The 2020 Brain Data Bank Challenge (BDBC-2020) is targeted to expose, discuss and accelerate on-going brain research from around the world.
This is a hybrid event, both virtual and in person. Competing teams can make presentations in the preliminary rounds on-line or in person with judging locations in Taiwan, Russia, and United States. Some teams from preliminary rounds will be invited to participate in the final round in Santa Clara, CA, USA.
Others with like interest and curiosity are invited to be in the audience and take advantage of this borderless sharing of state-of-the-art brain research and development.
Registration for early rounds is now closed.
Updates 11/23/2020: The BDBC-2020 is entering its Final Round hosted from California, USA to be held on Saturday, December 5, 2020. This is a free virtual event. REGISTER HERE. Besides Challenge presentations from 5 teams invited from regional preliminary rounds throughout the year, the Final Round program will include a Keynote and an international Special Panel on User Design Paradigm.
Final Round Challenge Agenda: December 5, 2020, 9:00 – 13:30 US Pacific Time
9:00 – 9:15am Introduction – IEEE Santa Clara Valley and local supporting chapters and BDBC: Joseph Wei, and Dr. Nan Chu
9:15 – 9:45am Keynote: Neurotechnology for Aging Brain and funding opportunities from National Institute on Aging (NIA): Dr. Yuan Luo, Program Director at NIA Division of Neuroscience
9:45 – 1:30pm Team presentation (winning teams from each previous competition)
- BDBC- Taiwan, Team MINE Professor Brain, National Central University,
– Title: “Utilizing Deep Learning Model to Predict Brain Age for Alzheimer’s Disease and Mild Cognitive Impairment Patients”
- BDBC- Boston, Team Pokemon Brain – University of Missouri-Kansas City,
– Title: “Improving deep learning performance using transfer learning to Predict Early Stages of Alzheimer in ADNI dataset”
- BDBC- Saint Petersburg, Team i-Pavlovian, The I. P. Pavlov Institute of Physiology, Russian Academy of Sciences,
– Title: “Identifying age and cognitive impairment based on EEG data”
- SPCN-2020, Team MTLNeuro, S.M. Kirov Military Medical Academy, Saint Petersburg, Russia;
– Title: “Functional Connectivity of Neural Networks and Cognitive Status in Patients with Alzheimer’s Disease”
- SPCN-2020, Team Visual Physiology, National Academy Karayev Institute of Physiology, Azerbaijan
– Title: “Neurophysiology Effects on Alzheimer’s Disease Rehabilitation by Safron and Curcuma Longa”
Panel: Codesigning with the End-user: An Emerging Neurotechnological Research Paradigm!
Moderator: Troy McDaniel, Arizona State University, USA
- Justin Yerbury, University of Wollongong, Australia
- Rebecca Monteleone, University of Toledo, OH, USA
- Katina Michael, ASU, USA & UoW, Australia
- BDBC Finale Awards – Judge Panel Announcement
- Acknowledgment of Impactful Contribution to BDBC, 2017 – 2020″
1:30pm Closure of BDBC-2020[rule style=”rule-dashed” ]
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The 2020 Brain Data Bank Challenge (BDBC-2020) invites topics on brain data analytics to improve the quality of life and safety of senior citizens. Knowing the senior population has been severely impacted by COVID-19, this year’s focus will be on the “Aging Brain”.
We seek to address (some or all) questions below, regarding the aging brain:
- How effectively do EEG, fNIRS, and/or fMRI datasets capture the aging brain?
- How does the aging brain respond to non-verbal signal (e.g., vision, facial expression, body language and temperature)?
- How can emerging techniques, e.g., Big Data Analytics, Artificial Intelligence, and Deep Learning, enhance the prediction of brain aging?
- How to facilitate ease of use, reliability and protection of brain datasets?
Furthermore, lessons learned from past BDBC presentations have led us to believe:
- Using Machine Learning can localize EEG dimensionality with optimized spatial temporal correlation to compress data by 280 fold.
