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Psychoneuroendocrinology
journal homepage: www.elsevier.com/locate/psyneuen
Becoming a mother entails anatomical changes in the ventral striatum of the
human brain that facilitate its responsiveness to offspring cues
Elseline Hoekzemaa,b,
*, Christian K. Tamnesc,d,e
, Puck Bernsa,b
, Erika Barba-Müllerf
,
Cristina Pozzobong
, Marisol Picadof
, Florencio Luccog
, Magdalena Martínez-Garcíah,i
,
Manuel Descoj,h,i,k
, Agustín Ballesterosg
, Eveline A. Cronea,b
, Oscar Vilarroyaf,l
,
Susanna Carmonah,i,j
a
Brain and Development Research Center, Leiden University, Leiden, the Netherlands
b
Leiden Institute for Brain and Cognition (LIBC), Leiden University, Leiden, the Netherlands
c
PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
d
NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
e
Department of Psychiatry, Diakonhjemmet Hospital, Oslo, Norway
f
Unitat de Recerca en Neurociència Cognitiva, Departament de Psiquiatria i Medicina Legal, Universitat Autònoma de Barcelona, Barcelona, Spain
g
Instituto Valenciano de Infertilidad, Barcelona, Spain
h
Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
i
Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
j
Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Spain
k
Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Spain
l
Fundació IMIM, Barcelona, Spain
A R T I C L E I N F O
Keywords:
Pregnancy
Ventral striatum
Nucleus accumbens
Reward circuit
Maternal brain
MRI
A B S T R A C T
In mothers, offspring cues are associated with a powerful reinforcing value that motivates maternal care. Animal
studies show that this is mediated by dopamine release into the nucleus accumbens, a core component of the
brain’s reward system located in the ventral striatum (VStr). The VStr is also known to respond to infant signals
in human mothers. However, it is unknown whether pregnancy modifies the anatomy or functionality of this
structure, and whether such modifications underlie its strong reactivity to offspring cues. Therefore, we analyzed
structural and functional neuroimaging data from a unique pre-conception prospective cohort study involving
first-time mothers investigated before and after their pregnancy as well as nulliparous control women scanned at
similar time intervals. First, we delineated the anatomy of the VStr in each subject’s neuroanatomical space and
examined whether there are volumetric changes in this structure across sessions. Then, we tested if these changes
could predict the mothers’ brain responses to visual stimuli of their infants. We found decreases in the right VStr
and a trend for left VStr reductions in the women who were pregnant between sessions compared to the women
who were not. Furthermore, VStr volume reductions across pregnancy were associated with infant-related VStr
responses in the postpartum period, with stronger volume decreases predicting stronger functional activation to
offspring cues. These findings provide the first indications that the transition to motherhood renders anatomical
adaptations in the VStr that promote the strong responsiveness of a mother’s reward circuit to cues of her infant.
1. Introduction
Pregnancy involves radical hormone surges that trigger adaptations
in the female body and brain, which benefit the protection and development
of the fetus (Brunton and Russell, 2008). Furthermore, these
adaptations also facilitate the postpartum care and protection of
mammalian offspring, whose survival depends on the rapid onset and
adequate expression of maternal caregiving. Hormonal priming of the
mother’s brain stimulates the emergence of maternal behaviors, a set of
species-specific behaviors that promote the survival and optimal development
of the highly dependent offspring (Brunton and Russell,
2008; Kohl and Dulac, 2018; Leuner et al., 2010; Lonstein et al., 2015;
Numan, 2006; Numan and Woodside, 2010). Hormonal fluctuations in
human gestation and parturition, acting in concert with other prenatal
https://doi.org/10.1016/j.psyneuen.2019.104507
Received 20 June 2019; Received in revised form 31 October 2019; Accepted 1 November 2019
⁎
Corresponding author at: Brain and Development Research Center, Leiden University, Leiden, the Netherlands.
E-mail address: e.a.hoekzema@fsw.leidenuniv.nl (E. Hoekzema).
Psychoneuroendocrinology 112 (2020) 104507
0306-4530/ © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
T
factors (Farre-Sender et al., 2018; Jones et al., 2019; Marques et al.,
2013; Simon et al., 2009), have also been associated with diverse aspects
of postpartum child health and development and the emergence
of maternal attachment (Bergman et al., 2010; Levine et al., 2007;
O’Connor et al., 2013; Olza-Fernandez et al., 2014).
Animal studies show that changes in the hedonic value allocated to
pups play a central role in triggering the maternal drive to approach
and care for the young. While virgin female rats generally display
avoidant or aversive reactions to pup odors, for maternal animals these
represent a strongly rewarding stimulus and potent reinforcer (Fleming
et al., 1989, 1994). For instance, studies in various mammalian species
have shown that pregnant and postpartum females bar-press for contact
with newborns (Hauser and Gandelman, 1985; Lee et al., 2000; Pryce
et al. 1993; Wilsoncroft, 1969). Accordingly, using a place preference
paradigm, maternal rats have been demonstrated to prefer pup-associated
chambers to chambers coupled with other rewards, such as cocaine
or food (Fleming et al., 1994; Mattson et al., 2001).
The powerful reinforcing value associated with stimuli of the young
is mediated by the activation of the mesolimbic reward circuit. This
circuit is thought to act as a driving force in translating biologically
relevant stimuli into adaptive responses and plays a key role in the
emergence of maternal behavior due to its role in motivation, reward
and the hedonic value of stimuli (Brunton and Russell, 2008; Kohl and
Dulac, 2018; Leuner et al., 2010; Lonstein et al., 2015; Numan, 2006;
Numan and Woodside, 2010). In maternal animals, this system is recruited
by exposure to pup-related stimuli. For instance, a functional
magnetic resonance imaging study in postpartum rats demonstrated
that pup suckling strongly activates brain regions pertaining to the
reward system (Febo et al., 2005; Ferris et al., 2005). In fact, sucklinginduced
activation exceeded the neural response to cocaine within
these reward-related areas (Ferris et al., 2005).
In response to pup cues, projections from the medial preoptic area to
the ventral tegmental area trigger dopamine release into the nucleus
accumbens, a core node of the mesolimbic reward circuit that integrates
multiple mesolimbic dopaminergic afferents and glutamatergic corticolimbic
projections (Haber and Knutson, 2010; Ikemoto, 2007; Knutson
and Cooper, 2005; Robbins and Everitt, 1996). This pup-induced recruitment
of the mesolimbic reward circuit is critical for the expression
of adequate maternal behaviors. For instance, lesions to the nucleus
accumbens shell disrupt pup retrieval (Li and Fleming, 2003), and low
levels of maternal care are associated with reduced dopamine release in
response to pup cues within the nucleus accumbens (Champagne et al.,
2004). Pup-associated cues, mediated by dopamine signaling in the
nucleus accumbens, thus represent a powerful reinforcer for maternal
animals that motivate the approach and caregiving of pups.
Hormonal priming of the brain during late pregnancy and parturition
plays a central role in the switch from pup avoidance to approach
and the induction of maternal behaviors (Brunton and Russell, 2008;
Kohl and Dulac, 2018; Leuner et al., 2010; Lonstein et al., 2015;
Numan, 2006; Numan and Woodside, 2010). Studies in various animal
species have shown that pregnancy hormones can trigger maternal
motivation. For instance, pregnancy-mimicking hormone treatments in
female rodents and monkeys have been demonstrated to increase the
frequency of bar pressing for stimuli related to the young and induce a
preference for young animals over food (Champagne et al., 2004; Li and
Fleming, 2003, Pryce et al., 1993). Pregnancy thus involves shifts in
pup-associated hedonic value and represents a sensitive period for
priming the reward circuit to optimally respond to offspring cues.
