text: **Study design**
  The participant underwent 26 MRI scanning sessions from 3 weeks 
  before conception through 2 years postpartum (162 weeks), during 
  which high-resolution anatomical and diffusion spectrum imaging 
  scans of the brain were acquired. Scans were distributed throughout 
  this period, including prepregnancy (four scans), first trimester (four 
  scans), second trimester (six scans), third trimester (five scans) and 
  postpartum (seven scans; Fig. 1c). The first 6 sessions took place at 
  the UCSB Brain Imaging Center (BIC), the final 20 sessions took place 
  at the UCI Facility for Imaging and Brain Research (FIBRE). The major- 
  ity of scans took place between 9 AM and 2 PM, limiting significant 
  AM–PM fluctuations49. The MRI protocol, scanner (Siemens 3T Prisma) 
  and software (version MR E11) were identical across sites. Each scan- 
  ner was checked weekly for the duration of the study and passed all 
  QC reports indicating no significant alterations in the geometry. To 
  ensure the robustness of the findings, after the final study session, the 
  participant completed back-to-back validation scans at UCI and UCSB 
  within a 12-h window to assess reliability between scanners. Intraclass 
  correlation coefficients (two-way, random effects, absolute agreement, 
  single rater) reveal ‘excellent’ test–retest reliability between scanners, 
  including ROI-level GMV (ICC = 0.97, 95% CI: 0.80–0.99), ROI-level 
  CT (ICC = 0.96, 95% CI: 0.90–0.98), MTL subfield volume (ICC = 0.99, 
  95% CI: 0.97–0.99) and ROI-level QA (ICC = 0.94, 95% CI: 0.91–0.97). 
  Furthermore, when examining the relationship between gestation 
  week and GMV among UCI-only gestational sessions, findings were 
  consistent (Supplementary Fig. 12), indicating that site differences 
  are highly unlikely to have contributed meaningfully to the observed 
  effects. Although not applicable here, we note that having a control 
  participant scanned over a similar duration within the same scanner is 
  critical for estimating how much variation in the brain can be attributed 
  to within-scanner variability. 