are new and which have been shown previously. Within the
string of 112 pictures, seven different pictures are shown
seven times, and these are the targets. The total score is
number of correct (old) responses to recurring items plus
number of correct (new) responses to nonrecurring items,, a
maximum of 96, and this total score was used in the analy-
ses. After this continuous performance learning trial, a
delayed recognition tests is administered after 30 min. The
participants are shown seven sheets, each with seven draw-
ings from the first trial, and the task is to decide which of
the drawings that were repeated seven times. Total possible
score is then seven. Generally, acquisition level declines
slowly but steadily from age 30, mostly due to an increase
of false alarms (Trahan et al., 1990), and gender effects or
effects of education are generally not observed (Trahan,
have also shown that the CVMT is a measure of visual
memory relatively independent of visual–spatial ability.We
(SD 34.7), when the participants got a version of the test by
mail, and sent the answers back. The retention interval var-
ied, because some participants used much time before they
filled out their answers, and some were hard to reach
(because they were on vacation, etc.).The participants were
not told that we would contact them again to administer the
additional memory tasks. The mean retention interval was
88.0 (52–242), 71.2 (46–139), and 71.7 (48–148) days for
the young, middle-aged and old group, respectively. The
retention interval was not significantly related to age group,
but a significant correlation between age and retention inter-
Neuroanatomy and visual memory across weeks
val was found (r 5 2.31, p , .05), which means that the
older participants generally responded faster than the youn-
ger. Retention interval was not related to variables as gen-
der (r 5 2.02, n.s.), IQ (r 5 .14, n.s.), right hippocampal
volume (r 5 .02, n.s.), right hemisphere cortical volume
(r 5 .21, n.s.), right hemisphere white matter volume (r 5
2.00, n.s.), or education (r 5 2.07, n.s.).
In the Rey-Osterrieth Complex Figure Test (Osterrieth,
1944; Rey, 1941), the participants are shown a complex
drawing, and asked to reproduce it. They are not told to
memorize the figure. When they have finished the drawing,
the figure is removed, and they are asked to reproduce it by
memory (immediate recall).The same procedure is repeated
after 20 min. The recall trials are sensitive to age (e.g.,
Spreen & Strauss, 1991), and the decline in performance is
found to begin in the 30’s. Recall scores are slightly related
to education (Delaney et al., 1988; Rosselli &Ardila, 1991).
This test involves spatial ability and motor skills, especially
visuospatial and visuomotor integration abilities, to a greater
extent than the CVMT. This adds to the complexity and
difficulty of the test. We repeated the free recall task by
sending the participants a letter after the learning session,
and they sent their answers back (the same retention inter-
vals as for the CVMT test).
A Siemens Symphony Quantum 1.5 T MR scanner with a
conventional head coil was used. The pulse sequences used
for morphometric analysis were:Two 3D magnetization pre-
pared gradient echo (MP-RAGE), T1-weighted sequences
matrix 5192 3 256, FOV 5 256 mm), with a scan time of
8.5 min per volume. Each volume consisted of 128 sagittal
slices with slice thickness 5 1.33 mm, and in-plane pixel
size of 1 mm 3 1 mm. The image files in DICOM format
were transferred to a Linux workstation for morphometric
MRI Volumetric Analyses
The automated procedures for volumetric measures of the
to each voxel in an MRI volume based on probabilistic
training set. The manually labeled training set is a result of
the validated techniques of the Center for Morphometric
Analysis, and the automated technique extracts the infor-
mation required for automating the segmentation proce-
dure. Since there is a considerable overlap in intensities
between different anatomical structures (even cortical gray
matter and white matter overlap by more than 12%; Fischl
et al., 2002), spatial information is required to disambigu-
ate the classification problem. The classification technique
employs a registration procedure that is robust to anatomi-
cal variability, including the ventricular enlargement typi-
cally associated with neurological diseases and aging. In
the present study, the same automated training set as used
in Fischl et al. (2002) is employed. Briefly, the segmenta-
tion is carried out as follows. First, an optimal linear trans-
form is computed that maximizes the likelihood of the input
image, given an atlas constructed from manually labeled
images. Next, a nonlinear transform is initialized with the
linear one, and the image is allowed to further deform to
better match the atlas. Finally, a Bayesian segmentation
procedure is carried out, and the maximum a posteriori
(MAP) estimate of the labelling is computed. The segmen-
(1) the prior probability of a given tissue class occurring at
a specific atlas location, (2) the likelihood of the image
given that tissue class, and (3) the probability of the local
Table 1. Sample characteristics
Young groupMiddle group Old groupTotal sample
A.M. Fjell et al.
