This lecture covers an introduction to neuroinformatics and its subfields, the content of the short course and future neuroinformatics applications.

This lecture gives an introduction to simulation, models, and the neural simulation tool NEST. 

This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.

This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.

The ionic basis of the action potential, including the Hodgkin Huxley model. 

This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.

Forms of plasticity on many levels - short-term, long-term, metaplasticity, structural plasticity. With examples related to modelling of biochemical networks. 

[NB: The sound uptake is a bit noisy the first few minutes, but gets better from about 5 mins in]

Introduction to modelling of chemical computation in the brain

Conference presentation on computationally demanding studies of synaptic plasticity on the molecular level

Part 1 of 2 of a tutorial on statistical models for neural data

Part 2 of 2 of a tutorial on statistical models for neural data.

Introduction to simple spiking neuron models.

This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.

Introduction to the course Cellular Mechanisms of Brain Function.

Forms of plasticity on many levels - short-term, long-term, metaplasticity, structural plasticity. With examples related to modelling of biochemical networks. 

[NB: The sound uptake is a bit noisy the first few minutes, but gets better from about 5 mins in]

Introduction to modelling of chemical computation in the brain

Conference presentation on computationally demanding studies of synaptic plasticity on the molecular level

Introduction to the role of models in theoretical neuroscience

Different types of models, model complexity, and how to choose an appropriate model.

Balanced E-I networks, stability and gain modulation