The nature of individual differences

1
The nature of individual differences in
resting EEG parameters in 5-year-old twins
Tatiana Stroganova, Svetlana Novikova, Irina
Posikera, Marina Tsetlin, Lev Kuravsky
E-mail vpf_child_at_mail.ru Moscow State
University of Psychology and Education, Psychologi
cal Institute of Russian Academy of Education
2
Introduction
Background EEG measures have been
repeatedly reported to depend exclusively on
genetic influences in adults and adolescents
(Lykken et al., 1982 van Beijsterveldt et al.,
1996), but there have been few genetic studies of
smaller children. There are just one study
devoted to EEG genetics in infants (Orekhova et
al., 2003) and one devoted to preschoolers (van
Baal et al., 1996). Under various
experimental conditions, the same EEG parameters
may reflect different brain processes. Therefore,
the contribution of genetic and environmental
factors may depend on the current functional
state. Little is known about the sources of
individual differences of EEG parameters measured
under experimental conditions other than the
so-called baseline (quiet wakefulness with eyes
closed). We estimated relative
contribution of genetic and environmental factors
to alpha gravity frequency and spectral
amplitudes of three frequency bands in preschool
EEG under two similar test conditions.
3
Methods
Participants 21 pairs of MZ and 20
pairs of same-sex DZ twins aged 5-6 years. All
participants were born within 32 to 41 weeks of
gestational age (mean37.2 weeks, SD1.91) and
had no any known medical problems. Zygosity was
determined according to the Goldsmith
questionnaire (Goldsmith, 1991).
Procedure EEG was registered during two
resting conditions of dark homogeneous visual
field, closed eyes and darkness, and one control
condition of visual attention to moving color
stimuli. On average, 40 s of the artifact-free
EEG record for each condition were analyzed for
each subject. Recording and processing
of EEG 12 electrodes were placed at AF3, AF4,
C3, C4, F7, F8, T5, T6, P3, P4, O1, and O2
positions. Linked ears served as the reference.
Epochs of 2.5 s length were Fast Fourier
Transformed (80 overlap) to yield the amplitude
spectrum between 1.2 and 15.2 Hz in discrete bins
of 0.4 Hz. Age-adjusted (Orekhova et al, 2006)
frequency boundaries of three EEG bands delta
(1.2-3.2 Hz), theta (3.6-7.6 Hz), and alpha
(8.0-12.8 Hz) were used. Alpha gravity
frequency (Lykken et al., 1982) was measured at
the occipital region in range of 7-11 Hz
(estimated in 94 of cases).
Statistical analysis ANOVA was performed to
assess the differences between two test
conditions in alpha gravity frequensy and in
reactivity of spectral amplitudes. Fisher
intrapair twin correlation and model fitting
methodology (confirmatory factor analysis) were
used for genetic analysis. The concordance of
results obtained for two similar functional loads
improves reliability of estimation. So we report
only results reproduced in two test conditions.
Preliminary analysis of genetic data
Analysis of variance has shown no main effects of
sex and zygosity or their interactions that were
reproduced in two subsamples that included one
twin of each pair.
4
Result 1. Reactivity of absolute amplitudes under
two test conditions.
Spectral amplitudes of alpha frequency band
changed quite similar from control to each of
test conditions demonstrating significant
increase. The same result was found for theta
band amplitudes. Reactivity of delta amplitudes
(near 3 Hz) was reliably greater under closed
eyes at posterior regions (see arrows). The two
test conditions are not equated in amount of
horizontal eye movements. Horizontal
eye movements disappear when eyes are closed but
remain under darkness condition producing
additive stimulation of cortex. Therefore
different delta reactivity could reflect
different degree of partial cortex
deafferentation in two test conditions (Steriade
et al., 1990). Alpha gravity frequency was near
8.5 Hz and did not significantly differ between
two test conditions.
Figure 1. Average amplitude spectra under two
experimental and one control conditions (N75).
Visual attention Closed eyes Darkness
5
Result 2. Assessing of intrapair twin resemblance
(correlational analysis).
Figure 2. Intraclass correlations in the MZ and
the DZ pairs for common logarithms of absolute
spectral amplitudes. ? closed eyes, B
darkness. Ovals indicate highly significant ( -
plt0.01 - plt.001) correlations in MZ and DZ
pairs over parietal regions within theta band in
both test conditions.
Concordance of results under both test
conditions was obtained for alpha as for theta
band. We suggest variability of alpha
amplitudes to depend essentially on genetic,
probably non-additive factors (all rMZ except
anterior regions are highly signifi-cant plt.001
all rDZ are ns). Remarkably, alpha
frequency has most likely nonadditive
heritability too (rMZ0.8 rDZ0.0).
