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Long-term memory (LTM) problems are associated with many psychiatric and neurological illnesses and are commonly measured using free and cued recall tasks. Although LTM has been linked with biologic mechanisms, the etiology of distinct LTM tasks is unknown. We studied LTM in 95 healthy female twin pairs identified through birth records in the state of Missouri. Performance on tasks of free recall of unrelated words, free and cued recall of categorized words, and the vocabulary section of the Wechsler Adult Intelligence Scale (WAIS-R) were examined using structural equation modeling. Additive genetic and unique environmental factors influenced LTM and intelligence. Free recall of unrelated and categorized words, and cued recall of categorized words, were moderately heritable (55%, 38%, and 37%). WAIS-R vocabulary score was highly heritable (77%). Controlling for verbal intelligence in multivariate analyses of recall, two components of genetic influence on LTM were found; one for all three recall scores and one for free and cued categorized word recall. Recall of unrelated and categorized words is influenced by different genetic and environmental factors indicating heterogeneity in LTM. Verbal intelligence is etiologically different from LTM indicating that these two abilities utilize different brain functions.
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Twin Research and Human Genetics Volume 9 Number 5 pp. 623–631
L
ong-term memory (LTM) problems are associated
with many psychiatric and neurological illnesses
and are commonly measured using free and cued
recall tasks. Although LTM has been linked with bio-
logic mechanisms, the etiology of distinct LTM tasks
is unknown. We studied LTM in 95 healthy female
twin pairs identified through birth records in the
state of Missouri. Performance on tasks of free
recall of unrelated words, free and cued recall of cat-
egorized words, and the vocabulary section of the
Wechsler Adult Intelligence Scale (WAIS-R) were
examined using structural equation modeling.
Additive genetic and unique environmental factors
influenced LTM and intelligence. Free recall of unre-
lated and categorized words, and cued recall of
categorized words, were moderately heritable (55%,
38%, and 37%). WAIS-R vocabulary score was
highly heritable (77%). Controlling for verbal intelli-
gence in multivariate analyses of recall, two
components of genetic influence on LTM were
found; one for all three recall scores and one for free
and cued categorized word recall. Recall of unre-
lated and categorized words is influenced by
different genetic and environmental factors indicat-
ing heterogeneity in LTM. Verbal intelligence is
etiologically different from LTM indicating that these
two abilities utilize different brain functions.
Disturbances of memory are a feature or consequence
of a variety of psychiatric and neurological illnesses
such as Alzheimer’s disease, schizophrenia, alcohol
abuse, depression, and head injury. Despite a great
deal of research addressing the role or impact of
memory loss on psychopathology, many basic issues
in the establishment and maintenance of memories
are unresolved.
Long-term, or episodic, memory allows for the
recording and storage of experiences over time
(Roediger et al., 2002). Long-term memory (LTM) is
thought to arise from increased and lasting changes in
synapse plasticity, with several studies in animals
implicating the role of the cAMP chain (Goda, 1995).
Additionally, the proteins brain-derived neurotrophic
factor (BDNF) and tissue plasminogen activator (tPA)
have been associated with long-term potentiation in
hippocampal cells, a mechanism thought to mimic the
process of LTM (Pang et al., 2004). Taken together,
these biologic and cellular level processes suggest a
potential role of genetics in protein regulation and
thus, LTM performance. Supporting this concept,
examination of LTM in subjects at high genetic risk
for Alzheimer’s disease indicated that carriers of the
APOE e4 allele are at increased risk for LTM decline
before being classified as cognitively impaired
(Caselli et al., 2004).
Twin studies have consistently demonstrated a
low to moderate influence of genetic effects on
general measures of memory. Heritability estimates
range from 17% to 68%, with the task(s) used to
assess memory performance and subject characteris-
tics (age, source population) hypothesized to effect
reported values (Alarcon et al., 1998; Finkel et al.,
1995a, 1995b; Reynolds et al., 2005; Thapar et al.,
1994). Few studies have specifically examined the
influence of genetics on LTM. In a sample of older
adult twins, the California Verbal Learning Test
(CVLT) was subjected to principal components
analysis. Free and cued word recall scores were asso-
ciated with a combined verbal learning and LTM
factor and found to be moderately heritable (56%;
Swan et al., 1999). However, results from a study of
twins discordant for schizophrenia suggests that
LTM may also be influenced by nongenetic factors
(Cannon et al., 2000).
Separate free and cued recall tasks are often used
to measure LTM ability and additional work indicates
that these tasks may measure different abilities.
