TY - JOUR UR - http://lib.ugent.be/catalog/pug01:1090740 ID - pug01:1090740 LA - eng TI - Coexistence of stable stationary behavior and partial synchrony in an all-to-all coupled spiking neural network PY - 2010 JO - (2010) PHYSICAL REVIEW E SN - 1539-3755 PB - 2010 AU - De Smet, Filip TW08 801001785665 055904949078 AU - Aeyels, Dirk TW06 801000317632 0000-0002-3031-7215 AB - We consider the stationary and the partially synchronous regimes in an all-to-all coupled neural network consisting of an inﬁnite number of leaky integrate-and-ﬁre neurons. Using analytical tools as well as simulation results, we show that two threshold values for the coupling strength may be distinguished. Below the lower threshold, no synchronization is possible; above the upper threshold, the stationary regime is unstable and partial synchrony prevails. In between there is a range of values for the coupling strength where both regimes may be observed. The assumption of an inﬁnite number of neurons is crucial: simulations with a ﬁnite number of neurons indicate that above the lower threshold partial synchrony always prevails—but with a transient time that may be unbounded with increasing system size. For values of the coupling strength in a neighborhood of the lower threshold, the ﬁnite model repeatedly builds up toward synchronous behavior, followed by a sudden breakdown, after which the synchronization is slowly built up again. The “transient” time needed to build up synchronization again increases with increasing system size, and in the limit of an inﬁnite number of neurons we retrieve stationary behavior. Similarly, within some range for the coupling strength in this neighborhood, a stable synchronous solution may exist for an inﬁnite number of neurons. ER -Download RIS file
00000nam^a2200301^i^4500 | |||
001 | 1090740 | ||
005 | 20180813140537.0 | ||
008 | 101221s2010------------------------eng-- | ||
022 | a 1539-3755 | ||
024 | a 000286746600001 2 wos | ||
024 | a 1854/LU-1090740 2 handle | ||
024 | a 10.1103/PhysRevE.82.066208 2 doi | ||
040 | a UGent | ||
245 | a Coexistence of stable stationary behavior and partial synchrony in an all-to-all coupled spiking neural network | ||
260 | c 2010 | ||
520 | a We consider the stationary and the partially synchronous regimes in an all-to-all coupled neural network consisting of an inﬁnite number of leaky integrate-and-ﬁre neurons. Using analytical tools as well as simulation results, we show that two threshold values for the coupling strength may be distinguished. Below the lower threshold, no synchronization is possible; above the upper threshold, the stationary regime is unstable and partial synchrony prevails. In between there is a range of values for the coupling strength where both regimes may be observed. The assumption of an inﬁnite number of neurons is crucial: simulations with a ﬁnite number of neurons indicate that above the lower threshold partial synchrony always prevails—but with a transient time that may be unbounded with increasing system size. For values of the coupling strength in a neighborhood of the lower threshold, the ﬁnite model repeatedly builds up toward synchronous behavior, followed by a sudden breakdown, after which the synchronization is slowly built up again. The “transient” time needed to build up synchronization again increases with increasing system size, and in the limit of an inﬁnite number of neurons we retrieve stationary behavior. Similarly, within some range for the coupling strength in this neighborhood, a stable synchronous solution may exist for an inﬁnite number of neurons. | ||
598 | a A1 | ||
700 | a De Smet, Filip u TW08 0 801001785665 0 055904949078 0 001998205858 9 F6E4666A-F0ED-11E1-A9DE-61C894A0A6B4 | ||
700 | a Aeyels, Dirk u TW06 0 801000317632 0 0000-0002-3031-7215 9 F3AFBA76-F0ED-11E1-A9DE-61C894A0A6B4 | ||
650 | a Mathematics and Statistics | ||
653 | a MODELS | ||
653 | a SYSTEMS | ||
653 | a MAPS | ||
653 | a MECHANISMS | ||
653 | a DYNAMICS | ||
653 | a OSCILLATORS | ||
653 | a VISUAL-CORTEX | ||
653 | a SELF-ORGANIZATION | ||
653 | a NEURONAL NETWORKS | ||
773 | t PHYSICAL REVIEW E g Phys. Rev. E. 2010. 82 (6) q 82:6< | ||
856 | 3 Full Text u https://biblio.ugent.be/publication/1090740/file/1090750 z [open] y PhysRevE.82.066208.pdf | ||
920 | a article | ||
Z30 | x EA 1 TW08 | ||
922 | a UGENT-EA |
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