a mnemonic theory of odor perception

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A Mnemonic Theory of Odor Perception

Richard J. StevensonMacquarie University

Robert A. BoakesUniversity of Sydney

The psychological basis of odor quality is poorly understood. For pragmatic reasons, descriptions of odor

quality generally rely on profiling odors in terms of what odorants they bring to mind. It is argued here

that this reliance on profiling reflects a basic property of odor perception, namely that odor quality

depends on the implicit memories that an odorant elicits. This is supported by evidence indicating that

odor quality as well as ones ability to discriminate odors is affected by experience. Developmental

studies and cross-cultural research also point to this conclusion. In this article, these findings are

reviewed and a model that attempts to account for them is proposed. Finally, the models consistency

with both neurophysiological and neuropsychological data is examined.

Progress in understanding the perception of stimulus qualities invision and audition has been based on the search for systematic

relationships between the physical attributes of a stimulus and the

subjective experience it produces; that is, on solving the stimulus

problem. Recent developments in molecular biology and neuro-

physiology have resulted in considerable advances in researchers

knowledge of the olfactory receptor system, which has hitherto

lagged well behind the knowledge of other sensory systems. Nev-

ertheless, as detailed below, major problems remain for any theory

of odor quality based solely on the physical properties of the

stimulus. A solution of the stimulus problem for olfaction appears

to remain remote. A different approach to the analysis of odor

qualities is one that takes into account the effects of past experi-

ence on the way that an individual perceives an odor. In this

article, we review recent experimental evidence on such effects

and present a theory of odor perception that is based on the

assumption that the qualities perceived in an odor reflect the

normally implicit memories that it elicits. Although the subjective

experience induced by an odor clearly consists of more than just its

perceptual qualities (e.g., its hedonic ones), in the absence of any

extant psychological theories of olfaction, models of basic percep-

tual processes are likely to be more useful. Consequently, our

primary focus here remains perceptual.

The Human Olfactory System

The olfactory system is characterized by having two discrete

modes of stimulation (Chifala & Polzella, 1995, Figure 1; Rozin,1982). Chemical stimuli can be transported to the olfactory recep-

tors via the nose through sniffing (orthonasal perception) or via therelease of volatile chemicals in the mouth during eating and

drinking (Pierce & Halpern, 1996). These volatiles then ascend via

the posterior nares of the nasopharynx to stimulate the olfactory

receptors (retronasal perception). Although there are some rela-

tively minor differences between the two modes of stimulation,

mainly resulting from the less efficient flow of air during retrona-

sal perception, crucially both result in binding to the same set of

receptors (Burdach & Doty, 1987; Voirol & Daget, 1986).

It is useful to draw a distinction between taste and smell,

because these terms are commonly confused. Taste is an anatom-

ically discrete sense from smell and is characterized by four types

of sensation (sweet, sour, salty, and bitter [and possibly a fifth,

umami]), which are detected by receptors or ion channels locatedprimarily on the tongue (McLaughlin & Margolskee, 1994). Most

basic tastants like sodium chloride, sucrose, quinine, and citric acid

have no smell, just as many odor stimuli completely lack taste.

This is typically confirmed by placing a substance on the tongue

while the nose is firmly pinched to prevent retronasal olfaction.

Any sensation is then most likely to be taste.

A further distinction is between the olfactory and nasal trigem-

inal systems. The nasal trigeminal system is mediated separately

from the sense of smell and refers to receptors located in the nasal

passage and in all parts of the system that come into contact with

inhaled substances. These receptors have at least two effects on

olfaction (see Green & Lawless, 1991). First, the sensations they

evoke, such as burning, itching, and stinging, are experienced as

part of the spectrum of olfactory sensations (Laska, Distel, &Hudson, 1997). Second, trigeminal irritation appears to reduce the

perceived intensity of pure odors (Cain & Murphy, 1980). This

article is primarily concerned with olfactory stimulation.

The main function of the olfactory receptors is to transduce

chemical stimuli into patterns of neural activity that, after process-

ing, allow the stimulus to be discriminated from thousands of other

odorous stimuli (Hildebrand & Shepherd, 1997). The olfactory

receptors are located on the olfactory mucosa (see Figure 1), which

is arranged in two discrete segments; one of these is accessed

exclusively from the left nostril, and the other is accessed exclu-

sively from the right (Lanza & Clerico, 1995). Each segment is

Richard J. Stevenson, Department of Psychology, Macquarie Univer-

sity, New South Wales, Australia; Robert A. Boakes, Department of

Psychology, University of Sydney, Sydney, Australia.

We thank David Laing, Judi Homewood, Fred Westbrook, Trevor Case,

Judi Wilson, and Julie Fitness for their many helpful comments on earlier

versions of this article.

Correspondence concerning this article should be addressed to Richard

J. Stevenson, Department of Psychology, Macquarie University, New

South Wales 2109, Australia. E-mail: [email protected]

Psychological Review Copyright 2003 by the American Psychological Association, Inc.2003, Vol. 110, No. 2, 340 364 0033-295X/03/$12.00 DOI: 10.1037/0033-295X.110.2.340

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covered with a layer of mucus that is vital for normal function

(Pelosi, 1996). The mucus probably assists chemical stimuli to

diffuse onto the olfactory receptor neurons, as well as removing

stimuli after transduction. The receptor neurons project into the

mucus, and the receptors are located on their cilia (for review, see

Buck, 1996, 2000; Hildebrand & Shepherd, 1997).

Olfactory receptors have been identified as belonging to a large

family of biologically active molecules called G-proteins(Buck &

Axel, 1991). Although this and many related discoveries, dis-

cussed below, have been made using mice and rats, these findingsalmost certainly apply to other mammals and to humans (Issel-

Tarver & Rine, 1997; Mombaerts, 1999). The G-protein receptors

are embedded in the cell membrane of the cilia, and when an

effective chemical stimulus arrives the binding results in depolar-

ization and an action potential (Hildebrand & Shepherd, 1997).

Only certain types of chemical appear to be effective stimuli, that

is, stimuli detectable by the olfactory system. First, they must fall

within a certain range of solubility. Methane, for example, is

relatively insoluble in water and odorless but can be smelled by

divers as solubility increases with higher air pressure (Laffort &

Gortan, 1987). Volatility, and hence molecular size, is a further

limitation, with few chemicals being odorous if they exceed a

molecular weight of around 300 (Ohloff, Winter, & Fehr, 1991).

The way that chemical stimuli might interact with olfactory

receptors has generated a large number of theories. These can be

grouped into three general classes: chemical (e.g., Amoore, 1964;

Boelens, 1974; Henning, 1916; Laska, Trolp, & Teubner, 1999),

vibrational (e.g., Dyson, 1938; Turin, 1996; Wright, 1977), and

enzymatic (which is not discussed further here; see Amoore,

1982). Two of these, chemical and vibrational, have received the

most attention. Chemical theories can be further subdivided into

those based on the physiochemical properties of the stimulus, such

as its overall shape or the presence of particular functional groups

(which is the more popular view) or on the molecules reactivity

(which has received far less support). Both chemical theory sub-

types presume that odors bind to particular receptor types and that

the pattern of activity from these different receptors generates a

representation of the stimulus that is complex and unique (Beets,

1978; Schiffman, 1974; Sullivan, Ressler, & Buck, 1995).

Vibrational theories also come in two forms. The first, now

largely discredited, assumes that chemicals emit particular fre-

quencies that are detected by the receptors in the same way that thevisual system senses light (see Moncrieff, 1951). More recent

forms of vibrational theory start from the premise that molecules

have particular sets of vibrational frequencies that uniquely define

them (Turin, 1996; Wright, 1977). These theories propose that

olfactory receptors are tuned to detect different vibrational fre-

quencies and therefore a representation of the stimulus is built up

from this unique pattern of vibrations.

It is currently estimated that the adult human olfactory mucosa

contains between 500 and 750 unique G-protein receptors (Buck &

Axel, 1991). This finding alone sets olfaction apart from the other

senses, each of which contain only a limited number of receptor

types. Each olfactory receptor neuron appears to produce only one

type of G-protein receptor (Malnic, Hirono, Sato, & Buck, 1999),and it is important to note that each receptor type appears sensitive

to many different chemicals (Malnic et al., 1999; Mombaerts,

1999). Families of particular G-protein receptor types appear to be

located together on the olfactory epithelium (Ressler, Sullivan, &

Buck, 1993), although the location of individual receptor types

within such areas appears random. The functional significance of

this arrangement is not understood.

