Psychology
2013. Vol.4, No.10, 771-775
Published Online October 2013 in SciRes (http://www.scirp.org/journal/psych) http://dx.doi.org/10.4236/psych.2013.410109
Husband-Wife Correlations in Neurocognitive Test Performance*
C. Thomas Gualtieri
North Carolina Neuropsychiatry Clinics, Chapel Hill, USA
Received June 20th, 2013; revised July 24th, 2013; accepted August 26th, 2013
Copyright © 2013 C. Thomas Gualtieri. This is an open access article distributed under the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the
original work is properly cited.
Spousal correlations are known to have a number of physical and mental characteristics, among which
general mental ability is one of the strongest. IQ tests have ordinarily been used in studies of assortative
mating, but in neurocognitive tests, less frequently. In this study, we examined spousal correlations in 76
husband-wife pairs using a computerized neuropsychological test battery. Significant spousal correlations
occurred in the two most highly g-loaded tests, shifting attention and symbol digit coding, but not in the
other tests or in any of the reaction time measures. The correlation between husbands and wives on the
neurocognitive index, a summary score based on the individual tests and analogous to the IQ score, was
even higher (r = .717). The pattern of spousal correlation described in IQ tests is thus replicated in a bat-
tery of neuropsychological tests. In a previous paper we reported positive correlations between first-degree
relatives who were administered the CNT battery, and which occurred primarily in tests of complex in-
formation processing, SDC and SAT (Hervey, Greenfield, & Gualtieri, 2012). In this paper, we note that
the same two tests contribute more strongly than any other tests to the high spousal correlation for neuro-
cognition. There is a certain symmetry, then, between the cognitive skills that play into spouse selection
and the cognitive skills that are inherited. A better word than symmetry might be inevitability. The find-
ings of these studies suggest that computerized neurocognitive testing is an appropriate tool for studies of
the genetics of cognition, that measures of processing speed are particularly salient and that the CNT is a
suitable instrument. The advantages of computerized neurocognitive tests like the CNT include speed and
efficiency, standard administration, suitability for repeated measures and elimination of scoring and tran-
scription errors. Tests that are Internet-based like the CNT are amenable to centralized data collection and
have flexibility in administration in different settings, even permitting the collection of data from remote
sources. In genetic studies of cognition, where large numbers of subjects are necessary, this technology
may also be inevitable.
Keywords: Computerized Test; Spousal Correlation; Processing Speed; General Mental Ability;
Assortative Mating
Introduction
Mating, among humans and in other species, is not a random
event. “Assortative mating” refers to the propensity of males
and females to choose mates non-randomly, on the basis of
shared or complementary characteristics. In studies of assorta-
tive mating, positive correlations between husbands and wives
have been discovered in various traits. Among these are physi-
cal attributes, like height (Hasstedt, 1995; Courtiol, Raymond,
Godelle, & Ferdy, 2010) and weight (Silventoinen, Kaprio,
Lahelma, Viken, & Rose, 2003); sociodemographic variables
like race (Risch et al., 2009) and language preference (Nagoshi,
Johnson, & Danko, 1990); ethnicity (Sebro, Hoffman, Lange,
Rogus, & Risch, 2010), economic status (Torche, 2010) and
education (Correia, 2003); and vulnerability to certain patho-
logical conditions (Negri, Melica, Zuliani, & Smeraldi, 1979;
Speakman, Djafarian, Stewart, & Jackson, 2007; Krueger,
Moffitt, Caspi, Bleske, & Silva, 1998; Norton et al., 2010; Van
Grootheest, Van den Berg, Cath, Willemsen, & Boomsma,
2008; Constantino & Todd, 2005; Konnov, Dobordzhginidze,
Deev, & Gratsianskiĭ, 2010).
Assortative mating appears to occur for personality traits
(Díaz-Morales, Quiroga Estévez, Escribano Barreno, & De-
lgado Prieto, 2009; Farley & Davis, 1977), but to a lesser de-
gree than that observed for physical traits, sociodemographic
traits, intelligence, and attitudes and values (Merikangas, 1982;
Epstein & Guttman, 1984).
