Hostname: page-component-76fb5796d-5g6vh Total loading time: 0 Render date: 2024-04-26T00:45:24.134Z Has data issue: false hasContentIssue false

BRAIN ACTIVITY OF INDUSTRIAL DESIGNERS IN CONSTRAINED AND OPEN DESIGN: THE EFFECT OF GENDER ON FREQUENCY BANDS

Published online by Cambridge University Press:  27 July 2021

Sonia Liliana da Silva Vieira*
Affiliation:
Politecnico di Milano, Italy
Mathias Benedek
Affiliation:
Karl-Franzens-Universität Graz, Austria
John S. Gero
Affiliation:
University of North Carolina at Charlotte, NC, United States
Gaetano Cascini
Affiliation:
Politecnico di Milano, Italy
Shumin Li
Affiliation:
Politecnico di Milano, Italy
*
Vieira, Sonia Liliana da Silva, University of Porto, INEGI, Portugal, vieirasonia88@gmail.com

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In this paper, we present results from an experiment using EEG to measure brain activity and explore EEG frequency power associated with gender differences of professional industrial designers while performing two prototypical stages of constrained and open design tasks, problem-solving and design sketching. Results indicate no main effect of gender. However, among other main effects, a consistent main effect of hemisphere for the six frequency bands under analysis was found. In the problem-solving stage, male designers show higher alpha and beta bands in channels of the prefrontal cortices and female designers in the right occipitotemporal cortex and secondary visual cortices. In the design sketching stage, male designers show higher alpha and beta bands in the right prefrontal cortex, and female designers in the right temporal cortex and left prefrontal cortex, where higher theta is also found. Prioritising different cognitive functions seem to play a role in each gender's approach to constrained and open design tasks. Results can be useful to design professionals, students and design educators, and for the development of methodological approaches in design research and education.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

