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

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

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

This lecture covers an introduction to connectomics, and image processing tools for the study of connectomics. 

This lecture covers acquisition techniques, the physics of MRI, diffusion imaging, prediction using fMRI. 

This lecture covers describing and characterizing an input-output relationship.

This lecture covers structured data, databases, federating neuroscience-relevant databases, ontologies. 

This lecture provides a history of data management, recent developments data management, and a brief description of scientific data management.…

Lecture on the most important concepts in software engineering

This lecture focuses on computational complexity which lies at the heart of computer science thinking. In short, it is a way to quickly gauge an…

This lecture will addresses what it means for a problem to have a computable solution, methods for combining computability results to analyse more…