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Neuroinformatics Assembly 2021 - Program

Program - Week 1

11:00 - 12:50 EDT Session 1: Introduction to INCF & perspectives of FAIR
icon keynoteChair: Maryann Martone, University of California, San Diego

Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience. FAIR defines a set of high level principles and practices for making digital objects, including data, software and workflows, Findable, Accessible, Interoperable and Reusable. But FAIR is not a specification; it leaves many of the specifics up to individual scientific disciplines to define. INCF has been leading the way in promoting, defining and implementing FAIR data practices for neuroscience. We have been bringing together researchers, infrastructure providers, industry and publishers through our programs and networks.

In this session, we will hear some perspectives on FAIR neuroscience from some of these stakeholders who have been working to develop and use FAIR tools for neuroscience. We will engage in a discussion on questions such as: how is neuroscience doing with respect to FAIR? What have been successes? What is currently very difficult? Where does neuroscience need to go? Audience participation will be encouraged.

  • Introduction
    Maryann Martone, University of California, San Diego 
  • FAIR atlases
    Speaker: Heidi Kleven, University of Oslo 
  • FAIR repositories and the difficulties therein
    Speaker: Joost Wagenaar, Blackfynn 
  • FAIR researcher perspective
    Speaker: Adam Ferguson, University of California, San Francisco 
  • Effort involved in truly FAIR neuroimaging: Towards community-driven research
    Speaker: Camille Maumet, Inria 
  • Responsible access to neuroscience data: Critical considerations
    Speaker: Damian Eke, De Montfort University
  • Discussion
12:50 - 13:00 EDT BREAK
13:00 - 14:30 EDT Session 2: Practical use cases for FAIR
icon keynoteChair: Anita Bandrowski, SciCrunch

We will explore some practical use cases and see whether these affect your repository, your tool, or your research. This will be a highly interactive session with online polling to engage the audience with the content.

  • FAIRSharing - Susanna Sansone, University of Oxford 
  • Elixr BioTools - Hervé Menager, Institut Pasteur 
  • - Lenny Teytelman,
  • The Immune Epitope Database - Randi Vita, La Jolla Institute for Allergy & Immunology
11:00 - 12:30 EDT Session 3: FAIR approaches for computational neuroscience
icon keynoteChair: Sharon Crook, Arizona State University

As models in neuroscience have become increasingly complex, it has become more difficult to share all aspects of models and model analysis, hindering model accessibility and reproducibility. In this session, we will discuss existing resources for promoting FAIR data and models in computational neuroscience, their impact on the field, and remaining barriers.

  • Introduction
    Sharon Crook, Arizona State University 
  • Considerations and challenges for FAIR in large and heteregeneous sets of personalized large-scale models
    Speaker: Kelly Shen, Rotman Research Institute at Baycrest Health Sciences
  • Do we have the tools and resources to develop FAIR large-scale brain circuit models?
    Speaker: Salvador Dura-Bernal, State University of New York (SUNY) Downstate
  • Structured validation processes in neural network simulations and analysis
    Speaker: Michael Denker, Institute of Neuroscience and Medicine
  • Discussion
12:30 - 12:40 EDT BREAK
12:40 - 13:00 EDT DataJoint Elements: Implementing standardized workflows in neurophysiology - Dimitri Yatsenko
13:00 - 14:30 EDT Session 4: FAIR approaches for neuroimaging research
icon keynoteChair: Satra Ghosh, MIT

Over the last three decades, neuroimaging research has seen large strides in the scale, diversity, and complexity of studies, the open availability of data and methodological resources, the quality of instrumentation and multimodal studies, and the number of researchers and consortia. The awareness of rigor and reproducibility has increased with the advent of funding mandates, and with the work done by national and international brain initiatives. This session will focus on the question of FAIRness in neuroimaging research touching on each of the FAIR elements through brief vignettes of ongoing research and challenges faced by the community to enact these principles.