- Using AI/Deep Learning can improve dataset performance and prediction sensitivity to above 90%.
- Low power CNN microchip with nano-sensor can be implanted for real-time prediction.
- 3D model manufacturing can make comprehensive brain display cost-effective.
We invite you to sign up as a participant (competing and presenting results) or as an observer (in the audience, not competing) to the challenge. You may also complete the form if you are interested in being a speaker.
Registration for early rounds is now closed.
Locations and Dates
This is a hybrid event, where online presentation of your challenge results is allowed. Optionally, depending on travel restrictions and social distancing due to COVID-19 at the time of the event, participants can present their results on site at Taoyuan City, Taiwan (Sept. 22), St. Petersburg, Russia (Sept. 22), or Cambridge, MA, USA (Nov. 5). Teams selected for the final round may present their results at Santa, Clara, USA (Dec 5).
Preliminary Round, September 22, Taiwan
Go to SPCN-2020 Taiwan for more details
Local contact: Po-Lei Lee, email@example.com
Preliminary Round, November 5, Boston, MA, United States
Go to the local Boston challenge page for more details
Local contact: Bruce Hecht, Bruce.Hecht@ieee.org
Preliminary Round, November 9-13, Russia
Local contact: Evgenia Grinenko, firstname.lastname@example.org
Final Round, December 5, Santa Clara, CA, United States
Local contact: Joseph Wei, email@example.com
Fees – please check with local organizers for on-site participation.
Nan Chu, CWLab International, IEEE Consumer Electronics Society Representative in Brain Initiative and Sensors Council
Seth Elkin Frankston, U.S. Army CCDC Soldier Center
Bruce Hecht, VG2PLAY
Saraju Mohanty, University of North Texas
Joseph Wei, Technology Ventures
Recommended datasets can be obtained from repository of the National Institute’s Alzheimer’s Disease Neuro Imaging in http://adni.loni.usc.edu/ ; or the NeuroImaging Tools & Resources Collaboratory: https://www.nitrc.org/search/?type_of_search=group&q=eeg+data. Other open-source brain image datasets, preferable 10 GB or more, are acceptable as well.
About ADNI NeuroImage data, please refer to training slides:
2020 Tutorials (including ADNI3):
Part I: https://spcn2020taiwan.files.wordpress.com/2020/10/t1-bdbc_adni_tutorial_part1.pdf
Part II: https://spcn2020taiwan.files.wordpress.com/2020/10/t1-bdbc_adni_tutorial_part2.pdf
2012 Tutorials (ADNI1 & ADNI2 only)
Part I: https://adni.loni.usc.edu/wp-content/uploads/2012/08/ADNI_data_training_slides_part1.pdf
Part II: https://adni.loni.usc.edu/wp-content/uploads/2012/08/slide_data_training_part2_reduced-size.pdf
2020 Tutorials on Deep Learning Research in Alzheimer’s Disease :
Part I: https://spcn2020taiwan.files.wordpress.com/2020/10/t2-sp2020_tutorial-cnn-part-i.pdf
Part II: https://spcn2020taiwan.files.wordpress.com/2020/10/t2-sp2020_tutorial-cnn-part-ii.pdf
BDBC Contestant’s Presentation Template: https://spcn2020taiwan.com/call-for-presentations/
Information from SPCN2020Taiwan.com can help you prepare for subsequent BDBC-2020 events to become qualified for the Finale.
Judging criteria will be based out of 100 points using the following criteria:
Dataset Description (10 points)
Research Questions to Address (10 points)
Proposed Method (20 points)
Analytics (20 points)
Results (20 points)
Presentation (10 points)
Impact Assessment (10 points)
The Judging Panel reserves the right for the final, in-disputable ranking decision.
Cash prizes up to $1000 for early rounds and $4000 for the final round will be awarded.