In humans, fMRI studies have also shown that the ventral striatum
(VStr) —the region containing the nucleus accumbens—is activated in
mothers in response to pictures or sounds of their child (Atzil et al.,
2011; Lorberbaum et al., 2002; Strathearn et al., 2008; Swain, 2011),
and the mesolimbic reward circuit is considered a crucial part of the
human maternal brain (Barba-Müller et al., 2019; Kim et al., 2015).
Links between the response of the VStr to infant cues and maternal
behavior have also been observed in human mothers. For instance,
mothers displaying primarily synchronous caregiving behaviors more
strongly activate the VStr in response to movies of their infants than
mothers showing mainly intrusive behaviors, and VStr activity is
functionally correlated with emotion regulation, theory of mind and
empathy networks, known to play a key role in human maternal behavior
(Atzil et al., 2011). In a previous study, we have shown that
pregnancy renders pronounced changes in the grey matter volume of
the human brain, located primarily in higher-order association areas of
the cortex involved in social cognition (Hoekzema et al., 2017). However,
it is unknown whether pregnancy is associated with changes in the
mesolimbic reward circuit that prepare a woman’s brain to maximally
respond to offspring cues. We hypothesized that pregnancy entails
modifications in the VStr that are associated with its subsequent functional
response to the women’s infants.
We have previously shown that the cortical morphometric changes
taking place during pregnancy highly resemble those that occur during
adolescence (Carmona et al., 2019), and we expect that the relation
between anatomy and function with regard to pregnancy-related neuroplasticity
follows a pattern similar to that observed in adolescence.
Studies in adolescent samples have found a negative correlation between
grey matter cortical thickness and the magnitude of activation,
with a thinner cortex in fronto-parietal regions being associated with a
stronger activation of these areas while performing tasks recruiting
those regions (Lu et al., 2009; Nunez et al., 2011). The biological mechanisms
mediating this inverse relation are unknown, but synaptic
pruning is considered to play an important role. Synaptic pruning
during developmental periods could not only contribute to decreasing
the thickness of the cortex but also increase the efficiency and selectivity
of synaptic activity, thus producing greater activation
(Anurova et al., 2015). Therefore, we predicted that stronger volume
reductions in the VStr would be associated with a stronger activation of
this region in response to offspring cues.
In this study, we measured VStr volume in structural magnetic resonance
imaging (MRI) brain scans of first-time mothers investigated
before and after their pregnancy, using a unique prospective pre-conception
cohort neuroimaging dataset (Hoekzema et al., 2017). Considering
the lack of clear signal intensity boundaries that hampers the
automatic demarcation of the VStr (Patenaude et al., 2011; Loh et al.,
2014; Nugent et al., 2013), we used a reliable previously established
manual delineation approach for investigating VStr anatomy (Carmona
et al., 2009, 2012; Gunduz et al., 2002; Hoekzema et al., 2014). We
then compared the VStr volumetric changes observed in first-time
mothers to those obtained in a control group of nulliparous women
scanned at similar time intervals. Furthermore, we tested if VStr volumetric
changes induced by pregnancy could predict VStr functional
responses to offspring cues after birth, using a postpartum fMRI paradigm
involving pictures of own and other infants. This allowed us to
examine—for the first time—whether pregnancy alters VStr volume in a
woman’s brain, and whether these changes are associated with the infant-related
VStr recruitment of the brain’s reward circuit that forms a
crucial part of the maternal brain.
2. Methods
2.1. Design
The data were acquired by means of a prospective cohort study that
was set up to examine the effects of pregnancy on the human brain. For
this study, nulliparous women participated in an MRI acquisition before
and after the pregnancy of their first child (hereafter referred to as the
‘Pre’ and ‘Post’ sessions respectively), allowing us to use each woman’s
pre-pregnancy brain scan as her individual baseline. A subsample additionally
participated in another follow-up session around 2 years after
birth (the ‘Post +2 years’ session). Two groups of nulliparous women
were recruited for this study, namely nulliparous women who were
planning to try to become pregnant in the near future and nulliparous
E. Hoekzema, et al. Psychoneuroendocrinology 112 (2020) 104507
2
women without such plans. Although individuals were recruited separately
for these groups based on their intention to become parents in the
near future, the final group allocation depended on the actual transition
from nulliparity into primiparity in between sessions. The final sample
of primiparous women (hereafter referred to as the ‘PRG’ group) and
nulliparous control women (the ‘CTR’ group) with complete longitudinal
datasets is described in the Results section.
The women who were not pregnant between sessions were also
investigated longitudinally with a comparable time interval. The participants
were recruited via the fertility center Instituto Valenciano de
Infertilidad (IVI, Barcelona), by flyers and by word of mouth.
Recruitment and data collection for all groups was initiated at the same
time. Sixty-five nulliparous women were scanned for the first time
point, including 43 women who wanted to become pregnant with their
first child. Pre-established exclusion criteria comprised having experienced
a previous pregnancy beyond the first trimester, neurological or
psychiatric conditions, or a history of substance use disorders as assessed
by means of the MINI International Neuropsychiatric Interview,
applied by a clinical psychologist (Sheehan et al., 1998).
The study was approved by the local ethics committee (Comitè Ètic
d’Investigació Clinica de l’Institut Municipal d’Assistència Sanitària),
and written informed consent was obtained from all subjects before
their participation in the study. For a more detailed and elaborate description
of the sample, recruitment and approach used in this study,
see Hoekzema et al. (Hoekzema et al., 2017).
2.2. MRI acquisitions
MRI images for all sessions were obtained in a Philips 3 T scanner.
High-resolution anatomical MRI brain scans were acquired using a T1weighted
gradient echo pulse sequence (TR = 8.2 ms, TE =3.7 ms,
NSA = 1, matrix = 256 × 256, FOV = 240 mm, 180 slices, voxel
size = 0.94 × 0.94 × 1 mm, no gap, flip angle 8°). The Post MRI session
also included an fMRI paradigm (T2*-weighted gradient echo EPI sequence.
TR = 3000 ms, TE =35 ms, matrix = 128 × 128,
FOV = 230 mm, 30 slices, voxel size = 1.8 × 1.8 × 4 mm, gap 0.5 mm,
flip angle 90°) that examined the new mothers' neural responses to their
babies. During the Post MRI session, images of the participant’s own
baby and of other unknown babies were shown using presentation
software (NeuroBehavioral Systems). The images represented cut-out
faces on a black background and were matched for size, resolution,
brightness and facial expression. For each participant, 28 images of her
own baby (14 of each infant in case of twins) and 28 images of another
unknown baby were presented in randomized order in an event-related
fashion (trial duration 1500 ms, randomized inter-trial interval
750–1250 ms), with an average number of trials of (M ± SD)
72.15 ± 6.64 and 72.40 ± 6.99 for the other baby and own baby
conditions respectively. For more details on this paradigm, see
Hoekzema et al. (Hoekzema et al., 2017).
