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

This lecture covers modeling the neuron in silicon, modeling vision and audition and sensory fusion using a deep network. 

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.

A basic introduction to clinical presentation of schizophrenia, its etiology, and current treatment options.

How genetics can contribute to our understanding of psychiatric phenotypes.

An overview of some of the essential concepts in neuropharmacology (e.g. receptor binding, agonism, antagonism), an introduction to pharmacodynamics and pharmacokinetics, and an overview of the drug discovery process relative to diseases of the Central Nervous System.

2nd part of the lecture. Introduction to cell receptors and signalling cascades

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

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.

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

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