Brain Performance versus Phase Transitions Torres Agudo, Joaquín J. Marro Borau, Joaquín Network models Complex networks Statistical physics We here illustrate how a well-founded study of the brain may originate in assuming analogies with phase-transition phenomena. Analyzing to what extent a weak signal endures in noisy environments, we identify the underlying mechanisms, and it results a description of how the excitability associated to (non-equilibrium) phase changes and criticality optimizes the processing of the signal. Our setting is a network of integrate-and-fire nodes in which connections are heterogeneous with rapid time-varying intensities mimicking fatigue and potentiation. Emergence then becomes quite robust against wiring topology modification—in fact, we considered from a fully connected network to the Homo sapiens connectome—showing the essential role of synaptic flickering on computations. We also suggest how to experimentally disclose significant changes during actual brain operation. 2015-07-27T09:30:05Z 2015-07-27T09:30:05Z 2015 info:eu-repo/semantics/article Torres Agudo, J.J.; Marro Borau, J. Brain Performance versus Phase Transitions. Scientific Reports, 5: 12216 (2015). [http://hdl.handle.net/10481/37117] 2045-2322 http://hdl.handle.net/10481/37117 10.1038/srep12216 eng http://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License Nature Publishing