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Spiking neurons with short-term synaptic plasticity form superior generative networks

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Veröffentlicht in: Scientific reports 8(2018) Artikel-Nummer 10651, 11 Seiten
Personen und Körperschaften: Leng, Luziwei (VerfasserIn), Breitwieser, Oliver (VerfasserIn), Bytschok, Ilja (VerfasserIn), Schemmel, Johannes (VerfasserIn), Meier, Karlheinz (VerfasserIn), Petrovici, Mihai A. (VerfasserIn)
Titel: Spiking neurons with short-term synaptic plasticity form superior generative networks/ Luziwei Leng, Roman Martel, Oliver Breitwieser, Ilja Bytschok, Walter Senn, Johannes Schemmel, Karlheinz Meier & Mihai A. Petrovici
Format: E-Book-Kapitel
Sprache: Englisch
veröffentlicht:
13 July 2018
Gesamtaufnahme: : Scientific reports, 8(2018) Artikel-Nummer 10651, 11 Seiten
, volume:8
Quelle: Verbunddaten SWB
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Zusammenfassung: Spiking networks that perform probabilistic inference have been proposed both as models of cortical computation and as candidates for solving problems in machine learning. However, the evidence for spike-based computation being in any way superior to non-spiking alternatives remains scarce. We propose that short-term synaptic plasticity can provide spiking networks with distinct computational advantages compared to their classical counterparts. When learning from high-dimensional, diverse datasets, deep attractors in the energy landscape often cause mixing problems to the sampling process. Classical algorithms solve this problem by employing various tempering techniques, which are both computationally demanding and require global state updates. We demonstrate how similar results can be achieved in spiking networks endowed with local short-term synaptic plasticity. Additionally, we discuss how these networks can even outperform tempering-based approaches when the training data is imbalanced. We thereby uncover a powerful computational property of the biologically inspired, local, spike-triggered synaptic dynamics based simply on a limited pool of synaptic resources, which enables them to deal with complex sensory data.
Beschreibung: Gesehen am 31.07.2018
Umfang: 11
ISSN: 2045-2322
DOI: 10.1038/s41598-018-28999-2