EEG as a potential ground truth for the assessment of cognitive state in software development activities: A multimodal imaging study

• Published in: PloS one Vol. 19; no. 3; p. e0299108
• Main Authors: Medeiros, Júlio, Simões, Marco, Castelhano, João, Abreu, Rodolfo, Couceiro, Ricardo, Henriques, Jorge, Castelo-Branco, Miguel, Madeira, Henrique, Teixeira, César, de Carvalho, Paulo
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 07.03.2024; Public Library of Science (PLoS)
• Subjects: Biology and Life Sciences; Brain - physiology; Cognition; Computer and Information Sciences; Diagnostic imaging; Electroencephalography; Electroencephalography - methods; Engineering and Technology; Evaluation; Health care industry; Humans; Innovations; Magnetic Resonance Imaging - methods; Medicine and Health Sciences; Multimodal Imaging; Program errors; Research and Analysis Methods; Software; Technology application; Portugal
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0299108

Cognitive human error and recent cognitive taxonomy on human error causes of software defects support the intuitive idea that, for instance, mental overload, attention slips, and working memory overload are important human causes for software bugs. In this paper, we approach the EEG as a reliable surrogate to MRI-based reference of the programmer’s cognitive state to be used in situations where heavy imaging techniques are infeasible. The idea is to use EEG biomarkers to validate other less intrusive physiological measures, that can be easily recorded by wearable devices and useful in the assessment of the developer’s cognitive state during software development tasks. Herein, our EEG study, with the support of fMRI, presents an extensive and systematic analysis by inspecting metrics and extracting relevant information about the most robust features, best EEG channels and the best hemodynamic time delay in the context of software development tasks. From the EEG-fMRI similarity analysis performed, we found significant correlations between a subset of EEG features and the Insula region of the brain, which has been reported as a region highly related to high cognitive tasks, such as software development tasks. We concluded that despite a clear inter-subject variability of the best EEG features and hemodynamic time delay used, the most robust and predominant EEG features, across all the subjects, are related to the Hjorth parameter Activity and Total Power features, from the EEG channels F4, FC4 and C4, and considering in most of the cases a hemodynamic time delay of 4 seconds used on the hemodynamic response function. These findings should be taken into account in future EEG-fMRI studies in the context of software debugging.