Unveiling the complex organization of recurrent patterns in spiking dynamical systems

Complex systems displaying recurrent spike patterns are ubiquitous in nature. Understanding the organization of these patterns is a challenging task. Here we study experimentally the spiking output of a semiconductor laser with feedback. By using symbolic analysis we unveil a nontrivial organization...

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Detalhes bibliográficos
Autores: Aragoneses Aguado, Andrés, Perrone, Sandro, Sorrentino Amaral, Taciano, Torrent Serra, Maria del Carmen|||0000-0001-7965-5656, Masoller Alonso, Cristina|||0000-0003-0768-2019
Formato: artículo
Fecha de publicación:2014
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/22813
Acesso em linha:https://hdl.handle.net/2117/22813
https://dx.doi.org/10.1038/srep04696
Access Level:acceso abierto
Palavra-chave:Semiconductor laser
Díodes semiconductors
Dinamics
Diode lasers
Nonlinear phenomena
Làsers de semiconductors
Diodes, Semiconductor
Dinàmica
Àrees temàtiques de la UPC::Física
Descrição
Resumo:Complex systems displaying recurrent spike patterns are ubiquitous in nature. Understanding the organization of these patterns is a challenging task. Here we study experimentally the spiking output of a semiconductor laser with feedback. By using symbolic analysis we unveil a nontrivial organization of patterns, revealing serial spike correlations. The probabilities of the patterns display a well-defined, hierarchical and clustered structure that can be understood in terms of a delayed model. Most importantly, we identify a minimal model, a modified circle map, which displays the same symbolic organization. The validity of this minimal model is confirmed by analyzing the output of the forced laser. Since the circle map describes many dynamical systems, including neurons and cardiac cells, our results suggest that similar correlations and hierarchies of patterns can be found in other systems. Our findings also pave the way for optical neurons that could provide a controllable set up to mimic neuronal activity.