Articolo in rivista, 2006, ENG, 10.1103/PhysRevE.74.036203
Zillmer, R (1); Livi, R (2,3); Politi, A (4,5); Torcini, A (4,5);
1) INFN Sezione Firenze, via Sansone 1, I-50019 Sesto Fiorentino, Italy 2) Dipartimento di Fisica, Universitá di Firenze, via Sansone 1, I-50019 Sesto Fiorentino, Italy 3) Sezione INFN, Unita INFM e Centro Interdipartimentale per lo Studio delle Dinamiche Complesse, via Sansone 1, I-50019 Sesto Fiorentino, Italy 4) Istituto dei Sistemi Complessi, CNR, CNR, via Madonna del Piano 10, I-50019 Sesto Fiorentino, Italy 5) Centro Interdipartimentale per lo Studio delle Dinamiche Complesse, via Sansone 1, I-50019 Sesto Fiorentino
The dynamical behavior of a weakly diluted fully inhibitory network of pulse-coupled spiking neurons is investigated. Upon increasing the coupling strength, a transition from regular to stochasticlike regime is observed. In the weak-coupling phase, a periodic dynamics is rapidly approached, with all neurons firing with the same rate and mutually phase locked. The strong-coupling phase is characterized by an irregular pattern, even though the maximum Lyapunov exponent is negative. The paradox is solved by drawing an analogy with the phenomenon of 'stable chaos,' i.e., by observing that the stochasticlike behavior is 'limited' to an exponentially long (with the system size) transient. Remarkably, the transient dynamics turns out to be stationary.
Physical review. E, Statistical, nonlinear, and soft matter physics (Print) 74 , pp. 036203–?
PARTIAL SYNCHRONIZATION, COMPLEX NETWORKS, OSCILLATORS, TRANSIENTS, Neural networks
Livi Roberto, Politi Antonio, Torcini Alessandro
ISC – Istituto dei sistemi complessi, INFM – Centro di responsabilità scientifica INFM
CNR authors
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:166994
DOI: 10.1103/PhysRevE.74.036203
ISI Web of Science (WOS): 000240870300040