Due to an unexpected technical problem, the radio frequency head
coil was replaced for some time with another head coil, and 28 scans in
total were acquired using the latter coil. There were no significant
differences between the groups in the number of scans acquired with
this head coil (χ2
= 4.21, P = 0.240). The head coil was introduced as
a nuisance covariate in all analyses, except for the analyses involving
the Post +2 years session where the coil was matched to the previous
session.
Five participants could not be included in the fMRI analyses due to
head motion (1 woman), artifacts in the data (2 women), or incomplete
data sets (2 women), rendering a sample of 20 primiparous women for
this part of the study (age at Pre session: 32.85 ± 4.13).
2.3. Delineation of the VStr
Considering the lack of clear boundaries in signal intensity that
hinders the demarcation of the VStr by automated approaches
(Patenaude et al., 2011; Loh et al., 2014; Nugent et al., 2013) as well as
potential biases resulting from the normalization process, we measured
VStr volumes in each subject’s native neuroanatomical space using a
previously established manual delineation approach (Carmona et al.
2009; Gunduz et al., 2002; Hoekzema et al., 2014; Carmona et al.,
2012). This represents a reliable—albeit time-consuming and laborintensive—method
for investigating VStr volume that renders volumes
that are in line with histological approaches (Lauer et al., 2001).
Prior to region of interest (ROI) delineation, the anatomical MRI
images were oriented into standardized head positions based on AC-PC
landmarks using a reorientation script (https://doi.org/10.5281/zenodo.2000727)
implemented in Matlab R2017b (www.mathworks.
com) and were visually examined to confirm adequate positioning.
Visualization and delineation of the images was performed with
MRIcroN software (http://www.cabiatl.com/ mricro/mricron). The
VStr was manually delineated on coronal slices according to previously
established criteria (Carmona et al., 2009; Gunduz et al., 2002;
Hoekzema et al., 2014; Carmona et al., 2012). In short, we used the
following landmarks: (1) the posterior limit of the VStr was established
as the most caudal slice anterior to the anterior commissure; (2) a line
perpendicular to the internal capsule demarcated the VStr region,
starting at the most inferior and external point of the lateral ventricle;
(3) the anterior limit was set as the most rostral slice before the external
capsule separated the caudate from the putamen; (4) the paraolfactory
gyrus delimitated the inferior and medial boundaries of the VStr. See
Fig. 1 for an illustration of the delimitation criteria. The delineation was
performed by two raters, who were blind to group and session information.
Following the training period, the inter-rater reliability was
computed based on 10 repeated regions of interest using intra-class
correlation coefficients (ICC: absolute agreement: left VStr: ICC = 0.95;
right VStr: ICC = 0.97).Volumes of the individual VStr ROIs were obtained
by multiplying the number of voxels included in the ROI by
voxel volume. VStr volumes are indicated in cubic millimeters.
2.4. Analyses of VStr volume
Statistical analyses were performed with SPSS 23 (IBM), using repeated-measures
general linear models with session (Pre/Post) as the
within-subjects factor and group (PRG/CTR) as the between-subjects
factor. First, we computed relative VStr volumes expressed as a
Fig. 1. Illustration of the delineation of the ventral striatum based on the described
criteria.
E. Hoekzema, et al. Psychoneuroendocrinology 112 (2020) 104507
3
percentage of total brain volume (TBV) (including total grey matter and
white matter volume) extracted from FreeSurfer 6.0 (http://surfer.nmr.
mgh.harvard.edu) (Fischl et al., 2002). This allowed us to correct for
the changes in total brain volume previously associated with pregnancy
(Rutherford et al., 2003) that were also observed in this sample
(Carmona et al., 2019; Hoekzema et al., 2017). The TBV-corrected
measures were used for subsequent analyses, although the results involving
the absolute volumes are also provided in the supplementary
material. In addition, to examine the specificity of these changes for the
ventral part of the striatum, we additionally investigated volume
changes in the dorsal striatum. Since the caudate and putamen can be
delineated with automatic approaches with a high accuracy based on
differences in signal intensity demarcating the boundaries of these
structures (Dewey et al., 2010), we extracted caudate and putamen
volumes using FreeSurfer and summed these to obtain a measure of the
dorsal striatum. Like the VStr volumes, the dorsal striatum measures
were corrected for total brain volume and examined using repeated
measures general linear models. Left and right volumes were separately
examined for all striatal measures since interhemispheric asymmetries
have been identified in the dopaminergic system—a highly evolutionarily
conserved system (Hoekzema et al. 2010; Perez-Fernandez et al.,
2014; Puig et al., 2014; Ryczko et al., 2016)—in rodent striata (Drew
et al., 1986; Molochnikov and Cohen, 2014).
To examine the effects of the duration of exposure to postpartum
factors (i.e. the time between parturition and the Post scan) on VStr
volume, Spearman’s correlation analyses were performed with this time
interval since this variable was not normally distributed. To further
investigate the possibility of postpartum factors affecting VStr volume,
we additionally extracted VStr measures from the Post+2 years session
and compared these to those extracted from the early postpartum session
using paired samples t-tests. For exploratory purposes, we additionally
examined whether the type of delivery (natural delivery
versus caesarean section) or breastfeeding status (breastfeeding or not
at the time of the session) were associated with distinct changes in VStr
volume by means of repeated measures general linear models, although
only small samples are available for these exploratory analyses. Results
were considered significant when below the statistical threshold of
p < 0.05.
2.5. Functional MRI analyses
Postpartum neural responses within the VStr were examined by
means of an fMRI task that has previously been used to examine mothers’
neural responses to their infants (Swain et al., 2007; Swain,
2011). First, the fMRI data were processed and analyzed in normalized
space to confirm the activation of this structure in human mothers in
response to cues of their infants. Then, each subject’s fMRI data was
processed in native space to allow extracting individual VStr responses
based on the delineated VStr regions. Analyses of the functional MRI
data were performed with SPM12 (https://www.fil.ion.ucl.ac.uk/spm/
).
2.5.1. Group analyses in MNI space
The functional images were first corrected for differences in slice
acquisition timing and realigned to the first volume. Motion parameters
were examined in Matlab for the presence of any frame-wise displacements
exceeding 3 mm (for translations) or 3° (for rotations).
Participants with any head movement that did not meet these criteria
were excluded from further analyses (1 woman).The movement parameters
were also included as covariates in subsequent analyses. Then,
the anatomical images were co-registered to the mean functional image
and normalized into MNI (ICBM) space using nonlinear registration
(Ashburner and Friston, 2005). Finally, the normalization parameters
and a full-width at half-maximum smoothing kernel of 12 mm were
applied to the functional images.
At the first level of analysis, general linear models were used to
model voxel-wise changes in BOLD response for the conditions of interest,
also including the movement parameters extracted during the
realignment and regressors based on temporal basis functions. The firstlevel
parameter estimates for the linear contrast ‘own baby pictures
> other baby pictures’ were entered into a second-level model
and one-sample t-tests were performed to examine whether new mothers
show a differential pattern of neural activity in response to pictures
of their own or other babies. To examine neural activity within the
VStr, ROIs of the left and right VStr drawn on a template image in
MRIcroN were applied to this model using Small Volume Correction.
The extracted p-values were Family-Wise Error (FWE)-corrected.
