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Nörobilim ve Tasarımın Kesişim Noktaları: Nörotasarım Araştırmasının Kapsam İncelemesi

Yıl 2026, Sayı: 17 , 238 - 260 , 30.04.2026
https://doi.org/10.32739/etkilesim.2026.9.17.337
https://izlik.org/JA85XL96DX

Öz

Günümüzde tasarım araştırmalarında nörobilim temelli ölçüm araçlarının kullanımı, yaratıcı süreçleri yalnızca betimlemekle kalmayıp ölçülebilir değişkenler üzerinden tartışabilmeye imkân verdiği için her geçen gün önem kazanmaktadır. Tasarım uygulamalarında gözlem ve yoruma dayalı yaklaşımlar, fMRI, EEG ve göz izleme gibi bilişsel nörobilim yöntemleriyle problem çözme ve fikir üretmedeki dikkat, bellek, karar verme ve yaratıcılık süreçlerini daha somut inceleyerek kanıta dayalı bir çerçeveye yönelmektedir. Nörotasarım çalışmaları çerçevesinde kapsam analizi yöntemiyle hazırlanan bu çalışma, PRISMA-ScR ilkeleri doğrultusunda, tasarım alanında bilişsel nörobilim araçlarının kullanımına ilişkin literatürü kapsamlı biçimde taramayı amaçlamaktadır. Tarama sürecinde Scopus ve Web of Science veri tabanlarından 2009-2025 tarihleri kapsamında ‘neurodesign’ anahtar kelimesi kullanılarak veriler çıkarılmış, önceden belirlenen dahil etme/dışlama ölçütleriyle değerlendirme yapılmıştır. İncelemeye alınan çalışmalar, kullanılan araç/teknik (fMRI, EEG, göz izleme vb.), örneklem türü, görev türü ve ölçülen bilişsel işlevler gibi boyutlarda sınıflandırılmıştır. Bu sınıflandırma üzerinden alanın genel eğilimleri, kavramsal boşlukları ve tekrarlayan yöntemsel tercihleri tartışılmakta; ayrıca nörobilim bulgularının tasarım eğitimine ve profesyonel uygulamaya aktarılabilmesi için uygulanabilir öneriler sunulmaktadır. Sonuç olarak çalışma, gelecekte yürütülecek nörobilim temelli tasarım araştırmaları için hem yöntemsel bir yol haritası hem de kuramsal bir zemin önermeyi hedeflemektedir.

