A Systematic Literature Review on Measuring Brain Activity While Reviewing Code and Paintings
Year: 2025
Type: review
Study design: Systematic Review
Abstract: In recent years, the intersection of cognitive neuroscience and software engineering has sparked significant interest, particularly in understanding developers’ mental activities. This systematic literature review (SLR) investigates the current methodologies for measuring and analyzing mental activity, particularly using EEG when reviewing code and paintings. The research addresses four key questions: (1) What methods are available to measure mental activity when reviewing code and pictures? (2) What are the methods for analyzing brain activity data especially extracted using EEG? (3) How do brain activity patterns differ when studying code and pictures obtained with EEG? and (4) Are there any differences in stress levels when reviewing code and drawing obtained with EEG? Our findings reveal various techniques for capturing and analyzing EEG data, yet highlight a significant gap in the empirical research addressing the last two questions. This underscores the need for targeted experiments to explore these specific brain activity patterns and stress level differences. These are crucial for advancing our understanding of cognitive processes in software engineering and related fields.
Source: IEEE Access
Authors: Gcinizwe Dlamini, Abu Huraira, Zamira Kholmatova, Andrei Mikriukov, Guzel Safiullina, Giancarlo Succi, Alexander Tormasov
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,075
OpenAlex ID: W4409560719