Naslov
Biological conservation law as an emerging functionality in dynamical neuronal networks

Autori
Podobnik, Boris ; Jusup, M ; Tiganj, Z ; Wang, WX ; Buldú, JM ; Stanley, HE

Izvornik
Proceedings of the National Academy of Sciences of the United States of America (0027-8424) 114 (2017), 45; 11826-11831

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
complex network, semerging properties, homeostatic plasticity, neuroscience, neuronal noise

Sažetak
Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law—the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective.

Izvorni jezik
Engleski

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