What kind of noise is brain noise: anomalous scaling behavior of the resting brain activity fluctuations

Abstract

The study of spontaneous fluctuations of brain activity, often referred as brain noise, is getting increasing attention in functional magnetic resonance imaging (fMRI) studies. Despite important efforts, much of the statistical properties of such fluctuations remain largely unknown. This work scrutinizes these fluctuations looking at specific statistical properties which are relevant to clarify its dynamical origins. Here, three statistical features which clearly differentiate brain data from naive expectations for random processes are uncovered: First, the variance of the fMRI mean signal as a function of the number of averaged voxels remains constant across a wide range of observed clusters sizes. Second, the anomalous behavior of the variance is originated by bursts of synchronized activity across regions, regardless of their widely different sizes. Finally, the correlation length (i.e., the length at which the correlation strength between two regions vanishes) as well as mutual information diverges with the cluster's size considered, such that arbitrarily large clusters exhibit the same collective dynamics than smaller ones. These three properties are known to be exclusive of complex systems exhibiting critical dynamics, where the spatio-temporal dynamics show these peculiar type of fluctuations. Thus, these findings are fully consistent with previous reports of brain critical dynamics, and are relevant for the interpretation of the role of fluctuations and variability in brain function in health and disease.

Brain Organization into Resting State Networks Emerges at Criticality on a Model of the Human Connectome

“…We compare now the dynamics of the model with previous experimental results, in particular, with two robust features exhibited by the spontaneous activity of human brain RSN [17]: 1) the correlation length of brain activity increases with size (as expected by the divergence of correlation length), and 2) the variance of the short-term correlations between pairs of brain sites remains high, independently of the number of pairs considered. Since these two properties are often seen as generic features of criticality, we decided to explore first whether the model exhibits similar dynamics.…”

“…Temporal fluctuations of the mean correlation in the RSN. As recently shown [17], the time evolution of the correlation within these patterns exhibits bursts of high correlation intermixed with instances of dis-coordination. Panel A in Fig.…”

“…Since these two properties are often seen as generic features of criticality, we decided to explore first whether the model exhibits similar dynamics. To compare with the experimental results, each node of the model was labeled as belonging to the closest human RSN by matching the node's coordinates provided by Hagmann et al [1] with a spatial mask of the RSN [5,17]. Nodes that were farther than 1 cm from the closest RSN were discarded from the analysis (see Supp.…”

“…The correlation length represents the average distance at which two points in the system behave independently, and is known to diverge at criticality [18]. Following a standard procedure [17,18], we computed the average correlation function of the signal fluctuations between all pairs of nodes in each cluster which are separated by a distance r, yielding the correlation function C(r) (see Supp. Info.).…”

Scale-free Dynamics and Critical Phenomena in Cortical Activity

“…However, only functional components showed significant modulations of the multi-fractal attributes between rest and task. Fraiman and Chialvo (2012) investigated the statistical properties of spatio-temporal dynamics in fMRI data. They considered three novel statistical features, which reveal the type of fluctuations generated by systems in a critical state.…”