Simon Vandekar

Contributions of Site Heterogeneity in Multi-site Brain-Phenotype Predictions

This paper evaluates how site heterogeneity affects brain-phenotype predictions in multi-site data, finding that larger sample sizes improve accuracy more than multi-site composition.

Facilitating Valid Statistical Inference in Biomedical Image Synthesis

This paper evaluates the statistical validity of synthetic biomedical images and introduces PAMS to improve biological inference.

Charting Cervical Spinal Cord Morphometry Across the Lifespan

The paper generates lifespan normative charts for cervical spinal cord morphometry using MRI data, revealing non-linear changes and sex differences across ages 0-100.

Imputation-Based Harmonization Mitigates Site Effects Without Data Leakage in Machine Learning Studies

The paper introduces MIRTH, an imputation-based harmonization method that mitigates site effects in neuroimaging data without data leakage, achieving high predictive accuracy in machine learning studies.

A Test for Confounding in Coupling of Multimodal Neuroimaging Data

The paper introduces a statistical test to detect confounding effects in multimodal neuroimaging data by assessing covariate influences on intermodal correspondence.

Lifespan Trajectories of Asymmetry in White Matter Tracts

This study characterizes white matter asymmetry across the lifespan using a large dataset, revealing dynamic changes in asymmetry patterns with age.

White matter microstructure and macrostructure brain charts across the human lifespan

The paper develops normative reference charts for white matter microstructure and macrostructure across the lifespan using diffusion MRI data from 50 studies.

BASSL-MI: Batch-Agnostic Self-Supervised Learning Uncovers Clinically Relevant Tumor Niches in Multiplexed Imaging

BASSL-MI uses self-supervised learning to identify clinically relevant tumor niches in multiplexed imaging without requiring cell segmentation.

Analytic Bounds on GAMLSS Model Variability of Normative White Matter Brain Charts

The paper evaluates the variability of GAMLSS-based brain charts using analytic and empirical methods, finding low coefficient of variation across most white matter features.

Multi-modal and multi-region distance model for neuroimaging: Application to ABCD study

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

Calibration of MRI-based reference intervals to new samples

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.

Improved Estimation of Correlation Accuracy for Machine Learning Brain-Phenotype Associations

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.

Comparing Brain-Behavior Relationships Across Dimensional, Tail-Sampled, and Propensity-Matched Models

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.

Semiparametric Confidence Sets for Arbitrary Effect Sizes in Longitudinal Neuroimaging

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.

Mapping individual differences in intermodal coupling in neurodevelopment

The paper introduces CEIDR, a method to test individual differences in intermodal brain coupling, and demonstrates its application in neurodevelopmental studies.

Study design features increase replicability in cross-sectional and longitudinal brain-wide association studies

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.

Consensus tissue domain detection in spatial -omics data using MILWRM

The paper introduces MILWRM, a tool for detecting tissue domains in spatial-omics data, and demonstrates its application in human colonic polyps and mouse brain slices.

Network Enrichment Significance Testing in Brain-Phenotype Association Studies

The paper introduces NEST, a framework for testing brain-phenotype associations within functional networks, applied to neurodevelopmental imaging data.

GammaGateR: semi-automated marker gating for single-cell multiplexed imaging

GammaGateR provides a semi-automated marker gating tool for multiplexed imaging data, improving consistency and reducing manual effort while revealing biological signals.

Evaluation of resampling-based inference for topological features of neuroimages

The paper evaluates resampling methods for neuroimage topological features, finding that wild bootstrap and permutation perform well in larger samples, while GRF-based methods have inflated error rates.

Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors

This study maps tumor evolution and microenvironment dynamics in colorectal cancer using spatial multi-omic data, identifying key genes associated with immune exclusion and prognosis.

Transcriptional Cartography Integrates Multiscale Biology of the Human Cortex

This paper integrates multiscale cortical biology by generating spatially dense gene expression maps from postmortem data, revealing transcriptional zones linked to microstructure and neuroimaging features.

Spatially-enhanced clusterwise inference for testing and localizing intermodal correspondence

The paper introduces CLEAN-R, a method to test and localize intermodal correspondence in neuroimaging data, demonstrating high statistical power and nominal type I error levels.

Voxel-wise Intermodal Coupling Analysis of Two or More Modalities using Local Covariance Decomposition

This paper introduces a method to analyze intermodal coupling between multiple brain imaging modalities and applies it to study neurodevelopmental patterns in adolescents.

Developmental coupling of cerebral blood flow and fMRI fluctuations in youth

This study examines how cerebral blood flow and fMRI fluctuations are coupled in youth, finding age-related decreases, sex differences, and links to executive function.

Quantifying and correcting slide-to-slide variation in multiplexed immunofluorescence images

This paper quantifies slide-to-slide variation in multiplexed immunofluorescence data and introduces normalization methods to correct it, showing that dividing by slide mean and functional data registration perform best.

A simple permutation-based test of intermodal correspondence

The paper introduces a permutation-based test to assess intermodal correspondence in neuroimaging data, showing it effectively detects known relationships and is conservative when none are expected.

Linked dimensions of psychopathology and connectivity in functional brain networks

The paper identifies brain-based dimensions of psychopathology using sCCA in youths, finding four dimensions linked to functional dysconnectivity that replicate in an independent dataset.

The correspondence problem: which brain maps are significantly similar?

This paper introduces a spatial permutation framework to test the significance of overlap between brain maps and demonstrates its application to task-based activity, resting-state networks, and anatomical landmarks.

Normative Brain Size Variation and the Remodeling of Brain Shape in Humans

The paper finds that larger-brained humans show preferential expansion of fronto-parietal cortical networks and related subcortical regions, at the expense of primary sensory/motor systems.