2015
Enforcing balance allows local supervised learning in spiking recurrent networks
NeurIPS 2015poster
To predict sensory inputs or control motor trajectories, the brain must constantly learn temporal dynamics based on error feedback. However, it remains unclear how such supervised learning is implemented in biological neural networks. Learning in recurrent spiking networks is notoriously difficult b…