Discusses three definitions of rate code in computational neuroscience, emphasizing temporal averaging, interspike intervals, and FANO factor.
Explores the mechanical and electrical properties of neural tissues, including the brain and spinal cord, as well as the recording of neural signals using various techniques.
Explores different types of noise in devices and circuits, including interference noise, inherent noise, and random signals.
Compares rate codes and temporal codes in neural dynamics, emphasizing timing codes, stochastic resonance, and neural coding challenges.
Covers the Spike Response Model (SRM) in computational neuroscience and its relation to the adaptive leaky integrate-and-fire model.
Explores electronic, thermomechanical, and amplifier noise, calibration of amplitude, frequency tracking, and system limits.
Explores the organization of the nervous system, including neuron structure, synapses, neurotransmitters, and neural circuits.
Compares diffusive noise and escape noise models in computational neuroscience, discussing simulation, calculation, and model fitting.
