This lecture presents two recent clinical case studies using TVB: stroke recovery and dementia (due to Alzheimer’s Disease (AD)). Using a multi-scale neurophysiological model based on empirical multi-modal neuroimaging data, we show how local and global biophysical parameters characterize changes in  individualized patient-specific brain dynamics, predict recovery of motor function for stroke patients, and correlate with individual differences in cognition for AD patients.

Tutorial on how to simulate brain tumor brains with TVB (reproducing publication: Marinazzo et al. 2020 Neuroimage). This tutorial comprises a didactic video, jupyter notebooks, and full data set for the construction of virtual brains from patients and health controls. Authors: Hannelore Aerts, Michael Schirner, Ben Jeurissen, DIrk Van Roost, Eric Achten, Petra Ritter, Daniele Marinazzo

The tutorial comprises a didactic video and jupyter notebooks (reproducing publication: Falcon et al. 2016 eNeuro). Contributors: Daniele Marinazzo, Petra Ritter, Paul Triebkorn, Ana Solodkin

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.

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.

This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and go through both motivation and process involved in moving your research computing to the cloud. 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 importing and creating brain models in The Virtual Brain by Patrik Bey is part of the TVB Node 10 series, a 4 day workshop dedicated to learning about The Virtual Brain, brain imaging, brain simulation, personalised brain models, TVB use cases, etc... TVB is a full brain simulation platform.

This tutorial by Paul Triebkorn on how to simulate using TVB is part of the TVB Node 10 series, a 4 day workshop dedicated to learning about The Virtual Brain, brain imaging, brain simulation, personalised brain models, TVB use cases, etc. TVB is a full brain simulation platform.

This tutorial on simulating The Virutal Mouse Brain by Patrik Bey is part of the TVB Node 10 series, a 4 day workshop dedicated to learning about The Virtual Brain, brain imaging, brain simulation, personalised brain models, TVB use cases, etc... TVB is a full brain simulation platform.

This tutorlal on modeling a virtual macaque brain by Julie Courtiol is part of the TVB Node 10 series, a 4 day workshop dedicated to learning about The Virtual Brain, brain imaging, brain simulation, personalised brain models, TVB use cases, etc. TVB is a full brain simulation platform.

This lecture on multi-scale entropy by Jil Meier is part of the TVB Node 10 series, a 4 day workshop dedicated to learning about The Virtual Brain, brain imaging, brain simulation, personalised brain models, TVB use cases, etc. TVB is a full brain simulation platform.

This lecture on generating 3D brain model outside The Virtual Brain by Michael Schirner is part of the TVB Node 10 series, a 4 day workshop dedicated to learning about The Virtual Brain, brain imaging, brain simulation, personalised brain models, TVB use cases, etc... TVB is a full brain simulation platform.

An overview of the Bayesian Virtual Epileptic Patient (BVEP), a research use case using TVB supported on the EBRAINS infrastructure.

This Jupyter Book is a series of interactive tutorials about quantitative T1 mapping, powered by qMRLab. Most figures are generated with Plot.ly – you can play with them by hovering your mouse over the data, zooming in (click and drag) and out (double click), moving the sliders, and changing the drop-down options. To view the code that was used to generate the figures in this blog post, hover your cursor in the top left corner of the frame that contains the tutorial and click the checkbox “All cells” in the popup that appears.

Jupyter Lab notebooks of these tutorials are also available through MyBinder, and inline code modification inside the Jupyter Book is provided by Thebelab. For both options, you can modify the code, change the figures, and regenerate the html that was used to create the tutorial below. This Jupyter Book also uses a Script of Scripts (SoS) kernel, allowing us to process the data using qMRLab in MATLAB/Octave and plot the figures with Plot.ly using Python, all within the same Jupyter Notebook.