The DOI matches its Crossref record; 38 of the 39 references it cites were found in a registry or an index.
A Fruity Note: Crossmodal associations between odors and musical notes
Abstract
Odors are notoriously difficult to describe, but they seem prone to a variety of crossmodal associations. In the present study, we generalize the previously-shown association between odors (from perfumery) and pitch (Belkin et al. 1997) to odors related to food and drink (in this case those associated with wine). We also demonstrate that, to a lesser extent (25% of the odor tested), participants preferentially match specific odors to certain types of instruments. The ratings of the odors along a number of dimensions are used in principal components analysis (PCA) to explore the psychological dimensions underlying the odor-pitch associations. The results demonstrate that both pleasantness and complexity, but not intensity, appear to play a role when choosing a pitch to match an odor. Our results suggest that these features of odor stimuli constitute psychological dimensions that can be consistently matched to auditory features.
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“Previously, it has been shown that specific auditory attributes are associated with basic tastes, both when presented as taste words (for instance, 'sweet'), and in the form of tasting solutions [80-88]”
From The Role of Intrinsic and Extrinsic Sensory Factors in Sweetness Perception of Food and Beverages: A Review (2019) · cites this paper as [83]
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Cites
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
An Index of Factorial Simplicity
Kaiser, H. F. (1974) · Psychometrika · doi:10.1007/bf02291575 · Cited by 14,898
Pallant, J. (2020) · Routledge eBooks · doi:10.4324/9781003117407 · Cited by 6,034
A Second Generation Little Jiffy
Kaiser, H. F. (1970) · Psychometrika · doi:10.1007/bf02291817 · Cited by 4,855
A Note on the Multiplying Factors for Various χ2 Approximations
Bartlett, M. S. (1954) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1954.tb00174.x · Cited by 2,168
Crossmodal correspondences: A tutorial review
Spence, C. (2011) · Attention, Perception, & Psychophysics · doi:10.3758/s13414-010-0073-7 · Cited by 1,618
Self-citationLogothetis, N. K., & Sheinberg, D. L. (1996) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.19.030196.003045 · Cited by 1,374
Morrot, G., Brochet, F., & Dubourdieu, D. (2001) · Brain and Language · doi:10.1006/brln.2001.2493 · Cited by 711
The Nose Smells What the Eye Sees
Gottfried, J. A., & Dolan, R. J. (2003) · Neuron · doi:10.1016/s0896-6273(03)00392-1 · Cited by 604
An Odor is Not Worth a Thousand Words: From Multidimensional Odors to Unidimensional Odor Objects
Yeshurun, Y., & Sobel, N. (2009) · Annual Review of Psychology · doi:10.1146/annurev.psych.60.110707.163639 · Cited by 520
Research works printed but not linked: 3
- 2003, 39, 375
- 2011, THE WORLD OF FINE WINE, 31, 96
- 2006, Acta Acustica United with Acustica, 92, 1009
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Spence, C. J. (2011) · Journal of Consumer Psychology · doi:10.1016/j.jcps.2011.09.004 · Cited by 435
Self-citationDeroy, O. D., Crisinel, A.-S., & Spence, C. J. (2013) · Psychonomic Bulletin & Review · doi:10.3758/s13423-013-0397-0 · Cited by 205
Self-citationWang, Q. J., Mielby, L. A., Junge, J. Y., Bertelsen, A. S., Kidmose, U., Spence, C., & Byrne, D. V. (2019) · Foods · doi:10.3390/foods8060211 · Cited by 168
Self-citationSpence, C. J., Reinoso‐Carvalho, F., Velasco, C., & Wang, Q. J. (2019) · Multisensory Research · doi:10.1163/22134808-20191403 · Cited by 176
Self-citationHow automatic are crossmodal correspondences?
Spence, C. J., & Deroy, O. D. (2013) · Consciousness and Cognition · doi:10.1016/j.concog.2012.12.006 · Cited by 170
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Metadata
- Authors
- Crisinel, A.-S., & Spence, C.
- Affiliations
- University of Oxford (GB)
- ORCID
- Spence, C.
- Venue
- Chemical Senses
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-08-18
- Volume
- 37
- Issue
- 2
- Pages
- 151-158
- ISSN
- 0379-864X (ISSN-L)
- 1464-3553
- OpenAlex
- W2143065224
- Cited by
- 120
- References
- 39
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 9 · 2023: 10 · 2022: 12 · 2021: 15 · 2020: 8 · 2019: 10 · 2018: 6 · 2017: 8 · 2016: 4 · 2015: 5 · 2014: 5 · 2013: 7 · 2012: 5
- FWCI
- 7.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Chemical Senses (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Life Sciences › Neuroscience › Sensory Systems › Olfactory and Sensory Function Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neuroscience and Music Perception
- Keywords
- cross-modal correspondence, musical notes, odor pleasantness, odor intensity
- MeSH terms
- Adolescent, Adult, Female, Flavoring Agents, Fruit, Humans, Middle Aged, Music, Odorants, Pitch Perception, Smell, Wine, Olfactory Perception
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