Abstract
This paper presents an empirical study that examines how human cognitive style affects brain signal activity when individuals engage in a visual content comprehension task. To facilitate this study, we adopted an accredited cognitive style framework (Field Dependent-Field Independent or FD-FI) and utilized a validated cognitive style elicitation task, namely the Group Embedded Figures Test (GEFT), to elicit visual content comprehension via static figures. Brain signal activity was captured through a high-precision EEG device and subsequently correlated with the GEFT-derived cognitive style. Furthermore, power spectral analysis allowed the observation of potential differences between the two cognitive style groups. Analysis of results yields different effects on FD and FI users and especially in the average power of brain signals in the cortical area. Identifying such brain signal variations between FD-FI users might lay the ground for designing novel real-time elicitation frameworks of human cognitive styles, thus providing innovative personalization and adaptation approaches in a variety of application domains.
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Acknowledgments
This work has been financially supported by the Hellenic Foundation for Research & Innovation (HFRI) under the 2nd Call for proposals for H.F.R.I. Research Projects to Support Faculty Members and Researchers, under the project entitled Electroencephalography and Eye Gaze driven Framework for Intelligent and Real-Time Human Cognitive Modelling (CogniX) with Proposal ID 3849.
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Trigka, M., Papadoulis, G., Dritsas, E., Fidas, C. (2023). Influences of Cognitive Styles on EEG-Based Activity: An Empirical Study on Visual Content Comprehension. In: Abdelnour Nocera, J., Kristín Lárusdóttir, M., Petrie, H., Piccinno, A., Winckler, M. (eds) Human-Computer Interaction – INTERACT 2023. INTERACT 2023. Lecture Notes in Computer Science, vol 14145. Springer, Cham. https://doi.org/10.1007/978-3-031-42293-5_61
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DOI: https://doi.org/10.1007/978-3-031-42293-5_61
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