A paper recently published in Neuron outlines three main obstacles to teaching students how to code. The Human Brain Project is proud to offer coding courses to young researchers through its Education programme.

The paper, titled ‘The next generation of neuroscientists needs to learn how to code, and we need new ways to teach them’, outlines three major barriers to bringing programming education into undergraduate and graduate programs:

• Instructor knowledge of coding
• Ease of access to coding tools
• Unknown needs of “applied” versus “basic” programming courses

The Human Brain Project offers solutions to two of these issues in particular:

Ease of access to coding tools

The author Ashley L. Juavinett points out that many coding languages are expensive and difficult to install for students and educators. She writes: 

“Coding languages and environments vary tremendously in their ease of access and understandability. While high-level languages such as MATLAB are accessible to native English speakers, MATLAB is very expensive without a departmental license. Furthermore, installing necessary software and packages for some coding environments can be a daunting, memory-consuming haul for students and educators alike. Thankfully, languages such as Python and R are free to use, and Jupyter Notebooks are a user-friendly way to run teaching-oriented code.”

Workshops organized by the HBP Education Programme regularly offer courses on coding with Python, a free to use language. For example, Fahad Khalid from Forschungszentrum Jülich gave an introduction to Python during the ‘3rd HBP Curriculum Workshop Series – High-performance computing for neuroscience’ workshop in July 2019.

Sessions on Jupyter Notebooks often feature in HBP Education Programme events as well. For instance, Jonathan Villemaire-Krajden from École Polytechnique Fédérale de Lausanne presented ‘Jupyter Notebooks in the Collaboratory’ during CodeJam #10 which took place in November 2019. The goal of the CodeJam workshops is to catalyze open-source, collaborative software development in computational and systems neuroscience and neuroinformatics, by bringing together researchers, students and engineers to share ideas, present their work, and write code together. The events are co-organized by the HBP Education Programme and the University of Heidelberg.

Unknown needs of “applied” versus “basic” programming courses

Juavinett also suggests that many neuroscience students are reluctant to learn coding because they may not consider it relevant to their studies. She writes:

“A more important consideration, however, is that coding content is made relatable to neuroscience and the student experience. Many neuroscience and biology students do not consider themselves ‘‘computational’’ and are often reluctant to take traditional coding courses. A discipline-specific introduction may motivate these students to conquer their fears and dive in.”

HBP Education events often help students to understand how coding can be used in brain research. The previously mentioned ‘3rd HBP Curriculum Workshop Series – High-performance computing for neuroscience’ taught the basics of supercomputing needed for using HPC systems in neuroscience research, and included introductory lectures with hands-on sessions about scientific computing in Python. Recordings of the sessions can be watched here.

The ability to code is increasingly valuable in the field of brain research, allowing scientists to run simulations of neurons, perform statistical analyses of data, and manage large databases. The Human Brain Project is proud to help the next generation of neuroscientists learn this fundamental skill.

Read the full paper in Neuron

The next generation of neuroscientists needs to learn how to code, and we need new ways to teach them by Ashley L. Juavinett

The HBP Education Programme

Click here to learn more about the HBP Education Programme.