RESEARCH ARTICLEOpen Access
Sex-related differences in sleep slow wave activity
in major depressive disorder: a high-density EEG
David T Plante*, Eric C Landsness, Michael J Peterson, Michael R Goldstein, Brady A Riedner, Timothy Wanger,
Jeffrey J Guokas, Giulio Tononi and Ruth M Benca
Background: Sleep disturbance plays an important role in major depressive disorder (MDD). Prior investigations
have demonstrated that slow wave activity (SWA) during sleep is altered in MDD; however, results have not been
consistent across studies, which may be due in part to sex-related differences in SWA and/or limited spatial
resolution of spectral analyses. This study sought to characterize SWA in MDD utilizing high-density
electroencephalography (hdEEG) to examine the topography of SWA across the cortex in MDD, as well as
sex-related variation in SWA topography in the disorder.
Methods: All-night recordings with 256 channel hdEEG were collected in 30 unipolar MDD subjects (19 women)
and 30 age and sex-matched control subjects. Spectral analyses of SWA were performed to determine group
differences. SWA was compared between MDD and controls, including analyses stratified by sex, using statistical
non-parametric mapping to correct for multiple comparisons of topographic data.
Results: As a group, MDD subjects demonstrated significant increases in all-night SWA primarily in bilateral
prefrontal channels. When stratified by sex, MDD women demonstrated global increases in SWA relative to
age-matched controls that were most consistent in bilateral prefrontal regions; however, MDD men showed no
significant differences relative to age-matched controls. Further analyses demonstrated increased SWA in MDD
women was most prominent in the first portion of the night.
Conclusions: Women, but not men with MDD demonstrate significant increases in SWA in multiple cortical areas
relative to control subjects. Further research is warranted to investigate the role of SWA in MDD, and to clarify how
increased SWA in women with MDD is related to the pathophysiology of the disorder.
Sleep disturbance has diagnostic, clinical, and functional
significance in major depressive disorder (MDD). Self-
report of insomnia and/or hypersomnia is a diagnostic
criterion for MDD, and sleep-related complaints occur
in the majority of MDD patients [1,2]. Sleep-related clin-
ical complaints are important in the natural history of
the disorder, as they increase the risk of developing a de-
pressive episode [3-7], attempting suicide [8,9], and re-
lapsing after remission [10-12]. Additionally, myriad
studies have examined polysomnographic measures in
MDD, demonstrating alterations in sleep continuity,
rapid eye movement (REM) sleep, and slow wave sleep
(SWS) [13,14]. Scoring of SWS relies on visual assess-
ment of frequency, amplitude, and proportion of delta
waves [15,16], which can occur in all stages of NREM
sleep and are not exclusive to SWS. Slow wave activity
(SWA), which represents the power density in the
1-4.5Hz range in all stages of NREM sleep, more accur-
ately captures the variation in slow oscillations during
sleep that is not reflected by traditional sleep staging
SWA has been established as a marker of sleep
homeostasis, as it increases in proportion to prior wake-
fulness and declines with sleep [19,20]. Based in part on
the antidepressant effects of sleep deprivation, it has
* Correspondence: firstname.lastname@example.org
Department of Psychiatry, University of Wisconsin School of Medicine and
Public Health, Madison, WI, USA
© 2012 Plante et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Plante et al. BMC Psychiatry 2012, 12:146
been hypothesized that MDD involves deficiency in sleep
homeostatic processes—the S-deficiency hypothesis of
depression [21,22]. Prior studies that have examined
SWA in MDD using spectral analysis support this hy-
pothesis, particularly suggesting decrements of SWA in
the first portion of the night [23,24]. However, findings
have not been consistent across studies, with other
investigations failing to demonstrate significant differ-
ences in SWA in depressed subjects relative to healthy
controls [25-28]. Moreover, significant sex-related effects
on SWA in MDD have been described, with increases in
SWA among depressed women and decreases in SWA
among depressed men, relative both to each other and
to healthy comparison subjects [29-31].
