The neuroscience of creative production: Comparing domain-specific and domain-general mechanisms

近年来，人们对创造力及其神经基础的兴趣激增。这不仅适用于理解人类认知和物质文化的进化起源，而且更实际地适用于将创造力作为经济和文化发展的主要驱动力的观点，特别是在我们这个快节奏的技术变革世界中。关于创造力的生物学基础的核心问题之一是，创造力主要依赖于领域特定的机制还是领域通用的机制。已经有令人信服的论据支持心理学和神经科学中的创造力模型。到目前为止，还没有一项关于创造力的神经科学的研究在同一个参与者身上同时研究了一个以上的领域。此外，许多关于创意生产的文献都集中在领域一般任务上，这些任务没有提供解决创意生产中领域特殊性的潜力。因此，我建议对创造性生产进行跨模式和多模式的神经成像研究，以探索创造性大脑机制的领域特异性和普遍性。我将加入一种成像基因组学方法，将神经成像数据与有关创意生产候选基因的遗传信息结合起来。 在跨模式实验中，创造性生产的三个领域(例如，绘画、唱歌和身体运动)将被单独观察，然后使用可以识别共享大脑网络的神经成像数据的“联合”分析进行相互比较。目标将是确定这三个领域共享哪些大脑区域，以及每个领域特定哪些区域。在多模式实验中，创造性生产将同时发生在两个领域(例如，用单词创造旋律)，这将与每个领域单独的创造性生产(即，单独创造旋律和单独创造文本)进行比较，同样的目的是识别领域特定的大脑区域与领域通用的大脑区域。最后，交叉模式分析将与大约12个影响创造力的候选基因的分析相结合，以便进行成像-基因组学联合分析，其中候选基因的基因类型将被用作神经成像数据的回归变量。总体而言，这项研究计划将提供第一种方法来检查不止一个领域的创造性生产，并将使用两种互补的神经成像方法和成像-基因组学相结合的分析方法来实现这一点。这将为创造性生产更多地依赖于领域特定的机制还是领域通用的机制提供新的线索。这一问题对如何在课堂和企业界提高创造力具有重要影响，特别是创造力培训应侧重于具体领域还是一般领域的方法。

There has been a surge of interest in creativity and its neural basis in recent years. This applies not only to an understanding of the evolutionary origins of human cognition and material culture, but also more pragmatically to a perspective of creativity as being a major driving force for economic and cultural development, especially in our fast-paced world of technological change. One of the central questions about the biological basis of creativity is whether creativity depends mainly on domain-specific or domain-general mechanisms. Compelling arguments have been made to support both models of creativity in psychology and neuroscience. Thus far, no work on the neuroscience of creativity has examined more than one domain at a time in the same participants. In addition, much of the literature on creative production has focused on domain-general tasks that do not offer the potential to address domain specificity in creative production. Therefore, I am proposing to carry out both cross-modal and multi-modal neuroimaging studies of creative production in order to explore the domain-specificity vs. -generality of the brain mechanisms for creativity. I will join this with an imaging genomics approach that combines neuroimaging data with genetic information about candidate genes for creative production. In the cross-modal experiments, three domains of creative production (e.g., drawing, singing, and body movement) will be looked at individually and then compared with one another using “conjunction” analyses of neuroimaging data that can identify shared brain networks. The goal will be to determine which brain areas are shared across the three domains and which areas are specific to each domain. In the multi-modal experiments, creative production will occur simultaneously across two domains (e.g., creating a melody with words), and this will be compared with creative production in each domain separately (i.e., creating a melody alone and creating a text alone), again with the aim of identifying domain-specific vs. domain-general brain areas. Finally, the cross-modal analysis will be consolidated with an analysis of about dozen candidate genes for creativity in order to perform a combined imaging-genomics analysis, where genotypes for the candidate genes will be used as regressors for the neuroimaging data. Overall, this research program will provide the first approach that examines creative production across more than one domain, and will do so using two complementary neuroimaging approaches and a combined imaging-genomics analysis. This will shed new light on whether creative production is dependent more on domain-specific or domain-general mechanisms. The issue has important implications for how creativity can be enhanced both in the classroom and in the corporate world, in particular whether creativity training should focus on domain-specific or domain-general approaches.