Abstract This study investigates the application of nonlinear Electroencephalography (EEG) features—correlation dimension, sample entropy, fractal dimension, permutation entropy, and Lyapunov exponent—to capture the brain's complex dynamics during various stages of design cognition, including idea generation, evolution, evaluation, and rest. Building on a nonlinear design dynamics model, which interprets design creativity as a nonlinear chaotic process sensitive to initial conditions, this study serves as a preliminary exploration highlighting distinctive nonlinear EEG patterns across cognitive states. The analysis reveals that the brain undergoes varying nonlinear and chaotic dynamics across design stages. Significant features, channels, and brain regions—particularly in the frontal, parietal, and central lobes—contribute to distinguishing these cognitive phases. The Lyapunov exponent, as the most frequently significant feature, supports theoretical models of design as a nonlinear, initial-condition-sensitive process. Correlation and fractal dimensions reflect changes in the brain's fractal properties, especially in frontal and central areas. Lyapunov exponent, correlation dimension, and sample entropy in parietal, central, and temporal regions effectively differentiate cognitive phases, offering a foundation for future investigations. Greater nonlinear activity in the left hemisphere suggests asymmetrical processing during design tasks. As a novel application of these features in this context, the study provides a comprehensive view of brain activity across design stages and establishes a basis for further exploration of the neurocognitive mechanisms behind design creativity.
Soroush et al. (Thu,) studied this question.