Abstract
The spontaneous activity of cortical networks is characterized by the emergence of different dynamic states. Although several attempts were accomplished to understand the origin of these dynamics, the underlying factors continue to be elusive. In this work, we specifically investigated the interplay between network topology and spontaneous dynamics within the framework of self-organized criticality (SOC). The obtained results support the hypothesis that the emergence of critical states occurs in specific complex network topologies. By combining multi-electrode recordings of spontaneous activity of in vitro cortical assemblies with theoretical models, we demonstrate that different ‘connectivity rules’ drive the network towards different dynamic states. In particular, scale-free architectures with different degree of small-worldness account better for the variability observed in experimental data, giving rise to different dynamic states. Moreover, in relationship with the balance between excitation and inhibition and percentage of inhibitory hubs, the simulated cortical networks fall in a critical regime.
Highlights
The spontaneous activity of cortical networks is characterized by the emergence of different dynamic states
In large-scale networks developing ex vivo and chronically coupled to Micro Electrode Arrays (MEAs) neurons can freely form synaptic connections during development and, besides the fact that they must grow on a rigid substrate, they are not constrained by any additional external cues
The degree distributions of RND networks have been fitted by a Gaussian distribution (Fig. 2d), whose mean value corresponds to the network average degree
Summary
The spontaneous activity of cortical networks is characterized by the emergence of different dynamic states. Its analysis has revealed that cortical networks generate scale-free activation patterns called neuronal avalanches, supporting the evidence of criticality in the brain. Such experimental findings come from in vitro (acute and organotypic cortical slices[4], and dissociated cultures5) and in vivo experimental models (awake monkeys[6], anesthetized rats[7] and cats8), up to the human brain[9]. Experimental evidences in vitro show that mature cortical assemblies not necessarily fall into a critical regime, but can show subcritical or supercritical states[5,10] Both at in vitro and in vivo level, functional and structural networks show features typical of complex networks. We found that only a specific (i.e., physiological) balance between excitation and inhibition is capable to drive the network towards a critical dynamic state
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