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  Signatures of criticality in efficient coding networks

Safavi, S., Chalk, M., Logothetis, N., & Levina, A. (2019). Signatures of criticality in efficient coding networks. Poster presented at DPG-Frühjahrstagung 2019, Regensburg, Germany.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-964B-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-9654-5
Genre: Poster

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Safavi, S1, 2, Author              
Chalk, M, Author
Logothetis, NK1, 2, Author              
Levina, A1, 2, Author              
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Theoretical and experimental evidence brought forward a hypothesis that the brain operates close to a critical state. Numerous studies investigated neural models that can attain various distances to criticality depending on a control parameter and quantified information processing capabilities as a function of closeness to criticality. However, quantifying these capabilities in a general sense is not sufficient to assure usefulness of criticality for the brain. Therefore, we introduce a complementary approach. We study a network that is optimized for a task relevant for the brain. Then, we investigate whether we observe the scale-free neuronal avalanches exclusively in the optimized network. More specifically, we used a network of leaky integrate-and-fire neurons with parameters optimized for efficient coding. Previously, it was shown that performance of such networks varies non-monotonically with the noise amplitude. We discovered, that only in the network with optimal noise level the avalanche size distribution follows a power-law and with too low or too high noise, the network appears either super-critical or sub-critical, respectively. We demonstrate that scale-free distribution of neuronal avalanches might be a consequence of optimal efficient coding in spiking neural networks. This result has important implications, as it shows how two influential, and previously disparate fields - efficient coding, and criticality - might be intimately related.

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 Dates: 2019-04
 Publication Status: Published online
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Title: DPG-Frühjahrstagung 2019
Place of Event: Regensburg, Germany
Start-/End Date: 2019-03-31 - 2019-04-05

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Title: DPG-Frühjahrstagung 2019
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: BP 12.52 Start / End Page: - Identifier: -