Colin S. Hawco

This study examines BOLD signal variability in autism and schizophrenia, finding reduced variability in these groups compared to controls, linked to poorer cognitive and functional outcomes.

The paper uses fALFF to compare brain activity patterns in ASD, SSD, and TDC groups, finding shared neurobiological features and variability differences.

BOONStim uses Bayesian optimization to improve TMS targeting by integrating fMRI and TMS simulation tools, showing faster convergence and accuracy compared to grid optimization.

The paper examines individual variability in functional connectivity during rest and an emotional-processing task in schizophrenia spectrum disorders and controls, identifying predictors like diagnosis and social cognition.

The paper introduces CLEAN-V, a method for testing variance components in neuroimaging data, showing improved power for detecting test-retest reliability and heritability.

This study compares volume-based, surface-based, and personalized surface-based approaches to identify dysconnectivity patterns in schizophrenia spectrum disorders using resting-state fMRI.

The paper links higher general intelligence to stable, efficient, and typical dynamic functional brain connectivity patterns using resting-state fMRI data.

The paper examines associations between externalizing/internalizing behaviors and cortico-amygdalar connectivity in children with NDDs and TDC, finding no significant linear relationships.

The paper analyzes brain activity variability across cognitive tasks using hierarchical clustering and dimensionality reduction, finding that individual differences are best represented multidimensionally.

The paper develops a transcriptome-based polygenic risk score (T-PRS) linking depression-related gene expression changes to neural face processing and anhedonia in a non-clinical sample.

The paper integrates brain imaging and behavioral data to identify transdiagnostic subgroups in children with ASD, ADHD, or OCD, finding stable groups based on cortical thickness and inattention symptoms.

The paper shows that different analysis workflows by 70 teams on the same fMRI dataset led to varied results, but meta-analysis found consensus in activated regions.