390 citations · 1.3k across the 16 of their papers we have counts for
16 papers
Decoding Working Memory Load from EEG with LSTM Networks
Samuel Goldstein, Zhenhong Hu, Mingzhou Ding
Working memory (WM) is a mechanism that temporarily stores and manipulates information in service of behavioral goals and is a highly dynamic process. Previous studies have conside…
Spiked Laplacian Graphs: Bayesian Community Detection in Heterogeneous Networks
Leo L Duan, George Michailidis, Mingzhou Ding
In network data analysis, it is becoming common to work with a collection of graphs that exhibit \emph{heterogeneity}. For example, neuroimaging data from patient cohorts are incre…
Spatio-temporal Granger causality: a new framework
Qiang Luo, Wenlian Lu, Wei Cheng +4
That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal…
Mitigating the effects of measurement noise on Granger causality
Hariharan Nalatore, Govindan Rangarajan, Mingzhou Ding
Computing Granger causal relations among bivariate experimentally observed time series has received increasing attention over the past few years. Such causal relations, if correctl…
Estimating Granger causality from Fourier and wavelet transforms of time series data
Mukeshwar Dhamala, Govindan Rangarajan, Mingzhou Ding
Experiments in many fields of science and engineering yield data in the form of time series. The Fourier and wavelet transform-based nonparametric methods are used widely to study…
Granger Causality: Basic Theory and Application to Neuroscience
Mingzhou Ding, Yonghong Chen, Steven L. Bressler
Multi-electrode neurophysiological recordings produce massive quantities of data. Multivariate time series analysis provides the basic framework for analyzing the patterns of neura…