References

Abraham, A. (2016). “Gender and creativity: An overview of psychological and neuroscientific literature”, Brain Imaging & Behavior, Vol. 2, pp. 609618.CrossRefGoogle Scholar
Abra, J. C. & Valentine-French, S. (1991). “Gender differences in creative achievement: A survey of explanations”, Genetic, Social, and General Psychology Monographs, Vol. 117, pp. 233284.Google ScholarPubMed
Alexiou, K, Zamenopoulos, T, Johnson, J, Gilbert, S. (2009). “Exploring the neurological basis of design cognition using brain imaging: some preliminary results”, Design Studies, Vol. 30(6), pp. 623647.10.1016/j.destud.2009.05.002CrossRefGoogle Scholar
Bazar, E., Bazar-Eroglu, C., Karakas, S., Schurmann, M. (1999). “Are cognitive processes manifested in eventrelated gamma, alpha, theta and delta oscillations in the EEG?”, Neuroscience Letters, Vol.259, pp. 165168.10.1016/S0304-3940(98)00934-3CrossRefGoogle Scholar
Baer, J., and Kaufman, J. (2008). “Gender differences in creativity”, Journal of Creative Behavior, Vol.42(2), pp. 75105.10.1002/j.2162-6057.2008.tb01289.xCrossRefGoogle Scholar
Benedek, M., & Fink, A. (2020). “Neuroscience: EEG”, In: M., Runco, M. & Pritzker, S. (Eds.), Encyclopedia of Creativity, 3rd edition, Vol. 2. Elsevier, Academic Press, pp. 216220.CrossRefGoogle Scholar
Crozier, S., Sirigu, A., Lehéricy, S., van de Moortele, P., Pillon, B., Grafman, J., Agid, Y., Dubois, B., LeBihan, D. (1999). “Distinct prefrontal activations in processing sequence at the sentence and script level: an fMRI study”, Neuropsychologia, Vol. 37(13), pp. 14691476.10.1016/S0028-3932(99)00054-8CrossRefGoogle Scholar
De Clercq, W., Vergult, A., Vanrumste, B., Van Paesschen, W., Van Huffel, S. (2006). “Canonical correlation analysis applied to remove muscle artifacts from the electroencephalogram.” IEEE Transactions on Biomedical Engineering, Vol.53, pp. 25832587.10.1109/TBME.2006.879459CrossRefGoogle ScholarPubMed
Fincham, J., Carter, C., van Veen, V., Stenger, V., Anderson, J. (2002). “Neural mechanisms of planning: a computational analysis using event-related fMRI.” Proc Natl Acad Sci USA, Vol. 99(5), pp.33463351.10.1073/pnas.052703399CrossRefGoogle ScholarPubMed
Fink, A., & Neubauer, A. (2006). EEG alpha oscillations during the performance of verbal creativity tasks: differential effects of sex and verbal intelligence. Int J Psychophysiology, 62 (1), 4653.10.1016/j.ijpsycho.2006.01.001CrossRefGoogle ScholarPubMed
Furnham, A., Fong, G., & Martin, N. (1999). “Sex and cross-cultural differences in the estimated multifaceted intelligence quotient score for self, parents and siblings”, Personality and Individual Differences, Vol. 26, pp. 10251034.10.1016/S0191-8869(98)00201-3CrossRefGoogle Scholar
Goel, V., Gold, B., Kapur, S., & Houle, S. (1998). “Neuroanatomical correlates of human reasoning”, J Cogn Neurosci. Vol. (3), pp. 293302.10.1162/089892998562744CrossRefGoogle Scholar
Goel, V., Gold, B., Kapur, S., Houle, S. (1997). “The seats of reason? An imaging study of deductive and inductive reasoning”, Neuroreport. Vol. 8(5), pp. 13051310.10.1097/00001756-199703240-00049CrossRefGoogle ScholarPubMed
Goel, V., Pirolli, P. (1992). “The structure of design problem spaces”, Cognitive Science, Vol. 16, pp. 395429.10.1207/s15516709cog1603_3CrossRefGoogle Scholar
Göker, M. (1997). “The effects of experience during design problem solving”, Design Studies, Vol. 18, pp. 405426.10.1016/S0142-694X(97)00009-4CrossRefGoogle Scholar
Harrington, G., Farias, D., Davis, C., Buonocore, M. (2007). “Comparison of the neural basis for imagined writing and drawing”, Hum Brain Mapp, Vol. 28(5), pp.450459.10.1002/hbm.20286CrossRefGoogle ScholarPubMed
Karwowski, M. (2011). “It doesn't hurt to ask. But sometimes it hurts to believe: Polish students’ creative selfefficacy and its predictors”, Psychology of Aesthetics, Creativity, and the Arts, Vol. 5, pp.154164.CrossRefGoogle Scholar
Kübler, A, Dixon, V, Garavan, H. (2006). “Automaticity and reestablishment of executive control-an fMRI study”, J Cogn Neurosci. Vol. 18(8), pp. 13311342.10.1162/jocn.2006.18.8.1331CrossRefGoogle ScholarPubMed
Le, T., Pardo, P., Hu, X. (1998). “4 T-fMRI study of Nonspatial Shifting of Selective Attention: Cerebellar and Parietal Contributions”, The American Physiological Society, Vol. 79(3), pp. 15351548.Google ScholarPubMed
Liang, C., Chang, C., Liu, Y. (2018). “Comparison of the cerebral activities exhibited by expert and novice visual communication designers during idea incubation”, International Journal of Design Creativity and Innovation, Vol. 7(4), pp. 213236.10.1080/21650349.2018.1562995CrossRefGoogle Scholar
Liang, C., Lin, C., Yao, C., Chang, W., Liu, Y., Chen, S. (2017). “Visual attention and association: An electroencephalography study in expert designers”, Design Studies, Vol. 48, pp.7695.10.1016/j.destud.2016.11.002CrossRefGoogle Scholar
Liu, L., Nguyen, T., Zeng, Y., Ben Hamza, A. (2016). “Identification of Relationships Between Electroencephalography (EEG) Bands and Design Activities”, ASME 2016 IDETC and CIEC. Vol. 7: 28th ICDTM. Charlotte, NC, USA, August 2124.Google Scholar
Liu, L., Li, Y., Xiong, Y., Cao, J., Yuan, P. (2018). “An EEG study of the relationship between design problem statements and cognitive behaviors during conceptual design”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 32, pp.351362.CrossRefGoogle Scholar