Variability of parietal theta amplitudes perhaps
is influenced by shared environment (rMZrDZ).

6
Result 3. Model fitting confirmed all findings of
the correlational analysis.
Figure 3. The percent of EEG spectral amplitude
variance explained by black - heritability, gray
- shared environment, and white - nonshared
environment estimates derived from the ace model
with 3 degrees of freedom. A closed eyes, B
darkness. 4 anterior regions were excluded
because of artifacts.
For spectral amlitudes within alpha and
theta but not delta band, results of model
fitting for darkness condition actually mirror
results during closed eyes condition.
The best fitting models for alpha amplitudes
always included genetic (additive or nonadditive)
component. Similarly, nonadditive genetic model
(de) satisfactorily explained variance of alpha
frequency. The best fitting model for
theta amplitudes at leads P3, P4, and T5 was ace
model with equated contribution of genetic (a)
and shared environmental (c) factors (4 degrees
of freedom).
7
Conclusion
1. The results suggest that the sources
of individual differences for oscillations within
alpha (8.0-12.8 Hz) as for theta (3.6-7.6 Hz)
frequency band did not differ between two
conditions of homogenous field of vision
darkness and closed eyes. The nature of
individual differences in variability of delta
(1.2-3.2 Hz) amplitudes remained unclear since
poor reproducibility of delta results in two test
conditions. 2. Variance of alpha
frequency as for alpha amplitudes depended mainly
on non-additive genetic factors in agreement with
previous adults (Lykken et al., 1982 Posthuma
et al., 2001) and childrens results (Orekhova et
al., 2003) though these distinct parameters
apparently have different nature. 3.
The influence of shared environment is probable
for theta amplitude at associative (first of all
parietal) regions. This finding contradicts Dutch
study of preschoolers (van Baal et al., 1996)
that showed strong heritability of theta
amplitudes. At the same time our finding is in
agreement with Plomins amplification theory and
with results of recent studies, reported rather
powerful environmental contribution in infant
theta amplitudes (Orekhova et al., 2003) and in
adolescent females ERP amplitude and
low-frequency EEG activity (Anokhin et al., 2001)
during the conditions of dark homogenous visual
field. 4. Both test conditions are
accompanied by theta increase. We suppose that
the reduced visual sensory input is unpleasant,
emotionally loaded situation for 5-year-olds.
Theta rhythm is well known to synchronize during
emotional load (see Orekhova et al., 2006, for
references). Cortical theta is provided by
increased activity of limbic system and related
structures, so called theta response system
(Demiralp et al., 1994). 5. Taking
into account functional role of theta
sinchronization we conclude that environmental
experience can modify the activity of structures
involved in regulation of slightly stressful
functional load (not resting state!) in
preschoolers under conditions of reduced visual
sensory input. This inference includes our study
in wide context of contemporary research of
placticity of cortico-lymbic structures in early
human and animal development (Chugani et al.,
2001 Plotsky Meaney, 1993).
8
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1. Anokhin A.P., van Baal G.C.M., van Beijsterveldt
   C.E.M., de Geus E.J.C., Grant G., Boomsma D.I.
   (2001). Genetic correlation between the P300
   event-related brain potential and the EEG power
   spectrum. Behavior Genetics, 31. 545-554.
2. Chugani H.T., Behen M.E., Muzik O., Juhász C.,
   Nagy F., Chugani D.C. (2001). Local brain
   functional activity following early social
   deprivation A study of postinstitutionalized
   Romanian orphans. NeuroImage, 14, 12901301.
3. Demiralp T., Basar-Eroglu C., Rahn E., Basar E.
   (1994). Event-related theta rhythms in cat
   hippocampus and prefrontal cortex during an
   omitted stimulus paradigm. Int J Psychophysiol.,
   18. 35-48.
4. Goldsmith HH. (1991). A zygosity questionnaire
   for young twins A research note. Behavior
   Genetics, 21. 257269.
5. Lykken D., Tellegen A., Iacono W.G. (1982). EEG
   spectra in twins evidence for a neglected
   mechanism of genetic determination. Physiological
   psychology, 10. 60-65.
6. Orekhova E.V., Stroganova T.A., Posikera I.N.,
   Malykh S.B. (2003). Heritability and
   environmentability of electroencephalogram in
   infants The twin study. Psychophysiology, 40.
   727-741.
7. Orekhova E.V., Stroganova T.A., Posikera I.N.,
   Elam M. (2006). EEG theta rhythm in infants and
   preschool children. Clin Neurophy-