3 citations · 6 across the 18 of their papers we have counts for
19 papers
MnemoDyn: Learning Resting State Dynamics from 40K FMRI sequences
Sourav Pal, Viet Luong, Hoseok Lee +5
We present a dynamical-systems based model for resting-state functional magnetic resonance imaging (rs-fMRI), trained on a dataset of roughly 40K rs-fMRI sequences covering a wide…
NeuroPilot: An Agent-Driven Smart Pipeline for Processing, Quality Control, and Managing Neuroimages
Yiyao Chen, Yucheng Li, Jungong Tong +7
Transforming raw neuroimage archives into analysis-ready derivatives relies on three brittle stages: data standardization, modality-specific preprocessing, and quality control (QC)…
CyberNeuro: A Privacy-Preserving Agentic Workbench for Cohort-Scale Neuroimage and Clinical Data Analysis
Ran Ren, Junhong Tong, Yunxi Kong +10
Despite tremendous success in neuroimaging methodology, making large-scale, high-dimensional datasets ready for AI/ML applications remains a critical operational bottleneck. Conven…
Neural operator-based digital twins for modeling amyloid- and tau propagation and treatment optimization in Alzheimer's disease
Xiaofeng Xu, Tingting Dan, Zifan Zhou +3
Accurately predicting the spatiotemporal evolution of amyloid- and tau proteins at the individual level is critical for improving the diagnosis and treatment of Alzheimer's dise…
Beyond Agreement: Scoring Panel-Surfaced Biomedical Entity Candidates for Curator Triage
Shuheng Cao, Ruiqi Chen, Renjie Cao +3
Biomedical NER is deceptively simple for modern LLMs: plausible biomedical mentions are easy to surface, but corpus-convention correctness depends on annotation conventions, span b…
Marrying Generative Model of Healthcare Events with Digital Twin of Social Determinants of Health for Disease Reasoning
Ziquan Wei, Tingting Dan, Guorong Wu
Despite the central role of sensor-derived measurements such as imaging traits and plasma biomarkers in biomedical research and clinical practice, existing generative models for di…
From Cortical Synchronous Rhythm to Brain Inspired Learning Mechanism: An Oscillatory Spiking Neural Network with Time-Delayed Coordination
Tingting Dan, Guorong Wu
Human cognition emerges from coordinated spiking dynamics in distributed neural circuits, where information is encoded via both firing rates and precise spike timing determined by…
GeoDynamics: A Geometric State-Space Neural Network for Understanding Brain Dynamics on Riemannian Manifolds
Tingting Dan, Jiaqi Ding, Guorong Wu
State-space models (SSMs) have become a cornerstone for unraveling brain dynamics, revealing how latent neural states evolve over time and give rise to observed signals. By combini…
Explore Brain-Inspired Machine Intelligence for Connecting Dots on Graphs Through Holographic Blueprint of Oscillatory Synchronization
Tingting Dan, Jiaqi Ding, Guorong Wu
Neural coupling in both neuroscience and artificial intelligence emerges as dynamic oscillatory patterns that encode abstract concepts. To this end, we hypothesize that a deeper un…
De-Individualizing fMRI Signals via Mahalanobis Whitening and Bures Geometry
Aaron Jacobson, Tingting Dan, Martin Styner +3
Functional connectivity has been widely investigated to understand brain disease in clinical studies and imaging-based neuroscience, and analyzing changes in functional connectivit…
Understanding Mechanistic Role of Structural and Functional Connectivity in Tau Propagation Through Multi-Layer Modeling
Tingting Dan, Xinwei Huang, Jiaqi Ding +2
Emerging neuroimaging evidence shows that pathological tau proteins build up along specific brain networks, suggesting that large-scale network architecture plays a key role in the…
Large Connectome Model: An fMRI Foundation Model of Brain Connectomes Empowered by Brain-Environment Interaction in Multitask Learning Landscape
Ziquan Wei, Tingting Dan, Guorong Wu
A reliable foundation model of functional neuroimages is critical to promote clinical applications where the performance of current AI models is significantly impeded by a limited…
Optimal Control For Anti-Abeta Treatment in Alzheimer's Disease using a Reaction-Diffusion Model
Sun Lee, Chiu-Yen Kao, Zhiyuan Li +3
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that severely impairs survival and quality of life. While anti-amyloid beta (Abeta) therapies can slow disease…
NeuroSymAD: A Neuro-Symbolic Framework for Interpretable Alzheimer's Disease Diagnosis
Yexiao He, Ziyao Wang, Yuning Zhang +4
Alzheimer's disease (AD) diagnosis is complex, requiring the integration of imaging and clinical data for accurate assessment. While deep learning has shown promise in brain MRI an…
NeuroPath: A Neural Pathway Transformer for Joining the Dots of Human Connectomes
Ziquan Wei, Tingting Dan, Jiaqi Ding +1
Although modern imaging technologies allow us to study connectivity between two distinct brain regions in-vivo, an in-depth understanding of how anatomical structure supports brain…
Machine Learning on Dynamic Functional Connectivity: Promise, Pitfalls, and Interpretations
Jiaqi Ding, Tingting Dan, Ziquan Wei +4
An unprecedented amount of existing functional Magnetic Resonance Imaging (fMRI) data provides a new opportunity to understand the relationship between functional fluctuation and h…
Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold
Tingting Dan, Ziquan Wei, Won Hwa Kim +1
The human brain is a complex inter-wired system that emerges spontaneous functional fluctuations. In spite of tremendous success in the experimental neuroscience field, a system-le…
Message Detouring: A Simple Yet Effective Cycle Representation for Expressive Graph Learning
Ziquan Wei, Tingting Dan, Guorong Wu
Graph learning is crucial in the fields of bioinformatics, social networks, and chemicals. Although high-order graphlets, such as cycles, are critical to achieving an informative g…
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals
Tingting Dan, Jiaqi Ding, Ziquan Wei +4
Graph neural networks (GNNs) are widely used in domains like social networks and biological systems. However, the locality assumption of GNNs, which limits information exchange to…