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  When less is more: Non-monotonic spike sequence processing in neurons.

Arnoldt, H., Chang, S., Jahnke, S., Urmersbach, B., Taschenberger, H., & Timme, M. (2015). When less is more: Non-monotonic spike sequence processing in neurons. PLOS Computational Biology, 11(2): e1004002. doi:10.1371/journal.pcbi.1004002.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0026-C662-F Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0027-CD15-C
Genre: Journal Article

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Arnoldt, H., Author
Chang, S.1, Author              
Jahnke, S., Author
Urmersbach, B., Author
Taschenberger, H.1, Author              
Timme, M., Author
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1Research Group of Activity-Dependent and Developmental Plasticity at the Calyx of Held, MPI for biophysical chemistry, Max Planck Society, ou_578581              

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 Abstract: Fundamental response properties of neurons centrally underly the computational capabilities of both individual nerve cells and neural networks. Most studies on neuronal input-output relations have focused on continuous-time inputs such as constant or noisy sinusoidal currents. Yet, most neurons communicate via exchanging action potentials (spikes) at discrete times. Here, we systematically analyze the stationary spiking response to regular spiking inputs and reveal that it is generically non-monotonic. Our theoretical analysis shows that the underlying mechanism relies solely on a combination of the discrete nature of the communication by spikes, the capability of locking output to input spikes and limited resources required for spike processing. Numerical simulations of mathematically idealized and biophysically detailed models, as well as neurophysiological experiments confirm and illustrate our theoretical predictions.

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Language(s): eng - English
 Dates: 2015-02-03
 Publication Status: Published online
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 Rev. Method: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1004002
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Title: PLOS Computational Biology
Source Genre: Journal
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Pages: 15 Volume / Issue: 11 (2) Sequence Number: e1004002 Start / End Page: - Identifier: -