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 one’s 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 model’s 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

340



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 identification

of 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-

ning’s (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 Macdonald’s (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, Amoore’s other approach, the identification of specific

anosmias—analogous 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 target ’s 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 describe

odor 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 test–retest 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

342 STEVENSON AND BOAKES



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 a

common 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 chemical’s 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 taste–smell

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, because sweet normally

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 sweet used 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 this

kind. 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 for sour ) 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, odor–taste

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 taste —that is,

sip, swirl around the mouth, and then expectorate—a 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).

343A MNEMONIC THEORY OF ODOR PERCEPTION



of scales. In the subsequent same– different discrimination test

their performance— equivalent to about 88% correct—was 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 of odors, asking participants to sniff each odor for 4 s and remain

silent. A subsequent same– different 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 and d 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 participants

were 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 Rabin’s (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 same– different 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 odor’s 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 experts—the most tested group—are

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 James’s (1890)

study, this has been referred to as acquired equivalence in 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 triangle

tests, 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




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).

Ueno’s (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, Ueno’s 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 model’s 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 James’s (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.




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

will occur irrespective of the stimulus’s 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 encodings— engrams (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 in Assumption 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 (see Assumption 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 reexperienced—that

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 (“it’s 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




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 Rozin’s observation (Rozin & Fallon,

1987)—that young children will readily play with it—with 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 5 –9

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

500 –750; 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).




A further aspect of the input pattern concerns how information

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

spars’s (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-quality

perception (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 odor–taste learning (Stevenson et al., 2000a,

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

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

ence may take place under certain conditions (see Commentary 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 Alzheimer’s disease (e.g., Winograd, Goldstein, Mon-

arch, Peluso, & Goldman, 1999), by Korsakoff ’s 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 all

the 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 odor ’s

input with previously encoded engrams typically leads to the type

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

lychee after lychee–sucrose pairings leads to the recovery of a

lychee–sucrose engram by virtue of the engram’s similarity to its

input.




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 of exposure 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 odor–taste 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 quality—the 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, odor–taste and odor– odor

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

lived—and 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 odor– odor 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-anisaldehyde– cherry) may therefore resemble

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

thus retard— but not prevent—acquisition 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.




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 as configural (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 odor’s 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:

odor–taste learning and odor–shock learning. In odor–shock 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).

Odor–taste 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 cue— hardly 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 effectsis 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 mood–arousal

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 odor’s 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.




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, odor–name 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 olfaction’s 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., “it’s 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)

Commentary on the formation of associations between odors

and semantic or episodic knowledge is discussed under

Assumption 7.

Commentary on Assumption 12 (Top-Down Influences)

The theory suggests that semantic or episodic knowledge may

facilitate odor identification by lowering the activation thresholds

of engrams in the olfactory processing module (i.e., olfactory

priming). The only direct evidence for this notion comes from a

study by Schab and Crowder (1991), who obtained priming in only

one of four reported experiments. Using familiar odors, Schab and

Crowder found that preexposure to an odor’s name alone facili-

tated correct identification when that odor was presented in a later

identification task, in comparison with a no-preexposure control.

Although it is difficult to draw strong conclusions from this study

because of Schab and Crowder’s failure to replicate their results,

the study suggests that having been previously exposed to a namecan later benefit a participant’s ability to identify an odor bearing

that same name. Other evidence on top-down influences comes

from research on wine tasting. A white wine that is artificially

colored red is misperceived as having features that are more

appropriate to red wine (Morrot, Brochet, & Dubourdieu, 2001).

Commentary on Assumption 13 (Imagery)

The theory suggests that odor imagery is unlikely because only

physically present stimuli can initiate access to the olfactory store

and hence activate engrams. Theory aside, empirical support for

odor imagery is weak. There are four types of study. The first

simply asks participants how clear and vivid their mental images

are for each of the different senses. Betts (1909), Sheehan (1967),

and Lawless (1997), among others, all report that the vividness of

olfactory images is considerably less than images from other

sensory modalities, including taste. A second approach has been to

ask participants to judge similarities between pairs of odorants,

some in a real and others in an imagined condition, and then usemultidimensional scaling to examine the odor space created for

each data set (Carrasco & Ridout, 1993). Although Carrasco and

Ridout (1993) concluded that imagery was present for olfaction,

they could not rule out verbal mediation in the imagery group as an

explanation (i.e., responses based on what the participant knows

about odors). More troubling still, in their multidimensional-

scaling solution the pleasantness– unpleasantness dimension that

usually emerges as the principal dimension for odors (Schiffman,

Robinson, & Erickson, 1977) was observed in the perceptual

condition but not in the imagery condition. This is very surprising

given that the affective quality of odors is one of their defining

characteristics (Richardson & Zucco, 1989).