A major limitation of prior studies of SWA in MDD is
the use of limited central derivations of the electro-
encephalogram (EEG) to quantify SWA. Since SWA is
most prominent during sleep in frontal brain regions
[32-35], the use of central channels to assess SWA may
not optimally reflect differences in sleep homeostatic
processes in depression. Furthermore, the use of a single
or only a few EEG derivations to perform spectral ana-
lysis provides limited spatial resolution, and thus, topo-
graphic alterations in SWA would not be evident using
these approaches. Therefore, this study was conducted
using high-density (hd) EEG to evaluate the topography
of sleep SWA in MDD relative to healthy age and sex-
matched comparison subjects. We hypothesized that dif-
ferences in SWA between MDD and control subjects
would be most pronounced in frontal channels, and that
there would be differential effects of sex on SWA in
MDD subjects, with women with MDD demonstrating
increases and men with MDD demonstrating reductions
in SWA compared to age and sex-matched healthy com-
Thirty right-handed outpatient MDD subjects (19 fe-
male) were selected from a larger study on sleep homeo-
stasis in neuropsychiatric disorders, conducted at the
University of Wisconsin-Madison. MDD was diagnosed
via the Structured Clinical Interview for DSM-IV Axis I
disorders (SCID)  and global depression severity was
evaluated with the clinician-administered 17-item Ham-
ilton Rating Scale for Depression (HRSD) . For in-
clusion, subjects were required to have at least moderate
depression defined as HRSD>15 and be free of psycho-
tropic medications (or other agents that could alter sleep
architecture) for ≥1 month. In addition, subjects were
unipolar and had no history of psychosis or active drug/
alcohol dependence. Subjects were free of significant
neurological and medical conditions, including evidence
of sleepdisorderedbreathing andsleeprelated
movement disorders, verified by in-laboratory polysom-
nography (see below). Age and sex-matched healthy
comparison subjects were evaluated with the non-
patient SCID  to rule out current or past psychiatric
All subjects provided informed consent and were
instructed to maintain regular sleep-wake schedules,
avoid napping, and to limit the use of caffeinated or al-
coholic beverages for the duration of the study. Adher-
ence was monitored using sleep-diaries and wrist motor
actigraphy (Actiwatch, Mini-Mitter, Bend, OR). This
study was approved by the Institutional Review Board of
the University of Wisconsin-Madison.
All subjects underwent in-laboratory hdEEG polysomno-
graphy (PSG) that utilized 256 channel hdEEG (Elec-
trical Geodesics Inc., Eugene, OR), as well as standard
monitoring with electrooculogram (EOG), sub-mental
electromyogram (EMG), electrocardiogram (ECG), bilat-
eral tibial EMG, respiratory inductance plethysmogra-
phy, pulse oximetry, and a position sensor. Participants
arrived at the laboratory between 20:00 and 21:00 for
set-up that took approximately two hours, and then were
allowed to sleep undisturbed in the laboratory beginning
within one hour of their usual bedtime. Sleep hdEEG
recordings were collected with vertex-referencing, using
NetStation software (Electrical Geodesics Inc., Eugene,
HdEEG signals were sampled at 500 Hz, first-order
high-pass filtered in NetStation (0.1Hz), downsampled
to 128 Hz, band-pass filtered (2-way least-squares FIR,
1-40 Hz) in MATLAB (The MathWorks Inc., Natick,
MA), and average-referenced to the average scalp volt-
age computed in all channels. Semi-automatic artifact
rejection was conducted to remove channels with high-
frequency noise or interrupted contact with the scalp
during individual epochs. Channels for which artifact
affected the majority of the recording were excluded.
Spectral analysis of NREM sleep was performed for each
channel in consecutive 6-second epochs (Welch’s aver-
aged modified periodgram with a Hamming window).
