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.

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.

Introduction to the types of glial cells, homeostasis (influence of cerebral blood flow and influence on neurons), insulation and protection of axons (myelin sheath; nodes of Ranvier), microglia and reactions of the CNS to injury.

Introduction to the principal of anatomical organization of neural systems in the human brain and spinal cord that mediate sensation, integrate signals, and motivate behavior.

This lecture focuses on the comprehension of nociception and pain sensation. It highlights how the somatosensory system and different molecular partners are involved in nociception and how nociception and pain sensation are studied in rodents and humans and the development of pain therapy.

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

Methods for dimensionality reduction of data, with focus on factor analysis.

Methods for dimensionality reduction of data, with focus on factor analysis.