Results from dual task studies suggest that overall
recall on free recall tasks is generally not affected by a
simultaneous task while performance on cued recall
tasks decreases substantially (Craik et al., 1996;
Fernandes & Moscovitch, 2000; Naveh-Benjamin et
al., 1998; Naveh-Benjamin & Guez, 2000). Only one
study, which used a different concurrent, random
Genetic Influences on Free and Cued
Recall in Long-Term Memory Tasks
Heather E. Volk,
1
Kathleen B. McDermott,
2
Henry L. Roediger III,
2
and Richard D. Todd
3
1
Doctoral Program in Public Health Studies, Saint Louis University School of Public Health, Saint Louis, Missouri, United States of America
2
Department of Psychology,Washington University, Saint Louis, Missouri, United States of America
3
Departments of Psychiatry and Genetics,Washington University School of Medicine, Saint Louis, Missouri, United States of America
Received 8 February, 2006; accepted 14 July, 2006.
Address for correspondence: Richard D. Todd, Department of
Psychiatry, Box 8134, Washington University School of Medicine,
660 South Euclid Ave., Saint Louis, MO 63110, USA. E-mail:
toddr@psychiatry.wustl.edu
stimulus task, indicated a similar decline in free recall
performance (Rohrer & Pashler, 2003). Despite these
decreases in cued recall performance, free recall is
thought to be the more difficult and resource demand-
ing of the two (Craik & McDowd, 1987). As
demonstrated by Park et al. (1996), a greater amount
of variance in free recall score was explained by speed
and working memory than for the cued recall score.
Conceptual repetition (following the target or cue
with an associated idea) has been found to affect free
recall with no effect on cued recall (McDermott &
Roediger, 1996).
To our knowledge, no study has examined etio-
logic influences on free and cued recall tasks
separately. Here we assess genetic and environmental
influences on free and cued recall in LTM using data
from a population-based twin sample.
Materials and Methods
Subjects
Fe
male–female twin pairs who met study criteria
were randomly selected from the Missouri
Adolescent Female Twin Study (MOAFTS).
MOAFTS is a large prospective twin study designed
to examine factors contributing to risk for alco-
holism in young women and adolescents (Heath et
al., 1994). Participants were identified through a
computerized database recording all live-birth twin
pairs born in Missouri between 1968 and 1997. A
semistructured diagnostic interview was given over
the telephone to all participants (Bucholz et al.,
1994). Pairs were considered for inclusion in the
present study if they did not live together, lived in
the United States, had no history of seizure disorder,
psychosis, autism or mental retardation, were not in
special education classes, had no known memory
problems, were not currently participating in
another study, and were not currently taking med-
ication.
A total number of 161 female-female twin pairs
were contacted for enrollment in this study. Of the
161 contacted 52 pairs were ineligible for this study.
Of these 52 pairs, 40 were participating in another
study, eight were living together at time of inter-
view, two were living overseas, and two could not
be contacted. One hundred and nine pairs were
further screened for enrollment in the study. Five
pairs were excluded based on current medication
use. Of the remaining 104 pairs, zygosity could not
be reliably determined for seven pairs; therefore,
memory testing was completed on 97 twin pairs. On
the day of testing, all participants were asked about
alcohol and illicit drug use that day; all denied
current drug use or intoxication. Two twin pairs
were subsequently excluded for cheating (one was
heard writing down word lists and another was
heard to be getting vocabulary word definitions
from someone else in the room). This analysis uti-
lizes data from 95 twin pairs (88 monozygotic [MZ]
and 102 dizygotic [DZ] individuals) aged 18 to 24
years (mean 21.37 ± 1.44 years).
Measures of Long-Term Memory
Subjects enrolled in the study were contacted by tele-
phone and participated in a three part series of tasks;
the first two of which assessed LTM abilities, and the
third assessed verbal intelligence. Instructions for
each task were administered immediately prior to the
task. For the free recall and cued recall tests, subjects
were instructed to attempt to recall as many words
as possible (in any order they wished) but not to
guess; that is, they were asked to be certain that all
words they recalled had indeed been read to them.
Word lists were pretested on undergraduate students
prior to beginning the study to ensure the absence of
floor or ceiling effects in recall. These lists were then
recorded as computer sound files equalized for
volume in a Midwestern female voice and used
throughout the study.
In the first task, subjects heard a recording of four
sets of 15 unrelated words at the rate of one word
every 2 seconds. Words within the lists were common
words (mean frequency 114.5 words per million,
mean length of 5.15 letters, ranging from one to three
syllables; Kucera & Francis, 1967). After each set of
15 words, subjects recalled as many words from the
list as possible in 1 minute. We will refer to this task
as the free recall of unrelated words.
The second task consisted of two 30 word lists,
each comprised of five words from six semantic cate-
gories taken from the Battig and Montague norms
(Battig & Montague, 1969). Words were 5.7 letters in
length on average, had a mean frequency of 32 words
per million, and a mean of 1.8 syllables in length.