Following an interaction between a chemical and the G-protein

receptor, the cell depolarizes, and an action potential passes along

to the first stage of information processing, the glomeruli, con-

tained in the olfactory bulb (Sullivan & Dryer, 1996). There are

estimated to be between 1,000 and 2,000 glomeruli. Each glomer-

ulus receives input primarily from a single G-protein receptor type

(Ressler, Sullivan, & Buck, 1993). The apparent mismatch be-

tween number of glomeruli and number of receptor types reflects

a current lack of precision in measurement; the general nature of

this relationship is all that is of concern in this article. The spatial

arrangement of glomeruli appears to be the same as that for

receptors on the olfactory epithelium, in that members of the same

G-protein families tend to be located close together (see Mori,

Nagao, & Yoshihara, 1999). One possible consequence of this

arrangement is that chemical stimuli that resemble each other in

whatever key feature(s) turn out to be important for receptor

binding will also tend to activate neighboring glomeruli. As in

other sensory systems, lateral inhibition occurs between glomeruli.

Thus, high activation of one glomerulus may suppress activity in

its neighbors and thus sharpen output to the next processing stage(Yokoi, Mori, & Nakanishi, 1995; but see Laurent, 1999, for an

alternative perspective).

A key implication to emerge from this account is that odor

quality is very unlikely to be dictated by one-to-one relationships

between particular receptors and an associated quality. This is

because of the sheer multitude of receptors, their apparent lack of

specificity, the fact that most odorous stimuli are composed of

many chemicals, and the general observation that olfactory coding

is probably represented at the neural level by a complex spatial and

temporal pattern of activity at the glomeruli that is relatively

unique to every chemical stimulus (e.g., Buck, 1996, 2000;

Figure 1. Cross-section of the head, illustrating the dual nature of olfac-

tory stimulation (via the nose or nasal pharynx) and the separateness of

taste (tongue) and smell (olfactory mucosa). From Sensation and Percep-

tion(5th ed., p. 451), by E. B. Goldstein, Copyright 1999. Reprinted withpermission of Brooks/Cole, an imprint of the Wadsworth Group, a division

of Thomson Learning.

341A MNEMONIC THEORY OF ODOR PERCEPTION


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Haberly, 1998; Malnic et al., 1999; Rubin & Katz, 1999; Sullivan

et al., 1995).

This perspective, which has emerged mainly from molecular

biology and neurophysiology over the last decade, has received

little if any attention from experimental psychologists, and the

implications for psychological accounts of odor quality have re-

mained largely unexplored. In fact, as we discuss below, psycho-logical research on odor-quality perception has been motivated by

the stimulus-problem approach, in which one receptor is equated

with one quality. In light of recent physiological findings it may

come as no surprise that these data provide little support for this

way of thinking.

Odor Quality and the Stimulus Problem

The psychological study of odor quality began with self-reports

of olfactory experience, later coupled with an attempt to identify

common sensory categories across different chemical stimuli (see

Amoore, 1982). This effort stemmed from the hope that such

categorization would lead to the discovery of a limited number of

primary odor sensations. It was then thought that the identificationof corresponding receptor types and the unraveling of the stimulus

problem would follow, just as it had for color perception (Saha-

kian, 1981). In this section we discuss various approaches to the

description of olfactory qualities, starting with a brief historical

background.

Linnaeus (see Amoore, 1982) was the first to attempt a system-

atic classification of olfactory sensation. He categorized plant

odors into seven categories, in an effort largely motivated by his

studies of plant taxonomy rather than of olfactory perception. The

first general classification system was proposed by Rimmel (see

Moncrieff, 1951) and included 18 categories, with a bias toward

categorization based on vegetative origin. A more abstract system

was proposed by Zwaardemaker (see Moncrieff, 1951). This con-tained 9 main categories, each of which was further divided into

two or three subcategories.

Modern attempts to identify odor primaries begin with Hen-

nings (1916) odor prism. Each corner of the prism represents a

primary quality, these being, flowery, foul, fruity, spicy, burnt, and

resinous. Henning claimed that odors would either be fully cap-

tured by a principal descriptor or fall on the surface or edges of the

prism if intermediate between categories. This claim produced a

flurry of experimental work that was largely unsupportive. The

general problem was the same as met by all classification systems

(Moncrieff, 1951): Many odors could not be accommodated within

the scheme or, as in this case, located on the surface of the prism

(e.g., Findley, 1924; Hazzard, 1930; MacDonald, 1922). For ex-

ample, in Macdonalds (1922) study, geraniol was judged to have

three principal qualities, these being flowery, fruity, and resinous,

yet the construction of the prism implies that this odor must have

a further quality, spiciness. Participants judgments were not con-

sistent with this prediction.

More recent attempts at defining primary odor qualities have

also met with problems. Amoore (1952) identified terms used by

chemists to describe odors. These were then analyzed to identify

those most commonly used. Seven terms were identified: ethereal,

camphor, minty, floral, musky, putrid, and burnt. Amoore and

Venstrom (1967) found significant correlations between the terms

characterizing particular chemicals and their molecular shape,

suggesting seven or so primary qualities and hence receptors.

However, Amoores other approach, the identification of specific

anosmiasanalogous to the study of anomalous color vision

revealed a much larger number of specific anosmias (about 43 at

last count; Amoore, 1982), and this finding is difficult to reconcile

with the earlier conclusion of seven primaries. Overall, attempts to

identify odor primaries must be judged as unsuccessful.A second approach to the analysis of odor quality has arisen

from the needs of professionals (e.g., sensory evaluation panels,

expert tasters, perfumers, flavorists, and wine tasters) for a stan-

dardized descriptive system that captures the differences between

odors and promotes communication between specialists (e.g.,

Brud, 1986). In one such system a target odor is compared with a

set of standard odors, with participants rating the targets similarity

to each comparison stimulus (e.g., Brud, 1986; Schultz, 1964).

However, this approach has proved unwieldy and has seen little

general application. Much more popular have been systems in

which a target odor is evaluated in relation to a standard list of

verbal descriptors (e.g., Dravnieks, 1985; Noble et al., 1987).

Harper, Bate-Smith, and Land (1968) pioneered the first system of

this kind by collecting a large number of terms used to describeodor quality. These were then winnowed down to a set of 44 items,

against which participants evaluate the target odor. Dravnieks

(1985) later extended the number of items in his widely used list

to 146. There is, however, no strict limit on the number of items

that could be included, apart from obvious practical considerations

like participant fatigue. These systems allow an odor to be profiled

quite rapidly, with participants rating each descriptor on degree of

presence (effectively a similarity rating). The profile developed for

a particular odor using this technique shows high testretest reli-

ability (Dravnieks, 1982).

Three points about descriptive profiling are pertinent here. The

first is that most of these schemes either explicitly or implicitly

involve similarity judgments, in that the participant is effectivelyasked to assess how similar the target is to a particular descriptor

(Lawless, 1999). This point is illustrated by the obvious prediction

that odors that receive similar profiles should also be judged,

globally, as more similar. Precisely such a relationship has been

observed (Dravnieks, Bock, Powers, Tibbetts, & Ford, 1978). The

second point concerns the items to which the odor is compared. In

the vast majority of cases these items are specific odorous objects

or categories of objects (Lawless, 1999). Third, and most impor-

tant of all, each of these rating schemes appears to need a large

number of descriptors to capture adequately, if indeed it does, the

experience of odor quality. This would seem to suggest that there

are no primary odor qualities (for a similar conclusion see Chas-

trette, Elmouaffek, & Sauvegrain, 1988).

Applying Adaptation and Discrimination

to the Stimulus Problem

An alternative approach to the stimulus problem has been to

study olfactory adaptation and discrimination. We turn first to

adaptation, which is a salient property of odor perception (Engen,

1982). Repeated or prolonged exposure produces a marked de-

crease in the perceived intensity of an odor, as measured by a range

of psychophysical techniques (Koster, 1971). This propensity can

be used to study the stimulus problem in the following way. If two

odors smell similar, it is a reasonable presumption that they might

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also share the same receptor types. It follows that taking two

odorants that smell similar and presenting one of them repeatedly

might produce cross-adaptation when the other similar smelling

odor is sniffed (e.g., Cain & Polak, 1992).

The results from such cross-adaptation studies are equivocal.