A third approach is to ask participants to imagine combining

chemosensory stimuli and then report on the relative intensity of

the components (e.g., Algom & Cain, 1991). Algom and Cain

(1991) reported that following such a request, participants per-

formed in the same way as when presented with real mixtures. This

type of claim has been challenged by both Schifferstein (1999) and

by Stevenson and Prescott (1997) on two grounds. First, partici-

pants do have considerable explicit knowledge about how certain

mixtures will behave and this knowledge appears to be used in the

imagery condition. A second criticism is that a more refined

analysis shows that the pattern of results obtained under imagery

conditions fails to match those from direct perception.

A fourth type of study was performed by Lyman and McDaniel

(1990), who found that a condition in which participants imagined

smelling items from a word list produced better subsequent rec-ognition of those actual odors than did a condition in which

participants were asked to visualize the list items. Although this is

the most convincing demonstration of olfactory imagery, it has two

problems that cloud its interpretation. First, it is plausible that

verbal rehearsal underlay enhanced recognition in the odor imag-

ery group (i.e., repeatedly saying to oneself “Imagine the smell of

banana,” etc.). Lyman and McDaniel’s experiment could not detect

this sort of non-olfactory facilitatory effect, because no verbal-

rehearsal (i.e., auditory imagery) control group was run (Schab &

Crowder’s, 1991, priming experiment suggests that this is not idle

carping). Second, participants in the odor and visual-imagery

groups surprisingly reported equal success in creating their respec-

tive type of image. This stands in marked contrast to other phe-

nomenological reports (see above). In conclusion, taking all the

odor-imagery studies together and contrasting them with other

sensory systems (see Richardson, 1999), at best it may be con-

cluded that the evidence for olfactory imagery is weak.

Commentary on Assumption 14 (Short-Term Storage and

Recognition Memory)

The theory suggests that activation of an engram may last

beyond its conscious perception. This has two consequences. First,

it allows for a form of olfactory short-term storage, which is

neither functionally nor structurally separate from the long-term




engram store but rather a consequence of its activation (e.g., see

Cowan, 1988, for discussion of similar models of memory). Sec-

ond, this residual activation may be very long lived, providing a

mechanism for odor-recognition memory.

There is currently no consensus on whether there is a discrete

olfactory short-term store (of any type). Traditionally, four types

of evidence have been presented to establish a distinction betweena long- and a short-term store: capacity differences, coding differ-

ences, neuropsychological differences, and serial position effects

(White, 1998). Given the type of short-term store proposed here,

there should be no capacity difference, no coding difference, and

no evidence of any neuropsychological dissociation. Serial posi-

tion effects are a more complex issue, because there is consider-

able uncertainty about their implications for dissociable memory

systems (e.g., Baddeley & Hitch, 1993).

In apparent contradiction to our predictions, there does appear to

be some evidence for capacity differences in olfaction. Short-term

recognition performance decreases as the number of odors to be

remembered on a given trial is increased (Engen, Kuisma, &

Eimas, 1973; F. N. Jones, Roberts, & Holman, 1978). The capacity

of long-term memory for odors is certainly large. Participants are

able to recognize, even after a 1-month delay, about 70% of a

48-odor set (Engen & Ross, 1973), and this level of recognition

appears to be independent of set size. This is, however, not the

whole story. Although increasing the number of stimuli increases

the number of items that must be retained (i.e., testing capacity), it

also increases the likelihood of odors sharing similar characteris-

tics (e.g., being fruit-like). According to the theory, this should

disrupt recognition performance, because when similar odors are

used they tend to activate overlapping engrams, making identifi-

cation more difficult (i.e., interference based on similarity). Be-

cause the detrimental effects of similarity have been observed

following both short and long delays (Engen & Ross, 1973; Jehl et

al., 1994), capacity-difference claims need to be treated with somecaution.

