Hardware for computing for non-ICT specialists
This lecture provides a history of data management, recent developments data management, and a brief description of scientific data management.
Computer arithmetic is necessarily performed using approximations to the real numbers they are intended to represent, and consequently it is possible for the discrepancies between the actual solution and the approximate solutions to diverge, i.e. to become increasingly different. This lecture focuses on how this happens and techniques for reducing the effects of these phenomena and discuss systems which are chaotic.
This lecture will addresses what it means for a problem to have a computable solution, methods for combining computability results to analyse more complicated problems, and finally look in detail at one particular problem which has no computable solution: the halting problem.
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 approximation to the computational resource required to perform a task. Methods to analyse a computer program and to perform the approximation are presented. Speaker: David Lester.
This lecture covers an introduction to connectomics, and image processing tools for the study of connectomics.
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 covers acquisition techniques, the physics of MRI, diffusion imaging, prediction using fMRI.
This lecture covers structured data, databases, federating neuroscience-relevant databases, ontologies.
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
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 the course Cellular Mechanisms of Brain Function.