Kaynakça

  • Ahram, T., Falcão, C., Barros, R. Q., Soares, M. M., & Karwowski, W. (2016). Neurodesign: Applications of neuroscience in design and human–system interactions. In M. M. Soares & F. Rebelo (Eds.), Ergonomics in design: Methods & techniques. CRC Press. https://doi.org/10.1201/9781315367668
  • Alexiou, K., Zamenopoulos, T., Johnson, J. H., & Gilbert, S. J. (2009). Exploring the neurological basis of design cognition using brain imaging: Some preliminary results. Design Studies, 30(6), 623–647. https://doi.org/10.1016/j.destud.2009.05.002
  • Alsharif, A. H., & Isa, S. M. (2024). Electroencephalography studies on marketing stimuli: A literature review and future research agenda. International Journal of Consumer Studies, 49(1). https://doi.org/10.1111/ijcs.70015
  • Auernhammer, J., Sonalkar, N., & Saggar, M. (2021). NeuroDesign: From neuroscience research to design thinking practice. In C. Meinel & L. Leifer (Eds.), Design thinking research: Understanding innovation (pp. 347-355). Springer. https://doi.org/10.1007/978-3-030-62037-0_16
  • Auernhammer, J., Liu, W., Ohashi, T., Leifer, L., Byler, E., & Pan, W. (2021). NeuroDesign: Embracing neuroscience instruments to investigate human collaboration in design. In T. Ahram, R. Taiar, K. Langlois, & A. Choplin (Eds.), Human interaction, emerging technologies and future applications III (Advances in Intelligent Systems and Computing, Vol. 1253, pp. 284-289). Springer. https://doi.org/10.1007/978-3-030-55307-4_43
  • Auernhammer, J., Bruno, J., Booras, A., McIntyre, C., Hasegan, D., & Saggar, M. (2023). NeuroDesign: Greater than the sum of its parts. In C. Meinel & L. Leifer (Eds.), Design thinking research: Understanding innovation (pp. 197–211). Springer. https://doi.org/10.1007/978-3-030-55307-4_43
  • Balters, S., Weinstein, T., Mayseless, N., Auernhammer, J., Hawthorne, G., Steinert, M., Meinel, C., Leifer, L. J., & Reiss, A. L. (2023). Design science and neuroscience: A systematic review of the emergent field of design neurocognition. Design Studies, 84, 101148. https://doi.org/10.1016/j.destud.2022.101148
  • Chowdhury, A., & Chakraborty, P. (2021). Memes that evoke emotions: A neurodesign strategy for brand communication and experience. In Design for Tomorrow (Vol. 1, pp. 147–156). Springer. https://doi.org/10.1007/978-981-16-0041-8_13
  • Çaydere, O. (2015). Faculty and student opinions on graphic design programs (Unpublished doctoral thesis). Gazi University Institute of Educational Sciences.
  • Chenais, N., & Görgen, A. (2024). Immersive interfaces for clinical applications: Current status and future perspective. Frontiers in Neurorobotics, 18. https://doi.org/10.3389/fnbot.2024.1362444
  • Cutellic, P., & Lotte, F. (2013). Augmented iterations: Integrating neural activity in evolutionary computation for design. HAL Open Science.
  • Cutellic, P. (2014). Le cube d’après: Integrated cognition for iterative and generative designs. In Proceedings of the ACADIA Conference. https://doi.org/10.13140/RG.2.1.5186.5444
  • -------------- (2018). An event-based generative design software implementing fast discriminative cognitive responses from visual ERP BCI. In Human–computer interaction in design (Vol. 2, pp. 131-138). https://doi.org/10.52842/conf.ecaade.2018.2.131
  • --------------- (2019). Towards encoding shape features with visual event-related potential–based brain–computer interfaces for generative design. International Journal of Architectural Computing, 17(1). https://doi.org/10.1177/1478077119832465
  • Glimcher, P. W., & Rustichini, A. (2004). Neuroeconomics: The consilience of brain and decision. Science, 306(5695), 447–452. https://doi.org/10.1126/science.1102566
  • Goucher-Lambert, K., Moss, J., & Cagan, J. (2018). Inspired internal search: Using neuroimaging to understand design ideation and concept generation with inspirational stimuli. In Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. https://doi.org/10.1115/DETC2018-85690
  • Göktaş, O., Ergin, E., Çetin, G., Özkoç, H. H., Fırat, A., & Gazel, G. G. (2024). Investigation of user–product interaction by determining the focal points of visual interest in different types of kitchen furniture: An eye-tracking study. Displays, 83, 102745. https://doi.org/10.1016/j.displa.2024.102745
  • Hay, L., Duffy, A. H. B., Gilbert, S. J., Lyall, L., Campbell, G., Coyle, D., & Grealy, M. A. (2019). The neural correlates of ideation in product design engineering practitioners. Design Science, 5, e29. https://doi.org/10.1017/dsj.2019.27
  • Hermosilla, C., & Magal-Royo, T. (2022). User experience requirements for hyperloop passengers’ cabin. DYNA, 97(4). https://doi.org/10.6036/10480
  • Hevner, A. R., Davis, C., Collins, R. W., & Gill, T. G. (2014). A neurodesign model for IS research. Informing Science: The International Journal of an Emerging Transdiscipline, 17, 103–132.
  • Kirkland, L. (2012). Using neuroscience to inform your UX strategy and design. Retrieved May 14, 2025 from https://www.uxmatters.com/mt/archives/2012/07/using-neuroscience-to-inform-your-ux-strategy-and-design.php
  • Kwon, J., Linihan, S., Iedema, A., Schmidt, A., Luo, C., & Marrufo, K. (2023). How interior design responds to neurodiversity: Implementing wearable technologies in neurodesign processes. Frontiers in Built Environment, 9. https://doi.org/10.3389/fbuil.2023.1211519
