Lehrinhalte
This module provides basic knowledge about the constituents of neural systems and their modeling, which includes basic neurobiological concepts and models concerning information processing within neurons and neural circuitry. Specific topics addressed are:
- Electrical properties of neurons (Nernst equation, Goldman equation, Goldman-Hodgkin-Katz current equation, membrane equation)
- Hodgkin-Huxley model (voltage-dependent conductances, gating variables, transient and persistent conductances, action-potential generation)
- Channel models (state diagram, stochastic dynamics)
- Synapse models (chemical and electrical synapses)
- Single-compartment neuron models (integrate-and-fire, conductance-based)
- Models of dendrites and axons (cable theory, Rall model, multi-compartment models, action-potential propagation)
- Models of synaptic plasticity and learning (release probability, short-term depression and facilitation, long-term plasticity, Hebbian rule, timing-based plasticity rules, supervised/unsupervised and reinforcement learning)
- Network models (feedforward and recurrent, excitatory-inhibitory, firing-rate and stochastic, associative memory)
- Phase-space analysis of neuron and network models (linear stability analysis, phase portraits, bifurcation theory
