Abstract
Background
Computer programming, the process of designing, writing, and testing executable computer code, is an essential skill in numerous fields. A description of the neural structures engaged and modified during programming skill acquisition could help improve training programs and provide clues to the neural substrates underlying the acquisition of related skills.
Methods
Fourteen female university students without prior computer programing experience were examined by functional magnetic resonance imaging (fMRI) during the early and late stages of a 5-month ‘Computer Processing’ course. Brain regions involved in task performance and learning were identified by comparing responses to programming and control tasks during the early and late stages.
Results
The accuracy of performing a programming task was significantly improved during the late stage. Various regions of the frontal, temporal, parietal, and occipital cortex as well as several subcortical structures (caudate nuclei and cerebellum) were activated during programming tasks. Brain activity in the right inferior frontal gyrus was greater during the late stage and significantly correlated with improved task performance. Although the left inferior frontal gyrus was also highly active during the programming task, there were no learning-induced changes in activity or a significant correlation between activity and improved task performances.
Conclusion
Computer programming learning among novices induces functional neuroplasticity within the right inferior frontal gyrus but not the left inferior gyrus (Broca’s area).
Similar content being viewed by others
Data availability
All data generated for this project are included in the Tables and Figures of this article.
References
Basso A, Capitani E, Laiacona M (1987) Raven’s coloured progressive matrices: normative values on 305 adult normal controls. Funct Neurol 2:189–194
Behzadi Y, Restom K, Liau J, Liu TT (2007) A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37:90–101. https://doi.org/10.1016/j.neuroimage.2007.04.042
Branzi FM, Pobric G, Jung J, Lambon Ralph MA (2021) The left angular gyrus is causally involved in context-dependent integration and associative encoding during narrative reading. J Cogn Neurosci 33:1082–1095. https://doi.org/10.1162/jocn_a_01698
Busjahn T, Bednarik R, Begel A, Crosby M, Paterson JH, Schulte C, Sharif B, Tamm S (2015) Eye movements in code reading: relaxing the linear order. In: 2015 IEEE 23rd International Conference on Program Comprehension, 2015. IEEE, pp 255–265
Castelhano J, Duarte IC, Ferreira C, Duraes J, Madeira H, Castelo-Branco M (2019) The role of the insula in intuitive expert bug detection in computer code: an fMRI study. Brain Imaging Behav 13:623–637
Chee MW, Hon N, Lee HL, Soon CS (2001) Relative language proficiency modulates BOLD signal change when bilinguals perform semantic judgments. Blood Oxygen Level Dependent Neuroimage 13:1155–1163. https://doi.org/10.1006/nimg.2001.0781
Cotton B, Tzeng OJ, Hardyck C (1980) Role of cerebral hemispheric processing in the visual half-field stimulus–response compatibility effect. J Exp Psychol 6:13
Ferstl EC, Neumann J, Bogler C, von Cramon DY (2008) The extended language network: a meta-analysis of neuroimaging studies on text comprehension. Hum Brain Mapp 29:581–593. https://doi.org/10.1002/hbm.20422
Fix V, Wiedenbeck S, Scholtz J (1993) Mental representations of programs by novices and experts. In: Proceedings of the INTERACT'93 and CHI'93 Conference on Human Factors in Computing Systems, 1993. pp 74–79
Floyd B, Santander T, Weimer W Decoding the representation of code in the brain: an fMRI study of code review and expertise. In: 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE), 2017. IEEE, pp 175–186
Galloway L, Krashen S (1980) Cerebral organization in bilingualism and second language. Research in second language acquisition:74–80.
Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL, Xu J, Jbabdi S, Webster M, Polimeni JR, Van Essen DC, Jenkinson M (2013) The minimal preprocessing pipelines for the human connectome project. Neuroimage 80:105–124. https://doi.org/10.1016/j.neuroimage.2013.04.127
Gordon H, Carmon A (1976) Transfer of dominance in speed of verbal response to visually presented stimuli from right to left hemisphere. Percept Mot Ski 42:1091–1100. https://doi.org/10.2466/pms.1976.42.3c.1091
Hickok G, Poeppel D (2007) The cortical organization of speech processing. Nat Rev Neurosci 8:393–402. https://doi.org/10.1038/nrn2113
Hosoda C, Tanaka K, Nariai T, Honda M, Hanakawa T (2013) Dynamic neural network reorganization associated with second language vocabulary acquisition: a multimodal imaging study. J Neurosci 33:13663–13672. https://doi.org/10.1523/jneurosci.0410-13.2013
Ikutani Y, Kubo T, Nishida S, Hata H, Matsumoto K, Ikeda K, Nishimoto S (2021) Expert programmers have fine-tuned cortical representations of source code. eNeuro. https://doi.org/10.1523/eneuro.0405-20.2020
Ivanova AA, Srikant S, Sueoka Y, Kean HH, Dhamala R, O’Reilly UM, Bers MU, Fedorenko E (2020) Comprehension of computer code relies primarily on domain-general executive brain regions. Elife. https://doi.org/10.7554/eLife.58906
Koenemann J, Robertson SP (1991) Expert problem solving strategies for program comprehension. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1991. pp 125-130
Kriegeskorte N, Goebel R, Bandettini P (2006) Information-based functional brain mapping. Proc Natl Acad Sci U S A 103:3863–3868. https://doi.org/10.1073/pnas.0600244103
Li P, Legault J, Litcofsky KA (2014) Neuroplasticity as a function of second language learning: anatomical changes in the human brain. Cortex 58:301–324. https://doi.org/10.1016/j.cortex.2014.05.001
Obler L (1981) Right hemisphere participation in second language acquisition. Individual differences and universals in language learning aptitude:53–64
Reiterer S, Pereda E, Bhattacharya J (2009) Measuring second language proficiency with EEG synchronization: how functional cortical networks and hemispheric involvement differ as a function of proficiency level in second language speakers. Second Lang Res 25:77–106
Salimi-Khorshidi G, Douaud G, Beckmann CF, Glasser MF, Griffanti L, Smith SM (2014) Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers. Neuroimage 90:449–468. https://doi.org/10.1016/j.neuroimage.2013.11.046
Schlegel AA, Rudelson JJ, Tse PU (2012) White matter structure changes as adults learn a second language. J Cogn Neurosci 24:1664–1670. https://doi.org/10.1162/jocn_a_00240
Siegmund J, Kästner C, Apel S, Parnin C, Bethmann A, Leich T, Saake G, Brechmann A (2014) Understanding understanding source code with functional magnetic resonance imaging. Paper presented at the Proceedings of the 36th International Conference on Software Engineering, Hyderabad, India, 2014, pp 378–389. doi:https://doi.org/10.1145/2568225.2568252
Siegmund J, Peitek N, Parnin C, Apel S, Hofmeister J, Kästner C, Begel A, Bethmann A, Brechmann A (2017) Measuring neural efficiency of program comprehension. Paper presented at the Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, Paderborn, Germany, 2017, pp 140–150. doi:https://doi.org/10.1145/3106237.3106268
Uwano H, Nakamura M, Monden A, Matsumoto K-i (2006) Analyzing individual performance of source code review using reviewers' eye movement. In: Proceedings of the 2006 symposium on Eye tracking research & applications, 2006. pp 133–140
Vessey I (1985) Expertise in debugging computer programs: a process analysis. Int J Man-Mach Stud 23:459–494
Von Mayrhauser A, Vans AM (1995) Program comprehension during software maintenance and evolution. Computer 28:44–55
Yamanishi J (2015) Report of research and study on programming education in foreign countries, Ministry of Education, Culture, Sports, Science and Technology (MEXT), 2014, Information Education Leadership Improvement Support Project, Syogaikoku ni okeru puroguramingu kyoiku ni kansuru tyosakenkyu, Monbukagakusyo heisei 26 nendo jyohokyoiku shidouryoku koujyo shienjigyo, Houkokusyo (in Japanese). https://www.mext.go.jp/a_menu/shotou/zyouhou/detail/__icsFiles/afieldfile/2018/08/10/programming_syogaikoku_houkokusyo.pdf
Yazbek S, Smayra T, Mallak I, Hage S, Sleilaty G, Atat C, Abdel Hay J, Moussa R (2020) Functional MRI study of language organization in left-handed and right-handed trilingual subjects. Sci Rep 10(1):13165. https://doi.org/10.1038/s41598-020-70167-y
Acknowledgements
We thank Dr. M. Abe for helpful discussion as well as H. Numazawa, A. Inoue, and the staff at the National Center of Neurology and Psychiatry for data acquisition. We would also like to thank Enago (www.enago.jp) for proofreading and editing this manuscript.
Funding
This study was supported by Grants-in-Aid for Scientific Research (KAKENHI) from the Japan Society for the Promotion of Science (Scientific Research C, 18K02589). TH also received grants from JSPS KAKENHI [Grant Numbers: JP19H05726 and JP19H03536m JP23H00414], AMED [Grant Numbers: JP18dm0207070, JP18dm0307003, and 18dm0307004], the Japan Science and Technology Agency (JST) Core Research for Evolutionary Science and Technology (CREST) Grant Number JP 21470534. KY also received grants from JSPS KAKENHI [Grant Numbers: 21K15679].
Author information
Authors and Affiliations
Contributions
TH, KY, HT, and TH participated in experimental design and data acquisition. KH, HT, and KY analyzed the data. KH, KY and TH interpreted the data and wrote the manuscript. All authors revised and approved the final version of the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Ethical approval
This study protocol was approved by Otsuma Women’s University Review Bord (29–002-2) and the National Center of Neurology and Psychiatry Review Board (a2017-021).
Consent to participate
Informed consent was obtained from all individual participants included in the study.
Consent to publish
The authors affirm that human research participants provided informed consent for publication of this study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Hishikawa, K., Yoshinaga, K., Togo, H. et al. Changes in functional brain activity patterns associated with computer programming learning in novices. Brain Struct Funct 228, 1691–1701 (2023). https://doi.org/10.1007/s00429-023-02674-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00429-023-02674-3