Jakob Seidlitz

The paper compares three plasma proteomic metrics across organ systems to assess their associations with brain structure and neurodegenerative disease, finding distinct relationships and modest predictive value.

CranioTrace automates head circumference and cranial shape measurement from neuroimaging, enabling population growth modeling and identifying disease-related growth trajectory shifts.

The paper models age-varying sex differences in brain structure using MRI data from 100,000 individuals, showing consistent sex biases that increase with age and are influenced by neuropsychiatric disorders.

The paper identifies two neuroanatomical subtypes of callous-unemotional traits using machine learning in a community sample of youth, showing distinct clinical and environmental profiles.

The paper investigates genetic effects on cortical similarity networks using MRI data and finds two genetically determined gradients linked to brain evolution and neuropsychiatric risks.

ComBat-Predict improves the generalizability of neuroimaging models to new sites by harmonizing site effects and reducing bias in cortical thickness predictions.

The paper examines how environmental factors influence brain structure, cognition, and mental health in adolescents using the ABCD dataset, finding that advantageous environments correlate with better developmental outcomes.

This study uses functional connectome harmonics to analyze neonatal brain gradients and finds that power and energy metrics differ between term and preterm neonates, predicting postmenstrual age.

The paper applies Functional Connectome Harmonics and Leading Eigenvector Dynamics Analysis to resting-state fMRI data from children to characterize preadolescent brain network organization.

The paper introduces a UGEE framework for analyzing multimodal neuroimaging data, showing it accurately estimates effects and is 100x faster than permutation methods.

This paper introduces ReForm, a method to calibrate MRI-based reference intervals for new samples without sharing reference data, showing comparable or better false positive rate control than alternative methods.

The paper introduces conditional-longitudinal models to analyze brain growth trajectories and finds associations between birth weight, psychopathology, and brain volume changes in adolescents.

The paper develops a new estimator to more accurately assess machine learning model performance in predicting brain-phenotype associations and shows it reduces bias in estimating predictive accuracy.

skiftiTools enables statistical analysis and visualization of TBSS-derived diffusion MRI data using R, supporting advanced modeling and data manipulation.

The paper shows that brain abnormalities after preterm birth are spatially heterogeneous but temporally consistent and plastic in response to social environments.

This study identifies shared genetic loci between psychiatric disorders and cortical brain structure using genome-wide association data from over 700,000 individuals.

This paper presents a normative framework for brain asymmetry across the lifespan using a large neuroimaging dataset, revealing distinct spatial patterns and providing tools for clinical and research applications.

ComBatLS improves multi-site image harmonization by preserving biological variance in features, outperforming existing methods in sex-imbalanced site scenarios and reducing sex biases.

The paper compares brain-behavior associations across different sampling models using ABCD Study data, finding increased effect sizes with tail-sampled groups but mixed results with propensity-matched models.

The paper identifies robust sex differences in personalized functional brain network topography in youth, linked to X-linked genes and brain regions involved in psychiatric disorders.

This paper develops a method for constructing confidence sets for arbitrary effect sizes in longitudinal neuroimaging data, enabling more accurate inference of brain changes over time.

This study shows that optimizing study design, such as increasing age variability and adding longitudinal measurements, improves replicability and effect sizes in brain-wide association studies.

The paper presents a 3D digital atlas of the human fetal brain at 21 weeks gestation, revealing molecular signatures of cortical expansion linked to neurogenesis timing and evolutionary boundaries.

This study investigates the cerebellum's role in cognitive aging using large datasets, finding that cerebellar volume is associated with better cognitive outcomes and protection against decline.

This study creates normative brain growth charts for rhesus macaques across their lifespan using MRI data, revealing developmental milestones and cross-species comparisons with humans.

The paper examines how morphometric similarity in brain regions changes during adolescence, finding distinct developmental patterns in paralimbic versus neocortical areas.

The paper shows thalamocortical connections develop along a sensorimotor-association gradient in youth, linking structural connectivity to cortical plasticity and environmental sensitivity.

The paper identifies three conserved spatiomolecular gradients in the adult human brain that align with developmental axes and predict functional territories.

This study identifies copy number variants (CNVs) associated with child psychopathology and cognitive function using data from the ABCD study.