Double-blind study of visual imagery in grapheme-color synesthesia

Brang, David; Ahn, EunSeon

doi:10.1016/j.cortex.2019.02.025

Cited by 8 publications

(10 citation statements)

References 52 publications

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“…In terms of perceptual differences between synaesthetes and non-synaesthetes, synaesthetes demonstrate enhanced perception in the concurrent modality of synaesthesia [47,48] and enhanced imagery in the concurrent [18,[49][50][51], and have altered cortical excitability in early processing areas [17,52]. Before reviewing these perceptual differences in detail, it is important to consider how these sensory differences are causally related to the cross-sensory experiences of synaesthesia.…”

Section: Perceptual and Cognitive Differencesmentioning

confidence: 99%

Stochastic resonance model of synaesthesia

Lalwani

Brang

2019

Phil. Trans. R. Soc. B

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In synaesthesia, stimulation of one sensory modality evokes additional experiences in another modality (e.g. sounds evoking colours). Along with these cross-sensory experiences, there are several cognitive and perceptual differences between synaesthetes and non-synaesthetes. For example, synaesthetes demonstrate enhanced imagery, increased cortical excitability and greater perceptual sensitivity in the concurrent modality. Previous models suggest that synaesthesia results from increased connectivity between corresponding sensory regions or disinhibited feedback from higher cortical areas. While these models explain how one sense can evoke qualitative experiences in another, they fail to predict the broader phenotype of differences observed in synaesthetes. Here, we propose a novel model of synaesthesia based on the principles of stochastic resonance. Specifically, we hypothesize that synaesthetes have greater neural noise in sensory regions, which allows pre-existing multisensory pathways to elicit supra-threshold activation (i.e. synaesthetic experiences). The strengths of this model are (a) it predicts the broader cognitive and perceptual differences in synaesthetes, (b) it provides a unified framework linking developmental and induced synaesthesias, and (c) it explains why synaesthetic associations are inconsistent at onset but stabilize over time. We review research consistent with this model and propose future studies to test its limits. This article is part of a discussion meeting issue ‘Bridging senses: novel insights from synaesthesia’.

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Section: Perceptual and Cognitive Differencesmentioning

confidence: 99%

Stochastic resonance model of synaesthesia

Lalwani

Brang

2019

Phil. Trans. R. Soc. B

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“…Our study has further highlighted the need to consider recruitment methods used within synaesthesia research (e.g. see [44]) as well as the potential utility of using a synaesthesia consistency measure (e.g. see [73]) and the importance of using a range of behavioural as well as self-report measures when considering visual mental imagery abilities.…”

Section: Discussionmentioning

confidence: 92%

“…[38]). However, not all studies have found this to be the case, with a recent study by Brang & Ahn [44] finding that, in comparison to non-synaesthetes, grapheme-colour synaesthetes reported greater usage of imagery on the SUIS but not more vivid imagery on the VVIQ. Furthermore, while Ward et al [37] found no group difference between non-synaesthetes and sequence-spatial synaesthetes scores on the VVIQ2 [70], they also reported that, for the nonsynaesthetes, there was no correlation between their score on the Imagery Ability subscale of the SCSQ [36] and their sequence-space consistency measure.…”

Section: Discussionmentioning

confidence: 92%

“…To date, we do not have a study that has combined self-report measures with those of both mental rotation and mental imagery task performance (within the same sample). Another limitation of previous studies (and a common problem with synaesthesia research) is the method used for recruiting participants (see [10] for discussion and [44] for a recent study using a double-blind method) and the impact this might have on the findings. Synaesthete participants are typically recruited from a pre-existing database that researchers have developed over years of conducting synaesthesia research, where synaesthetes have completed synaesthesia screening tools and consistency measures.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the relationship between grapheme colour-picking consistency and mental imagery

Spiller

Harkry

McCullagh

et al. 2019

Phil. Trans. R. Soc. B

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Previous research has indicated a potential link between mental imagery and synaesthesia. However, these findings are mainly based on imagery self-report measures and recruitment of self-selected synaesthetes. To avoid issues of self-selection and demand effects, we recruited participants from the general population, rather than synaesthetes specifically, and used colour-picking consistency tests for letters and numbers to assess a ‘synaesthete-like’ experience. Mental imagery ability and mental rotation ability were assessed using both self-report measures and behavioural assessments. Consistency in colour-picking for letters (but not numbers) was predicted by performance on the visual mental imagery task but not by a mental rotation task or self-report measures. Using the consistency score as a proxy measure of grapheme-colour synaesthesia, we provide more evidence for the suggestion that synaesthetic experience is associated with enhanced mental imagery, even when participants are naive to the research topic. This article is part of a discussion meeting issue ‘Bridging senses: novel insights from synaesthesia’.

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“…The study faces a number of limitations inherent in exploratory work and common amongst synaesthesia research [ 47 ]; these relate to blinding, sampling, and the identification of appropriate control participants. While it has been shown possible to conduct well-blinded experiments with synaesthetes [ 48 ], the nature of the current experimental tasks made this impracticable. Regarding control participants, in our study the Non-Synaesthete group used in ‘Group Experiment: part 2’ were not perfectly matched on demographic measures with the Synaesthete group, which may reduce the validity of the comparison with this group.…”

Section: Discussionmentioning

confidence: 99%

Sharing the load: How a personally coloured calculator for grapheme-colour synaesthetes can reduce processing costs

et al. 2021

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Synaesthesia refers to a diverse group of perceptions. These unusual perceptions are defined by the experience of concurrents; these are conscious experiences that are catalysed by attention to some normally unrelated stimulus, the inducer. In grapheme-colour synaesthesia numbers, letters, and words can all cause colour concurrents, and these are independent of the actual colour with which the graphemes are displayed. For example, when seeing the numeral ‘3’ a person with synaesthesia might experience green as the concurrent irrespective of whether the numeral is printed in blue, black, or red. As a trait, synaesthesia has the potential to cause both positive and negative effects. However, regardless of the end effect, synaesthesia incurs an initial cost when compared with its equivalent example from normal perception; this is the additional processing cost needed to generate the information on the concurrent. We contend that this cost can be reduced by mirroring the concurrent in the environment. We designed the Digital-Colour Calculator (DCC) app, allowing each user to personalise and select the colours with which it displays its digits; it is the first reported example of a device/approach that leverages the concurrent. In this article we report on the reactions to the DCC for a sample of fifty-three synaesthetes and thirty-five non-synaesthetes. The synaesthetes showed a strong preference for the DCC over its normal counterpart. The non-synaesthetes showed no obvious preference. When using the DCC a subsample of the synaesthete group showed consistent improvement in task speed (around 8%) whereas no synaesthete showed a decrement in their speed.

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Double-blind study of visual imagery in grapheme-color synesthesia

Cited by 8 publications

References 52 publications

Stochastic resonance model of synaesthesia

Stochastic resonance model of synaesthesia

Exploring the relationship between grapheme colour-picking consistency and mental imagery

Sharing the load: How a personally coloured calculator for grapheme-colour synaesthetes can reduce processing costs

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