2.5.2. Extraction contrast values in native space
To examine whether the changes in VStr volume across pregnancy
were associated with this structure’s subsequent reactivity to the women’s
infants, we additionally processed each subject’s fMRI data in
native space and applied the individually delineated regions of interest
to extract estimates of VStr responsivity. This processing pipeline also
involved correcting the functional images for slice acquisition timing
and realigning the images to the first volume. Subsequently, the coregistration
parameters resulting from the co-registration of the mean
functional image to the anatomical image were applied to all functional
images, followed by the application of a 12 mm smoothing kernel.
These functional data were then entered into first-level general linear
models.
These native-space models were then loaded into MarsBar 0.44
(http://marsbar.sourceforge.net/), where each person’s individual left
and right VStr ROIs were applied to the ‘own baby pictures > other
baby pictures’ contrast. The contrast estimates extracted from MarsBar
were subsequently entered into Spearman’s correlation analyses with
the variables representing the change in VStr volume across pregnancy
(the Post-Pre VStr volumes) for each hemisphere.
3. Results
3.1. Sample
Table 1 provides demographic and clinical information of the
sample. Our final sample consisted of 25 primiparous women (the ‘PRG’
group) and 20 nulliparous control women (the ‘CTR’ group) with
complete Pre and Post datasets. Unless explicitly stated otherwise, these
represent the sample sizes used in the comparisons. The Post session
took place on average at 73.56 ± 47.83 days (M ± SD) after parturition.
Our sample of primiparous women was additionally asked to
participate in another MRI session around 2 years after delivery. Of
these 25 women, 11 had not yet experienced a (partial) second pregnancy
since the last MRI session and were willing and able to participate
in this follow-up session (mean time since birth: M ± SD:
2.32 ± 0.50 years, age at Pre scan: 33.72 ± 3.32 years). There were
no statistically significant differences in Pre-to-Post time interval, age
or level of education between the PRG and CTR groups. Nonetheless, to
control for potential confounding factors, we also repeated our main
between-group analyses including these variables (age, educational
level, time between Pre and Post session, previous medical conditions,
relationship status) as covariates.
3.2. Changes in VStr volume across pregnancy
Repeated measures general linear models were applied to compare
the TBV-corrected VStr volume changes across sessions between women
who were pregnant between sessions and women who were not. These
analyses demonstrated a group (PRG/CTR) x session (Pre/Post) interaction
effect for the right VStr and a statistical trend for the left VStr
(VStr volumes (%TBV): M ± SD. Left: PRG: Pre: 0.031 ± 0.017, Post:
0.028 ± 0.015. CTR: Pre: 0.030 ± 0.013. Post: 0.031 ± 0.014.
F = 3.353, p = 0.074. Right: PRG: Pre: 0.035 ± 0.016, Post:
E. Hoekzema, et al. Psychoneuroendocrinology 112 (2020) 104507
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0.026 ± 0.014. CTR: Pre: 0.029 ± 0.015, Post: 0.029 ± 0.017.
F = 9.652, p = 0.003). Paired samples t-tests examining the changes
within each of the groups confirmed that the observed effect reflected
changes in the PRG sample (Left: t = 1.709, p = 0.100, Right:
t = 4.997, p < 0.001) while no changes in volume were observed in
the CTR group (Left: t = 0.891, p = 0.384, Right: t = 0.048,
p = 0.962). More specifically, the women who were pregnant between
the sessions were found to undergo reductions in VStr volume, comprising
volume decreases of 7 % and 26 % in terms of the average
volume change for the left and right VStr respectively. VStr volumes are
depicted in Fig. 2.
In addition, to test if the observed reductions specifically affected
the ventral part of the striatum, we examined whether pregnancy is
associated with volumetric changes in the dorsal striatum (the part of
the striatum comprising the caudate and putamen). Repeated measures
general linear models on dorsal striatal volumes revealed no significant
group x session interactions (Dorsal striatal volumes (%TBV): M ± SD:
Left: PRG: Pre: 0.925 ± 0.0062, Post: 0.915 ± 0.072. CTR: Pre:
0.910 ± 0.097, Post: 0.908 ± 0.0098. F = 0.797, p = 0.377. Right:
PRG: Pre: 0.927 ± 0.071, Post: 0.919 ± 0.071. CTR: Pre:
0.916 ± 0.086, Post: 0.910 ± 0.088. F = 0.104, p = 0.749), hereby
supporting the relative specificity of the changes for the ventral
striatum.
When repeating our main analyses including the demographic and
Table 1
Sample demographics.
Characteristic Primiparous women Nulliparous control women Between-group differences
Sample Size [nº subjects with complete longitudinal data]
Pre and Post session 25 20
Pre, Post and Post +2 session 11 –
fMRI paradigm 20 –
Age at Pre [years]
Mean ± SD 33.36 ± 3.97 31.10 ± 5.63 t = 1.58; p = 0.123
Education [nº subjects] X² = 0.06; p = 0.971
Secondary school 2 2
College 4 3
University 19 15
Pre-Post time [days]
Mean ± SD 463.52 ± 108.33 413.05 ± 106.86 t = 1.56; p = 0.126
Type of conception
Natural 9 –
Assisted 16 –
Type of parturition
Vaginal 17 –
Caesarean section 8 –
Breastfeeding status
Breastfeeding 18 –
Formula 7 –
Previous medical conditions
Depression/anxiety 3 1
Thyroid disorder 3 –
Anorexia 1 0
Endometriosis 1 1
Cholesterol / low blood glucose / hypertension 1 1
Relationship status [n.º subjects in stable relationship] 24 19
Mean ± SD [years] 6.49 ± 3.52 5.62 ± 7.17 t=-0.642; p = 0.525
Demographic and clinical information of the sample. There were no statistically significant differences in any of these variables (age, level of education, time between
the scans or relationship duration) between the groups. SD = standard deviation, t = t-statistic, p = p-value.
Fig. 2. VStr volumes. a) Scatter plots depicting the changes in TBV-corrected VStr volumes in women who were pregnant between sessions (PRG) and women who
were not (CTR). b) Violin plots depicting TBV-corrected VStr volumes for the women who were pregnant between sessions for the pre-conception (PRE) and postpregnancy
(POST) sessions. c) Bar charts depicting TBV-corrected VStr volume (M ± SEM) for each of the three sessions in the PRG group. TBV = Total Brain
Volume, PRE = pre-conception baseline session, POST = early postpartum session, POST+2yrs = postpartum session around 2 years after giving birth.
E. Hoekzema, et al. Psychoneuroendocrinology 112 (2020) 104507
5
clinical variables from Table 1 (age at the Pre session, educational level,
time between the Pre and Post sessions, previous medical conditions
and relationship status) as confounding factors, we observed highly
similar results (Left: F = 7.034, p = 0.012, Right: F = 12.953,
p = 0.001), although both the left and right VStr now showed significant
reductions across pregnancy.
Furthermore, in addition to TBV-corrected volumes, we also examined
whether we could observe changes in absolute VStr volumes.
These analyses rendered similar results, although significant group x
session interaction effects were found for both hemispheres rather than
a statistical trend for the left VStr (see Supplementary Table 1).
Finally, to confirm the absence of pre-existing group differences, we
also compared VStr volume at the baseline session between the groups.
These analyses rendered no significant results, neither for the absolute
(Left: t = 0.161, p = 0.873, Right: t = 1.145, p = 0.258) nor the TBVcorrected
volumes (Left: t = 0.275, p = 0.784, Right: t = 1.247,
p = 0.219), indicating that there were no significant differences between
the groups at baseline (see Supplementary Fig. 1).
