Paper Info
Title
Resting State Neural Correlates Of Cardiac Sympathetic Dynamics In Healthy Subjects
Abstract
Recent advances in functional Magnetic Resonance Imaging (fMRI) research have uncovered the existence of the central autonomic network (CAN), which comprises brain regions whose activity correlates with autonomic nervous system dynamics. By exploiting the spectral paradigm of heartbeat dynamics, cortical and sub-cortical areas functionally linked to vagal activity have been identified. However, due to methodological limitations, functional neural correlates of cardiac sympathetic dynamics remain uncharacterized. To this extent, we exploit the high spatio-temporal resolution of fMRI data from the Human Connectome Project to study the CAN activity by correlating a recently proposed instantaneous characterization of sympathetic activity (the sympathetic activity index - SAI) from heartbeat dynamics. SAI estimates are embedded into the probabilistic modeling of inhomogeneous point-processes, and are derived from a combination of disentangling coefficients linked to the orthonormal Laguerre functions. By analyzing resting state recordings from 34 young healthy people, we obtain positive correlations between instantaneous SAI estimates and a number of brain regions including frontal pole, insular cortex, frontal and temporal gyri, lateral occipital cortex, paracingulate and cingulate gyri, precuneus and temporal fusiform cortices, as well as thalamus, caudate nucleus, putamen, brain-stem, hippocampus, amygdala, and nucleus accumbens. Our findings significantly extend current knowledge on the CAN, opening new avenues in the characterization of healthy and pathological states in humans.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8856978
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Caudate nucleus,Computer vision,Neural correlates of consciousness,Precuneus,Neuroscience,Human Connectome Project,Functional magnetic resonance imaging,Computer science,Resting state fMRI,Insular cortex,Artificial intelligence,Hippocampus
Conference
2019
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Gaetano Valenza131448.21
Andrea Duggento2117.37
Luca Passamonti34311.28
nicola toschi43615.57
Riccardo Barbieri546070.50