Spousal correlation or “homogamy” is more evident in stud-
ies of cognitive traits than other psychological traits (Zonder-
man, Vandenberg, Spuhler, & Fain, 1977; Mascie-Taylor &
Gibson, 1979; Mascie-Taylor, 1989). Considering the various
dimensions by which cognition can be measured, the highest
spousal correlations are reported for general mental ability, or g.
IQ, for example, seems to have a higher spousal correlation (r =
about +.40) than any other behavioral trait and is higher than
most physical traits (e.g., height, r = +.30) (Mascie-Taylor,
1989; Jensen, 1998) (Nagoshi, Johnson, Yuen, & Ahern, 1986;
Nagoshi, Johnson, & Ahern, 1987). With respect to individual
*Acknowledgment/Financial Support: Financial support from NC Neuro-
p
sychiatry Attention & Memory Centers. Dr. Gualtieri is the
founder/developer of CNS Vital Signs, PA, an older version of the
CNT. The CNT is not a commercial property and is available at
www.ncneuropsych.com.

C. T. GUALTIERI
tests, for example the subtests of an IQ test battery, Jensen has
noted that the correlation for spouses is largely a matter of g;
that is, the degree to which cognitive tests show assortative
mating is highly correlated with the tests’ loadings on the g
factor.
As cognitive studies rely, with increasing frequency, on
computerized test batteries rather than time and labor intensive
paper-and-pencil tests, and on neuropsychological tests rather
than conventional IQ tests, it is appropriate to explore whether
similar patterns emerge when a computerized neurocognitive
test battery is applied to areas of investigation that have hitherto
been reliant on IQ measures.
Method
Subjects
The NCNC database contains the records of >16,000 indi-
viduals, patients or family members of patients at the North
Carolina Neuropsychiatry Clinics in Chapel Hill, Raleigh or
Charlotte. Every new patient at the Neuropsychiatry Clinics is
administered a computerized neurocognitive test battery; family
members are requested to take the test battery as well, in order
to better understand the evaluation process. Patients and family
members give written informed consent to allow their de-iden-
tified data to be used for purposes of research and evaluation;
they can take advantage of our website (www.ncneuropsych.com)
to withdraw consent at any time.
The database was found to contain the records of 76 hus-
band-wife pairs, parents of children who were referred as pa-
tients. All of the parents were in good health. Common condi-
tions like hypertension, obesity, anxiety, depression and ADD
were documented in some of the individuals, but none had a
disabling medical or neuropsychiatric disorder. The demo-
graphic characteristics of the husbands and wives are given in
Table 1.
Neurocognitive Evaluation: The CNT battery
The CNT battery is an updated version of a computerized test
battery called CNS Vital Signs, developed by the author (TG)
and introduced in 2003 (Gualtieri & Johnson, 2006). CNS Vital
Signs is currently used by clinicians and researchers and has
been applied in studies of patients with ADHD (Gualtieri &
Table 1.
The computerized test battery (CNT).
Test Time Factor
Verbal Memory VBM 3
Visual Memory VIM 3
Memory
Finger Tapping FTT 3 Motor speed and
coordination
Symbol Digit Coding SDC 4
Shifting Attention Test SAT 3
ST 5
Central Processing
speed
Stroop Test
RT
Continuous
Performance Test CPT 6
Effortful attention
Johnson, 2008a), traumatic brain injury (Gualtieri & Johnson,
2008b), dementia (Gualtieri & Johnson, 2005), mood disorders
(Iverson, Brooks, Langenecker, & Young, 2011) and other
clinical conditions (Brooks & Barlow, 2011). The CNT is iden-
tical to the original test battery, save these differences: stan-
dardization and scoring have been changed in accord with fac-
tor analysis of the tests and controlling for the effects of educa-
tion; validity measures are incorporated as described in a com-
panion paper; the new test is internet-based; and it is not a
commercial product.
The CNT battery contains eight tests that generate nine
scores. Seven tests are the topic of this paper; the eighth, key-
board speed, is a new test that is still in development, intro-
duced as an additional validity measure. The seven tests were
originally chosen because they were thought to address distinct
cognitive domains (Table 2).