Again, words were presented at the rate of one word
every 2 seconds. Following presentation of the first
30-word list, subjects were first asked to recall as
many of the words as possible in 2 minutes (free recall
of categorized words). Subsequently, a single category
name was provided to cue recall of grouped words
and subjects were asked to recall as many words in
that category as possible in 15 seconds (cued recall of
categorized words). This process was repeated for
each of the six categories, and then the entire process
was repeated for the second 30-word list.
Finally for the third task, subjects were given a
5-minute vocabulary test using 19 words from the
verbal performance section of the Wechsler Adult
Intelligence Scale (WAIS-R). The subject was given
increasingly difficult words until three words in a row
were missed. The number of correct words was then
transformed into the standardized WAIS vocabulary
score for subject age. Separate vocabulary words were
used for each twin.
Statistical Analysis
The total number of correctly recalled words was cal-
culated for each task in order to minimize the total
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Twin Research and Human Genetics October 2006
Heather E. Volk, Kathleen B. McDermott, Henry L. Roediger III, and Richard D. Todd
amount of variance for each task. Free and cued recall
scores were summed separately in the second task.
Four summary scores — free recall of unrelated
words, free recall of categorized words, cued recall of
categorized words, and the standardized WAIS vocab-
ulary score — were examined. Biometric models were
used to examine genetic and environmental influence
on the four scores described above. The per cent of
total variance contributed by additive genetic (A),
shared environmental (C), and unique environmental
(E) factors was calculated using structural equation
modeling. We assessed model goodness-of-fit using the
likelihood function, which can be compared using a
chi-square change statistic each time a parameter is
added to or dropped from the base ACE model.
Significant improvement from the base model can then
be assessed by comparing the calculated chi-square
statistic to the critical value for the appropriate
number of degrees of freedom difference between the
two models. We also compared Akaike information
criteria (AIC) between models to determine the most
parsimonious model which fit the data. The AIC is
calculated from the –2 log-likelihood values plus 2
times the number of parameters in the model (Akaike,
1974). The model with the lowest AIC value can thus
be determined to be the most parsimonious model.
Age was added to the model as a covariate for all four
scores. WAIS vocabulary score was included as a
covariate in the model for each of the three word-
recall scores.
Bivariate and multivariate analyses assessed genetic
and environmental influences using a Cholesky
decomposition model for the three word-recall
summary scores and WAIS verbal performance score.
Significant change in model fit from the base ACE
Cholesky decomposition model was determined as
described above. All analyses were carried out using
Mx, a structural equation modeling program devel-
oped for the analysis of twin data (Neale et al., 2002).
Results
Description of Sample,
Summary of Performance on Recall Tasks
This sample contains data from 95 female twin pairs
(88 MZ and 102 DZ individuals) aged 18 to 24 years
(mean 21.37 +
1.44 years) attained from the
MOAFTS. Subjects had a mean normalized WAIS
score of 8.10 (± 2.27). The average number of words
correct for each list of the two LTM tasks is reported
in Table 1. Similar trial means with few significant dif-
ferences between trials were found, supporting
aggregation of correct words across trials.
Twin correlations for WAIS score and each
memory task are presented in Table 2. For all mea-
sures, the correlation between MZ twins is greater
than that for DZ twins. However, the DZ correlation
is greater than half the MZ correlation for WAIS score
and free recall of unrelated words suggesting that both
genes and the shared family environment both explain
familial resemblance. In contrast, these correlations,
though moderate, suggest that resemblance in the
recall of free and cued unrelated words may be influ-
enced largely by genetic effects.
Genetic Analysis of Long-Term Memory
Univariate Models
As expected, model fitting demonstrated a substantial
genetic influence on the WAIS vocabulary score.
Dropping A from the model resulted in a significant
deterioration of fit while dropping C did not signifi-
cantly alter model fit. Thus, an AE model was chosen
as the best fitting model (Table 3). Adding age or
sibling interaction as a covariate to the model did not
significantly improve model fit. Additive genetic
factors contributed 78% and the unique environment
contributed 22% of the variance in vocabulary score.
