Ting Xu

The paper uses neuroimaging data to dissect the neural differences between unfairness and moral emotions like anger and disgust, identifying distinct brain networks involved in each.

The paper develops a brain affective arousal signature (BAAS) using fMRI and predictive modeling, showing its generalizability across valence domains and distinction from autonomic arousal.

This study identifies an arcuate fasciculus homolog in marmosets, showing convergent evolution with humans in connectivity patterns and vocalization-related brain activation.

The paper models reward and emotional prediction errors in social transgressions using fMRI and finds distinct neural mechanisms for each, with reward PE having a stronger impact on punishment decisions.

This paper introduces causal methods to detect batch effects in multi-site data, showing they provide more accurate or 'no answer' results compared to non-causal methods.

The paper identifies dissociable neural connectome patterns for reward and punishment sensitivity using multimodal fMRI and transcriptomic data, linking them to specific gene sets and neurotransmitter systems.

This study identifies cortical gradient perturbations in ADHD linked to neurotransmitter, cell type, and chromosome-specific transcriptomic signatures using neuroimaging and molecular data.

This study compares TMS-targeted functional networks in human and non-human primate prefrontal cortex using electric field modeling and fMRI, identifying species-specific network differences.

This study uses experience sampling to examine covert goal-relevant states during task performance, finding that fronto-parietal network activity is linked to better task performance.

The paper introduces a longitudinal dataset of school-age children and adolescents in China, detailing its design, sampling, and neuroimaging measurements.

The paper examines time-varying and stationary brain connectivity during movie watching across childhood to early adulthood, finding age and sex effects are stronger in time-varying connectivity, while stationary connectivity predicts intelligence.

The paper identifies 35 prefrontal areas in macaques, reveals regional receptor differences, and shows functional connectivity patterns across clusters of frontal lobe areas.

The paper develops a neurofunctional signature of disgust using fMRI and machine learning, showing it generalizes across core disgust, gustatory distaste, and socio-moral contexts.

This study investigates the heritability of human brain connectomes using a novel method, finding that heritability is insignificant after accounting for network variability.

This study characterizes the brain renin angiotensin II system's architecture and function using imaging transcriptomics and fMRI, showing AT1R's role in cognition and behavior through specific circuits and interactions with neurotransmitter systems.

This study uses movie-fMRI to show that cortical gradients during naturalistic processing are hierarchical and modality-specific, with distinct perception-to-cognition hierarchies.

This study shows that losartan improves reward learning by enhancing ventral striatal prediction errors and frontostriatal communication in healthy humans.

This study shows that Losartan, an angiotensin II type 1 receptor antagonist, alters social reward and punishment processing by modulating midbrain-striato-frontal circuits in humans.

This study uses a precision pharmacological fMRI approach to show that losartan reduces neural reactivity to fear-inducing stimuli by targeting AT1R, without affecting threat or novelty responses.

The paper identifies spatial variation in neighborhood correlations during volume-to-surface mapping of fMRI data and proposes a mitigation approach.

The paper examines dynamic and stationary brain connectivity during movie watching using fMRI, finding that dynamic connectivity varies with movie content while stationary connectivity remains consistent across clips.

This study shows that losartan reduces memory advantage for negative emotional material by decreasing hippocampus activity and its coupling with the amygdala.

This study characterizes cortical thickness development in Japanese macaques using latent growth models and identifies how maternal diet and inflammation influence regional cortical maturation patterns.

This paper introduces a new statistic called discriminability to improve replicability by distinguishing accidental from systematic deviations in data, showing its effectiveness in both simulated and real datasets.

This paper evaluates test-retest reliability of multilayer network measures in neuroimaging, identifying methodological factors affecting reliability and task-specific requirements.

This paper introduces a function-based method to align cortical organization across species, revealing evolutionary changes in brain regions associated with human cognition.

This paper evaluates the reliability, reproducibility, and predictive validity of functional connectivity gradients in fMRI data across different analytical settings.

The paper develops a pipeline to generate age-specific MRI brain templates and growth charts for children and adolescents, revealing neurodevelopmental differences between Chinese and US populations.

BrainSpace provides a toolbox for analyzing macroscale gradients in neuroimaging and connectomics data, enabling gradient identification, alignment, visualization, and association studies.