The avalanche-like behaviour of large-scale haemodynamic activity from wakefulness to deep sleep

Abstract

Increasing evidence suggests that responsiveness is associated with critical or near-critical cortical dynamics, which exhibit scale-free cascades of spatio-temporal activity. These cascades, or ‘avalanches’, have been detected at multiple scales, from in vitro and in vivo microcircuits to voltage imaging and brain-wide functional magnetic resonance imaging (fMRI) recordings. Criticality endows the cortex with certain information-processing capacities postulated as necessary for conscious wakefulness, yet it remains unknown how unresponsiveness impacts on the avalanche-like behaviour of large-scale human haemodynamic activity. We observed a scale-free hierarchy of co-activated connected clusters by applying a point-process transformation to fMRI data recorded during wakefulness and non-rapid eye movement (NREM) sleep. Maximum-likelihood estimates revealed a significant effect of sleep stage on the scaling parameters of the cluster size power-law distributions. Post hoc statistical tests showed that differences were maximal between wakefulness and N2 sleep. These results were robust against spatial coarse graining, fitting alternative statistical models and different point-process thresholds, and disappeared upon phase shuffling the fMRI time series. Evoked neural bistabilities preventing arousals during N2 sleep do not suffice to explain these differences, which point towards changes in the intrinsic dynamics of the brain that could be necessary to consolidate a state of deep unresponsiveness.

Why Brain Criticality Is Clinically Relevant: A Scoping Review

“…While the study of Dehghani et al (2012) casts doubt on these power-law findings, a recent study of EEG-fMRI data in healthy patients during sleep suggests that critical dynamics may be involved nonetheless ( Bocaccio et al, 2019 ). A power-law distribution of co-activated connected clusters (voxel groups) from fMRI data during sleep was confirmed using the Clauset et al (2009) criteria.…”

Avalanche criticality in individuals, fluid intelligence and working memory

“…Secondly, though we used the denoising fMRI data from HCP with standard data pre-processing procedure, it is still interesting / to investigate the pre-processing procedure affects the results. Thirdly, in the avalanche analysis, the activation events defined in this study was slightly different from definition used by others, such as threshold-crossing events (Tagliazucchi et al, 2012) or threshold-above events (Bocaccio et al, 2019;Wang et al, 2019). We compared these different methods and found all these methods could generate scale free avalanche activities, but unlike our method, the other two methods failed to generate critical branching process in consistent with theory (See Section II in Supplementary Materials).…”

Whole-Brain Models to Explore Altered States of Consciousness from the Bottom Up

“…According to this view, whole-brain models provide a fertile ground to explore how global signatures of different states of consciousness emerge from local dynamics. This promise is already being met, as shown by several recent articles [ 38 , 107 , 114 , 115 , 123 , 124 , 127 , 133 ].…”

“…For example, transitions from wakefulness into other states, such as the different stages of human sleep or the state induced by general anaesthetics, have been interpreted as phase transitions in neural mass models and in terms of the collective dynamics of coupled Stuart-Landau oscillators [114,115,124]. Noise-driven systems at dynamical criticality result in dynamics compatible with neuroimaging recordings obtained during conscious wakefulness, and departures from these dynamics better reflect different states of unconsciousness [38,107,127,[133][134][135]. As will be discussed in the following section, the stochastic switching between different attractors results in the kind of metastable behavior that is characteristic of conscious wakefulness [136].…”