Expert Programmers Have Fine-Tuned Cortical Representations of Source Code
Expert Programmers Have Fine-Tuned Cortical Representations of Source Code
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DOI：
10.1523/eneuro.0405-20.2020
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发表时间：
2020-01
期刊：
影响因子：
3.4
通讯作者：
Yoshiharu Ikutani;Takatomi Kubo;S. Nishida;Hideaki Hata;Ken-ichi Matsumoto;K. Ikeda;Shinji Nishimoto
中科院分区：
文献类型：
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作者：
Yoshiharu Ikutani;Takatomi Kubo;S. Nishida;Hideaki Hata;Ken-ichi Matsumoto;K. Ikeda;Shinji Nishimoto
专业知识使人类能够在特定领域的任务上取得出色的表现，编程也不例外。许多研究表明，专业程序员与新手在行为表现、知识结构和选择性注意力方面表现出显著差异。然而，程序员大脑中潜在的差异仍然不清楚。我们在这里通过使用数据驱动的解码方法将源代码的皮层表示与个人编程专业知识相关联来解决这个问题。这种方法使我们能够识别七个大脑区域，广泛分布在额叶、顶叶和颞叶皮层，它们与编程专业知识有着密切的关系。在这些脑区，大脑活动可以解码源代码的功能类别，解码准确率与个体在源代码分类任务中的行为表现显著相关。我们的研究结果表明，编程专业知识是建立在专门用于编程领域的微调皮层表征之上的。
Abstract Expertise enables humans to achieve outstanding performance on domain-specific tasks, and programming is no exception. Many studies have shown that expert programmers exhibit remarkable differences from novices in behavioral performance, knowledge structure, and selective attention. However, the underlying differences in the brain of programmers are still unclear. We here address this issue by associating the cortical representation of source code with individual programming expertise using a data-driven decoding approach. This approach enabled us to identify seven brain regions, widely distributed in the frontal, parietal, and temporal cortices, that have a tight relationship with programming expertise. In these brain regions, functional categories of source code could be decoded from brain activity and the decoding accuracies were significantly correlated with individual behavioral performances on a source-code categorization task. Our results suggest that programming expertise is built on fine-tuned cortical representations specialized for the domain of programming.