Cross-modal associations and synesthesia: Categorical perception and structure in vowel–color mappings in a large online sample

Self Cite

In synaesthetes, specific sensory stimuli (e.g. black letters) elicit additional experiences (e.g. colour). Synaesthesia is highly prevalent among individuals with autism spectrum disorder (ASD), but the mechanisms of this co-occurrence are not clear. We hypothesized autism and synaesthesia share atypical sensory sensitivity and perception. We assessed autistic traits, sensory sensitivity and visual perception in two synaesthete populations. In Study 1, synaesthetes ( N = 79, of different types) scored higher than non-synaesthetes ( N = 76) on the Attention-to-detail and Social skills subscales of the autism spectrum quotient indexing autistic traits, and on the Glasgow Sensory Questionnaire indexing sensory hypersensitivity and hyposensitivity which frequently occur in autism. Synaesthetes performed two local/global visual tasks because individuals with autism typically show a bias towards detail processing. In synaesthetes, elevated motion coherence thresholds (MCTs) suggested reduced global motion perception, and higher accuracy on an embedded figures task suggested enhanced local perception. In Study 2, sequence-space synaesthetes ( N = 18) completed the same tasks. Questionnaire and embedded figures results qualitatively resembled Study 1 results, but no significant group differences with non-synaesthetes ( N = 20) were obtained. Unexpectedly, sequence-space synaesthetes had reduced MCTs. Altogether, our studies suggest atypical sensory sensitivity and a bias towards detail processing are shared features of synaesthesia and ASD. This article is part of the discussion meeting issue ‘Bridging senses: novel insights from synaesthesia’.

Section: Methods Study 1: Heterogeneous Cohort Of Online Synaesthetesmentioning

confidence: 99%

Autistic traits in synaesthesia: atypical sensory sensitivity and enhanced perception of details

Leeuwen

Petersen

Burghoorn

et al. 2019

Self Cite

“…These included social media (e.g. Twitter, posts in synaesthesia-related Facebook groups, a Reddit 'Ask Me Anything' event in August 2016), flyers posted at Radboud University, advertising to the Russian synaesthesia community database, and recontacting consenting individuals who had previously participated in synaesthesia research through the Groot Nationaal Onderzoek (in English, 'Large National Study', http://gno.mpi.nl/tests) [26], the University of Amsterdam, or the University of Sussex. Those recruited to the genetics study directly at the University of Edinburgh were contacted through similar methods, including online advertisements, student forms and mailing lists, and recontacting previous participants.…”

Section: Methods (A) Participant Recruitmentmentioning

confidence: 99%

Investigating genetic links between grapheme–colour synaesthesia and neuropsychiatric traits

Tilot

Vino

Kučera

et al. 2019

Self Cite

Synaesthesia is a neurological phenomenon affecting perception, where triggering stimuli (e.g. letters and numbers) elicit unusual secondary sensory experiences (e.g. colours). Family-based studies point to a role for genetic factors in the development of this trait. However, the contributions of common genomic variation to synaesthesia have not yet been investigated. Here, we present the SynGenes cohort, the largest genotyped collection of unrelated people with grapheme–colour synaesthesia ( n = 723). Synaesthesia has been associated with a range of other neuropsychological traits, including enhanced memory and mental imagery, as well as greater sensory sensitivity. Motivated by the prior literature on putative trait overlaps, we investigated polygenic scores derived from published genome-wide scans of schizophrenia and autism spectrum disorder (ASD), comparing our SynGenes cohort to 2181 non-synaesthetic controls. We found a very slight association between schizophrenia polygenic scores and synaesthesia (Nagelkerke's R 2 = 0.0047, empirical p = 0.0027) and no significant association for scores related to ASD (Nagelkerke's R 2 = 0.00092, empirical p = 0.54) or body mass index ( R 2 = 0.00058, empirical p = 0.60), included as a negative control. As sample sizes for studying common genomic variation continue to increase, genetic investigations of the kind reported here may yield novel insights into the shared biology between synaesthesia and other traits, to complement findings from neuropsychology and brain imaging. This article is part of a discussion meeting issue ‘Bridging senses: novel insights from synaesthesia'.

“…in [i]), are lighter, greener and yellower. Cuskley et al [35] replicated these findings with a large sample size, and furthermore showed that letter category (a particular vowel) is a better predictor of colour than the acoustic measures, thus also showing a role of categorical (letter) perception.…”

Section: Introductionmentioning

confidence: 82%

Distinct colours in the ‘synaesthetic colour palette’

Rouw

Root

2019

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’.