Spiking time-dependent plasticity leads to efficient coding of predictions. Academic Article

abstract

• Latency reduction in postsynaptic spikes is a well-known effect of spiking time-dependent plasticity. We expand this notion for long postsynaptic spike trains on single neurons, showing that, for a fixed input spike train, STDP reduces the number of postsynaptic spikes and concentrates the remaining ones. Then, we study the consequences of this phenomena in terms of coding, finding that this mechanism improves the neural code by increasing the signal-to-noise ratio and lowering the metabolic costs of frequent stimuli. Finally, we illustrate that the reduction in postsynaptic latencies can lead to the emergence of predictions.

authors

• Ehsani, Mehrdad

published proceedings

• Biol Cybern

altmetric score

• 0.75

author list (cited authors)

• Vilimelis Aceituno, P., Ehsani, M., & Jost, J.

citation count

• 2

complete list of authors

• Vilimelis Aceituno, Pau||Ehsani, Masud||Jost, Jürgen

publication date

• February 2020

publisher

• Springer Nature  Publisher

published in

• Biological Cybernetics: communication and control in organisms and automata  Journal

keywords

• Action Potentials
• Animals
• Forecasting
• Humans
• Models, Neurological
• Neural Adaptation
• Neural Code
• Neuronal Plasticity
• Neurons
• Predictions
• Spiking Time-dependent Plasticity
• Synchronization

PubMed Central ID

• 31873797

Digital Object Identifier (DOI)

• 10.1007/s00422-019-00813-w

start page

• 43

end page

• 61

volume

• 114

issue

• 1

URL

• http://dx.doi.org/10.1007/s00422-019-00813-w