Abstract
Complex collective activity emerges spontaneously in cortical circuits in vivo and in vitro, such as alternation of up and down states, precise spatiotemporal patterns replay, and power law scaling of neural avalanches. We focus on such critical features observed in cortical slices. We study spontaneous dynamics emerging in noisy recurrent networks of spiking neurons with sparse structured connectivity. The emerging spontaneous dynamics is studied, in presence of noise, with fixed connections. Note that no short-term synaptic depression is used. Two different regimes of spontaneous activity emerge changing the connection strength or noise intensity: a low activity regime, characterized by a nearly exponential distribution of firing rates with a maximum at rate zero, and a high activity regime, characterized by a nearly Gaussian distribution peaked at a high rate for high activity, with long-lasting replay of stored patterns. Between this two regimes, a transition region is observed, where firing rates show a bimodal distribution, with alternation of up and down states. In this region, one observes neuronal avalanches exhibiting power laws in size and duration, and a waiting time distribution between successive avalanches which shows a non-monotonic behavior. During periods of high activity (up states) consecutive avalanches are correlated, since they are part of a short transient replay initiated by noise focusing, and waiting times show a power law distribution. One can think at this critical dynamics as a reservoire of dynamical patterns for memory functions.
Highlights
We study spontaneous dynamics emerging in noisy recurrent networks of spiking neurons with sparse structured connectivity
We studied the dynamics of the network with N = 3000 neurons as a function of two parameters, the parameter H0 setting the strengths of the connections, and the parameter α setting the noise level
Such non-equilibrium phase transition has been recently studied in a similar model (Scarpetta and de Candia, 2013, 2014) showing that in the region where the order parameter, which measures the similarity between spontaneous dynamics and the stored dynamic patterns, passes
Summary
Spontaneous cortical activity, i.e., ongoing activity in the absence of sensory stimulation, can show very complex collective features, with, in some cases, the membrane potential making spontaneous transitions between two different levels called up and down states (Steriade et al, 1993; Cowan and Wilson, 1994; Cossart et al, 2003; Shu et al, 2003). Results on in vitro and in vivo up states has suggested that this spontaneous activity occurred in a highly structured way, with repeating spatiotemporal patterns of cellular activity (Cossart et al, 2003; Luczak and MacLean, 2012) Because of their stereotyped spatio-temporal dynamics, it has been conjectured that network up states are circuit attractors (Cossart et al, 2003). The mean time the network spends in the down or in the up state is related to noise intensity and connection strength
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