Scheidter, K. | Search bioRxiv

bioRxiv2025

Patterns of brain-wide associations reflect socioeconomics

Previous brain-wide association studies (BWAS) cross-sectionally linked a specific behavioral trait, most commonly IQ or psychopathology, to variation in brain function or structure. Here, we expanded the focus of BWAS from effect sizes to interpretability and generalizability by mapping 649 variables to brain function and structure. We compared the resultant BWAS maps to other types of brain data to annotate the BWAS patterns. Socioeconomic status (SES) -- not IQ or psychopathology -- showed the strongest associations with both resting-state functional connectivity (RSFC) and cortical thickness in the Adolescent Brain Cognitive Development (ABCD) Study. A principal exposome brain pattern, anchored to sensory and motor cortex, captured 34% of the variance across all BWAS maps. This exposome pattern was strongly correlated with the SES and IQ BWAS maps and non-BWAS maps of sleep (EEG), norepinephrine (PET), and stimulants (drug trial), but not cognitive activation maps (task fMRI). Adjusting for SES, reduced brain-IQ associations by 40%. Brain with IQ associations did not generalize, as they could no longer be detected in subsamples drawn from only higher SES backgrounds, while brain with SES associations remained strong in higher-IQ-only subsamples. These findings reveal SES as the principal axis of population-level brain variation, possibly stemming from the sleep deprivation and heightened stress associated with lower SES, since socioeconomics can only indirectly affect the brain.

neuroscience↗

bioRxiv2021

Using synthetic MR images for field map-less distortion correction

Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion combined with underlying differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) structural images makes the alignment of functional and anatomical images a challenge. Typically, separately acquired field map data are used to correct fMRI distortions and a flexible cost function insensitive to cross-modal differences in image contrast and intensity is used for aligning fMRI and anatomical images. The quality of alignment achieved with this approach can vary greatly and depends on the quality of field map data. In addition, many publicly available datasets lack field map data entirely. To address this issue, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require separately acquired field map data. Synth combines information from T1w and T2w anatomical images to construct an idealized undistorted synthetic image that has similar contrast properties to fMRI data. The undistorted synthetic image then serves as an effective reference for individual-specific nonlinear unwarping to correct fMRI distortions. We demonstrate, in both pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club) data that Synth performs comparably well to other leading distortion correction approaches that utilize field map data, and often outperforms them. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.

neuroscience↗