189 citations · 888 across the 107 of their papers we have counts for
11 papers · 1 filter
Causality as a Minimum Energy Principle
Moo K. Chung, D. Vijay Anand, Anass B El-Yaagoubi +3
Classical causal models, such as Granger causality and structural equation modeling, are largely restricted to acyclic interactions and struggle to represent cyclic and higher-orde…
From Density to Void: Why Brain Networks Fail to Reveal Complex Higher-Order Structures
Moo K. Chung, Anass B. El-Yaagoubi, Anqi Qiu +1
In brain network analysis using resting-state fMRI, there is growing interest in modeling higher-order interactions beyond simple pairwise connectivity via persistent homology. Des…
Topological Analysis of Seizure-Induced Changes in Brain Hierarchy Through Effective Connectivity
Anass B. El-Yaagoubi, Moo K. Chung, Hernando Ombao
Traditional Topological Data Analysis (TDA) methods, such as Persistent Homology (PH), rely on distance measures (e.g., cross-correlation, partial correlation, coherence, and parti…
Spectral Topological Data Analysis of Brain Signals
Anass El-Yaagoubi, Shuhao Jiao, Moo K. Chung +1
Topological analyses of brain functional connectivity usually reduce each pair of channels to a single scalar dependence, typically the Pearson correlation, and so cannot resolve t…
Hodge-Decomposition of Brain Networks
D Vijay Anand, D. Vijay Anand, Anass B El-Yaagoubi +2
We analyze brain networks by decomposing them into three orthogonal components: gradient, curl, and harmonic flows, through the Hodge decomposition, a technique advantageous for ca…
Dynamic Topological Data Analysis of Functional Human Brain Networks
Moo K. Chung, Soumya Das, Hernando Ombao
Developing reliable methods to discriminate different transient brain states that change over time is a key neuroscientific challenge in brain imaging studies. Topological data ana…
Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification
Fuad Noman, Chee-Ming Ting, Hakmook Kang +4
Brain functional connectivity (FC) reveals biomarkers for identification of various neuropsychiatric disorders. Recent application of deep neural networks (DNNs) to connectome-base…
Separating Stimulus-Induced and Background Components of Dynamic Functional Connectivity in Naturalistic fMRI
Chee-Ming Ting, Jeremy I. Skipper, Steven L. Small +1
We consider the challenges in extracting stimulus-related neural dynamics from other intrinsic processes and noise in naturalistic functional magnetic resonance imaging (fMRI). Mos…
Conex-Connect: Learning Patterns in Extremal Brain Connectivity From Multi-Channel EEG Data
Matheus B. Guerrero, Raphaël Huser, Hernando Ombao
Epilepsy is a chronic neurological disorder affecting more than 50 million people globally. An epileptic seizure acts like a temporary shock to the neuronal system, disrupting norm…
Structural Brain Asymmetries in Youths with Combined and Inattentive Presentations of Attention Deficit Hyperactivity Disorder
Cintya Nirvana Dutta, Pamela K. Douglas, Hernando Ombao
Alterations in structural brain laterality are reported in attention-deficit/hyperactivity disorder (ADHD). However, few studies examined differences within presentations of ADHD.…
Statistical Model for Dynamically-Changing Correlation Matrices with Application to Brain Connectivity
Shih-Gu Huang, S. Balqis Samdin, Chee-Ming Ting +2
Background: Recent studies have indicated that functional connectivity is dynamic even during rest. A common approach to modeling the dynamic functional connectivity in whole-brain…