To increase the signal-to-noise ratio, analyses were
restricted to the 185 channels overlaying the scalp .
Sleep staging was performed by a registered polysomno-
graphic technologist in 30-second epochs according to
standard criteria  using AliceWSleepware (Philips
Respironics, Murrysville, PA) based on 6 EEG channels
at approximate 10-20 locations (F3, F4, C3, C4, O1, and
O2) re-referenced to the mastoids, sub-mental EMG and
Plante et al. BMC Psychiatry 2012, 12:146
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Slow wave activity time course
SWA time course was quantified using similar methods
described by other groups [29,40]. The exponential decay
function utilized was as follows: SWAt=(SWA0 * e-rt)+
SWA∞, in which SWAtis the SWA value at a given time
point t, SWA0represents the hypothetical SWA value at
time 0, t indicates time (min) from sleep onset, r is the rate
(min-1) of exponential decay, and SWA∞ indicates the
SWA value of the decay function’s asymptote. To optimize
fit for each decay function, for each subject, relative SWA
for each NREM period was calculated as a percent of the
average SWA across the first NREM periods 1-4, and
NREM period midpoints were used to derive the corre-
sponding time point values. NREM periods were defined
using duration and endpoint criteria in a manner similar to
prior studies , with the exception that NREM periods
were inclusive of all stages of NREM sleep (N1-N3).
Differences in all-night SWA (both global average of 185
channels and channel-by-channel) between MDD and
matched controls were examined using 2-tailed, unpaired
t-tests. Given aforementioned sex-related differences in
SWA in MDD [29,30], as well as reported differences in
SWA between healthy men and women that vary by age
[42-44], additional analyses between MDD and controls
stratified by sex were performed to maintain age-matching
of subjects. Also, effects of NREM period were explored
given the known decline of SWA across NREM periods
and prior studies that have demonstrated decrements in
SWA in MDD primarily occurring in the first NREM
period . To correct for multiple comparisons of the
topographical hdEEG data, statistical non-parametric map-
ping with suprathreshold cluster tests was utilized . For
correlational analyses of SWA with polysomnographic and
clinical data, hdEEG sleep data were first cleaned for out-
liers using a threshold of±2.5 standard deviations from the
mean at each channel. Statistical relationship between vari-
ables and SWA in each channel was assessed using linear
regression. To limit spurious findings due to multiple com-
parisons, correlation analyses of PSG variables were limited
to those measures significantly different between groups.
Additionally, topographic correlations were considered sig-
nificant only if clusters of ≥3 contiguous channels were sig-
nificant at α=0.05 within cortical regions of significant
difference between groups. Statistical analyses were per-
formed using MATLAB (The MathWorks Inc., Natick,
MA) and STATISTICA (StatSoft Inc.,Tulsa, OK).
MDD subjects were young to middle aged (mean 26.0 ±
9.1; range 18 to 53 years) with moderate depression
(mean HRSD 18.6 ± 2.7; range 15 to 25) and had not
taken psychotropic medications within≥5 months of en-
rollment (Table 1). Eleven MDD participants reported at
least one prior depressive episode. HC subjects did not
report a personal or family history of mood disorders.