The verbal memory (VBM) and visual memory (VIM) tests
are adaptations of the Rey Auditory Verbal Learning Test and
the Rey Visual Design Learning Test (Rey, 1964; Taylor, 1959).
VBM and VIM are tests of recognition memory; they are ad-
ministered at the beginning and the end of the battery, yielding
scores for immediate and delayed memory. The finger tapping
test (FTT) is administered in three 10 second segments to each
hand. The symbol digit coding test (SDC) is based on the sym-
bol digit modalities test (Smith, 1982). The Stroop Test (ST)
has three parts that generate simple and complex reaction times
(Stroop, 1935). Averaging the two complex reaction time
scores from the Stroop test a “response time” (RT) score. The
ST also generates an error score. The Shifting Attention Test
(SAT) measures the subject’s ability to shift from one instruc-
tion set to another quickly and accurately. Other computerized
batteries, like the NES2, CogState and CANTAB have shifting
attention tests. Color-shape tests like the SAT have also been
used in cognitive imaging studies (Le, Pardo, & Hu, 1998; Na-
gahama et al., 1998). The SAT score is calculated by subtract-
ing the number of errors from the number of correct responses.
The Continuous Performance Test presents 40 targets (the letter
“B”) embedded among 160 non-target letters over a five minute
interval (Rosvold & Delgado, 1956).
The tests generate raw scores and standard scores. Scores are
standardized by adjusting for age and education level. Raw
scores were used in these studies.
Data Analysis
The data being normally distributed, performances of hus-
bands and wives were correlated by Pearson product-moment.
Variance was measured by univariate linear regression of
wives’ scores on husbands’ scores.
Table 2.
Characteristics of husbands and wives.
Husbands Wives Pearson’s r
Mean SD Mean SD r Sig.
N 76 76
Age 47.3811.11246.16 10.484 .813 .000000
Educ 16.532.41116.31 1.965 .564 .000016
Compfam 2.65 .5612.69 .466 .063 .664758
772

C. T. GUALTIERI
Results
The salient characteristics of the husbands and wives are
presented in Table 2. Seventy-four of the couples were both
white and two were both African-American. The H-W pairs
were highly correlated for age and education level, but not for
self-reported computer familiarity.
Significant correlations were found for the cognitive index
score, the shifting attention tests and the symbol digit coding
test, but not for any of the other tests and not for any of the
reaction time measures. 51% of the variance in spouse A’s
cognitive index score was attributable to spouse B’s score; 25%
in the shifting attention test; and 8% in the symbol digit coding
test (Table 3).
Discussion
Homogamy, or assortative mating (AM), is one of the ways
Nature makes mate selection systematic. It is a fact of life not
only for the animals but also in every human society. The large
majority of mates resemble each other in a high number of
traits: age, race, religion, ethnicity, social class, economic status,
intellectual ability, education, personality traits, values and
opinions, physical attractiveness, hobbies, previous marital
status, occupation and various anthropometric measures, like
height, weight and eye color and hair color. Spousal correlation
is more evident in studies of cognition than physical character-
istics or other psychological traits (Zonderman et al., 1977;
Mascie-Taylor & Gibson, 1979; Mascie-Taylor, 1989; Mascie-
Taylor, 1989; Mascie-Taylor, 1989).
Why does it happen? We don’t really know. There are theo-
ries, of course: the Genetic Similarity Theory, that we are able
to detect genetically similar organisms—from how they look
and how they behave—and “channel our altruistic behavior
towards them” (Rushton, 1989). That means that we prefer to
invest in someone else’s genes if we happen to have the same
genes. Then, there is the Sexual Imprinting Theory, that we
select mates who resemble our counter-sexual parent (Berec-
zkei, Gyuris, & Weisfeld, 2004). This happens even when we
don’t share their genes: adopted children, for example, prefer
mates who resemble their counter-sexual adoptive parent. Then
there is the simple argument that AM works. A certain degree
of similarity between mates is said to enhance marital stability
Table 3.
Spousal correlations for the tests.
