The University of Southampton
University of Southampton Institutional Repository

Diagnosing synaesthesia with online colour pickers: maximising sensitivity and specificity

Diagnosing synaesthesia with online colour pickers: maximising sensitivity and specificity
Diagnosing synaesthesia with online colour pickers: maximising sensitivity and specificity
The most commonly used method for formally assessing grapheme-colour synaesthesia (i.e., experiencing colours in response to letter and/or number stimuli) involves selecting colours from a large colour palette on several occasions and measuring consistency of the colours selected. However, the ability to diagnose synaesthesia using this method depends on several factors that have not been directly contrasted. These include the type of colour space used (e.g., RGB, HSV, CIELUV, CIELAB) and different measures of consistency (e.g., city block and Euclidean distance in colour space). This study aims to find the most reliable way of diagnosing grapheme-colour synaesthesia based on maximising sensitivity (i.e., ability of a test to identify true synaesthetes) and specificity (i.e., ability of a test to identify true non-synaesthetes). We show, applying ROC (Receiver Operating Characteristics) to binary classification of a large sample of self-declared synaesthetes and non-synaesthetes, that the consistency criterion (i.e., cut-off value) for diagnosing synaesthesia is considerably higher than the current standard in the field. We also show that methods based on perceptual CIELUV and CIELAB colour models (rather than RGB and HSV colour representations) and Euclidean distances offer an even greater sensitivity and specificity than most currently used measures. Together, these findings offer improved heuristics for the behavioural assessment of grapheme-colour synaesthesia.
0165-0270
156-160
Rothen, Nicolas
e3e56320-46f8-41e4-b7d3-186f8b8c8aca
Seth, Anil
bd1d8eb9-c46c-402d-9490-08ad115c2e7f
Witzel, Christoph
dfb994f1-7007-441a-9e1a-ddb167f44166
Ward, James
35611092-46e8-43e1-bd4f-f3b92b3f9476
Rothen, Nicolas
e3e56320-46f8-41e4-b7d3-186f8b8c8aca
Seth, Anil
bd1d8eb9-c46c-402d-9490-08ad115c2e7f
Witzel, Christoph
dfb994f1-7007-441a-9e1a-ddb167f44166
Ward, James
35611092-46e8-43e1-bd4f-f3b92b3f9476

Rothen, Nicolas, Seth, Anil, Witzel, Christoph and Ward, James (2013) Diagnosing synaesthesia with online colour pickers: maximising sensitivity and specificity. Journal of Neuroscience Methods, 215 (1), 156-160. (doi:10.1016/j.jneumeth.2013.02.009).

Record type: Article

Abstract

The most commonly used method for formally assessing grapheme-colour synaesthesia (i.e., experiencing colours in response to letter and/or number stimuli) involves selecting colours from a large colour palette on several occasions and measuring consistency of the colours selected. However, the ability to diagnose synaesthesia using this method depends on several factors that have not been directly contrasted. These include the type of colour space used (e.g., RGB, HSV, CIELUV, CIELAB) and different measures of consistency (e.g., city block and Euclidean distance in colour space). This study aims to find the most reliable way of diagnosing grapheme-colour synaesthesia based on maximising sensitivity (i.e., ability of a test to identify true synaesthetes) and specificity (i.e., ability of a test to identify true non-synaesthetes). We show, applying ROC (Receiver Operating Characteristics) to binary classification of a large sample of self-declared synaesthetes and non-synaesthetes, that the consistency criterion (i.e., cut-off value) for diagnosing synaesthesia is considerably higher than the current standard in the field. We also show that methods based on perceptual CIELUV and CIELAB colour models (rather than RGB and HSV colour representations) and Euclidean distances offer an even greater sensitivity and specificity than most currently used measures. Together, these findings offer improved heuristics for the behavioural assessment of grapheme-colour synaesthesia.

This record has no associated files available for download.

More information

Accepted/In Press date: 12 February 2013
e-pub ahead of print date: 1 March 2013
Published date: 30 April 2013

Identifiers

Local EPrints ID: 438742
URI: http://eprints.soton.ac.uk/id/eprint/438742
ISSN: 0165-0270
PURE UUID: c53fe0af-43f0-4a7f-bf7b-b84020256ca9
ORCID for Christoph Witzel: ORCID iD orcid.org/0000-0001-9944-2420

Catalogue record

Date deposited: 23 Mar 2020 18:43
Last modified: 17 Mar 2024 04:00

Export record

Altmetrics

Contributors

Author: Nicolas Rothen
Author: Anil Seth
Author: James Ward

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×