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Spike-Threshold Adaptation Predicted by Membrane Potential Dynamics In Vivo
Author(s) -
Bertrand Fontaine,
José Luis Peña,
Romain Brette
Publication year - 2014
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1003560
Subject(s) - membrane potential , adaptation (eye) , millisecond , biological system , neuroscience , threshold model , spike (software development) , threshold voltage , biophysics , physics , biology , computer science , voltage , software engineering , astronomy , machine learning , transistor , quantum mechanics
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 .

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