This lesson covers the history of neuroscience and machine learning, and the story of how these two seemingly disparate fields are increasingly merging. 

In this lesson, you will learn about the current challenges facing the integration of machine learning and neuroscience. 

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 will highlight our current understanding and recent developments in the field of neurodegenerative disease research, as well as the future of diagnostics and treatment of neurodegenerative diseases.

This lecture continues from part one (previous lesson), highlighting our current understanding and recent developments in the field of neurodegenerative disease research, as well as the future of diagnostics and treatment of neurodegenerative diseases.

This lecture picks up from the previous lesson, providing an overview of neuroimaging techniques and their clinical applications.

This lesson provides a basic introduction to clinical presentation of schizophrenia, its etiology, and current treatment options.

This lecture focuses on the rationale for employing neuroimaging methods for movement disorders.

This lesson covers 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.

This lesson discuses forms of neural plasticity on many levels, including short-term, long-term, metaplasticity, and structural plasticity. During the lesson you will also be presented with examples related to the modelling of biochemical networks. 

This lesson provides an introduction to modelling of chemical computation in the brain.

This lesson is part 1 of 2 of a tutorial on statistical models for neural data.

This lesson is part 2 of 2 of a tutorial on statistical models for neural data.

This lesson gives an introduction to simple spiking neuron models.

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

This lesson provides an introduction to the myriad forms of cellular mechanisms whicn underpin healthy brain function and communication. 

This lecture describes forms of plasticity on many levels: short-term, long-term, metaplasticity, and structural plasticity. Included in this lecture are also examples related to modelling of biochemical networks.

This lesson provides an introduction to modelling of chemical computation in the brain.