RT Journal Article
SR Electronic
T1 Exploring Anti-correlated Resting State BOLD Signals Through Dynamic Functional Connectivity and Whole-brain Computational Modeling
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 085274
DO 10.1101/085274
A1 Murat Demirtaş
A1 Matthieu Gilson
A1 John D. Murray
A1 Dina Popovic
A1 Eduard Vieta
A1 Luis Pintor
A1 Vesna Prčkovska
A1 Pablo Villoslada
A1 Gustavo Deco
YR 2016
UL http://biorxiv.org/content/early/2016/11/02/085274.abstract
AB Resting-state functional magnetic resonance imaging and diffusion weight imaging became a conventional tool to study brain connectivity in healthy and diseased individuals. However, both techniques provide indirect measures of brain connectivity leading to controversies on their interpretation. Among these controversies, interpretation of anti-correlated functional connections and global average signal is a major challenge for the field. In this paper, we used dynamic functional connectivity to calculate the probability of anti-correlations between brain regions. The brain regions forming task-positive and task-negative networks showed high anti-correlation probabilities. The fluctuations in anti-correlation probabilities were significantly correlated with those in global average signal and functional connectivity. We investigated the mechanisms behind these fluctuations using whole-brain computational modeling approach. We found that the underlying effective connectivity and intrinsic noise reflect the static spatiotemporal patterns, whereas the hemodynamic response function is the key factor defining the fluctuations in functional connectivity and anti-correlations. Furthermore, we illustrated the clinical implications of these findings on a group of bipolar disorder patients suffering a depressive relapse (BPD).