An EEG-based method to decode cognitive factors in creative processes. (27th March 2023)

• Record Type: Journal Article
• Authors: Yin, Yuan; Zuo, Haoyu; Childs, Peter R. N.
• Is Part Of: AI EDAM. Volume 37(2023)
• Publication Date: 2023-03-27
• Subjects: Cognitive factor -- creativity process -- decoding -- EEG -- regression analysis; Engineering design -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; 620.00420285
• DOI: 10.1017/S0890060423000057
• Languages: English
• ISSNs: 0890-0604

Abstract

Abstract: Neurotechnology has been applied to gain insights on creativity-related cognitive factors. Prior research has identified relations between cognitive factors and creativity qualitatively; while quantitative relations, such as the relative importance of cognitive factors and creativity, have not been fully determined. Therefore, taking the creative design process as an example, this study using electroencephalography (EEG) aims to objectively identify how creativity-related cognitive factors of retrieval, recall, association, and combination contribute to creativity. The theoretical basis for an EEG-based decoding method to objectively identify which cognitive factors occur in a creative process is developed. Thirty participants were recruited for a practical study to verify the reliability of the decoding method. Based on the methodology, relationships between the relative importance level of the cognitive factor and creative output quality levels were detected. Results indicated that the occurrence of recall and association are reported with a high reliability level by the decoding method. The results also indicated that association is the dominant cognitive factor for higher creative output quality levels. Recall is the dominant cognitive factor for lower creative output quality levels.