Exploratory analyses examining the effects of type of delivery or
breastfeeding status on the changes in VStr volume rendered no significant
results (all P-values > 0.05, see Supplementary Tables 2–3).
3.3. Postpartum factors
Since the time period between the first and second scan also included
a fraction of the early postpartum period, we additionally performed
correlation analyses with the duration of exposure to postpartum
factors. These analyses indicated no significant associations
between changes in VStr volume and the length of the postpartum
period included within this time frame for the left (rs = 0.075,
p = 0.721) or the right VStr (rs=-0.041, p = 0.845).
In addition, to investigate whether changes in VStr volume could be
observed across the postpartum period, we additionally delineated the
VStr in the subjects who participated in a long-term follow-up session
acquired around 2 years after giving birth. Comparisons between the
early and late postpartum sessions indicated no further significant
changes in VStr volume across this time period, neither for the left VStr
nor the right VStr (M ± SD: Left: Post: 0.0298 ± 0.015, Post +2:
0.0267 ± 0.006, t = 1.033, p = 0.326. Right: Post: 0.0284 ± 0.013,
Post +2: 0.0264 ± 0.012, t = 0.461, p = 0.655), while the volume
reductions across pregnancy in the right VStr could also be observed
within this subsample (Left VStr: t = 0.551, p = 0.594, Right VStr:
t = 3.018, p = 0.013).
3.4. Ventro-striatal responses to offspring cues
To examine VStr activity in our sample of mothers in response to
visual cues of their babies, we performed group analyses on normalized
fMRI data and applied regions of interest of the left and right VStr that
were delineated in MNI space. These analyses indicated that both the
left and right VStr were strongly activated in response to own infant
cues in comparison to other infant cues (Left VStr: MNI coordinates:
x=-6, y = 12, z=-4, t = 5.45, p < 0.001 FWE-corrected. Right VStr:
MNI coordinates: x = 6, y = 14, z = 0, t = 4.90, p = 0.002, x = 10,
y = 8, z = 0, T = 4.27, p = 0.005 FWE-corrected, see Supplementary
Fig. 2), hereby supporting the involvement of this structure in the
human maternal brain. For completeness, whole-brain results for the
‘own baby pictures > other baby pictures’ and the reverse contrast are
provided in Supplementary Table 4.
3.5. Relation between VStr volume changes and VStr activity
Next, we applied each woman’s individual postpartum VStr ROIs to
her postpartum fMRI data processed in native space in order to allow
extracting a reliable indication of individual VStr activity in response to
cues of her infant. The extracted contrast values were then correlated
with the individually extracted changes in VStr volume across sessions
(the Post-Pre VStr volumes) to examine whether the changes in VStr
volumes across pregnancy were associated with a woman’s neural response
to her baby in this brain region. These analyses indicated that
the changes in right VStr volume were negatively associated with this
structure’s reactivity to own baby cues in the postpartum period (r =
-0.654, p = 0 .002), while no relation was observed between left VStr
volumetric changes and left VStr activity (r = 0.021, p = .930). Our
results thus indicate that stronger reductions in right VStr volume
across pregnancy are related to a stronger recruitment of this structure
in response to the women’s infants (see Fig. 3).
4. Discussion
In this paper, we set out to examine whether becoming a mother
renders changes in VStr structure that facilitate its responsivity to offspring
cues, using a unique pre-conception prospective dataset and a
reliable manual neuroanatomical delineation approach. Our results
indicate that pregnancy modifies the anatomy of the VStr. More specifically,
we found significant reductions in right VStr volume in women
who were pregnant between sessions compared to women who were
not and a trend for left VStr volume reductions, although it should be
noted that significant reductions were also observed in the left VStr
when investigating absolute volumes or when including demographic/
clinical variables as confounding factors. These effects were evident
when controlling for total brain volume and were not observed for the
dorsal part of the striatum, indicating that the VStr is specifically affected
across this period. When examining the functional activation of
the VStr, we found that the structural changes of the VStr across
pregnancy are associated with this structure’s subsequent responsiveness
to the women’s infants, with stronger right VStr volume reductions
predicting stronger functional activation to offspring cues. These findings
thus demonstrate that the VStr is anatomically modified across
pregnancy in women, and that these structural changes are associated
with this structure’s functional responses to the women’s babies.
In maternal animals, dopamine is released into the VStr in response
to pup-related cues, which is critical for the female’s maternal motivation
and the adequate expression of caregiving behaviors
(Champagne et al., 2004; Fleming et al., 1994). Studies in human mothers
have also demonstrated that this structure responds to offspring
cues (Atzil et al., 2011; Lorberbaum et al., 2002; Strathearn et al., 2008;
Swain, 2011), a finding that was replicated in the present study. The
current observations that the VStr undergoes anatomical changes across
pregnancy suggest that a woman’s neural reward circuit undergoes
adaptive changes during this preparatory phase to facilitate the pending
transition to motherhood. Accordingly, the observed link between volume
reductions across pregnancy and stronger activity in response to
cues that are highly relevant for new mothers may point to a
Fig. 3. Correlation between VStr volume changes and postpartum VStr activity.
Scatter plot depicting the correlation between right VStr volume changes (total
brain volume-corrected) and VStr activation to offspring cues as extracted by
applying the individually defined regions of interest to the fMRI data in native
space.
E. Hoekzema, et al. Psychoneuroendocrinology 112 (2020) 104507
6
specialization in the reward system that prepares a woman’s reward
circuit for maximal responsiveness to cues of her infant. It should be
noted that these findings do not infer a generalized heightened responsivity
of the mesolimbic reward system, but rather a strong reactivity
to specific stimuli that are highly relevant to a new mother, i.e.
to cues of her infant. In fact, an fMRI study in rats found that the reward
circuitry of postpartum females, while being recruited to a greater degree
by pup-related cues, was much less responsive to cocaine than in
non-mothers (Ferris et al., 2005), suggestive of a specific specialization
for contextually relevant stimuli in the brain’s reward system.
Volume reductions, as observed in the current study, can signify a
process of neurodegeneration, but can also represent a hallmark of
neural specialization. For instance, in adolescence, reductions in grey
matter volume are regarded as a refinement and specialization of brain
circuitry. Grey matter volume decreases across this period are thought
to reflect, at least in part, a process of synaptic pruning accompanied by
corresponding reductions in metabolic requirements and glial cells as
well as increased myelination (Blakemore, 2008; Peper et al., 2011; Sisk
and Zehr, 2005; Mills and Tamnes, 2014). Given the apparent similarities
between the changes occurring across pregnancy and adolescence,
in a previous study we compared the morphometric characteristics of
the modifications in the cortical mantle across these two hormonedriven
transitional stages of life (Carmona et al., 2019). Interestingly,
these analyses revealed a highly similar profile of anatomical alterations,
providing further support for the notion that similar neurobiological
processes may shape the brain in these periods of extreme
hormone changes. Interestingly, a study investigating both cortical grey
matter thickness and brain activity in adolescents showed that a thinner
cortical mantle was associated with increased brain activity on relevant
tasks within these networks (Lu et al., 2009), a finding that is in line
with the relation between volume reductions and stronger activity observed
in the current study. Considering the strong responsiveness of
the VStr to the women’s infants as well as the link between volume
reductions and greater activity within this structure, the observed
findings do not seem to point to a neurodegenerative process but are
suggestive of a specialization of the brain’s reward system that promotes
its reactivity to offspring cues in the maternal brain. Although
the cellular mechanisms underlying the observed changes cannot be
elucidated based on MRI data, which represents a limitation of neuroimaging
studies such as ours, our findings thus provide preliminary
support for a functional specialization rather than a loss of function.
