Phase changes in neuronal postsynaptic spiking due to short term plasticity

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...

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Bibliographic Details
Published in:PLoS computational biology 2017-09, Vol.13 (9), p.e1005634-e1005634
Main Authors: McDonnell, Mark D, Graham, Bruce P
Format: Article
Language:English
Subjects:
Action Potentials - physiology
Animals
Biology and Life Sciences
Brain
Brain research
Computational Biology
Computer simulation
Firing pattern
Information processing
Mathematical analysis
Medicine and Health Sciences
Models, Neurological
Nervous system
Neural circuitry
Neuronal Plasticity - physiology
Neurons
Neuroplasticity
Neurosciences
Observations
Phase transitions
Physical Sciences
Physiological aspects
Physiology
Research and Analysis Methods
Rhythms
Scholarships & fellowships
Sensory integration
Stochasticity
Synapses
Synaptic depression
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Summary: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.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1005634