Daikoku Tatsuya, Wiggins Geraint A, Nagai Yukie
International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo, Japan.
AI Lab, Vrije Universiteit Brussel, Brussels, Belgium.
Front Neurosci. 2021 Apr 20;15:640412. doi: 10.3389/fnins.2021.640412. eCollection 2021.
Creativity is part of human nature and is commonly understood as a phenomenon whereby something original and worthwhile is formed. Owing to this ability, humans can produce innovative information that often facilitates growth in our society. Creativity also contributes to esthetic and artistic productions, such as music and art. However, the mechanism by which creativity emerges in the brain remains debatable. Recently, a growing body of evidence has suggested that statistical learning contributes to creativity. Statistical learning is an innate and implicit function of the human brain and is considered essential for brain development. Through statistical learning, humans can produce and comprehend structured information, such as music. It is thought that creativity is linked to acquired knowledge, but so-called "eureka" moments often occur unexpectedly under subconscious conditions, without the intention to use the acquired knowledge. Given that a creative moment is intrinsically implicit, we postulate that some types of creativity can be linked to implicit statistical knowledge in the brain. This article reviews neural and computational studies on how creativity emerges within the framework of statistical learning in the brain (i.e., statistical creativity). Here, we propose a hierarchical model of statistical learning: statistically chunking into a unit (hereafter and shallow statistical learning) and combining several units (hereafter and deep statistical learning). We suggest that deep statistical learning contributes dominantly to statistical creativity in music. Furthermore, the temporal dynamics of perceptual uncertainty can be another potential causal factor in statistical creativity. Considering that statistical learning is fundamental to brain development, we also discuss how typical versus atypical brain development modulates hierarchical statistical learning and statistical creativity. We believe that this review will shed light on the key roles of statistical learning in musical creativity and facilitate further investigation of how creativity emerges in the brain.
创造力是人性的一部分，通常被理解为一种形成原创且有价值事物的现象。由于这种能力，人类能够产生创新信息，这往往促进我们社会的发展。创造力还促成了美学和艺术作品的产生，比如音乐和艺术。然而，创造力在大脑中产生的机制仍存在争议。最近，越来越多的证据表明统计学习对创造力有贡献。统计学习是人类大脑的一种内在且隐性的功能，被认为对大脑发育至关重要。通过统计学习，人类能够产生并理解结构化信息，比如音乐。人们认为创造力与习得知识有关，但所谓的“顿悟”时刻常常在潜意识状态下意外出现，并非有意运用习得知识。鉴于创造性时刻本质上是隐性的，我们推测某些类型的创造力可能与大脑中的隐性统计知识相关。本文回顾了关于创造力如何在大脑统计学习框架内产生（即统计创造力）的神经和计算研究。在此，我们提出一种统计学习的层级模型：将其统计性地分块为一个单元（以下简称浅层统计学习）以及组合多个单元（以下简称深层统计学习）。我们认为深层统计学习对音乐中的统计创造力起主要作用。此外，感知不确定性的时间动态可能是统计创造力中的另一个潜在因果因素。鉴于统计学习对大脑发育至关重要，我们还讨论了典型与非典型大脑发育如何调节层级统计学习和统计创造力。我们相信这篇综述将阐明统计学习在音乐创造力中的关键作用，并促进对创造力如何在大脑中产生的进一步研究。
