The Virtual Brain is an open-source, multi-scale, multi-modal brain simulation platform. In this lesson, you get introduced to brain simulation in general and to The Virtual brain in particular. Prof. Ritter will present the newest approaches for clinical applications of The Virtual brain - that is, for stroke, epilepsy, brain tumors and Alzheimer’s disease - and show how brain simulation can improve diagnostics, therapy and understanding of neurological disease.
The concept of neural masses, an application of mean field theory, is introduced as a possible surrogate for electrophysiological signals in brain simulation. The mathematics of neural mass models and their integration to a coupled network are explained. Bifurcation analysis is presented as an important technique in the understanding of non-linear systems and as a fundamental method in the design of brain simulations. Finally, the application of the described mathematics is demonstrated in the exploration of brain stimulation regimes.
The simulation of the virtual epileptic patient is presented as an example of advanced brain simulation as a translational approach to deliver improved results in clinics. The fundamentals of epilepsy are explained. On this basis, the concept of epilepsy simulation is developed. By using an iPython notebook, the detailed process of this approach is explained step by step. In the end, you are able to perform simple epilepsy simulations your own.
The practical usage of The Virtual brain in its graphical user interface and via python scripts is introduced. In the graphical user interface, you are guided through its data repository, simulator, phase plane exploration tool, connectivity editor, stimulus generator and the provided analyses. The implemented iPython notebooks of TVB are presented, and since they are public, can be used for further exploration of The Virtual brain.
A brief overview of the Python programming language, with an emphasis on tools relevant to data scientists. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.
Tutorial on collaborating with Git and GitHub. This tutorial was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.
Colt Steele provides a comprehensive introduction to the command line and 50 popular Linux commands. This is a long course (nearly 5 hours) but well worth it if you are going to spend a good part of your career working from a terminal, which is likely if you are interested in flexibility, power, and reproducibility in neuroscience research.
This lesson is courtesy of freeCodeCamp.
This lecture and tutorial focuses on measuring human functional brain networks. The lecture and tutorial were part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.
Neuronify is an educational tool meant to create intuition for how neurons and neural networks behave. You can use it to combine neurons with different connections, just like the ones we have in our brain, and explore how changes on single cells lead to behavioral changes in important networks. Neuronify is based on an integrate-and-fire model of neurons. This is one of the simplest models of neurons that exist. It focuses on the spike timing of a neuron and ignores the details of the action potential dynamics. These neurons are modeled as simple RC circuits. When the membrane potential is above a certain threshold, a spike is generated and the voltage is reset to its resting potential. This spike then signals other neurons through its synapses.
Neuronify aims to provide a low entry point to simulation-based neuroscience.
In this presentation by the OHBM OpenScienceSIG, Tom Shaw and Steffen Bollmann cover how containers can be useful for running the same software on different platforms and sharing analysis pipelines with other researchers. They demonstrate how to build docker containers from scratch, using Neurodocker, and cover how to use containers on an HPC with singularity.
This lecture focuses on how the immune system can target and attack the nervous system to produce autoimmune responses that may result in diseases such as multiple sclerosis, neuromyelitis and lupus cerebritis manifested by motor, sensory, and cognitive impairments. Despite the fact that the brain is an immune-privileged site, autoreactive lymphocytes producing proinflammatory cytokines can cause active brain inflammation, leading to myelin and axonal loss.
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 provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.
How genetics can contribute to our understanding of psychiatric phenotypes.
The lecture focuses on rationale for employing neuroimaging methods for movement disorders
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.