Differences in coding between short- and long-term stores have

not been adequately demonstrated in olfaction. Although evidence

for both perceptual and semantic coding has been obtained in a

number of experiments (e.g., Cain, De Wijk, Lulejian, Schiet, &

See, 1998; Cain & Potts, 1996; Jehl, Royet, & Holley, 1997), there

is no link between any particular type of memory—long term or

short term—and the coding used. As for neuropsychological data,

these provide no definitive evidence for a distinction between a

short- and a long-term store (see Mair, Harrison, & Flint, 1995;

White, 1998). Finally, recency and primacy effects have been

obtained using a recognition procedure (Reed, 2000). However, as

we noted above, it is difficult to assess the implications of such

findings. Taken together, these results provide little support for

any form of discrete short-term store. Rather, they suggest a

capacity to hold olfactory information, for either short or longer

periods, by virtue of residual activation. This process appears

sensitive to interference, on the basis of the similarity of the items

in the test set.

General Comments on the Assumptions

These have been developed in an attempt to accommodate

within a single theoretical framework a range of findings that were

previously seen as unconnected. These findings include poor dis-

criminability of novel odorants, lack of primary qualities, imper-

fect correlations between structure and quality, effects of past

experience on odor perception, and current understanding of the

olfactory transduction process. As should be clear from the com-

ments on specific assumptions, for some the empirical basis is well

established but for others it is still quite fragile. Two further

sources of data that have an important bearing on the theory areconsidered next: (a) whether the proposed system is compatible

with current neurophysiological findings and can be mapped onto

different parts of the brain, and (b) the extent to which the theory

provides a better understanding of abnormalities of odor percep-

tion following brain damage.

Neuroanatomical Basis of the Theory

In this section our aim is twofold: first, to demonstrate that our

model is broadly compatible with current knowledge in this area,

and second, to draw explicit parallels between the processing units

outlined in the theory and particular brain structures. Two caveats

are necessary. First, we make no attempt to provide a detailedoverview of olfactory neuroanatomy but instead concentrate on

consensus findings (see Savic, 2001, for review). Second, we

assume at this point some broad parallels between rat, monkey,

and human brains in olfactory neurophysiology and anatomy. The

validity of this assumption will be examined in the next section.

The gross neuroanatomy of the olfactory system is illustrated in

Figure 3. We described earlier the process of transduction and the

organization of primary information processing in the glomerular

layer of the olfactory bulb. This information passes from the bulb

into the olfactory tract, which then splits into three branches: the

lateral, medial, and intermediate (Heimer, Van Hoesen, & Rosene,

1977). The lateral branch is the most important and projects to the

entorhinal and piriform cortex and the amygdaloid complex, all of which are primarily located in the temporal lobe (Jones-Gotman &

Zatorre, 1993). In addition, the piriform cortex also extends to the

posterior orbitofrontal surface of the frontal lobe (Eslinger,

Damasio, & Van Hoesen, 1982). Three important sets of projec-

tions stem from these olfactory paleocortical areas: to the hypo-

thalamus, to the mediodorsal nucleus of the thalamus, and to

prefrontal cortex (Haberly, 1998). These latter two structures also

project to each other, and the prefrontal cortex has reciprocal

projections back to the piriform cortex. Four of these structures

appear to play an especially important role in olfactory perception,

learning, and memory. These are the olfactory bulb, the piriform

cortex, prefrontal cortex, and the mediodorsal nucleus of the

thalamus. The role of each structure and its possible mapping onto

our theory forms the remainder of this section.The key element of our theory is the olfactory processing

module. Its neuroanatomical correlate would be a brain structure

(or structures) that (a) receives information directly from the

glomeruli or related bulbar structures, (b) has appropriate neural

architecture to make multiple comparisons of this incoming input

with that stored from previous smelling episodes, and (c) has

appropriate connections to other olfactory-related brain structures

for both the onward flow of information and reciprocal connec-

tions back for learning. Three structures, either individually or in

combination, might fill this role: piriform cortex, prefrontal cortex,

and the olfactory bulb. Each is considered in turn.