Pearson’s r Lin reg
r Sig. r2
Index Score .717 .000 .514
Shifting Attention Test .496 .000 .246
Symbol Digit Coding .284 .013 .081
Verbal Memory .157 .175 .025
Visual Memory .145 .213 .021
Finger Tapping Test .076 .515 .006
Continuous Performance Test .050 .676 .003
Stroop Errors −.048 .68 .002
Stroop Response Time −.030 .797 .001
and fertility (Bereczkei & Csanaky, 1996; Bentler & Newcomb,
1978; Mascie-Taylor, 1989; Lucas et al., 2004; Wilson &
Cousins, 2003). Homogamy is the way that Nature preserves
the stability of a species. It is also a way for new species to
form, as organisms mate homogamously around some new and
interesting mutation until they form an entirely new species.
Studies have consistently indicated that homogamy for men-
tal ability reflects initial assortment (i.e., similarity at the time
of marriage) rather than convergence (i.e., increasing similarity
with time) (Watson et al., 2004; Zonderman et al., 1977). Nu-
merous studies from 1926 through 1979 have indicated spousal
correlations for intelligence ranging from .12 to .76, with a
weighted mean correlation of .44 (Johnson, Ahern, & Cole,
1980). With respect to individual tests, for example the subtests
of an IQ test battery, it has been noted that the correlation for
spouses is largely a matter of g; that is, the degree to which
cognitive tests show assortative mating is highly correlated
with the tests’ loadings on the g factor (Jensen, 1998). In this
study, a summary score based on the individual neurocognitive
tests and analogous to an IQ score, demonstrated a much higher
spousal correlation than any of the tests by themselves. Among
the individual tests, shifting attention and symbol digit coding
were significantly correlated; but none of the other tests were,
nor were any of the reaction time measures.
The shifting attention and coding tests on the CNT load to-
gether as a single measure of the speed and efficiency of infor-
mation processing, which is recognized to be a highly g loaded
factor (Jensen, 1998). Studies in our clinics of 179 adults who
were tested with the Wechsler scales and the CNT battery indi-
cated a positive correlation between full scale IQ and the sym-
bol digit coding test (r = .465, P < .01) and with the shifting
attention test (r = .59, P < .01) (Gualtieri, CT & Hervey, AS,
2013).
Recent studies have been more interested in specific tests
than measures of general mental ability. In two studies, one of
318 spouse pairs and one of 123, significant positive spousal
correlations were observed for almost all cognitive variables
except attention and psychomotor speed (Dufouil & Alpéro-
vitch, 2000; Zonderman et al., 1977). In our study, in contrast,
we found a clear differentiation between tests of processing
speed and other neuropsychological tests. Perhaps that is a
function of the smaller number of spouse pairs, or possibly the
fact that the parents in this sample have children with neuro-
psychiatric disorders. On the other hand, large N’s may artifi-
cially inflate the number of variables that are statistically sig-
nificant. An r of .18 may be significant in a study of 123 sub-
jects, but will only account for about 3% of variance attribut-
able to that factor. And, if anything, the presence of illness in
one spouse or another, or in the offspring, might work against
the hypothesis of positive spousal correlation. The small num-
ber of husband-wife pairs in this study is a problem; the fact
that our results are in accord with previous studies is re-assur-
ing.
In a previous paper we reported positive correlations between
first-degree relatives who were administered the CNT battery,
and which occurred primarily in tests of complex information
processing, SDC and SAT (Hervey, Greenfield, & Gualtieri,
2012). In this paper, we note that the same two tests contribute
more strongly than any other tests to the high spousal correla-
tion for neurocognition. There is a certain symmetry, then, be-
tween the cognitive skills that play into spouse selection and
the cognitive skills that are inherited. A better word than sym-

C. T. GUALTIERI
metry might be inevitability.
The findings of these studies suggest that computerized neu-
rocognitive testing is an appropriate tool for studies of the ge-
netics of cognition, that measures of processing speed are par-
ticularly salient and that the CNT is a suitable instrument. The
advantages of computerized neurocognitive tests like the CNT
include speed and efficiency, standard administration, suitabil-
ity for repeated measures and elimination of scoring and tran-
scription errors. Tests that are Internet-based like the CNT are
amenable to centralized data collection and have flexibility in
administration in different settings, even permitting the collec-
tion of data from remote sources. In genetic studies of cognition,
where large numbers of subjects are necessary this technology
may also be inevitable.
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