3 citations · 3 across the 6 of their papers we have counts for
6 papers
Nonlinear Coherence for Vector Time Series: Defining Region-to-Region Functional Brain Connectivity
Paolo Victor Redondo, Raphaël Huser, Hernando Ombao
Alterations in functional brain connectivity characterize neurodegenerative disorders such as Alzheimer's disease (AD) and frontotemporal dementia (FTD). As a non-invasive and cost…
Statistics of Extremes for Neuroscience
Paolo V. Redondo, Matheus B. Guerrero, Raphaël Huser +1
This chapter illustrates how tools from univariate and multivariate statistics of extremes can complement classical methods used to study brain signals and enhance the understandin…
Measuring Information Transfer Between Nodes in a Brain Network through Spectral Transfer Entropy
Paolo Victor Redondo, Raphael Huser, Hernando Ombao
Brain connectivity characterizes interactions between different regions of a brain network during resting-state or performance of a cognitive task. In studying brain signals such a…
Club Exco: clustering brain extreme communities from multi-channel EEG data
Matheus B. Guerrero, Paolo V. Redondo, Marco A. Pinto-Orellana +3
Current methods for clustering brain networks over time often rely on cross-dependence measures computed from the entire range of EEG signals, which can obscure information specifi…
Functional-Coefficient Models for Multivariate Time Series in Designed Experiments: with Applications to Brain Signals
Paolo Victor Redondo, Raphael Huser, Hernando Ombao
To study the neurophysiological basis of attention deficit hyperactivity disorder (ADHD), clinicians use electroencephalography (EEG) which record neuronal electrical activity on t…
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…