Cargando…
E-I balance emerges naturally from continuous Hebbian learning in autonomous neural networks
Spontaneous brain activity is characterized in part by a balanced asynchronous chaotic state. Cortical recordings show that excitatory (E) and inhibitory (I) drivings in the E-I balanced state are substantially larger than the overall input. We show that such a state arises naturally in fully adapti...
Autores principales: | Trapp, Philip, Echeveste, Rodrigo, Gros, Claudius |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997746/ https://www.ncbi.nlm.nih.gov/pubmed/29895972 http://dx.doi.org/10.1038/s41598-018-27099-5 |
Ejemplares similares
-
Should Hebbian learning be selective for negative excess kurtosis?
por: Gros, Claudius, et al.
Publicado: (2015) -
Drifting States and Synchronization Induced Chaos in Autonomous Networks of Excitable Neurons
por: Echeveste, Rodrigo, et al.
Publicado: (2016) -
A simple effective model for STDP: from spike pairs and triplets to rate-encoding plasticity
por: Echeveste, Rodrigo, et al.
Publicado: (2015) -
Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks
por: Panda, Priyadarshini, et al.
Publicado: (2017) -
Hebbian learning of context in recurrent neural networks
por: Brunnel, N
Publicado: (1995)