  • Introduction
    Satra Ghosh, MIT
  • Enhanced dataset search with semantic annotations and NIDM
    Speaker: David Keator, University of California, Irvine
  • The village that can climb the hill: perks & hurdles of designing, collecting, and sharing a FAIR dataset in neuroscience
    Speakers: Valentina Borghesani, CNeuromod & Julie A. Boyle, CRIUGM
  • Open science efforts for PET imaging - From guidelines over BIDS PET to OpenNeuroPET
    Speaker: Melanie Ganz-Benjaminsen, University of Copenhagen
  • Open for research: challenges and opportunities in re-using publicly available datasets
    Speaker: Elizabeth Dupré, McGill University
  • Ethics of FAIR in neuroimaging
    Speaker: Gustav Nilsonne, Karolinska Institutet
  • Discussion
14:30 - 15:30 EDT Poster slot 1 (1 hour)
14:30 EDT/ 20:30 CET
03:00 - 04:00 EST Poster slot 2 (1 hour)
09:00 CET /16:00 JST /17:00 AET
11:00 - 12:30 EDT Session 5: FAIR approaches for electrophysiology
icon keynoteChair: Thomas Wachtler, Ludwig-Maximilians University
  • Introduction
    Thomas Wachtler, Ludwig-Maximilians University
  • Curating electrophysiology data for reuse in EBRAINS
    Speaker: Andrew Davison, CNRS, Gif sur Yvette
  • How standards and use-cases shape up the FAIR DANDI archive
    Speakers: Yaroslav Halchenko, Dartmouth College
  • AEDAPT: Developing an open, portable, scalable Australian platform for FAIR electrophysiology and MEG data analytics
    Speaker: Tom Johnstone, Swinburne University of Technology
  • Towards a standardized data organization for electrophysiology
    Speaker: Sylvain Takerkart, CNRS-AMU
  • Discussion
12:30 - 13:00 EDT BREAK
13:00 - 14:30 EDT Session 6: Tools and infrastructure showcase
icon keynoteChair: Helena Ledmyr, INCF

This session will include presentations of infrastructure that embrace the FAIR principles developed by members of the INCF Community.

  • Introduction
    Helena, INCF
  • The Virtual Brain
    Speaker: Petra Ritter, Berlin Institute of Health
  • Addgene
    Speaker: Joanne Kamens, Addgene
  • Canadian Open Neuroscience Platform
    Speaker: Tristan Glatard, Concordia University
    Speaker: Steven Vermeulen and Jan Bjaalie, HBP
  • The China-Cuba-Canada neuroinformatics ecosystem for QEEG
    Speaker: Pedro Valdés Sosa, Cuban Neuroscience Center
  • INCF TrainingSuite
    Speaker: Mathew Abrams, INCF
20:00 - 21:00 EDT Poster slot 3 (1 hour)
20:00 CET /08:00 JST /09:00 AET
11:30 - 12:30 EDT Session 7: INCF councils and committees showcase
icon keynoteChair: Mathew Abrams, INCF

The objective of this session is to present the current and future activities of the INCF councils and committees and provide a forum in which the community can provide feedback and recommend new directions for the INCF network.

  • Introduction
    Mathew Abrams, INCF
  • Council for Training, Science, and Infrastructure (CTSI)
    Speaker: Jean Baptiste Poline, McGill University
  • Industry Advisory Council (IAC)
    Speaker: Vijay Iyer, MathWorks
  • Training and Education Committee (TEC)
    Speaker: William Grisham, University of California
  • Infrastructure Committee (IC)
    Speaker: Wojtek Goscinski, Monash University
  • Standards and Best Practices Committee (SBP)
    Speaker: Maryann Martone, University of California, San Diego
  • Discussion
12:30 - 13:00 EDT BREAK
13:00 - 14:00 EDT Session 8: Data science and neuroinformatics
icon keynoteChair: Ariel Rokem, University of Washington

Much like neuroinformatics, data science uses techniques from computational science to derive meaningful results from large complex datasets. In this session, we will explore the relationship between neuroinformatics and data science, by emphasizing a range of data science approaches and activities, ranging from the development and application of statistical methods, through the establishment of communities and platforms, and through the implementation of open-source software tools. Rather than rigid distinctions, in the data science of neuroinformatics, these activities and approaches intersect and interact in dynamic ways. Together with a panel of cutting-edge neuro-data-scientist speakers, we will explore these dynamics.

