The participant underwent a blood draw (n  = 19; Fig. 1c ) before 
MRI scanning. Sex steroid concentrations were determined via 
ultra-sensitive liquid chromatography–mass spectrometry at the 
Brigham and Women’s Hospital Research Assay Core (BRAC). Assay 
sensitivities, dynamic range and intra-assay coefficients of variation 
were as follows: estradiol—1.0 pg ml−1, 1–500 pg ml−1, <5% relative s.d. 
(RSD); progesterone—0.05 ng ml−1, 0.05–10 ng ml−1, 9.33% RSD. Sero-
logical samples were not acquired in five sessions due to scheduling 
conflicts with UC Irvine’s Center for Clinical Research.
MRI acquisition. MRI scanning sessions at the University of Califor -
nia, Santa Barbara and Irvine were conducted on 3T Prisma scanners 
equipped with 64-channel phased-array head/neck coil (of which 50 
coils are used for axial brain imaging). High-resolution anatomical scans 
were acquired using a T1-weighted (T1w) magnetization prepared rapid 
gradient echo (MPRAGE) sequence (repetition time (TR) = 2,500 ms, 
time to echo (TE) = 2.31 ms, inversion time (TI) = 934 ms, flip angle = 7°, 
0.8 mm thickness) followed by a gradient echo field map (TR = 758 ms, 
TE1 = 4.92 ms, TE2 = 7.38 ms, flip angle = 60°). A T2-weighted (T2w) 
turbo spin echo scan was also acquired with an oblique coronal orienta-
tion positioned orthogonally to the main axis of the hippocampus (TR/
TE = 9,860/50 ms, flip angle = 122°, 0.4 × 0.4 mm2 in-plane resolution, 
2-mm slice thickness, 38 interleaved slices with no gap, total acquisi-
tion time = 5 min and 42 sec). The Diffusion Spectrum Imaging (DSI) 
protocol sampled the entire brain with the following parameters: 
single phase, TR = 4,300 ms, echo time = 100.2 ms, 139 directions, 
b-max = 4,990, FoV = 259 × 259 mm, 78 slices, 1.7986 × 1.7986 × 1.8 mm 
voxel resolution. These images were linearly registered to the 
whole-brain T1w MPRAGE image. A custom foam headcase was used 
to provide extra padding around the head and neck, as well as to mini-
mize head motion. Additionally, a custom-built sound-absorbing foam 
girdle was placed around the participant’s waist to attenuate sound 
near the fetus during second-trimester and third-trimester scanning.
Image processing. Cortical volume and thickness. CT and GMV were 
measured with Advanced Normalization T ools54 version 2.1.0 (ANTs). 
We first built a subject-specific template (SST) (antsMultivariateT em-
plateConstruction2) and tissue priors (antsCookT emplatePriors) 
based on our participant’s two preconception whole-brain T1-weighted 
scans to examine neuroanatomical changes relative to the participant’s 
prepregnancy baseline. We used labels from the OASIS population 
template, provided by ANTs, as priors for this step. For each session, 
the structural image was processed and registered to the SST using the 
ANTs CT pipeline (antsCorticalThickness). This begins with an N4 bias 
field correction for field inhomogeneity, then brain extraction using a 
hybrid registration/segmentation method55. Tissue segmentation was 
performed using Atropos54 to create tissue masks of CSF , gray matter, 
white matter and deep gray matter. Atropos allows prior knowledge 
to guide the segmentation algorithm, and we used labels from our SST 
as priors to minimize warping and remain in native participant space. 
CT measurements were then estimated using the DiReCT algorithm56, 
which estimates the gray–white matter interface and the gray mat -
ter–CSF interface and computes a diffeomorphic mapping between 
the two interactions, from which thickness is derived. Each gray matter 
tissue mask was normalized to the template and multiplied to a Jaco-
bian image that was computed via affine and nonlinear transforms. 
Using MATLAB (version 2022a), summary, regional-level estimates 
of CT, GMV and CSF for each scan were obtained by taking the first 
eigenvariate (akin to a ‘weighted mean’57) across all voxels within each