spatial configuration of labels given the tissue class. This
latter term represents a large number of constraints on the
space of allowable segmentations, and prohibits label con-
figurations that never occur in the training set (e.g., hippo-
campus is never anterior to amygdala). The technique has
been previously shown to be comparable in accuracy to
manual labeling. In the present paper, volumes for cortical
gray matter, white matter, and hippocampus are reported.A
sample of the automated labelling is shown in Figure 1.All
volumes were regressed on intracranial volume obtained
uals were used in the statistical analyses.
Two different memory tests were administered. The Con-
tinuous Visual Memory Test (CVMT) was used to assess
visual recognition, while the Rey-Osterrieth Complex Fig-
ure Test was used to assess visual recall (see Methods sec-
tion). Correlation analyses with age and CVMT learning
scores, 30-min recognition scores, and 75-day recognition
scores, and Rey-Osterrieth learning, 20-min recall scores,
and 75-day recall scores are calculated. Further, correla-
tions between age and the ratios of the measures will be
calculated; CVMT learning0CVMT 30-min recognition
(CVMT Ratio 1), 30 min recognition075-day recognition
(CVMT Ratio 2), and Rey-Osterrieth learning0Rey-
Osterrieth 20-min recall (Rey Ratio 1), Rey-Osterrieth
20-min recall0Rey-Osterrieth 75-day recall (Rey Ratio 2).
Linear regression analyses with age and square of age simul-
taneously as predictor variables are done to check for pos-
sible nonlinear components. To test for interaction effects
between age and retention intervals, ANOVAs with 3 (age
groups) 3 2 (test times) are computed for recognition and
recall scores separately.
To get an estimate of the relationship between neuroana-
tomical volumetric measures, memory function, and age,
multiple regression analyses with right hemisphere cortical
volume and hippocampal volume simultaneously as predic-
tor variables and the different memory variables in turn as
dependent variables are done to investigate unique contri-
butions from either of the two neuroanatomical structures
to memory performance.
Greenhouse-Geisser corrections of the degrees of free-
dom will be used when appropriate, as will Bonferroni
correction of probability levels to control for multiple
Age was significantly correlated with aspects of memory
performance. The correlations between age and the various
memory test variables were r 5 2.48 for CVMT learning,
r 5 .50 for CVMT learning false alarms, r 5 2.42 for
CVMT 30-min recognition, r 5 2.57 for CVMT 75-day
recognition, r 5 2.53 for Rey-Osterrieth 5-min recall, r 5
2.53 for Rey-Osterrieth 20-min recall, and r 5 2.63 for
Rey-Osterrieth 75-day recall (for all rs, p , .0001). For the
ratio scores, the correlations with age were r 5 .31 ~p ,
.01) for CVMT Ratio 1 (learning030-min recognition), r 5
.20 (n.s.) for CVMT ratio 2 (30-min recognition075-day
recognition), r 5 .08 (n.s.) for Rey Ratio 1 (learning020-
min recall), and r 5 .28 ~p , .05) for Rey Ratio 2 (20-min
recall075-day recall). Regression analyses showed that in
no cases did a nonlinear component add significantly to the
amount of explained variance. Scatterplots illustrating the
Fig. 1. Sample of automated labelling (right picture) of a skull-stripped T1 weighted MRI picture (left picture).
Hippocampus (yellow areas), cerebral cortex (violet areas), and white matter (white0light green areas) are shown in
one slice in the coronal view of the brain of a young female participant.
Neuroanatomy and visual memory across weeks
relationship between age and memory performance are pre-
sented in Figure 2. Memory scores as a function of age and
retention interval are shown in Figure 3.
