dat_palette_bwg_instr.RDs from Distinct colours in the ‘synesthetic colour palette’

In grapheme-colour synesthesia, particular linguistic elements evoke particular colour sensations. Interestingly, when asked, non-synesthetes can also associate colours to letters, and previous studies show that specific letter-to-colour associations have similar biases to those of synesthetes. However, it is an open question whether the colours reported by synesthetes and non-synesthetes differ overall: is there a ‘synesthetic colour palette’? In this study, we visualize the overall distribution in colour space of colour concurrents in grapheme-colour synesthetes, and colour associations in non-synesthetic controls. We confirm the existence of a synesthetic colour palette: colour concurrents in synesthetes are different from colour associations in non-synesthetes. We quantify three factors that distinguish the colour palette of synesthetes and non-synesthetes: synesthetes have an increased over-representation of ‘pure’ (unmixed) hues, an increased presence of ‘warm’ (yellow-orange-brown) colours, and an increased presence of achromatic (grey, white, black) colours. Furthermore, we demonstrate that differences in the synesthetic colour palette can be used to train a machine learning algorithm to reliably classify single subjects as synesthetes versus non-synesthetes without using test–retest consistency. As far as we know, this is the first time an individual could be ‘diagnosed’ as synesthete, based only on his or her colours evoked by letters.This article is part of the discussion meeting issue ‘Bridging senses: new developments in synaesthesia’.

在形-颜色联觉（grapheme-colour synesthesia）中，特定语言元素会唤起特定的颜色感知。值得注意的是，即便被要求完成颜色-字母配对任务，非联觉者也可建立字母与颜色的联结；既往研究显示，特定的字母-颜色联结偏好与联觉者的偏好具有高度相似性。然而，联觉者与非联觉者所报告的颜色是否存在整体差异，仍是一个悬而未决的问题：是否存在专属的‘联觉色彩调色板’？本研究对形-颜色联觉者的联觉伴生色，以及非联觉对照组的颜色联结在颜色空间中的整体分布进行了可视化分析。我们证实了联觉色彩调色板的存在：联觉者的联觉伴生色与非联觉者的颜色联结存在显著差异。本研究量化了区分两类人群色彩调色板的三项特征：联觉者对‘纯色’（未混合色调）的过度表征比例更高，‘暖色调’（黄-橙-棕色系）的占比更高，同时无彩色（灰、白、黑）的占比也显著提升。此外，我们证明，可借助联觉色彩调色板的差异训练机器学习算法，无需依赖重测信度，即可可靠地将单个受试者分类为联觉者或非联觉者。据我们所知，这是首次实现仅基于字母唤起的颜色，即可对个体进行联觉者‘诊断’的研究。本文属于‘跨感官联结：联觉研究新进展’（Bridging senses: new developments in synaesthesia）专题讨论会议文集的一部分。