  • Introduction
    Ariel Rokem, University of Washington
  • Mine your own view: A self-supervised approach for learning representations from neural activity
    Speaker: Eva Dyer, Georgia Institute of Technology
  • Using deep learning for the study of behavior
    Speaker: Mackenzie Mathis, EPFL
  • Building an interoperable cloud ecosystem to support research assets sharing and scientific reproducibility in neuroimaging
    Speaker: Franco Pestilli, University of Texas, Austin
  • Discussion
10:30 - 12:30 EDT Session 09: International Brain Initiative
icon keynoteChairs: Kenji Doya, Okinawa Institute of Science and technology & Maryann Martone, University of California, San Diego

The International Brain Initiative (IBI) is a consortium of the world’s major large-scale brain initiatives and other organizations with a vested interest in catalyzing and advancing neuroscience research through international collaboration and knowledge sharing. This session will introduce the IBI and the current efforts of the Data Standards and Sharing Working Group with a view to gain input from a wider neuroscience and neuroinformatics community.

  • Introduction to the International Brain Initiative
    Jan Bjaalie, University of Oslo
  • Introduction to the IBI Data standards and sharing working group
    Speaker: Kenji Doya, Okinawa Institute of Science and Technology
  • icon keynoteKeynote: Title TBD
    Speaker: Kenneth Harris, University College London
  • icon keynoteKeynote: Key to fruitful sharing of data is fruitful data
    Speaker: Kristen Harris, The University of Texas at Austin
  • Introduction of three Task Forces of the Data Standards and Sharing WG
    - Data Governance White paper Task Force

    Speaker: Franco Pestilli, The University of Texas at Austin
    - Data Catalog Task Force
    Speaker: Sean Hill, The Centre for Addiction and Mental Health
    - Training Task Force
    Speaker: Sharon Crook, Arizona State University
  • Discussion on prospects and needs in neural data sharing
  • Closing remarks
    Speaker: Maryann Martone, University of California, San Diego
12:30 - 12:40 EDT BREAK
12:40 - 13:00 EDT Harnessing (FAIR) Neuroscience Data with MATLAB
13:00 - 14:00 EDT Session 10: Open Innovation & Intellectual property
icon keynoteChairs: Vijay Iyer, MathWorks, and Randy McIntosh, Baycrest
Participants: Joe Artuso (OpenBCI), Sue Tappan (MBF Bioscience), Markus

In recent years, leading academic institutes have begun to embrace and define Open Science. Some puzzles have emerged, including the role of intellectual property protection for innovations emerging in academia. Meanwhile, industry has been grappling with these puzzles for years. A notable milestone was the publication of Open Innovation in the 2000s, which highlighted limitations of closed innovation and benefits of more open innovation for companies to consider.

This session will cover questions such as

- What does open innovation mean for commercial entities? How does it help and challenge operations? 

- How do we balance intellectual property protection and open innovation? What is the relationship between intellectual property and open innovation?

- How do we incentivize open innovation for industry and academics?

- What are the risks and benefits of open innovation? For companies and for academics.

- Academia and industry often misunderstand each other. From an industry perspective, what’s one thing about open innovation that might surprise academic researchers? 

- Innovation is generally situated within a “supply chain” with the promise of benefits for both the innovators and the downstream consumers. Where do companies fit into a supply chain and how does that affect open innovation? 

- How can academia & industry collaborate in an open innovation context?

  • Introduction
    Vijay Iyer, MathWorks, and Randy McIntosh, Baycrest
  • Title - TBD
    Speaker: Joe Artuso, OpenBCI
  • Title - TBD
    Speaker: Sue Tappan, MBF Bioscience
  • Title - TBD
    Speaker: Markus Butz-Ostendorf, Biomax Informatics
  • Title - TBD
    Speaker: Ken Evans, InDoc
  • Discussion
14:00 - 15:00 EDT Posters & networking