Fractal Fluency: Processing of Fractal Stimuli Across Sight, Sound, and Touch.

Q3 Neuroscience
Richard P Taylor, Catherine Viengkham, Julian H Smith, Conor Rowland, Saba Moslehi, Sabrina Stadlober, Anastasija Lesjak, Martin Lesjak, Branka Spehar
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引用次数: 0

Abstract

People are continually exposed to the rich complexity generated by the repetition of fractal patterns at different size scales. Fractals are prevalent in natural scenery and also in patterns generated by artists and mathematicians. In this chapter, we will investigate the powerful significance of fractals for the human senses. In particular, we propose that fractals with mid-range complexity play a unique role in our visual experiences because the visual system has adapted to these prevalent natural patterns. This adaptation is evident at multiple stages of the visual system, ranging from data acquisition by the eye to processing of this data in the higher visual areas of the brain. Based on these results, we will discuss a fluency model in which the visual system processes mid-complexity fractals with relative ease. This fluency optimizes the observer's capabilities (such as enhanced attention and pattern recognition) and generates an aesthetic experience accompanied by a reduction in the observer's physiological stress levels. In addition to reviewing people's responses to viewing fractals, we will compare these responses to recent research focused on fractal sounds and fractal surface textures. We will extend our fractal fluency model to allow for stimuli across multiple senses.

分形流畅性:处理视觉、听觉和触觉的分形刺激。
人们不断接触到不同大小尺度的分形图案重复所产生的丰富复杂性。分形普遍存在于自然景观以及艺术家和数学家创造的图案中。在本章中,我们将研究分形对人类感官的强大意义。我们特别提出,具有中等复杂程度的分形在我们的视觉体验中发挥着独特的作用,因为视觉系统已经适应了这些普遍存在的自然图案。这种适应体现在视觉系统的多个阶段,从眼睛获取数据到大脑高级视觉区域处理这些数据。基于这些结果,我们将讨论一个流畅模型,在这个模型中,视觉系统可以相对轻松地处理中等复杂度的分形。这种流畅性优化了观察者的能力(如增强注意力和模式识别能力),并产生了美学体验,同时降低了观察者的生理压力水平。除了回顾人们观看分形时的反应之外,我们还将把这些反应与最近对分形声音和分形表面纹理的研究进行比较。我们将扩展我们的分形流畅度模型,使其适用于多种感官刺激。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Advances in neurobiology
Advances in neurobiology Neuroscience-Neurology
CiteScore
2.80
自引率
0.00%
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0
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