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

MPS-Authors
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Chang,  S.
Research Group of Activity-Dependent and Developmental Plasticity at the Calyx of Held, MPI for biophysical chemistry, Max Planck Society;

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Taschenberger,  H.
Research Group of Activity-Dependent and Developmental Plasticity at the Calyx of Held, MPI for biophysical chemistry, Max Planck Society;

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Citation

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.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0026-C662-F
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.