Abstract
Spontaneous activity measured in human subject under the absence of any task exhibits complex patterns of correlation that largely correspond to large-scale functional topographies obtained with a wide variety of cognitive and perceptual tasks. These “resting state networks” (RSNs) fluctuate over time, forming and dissolving on the scale of seconds to minutes. While these fluctuations, most prominently those of the default mode network, have been linked to cognitive function, it remains unclear whether they result from random noise or whether they index a non-stationary process which could be described as state switching.
In this study, we use a sliding windows approach to relate temporal dynamics of RSNs to global modulations in correlation and BOLD variance. We compare empirical data, phase-randomized surrogate data, and data simulated with a stationary model. We find that RSN time courses exhibit a large amount of coactivation in all three cases, and that the modulations in their activity are closely linked to global dynamics of the underlying BOLD signal.
We find that many properties of the observed fluctuations in FC and BOLD, including their ranges and their correlations amongst each other, are explained by fluctuations around the average FC structure. However, we also encounter interesting characteristics that are not explained in this way. In particular, we find that the brain spends more time in the peaks and troughs of modulations than can be expected from stationary dynamics.
Footnotes
↵* katharina.glomb{at}upf.edu
Conflict of interest: The authors declare no competing financial interests.
Funding (authors’ initials given after grant numbers) This work was supported by the European Union, FP7 Marie Curie ITN “INDIREA” (Grant N. 606901; KG), FP7 FET ICT Flagship Human Brain Project (Grant N. 604102; MG), ERC Advanced Human Brain Project (Grant N. 604102; GD), Horizon2020 ERC Consolidator (Grant N. …; PR); the Spanish Ministry for Economy, Industry and Competitiveness (MINECO) project “PIRE-PICCS” (Grant N. PCIN-2015-079), SEMAINE ERA-Net NEURON Project (Grant N. PCIN2013-026; APA), and ICoBAM (Grant N. PSI2013-42091-P; GD); the James S. McDonnell Foundation (Brain Network Recovery Group, Grant N. JSMF22002082; PR); the German Ministry of Education and Research (Grant N. 01GQ1504A and 01GQ0971-5; PR); the Max-Planck Society (Minerva Program; PR)