2 minute read

image of Shaylyn


I am a graduate student from Canada, specializing in Cognitive Neuroscience. My research involves neuroimaging with functional magnetic resonance imaging and I developed an interest in open science and open source projects during my undergraduate and early graduate studies.

In 2020/2021, my graduate lab shifted to running studies online. Our lab had been using other software for experiment design, so the online shift was a great chance for me and other lab members to start using PsychoPy.

PsychoPy Involvement

The experiments I have designed often involve picture/text stimuli with multiple locations. I often use code components to control the selection of the different locations. In learning PsychoPy, the community forums have been a helpful resource to learn some ways to achieve my study goals and troubleshoot problems as I learned to run studies online.

As I gained experience I was able to start contributing back to the community. I mostly contribute by answering questions on the community forum and I like tackling questions that involve interesting task designs or small code components. Some of these discussions are about figuring out the slight differences in PsychoPy vs PsychoJS and there was a bug in online studies that I helped fix.

My level of participation in the PsychoPy community depends on my research projects. When I am designing new cognitive experiments, I tend to be more active. The PsychoPy community has been a very welcoming place that helped get me involved in open science and open source initiatives. Helping out on the forum is a great way to improve problem solving, coding, and code communication skills.

One of these days I would love to build some PsychoPy experiments for neuroimaging studies. I also would like to design experiments in PsychoPy that capture vocal response times and durations. The Whisper transcription plug-in looks very exciting for this direction.

Contributing to open source projects uses many of the same skills as scientific research. You identify a ‘problem’ (perhaps a research question or computer bug) and make incremental changes based on your hypotheses to learn more about the mechanisms behind your ‘problem’. You should document your changes (research methods, version control) and your observations (research results, code comments and documentation). And if things go well, in the end you may have a research publication, or an open source contribution. In this way, coding is not very different from doing research!

Happy experimenting!

Shaylyn (she/her)