Topic: generative adversarial networks

Understanding synaptic plasticity is critical for elucidating mechanisms for neural development, learning and memory consolidation. Synaptic plasticity is modelled by simulating the activity of interacting neural populations, using hypothesized functions (plasticity rules) that modify the connections between neurons. Plasticity rules are typically hand-crafted from single-synapse experiment data, but have shown limited success in understanding network-level properties. Recent studies aim to discover rules using supervised learning rather than hand-crafting them. However, these approaches stil