Amanote Research

Amanote Research

  • Register
  • Sign In

E-I Balance Emerges Naturally From Continuous Hebbian Learning in Autonomous Neural Networks

Scientific Reports- United Kingdom

doi 10.1038/s41598-018-27099-5

Full Text

Abstract

Available in

Categories

Multidisciplinary

Date

June 12, 2018

Authors

Philip TrappRodrigo EchevesteClaudius Gros

Publisher

Springer Science and Business Media LLC


Related search

Hebbian Cross-Correlation Learning Emerges as Spike Timing Dependent Plasticity

BMC Neuroscience
NeuroscienceCellularMolecular Neuroscience
2011English

Learning to Generate Sequences With Combination of Hebbian and Non-Hebbian Plasticity in Recurrent Spiking Neural Networks

Frontiers in Neuroscience
Neuroscience
2017English

Biologically-Inspired Spiking Neural Networks With Hebbian Learning for Vision Processing

2008English

Realtime-Learning on an Autonomous Mobile Robot With Neural Networks

English

Predictive Hebbian Learning

1995English

Stable Hebbian Learning From Spike Timing-Dependent Plasticity

Journal of Neuroscience
Neuroscience
2000English

Self-Optimization in Continuous-Time Recurrent Neural Networks

Frontiers Robotics AI
Computer Science ApplicationsArtificial Intelligence
2018English

Neural Development of Binaural Tuning Through Hebbian Learning Predicts Frequency-Dependent Best Delays

Journal of Neuroscience
Neuroscience
2011English

Learning for Recurrent Neural Networks

Journal of Japan Society for Fuzzy Theory and Systems
1995English

Amanote Research

Note-taking for researchers

Follow Amanote


© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy