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Superior Olfactory Language and Cognition in Odor-Color Synaesthesia


Abstract and Figures

Olfaction is often considered a vestigial sense in humans, demoted throughout evolution to make way for the dominant sense of vision. This perspective on olfaction is reflected in how we think and talk about smells in the West, with odor imagery and odor language reported to be difficult. In the present study we demonstrate odor cognition is superior in odor-color synaesthesia, where there are additional sensory connections to odor concepts. Synaesthesia is a neurological phenomenon in which input in 1 modality leads to involuntary perceptual associations. Semantic accounts of synaesthesia posit synaesthetic associations are mediated by activation of inducing concepts. Therefore, synaesthetic associations may strengthen conceptual representations. To test this idea, we ran 6 odor-color synaesthetes and 17 matched controls on a battery of tasks exploring odor and color cognition. We found synaesthetes outperformed controls on tests of both odor and color discrimination, demonstrating for the first time enhanced perception in both the inducer (odor) and concurrent (color) modality. So, not only do synaesthetes have additional perceptual experiences in comparison to controls, their primary perceptual experience is also different. Finally, synaesthetes were more consistent and accurate at naming odors. We propose synaesthetic associations to odors strengthen odor concepts, making them more differentiated (facilitating odor discrimination) and easier to link with lexical representations (facilitating odor naming). In summary, we show for the first time that both odor language and perception is enhanced in people with synaesthetic associations to odors. (PsycINFO Database Record
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Journal of Experimental Psychology:
Human Perception and Performance
Superior Olfactory Language and Cognition in Odor-
Color Synaesthesia
Laura J. Speed and Asifa Majid
Online First Publication, August 17, 2017.
Speed, L. J., & Majid, A. (2017, August 17). Superior Olfactory Language and Cognition in Odor-
Color Synaesthesia. Journal of Experimental Psychology: Human Perception and Performance.
Advance online publication.
Superior Olfactory Language and Cognition in Odor-Color Synaesthesia
Laura J. Speed
Radboud University
Asifa Majid
Radboud University and Max Planck Institute for
Olfaction is often considered a vestigial sense in humans, demoted throughout evolution to make way for
the dominant sense of vision. This perspective on olfaction is reflected in how we think and talk about
smells in the West, with odor imagery and odor language reported to be difficult. In the present study we
demonstrate odor cognition is superior in odor-color synaesthesia, where there are additional sensory
connections to odor concepts. Synaesthesia is a neurological phenomenon in which input in 1 modality
leads to involuntary perceptual associations. Semantic accounts of synaesthesia posit synaesthetic
associations are mediated by activation of inducing concepts. Therefore, synaesthetic associations may
strengthen conceptual representations. To test this idea, we ran 6 odor-color synaesthetes and 17 matched
controls on a battery of tasks exploring odor and color cognition. We found synaesthetes outperformed
controls on tests of both odor and color discrimination, demonstrating for the first time enhanced
perception in both the inducer (odor) and concurrent (color) modality. So, not only do synaesthetes have
additional perceptual experiences in comparison to controls, their primary perceptual experience is also
different. Finally, synaesthetes were more consistent and accurate at naming odors. We propose
synaesthetic associations to odors strengthen odor concepts, making them more differentiated (facilitating
odor discrimination) and easier to link with lexical representations (facilitating odor naming). In
summary, we show for the first time that both odor language and perception is enhanced in people with
synaesthetic associations to odors.
Public Significance Statement
This study shows how odor-color synaesthesia can affect the way odors are perceived and named,
suggesting synaesthesia plays a role in shaping concepts. Broadly, this highlights the important role
of perceptual information in conceptual representations.
Keywords: olfaction, synaesthesia, odor discrimination, odor naming
Olfaction has been considered a vestigial sense for humans
across the centuries (Majid, Speed, Croijmans, & Arshamian,
2017). This opinion has biological support, with primates having a
proportionally smaller olfactory bulb (Baron, Frahm, Bhatnagar, &
Stephan, 1983) and a smaller surface area of olfactory neuroepi-
thelium (Le Gros Clark, 1959) than other mammals. Evolution-
arily, olfaction is thought to have been reduced in favor of the
development of the visual system, with primate posture becoming
more erect (Aiello & Dean, 1990), and the eyes moving to a more
central position on the face (Jones, Martin, & Pilbeam, 1992). This
view of olfaction as a lesser sense, at least in Western societies, is
reflected both culturally and psychologically. Olfaction is under-
valued in society. We go to great lengths to eliminate odors. In
fact, 55% of youngsters would rather give up their sense of smell
than give up technology (McCann Worldgroup, 2011). Psycholog-
ically, humans find it difficult to imagine odors (Crowder &
Schab, 1995; Herz, 2000), and to correctly identify and name them
(e.g., Cain, 1979; Desor & Beauchamp, 1974; Lawless & Engen,
1977; see Yeshurun & Sobel, 2010 and Olofsson & Gottfried,
2015 for recent reviews).
Recent research however suggests that problems with odor may
be a culturally specific phenomenon (Majid & Burenhult, 2014;
O’Meara & Majid, 2016; Wnuk & Majid, 2014; Majid, 2015).
Speakers of a number of languages in the world, such as Jahai in
Malaysia (Majid & Burenhult, 2014) and Maniq in Thailand
(Wnuk & Majid, 2014), do not show such limitations with odor
language. Speakers of these languages belong to hunter-gatherer
societies where odor is a prominent part of everyday culture, as
reflected in the rituals of the people and in their ideologies (e.g.,
Burenhult & Majid, 2011; Wnuk & Majid, 2014). The observed
Laura J. Speed, Centre for Language Studies, Radboud University; Asifa
Majid, Centre for Language Studies, Radboud University, and Max Planck
Institute for Psycholinguistics.
This work was supported by The Netherlands Organization for Scientific
Research: NWO VICI grant “Human olfaction at the intersection of lan-
guage, culture and biology” and NWO Aspasia “Cross-modal correspon-
dences across cultures.” Thanks to Simon Fisher, Katerina Kucera, Carly
Jaques, and Amanda Tilot from the Language & Genetics Department,
Max Planck Institute for Psycholinguistics for help with recruitment of
participants, and to Chris Street and Lila San Roque for comments on a
draft of the article.
Correspondence concerning this article should be addressed to Laura J.
Speed, Centre for Language Studies, Radboud University, Erasmusplein 1,
Nijmegen 6500HD, Netherlands. E-mail:
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Journal of Experimental Psychology:
Human Perception and Performance
© 2017 American Psychological Association
2017, Vol. 0, No. 999, 000
odor naming advantage and olfactory cultural preoccupation
within these societies suggests olfactory abilities in humans may
be more malleable than previously thought. That is, the importance
of, and experience with, odor in everyday life may be reflected in
language (cf. Malt & Majid, 2013). Similarly, in the West, there is
evidence that olfactory experience can improve odor naming.
Croijmans and Majid (2016) found wine experts were better able
to name the odor of wines compared with novices. This suggests
years of dedicated experience smelling and discussing wine odors
can lead to improvement in experts’ odor naming too (see also
Cain, 1979; Desor & Beauchamp, 1974). Odor perception may be
similarly malleable, and language may play a role here too. For
example, participants are better able to discriminate between odors
when given odor labels (de Wijk & Cain, 1994) or when trained
with odor labels (Rabin, 1988).
In the present work, we investigate another way in which
olfactory language and cognition can be boosted. In particular, we
assess how “extra” connections between olfaction and other per-
ceptual modalities, in terms of synaesthetic associations, may
affect odor processing. Specifically, we assessed odor language
and cognition in individuals with odor-color synaesthesia.
Synaesthesia is a neurological phenomenon in which stimula-
tion (inducers) in one sensory modality leads to involuntary sen-
sations (concurrents) within the same or different modality, as
when colors are evoked by visually presented letters (same mo-
dality) or evoked by sounds (different modality). People can ex-
perience days of the weeks and months of the year as having
specific colors, shapes, spatial locations, and even personalities
(for review see Cohen Kadosh & Henik, 2007; Hubbard & Ram-
achandran, 2005; Rich & Mattingley, 2002).
Synaesthetic associations may occur via cross-activation of sen-
sory regions in the brain because of reduced synaptic pruning,
leaving additional connections not present in nonsynaesthetes
(e.g., Hubbard, Arman, Ramachandran, & Boynton, 2005; Maurer
& Maurer, 1988; Ramachandran & Hubbard, 2001). Other re-
searchers have proposed synaesthetic experiences are because of
disinhibited feedback between regions of the brain (e.g., Grossen-
bacher, 1997; Grossenbacher & Lovelace, 2001). That is, feedback
connections in the brain that are typically inhibited in most people
are disinhibited in synaesthetes, such that information from an
inducer pathway can propagate down a concurrent pathway, acti-
vating a concurrent representation (Grossenbacher & Lovelace,
2001). Combining both accounts to some extent, Smilek, Dixon,
Cudahy, and Merikle (2001) propose the reentrant processing
model that suggests the cause of synaesthesia as involving both
cortical connectivity and inhibition. More important, the model
proposes that the inducer activates meaning representations in
high-level processing regions, which then activate concurrent sen-
sory information via feedback connections.
Recent models of synaesthesia also emphasize a semantic di-
mension, proposing semantic activation of an inducer is required
before a synaesthetic concurrent is experienced (e.g., Chiou &
Rich, 2014; Meier, 2014). For example, in grapheme-color syn-
aesthesia, colors are typically experienced regardless of whether
the inducer was seen, heard, or simply thought about (Rich, Brad-
shaw, & Mattingley, 2005), and synaesthetic colors can be trans-
ferred to newly learned graphemes from an ancient alphabet once
an association between those graphemes and the familiar Latin
alphabet has been made (Mroczko, Metzinger, Singer, & Nikoli´
2009). Nikoli´
c (2009) proposes synaesthesia could more accu-
rately be named “ideasthesia,” Greek for “sensing ideas,” to reflect
that synaesthetic perception-like experiences are associated to cer-
tain ideas or concepts, rather than percepts.
Synaesthesia is not merely a curious condition of unusual phe-
nomenology; it can affect multiple aspects of cognition, including
perception and memory. Individuals with grapheme-color synaes-
thesia, where letters or numbers are experienced as having specific
colors (e.g., Baron-Cohen, Harrison, Goldstein, & Wyke, 1993;
Baron-Cohen, Wyke, & Binnie, 1987; Dixon, Smilek, Cudahy, &
Merikle, 2000) have been shown to perform better in visual search
tasks (Palmeri, Blake, Marois, Flanery, & Whetsell, 2002) and
experience higher levels of perceptual grouping for graphemes
(Ramachandran & Hubbard, 2001). Similarly, synaesthetes who
experience color concurrents have better color discrimination
(Banissy et al., 2013; Banissy, Walsh, & Ward, 2009; Yaro &
Ward, 2007), and synaesthetes with tactile concurrents have better
tactile discrimination (Banissy et al., 2009). Synaesthetes also have
better memory for stimuli that induces their synaesthesia (Mills,
Innis, Westendorf, Owsianiecki, & McDonald, 2006; Smilek,
Dixon, Cudahy, & Merikle, 2002; Yaro & Ward, 2007; but see
Rothen & Meier, 2009). For example, 6 months after being given
a list of people’s names, MLS—a letter-color synaesthete—re-
called significantly more names than a control group (Mills et al.,
More impressively still, there is evidence synaesthesia influ-
ences other aspects of cognition beyond the specific inducer/
concurrent modalities. For example, synaesthesia is related to
enhanced creativity, with synaesthetes demonstrating superior
ability to generate new ideas, and they more often pursue the arts
than nonsynaesthetes (Mulvenna, 2013). Synaesthetes also outper-
form controls at inferring the meaning of sound-symbolic words,
suggesting synaesthesia may exaggerate crossmodal associations
more generally (Bankieris & Simner, 2015). In line with this
proposal, Brang, Williams, and Ramachandran (2012) found mul-
timodal facilitation was enhanced more in synaesthetes than con-
trols. Participants were presented with either a colored letter, a
single tone, or both simultaneously (multimodal condition), and
were instructed to respond as soon as they detected a visual or
auditory cue (or both). Responses of synaesthetes and controls
were faster in the multimodal condition, but this benefit was
greater for the synaesthetes than the controls. This was the case
even though none of the synaesthetes experienced synaesthesia
with sound.
Taken together, the evidence suggests synaesthesia boosts sev-
eral aspects of cognition, especially within the modalities involved
in the synaesthetic experience. Therefore, synaesthesia involving
odor presents an excellent test bed to explore the human olfactory
potential. Further, if synaesthetic associations are semantically
mediated (e.g., Chiou & Rich, 2014; Meier, 2014)—that is, asso-
ciations are driven by an inducing concept rather than percept—
synaesthetic associations may strengthen concepts (Meier, 2014).
This is particularly important when considering the olfactory do-
main, where semantic representations may be weak (Olofsson &
Gottfried, 2015). In such a case, synaesthetic associations to odor
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could help alleviate difficulties in the semantic representation of
To test this idea we explored odor language and cognition in
odor-color synaesthesia. Although research in synaesthesia has
been prolific in recent years, it has focused heavily on synaesthesia
involving the visual modality, more specifically grapheme-to-color
synaesthesia. According to Day (2014), around 60% of synaes-
thetes experience grapheme-to-vision associations. In comparison,
synaesthesia involving odor as inducer or concurrent is rare: Day
(2014) estimates 6% of synaesthetes experience odor-to-vision
associations. Similarly, the Synaesthesia Battery (Eagleman, Ka-
gan, Nelson, Sagaram, & Sarma, 2007) has over 19,000 partici-
pants claiming synaesthesia (Eagleman, Kagan, Nelson, Sagaram,
& Sarma, 2007), but odor-color synaesthesia is experienced by
only 18% (Novich, Cheng, & Eagleman, 2011). Thus, the present
research also delves into an understudied subpopulation of syn-
aesthetes, and thus potentially sheds new light on the synaesthesia
phenomenon more generally.
Individuals with odor-color synaesthesia experience color sen-
sations when they smell odors (Russell, Stevenson, & Rich, 2015;
see Figure 1 for some examples). One of the earliest reports of this
type of synaesthesia can be found in Cytowic (1989), where a man
with odor-color synaesthesia describes his experience:
I remember at age 2 my father was on a ladder painting the left side
of the wall. The paint smelled blue, although he was painting it white.
I remember to this day thinking why the paint was white, when it
smelled blue (p. 24).
If synaesthetic color associations to odors strengthen their se-
mantic representation, there may be implications for a number of
elements of odor cognition. First, more stable semantic representa-
tions could improve odor language, which—as mentioned earlier—
is impoverished in the West (e.g., Cain, 1979; Desor & Beau-
champ, 1974; Lawless & Engen, 1977). Olofsson and Gottfried
(2015) propose problems of odor language may be due, in part, to
the little opportunity odor representations have to connect to other
types of semantic information. Linking odors with color informa-
tion may, therefore, help resolve this problem. Russell et al. (2015)
provided initial evidence for this proposal, by showing odor-color
Figure 1. Examples of odor-color associations. Panel A: Selection of colors chosen by Synaesthete D on both
testing days to everyday odors. Panel B: Synaesthete E’s association to odors combine color and shape, as
depicted here. See the online article for the color version of this figure.
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
synaesthetes were more consistent across time at naming odors
than a group of control participants. In this study, we replicate and
extend this finding.
Previous research with nonsynaesthetes has also suggested that
linking odors with language or semantic information can improve
odor memory and odor discrimination. Self-generated labels for
odors, or experimenter-generated pairings of odors to a label,
improves memory for odors compared with no labels paired with
odors (e.g., Batic & Gabassi, 1987; Kärnekull, Jönsson, Willander,
Sikström, & Larsson, 2015; Lyman & McDaniel, 1986). Similarly,
odor discrimination is better when participants are given odor
labels (de Wijk & Cain, 1994) or are trained with odor labels
(Rabin, 1988). Visual information may also be important for odor
discrimination: Jadauji, Djordjevic, Lundström, and Pack (2012)
found odor discrimination was improved after repetitive transcra-
nial magnetic stimulation (rTMS) to the visual cortex. If stimula-
tion of the visual cortex can improve odor perception, then syn-
aesthetic associations between odor and color information could
also lead to such improvements.
Another aspect of cognition that could be affected by synaes-
thesia is mental imagery. Synaesthesia and visual imagery are
thought to be intimately related (Karwoski & Odbert, 1938), and
individuals with synaesthesia report more vivid visual imagery
than controls (Barnett & Newell, 2008). Odor imagery in synaes-
thesia has not yet been investigated. Odor imagery has been shown
to correlate with odor perception (Köster, Stelt, Nixdorf, Linscho-
ten, de Wijk, & Mojet, 2014), and it has also been suggested that
greater olfactory experience may enhance odor imagery (Bensafi,
Tillman, Poncelet, Przybylski, & Rouby, 2013). This suggests
odor-color synaesthetes should also have superior odor imagery,
and potentially also visual imagery, compared with nonsynaes-
Current Investigation
Over two separate days we conducted a battery of tests assessing
odor language and cognition in odor-color synaesthetes and a
group of age-matched controls. Participants were asked to name
and match colors to odors, so that we could assess to what extent
the consistency of synaesthetic color associations is driven by odor
nameability (as observed in Russell et al., 2015, and in nonsyn-
aesthetes, de Valk, Wnuk, Huisman, & Majid, 2016). A semantic
account of synaesthesia would predict that odor-color associations
would be more consistent for more easily named odors. In addi-
tion, odor language can be assessed by looking at odor naming
accuracy and consistency across both days.
To assess whether odor-color synaesthesia affects odor percep-
tion, we conducted two olfactory tests: odor discrimination and
odor threshold. Odor discrimination refers to how well one can
discriminate between different odors, and can reflect higher-level,
semantic abilities. Odor threshold on the other hand, reflects the
ability to detect the presence of an odor, and is therefore a more
low-level perceptual ability. If synaesthetic associations to odor
strengthen the semantic representation of odor then we would
predict enhancements in odor discrimination, but not odor thresh-
Although we were primarily interested in odor cognition, pre-
vious findings have shown superior color discrimination in other
types of synaesthesia involving color concurrents (Banissy et al.,
2013; Banissy et al., 2009; Yaro & Ward, 2007). Therefore, we
tested color discrimination in the present odor-color synaesthetes
too. This allows us to, first, replicate previous findings and extend
to a new form of synaesthesia; and second, use this data as a form
of manipulation check of the current participants’ synaesthesia.
To investigate further the role of synaesthesia in olfactory
cognition, we used established questionnaires to assess visual and
olfactory mental imagery (Gilbert, Crouch, & Kemp, 1998; Marks,
1973), as well as the importance of olfaction in everyday life
(Croy, Buschhüter, Seo, Negoias, & Hummel, 2010).
Materials and Method
The study received ethical approval from the Radboud Univer-
sity Humanities Ethics Assessment Committee.
Six participants with odor-color synaesthesia (all female, mean
age 36, SD 14.42) and 17 age-matched controls (all female,
mean age 39.76, SD 13.04) without synaesthesia took part in
the study. We tested this number of control participants to cover
the age range of the synaesthetes sufficiently. Synaesthetes were
recruited in collaboration with the Language and Genetics Depart-
ment at the Max Plank Institute for Psycholinguistics, Nijmegen.
Participants had completed an online synaesthesia questionnaire
( which confirmed the authenticity of
one type of synaesthesia (i.e., grapheme-color) with measures of
consistency, and participants had indicated they also had synaes-
thesia involving odor. In addition, one synaesthete who wrote a
blog about her synaesthetic experience was invited to participate.
Control participants were recruited from the Radboud University
participant pool and from the first author’s home town in the
United Kingdom, where connections with age-matched partici-
pants existed.
All synaesthetes had more than one form of synaesthesia, and
commented their experiences were difficult to articulate (see Table
1). As well as colors, odor-evoked synaesthetic images sometimes
also contained shapes (e.g., “concave shape”) and textures (e.g.,
“flat,” “lots of points”), and for some individuals also numbers or
emotions. Color experiences also differed between participants, for
example, one synaesthete described the smell of people as her
strongest inducer of synaesthesia, whereas another found it hard to
identify color responses to smells of people. Similarly, one partic-
Table 1
Additional Forms of Synaesthesia Experienced by Participants
Synaesthete Types of synaesthesia
A Smell-vivid memories, music-color, music-emotion,
time-forms, letter-color
B Sensory translations move between smell, music, color,
texture, and numbers
C Grapheme-color
D Grapheme-color, data-color, seasons-color, sound-color,
sensitivity for emotions of others
E Number-color, number-personality, number-gender
F Number-color, circular calendar
Note. We report types of synaesthesia participants described, and make
no claim as to whether or not they are established forms of synaesthesia.
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ipant described the colors induced by perfumes as an “overall
pleasant experience,” even if the perfume was strong or artificial;
but a different participant found her experience of colors evoked
by strong perfumes as negative and said they “scrambled the
brain.” Participants reported colors evoked by odors were useful in
day-to-day activities. One participant preferred to use shampoos
and shower gels that induce a brown/amber color, while another
uses the appearance of an unexpected color to indicate states, such
as moldy food. Despite these idiosyncrasies, all participants with
odor-color synaesthesia experience color sensations to odors.
Before participants with odor-color synaesthesia were invited
to take part in the study, phone interviews were conducted, and
written questionnaires administered, to learn more about each
individuals’ synaesthetic experience, and to serve as an addi-
tional check of their authenticity as odor-color synaesthetes.
Participants were given smell categories gleaned from the an-
thropological literature (i.e., household smells, food smells,
drink smells, outdoor smells, travel smells, smells of people,
building smells, medicinal smells, animal smells, perfumes, and
other smells), and asked to provide examples of odors within
each category for which they have synaesthetic color experi-
ences. Table 2 summarizes various odors participants high-
lighted as synaesthetic inducers.
Eight commercial fragrances (four masculine and four feminine)
and 16 Sniffin’ Sticks (Hummel, Sekinger, Wolf, Pauli, & Kobal,
1997) taken from the Burghart Standard Identification test cover-
ing a range of everyday odors were used in an odor-color matching
task and an odor naming and rating task (see Appendix). After the
preexperiment questionnaire/discussion was conducted with each
Table 2
Odors Identified as Color Inducers by Synaesthetes in a Preexperiment Questionnaire (One Synaesthete Did Not Complete the
Odor category A B C D E
Household smells Vinegar, bleach, artificial
detergents, peppermint
salts, washing up
Shampoos, shower
gels, washing
laundry, towels
Ant killing spray,
dishwashing soap
Bleach, washing powder Bleach, ethanol, cleaner
Food smells Real banana, artificial
banana, chocolate,
apple, stew
Chocolate, sour candy Swiss cheese Warm bread, melting
butter from broiling
meat, red beet,
Drink smells Cola, coffee, juice Water Green tea, red wine Wine
Outdoor smells Grass, soil, flowers Flowers, forest Flowers Spring, air Hay, geranium, lily of
the valley, wet
leaves, wet soil, sea
water, side of a ditch
Travel smells Exhaust, gas, trains Diesel, kerosene Petrol, bus, new cars
Smells of people hair Children, friends,
Boyfriend Daughter, colleague,
passersby, mother’s
clothes, friend’s
clothes, new born
Building smells Construction, paint,
doctors surgery, school
People’s houses,
work, doctors,
School Workshop for car
repair, workshop for
metal, workshop for
wood, church
Medicinal smells Cough medicine, antacid Cough syrup Codfish oil, penicillin,
herbal tablets,
Animal smells Puppy, cat boxes,
elephant, domestic
hay, dog, bear
Gerbils, farms,
Hamster, guinea pig Wet dogs, pigs,
chicken, male goats,
sheep, cows,
carnivores in zoo,
Perfumes Musky, floral, spicy and
fruity, ocean, grass
Masculine, female,
old fashioned,
Floral Floral, freshness, heavy
Ma Vie Hugo Boss,
Old Spice
Other smells Books, paper, leather New magazine,
old book,
Old books, leather Books, paper, leather
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participant, it was clear that everyday odors and fragrances were
common inducers of color experiences. Further motivation to use
Sniffin’ Sticks was that they are easy to transport and administer in
a controlled manner.
Including the two sets of odors also enabled us to investigate
odors with associations to common odor sources (i.e., Sniffin’
sticks) versus odor mixtures (i.e., fragrances). Fragrances were
prepared by spraying plastic pellets with the scent and placing
them inside a squeezy bottle that was refreshed every other day. A
book of 1600 Munsell color chips, distributed across 40 pages with
one hue on each page, was used to investigate color matches to
Burghart’s Odor Discrimination and Odor Threshold tests
(Hummel et al., 1997) were used to assess odor perception. Each
odor test contained 16 triplets of odors (see Procedure. for more
details). Following Banissy et al. (2009), we used the Farnsworth-
Munsell 100 Hue Test (FMT; Farnsworth, 1957) to assess color
discrimination. This test contained four trays of 21 color chips
ordered according to hue.
In addition, we administered two tests of mental imagery: the
Vividness of Visual Imagery Questionnaire (VVIQ; Marks, 1973)
and the Vividness of Olfactory Imagery Questionnaire (VOIQ;
Gilbert et al., 1998). We also administered a questionnaire assess-
ing the importance of olfaction in everyday life (Croy et al., 2010).
The questionnaire assesses three subscales: association with olfac-
tory sensations, application of the sense of smell, and readiness to
draw consequences from olfactory perception.
Participants completed the battery of tests over 2 days with a 1
day gap in between. This was predominantly so that consistency of
color associations to odors over time could be established. Fur-
thermore, by assessing consistency of color associations and con-
sistency of odor naming 2 days later, rather than within the same
day, we reduce the likelihood that participants memorize their
responses. In addition, we split the testing session over 2 days to
reduce the duration of a single session and thereby avoid partici-
pant fatigue. Each participant was given a response booklet con-
taining instructions and response sheets for all tests in the battery.
Testing took place in well-ventilated rooms, and participants were
instructed not to wear perfume, and not to eat, drink (except
water), or smoke at least 30 min before the session. Table 3 depicts
the order of tasks completed across the 2 days. Odor tasks were
rotated between nonodor tasks to prevent participant fatigue. Par-
ticipants gave informed consent and were encouraged to take
breaks and drink water if they wished through the sessions.
Odor-color associations. To explore the consistency of syn-
aesthetic odor-color associations—and whether or not these asso-
ciations were driven by odor nameablity—participants smelled the
odors one at a time and were instructed to pick a color chip most
closely matching their synaesthetic association from the Munsell
color book. Control participants were instructed to choose the
color they thought “goes best” with the odor. Before testing began,
participants familiarized themselves with the Munsell color book
and the order of hues.
Participants could smell each odor as many times as they
wished. A break of at least 30 s between each odor was enforced.
Odors were presented to participants in random order. After a color
chip was chosen, participants rated how vivid their color experi-
ence was and how vivid their overall experience was (if the
synaesthetic concurrent included other features such as motion and
shape) on a 7-point scale. Control participants were instructed to
consider vividness as reflecting the ease with which they could
generate an association to the odors. This task was completed on
both testing days so we could also assess the consistency of color
choices. There was also space for participants to draw any shape or
texture associations they had to the odor (see Figure 1); however,
only two individuals used this space and only for a small number
of odors.
Odor naming and rating. In a separate task, participants
were presented with the same set of odors in a different random
order and asked to rate the familiarity, pleasantness, and intensity
of the odor on a 7-point scale. Finally, they named the odors by
writing their answer in response to the prompt question “What
smell is this?” Again, participants could smell each odor as many
times as they wished, and a break of at least 30 s between each
odor was enforced. This task was completed on both testing days
so we could assess naming consistency.
Odor threshold. Participants were presented with triplets
of Sniffin’ Sticks, two of which contained just water and one of
which contained n-butanol. Across triplets, the concentration of
n-butanol varied. Participants wore a blindfold and each pen was
held beneath the participants’ nose for 5 s. The experimenter
informed the participant when to sniff by saying “Now.” Partici-
pants were instructed to indicate which pen contained the odorant.
A staircase procedure was utilized to determine each participants’
threshold. The task was completed on the second testing day only.
Odor discrimination. Participants were presented with trip-
lets of Sniffin’ Sticks, two of which contained the same odor and
one a different odor. Pens were presented to participants in the
same manner as the odor threshold test. Participants were asked to
indicate which of the three pens smelled different. A total score of
correct decisions was computed. This task was completed on the
first testing day only.
Color discrimination. Participants were presented with the
four trays of color chips from the FMT in turn. Two lamps with
daylight 860 illumination were placed on either side of the trays to
ensure comparable lighting conditions. Participants were in-
structed to arrange the chips in order of hue so that a smooth
continuum of color was formed. Each color chip possessed a code
so that an error score for each tray could be computed by inputting
the codes into the FMT scoring software. The error score for each
color chip is the sum of the differences between the number of that
Table 3
Order of Tasks across the 2 Days of Testing, Witha1Day
Break in Between
Day 1 Day 2
1. Odor-color associations 1. Odor-color associations
2. FMT 2. Color chip rating
3. Odor naming and rating 3. Odor naming and rating
4. VVIQ and VOIQ 4. Importance of olfaction questionnaire
5. Odor discrimination test 5. Odor threshold test
Note. FMT Farnsworth-Munsell 100 Hue Test; VVIQ Vividness of
Visual Imagery Questionnaire; VOIQ Vividness of Olfactory Imagery
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chip and the number of the chips adjacent to it, minus two. This
task was completed on the first testing day only.
Questionnaires. The VVIQ contained 16 statements describ-
ing visual scenes (e.g., The sun is rising above the horizon into a
hazy sky), and the VOIQ contained 16 statements describing ol-
factory scenes (e.g., The smell of your shirt or blouse when you
remove it). Participants were instructed to imagine each scene and
rate the strength of their mental image from 1, for example,
perfectly clear and vivid as normal vision”to5“no image at all
(only “knowing” that you are thinking of the object)”. They wrote
their ratings in a box provided next to each description. For the
VVIQ participants were instructed to complete the questionnaire
once imagining the described scenes with their eyes open, and
once with their eyes closed.
The importance of olfaction questionnaire contains 20 state-
ments (e.g., Certain smells immediately activate strong feelings).
Participants were instructed to read each statement carefully and
place a cross in a box corresponding to how much they agreed with
that statement: “totally agree,” “mostly agree,” “mostly disagree,”
or “totally disagree.”
To assess the role of odor-color synaesthesia in odor cognition
and language, we compared synaesthetes’ performance with that of
the age-matched control participants All results are displayed in
Table 5.
Odor-Color Associations and the Role of Naming
If semantic activation of an odor is required for a synaesthetic
color experience to occur, then color associations should be more
consistent for odors that are easy to name (named accurately and
consistently) than those that are difficult to name (named incor-
rectly and inconsistently Russell et al., 2015). To test this, we
assessed the role of naming (both accuracy and consistency) on the
consistency of color choices in synaesthetes and control partici-
pants. A name was correct if it matched the source of the Sniffin’
Stick (e.g., cinnamon, orange). For fragrances, naming was correct
if they used terms such as fragrance,perfume. If participants
specifically indicated a gender of fragrance that was incorrect,
their response was recorded as incorrect (e.g., saying male fra-
grance for a female perfume).
Accuracy of naming was assessed by three researchers, and if
any disagreements arose, accuracy was determined by the majority
opinion. A score of 1 was given if participants named an odor
correctly on either the first day or the second day. For example, if
the garlic Sniffin’ Stick was correctly named “garlic” on the first
day, but then “onion” the second day, it would be scored as 1. If,
however, the participant incorrectly said onion on both days they
would receive a score of 0. The overall score then reflects the
average across odors. For consistency, a score of 1 was given if a
participant named the odor the same on Day 1 and Day 2, other-
wise a score of 0 was given. If an odor was named consistently but
incorrectly on both occasions, it was still scored as consistent. If
participants perceived the odor as the same on both days, even if
they identified it incorrectly, their colors choices on both occasions
should still be more similar than if they had named the odor
Munsell colors were converted to CIE LAB values and the
distance between colors chosen on Day 1 and Day 2 was calculated
in terms of Delta E.
A smaller value of Delta E indicates a smaller
distance, and hence more similar colors (i.e., more consistent color
choices). Overall, there was no significant difference in Delta E
between synaesthetes and controls, t(21) .32, p.76, d.16.
Odor-Color Associations and Naming Accuracy
To assess the effect of naming accuracy on color associations,
Delta E values were analyzed with a 2 (naming correct vs. incor-
rect) 2 (synaesthetes vs. controls) mixed analysis of variance
(ANOVA) separately for Sniffin’ Sticks and fragrances. There was
a main effect of naming accuracy for Sniffin’ Sticks, F(1, 21)
7.1, p.014, p
2.25, such that Delta E was smaller (colors more
consistent) for odors named correctly compared with odors named
incorrectly (M37.00 vs. 47.68). There was no difference be-
tween synaesthetes and controls, F(1, 21) 1.73, p.20, p
.08, (M45.28 vs. 39.41) and no interaction between group and
naming consistency F(1, 21) 1.64, p.21, p
2.07. For
fragrances no effects were significant: neither the main effect of
naming accuracy F(1, 16) .17, p.69, p
2.01; group F(1,
16) .42, p.53, p
2.03; nor the interaction F(1, 16) .04,
p.84, p
Mean Delta E values for Sniffin’ Sticks and
fragrances named correctly and incorrectly are displayed in Figure 2.
Odor-Color Associations and Naming Consistency
Two further ANOVAs assessing naming consistency, instead of
naming accuracy found a main effect for Sniffin’ Sticks F(1, 21)
6.02, p.023, p
2.22, such that Delta E was smaller (colors
more consistent) for odors named consistently compared to odors
named inconsistently (M37.38 vs. 48.8). There was no differ-
ence between synaesthetes and controls F(1, 21) 1.44, p.24,
2.06, and no interaction between group and naming consis-
tency F(1, 21) .01, p.92, p
2.001. For fragrances, neither
main effects of naming consistency F(1, 17) .18, p.68, p
.01, group F(1, 17) .11, p.75, p
2.01, nor the interaction
were significant F(1, 17) .02, p.90, p
2.001; see Figure 3.
To summarize, easier to name everyday odors (i.e., Sniffin’
Sticks) were associated with more consistent synaesthetic color
experiences for synaesthetes, and more consistent associations for
control participants, supporting semantic accounts of synaesthesia
(cf., Chiou & Rich, 2014).
Vividness of Associations
Vividness of color association ratings were analyzed with a 2
2 mixed ANOVA with odor type (Sniffin’ Sticks vs. fragrances) as
a within subjects factor and group (synaesthetes vs. controls) as a
between subjects factor. There was no difference in vividness
ratings between Sniffin’ Sticks and fragrances F(1, 21) 1.11,
One synaesthete occasionally chose more than one color chip to reflect
their synaesthetic association. In such instances, we calculated the distance
for the most similar colors across the 2 days.
Six control participants were not included in this analysis because their
naming accuracy was 0 for fragrances.
Three control participants were not included in this analysis because
their naming consistency was 0 for fragrances.
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p.31, p
2.06, nor between synaesthetes and controls, F(1,
21) .31, p.58, p
2.02, and no interaction between the two
factors, F(1, 21) 1.14, p.30, p
2.05. Because control
participants were only asked about color associations, ratings of
“overall” intensity only applied to the synaesthetes. A pairwise t
test found no difference in overall vividness between Sniffin’
Sticks and fragrances, t(5) .3, p.75, d.03. Examples of
colors chosen by synaesthetes to specific odors are displayed in
Figure 1.
Odor Naming and Rating
Two independent ttests were conducted to compare accuracy in
naming (whether the odor was correctly named on either day, i.e.,
they gave the correct name at least once) and consistency in
naming responses (i.e., whether the same response was given on
both days) between synaesthetes and control participants. Synaes-
thetes were more accurate at naming both Sniffin’ Sticks, (M
57% vs. 40%), t(21) 3.28, p.004, d1.43, and fragrances,
(M44% vs. 20%), t(21) 2.39, p.026, d1.04. Synaes-
thetes were also more consistent in their naming across both days
than control participants (as Russell et al., 2015 found too), but this
was only the case for Sniffin’ Sticks (M66% vs. 44%), t(21)
2.52, p.02, d1.10, not fragrances, (M31% vs. 24%),
t(21) .79, p.44, d.34.
Ratings of odor familiarity, pleasantness, and intensity
submitted to 2 2 mixed ANOVAs with odor type (Sniffin’
Sticks vs. fragrances) as a within subjects factor and group (syn-
aesthetes vs. controls) as a between subjects factor.
For familiarity ratings there was a marginal effect of odor type,
with Sniffin’ sticks rated as more familiar than fragrances F(1,
21) 3.38, p.08, p
2.14, but there was no difference between
synaesthetes and controls F(1, 21) .89, p.36, p
2,.04, and
no interaction F(1, 21) .81, p.38, p
Fragrances were rated as more pleasant than Sniffin’ Sticks F(1,
21) 9.73, p.005, p
2,.32, but there was also an interaction
between odor type and group F(1, 21) 12.60, p.001, p
.38. Follow-up ttests showed controls perceived fragrances as
more pleasant than Sniffin’ Sticks (M5.81 vs. 4.24), t(16)
7.26, p.001, d1.91, but there was no difference between
fragrances and Sniffin’ Sticks for synaesthetes (M4.6 vs. 4.71),
t(5) .20, p.85, d.10. This is in line with comments from
some participants that strong commercial fragrances lead to un-
pleasant synaesthetic experiences (see Participants). There was no
overall difference between synaesthetes and controls F(1, 21)
1.12, p.3, p
Sniffin’ Sticks were rated as more intense than fragrances F(1,
21) 8.08, p.01, p
2.28, but there was no difference in
intensity ratings between synaesthetes and controls F(1, 21) 0.1,
p.93, p
2.001, and no interaction F(1, 21) .48, p.50,
Perceptual Tasks
Three independent ttests were conducted to compare perfor-
mance between synaesthetes and control participants on the odor
discrimination and odor threshold test, and the FMT.
Odor Threshold. There was no difference between synaes-
thetes and controls on the odor threshold task (M6.59 vs. 6.38)
t(21) ⫽⫺.13, p.9, d.05. Mean odor threshold scores are
displayed in Table 4.
Odor Discrimination. Synaesthetes outperformed controls on
the odor discrimination task (M13.83 vs. 11.71 out of 16),
t(21) 2.32, p.03, d1.01. Compared with existing norms for
odor discrimination for females in the general population (average
score of 12.69, Hummel, Kobal, Gudziol, & Mackay-Sim, 2007),
the present synaesthetes also appear to perform higher. Mean odor
discrimination scores are displayed in Table 4.
Color Discrimination. Using the FMT test we found synaes-
thetes (error score 39.33) were better at discriminating between
colors than control participants (error score 89.12), t(21) 2.15,
p.04, d.94, replicating findings with other forms of synaes-
thesia involving color concurrents (Banissy et al., 2009). The
present results can also be compared to norms for the general
population; for example, Verriest’s (1963) data for nonsynaes-
thetes. The range of error scores in that population varies from
Average ratings of familiarity, pleasantness and intensity of each odor
are included in Appendix as a resource for other researchers.
Figure 2. Delta E values for Sniffin’ Sticks and fragrances named cor-
rectly and incorrectly by synaesthetes and controls. Error bars depict 1 SE.
An asterisk indicates a significant difference.
Figure 3. Delta E values for Sniffin’ Sticks and fragrances named con-
sistently and inconsistently by synaesthetes and controls. Error bars depict
1SE. An asterisk indicates a significant difference.
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36.3 to 90.4. So, the present synaesthetes are close to the best
performing participants of Verriest (1963), while the control group
closer to the lowest performing participants. The mean error scores
for the synaesthetes and controls are also comparable to those
observed in Banissy et al. (2009) who concluded that synaesthetes
had superior color discrimination. Mean scores on the FMT are
displayed in Table 4.
We further explored whether the superior color discrimination
performance of synaesthetes occurred in specific regions of color
space. Following Laeng, Brennen, Elden, Gaare Paulsen, Banerjee,
and Lipton (2007) we divided the Munsell chips into their 10 step
hue subdivisions (red, yellow-red, yellow, green-yellow, green,
blue-green, blue, purple-blue, purple, and red-purple) and per-
formed a mixed ANOVA with hue as a within-participants factor
and group as a between-participants factor. There was a main
effect of hue F(9, 189) 7.36, p.001, p
2.26, and group F(1,
21) 5.75, p.026, p
2.22, but importantly there was a
significant interaction between hue and group F(9, 189) 2.43,
p.012, p
2.10. Synaesthetes made less errors than controls
within the yellow (d0.92), green-yellow (d1.30), green (d
1.04), red (d1.01), and red-purple (d1.26) subregions (see
Figure 4).
Visual and Olfactory Imagery
Ratings on the imagery questionnaires were averaged according
to the questionnaire guidelines (Gilbert et al., 1998; Marks, 1973).
Cronbach’s was high for the VVIQ eyes open (␣⫽.95), VVIQ
eyes closed (␣⫽.94),
and VOIQ (␣⫽.94). There was no
difference in visual imagery between synaesthetes and controls
when the VVIQ was completed with the eyes open (M1.85 vs.
2.24), t(21) 1.10, p.29, d0.48, or eyes closed (M1.7
vs. 2.25), t(21) 1.48, p.15, d0.65. Similarly, there was no
difference between synaesthetes and controls in olfactory imagery
ability, that is, VOIQ (M2.05 vs. 2.69), t(21) 1.52, p.14,
Importance of Olfaction Questionnaire
Again, questionnaire data were treated according to the original
guidelines of Croy et al. (2010). Cronbach’s was high for the
application (␣⫽.79) and association scale (␣⫽.81), but it was
fairly low for the consequence scale (␣⫽.56), suggesting this
scale should be interpreted with caution. An overall score with
responses summed across the three subscales was calculated. For
this measure synaesthetes (M61.17) were significantly higher
than nonsynaesthetes (M52.76), t(21) 2.4, p.026, d
1.05. Comparing subscales separately, synaesthetes scored higher
for measures of application, that is, how much a person uses their
sense of smell in everyday life (M21.33 vs. 16.24), t(21)
3.01, p.007, d1.31; but not for measures of association (e.g.,
emotions, memories and evaluations triggered by smell; M
20.83 vs. 18.12), t(21) 1.91, p.07, d.083, or measures of
consequence (i.e., conclusions drawn from olfactory impressions;
M19 vs. 18.41), t(21) .42, p.68, d.18.
We investigated odor perception and language in odor-color
synaesthetes, individuals who have involuntary color experiences
to odors. Overall, synaesthetes were more accurate and consistent
in naming odors, and better able to discriminate between odors
than age-matched control participants. In addition, synaesthetes
were better than controls at discriminating between colors, dem-
onstrating synaesthetes can have superior perception in both the
inducer and concurrent modality; to our knowledge, a finding not
previously reported.
Everyday odors that were easier to name were associated with
more consistent synaesthetic color experiences, and more consis-
tent color choices in control participants. This suggests synaes-
thetic associations to odors, and cross-modal associations between
odor and color demonstrated in nonsynaesthetes (e.g., Gilbert,
Martin, & Kemp, 1996; Stevenson, Rich, & Russell, 2012), can be
explained by semantic factors; that is, color information is more
accessible for odor concepts that are more accessible.
Why were color choices equally consistent in controls and synaes-
thetes? Although this finding appears problematic for a study of
synaesthesia, where consistency is a defining characteristic, we be-
Data from two participants was excluded in the reliability analysis of
the VVIQ because participants did not provide responses for the first
question in the questionnaire.
Table 4
Odor Threshold (Concentration Level), Odor Discrimination
(Total Number of Correct Responses), and Color Discrimination
(FMT Error Scores) Scores for Individual Synaesthete and
Controls (Mean; Error Bars in Brackets)
(FMT error score)
Controls 6.59 (.90) 11.71 (.48) 82.12 (10.90)
Synaesthete A 6 15 32
Synaesthete B 6.5 13 44
Synaesthete C 4.5 12 96
Synaesthete D 2 12 20
Synaesthete E 9.5 16 8
Synaesthete F 9.75 15 36
Note. FMT Farnsworth-Munsell 100 Hue Test.
Table 5
Means and SD for Each Task Administered
Task Synaesthetes Controls
Color distance (Delta E) 44.17 (12.98) 40.78 (7.27)
Naming consistency
.54 (.11) .38 (.17)
Naming accuracy
.53 (.14) .33 (.10)
Odor threshold 6.38 (2.97) 6.59 (3.73)
Odor discrimination
13.83 (1.72) 11.71 (1.99)
39.33 (30.51) 82.12 (44.92)
Visual imagery (open eyes) 1.85 (.54) 2.24 (.82)
Visual imagery (closed eyes) 1.70 (.55) 2.25 (.84)
Olfactory imagery 2.05 (.53) 2.69 (.96)
Olfactory importance (total)
61.17 (7.14) 52.76 (7.44)
Olfactory application
21.33 (2.34) 16.24 (3.87)
Olfactory association 20.83 (3.43) 18.12 (2.85)
Olfactory consequence 19.00 (3.29) 18.41 (2.83)
Note. Asterisk indicates a significant difference between synaesthetes
and controls. FMT Farnsworth-Munsell 100 Hue Test.
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lieve this finding is expected. Previous studies have demonstrated that
nonsynaesthetes can easily and consistently match colors to odors
(e.g., de Valk et al., 2016; Gilbert et al., 1996; Levitan et al., 2014).
Colors matched to odors often match the color of the source object (de
Valk et al., 2016; Gilbert et al., 1996); for example, caramel with
brown. Because odor sources typically have specific colors, it is not
surprising that people can easily place a color with an odor. The lack
of an additional advantage for odor-color synaesthetes could be be-
cause of competition between real-world odor-color associations and
synaesthetic odor-color associations. Figure 1 shows the synaesthetic
colors to leather and rose odors, for example, do not match the typical
color of the odor source (pink instead of brown, and yellow instead of
pink/red). So synaesthetic odor-color associations do not necessarily
mirror real-world odor-color associations. In fact, one participant
described her color concurrent to the odor of banana as beginning
with yellow, because she knows bananas are yellow, but then chang-
ing to her synaesthetic experience of pink.
It is possible that color choices in synaesthetes are a mixture of
real-world and synaesthetic associations. If correct, this might even
lead to the prediction that color choices in synaesthetes would be less
consistent than in controls, if they respond using real-world associa-
tions on one day, but synaesthetic associations on the other day. As
noted in the introduction, odors are difficult to name, and can often be
named differently by the same person on different days (e.g., Cain,
1979; Desor & Beauchamp, 1974; Lawless & Engen, 1977). Taken
together, it is possible odors are being perceived, or identified, differ-
ently on Day 1 and Day 2, leading to variable color concurrents.
Previously, Simner (2012) has suggested that using consistency as a
“gold standard” of synaesthesia is questionable, and may lead to a
selection bias, potentially ruling out cases of genuine synaesthesia that
do not display this feature. In line with this objection, one synaesthete
in the present study commented in the prestudy interview that her
synaesthetic colors can be modified over time. Because there are of
over 60 different forms of synaesthesia, sometimes with very different
phenomenologies, it might be time to reconsider what are merely
operational characteristics applicable to only some sorts of synaesthe-
sia and what are core characteristics common to all. For example,
consistency may be particularly relevant for grapheme-color synaes-
thesia because graphemes have fixed labels and stable concepts. In
comparison, odor naming is poor and the same odor can be perceived
differently from one occasion to the next, suggesting odor concepts
are more unstable.
Odor-color synaesthesia has benefits for olfactory language, with
odor naming both more consistent and accurate than among control
participants. This finding is in line with recent work suggesting odor
naming difficulties are not universal, and may be overcome by expe-
rience. In cultures, such as the Jahai in the Malay Peninsula, people
are just as good at naming odors as naming colors, and better at
Figure 4. Synaesthetes’ and controls’ average FMT error score across all 85 color chips (A) and across 10 step
hue subregions (B). Error bars reflect 1 SE. See the online article for the color version of this figure.
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naming odors than English speakers (Majid & Burenhult, 2014). For
the Jahai, odors are a significant part of their everyday life, featuring
in their communication, everyday actions, and belief system (Buren-
hult & Majid, 2011). Here we provide evidence of another way, aside
from cultural factors, olfactory naming can be boosted. Connections
between odor concepts and other sensory areas of the brain, such as
vision, can similarly improve odor naming ability. A recent study
found greater semantic richness (i.e., more semantic features) can lead
to enhanced conceptual activation, facilitating access to lexical rep-
resentations, and subsequent faster lexical selection and naming
(Rabovsky, Schad, & Abdel Rahman, 2016). We propose synaes-
thetic associations to odors act as additional semantic features, in-
creasing the semantic richness of the odor concept, and thereby
facilitating odor naming.
Odor-color synaesthetes were better than controls at discriminating
between odors, but not at detecting odors. Odor discrimination is
considered a higher-level process than odor detection. Supporting this,
lesions to the temporal lobes cause deficits in discrimination but not
detection (Zatorre & Jones-Gotman, 1991). In addition, cognitive
variables (measures of executive function and semantic memory)
predict individual odor discrimination scores, but not odor threshold
scores (Hedner, Larsson, Arnold, Zucco, & Hummel, 2010). Odor
discrimination is also improved with the availability of (de Wijk &
Cain, 1994) or training with (Rabin, 1988) odor labels. Synaesthetic
associations to odor, therefore, do not aid processing of low-level
sensory properties of an odor, but rather enhance discriminatory
properties, making odors more distinct from each other. Could the
lack of difference in the threshold task be because of more mundane
reasons? For example, it was the final task on the final day, so
participants were susceptible to olfactory fatigue. We think this is
unlikely because participants were given a one day break between
testing days. In addition, the odor discrimination task and odor thresh-
old task were completed with equal amounts of odor exposure on each
test day (see Table 1). Finally, the attested results fit the previously
reported findings of a conceptual, not perceptual, effect.
That odor-color synaesthesia improves both odor discrimination
and odor naming is consistent with models of synaesthesia in which
synaesthetic concurrents are seen as extra connections in a semantic
network, enriching conceptual representations (Meier, 2014). Accord-
ing to some models of semantics (e.g., Barsalou, 1999; Rogers,
Lambon Ralph, Garrard, Bozeat, McClelland, Hodges, & Patterson,
2004) meaning is distributed across modality-specific regions of the
brain. So, synaesthetic color activation to odors may have become
integrated with the concept of the odor, along with its olfactory
features. We suggest this conceptual enrichment strengthens odor
concepts so they become more differentiated (leading to improved
odor discrimination) and facilitate access to lexical information (lead-
ing to improved odor naming). It is possible, however, that the results
could be explained by another underlying mechanism that affects both
olfactory cognition and the propensity to develop odor synaesthesia.
Such an explanation could be explored by tracking the development
of synaesthesia and related cognition from an early age.
We also found synaesthetes were better at discriminating between
colors than controls. This replicates previous findings of improved
color discrimination (Banissy et al., 2009, 2013; Yaro & Ward, 2007),
and observed differences in early components of visual-evoked po-
tentials (Barnett et al., 2008; Goller, Otten, & Ward, 2009), to another
form of synaesthesia involving color concurrents. However, because
all participants additionally experience other forms of synaesthesia
involving color concurrents (see Table 1), we cannot conclude that
this superior performance is because of the presence of odor-color
synaesthesia specifically. Previous studies have also found that texture
discrimination is improved in mirror-touch synaesthesia (Banissy et
al., 2009) suggesting enhanced perceptual processing is “a core prop-
erty of synaesthesia.” Such advantages observed within the concurrent
domain could be related to differences in brain development, such as
enhanced cortical connections within the concurrent modality, or
enriched perceptual experience as a result of experience with the
concurrents (Banissy et al., 2009, 2013). Banissy et al. (2009) describe
synaesthesia as involving an “oversensitive concurrent perceptual
The FMT revealed synaesthetes’ superior color discrimination was
specific to the hue subregions yellow, green-yellow, green, purple,
and red-purple. Although we did not predict differences within spe-
cific regions, previous research has shown that 2-month-olds fail in a
color discrimination task specifically in the yellow/green and mid-
purple ranges (Teller, Peeples, & Sekel, 1978), but not other color
ranges. Making a link between this finding and the present result may
be premature, but, if synaesthesia is a developmental phenomenon
(Maurer & Maurer, 1988), then early experiences with color will be of
great importance to the development of synaesthetic associations. On
the other hand, there is evidence suggesting that although synaesthetic
associations can be observed early in development, they may take
several years to fully emerge (Simner & Bain, 2013). Furthermore, the
trajectory of development may differ across perceptual modalities: for
example, lexical-gustatory synaesthesia may develop only later
through associations with food-related words (Simner & Haywood,
2009). This is the first time color discrimination in synaesthesia has
been addressed in such detail, and it clearly requires further investi-
Using two mental imagery questionnaires assessing visual and odor
imagery, we did not find any differences between synaesthetes and
controls, although there was a numerical suggestion that synaesthetes
found both types of imagery easier. It is possible, then, that the
perceptual and conceptual enhancements observed here do not over-
lap with systems utilized in visual and olfactory imagery. On the other
hand, the current study may be underpowered to detect such effects,
with only six odor-color synaesthetes. Finally, a questionnaire assess-
ing the importance of olfaction found synaesthetes scored higher on
the application scale than controls; that is, synaesthetes were more
likely to intentionally use their sense of smell in everyday life. So,
synaesthesia involving odors also has implications for how the sense
of smell is used from day to day.
Human olfaction has been underestimated for centuries, but the
feats our sense of smell can accomplish are, in fact, quite astounding
(e.g., Bushdid, Magnasco, Vosshall, & Keller, 2014; Laska, Seibt, &
Weber, 2000; Majid et al., 2017; Porter et al., 2007). In this study, we
show olfactory language and cognition is further enhanced in people
with olfactory synaesthesia. We suggest synaesthetic associations
strengthen semantic links with odor concepts, leading to stronger
conceptual representations and subsequently better discrimination and
naming. This study is also the first, to our knowledge, to demonstrate
improved perceptual abilities in both the inducer and concurrent
modality simultaneously in synaesthesia. So not only do synaesthetes
have additional perceptual experiences (i.e., experience colors), but
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their primary perceptual experience (i.e., their experience of smells) is
also different to nonsynaesthetes. In sum, synaesthetic associations for
olfaction may not be epiphenomenal, but instead play a critical role in
shaping concepts.
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List of Odors
Odor Familiarity Pleasantness Intensity
Hugo Boss - Orange 4.67 5.54 4.48
Calvin Klein - Eternity 4.71 5.67 4.93
Armani Si 4.78 5.22 4.86
Dior - Jádore 5.22 5.58 4.96
Chanel - Bleu de Chanel 4.43 5.46 4.72
Davidoff - Cool Waters 4.65 5.70 4.98
Joop! 4.70 5.39 5.46
Hugo Boss - Boss Bottled 4.48 5.40 4.65
Sniffin’ Sticks
Orange 5.57 5.87 5.40
Coffee 4.98 4.85 5.63
Apple 4.07 5.00 5.65
Clove 3.59 3.39 6.29
Pineapple 3.97 4.79 5.53
Rose 4.33 5.30 5.37
Aniseed 4.11 4.72 5.02
Fish 3.70 1.84 6.41
Leather 3.33 3.85 4.35
Cinnamon 3.85 4.35 4.72
Peppermint 5.53 5.58 5.96
Banana 4.96 5.38 5.84
Lemon 3.43 4.34 4.88
Licorice 4.07 4.61 4.96
Turpentine 3.33 3.50 5.89
Garlic 3.96 2.37 6.46
Note. Odors used for odor-color associations and naming, with their average ratings of familiarity (1 very unfamiliar,
7very familiar), pleasantness (1 very unpleasant,7very pleasant), and intensity (1 low intensity,7high
Received January 31, 2017
Revision received May 12, 2017
Accepted May 30, 2017
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... Experimental studies typically present people with decontextualized odors in opaque jars or bottles and ask people to name the smell. Under these conditions, even familiar, everyday smells (e.g., chocolate, coffee, banana) are frequently named incorrectly [31,[39][40][41]57,58]. Compared with pictures, odors take up to four times longer to name, and responses are less accurate and consistent [31]. ...
... For most people, naming odors is difficult [31,[39][40][41]57,58], and this is often interpreted to mean that language is poorly connected to olfactory perceptual representations [28,111]. In a wide-ranging review of the literature, Yeshurun and Sobel [30] conclude that the weak connection between language and olfaction is symmetrical: it is as difficult to activate olfactory representations from language as it is to activate language from olfaction. ...
... associate odors with colors they do so in systematic ways [58,[103][104][105][106]. This could happen in at least two ways: odor perceptual representations could link directly to color due to statistical cooccurrences in the environment or the association between odors and colors could be mediated Box ...
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... This phenomenon, broadly speaking, occurs when stimulation in one sensory modality causes unusual, albeit unexpected output in another modality [9]. Synesthetes sometimes possess superior cognitive benefits relating to their form of synaesthesia [10]- [12]. ...
... For more information, see Synesthetes with odour to vision synesthesia have been shown to have a consistent and increased sensitivity for odour and colour discrimination, as well as the correct identification of odours [12]. A small body of research [13]- [15] has shown that it is possible to replicate the phenomenology of synesthesia in non-synesthetes. ...
... These results show that our system could enhance human odour discrimination in a simple task, which is comparable to that of natural synesthesia [12]. Although more prolonged usage of the system will need to be conducted to determine if the artificial emulation of odour-vision synesthesia can facilitate colour discrimination, odour identification and the extent of odour discrimination. ...
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The phenomenology of synaesthesia provides numerous cognitive benefits, which could be used towards augmenting interactive experiences with more refined multisensorial capabilities leading to more engaging and enriched experiences, better designs, and more transparent human-machine interfaces. In this study, we report a novel framework for the transformation of odours into the visual domain by applying the ideology from synaesthesia, to a low cost, portable, augmented reality / virtual reality system. The benefits of generating an artificial form of synesthesia are outlined and implemented using a custom made electronic nose to gather information about odour sources which is then sent to a mobile computing engine for characterisation, classification, and visualisation. The odours are visualised in the form of coloured 2D abstract shapes in real-time. Our results show that our affordable system has the potential to increase human odour discrimination comparable to that of natural syneasthesia highlighting the prospects for augmenting human-machine interfaces with an artificial form of this phenomenon.
... Historical interest in the topic of crossmodal correspondences involving odour first emerged amongst artists and scientists during the middle decades of the 19 th century (Baudelaire 1857(Baudelaire /1954Piesse 1857;Taylor 1963). However, while a small number of cases of olfactory-colour synaesthesia have been reported over the intervening years (e.g., see Speed & Majid 2018) the topic of involuntarily-induced crossmodal mental imagery ) would appear to provide a much more satisfactory explanation for the experience of scent that artists such as Cézanne once hoped to evoke in those viewing their paintings (Merleau-Ponty 1964). ...
