Neuroinformatics Reproducibility for Everyone

• reproducibility
• data reuse

This workshop will introduce reproducible workflows and a range of tools along the themes of organisation, documentation, analysis, and dissemination. After a brief introduction to the topic of reproducibility, the workshop will provide specific tips and tools useful in improving daily research workflows. The content will include modules such as data management, electronic lab notebooks, reproducible bioinformatics tools and methods, protocol and reagent sharing, data visualisation, and version control. All modules include interactive learning, real-time participation, and active knowledge sharing. The methods and tools introduced help researchers share work with their future self, their immediate colleagues, and the wider scientific community.

• Apply a conceptual framework for reproducibility, replicability, and robustness of research.
• Explore practical, accessible tools and methods for advancing the reproducibility of research.
• Reuse and adapt the Reproducibility for Everyone modular curriculum to their own training and research needs.
• Evaluate their reproducibility barriers and solutions through interactive knowledge sharing.

Every R4E workshop is customised for the audience. This workshop is for neuroinformatics students, postdoctoral scholars, and any active researchers. It is designed for participants without any prior knowledge of either the concepts or methods of reproducibility. This workshop introduces this curriculum to attendees, initiating them into the landscape of research data management, open research, and reproducible methods.

Fully transparent ERP & MRI study methodology descriptions with ARTEM-IS and eCOBIDAS

• MRI
• MEG
• eye tracking
• PET
• EEG

Accurate reporting is critical for transparent, reproducible, replicable, FAIR-compliant research in the scientific record, and allows advanced forms of meta-science to be conducted. Two recent initiatives that address this challenge are ARTEM-IS and eCOBIDAS. Both are community collaborations that aim to design tools that facilitate detailed methodology documentation in neuroscience. These projects engage in broad consultation to maximise ease of use, clarity and specificity in the tools.

• Walk users through the ARTEM-IS template for documenting an ERP study, and eCOBIDAS web-app for documenting an MRI study, in two parallel sessions.

Users are expected to bring a study that they would like to document. Ideally, but not necessarily it would be their own study.

BIDS Annotations, NIDM, and Query Across Datasets

• MRI
• tool

This workshop will focus on teaching researchers how to annotate BIDS datasets to make them more findable and reusable. We will identify some sample BIDS datasets and attendees will learn how to create un-ambiguous data dictionaries (JSON sidecar files) for BIDS formatted datasets using the latest tools from the NIDM and ReproNim efforts. Attendees will then learn how to query across the sample BIDS datasets using concept annotations created during the annotation portion of the training. Attendees will be taught how to use the query tools developed for NIDM by ReproNim while also being taught the core NIDM model and how to write their own queries. Attendees will then be introduced to NIDM tools allowing them to learn relationships between variables contained within the sample BIDS datasets using simple linear regression and how these derived data can be described using the BIDS-Prov extension. At the completion of this workshop attendees should be able to create their own BIDS annotation files using multiple tools, query within their BIDS dataset or across multiple BIDS datasets, and understand the current state of derived data provenance in BIDS and NIDM.

Event and condition annotation of BIDS data using HED – from start to finish

• EEG
• tool

Hierarchical Event Descriptors (HED) fill a major gap in the neuroinformatics standards toolkit, namely the specification of the nature(s) of events and time-limited conditions recorded as having occurred during time series recordings (EEG, MEG, iEEG, fMRI, etc.).

We, the HED Working Group, propose a half-day online INCF workshop on the need for, structure of, tools for, and use of HED annotation to prepare neuroimaging time series data for storing, sharing, and advanced analysis.