Although some odor pairs that are qualitatively similar will cross-

adapt (see, e.g., Cain & Polak, 1992; Pierce, Wysocki, Aronov,Webb, & Boden, 1996), others will not (Todrank, Wysocki, &

Beauchamp, 1991). Moreover, many odors that are clearly dis-

criminable and have very different qualities will cross-adapt (Ko-

ster, 1971). In addition, odors that are structurally similar and yet

perceptually distinct may also show cross-adaptation (Pierce,

Zeng, Aronov, Preti, & Wysocki, 1995), and in some cases pre-

exposure to the adapting odor may even act to increase the judged

intensity of the test stimulus (Engen & Bosak, 1969). These

findings argue against the idea of any simple relationship between

perceptual similarity and commonality of receptor types.

The use of discrimination to explore odor quality is based on the

assumption that the ease of discriminating two odors is inversely

related to the degree that they share perceptual qualities (e.g., Jehl,

Royet, & Holley, 1994). From this perspective, odors that share acommon structural feature (if this should be important in causing

odor quality) should be less discriminable than odors that do not

share this feature. Studies using odor discrimination are not only

the most objective (Wise, Olsson, & Cain, 2000) but also the least

explored. This is probably because of the practical costs imposed

by the many comparison trials needed to obtain sufficient data for

meaningful analysis and by the problem that adaptation precludes

the short intertrial intervals that can be used in equivalent studies

of vision or audition.

The effect of chemical structure on discriminability has been

examined in a number of recent studies using both primate and

human participants. The chemical structure of an odorant, most

notably its carbon chain length and its functional groups, has beenfound to affect discriminability in a lawful way, such that odorants

of greater structural similarity are generally less distinguishable

(Laska, Ayabe-Kanamura, Hubener, & Saito, 2000; Laska &

Teubner, 1999; Laska et al., 1999). These results suggest that

various aspects of a chemicals structure undoubtedly influence

participants perception of odor quality. However, there is also

evidence to suggest that such relationships are far from perfect

(e.g., Boelens, 1974; Polak, 1973).

The Role of Learning in Odor-Quality Perception

The guiding principle of psychological inquiry into odor quality

is based on the presumption that sensation results causally from the

features of the stimulus and that with sufficient searching these

features and their sensations will be identified, solving the stimulus

problem. Within such a framework, perception of an odor should

not be greatly influenced by past experience. However, recent

research on the role of learning in odor perception challenges this

assumption and suggests that perception of an odor is far more

sensitive to past experience than is the case for other modalities

(for a similar conclusion based on the animal literature, see Hud-

son, 1999).

One phenomenon that clearly makes this point is tastesmell

synesthesia, whereby olfactory stimulation can give rise to an

experience that properly belongs to the sensory modality of taste.

It has been known for some time that participants will spontane-

ously describe a wide range of odors as smelling sweet; notable

examples are strawberry, vanilla, and caramel (Harper et al.,

1968). It is not clear why this term is used, becausesweetnormally

refers to a sensation produced by stimulation of taste receptors on

the tongue and nothing corresponding to an olfactory sweet recep-

tor is known to exist. One possibility is that describing odors interms of sweetness, or other taste terms, is a linguistic phenome-

non with sweetused in a metaphorical rather than in a perceptual

way. However, the sweetness-enhancement effect argues against

this possibility. For example, if participants are asked to judge the

sweetness of a sucrose solution flavored by strawberry, they will

judge the mixture to be sweeter than the unflavored sucrose (Frank

& Byram, 1988; Frank, Ducheny, & Mize, 1989). The size of this

effect is directly related to how sweet the odor smells (Stevenson,

Prescott, & Boakes, 1999). This suggests that the perceptual ex-

perience of sweetness produced by something in the mouth is

based on a combination of sensory signals from the mouth, gen-

erated by (a) odorless sweet tastants such as sucrose and (b) signals

produced by retronasal stimulation of olfactory receptors by taste-

less odorants. Sweetness enhancement is not the only effect of thiskind. Sweet odors used to flavor a sour solution can reduce the

perceived sourness of the latter, whereas nonsweet odors can

reduce the perceived sweetness of a sucrose solution (Stevenson et

al., 1999). In addition, the sweet taste of saccharin, but not the

meaty taste of monosodium glutamate, can facilitate threshold

detection of the sweet smelling odor benzaldehyde, apparently via

their shared quality of sweetness (Dalton, Doolittle, Nagata, &

Breslin, 2000).

Many sweet-smelling odors have a history of co-occurrence

with sweet tastes. This has led to the suggestion that the odor

quality sweet may be acquired on the basis of individual experi-

ence (Frank & Byram, 1988; and see Laska et al., 1997, for a

related suggestion forsour) and, further, that it may be modifiableby varying the co-occurrence of odors and tastes in a laboratory

setting. We have repeatedly obtained such an effect, odortaste

learning, over a series of experiments (Stevenson, Boakes, &

Prescott, 1998; Stevenson, Boakes, & Wilson, 2000a, 2000b;

Stevenson, Prescott, & Boakes, 1995). These have all used the

same basic procedure. Participants rate a set of odors on a number

of dimensions in two identical sniffing tests, a pre- and a posttest.

In the intervening training phase they are asked to tastethat is,

sip, swirl around the mouth, and then expectoratea series of fluid

samples. Some samples consist of a sucrose solution to which a

target odor has been added as a flavorant and others may contain

a citric acid solution, tasting moderately sour, or plain water

flavored by adding further target odors. In general we have used

target odors that participants find only vaguely familiar and nor-

mally cannot identify. Lychee and water chestnut have been the

targets used in most of these experiments. The sniffing tests have

usually required linear analog ratings on four scales: liking, inten-

sity, sweetness, and sourness.

Such experiments have consistently produced the same result.

Target odors that have been mixed with sucrose are rated as

sweeter, and less sour, in the posttest than they were in the pretest,

whereas those mixed with citric acid are rated as less sweet, and

more sour, at posttest. There is little change from pre- to posttest

in the ratings for control odors mixed with water during training,

other than a slight increase in intensity (Stevenson et al., 1998).



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Because such a design raises the potential problem of demand

characteristics, the initial experiments contained conditions de-

signed to obscure their purpose. These included the inclusion in the

training phase of an irrelevant taska triangle test requiring

participants to decide which of three samples was different from

the other twoand of more dummy than critical trials, with spaced

training over several sessions. Recognition tests to assess aware-ness and postexperiment questionnaires revealed that participants

had no understanding of the purpose of the experiment and very

little, if any, explicit memory of which flavor had been mixed with

which taste. Learning of odortaste contingencies appeared to be

implicit, in that the size of the learning effect was unrelated to the

degree of awareness of the contingencies shown by a participant

(Stevenson et al., 1998, 1995). Later experiments suggested that

elaborate masking procedures are unnecessary. The effect was also

obtained when dummy trials were removed and training completed

in a single session, yet participants still displayed little explicit

memory for the odortaste contingencies (Stevenson et al., 2000a).

The size of the effect, produced by between four and eight

pairings of an odor with sucrose, is an increase of sweetness of

about 10 points on a 100-point scale under the range of experi-mental conditions used to date. This effect size does not seem to be

affected by whether the solutions are sampled from a cup in the

manner described above or sipped through a straw (i.e., precluding

serial learning of smell then taste). It is also very stable. When

retested 1 month after training, no detectable change was found in

participants ratings (Stevenson et al., 1998). An unexpected find-

ing was that the effect is resistant to both extinction and counter-

conditioning. In these experiments an odor was first mixed with

citric acid and then for 12 trials presented in water (Stevenson et

al., 2000a) or in sucrose solution (Stevenson et al., 2000b). No

difference was detected in the posttest ratings between an odor

given this extinction or counter-conditioning treatment and one

given odorsourness pairings alone. Both odors showed odortastelearning relative to control odors. In contrast, colortaste associ-

ations proved sensitive to both the extinction and the counter-

conditioning procedures. One experimental manipulation that can

decrease odortaste learning is to provide preexposure to an

odorby presenting it as a flavorant mixed in waterprior to

adding it to a sucrose or citric acid solution (Stevenson & Boakes,

in press). The significance of these various properties of odortaste

learning are discussed further below, but first we consider other

experiential treatments that change the way that an odor is

perceived.

One of these involves what we term odor-quality exchange or

odorodor learning. Exposure to a combination of odors, A X,

can imbue A with some of Xs perceptual qualities, and vice versa.

Experiments examining this effect have contained a training phase

in which participants sniff two such combinations, A X and B

Y. Each combination of a target odor (A, B) with a contaminant

(X, Y) is presented 12 times over two separate sessions. This is

followed by a posttest in which A, B, X, and Y are presented on

their own and participants are asked to rate each of them in terms

of how A-like, B-like, X-like, and Y-like they smell. For example,

X could be p-anisaldehyde, which is generally perceived as smell-

ing musty, and in this caseX-likewould mean rating each odor for

mustiness. Acquisition of this odor quality is then measured by the

difference between musty ratings for Target A and the same

ratings for Control Odor B, which has not been mixed with

p-anisaldehyde. With such a design, odor pairings are varied

across groups in counterbalanced fashion.

