This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

This lecture provides an introduction to the study of eye-tracking in humans. 

This lecture covers the linking neuronal activity to behavior using AI-based online detection. 

This lecture presents the Medical Informatics Platform's data federation in epilepsy.

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 neuroinformatics and its subfields, the content of the short course and future neuroinformatics applications.

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 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.

2nd part of the lecture. 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 will provide an overview of neuroimaging techniques and their clinical applications

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