Experimental evidence of nonlinear avalanche dynamics of energetic particle modes

Recent observations in HL-2A tokamak give new experimental evidences of energetic particle mode (EPM) avalanche. In a strong EPM burst, the mode structure propagates radially outward within two hundred Alfvén time, while the frequency of the dominant mode changes self-consistently to maximize wave-particle power exchange and mode growth. This suggests that significant energetic particle transport occurs in this avalanche phase, in agreement with theoretical framework of EPM convective amplification. A simplified relay runner model yields satisfactory interpretations of the measurements. The results can help understanding the nonlinear dynamics of energetic particle driven modes in future burning plasmas, such as ITER.

Critical behaviour of the stochastic Wilson-Cowan model

Spontaneous brain activity is characterized by bursts and avalanche-like dynamics, with scale-free features typical of critical behaviour. The stochastic version of the celebrated Wilson-Cowan model has been widely studied as a system of spiking neurons reproducing non-trivial features of the neural activity, from avalanche dynamics to oscillatory behaviours. However, to what extent such phenomena are related to the presence of a genuine critical point remains elusive. Here we address this central issue, providing analytical results in the linear approximation and extensive numerical analysis. In particular, we present results supporting the existence of a bona fide critical point, where a second-order-like phase transition occurs, characterized by scale-free avalanche dynamics, scaling with the system size and a diverging relaxation time-scale. Moreover, our study shows that the observed critical behaviour falls within the universality class of the mean-field branching process, where the exponents of the avalanche size and duration distributions are, respectively, 3/2 and 2. We also provide an accurate analysis of the system behaviour as a function of the total number of neurons, focusing on the time correlation functions of the firing rate in a wide range of the parameter space.

Snow-cornice and snow-avalanche monitoring using automatic time-lapse cameras in Tasiapik Valley, Nunavik (Québec) during the winter of 2017-18

A series of automatic time-lapse cameras installed along the southwestern side of Tasiapik Valley, near the village of Umiujaq, Nunavik (Northern Québec) documented several departure modes and types of snow involved in snow avalanches during winter 2017-18. These included cornice-avalanche dynamics, slab and loose snow avalanches, and clean and dirty snow avalanches. At the top of the selected slope, a camera monitored the development of a snow cornice beginning in November 2017, detecting multiple cornice failures over the winter and spring. The track and deposition area of the runout paths were monitored from two cameras downslope, revealing the concomitance of snow-cornice fall and snow-avalanche triggering. Snow-avalanche activity remained relatively infrequent until the end of May 2018. Spring snow-avalanche activity is characterized by wet and dirty snow avalanches carrying debris to the foot of the slope and by runout zones located near the road along the slope.

Critical behaviour of the stochastic Wilson-Cowan model

Spontaneous brain activity is characterized by bursts and avalanche-like dynamics, with scale-free features typical of critical behaviour. The stochastic version of the celebrated Wilson-Cowan model has been widely studied as a system of spiking neurons reproducing non-trivial features of the neural activity, from avalanche dynamics to oscillatory behaviours. However, to what extent such phenomena are related to the presence of a genuine critical point remains elusive. Here we address this central issue, providing analytical results in the linear approximation and extensive numerical analysis. In particular, we present results supporting the existence of a bona fide critical point, where a second-order-like phase transition occurs, characterized by scale-free avalanche dynamics, scaling with the system size and a diverging relaxation time-scale. Moreover, our study shows that the observed critical behaviour falls within the universality class of the mean-field branching process, where the exponents of the avalanche size and duration distributions are, respectively, -3/2 and -2. We also provide an accurate analysis of the system behaviour as a function of the total number of neurons, focusing on the time correlation functions of the firing rate in a wide range of the parameter space.

Long-term stability of avalanche scaling and integrative network organization in prefrontal and premotor cortex

Ongoing neuronal activity in the brain establishes functional networks that reflect normal and pathological brain function. Most estimates of these functional networks suffer from low spatiotemporal resolution and indirect measures of neuronal population activity, limiting the accuracy and reliability in their reconstruction over time. Here, we studied the stability of neuronal avalanche dynamics and corresponding reconstructed functional networks in the adult brain. Using chronically implanted high-density microelectrode arrays, the local field potential (LFP) of resting state activity was recorded in prefrontal and premotor cortex of awake nonhuman primates. Avalanche dynamics revealed stable scaling exhibiting an inverted parabolic profile and collapse exponent of 2 in line with a critical branching process over many days and weeks. Functional networks were based on a Bayesian-derived estimator and demonstrated stable integrative properties characterized by non-trivial high neighborhood overlap between strongly connected nodes and robustness to weak link pruning. Entropy-based mixing analysis revealed significant changes in strong link weights over weeks. The long-term stability in avalanche scaling and integrative network organization in the face of individual link weight changes should support the development of non-invasive biomarkers to characterize normal and abnormal brain states in the adult brain.

Perspectives on Snow Avalanche Dynamics Research

As an introduction for non-specialists to the Special Issue on snow avalanche dynamics, this paper first outlines how understanding the dynamics of snow avalanches can contribute to reducing risk for settlements and infrastructure. The main knowledge gaps in this field of research concern (i) the properties of the flow regimes and the transitions between them, and (ii) the dynamics of mass change due to erosion and deposition. These two aspects are intertwined and determine not only the reach of an avalanche, but also its velocity, course and impact pressure. Experimental studies described in this Special Issue comprise a wide range of scales from small rotating drums to real snow avalanches. In addition, several papers describe post-event field surveys of specific avalanches and analyze them using different methods and techniques, demonstrating how valuable qualitative insight can be gained in this way. The theoretical developments range from exploratory studies of fluid–particle interactions to a comprehensive review of half a century of avalanche flow modeling in Russia.