Attractor Networks: Hopfield Model Generalizations

Explores attractor networks, Hopfield model generalizations, and memory dynamics in computational neuroscience.

Explores synaptic plasticity, spike-timing models, and online memory learning challenges in computational neuroscience.

Explores the Stochastic Hopfield model, noisy neurons, firing probabilities, memory retrieval, and overlap equations in attractor networks.

Explores attractor networks, spiking neurons, memory data, and realistic networks in neural dynamics.

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.