Kosha Ruparel

This study investigates olfactory deficits and structural anomalies in the olfactory system among individuals with 22q11.2 deletion syndrome compared to psychosis spectrum and typically developing controls.

The paper identifies a founder variant in ADAP1 associated with increased risk of schizophrenia and bipolar disorder in a Colombian genetic isolate.

The paper introduces a longitudinal data resource combining multimodal imaging and cognitive phenotyping to study brain development and EF variation in adolescents.

This study examines the relationship between cannabis use, glutamate levels in the anterior cingulate cortex, and symptom severity across the psychosis spectrum using 7T proton magnetic resonance spectroscopy.

The paper introduces an open data resource combining neuroimaging and behavioral measures to study mood and sleep in adolescents and young adults.

This study evaluates the stability of polygenic scores across different genome-wide association studies, finding low individual-level consistency and highlighting challenges for precision medicine.

This study identifies altered functional brain dynamics in 22q11.2DS during facial affect processing using fMRI, showing preserved early visual and insular activation but diminished motor feedback and emotional memory signals.

The paper shows that reduced value signals in the ventromedial prefrontal cortex are linked to motivational and hedonic deficits across mood and psychotic disorders.

The study replicates and extends the Parieto-Frontal Integration Theory (PFIT) in youths, showing age-related strengthening of brain parameter-cognitive performance associations and suggesting an expanded network incorporating motivation and affect regions.

The paper identifies statistical issues in brain age gap analysis, showing that modifying the brain age gap can inflate model accuracy statistics and suggests developing new methods to quantify deviation from normal developmental trajectories.

The paper uses network control theory to show that structural brain networks mature during adolescence to reduce the energy cost of activating the frontoparietal system, supporting executive function development.

This study examines how structure-function coupling in brain networks develops during youth, finding it aligns with cortical hierarchies and supports cognitive improvements.

This study identifies two neurobiologically distinct subtypes of youth with internalizing symptoms using structural brain imaging and machine learning.

This study finds no significant differences in brain structure between adolescent and young adult cannabis users and non-users using high-resolution MRI scans.

The paper uses machine learning to analyze brain states from fMRI data and shows that white matter connectivity influences their dynamics and development.

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 paper examines the association between cortical thickness and impulsive choice in adolescents, finding reduced cortical thickness in specific brain regions linked to impulsive decision-making.

The paper develops an automated method to assess structural brain image quality using Euler number and validates its effectiveness in identifying low-quality images and its relationship with cortical thickness and age-related associations.

The paper constructs a multifactorial model of white matter connectivity during adolescence using Bayesian networks and diffusion imaging data, showing that architectural specifications become more influential with age.

This paper evaluates how in-scanner head motion affects structural connectivity estimates from diffusion tractography in a developmental cohort, showing motion biases connectivity strength in a consistency and length-dependent manner.

This paper shows that diffusion tensor imaging data are site-specific and demonstrates that ComBat effectively harmonizes them while preserving biological variability.