Cargando…
Hebbian Crosstalk Prevents Nonlinear Unsupervised Learning
Learning is thought to occur by localized, activity-induced changes in the strength of synaptic connections between neurons. Recent work has shown that induction of change at one connection can affect changes at others (“crosstalk”). We studied the role of such crosstalk in nonlinear Hebbian learnin...
Autores principales: | Cox, Kingsley J. A., Adams, Paul R. |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Frontiers Research Foundation
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759358/ https://www.ncbi.nlm.nih.gov/pubmed/19826612 http://dx.doi.org/10.3389/neuro.10.011.2009 |
Ejemplares similares
-
Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks
por: Panda, Priyadarshini, et al.
Publicado: (2017) -
Unsupervised Hebbian learning experimentally realized with analogue memristive crossbar arrays
por: Hansen, Mirko, et al.
Publicado: (2018) -
Voltage-dependent synaptic plasticity: Unsupervised probabilistic Hebbian plasticity rule based on neurons membrane potential
por: Garg, Nikhil, et al.
Publicado: (2022) -
Deep Learning With Asymmetric Connections and Hebbian Updates
por: Amit, Yali
Publicado: (2019) -
Learning cortical hierarchies with temporal Hebbian updates
por: Aceituno, Pau Vilimelis, et al.
Publicado: (2023)