Polysomnography demonstrated significant differences
Table 1 Demographic, clinical, and polysomnographic data
MDDHC pMDD FemalesHC FemalespMDD Males HC Malesp
Age (years)26.0 (9.1)25.4 (8.5) .79323.4 (5.6)23.1 (6.2).891 30.6 (12.1) 29.4 (10.7).811
HRSD-1718.6 (2.7) – 19.0 (3.0)–17.9 (1.6) –
TST (min.) 377.8 (66.3)412.7 (47.5).023390.5 (54.0)419.6 (49.8) .093 356.0 (81.7) 400.8 (42.9).122
WASO (min.) 43.3 (30.2) 30.2 (20.7).05538.1 (26.4) 30.7 (20.6).345 52.4 (35.4)29.4 (21.8).082
AI (#/hr.) 10.6 (5.6)7.9 (4.3).0439.4 (5.5)8.2 (3.8).424 12.6 (5.5)7.4 (5.3).036
SE (%)86.5 (7.9)89.6 (7.4).13288.7 (7.1) 89.2 (8.6) .84682.8 (8.1)90.1 (4.9) .018
SOL (min.)15.5 (16.5) 18.6 (24.3).566 11.6 (10.5)20.6 (28.0) .19922.1 (22.7) 15.1 (16.7).414
N1 (%) 8.1 (5.3)7.9 (4.7) .9267.5 (5.5) 7.7 (5.0) .8979.0 (5.0) 8.3 (4.2).724
N2 (%)57.7 (8.1) 60.4 (6.1).151 56.6 (8.6)60.4 (5.2).111 59.5 (7.2)60.4 (7.8).788
N3 (%) 16.8 (9.2)14.8 (7.1) .34820.0 (7.6) 15.9 (6.3) .07511.2 (9.3) 13.0 (8.2) .651
REM (%) 18.1 (6.6)16.9 (5.0) .44815.9 (6.5)16.0 (5.2) .923 22.3 (4.8)18.4 (4.5).071
131.2 (77.4) 122.2 (69.7) .641158.1 (78.4) 131.1 (71.2) .27580.1 (43.7)106.7 (67.4) .302
22.7 (13.1)17.3 (6.8).05428.8 (12.4)19.3 (6.8) .00612.1 (5.4)13.9 (5.3) .442
MDD, major depressive disorder; HC, healthy control; HRSD-17, Hamilton Rating Scale for Depression (17-item); TST, total sleep time; WASO, wake after sleep onset;
AI, arousal index; SE, sleep efficiency (TST/time in bed); SOL, sleep onset latency; N1/2/3, NREM stage 1/2/3 (% of TST); REM, stage REM (% of TST); REML, REM
latency (time from sleep onset to first REM sleep epoch); SWA, global slow wave activity (EEG power in 1 – 4.5 Hz range average 185 channels);
Values are displayed as mean (standard deviation).
*2-tailed, independent samples t-tests.
Plante et al. BMC Psychiatry 2012, 12:146
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between groups, with MDD subjects demonstrating
decreased total sleep time (TST) and increased arousal
index (AI) (Table 1). When stratified by sex, there were
no significant differences in polysomnographic variables
between women with MDD and female controls, but
depressed men had significantly higher AI and lower
sleep efficiency (SE) than male controls (Table 1).
All-night global SWA (average of 185 channels) was
not significantly different between MDD and HC groups;
however, there was a trend towards increased global
SWA in MDD (Table 1). Topographic analysis demon-
strated significantly increased SWA in MDD relative to
HC, primarily in bilateral prefrontal channels, as well as
left lateral parietal and occipital channels (Figure 1).
When groups were stratified by sex, female MDD sub-
jects demonstrated significantly higher global all-night
SWA compared to age-matched female controls (28.8
μV2/Hz ± 12.4 vs. 19.3 μV2/Hz ± 6.8, p=0.006). Topo-
graphic analysis demonstrated significant increases in
SWA in MDD women relative to HC women that were
most consistent in bilateral prefrontal channels, and
additionally significant in multiple other cortical regions
including frontal, lateral parietal, and occipital regions
(Figure 1). However, neither global (12.1μV2/Hz ± 5.4 vs.
13.9μV2/Hz ± 5.3, p=0.44) nor topographic differences
were observed for MDD men relative to age-matched
male controls (Figure 1).
