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This tutorial demonstrates how to extract the time course of calcium activity from each clusters of neuron somata, and store the data in a MATLAB matrix.

Difficulty level: Intermediate
Duration: 22:41
Speaker: : Mike X. Cohen

This lesson demonstrates how to use MATLAB to implement a multivariate dimension reduction method, PCA, on time series data.

Difficulty level: Intermediate
Duration: 17:19
Speaker: : Mike X. Cohen

This lesson describes the principles underlying functional magnetic resonance imaging (fMRI), diffusion-weighted imaging (DWI), tractography, and parcellation. These tools and concepts are explained in a broader context of neural connectivity and mental health. 

Difficulty level: Intermediate
Duration: 1:47:22

This tutorial walks participants through the application of dynamic causal modelling (DCM) to fMRI data using MATLAB. Participants are also shown various forms of DCM, how to generate and specify different models, and how to fit them to simulated neural and BOLD data.

 

This lesson corresponds to slides 158-187 of the PDF below. 

Difficulty level: Advanced
Duration: 1:22:10

This lesson explores how researchers try to understand neural networks, particularly in the case of observing neural activity. 

Difficulty level: Intermediate
Duration: 8:20
Speaker: : Marcus Ghosh

This lecture will provide an overview of neuroimaging techniques and their clinical applications.

Difficulty level: Beginner
Duration: 45:29
Speaker: : Dafna Ben Bashat

This lecture provides an introduction to the Brain Imaging Data Structure (BIDS), a standard for organizing human neuroimaging datasets.

Difficulty level: Intermediate
Duration: 56:49

In this lesson, you will learn about the Python project Nipype, an open-source, community-developed initiative under the umbrella of NiPy. Nipype provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a single workflow.

Difficulty level: Intermediate
Duration: 1:25:05
Speaker: : Satrajit Ghosh

This lecture covers the needs and challenges involved in creating a FAIR ecosystem for neuroimaging research.

Difficulty level: Beginner
Duration: 12:26
Speaker: : Camille Maumet

This lecture covers the NIDM data format within BIDS to make your datasets more searchable, and how to optimize your dataset searches.

Difficulty level: Beginner
Duration: 12:33
Speaker: : David Keator

This lecture covers the processes, benefits, and challenges involved in designing, collecting, and sharing FAIR neuroscience datasets.

Difficulty level: Beginner
Duration: 11:35

This lecture covers positron emission tomography (PET) imaging and the Brain Imaging Data Structure (BIDS), and how they work together within the PET-BIDS standard to make neuroscience more open and FAIR.

Difficulty level: Beginner
Duration: 12:06
Speaker: : Melanie Ganz

This lecture covers the benefits and difficulties involved when re-using open datasets, and how metadata is important to the process.

Difficulty level: Beginner
Duration: 11:20
Speaker: : Elizabeth DuPre

This lecture provides guidance on the ethical considerations the clinical neuroimaging community faces when applying the FAIR principles to their research. 

Difficulty level: Beginner
Duration: 13:11
Speaker: : Gustav Nilsonne

This lesson gives a description of the BrainHealth Databank, a repository of many types of health-related data, whose aim is to accelerate research, improve care, and to help better understand and diagnose mental illness, as well as develop new treatments and prevention strategies. 

 

This lesson corresponds to slides 46-78 of the PDF below. 

Difficulty level: Beginner
Duration: 1:12:25
Speaker: : Joanna Yu

This tutorial provides instruction on how to simulate brain tumors 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.

Difficulty level: Intermediate
Duration: 10:01

This lecture covers how to make modeling workflows FAIR by working through a practical example, dissecting the steps within the workflow, and detailing the tools and resources used at each step.

Difficulty level: Beginner
Duration: 15:14

This lecture focuses on the structured validation process within computational neuroscience, including the tools, services, and methods involved in simulation and analysis.

Difficulty level: Beginner
Duration: 14:19
Speaker: : Michael Denker

This lecture discusses the FAIR principles as they apply to electrophysiology data and metadata, the building blocks for community tools and standards, platforms and grassroots initiatives, and the challenges therein.

Difficulty level: Beginner
Duration: 8:11
Speaker: : Thomas Wachtler
Course:

This session provides users with an introduction to tools and resources that facilitate the implementation of FAIR in their research.

 

 

Difficulty level: Beginner
Duration: 38:36