189 citations · 888 across the 107 of their papers we have counts for
16 papers · 1 filter
BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data
Meini Tang, Chee-Ming Ting, Hernando Ombao
Intrinsic connectivity networks (ICNs) are specific dynamic functional brain networks that are consistently found under various conditions including rest and task. Studies have sho…
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly-Intractable Bayesian Inference
Luiza S. C. Piancastelli, Nial Friel, Wagner Barreto-Souza +1
In this paper, a multivariate count distribution with Conway-Maxwell (COM)-Poisson marginals is proposed. To do this, we develop a modification of the Sarmanov method for construct…
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…
Markov-Switching State-Space Models with Applications to Neuroimaging
David Degras, Chee-Ming Ting, Hernando Ombao
State-space models (SSM) with Markov switching offer a powerful framework for detecting multiple regimes in time series, analyzing mutual dependence and dynamics within regimes, an…
Filtrated Common Functional Principal Components for Multivariate Functional data
Shuhao Jiao, Ron D. Frostig, Hernando Ombao
Local field potentials (LFPs) are signals that measure electrical activity in localized cortical regions from implanted tetrodes in the human or animal brain. The LFP signals are c…
SCAU: Modeling spectral causality for multivariate time series with applications to electroencephalograms
Marco Antonio Pinto-Orellana, Peyman Mirtaheri, Hugo L. Hammer +1
Electroencephalograms (EEG) are noninvasive measurement signals of electrical neuronal activity in the brain. One of the current major statistical challenges is formally measuring…
Lattice Paths for Persistent Diagrams
Moo K. Chung, Hernando Ombao
Persistent homology has undergone significant development in recent years. However, one outstanding challenge is to build a coherent statistical inference procedure on persistent d…
Spectral Dependence
Hernando Ombao, Marco Pinto
This paper presents a general framework for modeling dependence in multivariate time series. Its fundamental approach relies on decomposing each signal in a system into various fre…
Brain Waves Analysis Via a Non-parametric Bayesian Mixture of Autoregressive Kernels
Guillermo Granados-Garcia, Mark Fiecas, Babak Shahbaba +2
The standard approach to analyzing brain electrical activity is to examine the spectral density function (SDF) and identify predefined frequency bands that have the most substantia…
Ridge-penalized adaptive Mantel test and its application in imaging genetics
Dustin Pluta, Tong Shen, Gui Xue +3
We propose a ridge-penalized adaptive Mantel test (AdaMant) for evaluating the association of two high-dimensional sets of features. By introducing a ridge penalty, AdaMant tests t…
Time-varying optimization for Spike Inference from Multi-Trial Calcium Recordings
Tong Shen, Kevin Johnston, Gyorgy Lur +3
Optical imaging of genetically encoded calcium indicators is a powerful tool to record the activity of a large number of neurons simultaneously over a long period of time from free…
Statistical Inference for Local Granger Causality
Yan Liu, Masanobu Taniguchi, Hernando Ombao
Granger causality has been employed to investigate causality relations between components of stationary multiple time series. We generalize this concept by developing statistical i…
Smooth Online Parameter Estimation for time varying VAR models with application to rat's LFP data
Anass El Yaagoubi Bourakna, Marco Pinto, Norbert Fortin +1
Multivariate time series data appear often as realizations of non-stationary processes where the covariance matrix or spectral matrix smoothly evolve over time. Most of the current…
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…
Change-point detection using spectral PCA for multivariate time series
Shuhao Jiao, Tong Shen, Zhaoxia Yu +1
We propose a two-stage approach Spec PC-CP to identify change points in multivariate time series. In the first stage, we obtain a low-dimensional summary of the high-dimensional ti…
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…