Every Brain Has a Cognitive Pattern
From taste and perception to cognitive compatibility in intelligent interface design
References The following references were used to distinguish established findings from this article’s hypotheses and proposals.
[1] Kozhevnikov, M., Evans, C., & Kosslyn, S. M. (2014). Cognitive Style as Environmentally Sensitive Individual Differences in Cognition: A Modern Synthesis and Applications in Education, Business, and Management. Psychological Science in the Public Interest, 15(1), 3-33. https://doi.org/10.1177/1529100614525555
[2] Blazhenkova, O., & Kozhevnikov, M. (2009). The new object-spatial-verbal cognitive style model: Theory and measurement. Applied Cognitive Psychology, 23(5), 638-663. https://doi.org/10.1002/acp.1473
[3] Kozhevnikov, M., Hegarty, M., & Mayer, R. E. (2002). Revising the Visualizer-Verbalizer Dimension: Evidence for Two Types of Visualizers. Cognition and Instruction, 20(1), 47-77. https://doi.org/10.1207/S1532690XCI2001_3
[4] Finn, E. S., Shen, X., Scheinost, D., et al. (2015). Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nature Neuroscience, 18, 1664-1671. https://doi.org/10.1038/nn.4135
[5] Schulz, M.-A., Baier, S., Timmermann, B., Bzdok, D., & Witt, K. (2021). A cognitive fingerprint in human random number generation. Scientific Reports, 11. https://doi.org/10.1038/s41598-021-98315-y
[6] Breit, M., Scherrer, V., Tucker-Drob, E. M., & Preckel, F. (2024). The Stability of Cognitive Abilities: A Meta-Analytic Review of Longitudinal Studies. Psychological Bulletin, 150(4), 399-439. https://doi.org/10.1037/bul0000425
[7] Winawer, J., Witthoft, N., Frank, M. C., Wu, L., Wade, A. R., & Boroditsky, L. (2007). Russian blues reveal effects of language on color discrimination. Proceedings of the National Academy of Sciences, 104(19), 7780-7785. https://doi.org/10.1073/pnas.0701644104
[8] Martinovic, J., Paramei, G. V., & MacInnes, W. J. (2020). Russian blues reveal the limits of language influencing colour discrimination. Cognition, 201, 104281. https://doi.org/10.1016/j.cognition.2020.104281
[9] Kearins, J. M. (1981). Visual spatial memory in Australian Aboriginal children of desert regions. Cognitive Psychology, 13(3), 434-460. https://doi.org/10.1016/0010-0285(81)90017-7
[10] Kearins, J. (1986). Visual spatial memory in Aboriginal and White Australian children. Australian Journal of Psychology, 38(3), 203-214. https://doi.org/10.1080/00049538608259009
[11] King, M. J., Katz, D. P., Thompson, L. A., & Macnamara, B. N. (2019). Genetic and environmental influences on spatial reasoning: A meta-analysis of twin studies. Intelligence, 73, 65-77. https://doi.org/10.1016/j.intell.2019.01.001
[12] Gero, J. S., & Kannengiesser, U. (2004). The situated function-behaviour-structure framework. Design Studies, 25(4), 373-391. https://doi.org/10.1016/j.destud.2003.10.010
[13] Dorst, K., & Cross, N. (2001). Creativity in the design process: co-evolution of problem-solution. Design Studies, 22(5), 425-437. https://doi.org/10.1016/S0142-694X(01)00009-6
[14] Jansson, D. G., & Smith, S. M. (1991). Design fixation. Design Studies, 12(1), 3-11. https://doi.org/10.1016/0142-694X(91)90003-F
[15] Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. (2006). Attention web designers: You have 50 milliseconds to make a good first impression! Behaviour & Information Technology, 25(2), 115-126. https://doi.org/10.1080/01449290500330448
[16] Brown, A., & Maydeu-Olivares, A. (2011). Item Response Modeling of Forced-Choice Questionnaires. Educational and Psychological Measurement, 71(3), 460-502. https://doi.org/10.1177/0013164410375112
[17] Qin, W., Zheng, Y., Kai, L., Yan, C., Siwei, P., & Dongbo, T. (2024). Item selection methods in multidimensional computerized adaptive testing for forced-choice items using Thurstonian IRT model. Behavior Research Methods, 56, 600-614. https://doi.org/10.3758/s13428-022-02037-6
[18] National Eye Institute. Types of Color Vision Deficiency. U.S. National Institutes of Health. https://www.nei.nih.gov/eye-health-information/eye-conditions-and-diseases/color-blindness/types-color-vision-deficiency
[19] Vessey, I. (1991). Cognitive Fit: A Theory-Based Analysis of the Graphs Versus Tables Literature. Decision Sciences, 22(2), 219-240. https://doi.org/10.1111/j.1540-5915.1991.tb00344.x
[20] Frias-Martinez, E., Chen, S. Y., & Liu, X. (2007). Automatic cognitive style identification of digital library users for personalization. Journal of the American Society for Information Science and Technology, 58(2), 237-251. https://doi.org/10.1002/asi.20477
[21] Hauser, J. R., Urban, G. L., Liberali, G., & Braun, M. (2009). Website Morphing. Marketing Science, 28(2), 202-223. https://doi.org/10.1287/mksc.1080.0459
[22] Papatheocharous, E., Belk, M., Germanakos, P., & Samaras, G. (2012). On Modelling Cognitive Styles of Users in Adaptive Interactive Systems using Artificial Neural Networks. In Proceedings of the 4th International Joint Conference on Computational Intelligence (NCTA-2012), 563-569. https://doi.org/10.5220/0004158905630569
[23] Belk, M., Fidas, C., Germanakos, P., & Samaras, G. (2015). Do human cognitive differences in information processing affect preference and performance of CAPTCHA? International Journal of Human-Computer Studies, 84, 1-18. https://doi.org/10.1016/j.ijhcs.2015.07.002
[24] Leung, S.-W., Lee, J., Johnson, C., & Robertson, D. (2012). Design preferences and cognitive styles: experimentation by automated website synthesis. Automated Experimentation, 4, 2. https://doi.org/10.1186/1759-4499-4-2
[25] Peng, Y.-H., Das, S., Bigham, J. P., & Wu, J. (2026). Efficient Personalization of Generative User Interfaces. arXiv:2604.09876. https://arxiv.org/abs/2604.09876