Christopher R. Madan

This study evaluates the reliability of structural covariance network analyses using MRI data, showing that small sample sizes and high-dimensional parcellations lead to unreliable graph-theoretic measures and inflated false discovery rates.

This study links altered structural brain complexity in post-acute anti-NMDA receptor encephalitis to memory dysfunction and psychiatric outcomes using fractal dimensionality analysis.

The paper assesses the numerical and spatial reliability of hippocampal subfields and amygdala nuclei segmentation in FreeSurfer 7 using repeated scans from 923 participants.

This study shows that brain shape in newborns develops rapidly and is a key indicator of maturity, outperforming brain size in predicting age and detecting prematurity.

The paper curates and provides analysis-ready diffusion MRI data for pediatric brain white-matter research, including automated quality control using a trained neural network.

This study shows cortical thickness is more linked to aging, while surface area is more linked to cognitive abilities, using brain imaging data from healthy adults.

This study investigates how mu oscillations change during motor imagery tasks and finds that suppression of mu oscillations correlates with successful imagery performance but not with individual imagery ability.

This study uses tDCS to investigate cerebellar involvement in optic flow perception, finding that anodal stimulation improves left-right motion discrimination.

This study examines how healthy cognitive aging affects resting-state fMRI signal measures, finding age-related changes in network amplitude and inter-network connectivity but some architectural invariance.

The paper develops a stimulus set of emotional and neutral images that controls for semantic relatedness and other confounding factors to improve memory research.

This study examines age-related changes in cortical gyrification using an accelerated longitudinal dataset, finding that sulcal morphology changes underlie these age-related decrements.

The paper examines structural and functional connectivity changes in a mouse model of vascular cognitive impairment, finding altered network connectivity and behavioural deficits.

The paper develops a computational method to estimate sulcal width and depth using cortical surface reconstructions, demonstrating its application across aging samples and test-retest reliability.

The paper replicates prior findings on age-related differences in head motion and cortical morphology estimates using a large dataset, and tests the influence of head motion on fractal dimensionality and gyrification.

This study predicts age from cortical morphology metrics across the lifespan using machine learning, achieving a median error of 6-7 years.

The paper examines age-related differences in subcortical structures by analyzing shape characteristics and their relationship to fractal dimensionality, finding that shape measures explain most of the variance in fractal dimensionality and are sensitive aging biomarkers.

Mindcontrol is a web application that enables collaborative quality control of neuroimaging data through visualization, annotation, and integration with datasets.