Jiook Cha

Slower cardiac-coupled cortical dynamics link depressive symptoms to inflexible affective updating

The paper links depressive symptoms to delayed affective updating by showing slower cardiac-coupled cortical dynamics mediate this delay during contextual shifts.

A more comprehensive and reliable analysis of individual differences with generalized random forest for high-dimensional data: validation and guidelines

This paper improves generalized random forest for analyzing individual treatment effects by stabilizing predictions and identifying key moderators in high-dimensional data.

Polygenic architecture of brain structure and function, behaviors, and psychopathologies in children

This study identifies genetic associations between brain structure/function, cognitive traits, and psychopathologies in children using polygenic scores and multivariate analysis.

Sex-Specific Effects of Anxiety on Cognition and Activity-Dependent Neural Networks: Insights from (Female) Mice and (Wo)Men

The paper examines sex-specific effects of anxiety on cognition and neural networks in mice and humans, finding earlier cognitive decline in female AD mice and faster dementia progression in anxious female humans.

Predicting task-related brain activity from resting-state brain dynamics with fMRI Transformer

This paper introduces SwiFUN, a deep-learning framework for predicting task-related brain activity from resting-state fMRI, achieving higher accuracy than existing methods in adults and children.

Awe is characterized as an ambivalent experience in the human behavior and cortex: integrated virtual reality-electroencephalogram study

This study uses virtual reality and EEG to show that awe involves ambivalent feelings, which are distinct from positive and negative emotions and predict awe ratings.

Overestimated Polygenic Prediction due to Overlapping Subjects in Genetic Datasets

This paper shows that polygenic risk scores (PRS) overestimate predictive accuracy when datasets have overlapping subjects, using Alzheimer's disease and other traits as examples.

Machine Learning Prediction of Incidence of Alzheimers Disease Using Large-Scale Administrative Health Data

This study uses machine learning to predict Alzheimer's disease incidence from administrative health data, achieving moderate accuracy in 1-4 year predictions.

Altered White Matter Microstructural Organization in Post-Traumatic Stress Disorder across 3,049 Adults: Results from the PGC-ENIGMA PTSD Consortium

This study identifies reduced fractional anisotropy in the tapetum region of the corpus callosum in PTSD patients using a large multi-cohort analysis of diffusion MRI data.

Diagnosis and Prognosis of Alzheimer’s Disease Using Brain Morphometry and White Matter Connectomes

This paper uses multimodal MRI and machine learning to classify Alzheimer's disease and mild cognitive impairment, showing high accuracy in diagnosis and progression prediction.

Diagnosis and Prognosis Using Machine Learning Trained on Brain Morphometry and White Matter Connectomes

This paper uses machine learning on brain morphometry and connectomes from MRI to predict Alzheimer's disease risk and progression, achieving high accuracy in both single-site and multi-site datasets.