Experiments using these procedures have examined acquisition

of odor properties using a number of targets (L-carvone, with a

minty smell; cis-3-hexanol, green or fresh grass; terpineol, disin-

fectant-like; methyl salicylate, mint or peppermint; guaiacol,

smoky; champignol, mushroom; and wood distillate, woody orresinous) and various contaminants, including water chestnut

(fruity), p-anisaldehyde (musty), cherry (cherry or berry), and

citral (lemony). Exposure to a particular target-contaminant mix-

ture does not always produce a change in the perceived quality of

the target. For example, neither L-carvone nor cis-3-hexanol were

detectably more fruity after being mixed with water chestnut.

Furthermore, on some occasions the effect occurs in only one

direction: An odor can yield some property without acquiring any,

and vice versa. Thus, in the same study (Stevenson, 2001a)

L-carvone was rated more musty after being mixed with

p-anisaldehyde, but the latter was not rated as more minty. It is not

yet possible to predict whether a contaminant will affect a target

odor. One important factor appears to be the detectability of the

components within the mixture (Stevenson, 2001b). Another re-lated issue is the familiarity or nameability of the components; for

example, wood distillate was the most easily identified target odor

and also the one least modified by a contaminant in Stevensons

(2001b) study.

The above results are based on ratings from small sets of scales.

This raises the possibility that the outcomes may be greatly influ-

enced by the particular labels given to the scales (e.g., Clark &

Lawless, 1994). Further measures taken in the above experiments

suggest that this is unlikely. All four experiments of this kind have

included a second posttest in which participants have rated the

similarity of pairs of odors. This was to test the prediction that

following exposure to a mixture of Target A with Contaminant X,

A should be rated as more similar to X than to Control Odor Y.Such an effect was found but, in general, only for pairs in which

the first posttest revealed transfer of odor qualities (Stevenson,

2001a, 2001b). A further test, included in one experiment (Steven-

son, 2001b), required participants to rate each odor on the 146

attributes used by Dravnieks (1985). Although less sensitive a

testpossibly because given lastthis measure revealed effects

of training similar to those detected by the limited number of

scales of the first posttest.

Learning and Odor Discrimination

To this point, the evidence we have reviewed on the effects of

learning on odor perception has relied on ratings of subjective

experience. Such measures have their limitations, notably because

of differences across individuals in the way that scale labels are

interpreted (Wise et al., 2000) and wider concerns with the reli-

ability of self-report data. Thus, it is clearly important to examine

the extent to which objective measures of odor perception, notably

discrimination performance, are affected by past experience.

At least two factors have been identified that can improve odor

discriminability: mere exposure and label learning. Several exper-

iments have demonstrated enhanced discrimination following

mere exposure to a set of odors. Rabin (1988; Experiment 1) had

a group of participants profile a set of seven odors of low famil-

iarity and near neutral hedonic tone using the Dravnieks (1985) set



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of scales. In the subsequent same different discrimination test

their performance equivalent to about 88% correctwas signif-

icantly better than that of the two nonexposed control groups at

81% correct. Enhancement of performance in such tests of odor

discrimination can be obtained following prior exposure even

when no task is required of participants. Jehl, Royet, and Holley

(1995) gave different groups 0, 1, 2, or 3 exposures to sets ofodors, asking participants to sniff each odor for 4 s and remain

silent. A subsequent samedifferent test revealed that discrimina-

tion performance increased with prior exposure, mainly reflecting

decreased false-alarm rates, with a d of about 4.0 for the group

given three exposures andd of about 1.6 for the group given no

preexposure.

Although the previous two experiments demonstrate that dis-

crimination improves with experience, they potentially confound

perceptual and memorial processes because of their reliance on

comparison between two temporally discrete stimuli. A further

experiment by Rabin (1988, Experiment 2) argues against this

possibility, because he obtained largely similar results to those

above under conditions in which the task involved simultaneous

presentation of two stimuli in a mixture. In this case participantswere given a target (e.g., A) followed (or preceded) on some trials

by the target mixed with a contaminant (e.g., A X). Participants

then judged same or different as in Rabins (1988) Experiment 1.

He found that prior familiarity with both target and contaminant

produced a considerable improvement in discrimination, with

scores equivalent to 58% correct when neither was familiar to

about 87% when both were familiar. Why exposure should benefit

both successive and simultaneous discrimination tasks is not well

understood, and no adequate theoretical explanation currently ex-

ists for any of these effects.

Learning labels for a set of odors can further improve discrim-

inability beyond the effect of mere exposure (which one should

note is a necessary condition for label learning to occur). Rabin(1988, Experiment 1) had another group of participants label the

same seven odors that were profiled by the exposure group. The

label group subsequently performed significantly better than the

exposure group on the samedifferent task (94% correct, com-

pared with 88% in the exposure group and 81% in the nonexposed

control groups). Although the precise nature of the benefit con-

ferred by label learning is unknown, at least two possibilities can

be canvassed. On most discrimination tests, as noted above, a

delay is present between the presentation (or the perception) of one

stimulus and the presentation (or the perception) of the subsequent

comparison stimulus. Labels may provide an easy verbal short-

hand, allowing the odors identity to be stored in working memory

(e.g., see Annett & Leslie, 1996, for the adverse effects of verbal

suppression on an odor-memory task). A second, less prosaic

explanation can also be made, on the basis of the notion that

language shapes perception. This perspective has been more com-

monly adopted when considering individuals who have some form

of special olfactory expertise (e.g., perfumers or wine experts).

Expertise in such individuals is usually characterized by both

perceptual knowledge and an extensive related vocabulary (e.g.,

see Solomon, 1990). Wine expertsthe most tested groupare

undoubtedly better at wine discrimination than nonexperts (e.g.,

Hughson & Boakes, 2001; Lawless, 1984). However, these bene-

fits tend to be small when appropriate exposure controls are

present (individuals with large amounts of perceptual experience

but no specialized vocabulary; see Melcher & Schooler, 1996).

Whether this linguistic benefit shown by experts represents a

difference in perceptual experience or simply a better ability to

describe and remember odors in verbal form (as suggested earlier)

is yet to be resolved.

Although label learning and mere exposure may typically en-

hance discriminability, exposure can in certain circumstances re-duce it. Experimental research with both humans and animals

using stimuli other than odors has shown that when two cues have

produced a common outcome they can become less discriminable

(e.g., Honey & Hall, 1989; Katz, 1963). Following Jamess (1890)

study, this has been referred to asacquired equivalencein contrast

with acquired distinctiveness (Hall, 1991). The previous section

referred to evidence from experiments on the exchange of odor

qualities indicating that after two odors have been experienced as

a mixture they are judged as more similar (Stevenson, 2001a,

2001b). Because similarity judgments should to some extent be

predictive of discriminability, this finding suggests that experienc-

ing two odors together might make later discrimination between

them more difficult. Following the training procedures in our

previous experiments (A X, B Y), we conducted triangletests, which revealed poorer discrimination between elements pre-

viously mixed together (A vs. X, B vs. Y; mean correct trials

77%) than between unmixed pairs (A vs. Y, B vs. X; mean correct

trials 87%; Stevenson, 2001c). More recent experiments, in

which only one odor mixture is experienced (i.e., A X or B

Y) followed by triangle tests involving comparisons of both A

versus X and B versus Y have revealed that the elements of the

preexposed mixture are more difficult to tell apart (mean correct

trials 77%) than non-preexposed stimuli (mean correct trials

89%; Stevenson & Case, in press). Thus, this process appears to be

one of acquired equivalence.

Cross-Cultural Differences in Odor Perception

The research reviewed in the previous two sections has shown

that the way people experience and discriminate between odors

can be significantly affected by relatively brief experiences in a

laboratory setting. This suggests that differences in odor percep-

tion across cultures could be quite large. Cultures differ in their use

of dietary flavorings and staples (Moore, 1970), their exposure to

culturally specific odors (e.g., church incense), and also in their

use of odorants in different contexts (e.g., cleaning agents, per-

fumes, medicinal flavors).

Unfortunately for our purposes, most cross-cultural research on

odors has focused on affective responses (Pangborn, 1975; Rozin,

1978). There appears to be only one published study, Ayabe-

Kanamura et al. (1998), and a conference abstract, Ueno (1993),

that have reported data on the qualities that participants from

different cultures perceive when smelling the same odorant. In

Ayabe-Kanamura et al.s (1998) study, German and Japanese

participants were asked to smell a range of culturally specific (e.g.,

aniseed for Germans, dried fish for Japanese) and international

odors (e.g., coffee). Judgments of liking revealed, as expected, that

culturally specific odors were more preferred by their respective

groups. More important here are differences between participants

reports about the qualities of many of the odors. Many German

participants thought that fermented soya beans were reminiscent of

cheesy smelly feet, that dried fish smelled of excrement, and



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soy sauce of fresh bread, but few Japanese thought so (Ayabe-

Kanamura et al., 1998, p. 34). Conversely, aniseed was evaluated

as disinfectant-like and Indian ink as medicinal by Japanese

participants but quite differently by Germans (Ayabe-Kanamura et

al., 1998, p. 34).

Uenos (1993) study compared Japanese and Sherpa (Nepalese)

participants perceptions of 20 Japanese food flavors. In this caseparticipants were asked to arrange the bottles containing the odors

into groups on the basis of their similarity. Cluster analysis re-

vealed that fishy odors were characterized in a different way by

Sherpa participants, in that they did not exist as a distinct cluster

as they did for the Japanese. Fish odors are rarely encountered by

Sherpas in their native Nepal.

Apart from supporting the claim that differences in experience

can produce alterations in odor quality, Uenos study also indi-

cated a close positive relationship between quality and liking.

Where odors differed markedly in quality between groups (e.g.,

dried fish), they also tended to differ markedly in pleasantness. On

the basis of this finding, the much larger literature relevant to

cross-cultural effects on liking is also consistent with the conclu-

sion that experience affects the perceived quality of an odor as well

as how much it is liked (e.g., Davis & Pangborn, 1985; Schaal et

al., 1997; Wysocki, Pierce, & Gilbert, 1991).

A Mnemonic Theory of Odor Perception

We noted at the start of this article that psychological ap-

proaches to odor-quality perception have been driven by attempts

to solve the stimulus problem, with visual or auditory psychophys-

ics as an implicit model. However, it has now been recognized that

understanding visual and auditory perception, particularly object

recognition (Logothetis & Sheinberg, 1996) and auditory scene

analysis (Bregman, 1990), requires much more than simply solv-ing the stimulus problem. In fact Bregman (1990) argued that

undue emphasis on such a purely psychophysical approach has

probably retarded understanding of auditory perception. Here we

argue that an understanding of odor quality cannot be achieved

without full reference to how we process olfactory information,

because odor-quality perception bears a much closer resemblance

to activities such as scene analysis and object recognition than it

does to psychophysical studies using single frequencies of light

and pure tones. This is because no such equivalent is possible in

olfaction, because all olfactory stimuli result in complex temporal

and spatial patterns of activation on the glomerular layer (e.g.,

Laurent, 1999). The emphasis for a psychological level explana-

tion of odor-quality perception must be the way in which this

pattern of activation is dealt with. This forms the central part of thetheory that we advance in this section.

The mnemonic theory is described first in information-

processing terms from the perspective of its core function (odor-

quality perception; see Figure 2) and then from the perspective of

its implications for related functions (e.g., familiarity, learning,

priming, memory, imagery). A commentary on these assumptions

follows. We then discuss whether the proposed system can be

mapped onto different parts of the central nervous system and the

extent to which the theory provides a better understanding of

abnormalities of odor perception following various kinds of dam-

age to the brain.

Overview

The essence of the mnemonic theory is that the complex output

pattern from the glomeruli forms the models input (Number 1 on

Figure 2). This input is then compared in parallel with the contents

of a store composed primarily of previously encountered glomer-

ular patterns (Number 2a on Figure 2). The greater the similarity

between the current input pattern and a stored pattern (an engram),

the greater the activation of that engram. Odor quality is repre-

sented here as the relative activation of these engrams.

Assumption 1 (Tabula Rasa)

Odors, in the main, do not possess any inherent psychologicalproperties beyond their degree of presence (intensity). For the

newborn human infant most odorants produce nothing more than

a blooming, buzzing confusion, to borrow Jamess (1890, p.

488) phrase. This is in contrast with tastants, which possess both

sensory and hedonic psychological properties that are unambigu-

ously innate. Although this assumption is provocative, evidence

does favor this account, as we make clear later.

Assumption 2 (Input Pattern)

Any stimulus falling within the bounds of detectability (e.g.,

molecular weight), will produce a complex and unique pattern of

Figure 2. Diagrammatic representation of the mnemonic theory of odor

perception.



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stimulation, both spatial and temporal, across the glomeruli. This

will occur irrespective of the stimuluss molecular simplicity or

complexity or the number of its chemical components. This pattern

forms both the input for the theory (Number 1 on Figure 2) and

provides the basis for the perception of odor intensity.

Assumption 3 (What Is the Pattern Compared With?)

The core element of the theory is a processing module (olfactory

processing module; see Figure 2), in which the input is compared

in parallel with all previous encodingsengrams (Number 2a in

Figure 2). These engrams are primarily composed of prior olfac-

tory input patterns, accumulated through exposure to different

chemicals and mixtures of chemicals. However, as we discuss later

in this article, perceptual information from other senses may also

be encoded in this store.

Assumption 4 (Pattern Matching)

Pattern matching in the olfactory processing module is proba-

bilistic, neither all-or-none nor exclusive. A given olfactory inputmay match and hence activate many engrams to a greater or lesser

extent, and this pattern of activations may vary somewhat between

repeat presentations of the same stimulus. In addition, there is

likely to be some degree of mutual inhibition between engrams so

that if one particular engram is strongly activated, then this will

tend to inhibit activation of other engrams that would provide only

a partial match.

Assumption 5 (Encoding Purely Olfactory Engrams)

When an input pattern (Number 1 in Figure 2) fails to match

strongly with any stored engram, this provides the conditions for

encoding a new olfactory engram. The process of encoding in-

volves the output from the olfactory processor module being fedback to an automatic comparator and encoder (via Numbers 3

and 4 to Number 2b in Figure 2), where it is automatically

compared with the olfactory input. Because the two will not match,

the contents of the comparator are encoded as a new engram and

stored in the processing module.

Assumption 6 (Resistance to Interference)

When an input pattern closely matches an engram in the pro-

cessing module, encoding is prevented. This occurs in the follow-

ing way: The processor output is again fed back (via the same

route as inAssumption 5) to the automatic comparator and encoder

where it is compared with the olfactory input. Because the two will

broadly match, the contents of the comparator are not encoded.

Assumption 7 (Encoding Composite Olfactory/Non-

Olfactory Engrams)

The store component of the olfactory processing module also

contains composite engrams composed of an olfactory and non-

olfactory component(s). Encoding composite engrams calls on a

further feature of the theory. When output from the olfactory

processor is fed back to the automatic comparator and encoder, it

is fed back via two other modules: a controlled associator that is

not relevant here (seeAssumption 11) and a sensory integrator that

is relevant (Number 4 in Figure 2). The sensory integrator corre-

lates the arrival of olfactory processor output with other perceptual

events. When two streams of perceptual information are tempo-

rally correlated they are fed back as a packet to the automatic

comparator and encoder (via the controlled associator). The packet

is then compared with the olfactory input in the automatic com-

parator and encoder. When the olfactory component of the packetis familiar and hence similar to the olfactory input, encoding is

retarded. When the olfactory component is unfamiliar, the contents

of the comparator are encoded in the processing module, resulting

in the formation of a composite engram of olfactory and non-

olfactory information.

Assumption 8 (Access Constraints on Engrams in the

Processing Module)

Both purely olfactory and composite engrams may be activated

only when the olfactory part of the engram is reexperiencedthat

is, content addressable memory. Hence recall of engrams in the

processing module can occur only via pattern matching from

olfactory input (Numbers 1 and 2a in Figure 2).

Assumption 9 (Feelings of Familiarity)

The familiarity of an odor is a product of the pattern-matching

process (Number 2a in Figure 2). Thus an input pattern that

matches few engrams closely will be judged as less familiar than

an input pattern that has stronger matches.

Assumption 10 (Identification)

The greater the activation of a particular engram in the process-

ing module the greater the likelihood that it will excite an asso-

ciative link or links to semantic or episodic knowledge (Number 5

in Figure 2). These associations can generate either partial (itsmells like some kind of herb) or complete (its oregano)

identification. This process is both variable and fallible. An odor-

ant identified correctly on one occasion may seem highly familiar,

but not identifiable, on the next.

Assumption 11 (Acquiring Associations Between Semantic

and Episodic Knowledge and Olfactory Engrams)

Associations between an engram in the olfactory processing

module and episodic or semantic knowledge may occur when

output from the processor (Number 2 in Figure 2) and the to-be-

associated information are both available to the controlled asso-

ciator (Number 3 in Figure 2). Such associations are effortful,

strengthened through repetition, and prone to interference.

Assumption 12 (Top-Down Influences)

Particular semantic or episodic knowledge may lower the

threshold for activation of individual or sets of related engrams in

the olfactory processing module via previously acquired associa-

tions (link between Numbers 5 and 2 in Figure 2). These may act

to facilitate identification of an odor. If it looks like an orange, and

feels and tastes in the mouth like an orange, its odor is much more

likely to be identified as orange-smelling. Verbal information

alone may play a similar role: If told beforehand this could smell



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like an orange or a mushroom, a person will be more prone to

identify orange odor as orange than they might if no such cue had

been provided.

Assumption 13 (Imagery)

The theory suggests that experience of odor quality is possible

only when an input pattern is available to the pattern matcher in the

processing module. Thus the only stimulus sufficient to activate

engrams in the olfactory processing module is a physically present

one, implying that odor imagery is unlikely (excepting perhaps

activation during an epileptic aura or schizophrenic hallucination).

Assumption 14 (Short-Term Storage and Recognition

Memory)

When an engram is activated, activation gradually decays but

lasts longer than both the offset of stimulation and the loss of

perception of the activating stimulus. Two consequences flow

from this. First, it allows for an apparent short-term storage ca-

pacity, as a consequence of the activation of engrams in theprocessing module. Thus facilitated identification of recently ex-

perienced odors is enabled in an analogous manner to that pro-

posed for top-down priming, through lowering the threshold nec-

essary to activate a particular engram (see Assumption 12).

Second, residual activation may ultimately last for a very long

time: days, weeks, or even months. This would by necessity mean

relatively flat forgetting curves (from minutes to months) and

provide a mechanism for olfactory recognition memory (see As-

sumption 12).

Commentary on the Assumptions

Commentary on Assumption 1 (Tabula Rasa)

The theory assumes that odors have no inherent psychological

properties. This implies that neonates, infants, and children prob-

ably perceive odor quality in a different manner from adults and

that their hedonic responses differ as well. Although limited, the

available evidence supports this view. Starting with hedonic re-

sponses, Steiner (1979) suggested that neonates possess an auto-

matic response to certain odors, typified by a facial expression akin

to that demonstrated when neonates sample the bitter tastant qui-

nine (see Steiner, Glaser, Hawilo, & Berridge, 2001). More con-

sidered studies have failed to confirm this view. Although there is

some limited evidence that infants a few hours old do show

dislikes for odors that adults also find unpleasant, the strength of

this response is nowhere near as potent as that shown toward

quinine (Soussignan, Schaal, Marlier, & Jiang, 1997). Because

olfactory exposure in utero is now known to alter preferences in

the neonate, it is difficult to eliminate the possibility that any

observed hedonic response arises simply from this type of expo-

sure (Schaal, Marlier, & Soussignan, 2000).

The hedonic responses of infants and older children to odors

present an equally mixed picture. Although one study has reported

evidence of hedonic differences in children akin to those in adults

(Schmidt & Beauchamp, 1988), doubts surround its methodology

(Engen & Engen, 1997), and in addition, other studies have shown

that such responses in this age group are highly sensitive to

experimental instructions (e.g., Strickland, Jessee, & Filsinger,

1988). For the archetypal foul odor, feces, (Angyal, 1941), it is

difficult to reconcile Rozins observation (Rozin & Fallon,

1987)that young children will readily play with itwith the

notion of an innate dislike for its odor. This view is supported by

two findings. First, Peto (1935) observed that 89 out of 92 children

under 5 years old, demonstrated no sign of dislike or disgust when

tested with putrefying and fecal odors. Second, Moncrieff (1966)found that children were largely indifferent to the fecal-like odor

of skatole.

For odor quality the data are more limited. First, there are no

relevant studies conducted with children less than 5 years old.

Second, studies of older children have examined only the ability to

identify odors. Although identification calls on a variety of cog-

nitive processes, it is known to correlate substantially with dis-

criminative ability (De Wijk & Cain, 1994a, 1994b; Eskenazi,

Cain, Novelly, & Friend, 1983), and one would therefore predict

poorer odor identification in children, as has been observed. Doty,

Shaman, Applebaum, et al. (1984) administered the University of

Pennsylvania Smell Identification Test (UPSIT; Doty, Shaman, &

Dann, 1984) to a large sample of participants (nearly 2,000) of

varying ages. The test involves smelling an odor and identifying

from a list of names the correct one for that stimulus. Children 59

years old performed significantly worse at recognition than did all

the older samples up to the age of 70 years. Only adults aged 80

or more years performed worse. Similar findings have been re-

ported by Cain et al. (1995), De Wijk and Cain (1994a, 1994b),

and Lehrner, Gluck, and Laska (1999). It is important to note that

Cain et al. (1995) did not find any difference between children and

adults in olfactory sensitivity, as measured by a standard olfactory

threshold test. This suggests that differences in sensitivity are

unlikely to be the cause of identification differences. Finally, using

a different technique, Larjola and Von Wright (1976) found that

younger children (mean age 5 years) were significantly worse at

recognizing odorants that they had just smelled than were olderchildren, both immediately and after a 1-month delay. Taken

together, these studies suggest that children probably perceive odor

quality in a different manner from that of adults and that such

differences are eliminated by progressive gains in olfactory

experience.

Commentary on Assumption 2 (Input Pattern)

The concept of a complex spatial and temporal pattern as the

neural representation of an odor is both widely accepted (e.g.,

Buck, 1996, 2000; Haberly, 1998; Laurent, 1999; Malnic et al.,

1999; Sullivan, Ressler, & Buck, 1995) and well supported exper-

imentally. According to this perspective, odors are encoded as acomplex pattern of activation across the 1,000 2,000 glomeruli in

the olfactory bulb. The evidence for this assertion, which is dis-

cussed in more depth in the studies cited above (and see the earlier

section The Human Olfactory System), can be summarized as

follows: (a) There are a large number of olfactory receptors (about

500750; Buck & Axel, 1991); (b) each receptor type is very

broadly tuned, responding to a variety of different chemical stimuli

(Malnic et al., 1999); and (c) information from each receptor type

is channeled on to specific glomeruli so that the pattern across all

glomeruli is likely to differ between odors, even if the pattern of

activation for a particular receptor does not (Malnic et al., 1999).



10/25

A further aspect of the input pattern concerns how information

about odor intensity is recovered. We adopted Lansky and Ro-

sparss (1993) suggestion that intensity information is extracted

very early in olfactory processing. However, such intensity infor-

mation must require further processing to account for effects like

sniff vigor constancy, whereby variations in sniff depth, and thus

amount of odorant delivered to receptors, produce little variation inodor intensity (Teghtsoonian, Teghtsoonian, Berglund, & Ber-

glund, 1978).

A further consideration is whether intensity information follows

the same processing path as quality information. As noted in the

section on the effects of brain injury that follows, it is very clear

that many such conditions spare the ability to perceive differences

in odor intensity (particularly the case of H.M.; but see West &

Doty, 1995) while eliminating the ability to perceive odor quality

(White, 1998). This suggests separate processing streams. How-

ever, one puzzling finding is that factor analysis of different tests

of olfactory function do not typically separate out measures of

sensitivity from those of quality perception, as might be expected

(Doty, Smith, McKeown, & Raj, 1994). One possibility is that

adequate sensitivity is a necessary prerequisite for odor-qualityperception (thus variations in sensitivity will affect odor-quality

perception) but that the absence of odor-quality perception need

not affect sensitivity.

Finally, it is well established that the perceived quality of certain

odorants changes as their concentration is increased (Gross-

Isseroff & Doron, 1989; Moncrieff, 1951). We note in passing that

such findings are easily accommodated within the theory on the

basis of changes in receptor binding, olfactory input, and thus

engrams activated.

Commentary on Assumption 3 (What Is the Pattern

Compared With?)

The theory assumes that there is a dedicated olfactory store (the

olfactory processing module) that receives input directly from the

olfactory bulb (i.e., glomeruli) and that stores previous input.

Evidence for this structure comes from three sources: (a) plausible

neuroanatomical correlates of the olfactory processing module (see

Neuroanatomical Basis of the Theory); (b) the neuropsychological

data, which suggest that memory and perception in olfaction are

indistinguishable (see Neuropsychological Data); and (c) the psy-

chological data, which provide some evidence of a separate olfac-

tory store. This latter assertion, which is considered in this section,

is based on four types of functional dissociation: (a) differences in

resistance to interference, (b) differences between olfactory mem-

ory and both implicit and explicit memory for other types of

stimuli, (c) the unusual difficulty that participants have in naming

odors, and (d) factor analytic studies of cognitive and olfactory

abilities.

Olfactory memory may be especially resistant to interference.

This has been suggested by two types of study: (a) those using a

recognition-memory procedure, which show little forgetting of

olfactory stimuli over long delays (e.g., Engen & Ross, 1973;

Lawless, 1978; Lawless & Cain, 1975), and (b) processes pre-

sumed to reflect engram encoding, namely the resistance to retro-

active interference of odortaste learning (Stevenson et al., 2000a,

2000b), and odorodor learning (Stevenson, Case, & Boakes, in

press). These conclusions need to be tempered, because interfer-

ence may take place under certain conditions (seeCommentary on

Assumption 6), and also other forms of stimuli, such as free-form

shapes and faces, may show similar effects (Lawless, 1978). None-

theless, as a general feature of a sensory system, such findings

appear to set olfaction apart.

A second unusual property stems from the apparent similarity,

but singular difference, between olfactory memory (i.e., the en-gram store in Figure 2) and implicit memory. Implicit memory is

a blanket term describing situations in which prior experience

affects performance without requiring intentional recollection

(Schacter, 1987). Several parallels between implicit and olfactory

memory exist, including effortless and rapid acquisition (DeSchep-

per & Treisman, 1996), resistance to interference (e.g., Graf &

Schacter, 1987), and the integral nature of perception and implicit

memory (e.g., Jacoby, Allan, Collins, & Larwill, 1988). Implicit

memory for stimuli in other modalities is generally unaffected by

aging, by Alzheimers disease (e.g., Winograd, Goldstein, Mon-

arch, Peluso, & Goldman, 1999), by Korsakoffs syndrome (e.g.,

Benzing & Squire, 1989; Nissen, Willingham, & Hartman, 1989),

or by temporal lobectomy (Gabrieli, Milberg, Keane, & Corkin,

1990). In contrast, olfactory memory is profoundly affected by allthe above conditions, as is explicit memory for stimuli in other

modalities, as discussed below. The implication from this is that,

although olfactory memory shares more features in common with

implicit than explicit memory, it differs in the neuropsychological

conditions that affect it, setting it apart from its closest theoretical

classification.

A third difference concerns the difficulty that adult participants

have in naming even common odors, when other cues are absent

(e.g., Cain, 1979; Desor & Beauchamp, 1974; Larsson, 1997;

Lawless & Engen, 1977). This suggests that odor memory is in

some way different from stores of visual information, for example,

where such difficulties are rare (e.g., Cain et al., 1995). Finally, a

recent factor analytic study of cognitive (e.g., verbal, tonal andsymbol memory, IQ, executive function) and olfactory abilities

(e.g., odor memory and identification; Danthiir, Roberts, Pallier, &

Stankov, 2001), revealed that odor memory was a structurally

independent factor. Taken together, these four sets of observations

support the notion of a psychologically discrete olfactory memory

system, which here forms the engram store of the olfactory pro-

cessing module.

Commentary on Assumption 4 (Pattern Matching)

A key information-processing step in the theory is pattern

matching between the olfactory input from the glomeruli and the

engram store. Support for this notion comes from both neuroana-

tomical data (see Neuroanatomical Basis of the Theory) and ex-

perimental psychology.

Although a matching-type process has been alluded to by sev-

eral authors (see Dodd, 1988; Ohloff et al., 1991; Polak, 1973;

Schild, 1988), its ability to account for the learning data (e.g.,

Stevenson, 2001a, 2001b, 2001c; Stevenson et al., 1998) is what

initially led us to suggest it. In particular, matching a target odors

input with previously encoded engrams typically leads to the type

of finding obtained in our learning studies. For example, smelling

lychee after lycheesucrose pairings leads to the recovery of a

lycheesucrose engram by virtue of the engrams similarity to its

input.



11/25

The matching process is also supported by its ability to account

for a number of other findings. The first is the absence of primary

odor qualities described earlier. Setting aside the fact that multiple

nonspecific receptors have been unambiguously identified (e.g.,

Buck, 2000), the mnemonic theory places no bounds on the type or

number of qualities that may be experienced other than noting that

richness of olfactory experience should increase as a function ofexposure to new odors.

A second finding is the role that similarity appears to play in

judgments of odor quality (Lawless, 1999). Exactly such a rela-

tionship would be expected by our theory, in that when a partic-

ipant is asked to compare an odor to a series of quality descriptors

this process is analogous to that of odor perception, excepting that

the former occurs in serial, whereas the latter occurs in parallel. It

is this important difference that we believe separates the experi-

ence of an odor in daily life from that reported by rating qualities

in the laboratory.

A third finding is the consistently imperfect correlation between

quality and chemical structure (e.g., Boelens, 1974; Polak, 1973),

regardless of the type of structural feature chosen for analysis.

Although such findings are a problem for any particular structure-quality model, they do not pose a problem for matching-based

theories such as the one proposed here. This is because a matching-

based theory can comfortably accommodate any type of feature-

based model (i.e., it is complementary). This follows from the

principle that similarity of glomerular layer input to the theory

(i.e., resulting from similar binding patterns of odorant to recep-

tors) will produce similar patterns of activation in the olfactory

processing module and thus a similar odor-quality percept.

Fourth, the process of pattern matching embraces the notion of

redintegration (Horowitz & Prytulak, 1969), in which a part of a

complex whole can recover its totality. Such effects have been

observed in both rat and human participants. In rats, extensive

lesions of the glomerular layer, including those parts known to bemost active for a target odorant, do not prevent appropriate re-

sponding to odor-stimulus relationships learnt earlier in the exper-

iment (Lu & Slotnick, 1994; Slotnick, Bell, Panhuber, & Laing,

1997). This suggests that even a fragmentary input may be suffi-

cient to recover the whole. In humans, redintegration can best be

demonstrated with odortaste learning, in that a sniffed odor can

recover an engram that includes the experience of that odor with

sucrose (e.g., Stevenson et al., 1995).

Finally, the very process of pattern matching should make it

difficult to dissect complex odor mixtures into their individual

components (Haberly & Bower, 1989). That is, each input pattern

will largely be treated as a unique stimulus, even when it is a

mixture of several chemicals, as most odors are. In humans,

exactly this phenomenon has been observed. In an extensive series

of investigations, Laing and colleagues (e.g., Laing & Francis,

1989; Livermore & Laing, 1998a, 1998b) have established that

ordinary participants, and even experts such as perfumers and

flavorists, are unable to identify more than two or three compo-

nents in an odor mixture.

Commentary on Assumption 5 (Encoding Purely Olfactory

Engrams)

Two types of evidence suggest that a novel odor is encoded in

a special store and that this encoding modifies subsequent percep-

tion of the odor. The first type comes from the experiments on odor

learning that we reviewed earlier. The second type of evidence

comes from studies showing that the mere act of smelling a novel

odor is sufficient to improve its discriminability from other novel

odors, an observation that until now has had no theoretical basis

(Jehl et al., 1995; Rabin, 1988; Rabin & Cain, 1984). This effect

has been most clearly demonstrated by Rabin (1988), who foundthat preexposing participants to a set of odors enabled them to

discriminate between members of that set significantly better than

non-preexposed controls. Such an outcome can be directly ac-

counted for by the theory. One should recall that when an odor is

first smelled, particularly if it is not that familiar (as in Rabin,

1988), the odor will match few engrams in the olfactory processor,

thus producing far less activation of any individual engram than

will a familiar odor. Three consequences should flow from this.

First, a novel odor will smell of multiple qualities rather than being

primarily characterized by one qualitythe consequence of lots of

partial activation of slightly to moderately similar engrams. This

supposition was supported in a recent study by Stevenson, Demp-

sey, and Button (2003), who found that novel odors were describedas having more qualities, of lesser similarity to the target, than

familiar odors. Second, odors that are unfamiliar will also be more

confusable (e.g., Rabin, 1988), as a direct consequence of the first

point. Third, a novel odor, initially producing partial activation of

many engrams, should with further exposure be encoded in the

engram store. Thus, on subsequent encounters, the target odor will

come to activate its own previous encoding, hence limiting its

pattern of reported qualities and enhancing its distinctiveness.

