Spike-Threshold Adaptation Predicted by Membrane Potential Dynamics In Vivo

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Abstract

Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo. © 2014 Fontaine et al.

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Fontaine, B., Peña, J. L., & Brette, R. (2014). Spike-Threshold Adaptation Predicted by Membrane Potential Dynamics In Vivo. PLoS Computational Biology, 10(4). https://doi.org/10.1371/journal.pcbi.1003560

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