Publications by authors named "Samy Castro"

The structural connectivity of human brain allows the coexistence of segregated and integrated states of activity. Neuromodulatory systems facilitate the transition between these functional states and recent computational studies have shown how an interplay between the noradrenergic and cholinergic systems define these transitions. However, there is still much to be known about the interaction between the structural connectivity and the effect of neuromodulation, and to what extent the connectome facilitates dynamic transitions.

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The capability of cortical regions to flexibly sustain an "ignited" state of activity has been discussed in relation to conscious perception or hierarchical information processing. Here, we investigate how the intrinsic propensity of different regions to get ignited is determined by the specific topological organisation of the structural connectome. More specifically, we simulated the resting-state dynamics of mean-field whole-brain models and assessed how dynamic multistability and ignition differ between a reference model embedding a realistic human connectome, and alternative models based on a variety of randomised connectome ensembles.

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Article Synopsis
  • The study investigates multistable behavior in neural networks, characterized by shifting between different synchronized states without external triggers, linked to how the brain processes new sensory information.
  • Key factors like network topology, delays, and noise significantly influence these dynamics, but the effects of local chaos versus stochasticity on state switching were previously underexplored.
  • Using a neural model, the research reveals that moderate levels of noise can enhance multistability in chaotic networks, while excessive noise disrupts it; interestingly, even nonchaotic networks can exhibit multistability under certain noise conditions.
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Chaotic dynamics has been shown in the dynamics of neurons and neural networks, in experimental data and numerical simulations. Theoretical studies have proposed an underlying role of chaos in neural systems. Nevertheless, whether chaotic neural oscillators make a significant contribution to network behaviour and whether the dynamical richness of neural networks is sensitive to the dynamics of isolated neurons, still remain open questions.

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