Commentary on Assumption 6 (Resistance to Interference)

The theory proposes that when a familiar odor is encountered,no further encoding of that odor will take place in the olfactory

processing module. (One should note that this does not exclude the

formation of explicit associations between engrams and semantic

or episodic knowledge mediated by the controlled associator). As

we discussed earlier (see Assumption 4), experimental data are

largely in accord with this view. First, odortaste and odorodor

learning are resistant to interference (Stevenson et al., 2000a,

2000b; Stevenson et al., in press). Second, odor-recognition mem-

ory has been demonstrated in several studies to be particularly long

livedand thus presumably resistant to interference (e.g., Engen

& Ross, 1973; Lawless & Cain, 1975; Lawless & Engen, 1977;

Rabin & Cain, 1984).

The theory, however, does allow some interference to occurunder two conditions. First, when an odor is moderately similar to

an existing engram, some encoding of the target will eventuate.

This may explain why odorodor learning effects are typically

small, on the basis that one member of the pair is often a familiar

odor (e.g., cherry), whereas the other is not (e.g., p-anisaldehyde).

The combination (p-anisaldehydecherry) may therefore resemble

the engram of the previously encountered odor (e.g., cherry) and

thus retardbut not preventacquisition of the combination (see

Stevenson, 2001c). The second type of interference, also a function

of similarity, can occur during recognition-memory tasks, and this

is discussed separately in Commentary on Assumption 14.



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Commentary on Assumption 7 (Encoding Composite

Olfactory/Non-Olfactory Engrams)

The theory uses two different forms of learning. The first type

of learning is the encoding of information in the automatic com-

parator and encoder into the engram store, which may include both

olfactory (see Assumption 5) and composite olfactory/non-olfactory information. This type of learning, which we have re-

ferred to previously asconfigural(Stevenson et al., 1995, 1998), is

envisaged to be relatively fast, effortless, long-lasting, and resis-

tant to interference. The second form of learning involves the

formation of associations between the contents of the controlled

associator. This might involve learning that an odor comes from a

particular source, learning information about the odor, or learning

the odors name (e.g., Davis, 1977; Rabin, 1988). In this case

learning is relatively slow, effortful, and prone to interference.

Because parsimony would demand one learning system, it is

necessary to justify the need for two. The best justification is to

contrast two forms of learning that are known to involve odors:

odortaste learning and odorshock learning. In odorshock learn-

ing olfactory cues are used to predict the onset of electric shock.Learning in this paradigm resembles that found in many other

studies of human associative learning, with acquisition occurring

only with conscious awareness of the contingencies and rapid

extinction occurring when participants realize that the odor cue no

longer predicts shock (Marinkovic, Schell, & Dawson, 1989; and

see Van den Burgh et al., 1999, for similar findings and Dawson

& Schell, 1987, for general discussion of the properties of this type

of learning).

Odortaste learning, as described earlier, appears to possess

very different properties. It involves fast acquisition (Prescott,

1999) with apparently no necessity for participants to be aware of

the experimental contingencies (Stevenson et al., 1998) and in-

volves so vivid a recollection of the taste component that theexperience probably counts as synesthetic (Stevenson et al., 1998).

In addition, such learning demonstrates both latent inhibition under

no-masking conditions (Stevenson & Boakes, in press) and resis-

tance to retroactive interference (Stevenson et al., 2000a, 2000b).

The two separate learning systems used in the theory allow these

differences to be explained. A controlled associator is necessary

for odor shock or related forms of learning, in which contingency

awareness must be achieved prior to any change in behavior (e.g.,

Shanks & St. John, 1994). However, if no association is formed

and information is treated as a configuration (one entity), then

there is no necessity for a controlled associator. It is under these

conditions that the second learning process operates, with infor-

mation being encoded as an engram in the store. The properties

that this process of learning has are unusual because it does not

rely on the formation of associations. Consequently, learning is

relatively fast and effortless, and the resulting engrams are resis-

tant to interference because of the access restrictions that we

described earlier (i.e., content addressable only).

The automatic comparator and encoder can also process

olfactory/non-olfactory engrams, such as that between an odor and

a taste. There is, however, no reason why other forms of sensory

information could not be co-stored in the same way, and presum-

ably such composite engrams would possess similar properties

(see Haberly, 2001, for a similar suggestion). These would include

the following: (a) resistance to interference and thus longevity, and

hence retrieval only via the odorous component of the engram; (b)

vividness, as with the taste component of odors; and (c) third,

emotiveness, as with all odor stimuli. Precisely such qualities have

been identified in a series of studies on odor-induced memories

(Chu & Downes, 2000a, 2000b), which have demonstrated their

vividness, longevity (often from childhood), and emotive proper-

ties. It is suggested here that these so-called Proustian memoriesemerge as a consequence of their storage as composite engrams in

the olfactory processing module.

Finally, odors are known to be involved in one type of memory

phenomenon that may be harder to reconcile with the format

adopted here. This concerns using odors as a contextual cue.

Several demonstrations have been made of this effect, whereby

recall is facilitated when the olfactory context present during

learning is reinstated at test (e.g., Cann & Ross, 1989; Pointer &

Bond, 1998). As we have argued, associations between an odor

and a label require some effort to form, yet in these studies odor

was present as an incidental cuehardly an ideal situation to form

associative links between the odor and the to-be-remembered

information (e.g., words or faces). One explanation of such effects

is given by the encoding-specificity account (Tulving, 1983), in

which all available cues present during learning become part of the

trace, thus the presence of such cues during recall will assist

retrieval. This account presents a problem for the present theory, in

that it assumes storage in a common memory system under con-

ditions in which one would not expect this to occur. One possible

resolution of this problem (see Cann & Ross, 1989; Epple & Herz,

1999; Herz & Engen, 1996) is to assume that this effect is not

mediated through the odor per se but through the mood or arousal

state that an odor may invoke during testing. Thus the odor acts

only indirectly as a retrieval cue by reinstating the moodarousal

level present during learning. However, one should note that the

claim that mood can act as a contextual cue is itself controversial.

Commentary on Assumption 8 (Access Constraints on

Engrams in the Processing Module)

As we noted earlier, the contents of the engram store can be

accessed only by the physical presence of an odorant (content

addressable memory). Apart from the implications for limiting

interference (see Commentary on Assumption 6), it also has im-

portant ramifications for odor imagery, which are discussed later.

Commentary on Assumption 9 (Feelings of Familiarity)

The degree to which an odor feels familiar or novel appears,along with its intensive, qualitative, and emotional dimensions, to

be an intrinsic part of odor perception. For example, Lawless and

Engen (1977) found that response latencies were shortest when

participants were asked to judge the familiarity of an odor. Ac-

cording to the theory, familiarity is considered to be a function of

the degree of engram activation in the olfactory processing mod-

ule. From this perspective, an odors familiarity, as with its quality,

will not be affected by where it is smelled or by the fact that the

participant may not be able to identify either the name or place

where the odor was last encountered. Familiarity is therefore an

emergent property of the olfactory processing module.



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Commentary on Assumption 10 (Identification)

As we noted earlier, odors, even familiar ones, can be difficult

to name (e.g., Cain, 1979; Desor & Beauchamp, 1974; Larsson,

1997; Lawless & Engen, 1977). The theory accounts for poor

naming in three ways. First, odorname associations may initially

be hard to form compared with other senses (e.g., Davis, 1977).

This is because olfactory memory (the processing module) is a

discrete entity with a paleocortical location (Haberly, 1998; see

Neuroanatomical Basis of the Theory for further discussion) and

thus physically distant from the likely (neocortical) site of seman-

tic and episodic memory (see also Herz & Engen, 1996, for a

discussion of other potential ramifications of olfactions unique

anatomy). Second, the matching process between the input and the

stored engrams is assumed to be probabilistic (see Assumption 4);

consequently, even familiar odors may occasionally be misidenti-

fied (i.e., the wrong engram or engrams activated), leading to the

production of an incorrect name (e.g., Cain & Potts, 1996). Third,

the activation of associations to semantic memory is also predicted

to be probabilistic; thus, increasing the number of engrams acti-

vated should make category-level identification relatively easy(e.g., its a fruit). However, familiar odors, with fewer but more

strongly activated engrams, may be vulnerable to anomia because

of the greater impact of the probabilistic nature of activation on the

limited number of name-specific associations.

Commentary on Assumption 11 (Acquiring Associations

Between Semantic and Episodic Knowledge and Olfactory

Engrams)

a mnemonic theory of odor perception

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