• Documenting temporal structure in time series data (evolving concepts, history, needs and benefits)
• Annotating a BIDS dataset from start to finish
• Adding annotations to EEG data using the HED tools ecosystem
• Using the SCORE HED library schema for clinical EEG data annotation
• Applying HED annotation to fMRI datasets

Enabling multi-scale data integration: Turning data to knowledge

• FAIR data managment
• standards
• BIDS
• metadata
• workflows
• provenance

The workshop is organized by the German National Research Data Infrastructure Initiative Neuroscience (NFDI-Neuro). The initiative is community driven and comprises ca. 50 contributing national partners and collaborates. NFDI-Neuro partners with EBRAINS AISB, the coordinating entity of the EU Human Brain Project and the EBRAINS infrastructure. We will introduce common methods that enable digital reproducible Neuroscience. Each class of research data management method is first introduced conceptually - followed by a practical hands-on session. For hands-on sessions we will use the Collaboratory by EBRAINS as a joint digital workspace providing a range of functionalities including compute and storage resources.

• Why is multilevel data integration important?
• Introduction to data structure standards
• Introduction to metadata schemas
• Introduction to EBRAINS Knowledge Graph for data discovery
• Introduction to reproducible digital workflows
• Introduction to provenance tracking

NWB User Training Tutorial

• standards
• NWB
• neurophysiology

This training will cover the basics of Neurodata Without Borders (NWB), a data standard for neurophysiology data designed to maximize reusability of the data. We will demonstrate converting experiment data to NWB in Python and publishing on the DANDI Archive. Then we will give a tour of the available training resources for automated conversion from proprietary formats, and for building and publishing extensions. We will conclude with a Q+A section to help users with specific conversion questions.

Neuroscience data integration through use of digital brain atlases - Level: PhD, Credits: 2

• brain atlas
• data

Understanding how the brain works is one of the grand challenges in science and requires the integration of huge amounts of heterogeneous and complex data. Numerous research publications present experimental data at various levels of granularity and describe a wide range of structural and functional aspects of the brain. The management of this deluge of data represents a bottleneck for progress, with a main challenge being that the multiple data categories are difficult to compare. In this context, reference atlases of the brain are important tools for assigning anatomical location and (semi-)automatically analyzing data captured with the many methods and instruments used to study the brain. Reference atlases for the brain rank among the most frequently used and highest cited publications in neuroscience. But integration of data through the use of conventional reference atlases has been difficult to achieve.

With a new generation of three-dimensional digital reference atlases, new solutions for integrating and disseminating brain data are being developed. In many ways, future digital reference atlases and the data systems that will be built around them will be similar to current geographical atlases, such as Google Maps and Google Earth, which provide interactive access to huge amounts of high resolution image data, together with additional information (annotations, practical information, photographs) and more detailed visualizations (e.g. "street view") for specific areas. Digital brain atlases play an important role in several large international projects, including the European Union ICT Future Emerging Technologies Flagship project, the Human Brain Project.This course contains an introduction to currently available reference atlases for mouse and rat brain. It will demonstrate how the 3D brain templates for the reference atlases are acquired, how they are used as a basis for delineating the structures of the brain, how they can be enriched by other data modalities, and how they can be used as a basis for assigning location (coordinate based or semantic) to a wide range of structural and functional data collected from the brain. The course will also outline examples of data system employed to organize neuroscience data collections in the context of reference atlases as well as analytical workflows applied to the data, with opportunities for hands-on exploration of selected tools.

Read more about how digital brain atlases are used in the EBRAINS infrastructure at https://ebrains.eu/services/atlases

Registration

• The course is open for up to 40 participants.
• Register to the course using the following form: https://nettskjema.no/a/263372
• PhD candidates admitted to a PhD programme at UiO who wish to obtain 2 study credits can sign up via StudentWeb
• Applicants not admitted to a PhD programme at UiO who wish to obtain 2 study credits must apply for a right to study (see link) using this form: https://nettskjema.uio.no/answer/79776.html

Schedule
The course will be arranged on Thursday September 15 and Friday September 16, 2022, as a digital Satellite event to the 2022 INCF Neuroinformatics assembly.

Practical information about attendance via Zoom, program and syllabus / reading list will be published on this page. Examination will be in the form of a home assignment, to be completed within two days after the course (estimate work time = 8 hours).

Tentative schedule: 
September 15, 09:00-16:00, lunch break 12:00-13:00
September 16, 09:00-16:30, lunch break 12:00-13:00