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，而且更实用地适用于将创造力视为经济和文化发展的主要驱动力的观点，特别是在我们快速发展的技术变革世界中。关于创造力的生物学基础的一个核心问题是，创造力主要取决于特定领域的机制还是一般领域的机制。在心理学和神经科学中，创造力的两种模型都得到了令人信服的支持。到目前为止，还没有研究创造力的神经科学在同一时间对同一参与者进行多个领域的研究。此外，许多关于创意生产的文献都集中在一般领域的任务上，这些任务没有提供解决创意生产领域特殊性的潜力。因此，我建议进行跨模态和多模态的创造性生产的神经影像学研究，以探索领域特异性与一般性的大脑机制的创造力。我将加入一个成像基因组学的方法，结合神经成像数据与遗传信息的候选基因的创造性生产。 在跨模态实验中，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。我们的目标是确定哪些大脑区域在这三个领域中是共享的，哪些区域是每个领域所特有的。在多模态实验中，创造性生产将同时发生在两个领域（例如，用文字创作旋律），这将分别与每个领域的创意制作进行比较（即，单独创建旋律和单独创建文本），目的也是识别特定领域与一般领域的大脑区域。最后，交叉模态分析将与大约12个创造力候选基因的分析相结合，以进行组合成像-基因组学分析，其中候选基因的基因型将用作神经成像数据的回归因子。总的来说，这项研究计划将提供第一种方法，在一个以上的领域检查创造性生产，并将使用两种互补的神经成像方法和结合成像基因组学分析。这将为创意生产更多地依赖于特定领域机制还是一般领域机制提供新的线索。这个问题对于如何在课堂和企业世界中提高创造力具有重要意义，特别是创造力培训是否应该侧重于特定领域或一般领域的方法。

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.