ANOVA with 3 (age groups) 3 2 (test times) for CVMT
yielded significant main effects of age group @F~2,67! 5
15.972, p , .0001] and test time @F~1,67! 5 25.800, p ,
.0001], but no significant Test Time 3 Age Group inter-
action @F~2,67! 5 1.714, p 5 .188]. Likewise, ANOVA
with 3 (age groups) 3 2 (test times) for Rey-Osterrieth
yielded significant main effects of age group @F~2,67! 5
19.529, p , .0001] and test time @F~1,67! 5 419.017, p ,
.0001], but no significant Test Time 3 Age Group inter-
action @F~2,67! 51.239, p 5 .296].
Pearson correlations between age and volumetric measures
and memory performance and volumetric measures are
Fig. 2. Regression plots showing the relationship between age and visual memory, recall and recognition, at different
retention intervals. In no cases did a non-linear component add significantly to the amount of explained variance.
CVMT learning589.724 2.206x, R25.26 ~p , .0001), CVMT 30 min recognition51.9712.042x, R25.23 ~p ,
.0001), CVMT 75 days recognition 5 6.601 2 .055x, R25 .36 ~p , .0001), Rey-Osterrieth 5 min recall 5 31.110 2
.173x, R25 .25 ~p , .0001), Rey-Osterrieth 20 min recall 5 30.864 2 .179x, R25 .26 ~p , .0001), Rey-Osterrieth
75 day recall 5 13.662 2 .143x, R25 .37 ~p , .0001).
Fig. 3. Relationship between memory scores and age group.
A.M. Fjell et al.
shown in Table 2. Scatterplots illustrating the relationship
between neuroanatomical volume, age, and memory func-
tion are presented in Figure 4 and 5. Cortical, white matter,
and hippocampal volume, in right and left hemisphere,
showed several significant correlations with memory scores.
Although there was a slight tendency for right hemisphere
volumes to be more strongly correlated with the memory
measures, the coefficients were almost identical. However,
no significant correlations between neuroanatomical vol-
umes and the ratio scores were identified. Regression analy-
ses showed that the relationship between age and right
hemisphere hippocampal volume @y521.19710.09353x
~p , .01! 2 0.001142x2~p , .01!; F~2,42! 512.92, p ,
.0001, R25 .39] and white matter volume @y 5 21.003 1
0.08633x ~p , .05! 2 0.001083x2~p , .01!; F~2,41! 5
13.53, p , .0001, R25 .40] were best explained by a cur-
vilinear function. Thus, we could not use partial correla-
tions or multiple linear regressions to isolate the relation-
ship between the neuroanatomical volumes and memory
performance from the influence of age. The neuroanatom-
ical volumes and the different memory variables were all
related in a linear fashion.
To investigate the unique contributions from cortical and
hippocampal volume to memory function, we performed
multiple regression analyses with each of the memory vari-
ables in turn as dependent variables and cortical and hippo-
campal volume simultaneously as independent variables.
For CVMT learning and CVMT 75 days recognition, cor-
tical volume gave unique significant contributions to the
amount of explained variance, while hippocampal volume
contributed uniquely in the case of Rey-Osterrieth 75-day
recall and marginally for Rey-Osterrieth learning (p5.055).
In the rest of the analyses, none of the volumes contributed
significantly independently of the other.
Table 2. Pearson correlations between volumetric brain measures of the right (RH) and left (LH) hemisphere, age,
and visual memory tests
RH cortex RH WM RH hippocLH cortexLH WM LH hippoc
CVMT false alarm
CVMT 30 min
CVMT 75 days
CVMT total030 min ratio
CVMT 30 min075 days ratio
Rey-Osterieth 20 min
Rey-Osterieth 75 days
Rey-Osterieth learning020 min ratio
Rey-Osterieth 20 min075 days
Italic characters mean p ,.05, underlined characters means that the Bonferroni corrected p-values are , .05 (actual p-values , .001).
Fig. 4. Regression plots showing the relationship between right hemisphere hippocampal, cortical, and white matter
volume and age. The relationships between age and hippocampal and white matter volume were best described as
non-linear: Hippocampus521.1971.09353x20.001142x2, R25.39 ~p , .0001), cortex52.10520.03848x, R25
.69 ~p , .0001), white matter 5 21.003 1 0.08633x 2 0.001083x2, R25 .40 ~p , .0001).
Neuroanatomy and visual memory across weeks
Fig. 5. Regression plots showing the relation-
ships between visual memory at two different
retention intervals (20–30 min or 75 days) and
right hemisphere cortical volume (left col-
umn) and right hemisphere hippocampal
volume (right column). In no cases did the
introduction of a non-linear component (rep-
resented by the dashed line) add significantly
to the amount of explained variance.
A.M. Fjell et al.
Are Longer Retention Intervals More
Detrimental for the Memory Performance
of Older People Than Younger?
For both visual recall and visual recognition, the correla-
tions with age were stronger at retention interval over weeks
than over minutes. Further, the correlation between age and
the ratio between CVMT learning and 30-min recognition
was significant, as was the correlation between Rey-
Osterrieth 20-min recall and 75-day recall, explaining about
10% of the variance. This gives some indication that the
rate of forgetting may be different at different ages. How-
ever,ANOVAs failed to show significant interaction effects
between age and retention interval for either CVMT or for
Rey-Osterrieth. This disconfirms the hypothesis that older
people have a steeper rate of forgetting than younger, and
does not correspond to the finding by Tombaugh and Hub-
ley (2001) with auditory verbal material. Previous studies
using shorter retention intervals have found that recogni-
tion abilities generally are preserved in older adults (Ander-
son et al., 1998; Raz et al., 1997), and that age-related
memory problems may be attributed to retrieval deficits,
cue is the to-be-remembered material itself. Tombaugh and
Hubley (2001) only found the age-acceleration in forget-
ting for a free recall format and suggested that frontally
based retrieval deficits may explain the accelerated rate of
forgetting over longer time intervals identified in their study.
The present results indicate that older people are able to
store information over long time intervals without decay
from the long-term memory store. Thus, the memory prob-
lems that older people experience in everyday life are hardly
caused by actual decay from long-term memory and should
be attributed to other cognitive processes (e.g., retrieval
skills).As a consequence, reduction in memory capabilities
by neuropsychological tests with retention intervals of less
than an hour, at least with regard to the kind of visually
Can Variations in Hippocampal Volume
Explain Variations in Visual Memory
sphere structures are theoretically more related to visual
memory processing, and the correlations were similar, we
will restrict the discussion to right hemisphere volumes only.
Right hemisphere hippocampal volume generally corre-
lated higher with the Rey-Osterrieth variables than the
CVMT variables, reaching r 5 .47 in case of the 75-day
recall task, thus explaining up to 22% of the variance. This
is the most demanding of all the memory tasks, and suc-
cessful performance requires the participant to be able to
bered according to semantic or phonological content over
long time intervals. Also, the test requires visuospatial and
visuomotor integration for successful performance, which
makes it more complex than the CVMT where performance
is based on recognition alone. From our data, it is reason-
able to conclude that hippocampal volume covaries with
the ability to perform such demanding memory tasks. How-
ever, while hippocampal volume predicted visual recall after
75 days, this was not the case for the recognition task. From
electrophysiological animal studies it has been indicated
that hippocampal neurons provide a possible substrate for
recognition memory processes involving spatial and other
associative information, and is less important for familiar-
ity discrimination of individual items (Brown and Aggle-
ton, 2001). Such findings point to a critical role for
hippocampus in recognition memory when the familiarity
judgment depends on associations between items rather than
on the individual items themselves, where perirhinal cortex
probably exert more influence. In a recall task as the Rey-
Osterrieth complex figure test, the challenge is twofold.
