DOI: 10.1007/978-1-4020-9143-8_13
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An Expressive Body Language Underlies Drosophila Courtship Behavior

Abstract: Recurrent connections are thought to be a common feature of the neural circuits that encode memories, but how memories are laid down in such circuits is not fully understood. Here we present evidence that courtship memory in Drosophila relies on the recurrent circuit between mushroom body gamma (MBg), M6 output, and aSP13 dopaminergic neurons. We demonstrate persistent neuronal activity of aSP13 neurons and show that it transiently potentiates synaptic transmission from MBg>M6 neurons. M6 neurons in turn provi… Show more

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Cited by 2 publications
(2 citation statements)
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“…Irreducible unstable periodic orbits (IUPO) have been shown to capture the complexity of chaotic systems in a condensed manner. [1][2][3][4][5][6][7] As IUPO are generally composed of a number of network elements, and since the whole network can be exhausted by IUPO in an efficient and well-controlled manner, they are highly suitable for a mesoscopic description of complex networks. In the past, IUPO have been used to extract salient, essentially macroscopic, properties from dynamical systems.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Irreducible unstable periodic orbits (IUPO) have been shown to capture the complexity of chaotic systems in a condensed manner. [1][2][3][4][5][6][7] As IUPO are generally composed of a number of network elements, and since the whole network can be exhausted by IUPO in an efficient and well-controlled manner, they are highly suitable for a mesoscopic description of complex networks. In the past, IUPO have been used to extract salient, essentially macroscopic, properties from dynamical systems.…”
Section: Introductionmentioning
confidence: 99%
“…In the past, IUPO have been used to extract salient, essentially macroscopic, properties from dynamical systems. [1][2][3][4][5][6][7] We will show that a similar approach allows one to extract mesoscopic properties from general complex networks, where the dynamical notion of "instability" is generally replaced by a corresponding probabilistic branching property. We will finally demonstrate how, upon a specification of the general method, we can cope with the presence of noise.…”
Section: Introductionmentioning
confidence: 99%