Lindsay D. Oliver

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 SAN, a method to harmonize cortical thickness data across scanners by normalizing spatial autocorrelation, improving data quality and reproducibility.

RELIEF removes inter-scanner biases in neuroimaging data by using multivariate factorization, improving data integration and statistical power.