Cargando…
A Model of Fast Hebbian Spike Latency Normalization
Hebbian changes of excitatory synapses are driven by and enhance correlations between pre- and postsynaptic neuronal activations, forming a positive feedback loop that can lead to instability in simulated neural networks. Because Hebbian learning may occur on time scales of seconds to minutes, it is...
Autores principales: | Einarsson, Hafsteinn, Gauy, Marcelo M., Lengler, Johannes, Steger, Angelika |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5430963/ https://www.ncbi.nlm.nih.gov/pubmed/28555102 http://dx.doi.org/10.3389/fncom.2017.00033 |
Ejemplares similares
-
A Hippocampal Model for Behavioral Time Acquisition and Fast Bidirectional Replay of Spatio-Temporal Memory Sequences
por: Matheus Gauy, Marcelo, et al.
Publicado: (2018) -
A high-capacity model for one shot association learning in the brain
por: Einarsson, Hafsteinn, et al.
Publicado: (2014) -
Voltage dependence of synaptic plasticity is essential for rate based learning with short stimuli
por: Weissenberger, Felix, et al.
Publicado: (2018) -
Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks
por: Panda, Priyadarshini, et al.
Publicado: (2017) -
Non-Hebbian spike-timing-dependent plasticity in cerebellar circuits
por: Piochon, Claire, et al.
Publicado: (2013)