A successful Professional Development Workshop on Brain Data Science held at SfN 2022 in San Diego

The INCF Training and Education Committee held a very successful Professional Development Workshop on Brain Data Science at SfN in San Diego. The workshop, entitled “Brain Data Science: A World of New Neuroscience Career Opportunities”, presented the many new career options that are becoming available in the intersection between neuroscience and data science.

The speakers included Saskia de Vries (Allen Institute), Dimitri Yatsenko (Datajoint and INCF Industry Advisory Council), Edda Thiels (NSF), Ariel Rokem (U Washington, Neurohackademy, INCF Training & Education Committee Chair), and Mathew Abrams (Director, INCF) presented how they do what they do, how they got there, and where they are going to a record audience of over 400 attendees. Audience participation surpassed expectations and included an additional 30 minutes of 1:1 discussions between panelists and attendees after the workshop ended, thus indicating that there is significant community interest in learning more about Brain Data Science and the career opportunities therein. The INCF Training and Education Committee plans to host more events like this one throughout 2023. Stay tuned!

Ariel Rokem (U Washington, Neurohackademy), the INCF Training & Education Committee Chair, talked about his journey into combining neuroscience with data science, and about data science-related roles in academia “Academic data scientists, research software engineers and other fantastic beasts”.

His final recommendations to attendees were:

• Learn how to program (Take a Carpentry workshop!)
• Find mentors and collaborators
• Become part of a community
• Search for opportunities to fund your work
• Adopt new (promising!) technologies
• Teach others (Teach a Carpentry workshop!)

Saskia de Vries (Principal Product Manager at Allen Institute for Neural Dynamics) talked about her journey “from bench science to data science”. She  joined the Allen Institute in 2012 as a scientist in the neural coding team, and has studied visual processing using a combination of physiological, computational, behavioral and molecular tools. She explained that in order to produce high quantities of quality data, standardized data processing pipelines are needed - and that requires  close collaboration between lab scientists and engineers.

Edda Thiels (National Science Foundation, NSF) gave the funder agency’s perspective - that data science increasingly is needed to advance knowledge and discovery in neuroscience and many other fields, and that resources for adequate training and access to infrastructure is needed to enable researchers to make the transition.

Mathew Abrams, INCF Director for Science and Training) talked about INCF and its focus on standards in neuroscience, explained why training is important to realize INCF’s mission, and presented INCF’s  suite of interconnected training resources: TrainingSpace for educational resources, Neurostarts for questions and discussion, and KnowledgeSpace for finding data and other resources.

Dimitri Yatsenko (Datajoint, INCF Industry Advisory Council) talked about his journey from software development into neuroscience studies, how he conceived and implemented the first version of DataJoint during his graduate studies to manage data and computation for calcium imaging combined with visual stimuli, and how automated workflows like those Datajoint offer can improve efficiency and reproducibility of science and facilitate collaborations on a larger scale. 

He listed some of the benefits of automated research workflows:

• reduce barriers to participation in advanced research activities
• ease access to high-performance computing capabilities
• increase the transparency and reproducibility of research
• foster timely incentives and credit assignment for efficient allocation of human effort and funding
• combine AI and human input into the complete cycle of discovery