The piriform cortex has a number of features that make it a

plausible (if not the most promising) neural correlate of the olfac-

tory processing module. These features, which are outlined below,

have led several researchers to suggest that the piriform cortex is

a paradigmatic example of content-addressable memory, that is, a

system functionally analogous to the olfactory processing module

proposed in our theory (see Barkai, Bergman, Horwitz, & Has-

selmo, 1994; Haberly, 2001; Haberly & Bower, 1989; Hasselmo,

Anderson, & Bower, 1992). The features that suggest it as a

putative olfactory processing module are as follows:

1. Lesions of the piriform cortex can retard odor-

discrimination learning in rats (Slotnick & Schoonover,

1992).

2. Small areas of the piriform cortex receive input from all

areas of the olfactory bulb (Haberly, 1985), although a

recent tracing study in mice suggests some organization,albeit with considerable convergence of multiple glomer-

uli output to multiple points in the piriform cortex (Zou,

Horowitz, Montmayeur, Snapper, & Buck, 2001).

3. Many cells within the piriform cortex respond to olfac-

tory stimulation during single-unit recording (Haberly,

1969), and the structure is metabolically active during

olfaction (Sharp, Kauer, & Shepherd, 1977).

4. The piriform cortex receives input from prefrontal cortex,

allowing for the co-storage and association of informa-

tion from other sensory systems (Haberly, 1985).

5. Major projections from the piriform cortex go to the

prefrontal cortex and thalamic structures, which are also

involved in olfactory discrimination and learning (see

below for a more detailed discussion; see also Schoen-baum & Eichenbaum, 1995).

6. In humans, several neuroimaging studies have found the

piriform cortex active during smelling (for review, see

Doty, 2001).

7. Olfactory identification ability, as measured by the

UPSIT, is correlated with activity in the piriform cortex

(Kareken et al., 2001).

The neural architecture of the piriform cortex also lends

itself to the type of pattern matching and storage system that

would be required by the olfactory processing module. Input

from the olfactory bulb via the lateral olfactory tract (see thediscussion above) synapses onto the top of a series of vertical

pyramidal cells. These cells are organized in layers, with lower

levels containing separate local inhibitory and excitatory inter-

connections. In this model of piriform cortical function, the

pyramidal cell layers form the neural basis of the odor store,

with engrams stored in a distributed fashion across these cells.

It is important to note that these cells demonstrate the plasticity

necessary for this role, in that they show both long-term poten-

tiation (Kanter & Haberly, 1993) and increased spine density

following olfactory learning (Knafo, Grossman, Barkai, &

Benshalom, 2001).

Figure 3. Schematic representation of olfactory pathways in humans. Olfactory centers represented include the

following: olfactory bulb (OB), lateral olfactory tract (LOT), olfactory tubercle (OT), anterior olfactory nucleus

(AON), piriform cortex (PC), entorhinal cortex (EC), amygdaloid complex (AC), hypothalamus (Hy), hippocam-

pal system (Hi), mediodorsal nucleus of the thalamus (MD), and orbitofrontal cortex (OFC). From “The

Neuropsychology of Odor Memory,” by R. Mair, L. M. Harrison, and D. L. Flint, in Memory for Odors (p. 47),

1995, Hillsdale, NJ: Erlbaum. Copyright 1995 by Erlbaum. Reprinted with permission.




The evidence presented above is broadly supportive of the

piriform cortex as a neural correlate of the olfactory processing

module. However, some recent human functional magnetic reso-

nance imaging (fMRI) and rat neurophysiological data raise im-

portant issues that warrant comment. In particular, one human

fMRI study has found that the piriform cortex is activated by

sniffing odorless air and that this activation is correlated with thedegree of sniff vigor (Sobel et al., 1998). In addition, both human

fMRI (Sobel et al., 2000) and single-cell recordings from the

piriform cortex in rats (Wilson, 1998, 2000), suggest that the

piriform cortex adapts fairly rapidly to repeated presentations of

the same odor. It is important to note that Sobel et al. (2000)

showed that detection of the presence of an odor on a particular

trial could occur without significant activation in the piriform

cortex. Moreover, several human fMRI studies have failed to find

activation here (see Zald & Pardo, 2000), a result Sobel et al.