... Over the course of the last century or so, a number of striking cases of odour-colour synaesthesia have been reported in the literature (see Cytowic 1993;Ginsberg 1923;Luria 1968;Speed & Majid 2018). Despite the fact that cases of odour-colour synaesthesia obviously do exist, it is not clear that the nature of the idiosyncratic colour-odour associations involved necessarily have any relevance in terms of either predicting, or else helping to explain, the widespread crossmodal correspondences between odour and colour that have been documented in the general (that is, the non-synaesthetic) population. ...
... While acknowledging the existence of a very small number of individuals who may well experience olfactory-colour synaesthesia (Speed & Majid 2018), in the contemporary era, researchers have generally tended to consider these shared odour-colour correspondences as representing a somewhat distinct class of empirical phenomenon (see Spence in press, for a review). In fact, nowadays the majority of researchers have tended to explain these crossmodal mappings in terms of learned associations instead (Spence 2011, in press) and/or in terms of less clearly defined 'natural mappings' (see Spector & Maurer 2012). ...
... In that case, the same synaesthetic colors should be activated during comprehension of language describing the sound of that musical instrument. Initial evidence suggests a relationship between synaesthesia and language (Russell, Stevenson, & Rich, 2015;Speed & Majid, 2018b). For example, the colors experienced by individuals with odor-color synaesthesia, who experience colors when they smell odors, were shown to be driven by the name given to the odor (Russell et al., 2015). ...
... For example, the colors experienced by individuals with odor-color synaesthesia, who experience colors when they smell odors, were shown to be driven by the name given to the odor (Russell et al., 2015). Importantly, odor-color synaesthetes were better at naming odors than control participants without synaesthesia (Speed & Majid, 2018b). It suggests that color associations become integrated into the conceptual representation of the odor, subsequently facilitating naming. ...
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Embodied theories of cognition consider many aspects of language and other cognitive domains as the result of sensory and motor processes. In this view, the appraisal and the use of concepts are based on mechanisms of simulation grounded on prior sensorimotor experiences. Even though these theories continue receiving attention and support, increasing evidence indicates the need to consider the flexible nature of the simulation process, and to accordingly refine embodied accounts. In this consensus paper, we discuss two potential sources of variability in experimental studies on embodiment of language: individual differences and context. Specifically, we show how factors contributing to individual differences may explain inconsistent findings in embodied language phenomena. These factors include sensorimotor or cultural experiences, imagery, context-related factors, and cognitive strategies. We also analyze the different contextual modulations, from single words to sentences and narratives, as well as the top-down and bottom-up influences. Similarly, we review recent efforts to include cultural and language diversity, aging, neurodegenerative diseases, and brain disorders, as well as bilingual evidence into the embodiment framework. We address the importance of considering individual differences and context in clinical studies to drive translational research more efficiently, and we indicate recommendations on how to correctly address these issues in future research. Systematically investigating individual differences and context may contribute to understanding the dynamic nature of simulation in language processes, refining embodied theories of cognition, and ultimately filling the gap between cognition in artificial experimental settings and cognition in the wild (i.e., in everyday life).
... ex. CohenKadosh et Henik, 2007;Speed et Majid, 2017), ainsi qu'à des capacités de pensée divergente hautement développées parce que le profil cognitif tend à faire des associations indirectes et inhabituelles (p. ex.Ramachandran et Hubbard, 2003a).Par ailleurs, peu d'études mettent en valeur l'absence d'effet de la synesthésie en ce qui a trait aux aptitudes en créativité ou du moins, peu d'études sont indicatives de résultats dans les normes à ce sujet chez les synesthètes. ...
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La synesthésie est une condition neurologique dans laquelle une stimulation sensorielle ou cognitive dans une modalité spécifique engendre de façon automatique et involontaire une autre expérience perceptuelle inhabituelle. La synesthésie influencerait le développement de certaines habiletés cognitives, notamment sur le plan mnésique. Par ailleurs, une hypothèse intuitive populaire au sein de la communauté scientifique stipule que ces expériences sensorielles atypiques facilitent la créativité. En effet, comme elles dotent d’un répertoire perceptuel original, il est concevable qu’elles puissent mener à une aptitude à faire des associations non conventionnelles entre diverses catégories d’éléments. Par conséquent, cette recherche qualitative vise à mieux comprendre les influences des expériences synesthésiques sur la créativité, du point de vue de ceux qui vivent ces expériences. Dans le but de mieux comprendre la phénoménologie de la synesthésie en créativité, les questions de notre recherche se résument ainsi : Quel sens peut avoir l’expérience de la synesthésie en créativité et quelles répercussions a-t-elle sur la créativité? Nous sommes intéressés à comprendre comment la synesthésie peut être perçue, avoir de l’influence et être utilisée lors d’un processus créatif. À notre connaissance, il s’agit de la première étude à explorer la phénoménologie de la synesthésie tant auprès de plusieurs individus qu’au sein de plusieurs formes de synesthésie, à l’égard d’une caractéristique soi-disant centrale à cette condition, soit la créativité. Dans le cadre de cette recherche, 17 personnes avec diverses synesthésies, âgées de 21 ans à 72 ans, ont été rencontrées afin de partager leurs expériences lors d’entretiens individuels semi-dirigés. Ces entrevues ont été retranscrites et analysées d’après la méthode phénoménologique de recherche en psychologie. Au final, la structure fondamentale du phénomène étudié qui émerge de nos analyses comprend les 10 thèmes suivant en ce qui a trait au sens donné à l’expérience de la synesthésie sur le plan de la créativité : 1) L’expérience de la synesthésie oriente, module le processus créatif en fonction des associations synesthésiques afin d’être dans un état particulier et d’accroître le bien-être; 2) L’expérience de la synesthésie constitue un apport sensoriel, perceptuel et émotionnel à la créativité; 3) L’expérience de la synesthésie optimise les fonctions cognitives; 4) L’expérience de la synesthésie alimente la stimulation intellectuelle et la motivation dans un processus créatif; xvi 5) L’expérience de la synesthésie donne un sens à des éléments et à un vécu; 6) L’expérience de la synesthésie est perçue comme un système instinctif qui influence la créativité, une intuition à l’origine d’un processus de décision ou un réflexe consistant à transposer des associations qui sont indépendantes de la cognition; 7) L’expérience de la synesthésie permet de mieux se connaître, de s’identifier, d’exprimer et d’assumer ce qui constitue son individualité; 8) L’expérience de la synesthésie constitue une courroie de communication avec autrui, d’échange avec d’autres réalités; 9) L’expérience de la synesthésie peut ne pas avoir d’influence sur la créativité; les associations synesthésiques peuvent être perçues comme des états de faits qui sont d’utilité pratique et qui n’ont pas de répercussion sur les choix face à des besoins; 10) L’expérience de la synesthésie peut être un frein à la créativité. La présente étude a permis de développer une meilleure compréhension des composantes de la créativité, de faire avancer l’état des connaissances sur les expériences synesthésiques et d’identifier le coeur de leurs influences sur la créativité. Pour la première fois, l’étendue des avantages et des inconvénients des expériences synesthésiques sur la créativité a été exposée. Mener cette étude auprès de synesthètes qui présentent une variété de synesthésies a aussi permis d’identifier des processus sous-jacents à la créativité qui sont communs dans le vaste spectre de la synesthésie et d’amener des pistes d’explications quant aux différences individuelles pouvant émerger. Du coup, divers processus qui peuvent influencer et alimenter la créativité chez tous les individus ont été mis en lumière. Enfin, cette recherche peut apporter un éclairage sur les mécanismes universels d’interactions entre les sens et sur leur usage à certaines fins. De futures études avec de larges échantillons de participants devraient tenter de départager différents attributs de la synesthésie et d’explorer leur contribution respective dans divers aspects de la cognition et des émotions. Les répercussions de l’exploitation d’associations automatiques, synesthésiques ou non, pourraient aussi faire l’objet d’études dans les cadres d’interventions thérapeutiques et pédagogiques. Enfin, la mise sur pied de regroupements de chercheurs en synesthésie et de synesthètes pourrait stimuler le développement et la diffusion des connaissances sur la synesthésie et sur le potentiel humain, démarginaliser cette condition et déconstruire des conceptions erronées, et faire accroître l’épanouissement des individus de la grande communauté synesthète.
... By contrast, people typically have far less difficulty labelling/identifying colours, though, at the same time, colour patches are not always linked to specific source objects in the way that olfactory stimuli so often are. It is also worth noting here that one of the key differences thought to distinguish synaesthesia from the crossmodal correspondences is the unidirectionality of the inducer-concurrent relation in the case of synaesthesia (Speed & Majid, 2018), especially in the case of crossmodal synaesthetic relations. By contrast, a bidirectional mapping is often implicitly assumed by those who have chosen to investigate crossmodal correspondences. ...
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The last few years have seen a rapid growth of interest amongst researchers in the crossmodal correspondences. One of the correspondences that has long intrigued artists is the putative association between colours and odours. While traditionally conceptualised in terms of synaesthesia, over the last quarter century or so, at least 20 published peer-reviewed articles have assessed the consistent, and non-random, nature of the colours that people intuitively associate with specific (both familiar and unfamiliar) odours in a non-food context. Having demonstrated such consistent mappings amongst the general (i.e. non-synaesthetic) population, researchers have now started to investigate whether they are shared cross-culturally, and to document their developmental acquisition. Over the years, several different explanations have been put forward by researchers for the existence of crossmodal correspondences, including the statistical, semantic, structural, and emotional-mediation accounts. While several of these approaches would appear to have some explanatory validity as far as the odour-colour correspondences are concerned, contemporary researchers have focussed on learned associations as the dominant explanatory framework. The nature of the colour-odour associations that have been reported to date appear to depend on the familiarity of the odour and the ease of source naming, and hence the kind of association/representation that is accessed. While the bidirectionality of odour-colour correspondences has not yet been rigorously assessed, many designers are nevertheless already starting to build on odour-colour crossmodal correspondences in their packaging/labelling/branding work.
... According to Day, odor-vision synesthesia corresponds only to 6.13%. Individuals with odor-color synaesthesia experience color sensations when they smell odors (Speed and Majid 2018). ...