Given the sex-related differences in all-night global
SWA observed, analyses both unstratified and stratified
by sex were performed to examine the role of NREM
period. In the unstratified analysis, a 2 (group) by 3
(NREM period) mixed model ANOVA was utilized,
which showeda main
(F2,46=39.28, p<0.0001) and a significant group x period
interaction (F2,92=4.83, p=0.01), without main effect of
group (F1,46=0.81,; p=0.37). Post hoc analyses, using
Tukey’s HSD to correct for multiple comparisons,
showed a significant decline of global SWA from
NREM1 to NREM3 for both MDD (p=0.0001) and HC
(p=0.001), with no significant differences between MDD
and HC groups in any NREM period (Figure 2). In the
stratified analyses, a 4 (group) by 3 (NREM period)
mixed model ANOVA was utilized to examine global
SWA across the night among groups stratified by sex.
(F2,44=40.06, p<0.0001) and a group x period inter-
action (F6,88=5.76, p<0.0001). Post hoc analysis demon-
strated a significant decline of global SWA from
effectof NREM period
maineffect of period
Figure 1 Topographic all-night SWA (1-4.5 Hz) in MDD subjects versus healthy controls, both unstratified and stratified by sex. T-values
plotted for the comparisons between groups (2-tailed, unpaired t-test) at each channel. The minimum and maximum t-values for each map are
plotted in white and black respectively, with the corresponding numeric range for color scale (upper left). Corresponding p-values plotted for
each channel with white dots denoting channels with significant between-group differences following statistical non-parametric mapping with
suprathreshold cluster tests to correct for multiple comparisons.
Plante et al. BMC Psychiatry 2012, 12:146
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NREM1 to NREM3 for MDD (p=0.0001) and HC
women (p=0.012), but not for MDD or HC men after
correcting for multiple comparisons (Figure 2). MDD
women showed a trend towards greater global SWA
than age-matched HC women (p=0.097) in NREM1,
however, there were no other differences between MDD
subjects of either sex and age-matched HC subjects in
NREM2 or NREM3.
Subsequent topographic analysis of SWA in NREM1
demonstrated nearly identical patterns as all-night SWA
in both stratified and unstratified analyses (See Additional
file 1: Figure S1). Additional exploratory topographic ana-
lyses of SWA in NREM2 and NREM3 demonstrated no
significant differences between groups (either stratified or
unstratified by sex).
Fitted exponential decay functions are depicted in
Figure 3 and calculated SWA time course variables
presented in Table 2. In the unstratified analysis, there
was a trend for greater SWA0in MDD relative to control
subjects (p=0.10). When SWA time course was stratified
by sex, MDD women demonstrated significantly greater
SWA0relative to HC women (p=0.03). There were no
other significant differences in SWA time course vari-
ables in either unstratified or stratified analyses.
Although MDD and HC subjects were age and sex-
matched in the unstratified analysis, when stratified by
sex, the ages between male and female participants were
not identical (Table 1). Therefore, a secondary analysis
was performed using analysis of covariance (ANCOVA)
to compare differences in all-night global SWA among
all groups that included age as a covariate. ANCOVA
revealed a significant main effect of sex (F1,55=14.00,
p=0.0004), a trend towards main effect of diagnosis
(F1,55=3.24, p=0.077), a significant diagnosis x sex inter-
action (F1,55=5.98, p=0.018), and a significant effect of
age (F1,55=4.99, p=0.030). Adjusted means for SWA
were marginally different compared to unadjusted values
(adjusted mean±std error: MDD women: 28.05±1.94,
MDD men: 13.56±2.60, HC women: 18.55±1.95, HC
men: 15.00±2.56 μV2/Hz). Post hoc analysis showed
MDD women demonstrated significantly greater SWA
than HC women (p=0.0009), HC men (p=0.0002), and
MDD men (p<0.0001). However, there were no other
significant differences in SWA between groups including
between HC women and HC men (p=0.28).
There were no significant correlations of SWA (either
all-night or in NREM1) with HRSD scores in MDD, ei-
ther stratified or unstratified by sex. Additionally, there
were no significant correlations of polysomnographic
variables with global or topographic SWA (either all-
night or NREM1) in HC or MDD subjects, either strati-
fied or unstratified by sex.