In addition to investigating the changes in the VStr across pregnancy,
we examined whether we could find indications of postpartum
factors affecting VStr anatomy such as sleep loss or interaction with the
infant. Correlation analyses with the duration of exposure to postpartum
factors rendered no significant results. Furthermore, we compared
VStr volumes derived from the sessions in the early postpartum
period and those around 2 years after giving birth. In accordance with
our correlation results, these analyses revealed no changes in VStr volume
across the first two years of motherhood. Taken together, these
results suggest that adaptive changes in the reward system primarily
occur during pregnancy, presumably driven by the strong endocrine
changes associated with this period. Accordingly, studies in various
animal species have stressed the role of pregnancy hormones in the
emergence of the maternal motivational drive. For instance, a pregnancy-mimicking
treatment of estradiol and progesterone was found to
induce a preference for pups over food in a conditioned place preference
task in female rats (Fleming et al., 1994) and an increased
frequency of bar pressing for maternal reinforcement in marmoset
monkeys (Pryce et al., 1993). However, it should be noted that it is not
possible to discern the factors contributing to the observed changes
based on our data. Unfortunately, due to logistic challenges, hormone
samples could not be obtained from our participants during pregnancy.
This represents an important limitation of this study, as this hampers
revealing the mechanisms driving this neuroplasticity. Furthermore,
maternal brain changes are likely to represent an interplay between
environmental and endocrine factors, and future research monitoring
various endocrine and environmental factors in detail is needed to
address this limitation and further pinpoint the mediators driving the
observed neural plasticity.
When examining our results, it seems that the observed effects are
asymmetrical with regard to hemisphere and are generally stronger in
the right than the left VStr. For instance, significant changes in VStr
volume were only detected in the right hemisphere, while a statistical
trend was observed for changes in the left VStr. Likewise, while the VStr
was activated bilaterally in response to infant cues, a significant association
between VStr volume changes and VStr activity was only observed
for the right VStr. Some previous studies investigating the neural
responses to own infant cues in comparison to stimuli derived from
other infants found only right-lateralized VStr activity (Atzil et al.,
2011; Lorberbaum et al., 2002), although another study observed VStr
activation only in the left hemisphere (Strathearn et al., 2008). Interestingly,
interhemispheric asymmetries have repeatedly been demonstrated
in the mesostriatal dopaminergic system (Molochnikov and
Cohen, 2014). For instance, female rats have higher dopamine D2 receptor
densities in the right striatum (Drew et al., 1986). In humans,
indications have also been observed of increased right-sided ventrostriatal
dopamine release in humans during rest and in response to
rewarding stimuli (Cannon et al., 2009; Martin-Soelch et al., 2011).
Functional connectivity analyses of VStr lateralization suggest that the
left VStr is more related to internally directed processes, while the right
VStr is more strongly involved in externally oriented processes (Zhang
et al., 2017), providing a potential framework for interpreting stronger
right-sided effects as a mother’s reactivity to infants involves a strong
focus on external stimuli. However, the presence and significance of a
potential hemispheric lateralization in this context remain to be de-
termined.
Taken together, we have shown that becoming a mother entails
anatomical alterations in a core structure of the brain’s reward system
that is known to play a key role in the human and non-human animal
maternal brain. Furthermore, these changes were associated with a
stronger response within this structure to the women’s babies after
birth. These results suggest that pregnancy triggers neuroanatomical
adaptations within the VStr that prepare a woman’s reward circuit to
maximally respond to cues of her infant, hereby increasing the incentive
value of the newborn.
Declaration of Competing Interest
None.
Acknowledgements
This project was supported by an Innovational Research Incentives
Scheme grant (Veni, 451-14-036) by the Netherlands Organisation for
Scientific Research (NWO), the Netherlands, and a NARSAD Grant from
the Brain & Behavior Research Foundation, U.S.A. (grant number
25312) awarded to Elseline Hoekzema, as well as a Ministerio de
Ciencia, Innovación y Universidades (Spain) Instituto de Salud Carlos
III project (PI17/00064) and a Miguel Servet Type I research contract
CP16/00096 awarded to Susanna Carmona. In addition, Magdalena
Martínez-García was funded by a Ministerio de Ciencia, Innovación y
Universidades (Spain), Instituto de Salud Carlos III (PFIS contract FI18/
00255) grant.
Appendix A. Supplementary data
Supplementary material related to this article can be found, in the
online version, at doi:10.1016/j.psyneuen.2019.104507.
E. Hoekzema, et al. Psychoneuroendocrinology 112 (2020) 104507
7
References
Anurova, I., Renier, L.A., De Volder, A.G., Carlson, S., Rauschecker, J.P., 2015.
Relationship between cortical thickness and functional activation in the early blind.
Cereb. Cortex 25, 2035–2048.
Ashburner, J., Friston, K.J., 2005. Unified segmentation. Neuroimage. 26, 839–851.
Atzil, S., Hendler, T., Feldman, R., 2011. Specifying the neurobiological basis of human
attachment: brain, hormones, and behavior in synchronous and intrusive mothers.
Neuropsychopharmacology 36, 2603–2615.
Barba-Müller, E., Craddock, S., Carmona, S., Hoekzema, E., 2019. Brain plasticity in
pregnancy and the postpartum period: links to maternal caregiving and mental
health. Arch. Womens Ment. Health.
Bergman, K., Sarkar, P., Glover, V., O’Connor, T.G., 2010. Maternal prenatal cortisol and
infant cognitive development: moderation by infant-mother attachment. Biol.
Psychiatry 67, 1026–1032.
Blakemore, S.J., 2008. The social brain in adolescence. Nat. Rev. Neurosci. 9, 267–277.
Brunton, P.J., Russell, J.A., 2008. The expectant brain: adapting for motherhood. Nat.
Rev. Neurosci. 9, 11–25.
Cannon, D.M., Klaver, J.M., Peck, S.A., Rallis-Voak, D., Erickson, K., Drevets, W.C., 2009.
Dopamine type-1 receptor binding in major depressive disorder assessed using positron
emission tomography and [11C]NNC-112. Neuropsychopharmacology 34,
1277–1287.
Carmona, S., Hoekzema, E., Ramos-Quiroga, J.A., Richarte, V., Canals, C., Bosch, R.,
Rovira, M., Soliva, J.C., Bulbena, A., Tobena, A., Casas, M., Vilarroya, O., 2012.
Response inhibition and reward anticipation in medication-naive adults with attention-deficit/hyperactivity
disorder: a within-subject case-control neuroimaging
study. Hum. Brain Mapp. 33, 2350–2361.
