Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks.
Roman PogodinDane S. CorneilAlexander SeeholzerJoseph HengWulfram GerstnerPublished in: CoRR (2019)
Keyphrases
- recurrent neural networks
- hebbian learning
- working memory
- cognitive load
- computational model
- focus of attention
- information processing
- cognitive architecture
- neural network
- long term memory
- feed forward
- working memory capacity
- individual differences
- reinforcement learning
- hidden layer
- echo state networks
- short term memory
- recurrent networks
- artificial neural networks
- prefrontal cortex
- neural network model
- decision making