5 papers
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…
Classification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network
Chun-Ren Phang, Chee-Ming Ting, Fuad Noman +1
We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introdu…
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…
Short-segment heart sound classification using an ensemble of deep convolutional neural networks
Fuad Noman, Chee-Ming Ting, Sh-Hussain Salleh +1
This paper proposes a framework based on deep convolutional neural networks (CNNs) for automatic heart sound classification using short-segments of individual heart beats. We desig…
Modeling Brain Connectivity with Graphical Models on Frequency Domain
Xu Gao, Weining Shen, Chee-Ming Ting +3
Multichannel electroencephalograms (EEGs) have been widely used to study cortical connectivity during acquisition of motor skills. In this paper, we introduce copula Gaussian graph…