The best model for the uncategorized word free
recall was an AE model without sibling interaction or
covariates (age and WAIS vocabulary score). Dropping
C from the base model did not significantly affect
625
Table 1
Descriptive Characteristics of Sample and Long-Term Memory Scales
Mean ±
SD
Significance Test vs. List 1
for Each Section
Age 21.4 ± 1.44
WAIS Verbal Score 8.2 ± 2.24
Uncategorized Words
Free Recall Summary Score 32.9 ± 9.13
List 1 8.3 ± 2.41
List 2 8.3 ± 2.65
p
= .67
List 3 7.9 ± 2.91
p
= .0039
List 4 8.2 ± 3.00
p
= .20
Categorized Words
Free Recall Summary Score 60.8 ± 16.6
List 1 19.9 ± 6.27
List 2 21.0 ± 5.91
p
= .0013
List 3 19.5 ± 6.3
p
= .39
Cued Recall Summary Score 64.8 ± 12.7
List 1 21.0 ± 5.91
List 2 22.3 ± 4.62
p
< .0000
List 3 21.2 ± 4.81
p
= .46
Note: * All significance tests conducted at the alpha = .05 level
Table 2
Phenotypic Correlations by Zygosity
MZ DZ
WAIS Score .66 .54
Uncategorized Free Recall .56 .34
Categorized Free Recall .46 –.04
Categorized Cued Recall .41 .10
Note: MZ = monozygotic twin, DZ= dizygotic twin
Twin Research and Human Genetics October 2006
Twin Study of Long-Term Memory
model fit while dropping A slightly decreased the AIC.
As demonstrated in Table 3, additive genetic factors
accounted for 55% and unique environmental factors
accounted for 45% of the variance in total number of
correctly recalled random words.
Model fitting results showed the AE model with
WAIS vocabulary score included as a covariate to be
the best fitting model for both free and cued recall of
categorized word lists. Dropping C from the model
did not significantly alter model fit from the base ACE
model as the C term was very small. Dropping A from
the model did not significantly change model fit,
although the AIC indicated an AE model as the most
parsimonious in each case. Additive genetic factors
accounted for 38% of the variance in free recall and
37% of the variance in cued recall of categorized
words (Table 3).
Bivariate Models
As the WAIS score was found to be an important
covariate for free and cued recall of categorized
words, bivariate analyses were conducted using
Cholesky decomposition models. For all analyses, an
ACE Cholesky decomposition was used as the base
model. Additive genetic and unique environmental
factors were found for the WAIS score and both free
recall of uncategorized words and free and cued recall
of categorized words. As the shared environment was
not found to contribute significantly to the variance in
the WAIS score or the recall score in the univariate
analyses above, the C terms were dropped from each
bivariate model resulting in a more parsimonious
model (Table 4).
Reducing the models further suggested different
underlying components accounting for the variation in
the WAIS score and word recall. A model including
specific genetic and specific unique environmental
terms best fit the data when examining the WAIS
score and uncategorized free recall (Table 4). These
distinct genetic factors accounted for 77% and 55%
of the variance in WAIS score and free recall of
uncategorized words, respectively (Table 5).
In contrast, a model including specific genetic and
overlapping unique environmental factors best
explained the variance in the WAIS score and the free
and cued recall of categorized words (Table 4).
Specific genetic factors accounted for 74%, 31% and
35% of the variance in WAIS score, cued categorized
word recall, and free categorized word recall, respec-
tively (Table 5). A unique environmental factor
contributed to the covariation of these tasks (27%
WAIS, 7% cued recall, 3% free recall) while a second
unique environmental factor specific to cued catego-
rized word recall (62%) or free categorized word
recall (62%) explained more variance in these tasks.
A bivariate model was then constructed to
examine overlapping influences on the free and cued
recall of categorized words. An ACE Cholesky
decomposition model was first fit to the data. Shared
environmental factors were then dropped from the
model resulting in a more parsimonious model.
Further reduction of the model indicated that a single
additive genetic factor accounted for 37% of the
variance in both free and cued recall. The first
unique environmental influence accounted for 62%
of the variance in free recall and 44% of the variance
in cued recall while the second unique environmental
factor contributed 19% of the variance to cued recall
score (Table 5).
In order to examine overlapping influences on the
three memory tasks, a multivariate Cholesky decom-
position model evaluated the number of correctly
recalled words from task 1 (free recall of uncatego-
rized words) and task 2 (free and cued recall of
categorized words). A model including additive
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Twin Research and Human Genetics October 2006
Heather E. Volk, Kathleen B. McDermott, Henry L. Roediger III, and Richard D. Todd
Table 3
Univariate Models for WAIS and Long-Term Memory Test Scores
Model A
2
C
2
E
2
–2LL
df
AIC
WAIS Score ACE .65 .13 .23 801.97 186 807.97
AAEE
.78 .22 802.10 187 806.10
CE .55 .45 810.08 187 814.08
Uncategorized Free Recall ACE .41 .13 .46 1356.40 186 1362.40
AAEE
.55 .45 1356.63 187 1360.63
CE .43 .56 1358.18 187 1362.18
Categorized Free Recall* ACE .38 .93x10
-5
.62 1592.80 185 1598.80
AAEE
.38 .62 1592.80 186 1596.80
CE .23 .77 1596.34 186 1600.34
Categorized Cued Recall* ACE .37 0.66x10
-5
.63 1485.32 185 1491.32
AAEE
.37 .63 1485.24 186 1489.24
CE .25 .75 1487.69 186 1491.69
Note: *WAIS Score is included as a covariate for categorized free and cued recall models. Bolded model indicates best fit. All comparisons were made to the saturated (ACE)
model. A = additive genetic, C = shared environment, E = unique environment, AIC = Akaike information criteria,
df
= degrees of freedom.
genetic and unique environmental factors best
explained variance in these three tasks (Table 4). The
first additive genetic factor contributed 56% of the
variance in the free recall of uncategorized words,
28% of the variance in the free recall of categorized
words and 29% of the variance in the cued recall of
categorized words (Table 5).
Approximately 6% of the variance in the free and
cued recall of categorized words was explained by a
second additive genetic factor, while the third
accounted for 1% of the variance in the cued recall
of categorized words alone. Examination of unique
environmental factors indicated that a factor influ-
encing all three scores accounted predominantly for
variance in uncategorized free recall score (45%),
while a second unique environmental factor con-
tributed similar amounts of variance to categorized
free and cued recall scores (48% and 31% respec-
tively). A third unique environmental factor also
accounted for 18% of the variance in the categorized
cued recall score.
Since we found that the WAIS score was an
important covariate of free and cued categorized
word recall in the univariate analyses, we also exam-
ined the contribution of genetic and environmental
factors on the free and cued recall of categorized
words (part 2) and the WAIS score. The first additive
genetic factor contributed 40% of the variance in the
free and cued recall of categorized words and only
6% of the variance in the WAIS score. A second
additive genetic factor primarily explained variance
in the WAIS score (55%) and a small portion of that
in cued recall of categorized words (2%). The third
additive genetic factor was specific to the WAIS score
627
Table 4
Bivariate and Multivariate Models for WAIS and Long-Term Memory Test Scores
Working Model Comparison –2LL
df
Number Chi-square
df
AIC
Model Parameters change change
WAIS and Uncategorized Free Recall ACE 2155.79 369 11 2177.79
AE ACE 2157.30 372 8 1.51 3 2173.30
CE ACE 2162.51 372 8 6.72 3 2178.51
Specific A, E AE 2157.53 373 7 0.23 1 2171.53
A, Specific E AE 2157.79 373 7 0.49 1 2171.79
SSppeecciiffiicc AA,, SSppeecciiffiicc EE
AE 2158.73 374 6 1.43 1 2170.73
WAIS and Categorized Free Recall ACE 2394.20 369 11 2416.20
AE ACE 2394.87 372 8 0.67 3 2410.87
CE ACE 2405.20 372 8 11.0 3 2421.20
SSppeecciiffiicc AA,, EE
AE 2395.54 373 7 0.67 1 2409.54
A, Specific E AE 2396.19 373 7 1.32 1 2410.19
Specific A, Specific E A, Specific E 2398.98 374 6 2.79 1 2410.98
WAIS and Categorized Cued Recall ACE 2289.87 369 11 2311.87
AE ACE 2287.39 372 8 2.48 3 2303.39
CE ACE 2297.19 372 8 7.37 3 2313.19
SSppeecciiffiicc AA,, EE
AE 2288.21 373 7 0.82 1 2302.21
A, Specific E AE 2292.52 373 7 5.13* 1 2306.52
Categorized Free and Cued Recall ACE 2789.99 369 11 2811.99
AE ACE 2791.23 372 8 1.24 3 2807.23
CE ACE 2793.63 372 8 3.64 3 2809.63
SShhaarreedd AA,, EE
AE 2791.41 373 7 0.18 1 2805.41
Uncategorized Free Recall, ACE 4029.43 549 21 4071.43
Categorized Free and Cued Recall
AAEE
ACE 4029.32 555 15 0.11 6 4059.32
2A,E AE 4031.61 556 14 2.29 1 4059.61
Categorized Free Recall, ACE 3573.74 549 21 3615.74
Categorized Cued Recall, WAIS AE ACE 3575.32 555 15 1.58 6 3605.32
AA,, 11 sshhaarreedd EE,,
AE 3576.21 557 13 0.89 2 3602.21
22 ssppeecciiffiicc EE
2A, 1 shared E, A, 1 shared E, 3582.84 599 11 6.624* 2 3604.84
2 specific E 2 specific E
Note: Bolded model indicates best fit. A = additive genetic, C = shared environment, E = unique environment,
df
= degrees of freedom, AIC = Akaike information criteria.
*statistically significant at
p
= .05.
