Zhen Yuan

This study characterizes the spatiotemporal response properties of fUS-CBV signals in mice during whisker stimulation, showing they retain structured information for reliable decoding.

This study examines how shared excluded experiences affect interpersonal neural synchronization in depressed adolescents compared to healthy controls, finding altered brain-behavior patterns and stronger neural synchronization in depressed adolescents.

The paper develops population-specific brain charts for Chinese individuals, revealing distinct neurodevelopmental patterns compared to Western populations and showing better performance in predicting brain phenotypes.

This study shows ultrasound directly activates sparse neurons in deafened mice, modulates visual circuits, and confirms direct mechanical effects independent of auditory input.

This paper introduces a sapphire-based optrode that combines high-intensity LED optogenetic stimulation with low-noise neural recording, demonstrating its effectiveness in vivo.

This study identifies reduced BOLD-CSF coupling as a biomarker for Primary Progressive Aphasia, linking glymphatic dysfunction to clinical and structural brain changes.

The paper examines scale-free dynamics in cerebrospinal fluid regions and finds higher Hurst exponents in Alzheimer's Disease patients compared to cognitively normal individuals, correlating with AD biomarkers.

This study links regional glymphatic dysfunction to SCA3 pathophysiology by showing impaired glymphatic markers and their correlation with disease severity.

This study identifies distinct brain module organizations in FTD subtypes using resting-state fMRI and machine learning, finding altered modular properties and classification accuracy of 85%.

This study uses behavioral modeling and multimodal neuroimaging to show that internet gaming disorder is associated with increased risk-taking behavior and altered brain activation patterns in response to feedback.

This study investigates how word structure affects brain activity in Chinese speakers using EEG and fNIRS, finding distinct patterns for morphological priming and word structure effects.

This study uses individual-specific functional connectivity and machine learning to detect and predict Alzheimer's disease symptoms in elderly people with and without APOE ε4 allele.

The paper investigates how the brain processes proximity and similarity grouping principles in visual perception using EEG and MVPA, finding dissociated neural stages for each principle.