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This paper presents results of experiments carried out between 2013 and 2016, in which we searched for correspondences between the olfactory stimuli of perfumes and the visual stimuli of their primary packaging. In the present study, we explore a potential correlation between colors and smells. The chosen methodology consisted of analyzing colors from two different points of view: first, how companies use colors to represent smells; and second, how consumers perceive fragrances and how they correlate them to colors. We called these two approaches the 'representation of colors' and the 'perception of colors.' Our method also entailed searching online for catalogs of fragrance companies and selecting those that use colors associated with fragrance families. In order to investigate the consumer's perception, we carried out sensorial experiments in which a group of people performed a blind analysis of four Brazilian perfumes. Quantitative and qualitative explorations were conducted. Basic statistics were used that confirmed companies' practices. The research results concluded that consumers not only associate specific colors to fragrances, but they may associate the lightness of a color to the intensity of a fragrance. For example, participants of the experiments perceived a fragrance as softer attributing the softness to the lighter colors of the packaging. The results presented in this paper could be useful for designers and marketers because they highlight the importance of the correspondences between the senses, as well as the correlation between color and odor intensity.
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People associate information with different senses but the mechanism by which this happens is unclear. Such associations are thought to arise from innate structural associations in the brain, statistical associations in the environment, via shared affective content, or through language. A developmental perspective on crossmodal associations can help determine which explanations are more likely for specific associations. Certain associations with pitch (e.g., pitch–height) have been observed early in infancy, but others may only occur late into childhood (e.g., pitch–size). In contrast, tactile–chroma associations have been observed in children, but not adults. One modality that has received little attention developmentally is olfaction. In the present investigation, we explored crossmodal associations from sound, tactile stimuli, and odor to a range of stimuli by testing a broad range of participants. Across the three modalities, we found little evidence for crossmodal associations in young children. This suggests an account based on innate structures is unlikely. Instead, the number and strength of associations increased over the lifespan. This suggests that experience plays a crucial role in crossmodal associations from sound, touch, and smell to other senses.
A longstanding debate within philosophy and neuroscience involves the extent to which sensory information is a necessary condition for conceptual knowledge. Much of our understanding of this relationship has been informed by examining the impact of congenital blindness and deafness on language and cognitive development. Relatively little is known about the “lesser” senses of smell and taste. Here we report a neuropsychological case-control study contrasting a young adult male (P01) diagnosed with anosmia (i.e. no olfaction) during early childhood relative to an age- and sex-matched control group. A structural MRI of P01’s brain revealed profoundly atrophic/aplastic olfactory bulbs, and standardized smell testing confirmed his prior pediatric diagnosis of anosmia. Participants completed three language experiments examining comprehension, production, and subjective experiential ratings of odor salient words (e.g. sewer) and scenarios (e.g. fish market). P01’s ratings of odor salience of single words were lower than all control participants, whereas his ratings on five other perceptual and affective dimensions were similar to controls. P01 produced unusual associations when cued to generate words that smelled similar to odor-neutral target words (e.g. ink → plant). In narrative picture description for odor salient scenes (e.g. bakery), P01 was indistinguishable from controls. These results suggest that odor deprivation does not overtly impair functional language use. However, subtle lexical-semantic effects of anosmia may be revealed using sensitive linguistic measures.
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Wernicke (1900, as cited in G. H. Eggert, 1977) suggested that semantic knowledge arises from the interaction of perceptual representations of objects and words. The authors present a parallel distributed processing implementation of this theory, in which semantic representations emerge from mechanisms that acquire the mappings between visual representations of objects and their verbal descriptions. To test the theory, they trained the model to associate names, verbal descriptions, and visual representations of objects. When its inputs and outputs are constructed to capture aspects of structure apparent in attribute-norming experiments, the model provides an intuitive account of semantic task performance. The authors then used the model to understand the structure of impaired performance in patients with selective and progressive impairments of conceptual knowledge. Data from 4 well-known semantic tasks revealed consistent patterns that find a ready explanation in the model. The relationship between the model and related theories of semantic representation is discussed.
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Olfaction is often viewed as difficult, yet the empirical evidence suggests a different picture. A closer look shows people around the world differ in their ability to detect, discriminate, and name odors. This gives rise to the question of what influences our ability to smell. Instead of focusing on olfactory deficiencies, this review presents a positive perspective by focusing on factors that make someone a better smeller. We consider three driving forces in improving olfactory ability: one’s biological makeup, one’s experience, and the environment. For each factor, we consider aspects proposed to improve odor perception and critically examine the evidence; as well as introducing lesser discussed areas. In terms of biology, there are cases of neurodiversity, such as olfactory synesthesia, that serve to enhance olfactory ability. Our lifetime experience, be it typical development or unique training experience, can also modify the trajectory of olfaction. Finally, our odor environment, in terms of ambient odor or culinary traditions, can influence odor perception too. Rather than highlighting the weaknesses of olfaction, we emphasize routes to harnessing our olfactory potential.
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People appear to have systematic associations between odors and colors. Previous research has emphasized the perceptual nature of these associations, but little attention has been paid to what role language might play. It is possible odor–color associations arise through a process of labeling; that is, participants select a descriptor for an odor and then choose a color accordingly (e.g., banana odor → “banana” label → yellow). If correct, this would predict odor–color associations would differ as odor descriptions differ. We compared speakers of Dutch (who overwhelmingly describe odors by referring to the source; e.g., smells like banana) with speakers of Maniq and Thai (who also describe odors with dedicated, abstract smell vocabulary; e.g., musty), and tested whether the type of descriptor mattered for odor–color associations. Participants were asked to select a color that they associated with an odor on two separate occasions (to test for consistency), and finally to label the odors. We found the hunter-gatherer Maniq showed few, if any, consistent or accurate odor–color associations. More importantly, we found the types of descriptors used to name the smells were related to the odor–color associations. When people used abstract smell terms to describe odors, they were less likely to choose a color match, but when they described an odor with a source-based term, their color choices more accurately reflected the odor source, particularly when the odor source was named correctly (e.g., banana odor → yellow). This suggests language is an important factor in odor–color cross-modal associations. Electronic supplementary material The online version of this article (doi:10.3758/s13423-016-1179-2) contains supplementary material, which is available to authorized users.
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People in Western cultures are poor at naming smells and flavors. However, for wine and coffee experts, describing smells and flavors is part of their daily routine. So are experts better than lay people at conveying smells and flavors in language? If smells and flavors are more easily linguistically expressed by experts, or more “codable”, then experts should be better than novices at describing smells and flavors. If experts are indeed better, we can also ask how general this advantage is: do experts show higher codability only for smells and flavors they are expert in (i.e., wine experts for wine and coffee experts for coffee) or is their linguistic dexterity more general? To address these questions, wine experts, coffee experts, and novices were asked to describe the smell and flavor of wines, coffees, everyday odors, and basic tastes. The resulting descriptions were compared on a number of measures. We found expertise endows a modest advantage in smell and flavor naming. Wine experts showed more consistency in how they described wine smells and flavors than coffee experts, and novices; but coffee experts were not more consistent for coffee descriptions. Neither expert group was any more accurate at identifying everyday smells or tastes. Interestingly, both wine and coffee experts tended to use more source-based terms (e.g., vanilla) in descriptions of their own area of expertise whereas novices tended to use more evaluative terms (e.g., nice). However, the overall linguistic strategies for both groups were en par. To conclude, experts only have a limited, domain-specific advantage when communicating about smells and flavors. The ability to communicate about smells and flavors is a matter not only of perceptual training, but specific linguistic training too.
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Odors are often difficult to identify, and can be perceived either via the nose or mouth ("flavor"; not usually perceived as a "smell"). These features provide a unique opportunity to contrast conceptual and perceptual accounts of synesthesia. We presented six olfactory-visual synesthetes with a range of odorants. They tried to identify each smell, evaluate its attributes and illustrate their elicited visual experience. Judges rated the similarity of each synesthetes' illustrations over time (test-retest reliability). Synesthetic images were most similar from the same odor named consistently, but even inconsistently named same odors generated more similar images than different odors. This was driven by hedonic similarity. Odors presented as flavors only resulted in similar images when consistently named. Thus, the primary factor in generating a reliable synesthetic image is the name, with some influence of odor hedonics. Hedonics are a basic form of semantic knowledge, making this consistent with a conceptual basis for synaesthetic links.
The sense of smell has widely been viewed as inferior to the other senses. This is reflected in the lack of treatment of olfaction in ethnographies and linguistic descriptions. We present novel data from the olfactory lexicon of Seri, a language isolate of Mexico, which sheds new light onto the possibilities for olfactory terminologies. We also present the Seri smellscape, highlighting the cultural significance of odors in Seri culture that, along with the olfactory language, is now under threat as globalization takes hold and traditional ways of life are transformed. © 2016, Indiana University Anthropological Linguistics. All rights reserved.
Olfactory and gustatory mental images are defined as short-term memory representations of olfactory or gustatory events that give rise to the experience of smelling with the mind's nose or tasting with the mind's tongue. This chapter reviews converging evidence supporting the view that, as with visual mental images, odor and taste mental images preserve some aspects of olfactory and gustatory percepts. The variability that affects both types of imagery is also considered in an experiment comparing the effect of experience on chemosensory mental imagery and auditory mental imagery. © 2013 Springer Science+Business Media, LLC. All rights reserved.
Most people find it profoundly difficult to name familiar smells. This difficulty persists even when perceptual odor processing and visual object naming are unimpaired, implying deficient sensory-specific interactions with the language system. Here we synthesize recent behavioral and neuroimaging data to develop a biologically informed framework for olfactory lexical processing in the human brain. Our central premise is that the difficulty in naming common objects through olfactory (compared with visual) stimulation is the end result of cumulative effects occurring at three successive stages of the olfactory language pathway: object perception, lexical-semantic integration, and verbalization. Understanding the neurocognitive mechanisms by which the language network interacts with olfaction can yield unique insights into the elusive nature of olfactory naming. Copyright © 2015. Published by Elsevier Ltd.