@article{90bf1464fe434bdcac3ad23441e93422,
title = "Temporal transitions of spontaneous brain activity",
abstract = "Spontaneous brain activity, typically investigated using resting-state fMRI (rsfMRI), provides a measure of inter-areal resting-state functional connectivity (RSFC). Although it has been established that RSFC is non-stationary, previous dynamic rsfMRI studies mainly focused on revealing the spatial characteristics of dynamic RSFC patterns, but the temporal relationship between these RSFC patterns remains elusive. Here we investigated the temporal organization of characteristic RSFC patterns in awake rats and humans. We found that transitions between RSFC patterns were not random but followed specific sequential orders. The organization of RSFC pattern transitions was further analyzed using graph theory, and pivotal RSFC patterns in transitions were identified. This study has demonstrated that spontaneous brain activity is not only nonrandom spatially, but also nonrandom temporally, and this feature is well conserved between rodents and humans. These results offer new insights into understanding the spatiotemporal dynamics of spontaneous activity in the mammalian brain.",
author = "Zhiwei Ma and Nanyin Zhang",
note = "Funding Information: Human subjects: This study only involves analysis of human imaging data that were publicly available (Human Connectome Project). No informed consent was obtained. The study has been approved by the IRB of the Pennsylvania State University (STUDY00005665). Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#43583-1) of the Pennsylvania State University. Funding Information: The present study was partially supported by National Institute of Neurological Disorders and Stroke Grant R01NS085200 (PI: Nanyin Zhang, PhD) and National Institute of Mental Health Grant R01MH098003 and RF1MH114224 (PI: Nanyin Zhang, PhD). Part of this research was conducted using the high-performance computing resources provided by the Institute for CyberScience at the Pennsylvania State University (https://ics.psu.edu). Human data were provided by the HCP, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. National Institute of Mental Health R01MH098003 Nanyin Zhang National Institute of Neurological Disorders and Stroke R01NS085200 Nanyin Zhang National Institute of Mental Health RF1MH114224 Nanyin Zhang The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. Funding Information: The present study was partially supported by National Institute of Neurological Disorders and Stroke Grant R01NS085200 (PI: Nanyin Zhang, PhD) and National Institute of Mental Health Grant R01MH098003 and RF1MH114224 (PI: Nanyin Zhang, PhD). Part of this research was conducted using the high-performance computing resources provided by the Institute for CyberScience at the Pennsylvania State University (https://ics.psu.edu). Human data were provided by the HCP, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. Publisher Copyright: {\textcopyright} Ma and Zhang.",
year = "2018",
month = mar,
day = "8",
doi = "10.7554/eLife.33562",
language = "English (US)",
volume = "7",
journal = "eLife",
issn = "2050-084X",
publisher = "eLife Sciences Publications Ltd",
}