AUTHOR=Sharaev Maksim G. , Zavyalova Viktoria V. , Ushakov Vadim L. , Kartashov Sergey I. , Velichkovsky Boris M. TITLE=Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data JOURNAL=Frontiers in Human Neuroscience VOLUME=10 YEAR=2016 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2016.00014 DOI=10.3389/fnhum.2016.00014 ISSN=1662-5161 ABSTRACT=
The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of Blood-oxygen-level dependent (BOLD) activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e., effective connectivity), however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), left and right intraparietal cortex (LIPC and RIPC). For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078–0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (