Title
Simultaneous Estimation Of The In-Mean And In-Variance Causal Connectomes Of The Human Brain
Abstract
In recent years, the study of the human connectome (i.e. of statistical relationships between non spatially contiguous neurophysiological events in the human brain) has been enormously fuelled by technological advances in high-field functional magnetic resonance imaging (fMRI) as well as by coordinated world wide data-collection efforts like the Human Connectome Project (HCP). In this context, Granger Causality (GC) approaches have recently been employed to incorporate information about the directionality of the influence exerted by a brain region on another. However, while fluctuations in the Blood Oxygenation Level Dependent (BOLD) signal at rest also contain important information about the physiological processes that underlie neurovascular coupling and associations between disjoint brain regions, so far all connectivity estimation frameworks have focused on central tendencies, hence completely disregarding so-called in-variance causality (i.e. the directed influence of the volatility of one signal on the volatility of another). In this paper, we develop a framework for simultaneous estimation of both in-mean and invariance causality in complex networks. We validate our approach using synthetic data from complex ensembles of coupled nonlinear oscillators, and successively employ HCP data to provide the very first estimate of the in-variance connectome of the human brain.
Year
DOI
Venue
2017
10.1109/EMBC.2017.8037824
2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Computer vision,Neuroscience,Causality,Human Connectome Project,Neurophysiology,Functional magnetic resonance imaging,Computer science,Connectome,Granger causality,Artificial intelligence,Complex network,Human Connectome
Conference
2017
ISSN
Citations 
PageRank 
1094-687X
0
0.34
References 
Authors
4
4
Name
Order
Citations
PageRank
Andrea Duggento1117.37
Luca Passamonti24311.28
maria guerrisi3116.95
nicola toschi43615.57