Tracking intrinsic connectivity brain network features during successive (Pseudo-) resting states and interoceptive task fMRI.

Conf Proc IEEE Eng Med Biol Soc. 2016 Aug;2016:5567-5570

Authors: Jarrahi B, Mantini D

Abstract
Advanced multivariate analyses of functional magnetic resonance imaging (fMRI) data based on blood oxygen level-dependent (BOLD) contras have revealed that the human brain organizes its activities into multiple intrinsic connectivity networks (ICNs). Several fMRI studies have evaluated the modulations of these networks during different cognitive or emotional tasks using blind source separation techniques particularly the independent component analysis (ICA). In this exploratory study, we applied ICA methodology to examine ICN modulations under different interoceptive conditions. Fifteen right-handed healthy subjects (age range 21-48 years) underwent a series of eyes-open resting-state and interoceptive task fMRI scans. Using a high-order ICA model, the functional imaging data were decomposed into 75 independent components and 36 were identified as non-artifactual ICNs. ICN spatial modulations were evaluated in terms of the network volume and maximum activations. ICN temporal modulations were assessed based on the power density frequency spectra. Following a false discovery rate multiple comparison correction threshold of ρ <; 0.05, we found significant changes in spatial feature of the attention/cognitive, default-mode, visual and salience networks. More liberal statistical criteria (uncorrected ρ <; 0.05) also indicated differences in network volumes between different states especially involving the sensorimotor, subcortical, cerebellar and brainstem networks. Significant power spectra changes were also found in several attention/cognitive and visual networks as well as the sensorimotor, salience, and subcortical networks especially when resting-states where compared with the interoceptive task fMRI. Further investigations of how interoceptive sensations alter the spatial and temporal features of the human brain networks can elucidate the foundational underpinnings of brain-body relation.

PMID: 28325028 [PubMed - in process]