Opinion paper Topical Sections

Using neuroscience techniques to understand and improve design cognition

Running title: Neuroscience and design
  • Received: 14 July 2020 Accepted: 18 August 2020 Published: 24 August 2020
  • Cognitive neuroscience research has traditionally focused on understanding the brain mechanisms that enable cognition by means of experimental laboratory tasks. With a budding literature, there is growing interest in the application of the related methods and findings to real-world settings. In this opinion paper we explore the potential and promise of employing current cognitive neuroscience methodologies in the field of design. We review recent evidence from preliminary studies that have employed such methods toward identifying the neural bases of design thinking and discuss their impact and limitations. Further, we highlight the importance of pairing neuroscience methods with well-established behavioral paradigms during ecologically-valid, real-world design tasks. Experimental investigations that meet these requirements can generate powerful datasets of neurocognitive measures that can offer new insights into the complex cognitive and brain systems enabling design thinking. We argue that this new knowledge can lead to the development and implementation of new techniques toward cultivating and improving design thinking in design education and professional practice.

    Citation: Evangelia G. Chrysikou, John S. Gero. Using neuroscience techniques to understand and improve design cognition[J]. AIMS Neuroscience, 2020, 7(3): 319-326. doi: 10.3934/Neuroscience.2020018

    Related Papers:

  • Cognitive neuroscience research has traditionally focused on understanding the brain mechanisms that enable cognition by means of experimental laboratory tasks. With a budding literature, there is growing interest in the application of the related methods and findings to real-world settings. In this opinion paper we explore the potential and promise of employing current cognitive neuroscience methodologies in the field of design. We review recent evidence from preliminary studies that have employed such methods toward identifying the neural bases of design thinking and discuss their impact and limitations. Further, we highlight the importance of pairing neuroscience methods with well-established behavioral paradigms during ecologically-valid, real-world design tasks. Experimental investigations that meet these requirements can generate powerful datasets of neurocognitive measures that can offer new insights into the complex cognitive and brain systems enabling design thinking. We argue that this new knowledge can lead to the development and implementation of new techniques toward cultivating and improving design thinking in design education and professional practice.


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    Acknowledgments



    Dr. Gero is funded by the National Science Foundation, Grant No. EEC-1929896. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

    Conflict of interest



    Both authors declare no conflicts of interest in this paper.