Twin Research and Human Genetics October 2006
Twin Study of Long-Term Memory
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Twin Research and Human Genetics October 2006
Heather E. Volk, Kathleen B. McDermott, Henry L. Roediger III, and Richard D. Todd
Table 5
Path Values for Bivariate and Multivariate Models
Model A1 A2 A3 C1 C2 C3 E1 E2 E3
ACE WAIS .76 .43 .49
Uncategorized Free Recall .07 .54 .01 .48 .10 .68
AE WAIS .88—————.48——
Uncategorized Free Recall .06 .74 ————.07.67—
CE WAIS .75 .66
Uncategorized Free Recall .01 .67 .17 .72
Specific A, E WAIS .88 —————.48——
Uncategorized Free Recall .74 —————.10.67
A, Specific E WAIS .88 —————.47——
Uncategorized Free Recall .09 .74 —————.66
SSppeecciiffiicc AA,, SSppeecciiffiicc EE
WAIS .88—————.47——
Uncategorized Free Recall .74 —————.67
ACE WAIS .78 .40 .48
Categorized Free Recall .14 .60 .00 .00 —.10 .78
AE WAIS .88—————.47——
Categorized Free Recall .12 .61 ————.09.78—
CE WAIS .74 .67
Categorized Free Recall .02 .47 .18 .86
SSppeecciiffiicc AA,, EE
WAIS .88—————.48——
Categorized Free Recall .59 ————.10.67
A, Specific E WAIS .88 —————.47——
Categorized Free Recall .09 .74 —————.66
Specific A, Specific E WAIS .88 —————.47——
Categorized Free Recall .74 ————.00.67
ACE WAIS .88 .22 .47
Categorized Cued Recall .21 .00 .49 .00 .12 .84
AE WAIS .88—————.47——
Categorized Cued Recall .24 .59 ————.10.77—
CE WAIS .74 .67
Categorized Cued Recall .12 .48 .22 .84
SSppeecciiffiicc AA,, EE
WAIS .86—————.52——
Categorized Cued Recall .56 ————.26.79—
A, Specific E WAIS .89 —————.46——
Categorized Cued Recall .28 .58 —————.76
ACE Categorized Free Recall .61 .06 .79
Cued Recall .58 .00 .22 .00 .67 .41
AE Categorized Free Recall .61 —————.79——
Cued Recall .61 .11 ————.67.42
CE Categorized Free Recall .47 —.88
Cued Recall .47 .15 .76 .41
SShhaarreedd AA,, EE
Categorized Free Recall .61 ————.79.00
Cued Recall .61 ————.66.44
ACE Uncategorized Free Recall .65 .39 .67
Categorized Free Recall .52 .23 .17 .02 .42 .68
Cued Recall .56 .17 .00 .09 .14 00 .39 .56 .40
AAEE
Uncategorized Free Recall .74 —————.67——
Categorized Free Recall .53 .25 ————.42.69—
Cued Recall .54 .23 .11 .40 .56 .42
2A, E Uncategorized Free Recall .74 —————.67——
Categorized Free Recall .53 .25 ————.43.69—
Cued Recall .54 .23 ————.39.56.44
(17%; Table 5). Unique environmental factors were
found to influence both free recall and cued recall of
categorized words. Variance in the WAIS vocabulary
score was explained by a separate, specific unique
environmental factor (22%).
Discussion
Results from univariate structural equation models
indicate that the WAIS verbal score is highly influ-
enced by genetic factors. However, the free recall of
uncategorized words and both the free and cued recall
of categorized words were only moderately heritable.
The WAIS verbal score, used here as an indicator of
IQ, was found to be a covariate for both the free and
cued recall of grouped words, but not the uncatego-
rized word lists in part 1.
Bivariate model results support these findings and
further demonstrate that while free and cued recall are
largely influenced by the same factors, there appear to
be separate influences that also independently influ-
ence cued recall. Specific additive genetic and unique
environmental factors influenced the WAIS score and
free recall for both LTM tasks while the WAIS score
and cued categorized word recall were seen to have
the same unique environmental influence. This shared
factor demonstrates a marked difference between free
and cued recall processes and related constructs, such
as intelligence, which may influence performance on
tests of memory. This distinction is present regardless
of the type of words used in the free recall task.
However, the free and cued recall of categorized
words were influenced by similar additive genetic and
unique environmental factors, which indicates that the
free and cued recall of categorized words tap into
similar processes. The unique environmental factor
accounting for variance in the free and cued recall
score is likely the category name cue itself. The addi-
tional unique environmental factor related to cued
recall may come from the variance shared with IQ.
The free recall of uncategorized words, however, may
measure a different aspect of LTM. Multivariate
model results indicate that the factors accountable for
much of the variance in the free recall of uncatego-
rized words are less important in the recall of
categorized words. Additionally, the free recall of cate-
gorized words is influenced by genetic and
environmental variance in a similar manner as the
cued recall of these same lists rather than the free
recall of uncategorized lists. Again, the unique envi-
ronmental component of categorized word cued recall
may include a contribution from verbal IQ. This influ-
ence of verbal IQ may come from response to
classroom education, cognitive ability, or differential
social treatment, all of which could affect cue-related
word recall performance.