(1998) attributed to rapid habituation and variations in control

procedures that may or may not include odorless sniffing. Al-

though all of these findings can be readily accounted for (e.g., that

activation does not always equate with processing and that sniffing

acts as the attentional spotlight of olfaction), they do suggest the

need for caution before one may firmly conclude that primary

olfactory processing occurs here.

The prefrontal cortex has also been identified as an important

olfactory processing center. Prefrontal cortex (especially Brod-

mann’s Area 11) receives input directly from the bulb, from

several areas of olfactory cortex, and from the mediodorsal nucleus

of the thalamus (Haberly, 1998). Lesions of these prefrontal areas

in rats produce deficits in olfactory discrimination learning

(Eichenbaum, Shedlack, & Eckmann, 1980), with lesioned animals

taking between 3 and 4 times as many trials to reach criterion in an

olfactory go/no-go discrimination task. Single-cell recordings in

monkey prefrontal regions have also identified prefrontal cortex as

a convergence site for information from olfactory and non-olfactory sources (Rolls & Baylis, 1994), with single-cell record-

ings indicating olfactory and visual and olfactory and taste-specific

cells. Finally, human neuroimaging studies find prefrontal cortex

activated in many different odor-processing tasks (Cabeza & Ny-

berg, 2000).

In terms of neural correlates of the theory, we suggest that

prefrontal cortical regions may have more features akin to the

controlled associator than to the olfactory processing module. This

suggestion is made for several reasons. First, single-cell activity in

rat prefrontal regions during an olfactory discrimination paradigm

is virtually identical to that of the piriform cortex (Schoenbaum &

Eichenbaum, 1995). The theory would predict such parallelism,

because the olfactory processing module should project this infor-

mation to the controlled associator (see Figure 2). Second, pre-

frontal areas are believed to be involved in the association of

on-going sensory input (Fuster, 2000; Schoenbaum & Eichen-

baum, 1995). This is essentially the role that we have identified for

the controlled associator, and it is well demonstrated in Rolls and

Baylis’s (1994) findings described above. Third, damage to pre-

frontal regions produces deficits in human participants’ ability to

extinguish acquired responses (e.g., Rolls, Hornak, Wade, &

McGrath, 1994). Because associations produced by the controlled

associator are, according to the theory, sensitive to interference,

this would also suggest a further functional correspondence.

Fourth, prefrontal cortex (Brodmann’s Area 11) is known to be

involved in the formation of associations between names and faces

(Herholz et al., 2001), a process that may parallel the one between

names and odors—another function attributed to the controlled

associator.

A further candidate structure for the olfactory processing mod-

ule is the olfactory bulb. Although the bulb has (a) the information

necessary for such processing, (b) the capacity to demonstratelearning (Shepherd & Greer, 1998), and (c) direct connections to

prefrontal cortex and olfactory cortex (Shepherd & Greer, 1998), it

is questionable whether it has the necessary neuronal architecture

to store olfactory (and presumably non-olfactory) information.

However, the possibility that the bulb may play this role cannot be

excluded, and its role in olfactory learning and memory requires

further elaboration.

A final structure that has demonstrated importance in olfactory

learning and memory is the mediodorsal nucleus of the thalamus.

Mediothalamic structures are known to be involved in (a) the

correlation of sensory information from different perceptual sys-

tems, (b) learning, and (c) memory retrieval (Lezak, 1995). In rats,

lesions to the mediodorsal thalamus lead to impaired olfactory

learning, although not as severe as those following prefrontal

lesions (Eichenbaum et al., 1980). In addition, such lesions tend to

manifest behaviorally during more complex learning tasks only.

Montaldi and Parkin (1989) suggested that mediothalamic deficits

result from the breakdown of the use of contextual cues in learning

and retrieval. Precisely this sort of deficit would be expected if

non-olfactory sensory information (the context) was not appropri-

ately correlated with olfactory information, that is, a failure of

cross-modal integration. In drawing parallels to the theory, we

suggest that the mediodorsal nucleus of the thalamus corresponds

to the sensory integrator, correlating input from olfactory and

non-olfactory sources for processing in the controlled associator or

comparator and encoder.

