Stochastic Resonance Crossovers in Complex Networks Pinamonti, Giovanni Marro Borau, Joaquín Torres Agudo, Joaquín J. Background noise (acoustics) Neurons Phase transitions Resonance Resonance frequency Signal processing Synapses Working memory Here we numerically study the emergence of stochastic resonance as a mild phenomenon and how this transforms into an amazing enhancement of the signal-to-noise ratio at several levels of a disturbing ambient noise. The setting is a cooperative, interacting complex system modelled as an Ising-Hopfield network in which the intensity of mutual interactions or “synapses” varies with time in such a way that it accounts for, e.g., a kind of fatigue reported to occur in the cortex. This induces nonequilibrium phase transitions whose rising comes associated to various mechanisms producing two types of resonance. The model thus clarifies the details of the signal transmission and the causes of correlation among noise and signal. We also describe short-time persistent memory states, and conclude on the limited relevance of the network wiring topology. Our results, in qualitative agreement with the observation of excellent transmission of weak signals in the brain when competing with both intrinsic and external noise, are expected to be of wide validity and may have technological application. We also present here a first contact between the model behavior and psychotechnical data. 2014-03-21T12:11:25Z 2014-03-21T12:11:25Z 2012 info:eu-repo/semantics/article Pinamonti, G.; Marro, J.; Torres, J.J. Stochastic Resonance Crossovers in Complex Networks. Plos One 7(12): e51170 (2012). [http://hdl.handle.net/10481/31017] 1932-6203 doi: 10.1371/journal.pone.0051170 http://hdl.handle.net/10481/31017 eng http://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License Public Library of Science (PLOS)