|Appears in Collections:||Computing Science and Mathematics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Phase changes in neuronal postsynaptic spiking due to short term plasticity|
|Author(s):||McDonnell, Mark D|
|Citation:||McDonnell MD & Graham B (2017) Phase changes in neuronal postsynaptic spiking due to short term plasticity. PLoS Computational Biology, 13 (9), Art. No.: e1005634. https://doi.org/10.1371/journal.pcbi.1005634.|
Balancing resource and energy usage for optimal performance in neural system
|Abstract:||In the brain, the postsynaptic response of a neuron to time-varying inputs is determined by the interaction of presynaptic spike times with the short-term dynamics of each synapse. For a neuron driven by stochastic synapses, synaptic depression results in a quite different postsynaptic response to a large population input depending on how correlated in time the spikes across individual synapses are. Here we show using both simulations and mathematical analysis that not only the rate but the phase of the postsynaptic response to a rhythmic population input varies as a function of synaptic dynamics and synaptic configuration. Resultant phase leads may compensate for transmission delays and be predictive of rhythmic changes. This could be particularly important for sensory processing and motor rhythm generation in the nervous system. © 2017 McDonnell, Graham.|
|Rights:||© 2017 McDonnell, Graham. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.|
|journal.pcbi.1005634.pdf||Fulltext - Published Version||5.89 MB||Adobe PDF||View/Open|
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