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

Area of Science:

• Psychology and Cognitive Neuroscience
• Computational Research Methods

Background:

• Coding is crucial for modern psychology and neuroscience research, enabling complex experiments and large-scale data analysis.
• Many researchers lack formal coding training, creating a barrier to efficient and reproducible scientific practices.

Purpose of the Study:

• To provide practical coding guidelines for researchers across all experience levels.
• To promote best practices for code quality, automation, and reusability in scientific research.

Main Methods:

• Development of ten core principles for scientific coding.
• Tailoring practices for beginner, intermediate, and advanced programmers.
• Emphasis on collaborative environments and code sharing for principal investigators.

Main Results:

• Implementation of the ten principles can streamline research projects and automate tasks.
• Improved code quality, reusability, and reduced human error are key benefits.
• Fostering a culture of code sharing enhances research reliability.

Conclusions:

• Adopting standardized coding practices is essential for advancing experimental psychology and cognitive neuroscience.
• High-quality, reusable, and shareable code increases the trustworthiness and reproducibility of scientific findings.