关键词: 创造力, 神经振荡, 脑电图, alpha神经振荡, 交叉节律耦合

Abstract:

Creativity has traditionally been defined as the ability to generate ideas that are novel and useful. Neuroscientific studies revealed first insights into neural mechanisms underlying creativity, yet the neural mechanisms underlying creative thinking are poorly understood. This review systematically illustrates the roles of neural oscillations in the process of creativity from the perspectives of single rhythmic neural oscillations and multi rhythmic neural oscillations cross frequency coupling. The paper also discusses the cooperative effects of cognitive functions and provides a new insight into the dynamic collaborative mode of functional networks and the specific role of structural networks in creative thinking that would contribute to deepening the understanding of the cognitive processes and neural mechanisms of creativity. In the end, several potential directions of this field for future studies are discussed.
A large number of researches demonstrates that there appears to be robust evidence that EEG alpha power is particularly sensitive to various creativity-related demands involved in creative ideation. The frontal alpha band oscillations during the process of creative thinking, which was initially considered as an electrophysiological correlate of cortical idling, are now generally treated to the increase of internal processing demand or the top-down cognitive control in the process of creativity generation, in order to gate neural information to the task-relevant regions. Meanwhile, the right temporal alpha oscillations play a critical role in the ability to override habitual, but misleading, associations and enhances the connection of long-distance semantic concepts during creative problem solving. In addition, the theta band oscillations of parietal-occipital junction increased with the increase of creativity, which can facilitate the neural information communications between brain regions throughout a relative long distance, in order to achieve the functional regulation of top-down brain regions, and the collaborative regulation of multiple brain regions. As for gamma band, the high frequency oscillation property makes it suitable for the integration of multiple objects features in the local neural network and hold the relevant representations. Neural oscillations cross-frequency coupling (CFC) refers to the effect of the cross modulation between the electrophysiological oscillation rhythm in different ensembles of neurons. The CFC can reflect the mechanism of information transfer among the frontal lobe, temporal lobe and parietal lobe during the creative generation process. Which also reflects the exchange of local field potentials, electroencephalograph (EEG) and other neural electrophysiological activities at different spatial or temporal scales of the process of creative thinking.
Perhaps the most important problem in the neuroscientific study of creativity is a general lack of conceptual clarity. While researchers usually aim to investigate the neural correlates of creativity, they can actually address only a specific aspect of the construct. Consequently, future research firstly needs to continuously integrate data resources to identify the main components of creativity and need to be very specific in their definitions of the construct under investigation. 
Second, it is necessary to combine multimodal brain imaging to provide new insight into the dynamic collaborative mode of functional networks and the specific role of structural networks in creative thinking that would contribute to deepening the understanding of the cognitive processes and neural mechanisms of creativity.
 Third, emerging evidence suggests that the complex cognitive processes of creative thinking involve the interaction of multiple brain regions and networks and may not depend on the specific function of a single brain region. Hence there is equally important to develop advanced algorithms of EEG data processing with more ecological validity, such as multiscale sample entropy calculation (MSE). It can calculate the complexity of brain network changes. Consequently, it can accelerate to explore the more pinpoint dynamic neural mechanisms in the process of creativity. Which is a critical and fundamental endeavor for scientific research on creativity. 
Last, the role of computational neuroscience and machine learning on creativity research should be strengthened. Based on a certain theoretical framework and empirical research, standing at the philosophical point of view and combined the EEG and machine learning (ML), and set out to explore the profound the brain network basis of creativity. And we put it as a research starting point of the thesis. For instance, future studies could combine multi-omics and multimodal data with ML techniques including the support vector machine (SVM), k-nearest neighbors (k-NN), artificial neural networks (ANN), and linear discriminant analysis (LDA), to achieve the goal of accurate prediction and assessment of individuals’ creativity. 

Key words: creativity, neural oscillation, electroencephalography (EEG), alpha neural oscillation, cross-frequency coupling (CFC)