@article{dea12,
author = {de Arcangelis L,},
pages = {243-257},
title = {Are dragon neuronal avalanches dungeons for
self-organized brain activity?},
volume = {205},
note = {Articolo in rivista},
issn = {1951-6355},
journal = {THE EUROPEAN PHYSICAL JOURNAL. SPECIAL TOPICS},
year = {2012},
wosId = {000303337700016},
scopusId = {2-s2.0-84860527469},
abstract = {Recent experiments have detected a novel form of
spontaneous neuronal activity both in vitro and in vivo: neuronal
avalanches. The statistical properties of this activity are typical of critical
phenomena, with power laws characterizing the distributions of
avalanche size and duration. A critical behaviour for the spontaneous
brain activity has important consequences on stimulated activity and
learning. Very interestingly, these statistical properties can be altered in
significant ways in epilepsy and by pharmacological manipulations. In
particular, there can be an increase in the number of large events anticipated
by the power law, referred to herein as dragon-king avalanches.
This behaviour, as verified by numerical models, can originate from
a number of different mechanisms. For instance, it is observed experimentally
that the emergence of a critical behaviour depends on the
subtle balance between excitatory and inhibitory mechanisms acting
in the system. Perturbing this balance, by increasing either synaptic
excitation or the incidence of depolarized neuronal up-states causes frequent
dragon-king avalanches. Conversely, an unbalanced GABAergic
inhibition or long periods of low activity in the network give rise to
sub-critical behaviour. Moreover, the existence of power laws, common
to other stochastic processes, like earthquakes or solar flares, suggests
that correlations are relevant in these phenomena. The dragon-king
avalanches may then also be the expression of pathological correlations
leading to frequent avalanches encompassing all neurons. We will review
the statistics of neuronal avalanches in experimental systems. We
then present numerical simulations of a neuronal network model introducing
within the self-organized criticality framework ingredients from
the physiology of real neurons, as the refractory period, synaptic plasticity
and inhibitory synapses. The avalanche critical behaviour and the
role of dragon-king avalanches will be discussed in relation to different
drives, neuronal states and microscopic mechanisms of charge storage
and release in neuronal networks.}
}