Design Creativity Raw EEG Recordings - Loosely Controlled Modified TTCT-F Creativity Experiments

Published: 29 November 2023| Version 1 | DOI: 10.17632/82pgy2k6sk.1
Morteza Zangeneh Soroush, Mengting Zhao, Wenjun Jia, Yong Zeng


This dataset contains raw EEG signals recorded from 28 participants during design creativity experiments. The preprocessed version of these EEG signals has been uploaded as a separate dataset in Mendeley Data. More information and a detailed explanation can be found in the dataset, including the preprocessed version. The Preprocessed EEGs can be found at: Zangeneh Soroush, Morteza; Zhao, Mengting; Jia, Wenjun; Zeng, Yong (2023), “Design Creativity: EEG Dataset in Loosely Controlled Modified TTCT-F Creativity Experiments”, Mendeley Data, V1, doi: 10.17632/24yp3xp58b.1 The present dataset comprises electroencephalography (EEG) signals captured while participants engaged in creativity tasks. This study involved 29 graduate students, all of whom were right-handed, possessed normal or corrected-to-normal vision, reported sound mental health, and had no history of medical or psychiatric conditions or treatments. The EEG cap placement conformed to the 10-10 international standard system, and EEG signals were recorded using a 64-channel BrainVision actiCHamp, sampled at a frequency of 500 Hz. The creativity experiments were based on a modified version of the figural Torrance Test of Creative Thinking (TTCT-F). In each experiment, participants were presented with three incomplete sketches. They were tasked with three distinct creativity exercises for each sketch: idea generation, idea evolution, and idea evaluation. During the idea generation phase, participants were instructed to intuitively complete a sketch, guided by their initial impression of the image. The idea evolution (IDE) task required participants to create a drawing that markedly differed from the initial sketch. In the idea evaluation (IDR) phase, they assessed the difficulty encountered in both the idea generation and evolution tasks in terms of thinking and drawing. All tasks were self-paced and open-ended, with a maximum duration of three minutes. Additionally, rest periods (RST1 and RST2) of three minutes were incorporated at the start and end of each experiment session. The raw EEGs (this dataset) are neither pre-processed nor segmented. Interested researchers can use these signals to implement their proposed EEG analysis and preprocessing methods. We aimed to contribute to the creation of a more robust and dynamic scientific environment where data can be fully explored and utilized for the advancement of the field. Raw data access would allow other researchers to perform different preprocessing approaches, validate the methodologies, and ensure that the data remains applicable for future studies employing emerging analytical techniques.



Concordia University


Neuroscience, Computer-Aided Design, Neural Basis of Higher-Order Cognition, Computational Neuroscience, Cognition, Creativity, Electroencephalography, Conceptual Design, Cognitive Neuroscience, Electroencephalogram, Brain-Computer Interface