2002
DOI: 10.1007/3-540-46084-5_28
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Characterization of Triphasic Rhythms in Central Pattern Generators (II): Burst Information Analysis

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Cited by 13 publications
(9 citation statements)
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“…The signatures depend both on the particular settings of the individual neurons and on the topology of connections, but this topology is the final shaper of the neural signatures. The results reported in this section can be reproduced with other neuron models and network architectures [13,14]. In general, the presence of slow chemical connections produced a more precise ISI return plot than those corresponding to the circuits without the slow synapses.…”
Section: Signatures Are Shaped By the Network Connectionssupporting
confidence: 61%
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“…The signatures depend both on the particular settings of the individual neurons and on the topology of connections, but this topology is the final shaper of the neural signatures. The results reported in this section can be reproduced with other neuron models and network architectures [13,14]. In general, the presence of slow chemical connections produced a more precise ISI return plot than those corresponding to the circuits without the slow synapses.…”
Section: Signatures Are Shaped By the Network Connectionssupporting
confidence: 61%
“…In this paper we review some of our modeling work about the origin of the neural signatures and their role in implementing multiple codes in spiking-bursting activity [13,14,15,16,17].…”
Section: Bursts As Unitary Eventsmentioning
confidence: 99%
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“…The intraburst spike distribution of CPG neurons has not been analyzed in great detail since, typically, it is thought that the slow wave dynamics is the main factor shaping the rhythmic behavior of the system. However, several recent experimental and modeling results indicate that the temporal structure of the bursts can be important for CPG neurons [8,9,10,11]. In particular, CPG cells could use the specific temporal structure of their fast dynamics, in addition to the phase and frequency of the slow wave, as an information encoding mechanism.…”
Section: Discussionmentioning
confidence: 99%
“…These signatures consist of a cell-specific interspike interval (ISI) distribution. The origin of these signatures has been studied using model networks [9,10,11]. In these models the synaptic configuration of the network is the main factor shaping the signatures, although the intrinsic dynamics of each cell can also contribute to the specific ISI distributions.…”
Section: Introductionmentioning
confidence: 99%