Our findings demonstrated an increase in SWA in young
to middle aged women with unipolar MDD. Moreover,
increases in SWA in MDD women primarily occurred
during the first portion of the night and were most
prominent in prefrontal regions. In contrast, men with
MDD did not demonstrate significant changes in SWA,
corroborating prior investigations that demonstrate sex-
specific differences in SWA in MDD [29,30]. Strengths
of this investigation include age and sex-matching of
subjects, which allowed for analyses stratified by sex, as
well as lack of confounding psychotropic medications
and use of hdEEG for spectral analysis. These results
highlight the importance of both sex and EEG topog-
raphy in the evaluation of SWA in mood disorders.
Figure 2 Global SWA (1-4.5Hz) across NREM periods for MDD
and healthy controls A) unstratified and B) stratified by sex.
Error bars represent standard error of the mean.
Plante et al. BMC Psychiatry 2012, 12:146
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The findings of this study must be taken in context of
the ratio of women to men, which was roughly 2:1, ap-
proximating the differential prevalence of MDD by sex
in the general population . Notably, two known
prior studies in the literature that have demonstrated
similarly increased SWA or delta counts (using period
amplitude analysis) in depressive illness relative to
controls have both had disproportionately high ratios of
female to male MDD subjects of greater than 3:1; how-
ever, neither study stratified their analyses by sex
[47,48]. Our stratified analysis found that in women
with MDD, SWA was globally increased relative to fe-
male HC, but was most prominently increased in bilat-
eral prefrontal cortical regions, consistent with multiple
Figure 3 Time course of relative slow wave activity (SWA) across non-rapid eye movement (NREM) sleep periods. Individual SWA values
per NREM sleep period (expressed as a percentage of all night SWA) are plotted at period midpoint relative to sleep onset for MDD and healthy
controls A) unstratified and B) stratified by sex. All data from the first four NREM periods were included to maximize fit of the exponential
function. Lines represent exponential functions that were fitted to the data using the equation SWAt=(SWA0* e-rt)+SWA∞, in which SWAtis the
SWA value at a given time point t, SWA0represents the hypothetical SWA value at time 0, t indicates time (min) from sleep onset, r is the rate
(min-1) of exponential decay, and SWA∞indicates the SWA value of the decay function’s asymptote.
Plante et al. BMC Psychiatry 2012, 12:146
Page 6 of 10
structural and functional neuroimaging investigations
which have demonstrated the importance of the pre-
frontal cortex in the neurobiology of depression [49,50].
However, it is currently not clear how increased SWA
in women with MDD is related to the pathophysiology
of the disorder.
This study highlights the importance of electrode place-
ment in the evaluation of SWA during sleep in mood disor-
ders. Notably, we did not find a significant difference in
SWA between MDD and control subjects in central chan-
nels, including analyses stratified by sex. Since the previous
scientific literature regarding SWA in depression has utilized
central EEG derivations, it is conceivable that the aforemen-
tioned inconsistencies between previous studies may be in
part due to a lack of topographical resolution or increased
variability of SWA in central regions. Thus, the findings of
this study suggest spectral analysis of sleep using central
derivations may be inadequate to capture the alterations in
SWA occurring across the cortex in mood disorders.
