Abstract
The visual system successfully binds the shapes and colours of objects; therefore, our visual experience regarding the objects around us is coherent. However, this binding process can break down when attention is diverted, producing illusory conjunctions (ICs); for example, when presented with a red 2 and a green 5, the observer may report a green 2 and a red 5. The strongest observation of binding in human cognition is found in synaesthesia. In grapheme-colour synaesthesia, linguistic stimuli (e.g., letters or numbers) are strongly associated with colours. It is debatable whether these highly stable bindings constitute a form of early binding that occurs outside the focus of attention. We examined for the first time the occurrence of ICs in grapheme-colour synaesthesia. Experiment 1 replicated our previous finding, showing the effects of numerical distance on ICs (Arend et al., Psychon. Bull. Rev. 2013, 20, 1181-1186). Participants viewed a display containing two centrally presented letters and two coloured numbers and were asked to report: (1) whether the letters were same/different, (2) the colour of the larger number, and (3) the level of confidence concerning the colour of the number. Experiment 2 used a modified version of this task. Synaesthetes (N=5) and controls (N=15) viewed number-colour pairs that were congruent or incongruent with that of the synaesthetic association. Grapheme-colour synaesthesia significantly affected ICs on incongruent but not on congruent trials. Our findings strongly support the notion that shape and colour are free-floating features in synaesthesia, similar to what is observed in normal cognition.
Original language | English |
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Pages (from-to) | 235-251 |
Number of pages | 17 |
Journal | Multisensory Research |
Volume | 30 |
Issue number | 3-5 |
DOIs | |
State | Published - 1 Jan 2017 |
Keywords
- Synaesthesia
- feature integration
- illusory conjunctions
- spatial attention
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Ophthalmology
- Sensory Systems
- Computer Vision and Pattern Recognition
- Cognitive Neuroscience