  • Labrada, S. M., Fonseca, E. M., & Marquez-Barja, J. M. (2024). Requirement system for the interface design of applications for children with neurodevelopmental disorders. In Proceedings of the IEEE Global Engineering Education Conference (EDUCON). https://doi.org/10.1109/EDUCON60312.2024.10578799
  • Liu, Q., Huang, R., Zhu, R., & Chen, Y. (2024). Exploring neurodesign in cultivating empathy and creativity in primary education in China. https://doi.org/10.1145/3675094.3677596
  • Liu, W., Jin, Y., Li, B., Lyu, Z., Pan, W., Wang, N., & Zhao, X. (2020). NeuroDesign: Making decisions and solving problems through understanding of the human brain. In A. Marcus & E. Rosenzweig (Eds.), Human–computer interaction (LNCS Vol. 12200). Springer. https://doi.org/10.1007/978-3-030-49713-2_14
  • Liu, W., Lee, K. P., Gray, C. M., Toombs, A. L., Chen, K. H., & Leifer, L. (2021). Transdisciplinary teaching and learning in UX design: A program review and AR case studies. Applied Sciences, 11, 10648. https://doi.org/10.3390/app112210648
  • Lu, G., & Hou, G. (2020). Effects of semantic congruence on sign identification: An ERP study. Human Factors: The Journal of the Human Factors and Ergonomics Society, 62(5). https://doi.org/10.1177/0018720819854880
  • Ohashi, T., Auernhammer, J., Liu, W., Pan, W., & Leifer, L. (2022). NeuroDesignScience: Systematic literature review of current research on design using neuroscience techniques. In J. S. Gero (Ed.), Design computing and cognition ’20 (pp. 575–592). Springer. https://doi.org/10.1007/978-3-030-90625-2_34
  • Paoletti, A., & Imbesi, L. (2021). A neurodesign case study: Measuring the emotional index for redesign. Design Principles and Practices: An International Journal, 15(1), 33–44. https://doi.org/10.18848/1833-1874/CGP/v15i01/33-44
  • Ralph, P., & Wand, Y. (2009). A proposal for a formal definition of the design concept. In K. Lyytinen, P. Loucopoulos, J. Mylopoulos, & B. Robinson (Eds.), Design requirements engineering: A ten-year perspective (Lecture Notes in Business Information Processing, Vol. 14, pp. 103–136). Springer. https://doi.org/10.1007/978-3-540-92966-6_6
  • Salingaros, N. A. (2025a). Environments that boost creativity: AI-generated living geometry. Multimodal Technologies and Interaction, 9(38). https://doi.org/10.3390/mti9050038
  • ------------------------ (2025b). Façade psychology is hardwired: AI selects windows supporting health. Buildings, 15(1645). https://doi.org/10.3390/buildings15101645
  • Shealy, T., & Gero, J. S. (2019). The neurocognition of three engineering concept generation techniques. Proceedings of the Design Society: International Conference on Engineering Design, 1(1), 1833–1842. https://doi.org/10.1017/dsi.2019.189
  • Simon, H. A. (1977). The new science of management decision. MIT Press.
  • Sola, H. M., Qureshi, F. H., & Khawaja, S. (2025). Human-centered design meets AI-driven algorithms: Comparative analysis of political campaign branding in the Harris–Trump presidential campaigns. Informatics, 12(30). https://doi.org/10.3390/informatics12010030
  • Thienen, J. V., Borchart, K. P., Jaschek, C., Krebs, E., Hildebrand, J., Ratz, H., & Meinel, C. (2021). Leveraging video games to improve IT solutions for remote work. In Proceedings of the IEEE Conference on Games. IEEE. https://doi.org/10.1109/CoG52621.2021.9618986
  • Tricco, A. C., Lillie, E., Zarin, W., O’Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., Hempel, S., Akl, E. A., Chang, C., McGowan, J., Stewart, L., Hartling, L., Aldcroft, A., Wilson, M. G., Garritty, C., … Moher, D. (2018). PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Annals of Internal Medicine, 169(7), 467–473. https://doi.org/10.7326/M18-0850
  • Vartanian, O., Navarrete, G., Chatterjee, A., Fich, L. B., Gonzalez-Mora, J. L., Leder, H., Modroño, C., Nadal, M., Rostrup, N., & Skov, M. (2015). Architectural design and the brain: Effects of ceiling height and perceived enclosure on beauty judgments and approach–avoidance decisions. Journal of Environmental Psychology, 41, 10–18. https://doi.org/10.1016/j.jenvp.2014.11.006
  • Vecchiato, G., Astolfi, L., Fallani, F. D. V., Toppi, J., Aloise, F., Bez, F., Wei, D., Kong, W., Dai, J., Cincotti, F., Mattia, D., Babiloni, F., & Babiloni, C. (2011). On the use of EEG or MEG brain imaging tools in neuromarketing research. Computational Intelligence and Neuroscience, 2011, 643489. https://doi.org/10.1155/2011/643489
  • Vieira, S., Gero, J. S., Delmoral, J., Gattol, V., Fernandes, C., Parente, M., & Fernandes, A. A. (2020). The neurophysiological activations of mechanical engineers and industrial designers while designing and problem-solving. Design Science, 6, e26. https://doi.org/10.1017/dsj.2020.26
  • Zallio, M., Berry, D., & Leifer, L. J. (2020). Meaningful age-friendly design: Case studies on enabling assistive technology. In T. Ahram & C. Falcao (Eds.), Advances in usability and user experience (Advances in Intelligent Systems and Computing, Vol. 972, pp. 779–790). Springer. https://doi.org/10.1007/978-3-030-19135-1_76
  • Wang, R. W. Y., Ke, T. M., Chuang, S. W., & Liu, I. N. (2020). Sex differences in high-level appreciation of automobile design–evoked gamma broadband synchronisation. Scientific Reports, 10, 66515. https://doi.org/10.1038/s41598-020-66515-7
  • Wang, X., Huang, Y., Ma, Q., & Li, N. (2012). Event-related potential P2 correlates of implicit aesthetic experience. NeuroReport, 23(14), 862–866. https://doi.org/10.1097/WNR.0b013e3283587161

Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research

Yıl 2026, Sayı: 17 , 238 - 260 , 30.04.2026
https://doi.org/10.32739/etkilesim.2026.9.17.337
https://izlik.org/JA85XL96DX

Öz

Today, the use of neuroscience-based measurement tools in design research is gaining importance because they allow for discussing creative processes not only through description but also through measurable variables. Observational and interpretive approaches in design apolications are moving towards an evidence-based framework by examining attention, memory, decision-making, and creativity processes in problem-solving and idea generation more concretely using cognitive neuroscience methods such as fMRI, EEG, and eye-tracking. This study aims to review the literature comprehensively on the use of cognitive neuroscience tools in design, in accordance with the PRISMA-ScR principles. During the search process, data were extracted from the Scopus and Web of Science databases using the keyword ‘neurodesign’ for the years 2009-2025. After eliminating duplicate studies, evaluation was performed at the title-abstract and full-text stages using predefined inclusion/exclusion criteria. The studies reviewed were classified according to the tools/techniques used (fMRI, EEG, eye tracking, etc.), sample type (design student/professional designer), task type (idea generation, problem framing, evaluation, prototyping, etc.), and measured cognitive functions (attention, memory, problem solving, creativity). Based on this classification, general trends in the field, conceptual gaps, and recurring methodological choices are discussed; furthermore, feasible suggestions are offered for transferring neuroscience findings into design education and professional practice. In conclusion, the study aims to propose both a methodological roadmap and a theoretical foundation for future neuroscience-based design research.

