Markers of criticality in phase synchronisation
arXiv:1404.5774 · doi:10.3389/fnsys.2014.00176
Abstract
The concept of the brain as a critical system is very attractive because systems close to criticality are thought to maximise their dynamic range of information processing and communication. To date, there have been two key experimental observations supporting this hypothesis: i) neuronal avalanches with power law distribution of size and ii) long-range temporal correlations (LRTCs) in the amplitude of neural oscillations. The case for how these maximise dynamic range of information processing and communication is still being made and because a significant substrate for information coding and transmission is neural synchrony it is of interest to link synchronisation measures with those of criticality. We propose a framework for characterising criticality in synchronisation based on a new metric of phase synchronisation (rate of change of phase difference) and a set of methods we have developed for detecting LRTCs. We test this framework against two classical models of criticality (Ising and Kuramoto) and recently described variants of these models aimed to more closely represent human brain dynamics. From these simulations we determine the parameters at which these systems show evidence of LRTCs in phase synchronisation. We demonstrate proof of principle by analysing pairs of human simultaneous EEG and EMG time series, suggesting that LRTCs of corticomuscular phase synchronisation can be detected in the resting state. The existence of LRTCs in fluctuations of phase synchronisation suggests that these fluctuations are governed by non-local behaviour. This has important implications regarding the conditions under which one should expect to see LRTCs in phase synchronisation. Specifically, brain resting states may exhibit LRTCs reflecting a state of readiness facilitating rapid task-dependent shifts towards and away from synchronous states that abolish LRTCs.
arXiv comment32 pages, 15 figures
References in corpus (13)
- Effect of Trends on Detrended Fluctuation Analysis
- Emergent complex neural dynamics
- Optimal Dynamical Range of Excitable Networks at Criticality
- Griffiths phases and the stretching of criticality in brain networks
- Failure of adaptive self-organized criticality during epileptic seizure attacks
- Scaling and memory of intraday volatility return intervals in stock market
- A practical guide to measuring the Hurst parameter
- Structural Inference of Hierarchies in Networks
- Markers of criticality in phase synchronisation
- Phase Transitions and Chaos in Long-Range Models of Coupled Oscillators
- Scaling properties of neuronal avalanches are consistent with critical dynamics
- A power-law distribution of phase-locking intervals does not imply critical interaction
- A maximum likelihood based technique for validating detrended fluctuation analysis (ML-DFA)
Cited by in corpus (10)
- The Kuramoto model in complex networks
- Markers of criticality in phase synchronisation
- Conserved Ising Model on the Human Connectome
- Neurofeedback Tunes Scale-Free Dynamics in Spontaneous Brain Activity
- Beta-rhythm oscillations and synchronization transition in network models of Izhikevich neurons: effect of topology and synaptic type
- Reservoir Computing based on Quenched Chaos
- Criticality or Supersymmetry Breaking ?
- Critical Neuromorphic Computing based on Explosive Synchronization
- Fractal analyses of networks of integrate-and-fire stochastic spiking neurons
- Distinct criticality of phase and amplitude dynamics in the resting brain