On the Influence of the Baseline in Neuroimaging Experiments on Program Comprehension

Background : Neuroimaging methods have been proved insightful in program-comprehension research. A key problem is that different baselines have been used in different experiments. A baseline is a task during which the “normal” brain activation is captured as a reference compared to the task of interest. Unfortunately, the influence of the choice of the baseline is still unclear. Aims : We investigate whether and to what extent the selected baseline influences the results of neuroimaging experiments on program comprehension. This helps to understand the tradeoffs in baseline selection with the ultimate goal of making the baseline selection informed and transparent. Method : We have conducted a pre-registered program-comprehension study with 20 participants using multiple baselines (i.e., reading, calculations, problem solving, and cross-fixation). We monitored brain activation with a 64-channel electroencephalography (EEG) device. We compared how the different baselines affect the results regarding brain activation of program comprehension. Results and Implications : We found significant differences in mental load across baselines suggesting that selecting a suitable baseline is critical. Our results show that a standard problem-solving task, operationalized by the Raven-Progressive Matrices, is a well-suited default baseline for program-comprehension studies. Our results highlight the need for carefully designing and selecting a baseline in program-comprehension studies.

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Publication Details

Journal
ACM Transactions on Software Engineering and Methodology
Published
2025-06-17
DOI
https://doi.org/10.1145/3744739
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
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article

On the Influence of the Baseline in Neuroimaging Experiments on Program Comprehension

Annabelle Bergum, Norman Peitek, Janet Siegmund, Sven Apel et al.
ACM Transactions on Software Engineering and Methodology
EEG and Brain-Computer Interfaces
article

On the Influence of the Baseline in Neuroimaging Experiments on Program Comprehension

Annabelle Bergum, Norman Peitek, Janet Siegmund, Sven Apel, Maurice Rekrut
article en

Abstract

Background : Neuroimaging methods have been proved insightful in program-comprehension research. A key problem is that different baselines have been used in different experiments. A baseline is a task during which the “normal” brain activation is captured as a reference compared to the task of interest. Unfortunately, the influence of the choice of the baseline is still unclear. Aims : We investigate whether and to what extent the selected baseline influences the results of neuroimaging experiments on program comprehension. This helps to understand the tradeoffs in baseline selection with the ultimate goal of making the baseline selection informed and transparent. Method : We have conducted a pre-registered program-comprehension study with 20 participants using multiple baselines (i.e., reading, calculations, problem solving, and cross-fixation). We monitored brain activation with a 64-channel electroencephalography (EEG) device. We compared how the different baselines affect the results regarding brain activation of program comprehension. Results and Implications : We found significant differences in mental load across baselines suggesting that selecting a suitable baseline is critical. Our results show that a standard problem-solving task, operationalized by the Raven-Progressive Matrices, is a well-suited default baseline for program-comprehension studies. Our results highlight the need for carefully designing and selecting a baseline in program-comprehension studies.

ACM Transactions on Software Engineering and MethodologyVol. 35(3)
Chemnitz University of Technology (DE), German Research Centre for Artificial Intelligence (DE), Saarland University (DE)
Openalex Percentile: Top 87%
EEG and Brain-Computer Interfaces
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On the Influence of the Baseline in Neuroimaging Experiments on Program Comprehension — Annabelle Bergum, Norman Peitek, et al. · ACM Transactions on Software Engineering and Methodology (2025) | TGRS Research Map | TGRS