Kaynakça

  • Ahram, T., Falcão, C., Barros, R. Q., Soares, M. M., & Karwowski, W. (2016). Neurodesign: Applications of neuroscience in design and human–system interactions. In M. M. Soares & F. Rebelo (Eds.), Ergonomics in design: Methods & techniques. CRC Press. https://doi.org/10.1201/9781315367668
  • Alexiou, K., Zamenopoulos, T., Johnson, J. H., & Gilbert, S. J. (2009). Exploring the neurological basis of design cognition using brain imaging: Some preliminary results. Design Studies, 30(6), 623–647. https://doi.org/10.1016/j.destud.2009.05.002
  • Alsharif, A. H., & Isa, S. M. (2024). Electroencephalography studies on marketing stimuli: A literature review and future research agenda. International Journal of Consumer Studies, 49(1). https://doi.org/10.1111/ijcs.70015
  • Auernhammer, J., Sonalkar, N., & Saggar, M. (2021). NeuroDesign: From neuroscience research to design thinking practice. In C. Meinel & L. Leifer (Eds.), Design thinking research: Understanding innovation (pp. 347-355). Springer. https://doi.org/10.1007/978-3-030-62037-0_16
  • Auernhammer, J., Liu, W., Ohashi, T., Leifer, L., Byler, E., & Pan, W. (2021). NeuroDesign: Embracing neuroscience instruments to investigate human collaboration in design. In T. Ahram, R. Taiar, K. Langlois, & A. Choplin (Eds.), Human interaction, emerging technologies and future applications III (Advances in Intelligent Systems and Computing, Vol. 1253, pp. 284-289). Springer. https://doi.org/10.1007/978-3-030-55307-4_43
  • Auernhammer, J., Bruno, J., Booras, A., McIntyre, C., Hasegan, D., & Saggar, M. (2023). NeuroDesign: Greater than the sum of its parts. In C. Meinel & L. Leifer (Eds.), Design thinking research: Understanding innovation (pp. 197–211). Springer. https://doi.org/10.1007/978-3-030-55307-4_43
  • Balters, S., Weinstein, T., Mayseless, N., Auernhammer, J., Hawthorne, G., Steinert, M., Meinel, C., Leifer, L. J., & Reiss, A. L. (2023). Design science and neuroscience: A systematic review of the emergent field of design neurocognition. Design Studies, 84, 101148. https://doi.org/10.1016/j.destud.2022.101148
  • Chowdhury, A., & Chakraborty, P. (2021). Memes that evoke emotions: A neurodesign strategy for brand communication and experience. In Design for Tomorrow (Vol. 1, pp. 147–156). Springer. https://doi.org/10.1007/978-981-16-0041-8_13
  • Çaydere, O. (2015). Faculty and student opinions on graphic design programs (Unpublished doctoral thesis). Gazi University Institute of Educational Sciences.
  • Chenais, N., & Görgen, A. (2024). Immersive interfaces for clinical applications: Current status and future perspective. Frontiers in Neurorobotics, 18. https://doi.org/10.3389/fnbot.2024.1362444
  • Cutellic, P., & Lotte, F. (2013). Augmented iterations: Integrating neural activity in evolutionary computation for design. HAL Open Science.
  • Cutellic, P. (2014). Le cube d’après: Integrated cognition for iterative and generative designs. In Proceedings of the ACADIA Conference. https://doi.org/10.13140/RG.2.1.5186.5444
  • -------------- (2018). An event-based generative design software implementing fast discriminative cognitive responses from visual ERP BCI. In Human–computer interaction in design (Vol. 2, pp. 131-138). https://doi.org/10.52842/conf.ecaade.2018.2.131
  • --------------- (2019). Towards encoding shape features with visual event-related potential–based brain–computer interfaces for generative design. International Journal of Architectural Computing, 17(1). https://doi.org/10.1177/1478077119832465
  • Glimcher, P. W., & Rustichini, A. (2004). Neuroeconomics: The consilience of brain and decision. Science, 306(5695), 447–452. https://doi.org/10.1126/science.1102566
  • Goucher-Lambert, K., Moss, J., & Cagan, J. (2018). Inspired internal search: Using neuroimaging to understand design ideation and concept generation with inspirational stimuli. In Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. https://doi.org/10.1115/DETC2018-85690
  • Göktaş, O., Ergin, E., Çetin, G., Özkoç, H. H., Fırat, A., & Gazel, G. G. (2024). Investigation of user–product interaction by determining the focal points of visual interest in different types of kitchen furniture: An eye-tracking study. Displays, 83, 102745. https://doi.org/10.1016/j.displa.2024.102745
  • Hay, L., Duffy, A. H. B., Gilbert, S. J., Lyall, L., Campbell, G., Coyle, D., & Grealy, M. A. (2019). The neural correlates of ideation in product design engineering practitioners. Design Science, 5, e29. https://doi.org/10.1017/dsj.2019.27
  • Hermosilla, C., & Magal-Royo, T. (2022). User experience requirements for hyperloop passengers’ cabin. DYNA, 97(4). https://doi.org/10.6036/10480
  • Hevner, A. R., Davis, C., Collins, R. W., & Gill, T. G. (2014). A neurodesign model for IS research. Informing Science: The International Journal of an Emerging Transdiscipline, 17, 103–132.
  • Kirkland, L. (2012). Using neuroscience to inform your UX strategy and design. Retrieved May 14, 2025 from https://www.uxmatters.com/mt/archives/2012/07/using-neuroscience-to-inform-your-ux-strategy-and-design.php
  • Kwon, J., Linihan, S., Iedema, A., Schmidt, A., Luo, C., & Marrufo, K. (2023). How interior design responds to neurodiversity: Implementing wearable technologies in neurodesign processes. Frontiers in Built Environment, 9. https://doi.org/10.3389/fbuil.2023.1211519
