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OpenNeuro.org Tutorials

OpenNeuro.org

This course consists of brief tutorials on OpenNeuro.org, a free and open platform for analyzing and sharing neuroimaging data. During this course, you will learn how to deal with your neuroscientific datasets using OpenNeuro.org for operations such as uploading and version control, as well as how to analyze and share your data. 

 

Digital Health for Mental Health

Krembil Centre for Neuroinformatics

As technological improvements continue to facilitate innovations in the mental health space, researchers and clinicians are faced with novel opportunities and challenges regarding study design, diagnoses, treatments, and follow-up care. This course includes a lecture outlining these new developments, as well as a workshop which introduces users to Synapse, an open-source platform for collaborative data analysis. 

 

FAIR neuroscience and EBRAINS tools for data sharing, analysis, and simulation

INCF

This workshop provides an opportunity to explore the advanced tools and techniques for data sharing, analysis, visualization, and simulation.

 

INCF Assembly 2022 - Training Day 1

INCF

This course contains sessions from the first day of INCF's Neuroinformatics Assembly 2022.

 

How to Use Allen Institute for Brain Science Resources

Allen Institute for Brain Science

This course features tutorials on how to use Allen atlases and digital brain atlasing tools, including operational and user features of the Allen Mouse Brain Atlas, as well as the Allen Institute's 3D viewing tool, Brain Explorer®.

 

Open Science Framework (OSF)

Center for Open Science

This course is intended to introduce researchers to the Open Science Framework (OSF). OSF is a free, open source web application built by the Center for Open Science, a non-profit dedicated to improving the alignment between scientific values and scientific practices. OSF is part collaboration tool, part version control software, and part data archive.

 

Simulating Brain Microcircuit Activity and Signals in Mental Health

Krembil Centre for Neuroinformatics

This course offers lectures on the origin and functional significance of certain electrophysiological signals in the brain, as well as a hands-on tutorial on how to simulate, statistically evaluate, and visualize such signals. Participants will learn the simulation of signals at different spatial scales, including single-cell (neuronal spiking) and global (EEG), and how these may serve as biomarkers in the evaluation of mental health data.

 
INCF TrainingSpace

Session 4: "Is This FAIR?": Transparency in EDI, Career Development, & Management

INCF

There is a growing recognition and adoption of open and FAIR science practices in neuroscience research. This is predominately regarded as scientific progress and has enabled significant opportunities for large, collaborative, team science. The efforts and practical work that go into creating an open and FAIR landscape extend far beyond just the science.

 

NeuroTools Webinar Series

Neuroscience Information Framework

Presented by the Neuroscience Information Framework (NIF), this series consists of several lectures characterizing cutting-edge, open-source software platforms and computational tools for neuroscientists. This course offers detailed descriptions of various neuroinformatic resources such as cloud-computing services, web-based annotation tools, genome browsers, and platforms for designing and building biophysically detailed models of neurons and neural ensembles.

 
INCF TrainingSpace

Session 7: Practical Guide to Overcome the Reproducibility Crisis in Small Animal Neuroimaging: Workflows, Tools, and Repositories

INCF

The workshop will include interactive seminars given by selected experts in the field covering all aspects of (FAIR) small animal MRI data acquisition, analysis, and sharing. The seminars will be followed by hands-on training where participants will perform use case scenarios using software established by the organizers. This will include an introduction to the basics of using command line interfaces, Python installation, working with Docker/Singularity containers, Datalad/Git, and BIDS.

 
INCF TrainingSpace

Session 9: Event Annotation in Neuroimaging Using HED: From Experiment to Analysis

INCF

This workshop delves into the need for, structure of, tools for, and use of hierarchical event descriptor (HED) annotation to prepare neuroimaging time series data for storing, sharing, and advanced analysis. HED are a controlled vocabulary of terms describing events in a machine-actionable form so that algorithms can use the information without manual recoding.

 

Current Methods in Neurotechnology

NeurotechEU

The lecture series focuses on current trends in modern techniques in neuroscience. Inspiring scientists from the NeurotechEU Alliance will give an overview of the latest advances and developments.

 

Reinforcement Learning

Neuromatch Academy

Neuromatch Academy aims to introduce traditional and emerging tools of computational neuroscience to trainees.

 

Neuroimaging Connectomics

Krembil Centre for Neuroinformatics

This course consists of one lesson and one tutorial, focusing on the neural connectivity measures derived from neuroimaging, specifically from methods like functional magnetic resonance imaging (fMRI) and diffusion-weighted imaging (DWI). Additional tools such as tractography and parcellation are discussed in the context of brain connectivity and mental health. The tutorial leads participants through the computation of brain connectomes from fMRI data. 

 

Versioning & Containerization

This course outlines how versioning code, data, and analysis software is crucially important to rigorous and open neuroscience workflows that maximize reproducibility and minimize errors.Version control systems, code-capable notebooks, and virtualization containers such as Git, Jupyter, and Docker, respectively, have become essential tools in data science.

 

Reproducible Science (Including Git, Docker, and Binder)

Krembil Centre for Neuroinformatics

This course consists of two workshops which focus on the need for reproducibility in science, particularly under the umbrella roadmap of FAIR scienctific principles. The tutorials also provide an introduction to some of the most commonly used open-source scientific tools, including Git, GitHub, Google Colab, Binder, Docker, and the programming languages Python and R. 

 

Population-Based Data Resources & Integrative Research Methods

Krembil Centre for Neuroinformatics

As research methods and experimental technologies become ever more sophisticated, the amount of health-related data per individual which has become accessible is vast, giving rise to a corresponding need for cross-domain data integration, whole-person modelling, and improved precision medicine. This course provides lessons describing state of the art methods and repositories, as well as a tutorial on computational methods for data integration. 

 

INCF Assembly 2022 - Training Day 2

INCF

This course contains sessions from the second day of INCF's Neuroinformatics Assembly 2022.

 
INCF TrainingSpace

Session 1: A FAIR Roadmap for Knowledge Graphs and Ontologies

INCF

This course corresponds to the first session of talks given at INCF's Neuroinformatics Assembly 2023. The sessions consists of several lectures, focusing on using the principles of FAIR (findability, accessibility, interoperability, and reusability) to inform future directions in neuroscience and neuroinformatics. In particular, these talks deal with the development of knowledge graphs and ontologies. 

 

Brain Medicine for Non-Specialists

HBP Education Programme

The human mind is a complex system that produces, processes, and transmits information in an incomparable manner. Human thoughts and actions depend profoundly on the proper function of neurons. If this function is disrupted, degeneration and disease can be the consequence. This course provides insights into state-of-the-art views on neurodegenerative, neuropsychiatric, and neuroimmunological disorders as well as clinical neuroanatomy and clinical aspects of brain imaging.