Here are all the sub-topics within the Neuron chapter, collected in one place for easy browsing. These may or may not be optional for a given course, depending on the instructor's specifications of what to read:
- Neuron Biology -- more detailed description of neuron biology.
- Neuron Electrophysiology -- more detailed description of the electrophysiology of the neuron, and how the underlying concentration gradients of ions give rise to the electrical integration properties of the neuron.
- Net Input Detail -- details on how net inputs are computed across multiple different input projections.
- Adaptive Exponential Spiking Model -- the AdEx model has won multiple competitions for best fitting actual cortical neuron firing patterns, and is what we actually use in spiking mode output.
- Temporal Dynamics -- longer time-scale temporal dynamics of neurons (adaptation and hysteresis currents, and synaptic depression).
- Sigmoidal Unit Activation Function -- a more abstract formalism for simulating the behavior of neurons, used in more abstract neural network models (e.g., backpropagation models).
- Bayesian Optimal Detector -- how the equilibrium membrane potential represents a Bayesian optimal way of integrating the different inputs to the neuron.