These results partially agree with those indicating
that free and cued recall are distinct processes (Tulving
& Pearlstone, 1966; Tulving & Psotka, 1971). The
larger estimated genetic effect on the free recall of
uncategorized words suggests that there may be an eti-
ologic difference in LTM. However, we also find that
these recall processes are influenced by the same
unique environmental factors. Additionally, our esti-
mates of heritability for IQ (as measured by WAIS
verbal score) and LTM components are consistent
with those from previous twin studies (Alarcon et al.,
1998; Finkel et al., 1995a, 1995b; Reynolds et al.,
2005; Thapar et al., 1994). The present analyses
extend this work by suggesting that etiologic differ-
ences in recall come from two sources. First, while
shared additive genetic and unique environmental
variance is present, these factors differentially affect
the recall of categorized and uncategorized words.
Thus, ability to recall different types of words may
involve different types of brain function. Second, our
results indicate shared variance between IQ and cate-
gorized word recall. In the bivariate models, the
shared variance between IQ and free and cued
629
Table 5 (CONTINUED)
Path Values for Bivariate and Multivariate Models
Model A1 A2 A3 C1 C2 C3 E1 E2 E3
ACE Categorized Free Recall .62 .00 .78
Cued Recall .61 .04 .14 .07 .66 .41
WAIS .18 .77 .02 .34 .17 .02 .06 .05 .47
AE Categorized Free Recall .62 —————.78——
Cued Recall .62 .13 ————.65.41—
WAIS .18 .72 .47 .05 .03 .47
AA,, 11 sshhaarreedd EE,, 22 ssppeecciiffiicc EE
Categorized Free Recall .63 —————.78——
Cued Recall .63 .13 ————.63.41—
WAIS .24.74.42—————.46
2A, 1 shared E, 2 specific E Categorized Free Recall .12 —————.99——
Cued Recall .09 .62 ————.72.31—
WAIS .69.59——————.41
Note: Bolded model indicates best fit. A = additive genetic, C = shared environment, E = unique environment.
Twin Research and Human Genetics October 2006
Twin Study of Long-Term Memory
categorized word recall is attributed to a unique envi-
ronmental factor indicating the potential for an
outside event or stimulus to influence these traits
jointly. However, in the multivariate model we find a
small amount of additive genetic variance in the WAIS
score explained by factors also related to categorized
word recall. Thus, processes measured by these tasks
may not be etiologically distinct. Application of these
results to neuroimaging studies may provide valuable
insight into the etiology of recall processes and enable
better understanding of LTM function in individuals
with disorders of memory.
This study is not without limitations. The analysis
was conducted on a sample of young adult females
and may not be generalizable to males or subjects of
younger or older age. However, estimates of genetic
effects here fall into the range reported earlier in older
samples of twins of both genders (Swan et al., 1999).
We may not have had sufficient power in our sample
to differentiate between more complex models.
However, this work is conducted on healthy individu-
als from the general population and may serve as an
introduction to future work on the study of the genet-
ics of specific memory tasks and processes.
Additionally, the WAIS verbal score was used here as a
proxy measure for a full IQ assessment. A more accu-
rate determination of IQ may have provided different
results. Finally, although the twins were screened for
major neurological, psychiatric, and learning disorders
we do not have specific measures of psychopathology
or neuroimaging data which may have provided addi-
tional insight into the unshared and environmental
causes of variation indicated in this study. Future
work integrating neurologic, psychiatric, and cognitive
assessments will aid in answering remaining questions
regarding shared etiologic influences.
These results provide a valuable insight into the
etiology of disorders of memory. If different genetic
influences underlie different parts of LTM, then it is
possible that different genes are also are implicated in
different memory-based disorders. The genetic varia-
tion underlying different forms of memory likely
differentially impacts psychiatric and neurological dis-
orders characterized by memory problems. This
information will help focus molecular genetic studies
for known heritable conditions, such as Alzheimer’s
disease, where specific types of memory are affected.
Additionally, this study underlines the need to use
genetically specific memory tasks when studying
familial disorders with memory problems. Memory
tasks which are influenced by genetic factors may be
more suited for diseases with a known genetic compo-
nent, like schizophrenia. Likewise, the effect of head
trauma on memory may be better assessed using a
memory test with a strong environmental influence. In
this manner, memory ability can be better assessed
leading to an increased understanding of the etiology
of debilitating illnesses associated with memory
impairment.
Acknowledgments
This work is supported by 1F31MH074272 (HEV)
and the Blanche F. Ittleson endowment fund. We
thank Endel Tulving, PhD for assistance in study
design, John Engel for data collection, and Andrew
Heath, DPhil for access to twins from the Missouri
Adolescent Female Twin Study.
