Neurohackademy: Combining Online and Offline Neurological Informatics Education

Background Introduction

In recent years, human neuroscience has entered an era of big data. Due to initiatives like the Human Connectome Project and the Adolescent Brain Cognitive Development (ABCD) study, scientists have acquired datasets of previously unimaginable scale and scope. These datasets hold significant scientific potential for both basic and clinical research. However, they also pose various new challenges for researchers, including the generation, processing, access, analysis, and interpretation of these data. One of the main challenges is the so-called “big data skills gap”: research projects utilizing these datasets require a different knowledge base and skill set, as well as technical and conceptual tools different from those used in traditional small-scale experimental research.

Research and Source

The study was jointly completed by Ariel Rokem and Noah C. Benson, both researchers at the eScience Institute of the University of Washington. The article was published in the 2024 issue of the journal Neuroinformatics and is titled “Hands-on neuroinformatics education at the crossroads of online and in-person: lessons learned from neurohackademy.”

Research Content

Neurohackademy is a two-week course designed to train early-career neuroscience researchers in data science methods and their application in neuroimaging. The event aims to bridge the big data skills gap by introducing participants to data science methods and skills that are often overlooked in traditional courses. These skills are crucial for analyzing and interpreting large, complex datasets that have become increasingly important due to centralized data collection efforts.

In 2020, due to the COVID-19 pandemic, Neurohackademy quickly transitioned from an in-person event to an online one, attracting hundreds of participants from around the world. Subsequent activities in 2022 and 2023 evolved into a “hybrid” format that included both online and in-person participants. This article discusses the technical and socio-technical elements of hybrid events and summarizes the experience of organizing these activities, with a particular focus on their role in creating an inclusive global practice community.

Research Process

Phase One: Explicit Learning Phase

Participants first attend lectures on the application of data science methods to human neuroscience topics. These lectures include discussions on general themes like neuroethics and data governance, as well as tutorials on specific topics such as programming, software engineering, data visualization, and machine learning.

Phase Two: Project-Based Learning Phase

In this phase, participants join hackathons where they can propose projects and ideas, then team up with other participants. During this stage, course instructors and organizers act as mentors as needed, offering participants the opportunity to learn by doing.

Special Experimental Methods

In 2020, due to the pandemic, Neurohackademy transitioned from offline to online. This move not only removed the limitations of physical space but also enabled more researchers, hindered by travel, financial, visa, and other barriers, to participate. To adapt to this change, organizers employed numerous online tools such as Slack and Zoom to ensure remote participants could engage and interact.

In 2021, based on the experience from 2020, the event was optimized by reducing the course load and promoting the natural process of team formation. In 2022 and 2023, the events transitioned to a “hybrid” format while continuing to adhere to some public health measures, allowing some participants to join online and others in-person.

Research Results

Through a series of online and hybrid events, the research summarized two main points:

1. We can reach a broader and more diverse audience through online and hybrid workshops compared to purely in-person workshops.
2. Although challenging, it is possible to host meaningful hackathon events involving online participants.

In the 2022 and 2023 hybrid events, multiple technical tools, including Slack and Zoom, were used to facilitate participant interaction. They addressed technical infrastructure, teaching and communication, as well as the integration of remote and in-person participants as the three major challenges.

Conclusion

Scientific and Applied Value

Neurohackademy’s unique design philosophy and teaching methods help bridge the big data skills gap in neuroscience research. By combining the principles of Brainhack and Software Carpentry, participants can learn key data science skills and gain hands-on project experience in hackathon sessions, understanding the importance of interdisciplinary collaboration and innovation.

This learning method not only enhances students’ practical skills, collaborative abilities, and motivation but also creates a new global practice community for researchers. In the future, such activities will be of significant importance for skill enhancement and scientific innovation among neuroscience researchers.

Research Highlights

1. Innovative Hybrid Activity Format: The hybrid format of Neurohackademy allows participants from diverse backgrounds and conditions to join, breaking the traditional limitations of physical space.
2. Bridging the Skills Gap through Big Data Training: The activities not only teach participants essential programming and data management skills but also promote interdisciplinary collaboration and creative problem-solving through hands-on projects.
3. Establishing a Global Practice Community: Through online participation from around the world, a global practice community at the intersection of neuroimaging and data science was created.

Practical Significance of Specific Insights

1. Technical Support for Teaching and Learning: The use of online tools such as Slack and Zoom, combined with the establishment of standardized computing environments, greatly enhances the practicality of the courses and the convenience for participants.
2. Organic Integration of Software and Hardware: Using cloud computing platforms, in particular, ensured that all participants could work in a unified computing environment, overcoming limitations of different computing equipment and operating systems.
3. Promoting Deep Integration of Online and Offline Participants: Tools such as Owl devices were used to ensure interaction and collaboration between online and offline participants, providing valuable references for future hybrid teaching.

Comprehensive Evaluation and Outlook

Neurohackademy addresses the big data skills gap in neuroscience through a series of innovative ideas and methods and provides valuable experience for future educational activities. To better adapt to post-pandemic education models, we believe such activities will continue to evolve and create more learning and collaboration opportunities for more researchers and students.

Neurohackademy’s practice demonstrates that combining online and offline methods in education is feasible and effective, providing an exemplary case for similar educational projects. Future challenges may lie in how to scale up and apply these methods more widely to benefit more academic and research personnel.