Abstract

In grapheme-colour synaesthesia, particular linguistic elements evoke particular colour sensations. Interestingly, when asked, non-synaesthetes can also associate colours to letters, and previous studies show that specific letter-to-colour associations have similar biases to those of synaesthetes. However, it is an open question whether the colours reported by synaesthetes and non-synaesthetes differ overall: is there a 'synaesthetic colour palette'? In this study, we visualize the overall distribution in colour space of colour concurrents in grapheme-colour synaesthetes, and colour associations in non-synaesthetic controls. We confirm the existence of a synaesthetic colour palette: colour concurrents in synaesthetes are different from colour associations in non-synaesthetes. We quantify three factors that distinguish the colour palette of synaesthetes and non-synaesthetes: synaesthetes 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 synaesthetic colour palette can be used to train a machine learning algorithm to reliably classify single subjects as synaesthetes versus non-synaesthetes without using test-retest consistency data. As far as we know, this is the first time an individual could be 'diagnosed' as a synaesthete, based only on his or her colours evoked by letters. This article is part of a discussion meeting issue 'Bridging senses: novel insights from synaesthesia'.

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