    [1] Chrysikou EG, Berryhill ME, Bikson M, et al. (2017) Editorial: Revisiting the effectiveness of transcranial direct current brain stimulation for cognition: Evidence, challenges, and open questions. Front Hum Neurosci 11: Article 448. doi: 10.3389/fnhum.2017.00448
    [2] Simon HA (1969)  The Sciences of the Artificial Cambridge: MIT Press.
    [3] Kannengiesser U, Gero JS (2019) Design thinking, fast and slow: A framework for Kahneman's dual-system theory in design. Des Sci 5. doi: 10.1017/dsj.2019.9
    [4] Chrysikou EG (2014) Creative states: A cognitive neuroscience approach to understanding and improving creativity in design. Studying Visual and Spatial Reasoning for Design Creativity New York, NY: Springer, 227-243.
    [5] Gero JS, Jiang H, Williams C (2013) Design cognition differences when using unstructured, partially structured and structured concept generation creativity techniques. Int J Des Creativity Innov 1: 196-214. doi: 10.1080/21650349.2013.801760
    [6] Crutcher RJ (1994) Telling what we know: The use of verbal report methodologies in psychological research. Psychol Sci 5: 241-244. doi: 10.1111/j.1467-9280.1994.tb00619.x
    [7] Ericsson K, Simon H (1993)  Protocol Analysis: Verbal Reports as Data MIT Press. doi: 10.7551/mitpress/5657.001.0001
    [8] Kan JWT, Gero JS (2017)  Quantitative Methods for Studying Design Protocols Dordrecht: Springer.
    [9] Vieira S, Gero JS, Delmoral J, et al. (2019) Understanding the design neurocognition of mechanical engineers when designing and problem-solving. ASME IDETC paper IDETC2019-97838.
    [10] Gero JS, Milovanovic J (2020) A framework for studying design thinking through measuring designers' minds, bodies and brains. Des Sci 6: e19. doi: 10.1017/dsj.2020.15
    [11] Bassett D, Sporns O (2017) Network neuroscience. Nat Neurosci 20: 353-364. doi: 10.1038/nn.4502
    [12] Alexiou K, Zamenopoulos T, Johnson J, et al. (2009) Exploring the neurological basis of design cognition using brain imaging: some preliminary results. Des Stud 30: 623-647. doi: 10.1016/j.destud.2009.05.002
    [13] Goucher-Lambert K, Moss J, Cagan J (2019) A neuroimaging investigation of design ideation with and without inspirational stimuli—understanding the meaning of near and far stimuli. Des Stud 60: 1-38. doi: 10.1016/j.destud.2018.07.001
    [14] Ellamil M, Dobson C, Beeman M, et al. (2012) Evaluative and generative modes of thought during the creative process. Neuroimage 59: 1783-1794. doi: 10.1016/j.neuroimage.2011.08.008
    [15] Bermudez J, Krizaj D, Lipschitz C, et al. (2017) Externally-induced meditative states: an exploratory fMRI study of architects' responses to contemplative architecture. Front Archit Res 6: 123-136. doi: 10.1016/j.foar.2017.02.002
    [16] Liu L, Li Y, Xiong Y, et al. (2018) An EEG study of the relationship between design problem statements and cognitive behaviors during conceptual design. Artif Intell Eng Des Anal Manuf 32: 351-362. doi: 10.1017/S0890060417000683
    [17] Nguyen P, Nguyen T, Zeng Y (2017) Empirical approaches to quantifying effort, fatigue and concentration in the conceptual design process: An EEG study. Res Eng Des 29: 393-409. doi: 10.1007/s00163-017-0273-4
    [18] Liang C, Lin C, Yao C, et al. (2017) Visual attention and association: An electroencephalography study in expert designers. Des Stud 48: 76-95. doi: 10.1016/j.destud.2016.11.002
    [19] Shealy T, Gero J (2019) .
    [20] Shealy T, Hu M, Gero J (2018)  Patterns of cortical activation when using concept generation techniques of brainstorming, morphological analysis, and TRIZ.
    [21] Borgianni Y, Maccioni L (2020) Review of the use of neurophysiological and biometric measures in experimental design research. Artif Intell Eng Des Anal Manuf 34: 248-285. doi: 10.1017/S0890060420000062
    [22] Clancey WJ (1997)  Situated Cognition: On Human Knowledge and Computer Representations Cambridge: Cambridge University Press.
    [23] Limb C, Braun A (2008) Neural substrates of spontaneous musical performance: An fMRI study of jazz improvisation. PLoS One 3: e1679. doi: 10.1371/journal.pone.0001679
    [24] Chrysikou EG, Thompson-Schill SL (2011) Dissociable brain states linked to common and creative object use. Hum Brain Mapp 32: 665-675. doi: 10.1002/hbm.21056
    [25] Matheson HE, Buxbaum LJ, Thompson-Schill SL (2017) Differential tuning of ventral and dorsal streams during the generation of common and uncommon tool uses. J Cogn Neurosci 29: 1791-1802. doi: 10.1162/jocn_a_01161
    [26] Moss J, Schunn CD (2015) Comprehension through explanation as the interaction of the brain's coherence and cognitive control networks. Front Hum Neurosci 9: Article 562. doi: 10.3389/fnhum.2015.00562
    [27] Moss J, Schunn CD, Schneider W, et al. (2013) The nature of mind wandering during reading varies with the cognitive control demands of the reading strategy. Brain Res 1539: 48-60. doi: 10.1016/j.brainres.2013.09.047
    [28] Moss J, Schunn CD, Schneider W, et al. (2011) The neural correlates of strategic reading comprehension: Cognitive control and discourse comprehension. Neuroimage 58: 675-686. doi: 10.1016/j.neuroimage.2011.06.034
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