A neural network model for the Suprachiasmatic Nucleus in mammals.

ROMÁN M; NIETO PS; PEROTTI J; GARBARINO PICO E; TAMARIT FA

Congreso; XLVIII Reunión Anual Sociedad Argentina de Investigación en Bioquímica y Biología Molecular (SAIB).; 2012

Living organisms exhibit rhythmic variations in diverse biological functions. Among these there are the so-called circadian rhythms: variations with a period close to 24 hours. Such rhythms, which are entrainable to external changes of similar periodicity (e.g., light/dark cycles), are also endogenous and can persist even in constant conditions. In the case of mammals, the circadian rhythms are coordinated by the suprachiasmatic nucleus (SCN), a brain structure composed of approximately 20000 neurons. Each of these neurons contain within themselves a (genetic) clock machinery and it is their synchronized expression that allows the SCN to behave as a central robust clock. This structure is often studied experimentally , by cutting slices of tissue and using bioluminescence techniques in order to measure genetic expression. However, discerning the structure of this neural network turns out to be unattainable experimentally. Employing a clock-neuron model (Bernard ., 2007) we simulate the dynamics of a twodimensional network with different architectures and compare some emerging properties. In particular, the embedded scale free network (Rozenfeld ., 2008) is introduced, which presents simultaneously high degree of synchronization and the formation of spatio-temporal patterns.