There are limitations of this study that merit discus-
sion. Although a prior investigation has demonstrated
decreases in SWA in men with MDD , we did not
find statistically significant differences in men with
MDD relative to matched HC subjects. However, it is
possible that our study was underpowered to detect dif-
ferences in SWA or decline of SWA across sleep among
males. It is also possible that significant prefrontal
increases in SWA in MDD in the unstratified analysis
would not have been demonstrated had the ratio of men
to women been proportionate. Furthermore, subjects did
not have an adaptation night in the sleep laboratory,
which may have affected results, if groups were differen-
tially affected by first-night effects. Although delta EEG
activity is not significantly different in the luteal versus
follicular phase of the menstrual cycle in either healthy
subjects or patients with severe premenstrual syndrome,
it is also possible that not assessing menstrual status at
the time of polysomnography may have influenced the
results . Finally, subjects were young to middle aged,
and thus, results may not be applicable to older subjects
with MDD, as it has been suggested alterations in SWA
in MDD are more apparent in young to middle aged
This study was not able to determine whether
increased SWA in MDD is a causal phenomenon for the
disorder or an epiphenomenon resulting from chronic
sleep disruption associated with the illness. Topographic
increases in SWA in depressed women observed in this
study are not specific to MDD, as such findings are also
deprivation [33-35]. It is intriguing that increases in
SWA are observed in both MDD and sleep deprivation
paradigms, as both are associated with impairments in
cognitive functions such as attention and working mem-
ory, as well as subjective fatigue [52,53]. Given the
results of this study, further experiments are warranted
that examine the relationship between sleep homeostatic
processes and executive function in MDD, using sleep
restriction and/or sleep delay paradigms , and the
effects of sex on these parameters.
Our results suggest that increased SWA, particularly
during early portions of the night, may be related to the
pathophysiology of MDD in women. In accordance with
this hypothesis, it has been previously proposed that
increases in NREM sleep intensity may be depressogenic
, and a recent demonstration that selective slow-
wave deprivation has an acute antidepressant response
supports this contention . In addition, when com-
pared to healthy controls, young MDD women exhibited
greater low-frequency EEG activity in frontal regions
during extended wakefulness , which has been
demonstrated to be a waking correlate of sleep homeo-
stasis [34,57]. Both increased SWA during baseline sleep
and anenhanced homeostatic
deprivation paradigms have also been reported, suggest-
ing that MDD women live with an elevated level of
homeostatic sleep pressure [31,58,59]. Although our
results would support this contention, our experimental
following acute sleep
Table 2 SWA time course variables derived from fitted exponential decay functions*
MDDHCMDD FemalesHC FemalesMDD MalesHC Males
(N = 30)(N = 30) p(N = 19)(N = 19)p(N = 11) (N = 11)p
0.630.55– 0.710.51 – 0.660.65–
177.34141.00 0.10230.04 146.860.03150.79 137.300.68
(CI) (143.41-211.27)(113.44-168.55)(176.43-283.66) (95.57-198.15)(89.50-212.09)(102.63-171.97)
0.0108 0.00630.18 0.0112 0.00530.150.01780.00820.16
(CI) (0.0060-0.155) (0.0017-0.0110)(0.0060-0.0163)(−0.0011-0.0116)(0.0057-0.0299)(0.0011-0.0154)
58.3045.82 0.52 53.2436.49 0.63 74.3555.74 0.28
(CI)(41.86-74.74) (10.23-81.40)(33.41-73.08)(−33.48-106.47) (60.13-88.56)(22.47-89.02)
*Values derived from exponential functions that were fitted to the data using the equation SWAt=(SWA0* e-rt)+SWA∞, in which SWAtis the SWA value at a given
time point t, SWA0represents the hypothetical SWA value at time 0, t indicates time (min) from sleep onset, r is the rate (min-1) of exponential decay, and SWA∞
indicates the SWA value of the decay function’s asymptote. CI denotes the 95% confidence interval. R2for the exponential function reflects goodness of fit.
Plante et al. BMC Psychiatry 2012, 12:146
Page 7 of 10
design did not include manipulations of sleep homeosta-
sis, and thus only provides partial evidence for this hy-
pothesis. Moreover, given our cross-sectional design, we
were not able to determine whether increased SWA in
MDD is a state or trait marker for MDD in women, nor
are we able to determine if increased SWA is causative
for depressive symptoms or an epiphenomenon of some
other neurobiological process, which may be mediated
by sex-related differences in neurobiology.
