Delves into simulating network dynamics in in silico neuroscience, covering spontaneous and evoked activity, in-vitro and in-vivo simulations, and sensitivity analysis.
Explores networks of spiking neurons, mean-field models, transfer functions, and predictions of state space and neuron behavior.
Explores controlling behavior in animals and robots, covering historical perspectives, neuron activation, Drosophila model, advanced techniques, and mini-project organization.
Explores analog-to-digital conversion, neural signal optimization, multichannel architectures, and on-chip compression techniques in neuroengineering.