  • Labrada, S. M., Fonseca, E. M., & Marquez-Barja, J. M. (2024). Requirement system for the interface design of applications for children with neurodevelopmental disorders. In Proceedings of the IEEE Global Engineering Education Conference (EDUCON). https://doi.org/10.1109/EDUCON60312.2024.10578799
  • Liu, Q., Huang, R., Zhu, R., & Chen, Y. (2024). Exploring neurodesign in cultivating empathy and creativity in primary education in China. https://doi.org/10.1145/3675094.3677596
  • Liu, W., Jin, Y., Li, B., Lyu, Z., Pan, W., Wang, N., & Zhao, X. (2020). NeuroDesign: Making decisions and solving problems through understanding of the human brain. In A. Marcus & E. Rosenzweig (Eds.), Human–computer interaction (LNCS Vol. 12200). Springer. https://doi.org/10.1007/978-3-030-49713-2_14
  • Liu, W., Lee, K. P., Gray, C. M., Toombs, A. L., Chen, K. H., & Leifer, L. (2021). Transdisciplinary teaching and learning in UX design: A program review and AR case studies. Applied Sciences, 11, 10648. https://doi.org/10.3390/app112210648
  • Lu, G., & Hou, G. (2020). Effects of semantic congruence on sign identification: An ERP study. Human Factors: The Journal of the Human Factors and Ergonomics Society, 62(5). https://doi.org/10.1177/0018720819854880
  • Ohashi, T., Auernhammer, J., Liu, W., Pan, W., & Leifer, L. (2022). NeuroDesignScience: Systematic literature review of current research on design using neuroscience techniques. In J. S. Gero (Ed.), Design computing and cognition ’20 (pp. 575–592). Springer. https://doi.org/10.1007/978-3-030-90625-2_34
  • Paoletti, A., & Imbesi, L. (2021). A neurodesign case study: Measuring the emotional index for redesign. Design Principles and Practices: An International Journal, 15(1), 33–44. https://doi.org/10.18848/1833-1874/CGP/v15i01/33-44
  • Ralph, P., & Wand, Y. (2009). A proposal for a formal definition of the design concept. In K. Lyytinen, P. Loucopoulos, J. Mylopoulos, & B. Robinson (Eds.), Design requirements engineering: A ten-year perspective (Lecture Notes in Business Information Processing, Vol. 14, pp. 103–136). Springer. https://doi.org/10.1007/978-3-540-92966-6_6
  • Salingaros, N. A. (2025a). Environments that boost creativity: AI-generated living geometry. Multimodal Technologies and Interaction, 9(38). https://doi.org/10.3390/mti9050038
  • ------------------------ (2025b). Façade psychology is hardwired: AI selects windows supporting health. Buildings, 15(1645). https://doi.org/10.3390/buildings15101645
  • Shealy, T., & Gero, J. S. (2019). The neurocognition of three engineering concept generation techniques. Proceedings of the Design Society: International Conference on Engineering Design, 1(1), 1833–1842. https://doi.org/10.1017/dsi.2019.189
  • Simon, H. A. (1977). The new science of management decision. MIT Press.
  • Sola, H. M., Qureshi, F. H., & Khawaja, S. (2025). Human-centered design meets AI-driven algorithms: Comparative analysis of political campaign branding in the Harris–Trump presidential campaigns. Informatics, 12(30). https://doi.org/10.3390/informatics12010030
  • Thienen, J. V., Borchart, K. P., Jaschek, C., Krebs, E., Hildebrand, J., Ratz, H., & Meinel, C. (2021). Leveraging video games to improve IT solutions for remote work. In Proceedings of the IEEE Conference on Games. IEEE. https://doi.org/10.1109/CoG52621.2021.9618986
  • Tricco, A. C., Lillie, E., Zarin, W., O’Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., Hempel, S., Akl, E. A., Chang, C., McGowan, J., Stewart, L., Hartling, L., Aldcroft, A., Wilson, M. G., Garritty, C., … Moher, D. (2018). PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Annals of Internal Medicine, 169(7), 467–473. https://doi.org/10.7326/M18-0850
  • Vartanian, O., Navarrete, G., Chatterjee, A., Fich, L. B., Gonzalez-Mora, J. L., Leder, H., Modroño, C., Nadal, M., Rostrup, N., & Skov, M. (2015). Architectural design and the brain: Effects of ceiling height and perceived enclosure on beauty judgments and approach–avoidance decisions. Journal of Environmental Psychology, 41, 10–18. https://doi.org/10.1016/j.jenvp.2014.11.006
  • Vecchiato, G., Astolfi, L., Fallani, F. D. V., Toppi, J., Aloise, F., Bez, F., Wei, D., Kong, W., Dai, J., Cincotti, F., Mattia, D., Babiloni, F., & Babiloni, C. (2011). On the use of EEG or MEG brain imaging tools in neuromarketing research. Computational Intelligence and Neuroscience, 2011, 643489. https://doi.org/10.1155/2011/643489
  • Vieira, S., Gero, J. S., Delmoral, J., Gattol, V., Fernandes, C., Parente, M., & Fernandes, A. A. (2020). The neurophysiological activations of mechanical engineers and industrial designers while designing and problem-solving. Design Science, 6, e26. https://doi.org/10.1017/dsj.2020.26
  • Zallio, M., Berry, D., & Leifer, L. J. (2020). Meaningful age-friendly design: Case studies on enabling assistive technology. In T. Ahram & C. Falcao (Eds.), Advances in usability and user experience (Advances in Intelligent Systems and Computing, Vol. 972, pp. 779–790). Springer. https://doi.org/10.1007/978-3-030-19135-1_76
  • Wang, R. W. Y., Ke, T. M., Chuang, S. W., & Liu, I. N. (2020). Sex differences in high-level appreciation of automobile design–evoked gamma broadband synchronisation. Scientific Reports, 10, 66515. https://doi.org/10.1038/s41598-020-66515-7
  • Wang, X., Huang, Y., Ma, Q., & Li, N. (2012). Event-related potential P2 correlates of implicit aesthetic experience. NeuroReport, 23(14), 862–866. https://doi.org/10.1097/WNR.0b013e3283587161
Toplam 43 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İletişim Çalışmaları
Bölüm Araştırma Makalesi
Yazarlar