Marsh, R., Zhu, H., Schultz, R., Quackenbush, G., Royal, J., Skudlarski, P., Peterson, B. (2006). “A developmental fMRI study of self-regulatory control”, Hum Brain Mapp. Vol. 27(11), pp. 848863.10.1002/hbm.20225CrossRefGoogle ScholarPubMed
Martindale, C. & Hines, D. (1975). “Creativity and cortical activation during creative, intellectual and EEG feedback tasks”, Biological Psychology, Vol. 3, pp. 91100.10.1016/0301-0511(75)90011-3CrossRefGoogle ScholarPubMed
Martindale, C. & Hasenfus, N. (1978). “EEG differences as a function of creativity, stage of the creative process, and effort to be original”, Biological Psychology, Vol. 6(3), pp. 157167.10.1016/0301-0511(78)90018-2CrossRefGoogle ScholarPubMed
Nagornova, V. (2007). “Changes in the EEG power during tests for nonverbal (figurative) creativity”, Human Physiology, Vol. 33 (3), pp. 277284.10.1134/S0362119707030036CrossRefGoogle Scholar
Pekkola, J., Ojanen, V., Autti, T., Jääskeläinen, I.P., Möttönen, R., Tarkiainen, A., Sams, M. (2005). “Primary auditory cortex activation by visual speech: an fMRI study at 3 T”, Neuroreport, Vol. 16(2), pp.125128.10.1097/00001756-200502080-00010CrossRefGoogle ScholarPubMed
Pidgeon, L., Grealy, M., Duffy, A., Hay, L., McTeague, C., Vuletic, T., Coyle, D., Gilbert, S. (2016). “Functional neuroimaging of visual creativity: a systematic review and meta-analysis”, Brain and Behavior, Vol. 6(10), pp. 126.10.1002/brb3.540CrossRefGoogle ScholarPubMed
Platel, H., Price, C., Baron, J., Wise, R., Lambert, J., Frackowiak, R., Lechevalier, B., Eustache, F. (1997). “The structural components of music perception. A functional anatomical study”, Brain, Vol. 120(2), pp. 229243.10.1093/brain/120.2.229CrossRefGoogle ScholarPubMed
Rapp, A.M., Leube, D.T., Erb, M., Grodd, W., & Kircher, T.T. (2004). “Neural correlates of metaphor processing”, Cogn Brain Res. Vol. 20(3), pp. 395402.10.1016/j.cogbrainres.2004.03.017CrossRefGoogle ScholarPubMed
Razumnikova, O. M. (2004). “Gender differences in hemispheric organization during divergent thinking: an EEG investigation in human subjects”, Neuroscience Letters, Vol. 362(3), pp. 193195.10.1016/j.neulet.2004.02.066CrossRefGoogle ScholarPubMed
Rizzolatti, G., Fadiga, L., Matelli, M., Bettinardi, V., Paulesu, E., Perani, D., Fazio, F. (1996). “Localization of grasp representations in humans by PET: 1. Observation versus execution”, Exp Brain Res. Vol. 111(2), pp. 246252.10.1007/BF00227301CrossRefGoogle ScholarPubMed
Ruth, J. & Birren, J. (1985). “Creativity in adulthood and old age: Relations to intelligence, sex and mode of testing”, International Journal of Behavioral Development, Vol. 8, pp. 99109.10.1177/016502548500800107CrossRefGoogle Scholar
Shibata, M., Abe, J., Terao, A., Miyamoto, T. (2007). “Neural mechanisms involved in the comprehension of metaphoric and literal sentences: an fMRI study”, Brain Res. Vol. 1166, pp. 92102.CrossRefGoogle Scholar
Slotnick, S., Moo, L. (2006). “Prefrontal cortex hemispheric specialization for categorical and coordinate visual spatial memory”, Neuropsychologia, Vol. 44 (9), pp. 15601568.10.1016/j.neuropsychologia.2006.01.018CrossRefGoogle ScholarPubMed
Stevens, C. & Zabelina, D. (2019). “Creativity comes in waves: An EEG-focused exploration of the creative brainCurrent Opinion in Behavioral Sciences, Vol. 27, pp. 154162.10.1016/j.cobeha.2019.02.003CrossRefGoogle Scholar
Vieira, S., Gero, J., Delmoral, J., Gattol, V., Fernandes, C., Parente, M., Fernandes, A. (2020a). “The neurophysiological activations of mechanical engineers and industrial designers while designing and problem-solving”, Design Science, Vol. 6(e26), pp. 135.10.1017/dsj.2020.26CrossRefGoogle Scholar
Vieira, S., Gero, J., Gattol, V., Delmoral, J., Li, S., Cascini, G., Fernandes, A. (2020a). “Designing-related neural processes: Higher alpha, theta and beta bands’ key roles in distinguishing designing from problem-solving”, Design Computing and Cognition DCC'20.Google Scholar
Vieira, S., Gero, J. S., Delmoral, J., Fernandes, A. (2020c). “Brain activity in constrained and open design spaces: an EEG study”, International Conference on Design Creativity, August 2020, Finland.10.35199/ICDC.2020.09CrossRefGoogle Scholar
Vieira, S., Gero, J., Delmoral, J., Gattol, V., Fernandes, C., Fernandes, A. (2019a). “Understanding the design neurocognition of mechanical engineers when designing and problem-solving,” ASME IDETC.10.1115/DETC2019-97838CrossRefGoogle Scholar
Vieira, S., Gero, J., Delmoral, J., Gattol, V., Fernandes, C., Fernandes, A. (2019b). “Comparing the design neurocognition of mechanical engineers and architects: A study of the effect of designer's domain”, in Proceedings of the 22nd International Conference on Engineering Design.10.1017/dsi.2019.191CrossRefGoogle Scholar
Visser, W. (2009). “Design: one, but in different forms”, Design Studies, Vol. 30(3), pp. 187223.10.1016/j.destud.2008.11.004CrossRefGoogle Scholar
Waberski, T., Gobbele, R., Lamberty, K., Buchner, H., Marshall, J., Fink, G. (2008). “Timing of visuo-spatial information processing: Electrical source imaging related to line bisection judgements”, Neuropsychologia, Vol. 46, pp. 12011210.10.1016/j.neuropsychologia.2007.10.024CrossRefGoogle ScholarPubMed