ArticleBiological cybernetics2020
Spiking time-dependent plasticity leads to efficient coding of predictions.
Article in Biological cybernetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Spike Timing-Dependent Plasticity and Random Inputs Shape Interspike Interval Regularity of Model STN Neurons.Biomedicines · 2025Article
- Learning cortical hierarchies with temporal Hebbian updates.Frontiers in computational neuroscience · 2023Article
- Neural synchrony in cortical networks: mechanisms and implications for neural information processing and coding.Frontiers in integrative neuroscience · 2022Article
- Characterization of Generalizability of Spike Timing Dependent Plasticity Trained Spiking Neural Networks.Frontiers in neuroscience · 2021Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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