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... There is plenty of evidence suggesting genetic basis of memory functions. First, substantial heritability of memory ability has been demonstrated in twins and family studies, which estimated the heritability of working memory or short-term memory (STM) to be 15%~72% [8][9][10] and long-term memory (LTM) to be moderately heritable (37%~55%) [11]. Using high-throughput singlenucleotide polymorphism (SNP) data, one recent study demonstrated SNP-based heritability for working memory being 31%~41% [12]. ...
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... Episodic memory, the conscious recollection of past experiences, is a complex polygenic phenotype (Rasch, Papassotiropoulos, & de Quervain, 2010). Twin and adoption studies have estimated the heritability for episodic memory to 30–60% (Finkel, Pedersen, & McGue, 1995; Johansson et al., 1999; Volk, McDermott, Roediger, & Todd, 2006), and genetic influences on cognitive abilities continue to be high in old age (McClearn, 2006; Plomin, Pedersen, Lichtenstein, & McClearn, 1994; Swan et al., 1999 ). Gene–gene and gene–environment interactions add to the high heterogeneity of cognitive performance . ...
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... The studies also employed tasks that have a strong memory component, making performance in them partly dependent on either long-term memory (previous exposure to and familiarity with the popular melodies; Drayna et al. 2001) or working memory (maintaining a memory representation of the preceding tone/melody and making a comparison against it; Mosing et al. 2014a). Therefore, the derived heritability estimates may reflect not only musical ability, but also the moderateto-high heritability of general cognitive capacity and memory (Deary et al. 2009;Lee et al. 2010;Volk et al. 2006). Indeed, Mosing et al. (2014b) found that there were phenotypic correlations between intelligence and SMDT performance and that the covariation between these variables could be explained by shared genetic influences. ...
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The Ss learned, on a single trial, lists of words belonging to explicitly designated conceptual categories. Lists varied in terms of length (12, 24, and 48 words) and number of words per category (1, 2, and 4). Immediate recall was tested either in presence or absence of category names as retrieval cues. Cued recall was higher than noncued recall, the difference varying directly with list length and inversely with number of items per category. This finding was interpreted as indicating that sufficiently intact memory traces of many words not recalled under the noncued recall conditions were available in the memory storage, but not accessible for retrieval. Further analysis of the data in terms of recall of categories and recall of words within recalled categories suggested two independent retrieval processes, one concerned with the accessibility of higher-order memory units, the other with accessibility of items within higher-order units.
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While genetic influences in schizophrenia are substantial, the disorder's molecular genetic basis remains elusive. Progress has been hindered by lack of means to detect nonpenetrant carriers of the predisposing genes and by uncertainties concerning the extent of locus heterogeneity. One approach to solving this complexity is to examine the inheritance of pathophysiological processes mediating between genotype and disease phenotype. Here we evaluate whether deficits in neurocognitive functioning covary with degree of genetic relationship with a proband in the unaffected MZ and DZ co-twins of patients with schizophrenia. Twin pairs discordant for schizophrenia were recruited from a total population cohort and were compared with a demographically balanced sample of control twin pairs, on a comprehensive neuropsychological test battery. The following four neuropsychological functions contributed uniquely to the discrimination of degree of genetic loading for schizophrenia and, when combined, were more highly correlated within MZ pairs than within DZ pairs, in both discordant and control twins: spatial working memory (i.e., remembering a sequence of spatial locations over a brief delay), divided attention (i.e., simultaneous performance of a counting and visual-search task), intrusions during recall of a word list (i.e., “remembering” nonlist items), and choice reaction time to visual targets. Together with evidence from human and animal studies of mediation of these functions by partially distinct brain systems, our findings suggest that there are multiple independently inherited dimensions of neural deficit in schizophrenia and encourage a search for genes contributing to quantitative variation in discrete aspects of disease liability. On tests of verbal and visual episodic memory, but not on the liability-related measures, patients were more impaired than their own MZ co-twins, suggesting a preferential impact of nongenetic influences on long-term memory systems.
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Cross-sectional reports suggest heritability of cognitive ability increases throughout adulthood. To investigate this hypothesis, quantitative genetic analyses were conducted on four measures of cognitive ability (verbal, spatial, perceptual speed, memory). Data from Minnesota and Swedish twin studies of aging were compared. Heritability estimates and the factor structure of cognitive abilities could be equated across younger twins (age, 27-50) and middle-aged twins (age, 50-65) from both studies, suggesting stability of heritability during adulthood. The heritability of 81% for a general cognitive factor confirmed earlier findings of high heritability in younger and middle-aged samples. Older Swedish twins (age, 65-85) demonstrated significantly lower heritability estimates for cognitive abilities (54%) and a significantly different factor structure of cognitive ability.