The differences in brain structure and function between
men and women, and how these alterations may relate to
the pathophysiology of mood disorders is a complex topic,
as dissecting which components are biologically deter-
mined and which are the consequence of environmental
conditioning due to gender-related sociocultural experience
is fraught with difficulty . Still, there is significant evi-
dence that there are sex-related differences in gene expres-
sion, epigenetic regulatory mechanisms, hypothalamus-
pituitary-adrenal axis regulation, and modulation of neuro-
transmitter systems by neurosteroids between men and
women, which may relate to differences in susceptibility to
neuropsychiatric illness [61-63]. It is currently not clear
how our neurophysiologic finding of increased SWA in
women with MDD may be related to any of these mechan-
isms, and thus, further research that examines SWA in re-
lation to sex-dependent hormonal, genetic, and epigenetic
mechanisms in mood disorders may provide deeper
insights into this conceptual framework.
In conclusion, sleep disturbance and MDD are intim-
ately linked; however, previous research that has exam-
inedthe role of SWA
inconsistent. This study demonstrates sex-related differ-
ences in SWA, in which women with MDD had elevated
SWA, most prominently in prefrontal regions and dur-
ing the first portion of the night. Failure to account for
sex-related differences in SWA and the use of limited
EEG derivations to perform spectral analysis in prior
investigations may have contributed to inconsistencies in
the literature. However, given the heterogeneity of MDD
[50,64], it is also plausible that other factors contribute
to alterations in SWA in the disorder. Further research
is indicated to examine the effects of sex-specific neuro-
biology, neurocognitive symptoms, and SWA in mood
disorders to clarify how increased SWA in women with
MDD is related to the pathophysiology of the disorder.
Additional file 1: Figure S1. Topographic SWA (1-4.5 Hz) during NREM1
in MDD subjects versus healthy controls, both unstratified and stratified
by sex. T-values plotted for the comparisons between groups (2-tailed,
unpaired t-test) at each channel. The minimum and maximum t-values
for each map are plotted in white and black respectively, with the
corresponding numeric range for color scale (upper left). Corresponding
p-values plotted for each channel with white dots denoting channels
with significant between-group differences following statistical non-
parametric mapping with suprathreshold cluster tests to correct for
DTP has owned stock in Pfizer, and has received honoraria from Oakstone
Medical Publishing and royalties from Cambridge University Press. MJP has
received unrelated research support from Sanofi-Aventis. GT has consulted
for Sanofi-Aventis and Takeda, and he is currently the David P. White Chair in
Sleep Medicine at the University of Wisconsin–Madison, endowed by Phillips
Respironics. GT has also received unrelated research support from Phillips
Respironics. RMB has consulted for Merck and Sanofi-Aventis. All other
authors declare they have no competing interests.
DTP designed the study, managed literature searches and analyses, and
wrote the initial and final draft of the manuscript. ECL and MJP contributed
to the study design, evaluation of participants, management of hdEEG
processing and analyses, and writing the article. MRG, TW, and JJG
performed statistical analyses and hdEEG processing, designed tables/figures,
and contributed to the writing of the manuscript. BA performed data
analysis and interpretation, and also contributed to the writing of the
manuscript. GT contributed to the study design, data analysis and
interpretation, and to writing the article. RMB contributed by being the
principal investigator, contributing to the study design, participating in data
analysis and interpretation, and writing the article. All authors contributed to
and have approved the final manuscript.
This research was funded by the National Institute of Mental Health
(5P20MH077967 to GT and RMB, and F30MH082601 to ECL) and the National
Alliance for Research on Schizophrenia and Depression Young Investigator
Award to MJP. The NIMH and NARSAD had no further role in the study
design, data collection, analysis and interpretation of the data, and the
decision to submit the paper for publication.
Received: 22 November 2011 Accepted: 10 September 2012
Published: 18 September 2012
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Cite this article as: Plante et al.: Sex-related differences in sleep slow
wave activity in major depressive disorder: a high-density EEG
investigation. BMC Psychiatry 2012 12:146.
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