Ten principles for reliable, efficient, and adaptable coding in psychology and cognitive neuroscience

This is the authors' abstract. We don't add key points for this paper.

Writing code is becoming essential for psychology and neuroscience research, supporting increasingly advanced experimental designs, processing of ever-larger datasets and easy reproduction of scientific results. Despite its critical role, coding remains challenging for many researchers, as it is typically not part of formal academic training. We present a range of practices tailored to different levels of programming experience, from beginners to advanced users. Our ten principles help researchers streamline and automate their projects, reduce human error, and improve the quality and reusability of their code. For principal investigators, we highlight the benefits of fostering a collaborative environment that values code sharing. Maintaining basic standards for code quality, reusability, and shareability is critical for increasing the trustworthiness and reliability of research in experimental psychology and cognitive neuroscience.