Simge Kırteke 0000-0003-0621-8177

Ertan Toy 0000-0002-7959-7967

Gönderilme Tarihi 23 Kasım 2025
Kabul Tarihi 22 Ocak 2026
Yayımlanma Tarihi 30 Nisan 2026
DOI https://doi.org/10.32739/etkilesim.2026.9.17.337
IZ https://izlik.org/JA85XL96DX
Yayımlandığı Sayı Yıl 2026 Sayı: 17

Kaynak Göster

APA Kırteke, S., & Toy, E. (2026). Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research. Etkileşim, 17, 238-260. https://doi.org/10.32739/etkilesim.2026.9.17.337
AMA 1.Kırteke S, Toy E. Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research. Etkileşim. 2026;(17):238-260. doi:10.32739/etkilesim.2026.9.17.337
Chicago Kırteke, Simge, ve Ertan Toy. 2026. “Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research”. Etkileşim, sy 17: 238-60. https://doi.org/10.32739/etkilesim.2026.9.17.337.
EndNote Kırteke S, Toy E (01 Nisan 2026) Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research. Etkileşim 17 238–260.
IEEE [1]S. Kırteke ve E. Toy, “Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research”, Etkileşim, sy 17, ss. 238–260, Nis. 2026, doi: 10.32739/etkilesim.2026.9.17.337.
ISNAD Kırteke, Simge - Toy, Ertan. “Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research”. Etkileşim. 17 (01 Nisan 2026): 238-260. https://doi.org/10.32739/etkilesim.2026.9.17.337.
JAMA 1.Kırteke S, Toy E. Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research. Etkileşim. 2026;:238–260.
MLA Kırteke, Simge, ve Ertan Toy. “Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research”. Etkileşim, sy 17, Nisan 2026, ss. 238-60, doi:10.32739/etkilesim.2026.9.17.337.
Vancouver 1.Simge Kırteke, Ertan Toy. Intersections of Neuroscience and Design: A Scoping Review of Neurodesign Research. Etkileşim. 01 Nisan 2026;(17):238-60. doi:10.32739/etkilesim.2026.9.17.337