One has to remember the individual parts constituting the
figure, and one has to remember the spatial relationship
between these parts. Thus, structures within the hippocam-
pus are probably critical for successful performance of such
tasks. The CVMT task, requiring recognition of visually
presented meaningless material, does not involve spatial
relationships between individual figures or drawings. Thus,
other variables than hippocampal size may be more rele-
vant for this kind of memory task. An argument for the
view that hippocampus in more important in recall tasks in
general than in recognition tasks is implied in the fMRI
study by Eldridge et al. (2000). They showed that activity
in the hippocampus increased only when retrieval was
accompanied by conscious recollection of the learning epi-
sode, and not for items recognized based on familiarity or
in a recognition task, it is reasonable to suggest that recog-
nition based on both familiarity and recollection has more
in common with recall than recognition based on familiar-
ity alone. Thus, the results in the present study may be
interpreted within such a framework.
Further, the present findings show that neuroanatomical
volumetric changes in hippocampus with increasing age
generally are not more related to memory performance than
the global reductions of cortical grey matter. One explana-
tion may be that processes important for successful mem-
as the frontally based retrieval system known to be vulner-
able to normal age changes (e.g., Stebbins et al., 2002;
Ungerleider, 1995), or the associational neocortical sites
which are active during memory acquisition (Zola-Morgan
& Squire, 1996). For the present recognition tasks, cortical
volume is actually a more powerful predictor of memory
performance than is hippocampal volume. Wicket et al.
(2000) state that human abilities generally are more strongly
Neuroanatomy and visual memory across weeks
related to gross neuroanatomical volumetric measures than
more specific ones. In light of this, our finding is not sur-
prising. Further, the age-related reduction in cortical
volume is much more prominent than the reduction in hip-
pocampal volume. Nearly 70% of the variance in cortical
volume is explainable by age alone, while hippocampal vol-
ume is much less related to age than cortical volume, with
about 22% shared variance.These results are comparable to
those of previous studies (e.g., Hackert et al., 2002; Schuff
et al., 1999; Tisserand et al., 2000). Since performance on
the various memory tests also is reduced with increasing
age, it is obvious that the relationships between the volu-
metric and the neuropsychological parameters at least partly
depend on the variance induced by age. This does not inval-
idate the relationship between hippocampal and cortical vol-
ume and memory performance, but it implies that the
relationship is quite dependent on the variance induced by
age. This may also contribute to the present finding that
cortical volume is more correlated with memory perfor-
mance than is hippocampal volume.
Volume of hippocampus and white matter exhibit a non-
linear relationship with age. This is not the case for the
memory tests, which all relate linearly to age. Thus, the two
classes of measures relate to age differently, which makes it
more difficult to understand the relationship between them.
with increasing age throughout the adult life-span, while
some of the neuroanatomical volumes (hippocampus and
white matter) increases with increased age at first, before
the reduction sets in.
The present study has demonstrated several relationships
between memory function and neuroanatomical volume.
However, the ones that most strictly index rate of forget-
ting, are the ratio scores. None of the ratio scores showed
significant correlations with the neuroanatomical volumet-
ric measures. Thus, while processes in right hemisphere
hippocampus may be crucial for consolidation of visual
material in long-term memory, this is not reflected in gross
Limitations of the Present Study
Limitations of the present study exist, mainly that the sam-
ple size, especially for the volumetric analyses, is relatively
small. This will of course reduce the statistical power of the
analyses.Alarger sample would also have allowed analyses
at different retention intervals to more precisely pinpoint
differences in memory capabilities between participants at
different ages. Further, a relationship (r 5 2.31, p , .05)
between age and retention interval for the extended mem-
ory tests exists. The older participants may therefore have
gained an advantage in responding faster than the youngest.
However, the differences in retention interval are probably
too small to explain the lack of difference between the youn-
gest and the two older groups, and the difference was not
significant in an ANOVA analysis. Future research with a
larger sample size is needed to confirm the present findings
across systematically varied retention intervals.
Support for this research was provided by the Norwegian Research
Council, the Institute of Psychology at the University of Oslo, the
National Institutes of Health (R01-NS39581, R01-RR16594,
P41-RR14075, and R01-RR13609), the Mental Illness and Neuro-
science Discovery (MIND) Institute, and in part by the Bio-
medical Informatics Research Network Project (BIRN, http:00
www.nbirn.net), which is funded by the National Center for
Research Resources at the National Institutes of Health (NCRR
BIRN Morphometric Project BIRN002).The two first authors have
contributed equally to the present paper, and their names are pre-
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