心理学和认知神经科学中可靠、高效和适应性强的编码的十大原则。

Johannes Roth, Yunyan Duan, Florian P Mahner, Philipp Kaniuth, Thomas S A Wallis, Martin N Hebart
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引用次数: 0

摘要

对于心理学和神经科学研究来说,编写代码正变得至关重要,它支持越来越先进的实验设计、处理越来越大的数据集以及轻松再现科学结果。尽管编码具有关键作用,但对许多研究人员来说仍然具有挑战性,因为它通常不是正式学术培训的一部分。我们为从初学者到高级用户的不同层次的编程经验提供了一系列的实践。我们的十条原则帮助研究人员简化和自动化他们的项目,减少人为错误,提高代码的质量和可重用性。对于主要的研究者,我们强调培育一个重视代码共享的协作环境的好处。维护代码质量、可重用性和可共享性的基本标准对于提高实验心理学和认知神经科学研究的可信度和可靠性至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ten principles for reliable, efficient, and adaptable coding in psychology and cognitive neuroscience.

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.

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