Carmona, S., Martinez-Garcia, M., Paternina-Die, M., Barba-Muller, E., Wierenga, L.M.,
eman-Gomez, Y., Pretus, C., Marcos-Vidal, L., Beumala, L., Cortizo, R., Pozzobon, C.,
Picado, M., Lucco, F., Garcia-Garcia, D., Soliva, J.C., Tobena, A., Peper, J.S., Crone,
E.A., Ballesteros, A., Vilarroya, O., Desco, M., Hoekzema, E., 2019. Pregnancy and
adolescence entail similar neuroanatomical adaptations: a comparative analysis of
cerebral morphometric changes. Hum. Brain Mapp. 40, 2143–2152.
Carmona, S., Proal, E., Hoekzema, E.A., Gispert, J.D., Picado, M., Moreno, I., Soliva, J.C.,
Bielsa, A., Rovira, M., Hilferty, J., Bulbena, A., Casas, M., Tobena, A., Vilarroya, O.,
2009. Ventro-striatal reductions underpin symptoms of hyperactivity and impulsivity
in attention-deficit/hyperactivity disorder. Biol. Psychiatry 66, 972–977.
Champagne, F.A., Chretien, P., Stevenson, C.W., Zhang, T.Y., Gratton, A., Meaney, M.J.,
2004. Variations in nucleus accumbens dopamine associated with individual differences
in maternal behavior in the rat. J. Neurosci. 24, 4113–4123.
Dewey, J., Hana, G., Russell, T., Price, J., McCaffrey, D., Harezlak, J., Sem, E., Anyanwu,
J.C., Guttmann, C.R., Navia, B., Cohen, R., Tate, D.F., 2010. Reliability and validity of
MRI-based automated volumetry software relative to auto-assisted manual measurement
of subcortical structures in HIV-infected patients from a multisite study.
Neuroimage 51, 1334–1344.
Drew, K.L., Lyon, R.A., Titeler, M., Glick, S.D., 1986. Asymmetry in D-2 binding in female
rat striata. Brain Res. 363, 192–195.
Farre-Sender, B., Torres, A., Gelabert, E., Andres, S., Roca, A., Lasheras, G., Valdes, M.,
Garcia-Esteve, L., 2018. Mother-infant bonding in the postpartum period: assessment
of the impact of pre-delivery factors in a clinical sample. Arch. Womens Ment. Health
21, 287–297.
Febo, M., Numan, M., Ferris, C.F., 2005. Functional magnetic resonance imaging shows
oxytocin activates brain regions associated with mother-pup bonding during suckling.
J. Neurosci. 25, 11637–11644.
Ferris, C.F., Kulkarni, P., Sullivan Jr., J.M., Harder, J.A., Messenger, T.L., Febo, M., 2005.
Pup suckling is more rewarding than cocaine: evidence from functional magnetic
resonance imaging and three-dimensional computational analysis. J. Neurosci. 25,
149–156.
Fischl, B., Salat, D.H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der, K.A.,
Killiany, R., Kennedy, D., Klaveness, S., Montillo, A., Makris, N., Rosen, B., Dale,
A.M., 2002. Whole brain segmentation: automated labeling of neuroanatomical
structures in the human brain. Neuron 33, 341–355.
Fleming, A.S., Cheung, U., Myhal, N., Kessler, Z., 1989. Effects of maternal hormones on’
timidity’ and attraction to pup-related odors in female rats. Physiol. Behav. 46,
449–453.
Fleming, A.S., Korsmit, M., Deller, M., 1994. Rats pups are potent reinforcers to the
maternal animal: effects of experience, parity, hormones and dopamine function.
Psychobiology 22, 44–53.
Gunduz, H., Wu, H., Ashtari, M., Bogerts, B., Crandall, D., Robinson, D.G., Alvir, J.,
Lieberman, J., Kane, J., Bilder, R., 2002. Basal ganglia volumes in first-episode
schizophrenia and healthy comparison subjects. Biol. Psychiatry 51, 801–808.
Haber, S.N., Knutson, B., 2010. The reward circuit: linking primate anatomy and human
imaging. Neuropsychopharmacology 35, 4–26.
Hauser, H., Gandelman, R., 1985. Lever pressing for pups: evidence for hormonal influence
upon maternal behavior of mice. Horm. Behav. 19, 454–468.
Hoekzema, E., Barba-Muller, E., Pozzobon, C., Picado, M., Lucco, F., Garcia-Garcia, D.,
Soliva, J.C., Tobena, A., Desco, M., Crone, E.A., Ballesteros, A., Carmona, S.,
Vilarroya, O., 2017. Pregnancy leads to long-lasting changes in human brain structure.
Nat. Neurosci. 20, 287–296.
Hoekzema, E., Carmona, S., Ramos-Quiroga, J.A., Canals, C., Moreno, A., Richarte, F.V.,
Picado, M., Bosch, R., Duno, L., Soliva, J.C., Rovira, M., Bulbena, A., Tobena, A.,
Casas, M., Vilarroya, O., 2014. Stimulant drugs trigger transient volumetric changes
in the human ventral striatum. Brain Struct. Funct. 219, 23–34.
Ikemoto, S., 2007. Dopamine reward circuitry: two projection systems from the ventral
midbrain to the nucleus accumbens-olfactory tubercle complex. Brain Res. Rev. 56,
27–78.
Jones, S.L., Dufoix, R., Laplante, D.P., Elgbeili, G., Patel, R., Chakravarty, M.M., King, S.,
Pruessner, J.C., 2019. Larger amygdala volume mediates the association between
prenatal maternal stress and higher levels of externalizing behaviors: sex specific
effects in project ice storm. Front Hum. Neurosci. 13, 144.
Kim, P., Strathearn, L., Swain, J.E., 2015. The maternal brain and its plasticity in humans.
Horm. Behav.
Knutson, B., Cooper, J.C., 2005. Functional magnetic resonance imaging of reward prediction.
Curr. Opin. Neurol. 18, 411–417.
Kohl, J., Dulac, C., 2018. Neural control of parental behaviors. Curr. Opin. Neurobiol. 49,
116–122.
Lauer, M., Senitz, D., Beckmann, H., 2001. Increased volume of the nucleus accumbens in
schizophrenia. J. Neural Transm. (Vienna) 108, 645–660.
Lee, A., Clancy, S., Fleming, A.S., 2000. Mother rats bar-press for pups: effects of lesions of
the mpoa and limbic sites on maternal behavior and operant responding for pupreinforcement.
Behav. Brain Res. 108, 215–231.
Leuner, B., Glasper, E.R., Gould, E., 2010. Parenting and plasticity. Trends Neurosci. 33,
465–473.
Levine, A., Zagoory-Sharon, O., Feldman, R., Weller, A., 2007. Oxytocin during pregnancy
and early postpartum: individual patterns and maternal-fetal attachment. Peptides
28, 1162–1169.
Li, M., Fleming, A.S., 2003. The nucleus accumbens shell is critical for normal expression
of pup-retrieval in postpartum female rats. Behav. Brain Res. 145, 99–111.
Loh, W.Y., Ahmadzai, Z.M., Gabra Fam, L., Connelly, A., Spittle, A.J., Lee, K.J., Inder,
T.E., Cheong, J.L.Y., Doyle, L.W., Anderson, P.J., Thompson, D.K., 2014. Comparing
FreeSurfer with manual segmentation in the basal ganglia and thalamus of 7-year old
children. Proc. Intl. Soc. Mag. Reson. Med. 22.
Lonstein, J.S., Levy, F., Fleming, A.S., 2015. Common and divergent psychobiological
mechanisms underlying maternal behaviors in non-human and human mammals.
Horm. Behav. 73, 156–185.
Lorberbaum, J.P., Newman, J.D., Horwitz, A.R., Dubno, J.R., Lydiard, R.B., Hamner,
M.B., Bohning, D.E., George, M.S., 2002. A potential role for thalamocingulate circuitry
in human maternal behavior. Biol. Psychiatry 51, 431–445.
Lu, L.H., Dapretto, M., O’Hare, E.D., Kan, E., McCourt, S.T., Thompson, P.M., Toga, A.W.,
Bookheimer, S.Y., Sowell, E.R., 2009. Relationships between brain activation and
brain structure in normally developing children. Cereb. Cortex 19, 2595–2604.
Marques, A.H., O’Connor, T.G., Roth, C., Susser, E., Bjorke-Monsen, A.L., 2013. The influence
of maternal prenatal and early childhood nutrition and maternal prenatal
stress on offspring immune system development and neurodevelopmental disorders.
Front. Neurosci. 7, 120.
Martin-Soelch, C., Szczepanik, J., Nugent, A., Barhaghi, K., Rallis, D., Herscovitch, P.,
Carson, R.E., Drevets, W.C., 2011. Lateralization and gender differences in the dopaminergic
response to unpredictable reward in the human ventral striatum. Eur. J.
Neurosci. 33, 1706–1715.
Mattson, B.J., Williams, S., Rosenblatt, J.S., Morrell, J.I., 2001. Comparison of two positive
reinforcing stimuli: pups and cocaine throughout the postpartum period.
Behav. Neurosci. 115, 683–694.
Mills, K.L., Tamnes, C.K., 2014. Methods and considerations for longitudinal structural
brain imaging analysis across development. Dev. Cogn. Neurosci. 9, 172–190.
Molochnikov, I., Cohen, D., 2014. Hemispheric differences in the mesostriatal dopaminergic
system. Front Syst. Neurosci. 8, 110.
Nugent, A.C., Luckenbaugh, D.A., Wood, S.E., Bogers, W., Zarate Jr., C.A., Drevets, W.C.,
2013. Automated subcortical segmentation using FIRST: test-retest reliability, interscanner
reliability, and comparison to manual segmentation. Hum. Brain Mapp. 34,
2313–2329.
Numan, M., 2006. Hypothalamic neural circuits regulating maternal responsiveness toward
infants. Behav. Cogn. Neurosci. Rev. 5, 163–190.
Numan, M., Woodside, B., 2010. Maternity: neural mechanisms, motivational processes,
and physiological adaptations. Behav. Neurosci. 124, 715–741.
Nunez, S.C., Dapretto, M., Katzir, T., Starr, A., Bramen, J., Kan, E., Bookheimer, S.,
Sowell, E.R., 2011. fMRI of syntactic processing in typically developing children:
structural correlates in the inferior frontal gyrus. Dev. Cogn. Neurosci. 1, 313–323.
O’Connor, T.G., Bergman, K., Sarkar, P., Glover, V., 2013. Prenatal cortisol exposure
predicts infant cortisol response to acute stress. Dev. Psychobiol. 55, 145–155.
Olza-Fernandez, I., Marin Gabriel, M.A., Gil-Sanchez, A., Garcia-Segura, L.M., Arevalo,
M.A., 2014. Neuroendocrinology of childbirth and mother-child attachment: the basis
of an etiopathogenic model of perinatal neurobiological disorders. Front.
Neuroendocrinol. 35, 459–472.
Patenaude, B., Smith, S.M., Kennedy, D.N., Jenkinson, M., 2011. A Bayesian model of
shape and appearance for subcortical brain segmentation. Neuroimage 56, 907–922.
Peper, J.S., Hulshoff Pol, H.E., Crone, E.A., van Honk, J., 2011. Sex steroids and brain
structure in pubertal boys and girls: a mini-review of neuroimaging studies.
Neuroscience 191, 28–37.
Perez-Fernandez, J., Stephenson-Jones, M., Suryanarayana, S.M., Robertson, B., Grillner,
S., 2014. Evolutionarily conserved organization of the dopaminergic system in lamprey:
SNc/VTA afferent and efferent connectivity and D2 receptor expression. J.
Comp. Neurol. 522, 3775–3794.
Pryce, C.R., Dobeli, M., Martin, R.D., 1993. Effects of sex steroids on maternal motivation
in the common marmoset (Callithrix jacchus): development and application of an
operant system with maternal reinforcement. J. Comp. Psychol. 107, 99–115.
Puig, M.V., Rose, J., Schmidt, R., Freund, N., 2014. Dopamine modulation of learning and
memory in the prefrontal cortex: insights from studies in primates, rodents, and birds.
Front. Neural Circuits 8, 93.
Robbins, T.W., Everitt, B.J., 1996. Neurobehavioural mechanisms of reward and motivation.
Curr. Opin. Neurobiol. 6, 228–236.
Rutherford, J.M., Moody, A., Crawshaw, S., Rubin, P.C., 2003. Magnetic resonance
E. Hoekzema, et al. Psychoneuroendocrinology 112 (2020) 104507
8
spectroscopy in pre-eclampsia: evidence of cerebral ischaemia. BJOG 110, 416–423.
Ryczko, D., Cone, J.J., Alpert, M.H., Goetz, L., Auclair, F., Dube, C., Parent, M., Roitman,
M.F., Alford, S., Dubuc, R., 2016. A descending dopamine pathway conserved from
basal vertebrates to mammals. Proc. Natl. Acad. Sci. U. S. A. 113, E2440–E2449.
Sheehan, D.V., Lecrubier, Y., Sheehan, K.H., Amorim, P., Janavs, J., Weiller, E., Hergueta,
T., Baker, R., Dunbar, G.C., 1998. The Mini-International Neuropsychiatric Interview
(M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview
for DSM-IV and ICD-10. J. Clin. Psychiatry 59 (Suppl 20), 22–33.
Simon, E., Bogels, S., Stoel, R., De, S.S., 2009. Risk factors occurring during pregnancy
and birth in relation to brain functioning and child’s anxiety. J. Anxiety Disord. 23,
1024–1030.
Sisk, C.L., Zehr, J.L., 2005. Pubertal hormones organize the adolescent brain and behavior.
Front. Neuroendocrinol. 26, 163–174.
Strathearn, L., Li, J., Fonagy, P., Montague, P.R., 2008. What’s in a smile? Maternal brain
responses to infant facial cues. Pediatrics 122, 40–51.
Swain, J.E., 2011. The human parental brain: in vivo neuroimaging. Prog.
Neuropsychopharmacol. Biol. Psychiatry 35, 1242–1254.
Swain, J.E., Lorberbaum, J.P., Kose, S., Strathearn, L., 2007. Brain basis of early parentinfant
interactions: psychology, physiology, and in vivo functional neuroimaging
studies. J. Child Psychol. Psychiatry 48, 262–287.
Wilsoncroft, V.E., 1969. Babies by bar-press: maternal behavior in the rat. Behav. Res.
Methods. Instrum. 1, 229–230.
Zhang, S., Hu, S., Chao, H.H., Li, C.R., 2017. Hemispheric lateralization of resting-state
functional connectivity of the ventral striatum: an exploratory study. Brain Struct.
Funct. 222, 2573–2583.
E. Hoekzema, et al. Psychoneuroendocrinology 112 (2020) 104507
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