In conclusion, studies involving animals have identified severalbrain areas involved in olfactory learning and memory. These

include the piriform cortex, prefrontal cortex, mediodorsal nucleus

of thalamus, and the olfactory bulb. All of these structures dem-

onstrate plasticity, suggesting the ubiquity of learning phenomena

in olfactory brain structures. Finally, a tentative case can be made

for correspondences between the modular components of the the-

ory and particular brain structures: the piriform cortex with the

olfactory processing module, the prefrontal cortex with the con-

trolled associator, and the mediodorsal nucleus of the thalamus

with the sensory integrator.

Neuropsychological Data

Two types of prediction can be made about the human olfactory

neuropsychological data. The first derives from the theory and can

be succinctly stated. Any interruption in the flow of information

between modules should result in deficits in odor-quality percep-

tion—as measured by discrimination and identification—without

losses in detectability or sensitivity. (One should note that more

elaborate predictions could be derived but that experimental in-

vestigations to date are relatively blunt.) The second type of

prediction derives from the animal literature discussed above,

namely that similar brain regions should also feature in human

olfaction. We deal with this latter issue first.




In animals, lesions of prefrontal cortex, piriform cortex, and

mediodorsal nucleus of the thalamus impair odor discrimination.

In humans, several conditions affecting similar areas also impair

olfactory function. These include aging, Alzheimer’s disease, Kor-

sakoff ’s syndrome, temporal lobectomy, focal lesions to prefrontal

and certain temporal lobe areas (for a review, see Mair et al.,

1995), and Parkinson’s disease (Mesholam, Moberg, Mahr, &Doty, 1998). Neurological damage in aging may occur primarily in

frontal regions (Gabrieli, 1998) as well as in other cortical and

subcortical areas. Alzheimer’s disease may initially damage me-

dial temporal lobe structures before extending to other areas (Gab-

rieli, 1998). Korsakoff ’s syndrome especially involves lesions to

thalamic and limbic structures as well as other areas (Lezak, 1995).

Focal lesions are self explanatory. Thus all these conditions affect

areas involved in olfaction: aging affects frontal structures, Alz-

heimer’s affects piriform cortex in the medial temporal lobe,

Korsakoff ’s affects the thalamus (and possibly medial temporal

lobes), and focal lesions affect frontal or medial temporal lobes.

Finally, for Parkinson’s disease, the role of its affected brain

structures are more difficult to directly link to olfactory function

and deficits here may occur through difficulty in intentional sniff-

ing (see Barz et al., 1997, for an alternative account). Overall, it

appears that brain structures important for olfaction in rats and

monkeys are also important for human olfactory perception.

Within the present theory, lesions in the three main brain areas

discussed above are predicted to spare detection and sensitivity but

impair perception of odor quality as indicated, for example, by

reduced odor discriminability or identification. Before examining

the data it is important to exclude apparent deficits that arise from

two sources. The first, and most obvious, is reduced sensitivity

from damage at the peripheral receptor level (see Varney, 1988).

The second and more subtle source is an inability to perform the

experimental task. This latter concern is very real, because many

disorders of olfaction are associated with impaired explicit-memory function (see Commentary on Assumption 3). Most of

the studies discussed here test for sensitivity changes by compar-

ing olfactory detection thresholds in brain-damaged and normal

participants. However, only a few studies have checked for

generalized-task-performance deficits, and we give these studies

proportionally more weight.

Aging undoubtedly increases olfactory thresholds; older partic-

ipants (50 years or older) typically show lower sensitivity than do

younger participants (e.g., Murphy, 1993; Schiffman, 1993). Older

participants also exhibit reduced suprathreshold discrimination and

identification when compared with younger participants (Cain et

al., 1995; Doty, 1992). This is probably caused both by reduced

sensitivity and by damage to frontal regions. For Alzheimer’s

disease, some studies (e.g., Doty, Reyes, & Gregor, 1987; Morgan,

Nordin, & Murphy, 1995) have identified reduced sensitivity,

whereas others have not (e.g., Kareken et al., 2001; Koss,

Weiffenbach, Haxby, & Friedland, 1988; Rezek, 1987). However,

all studies that have used odor-identification tasks have found

large deficits in such patients, even when nonverbal (picture-

based) procedures were used. More recently, a positron emission

tomography study revealed significant differences in activity be-

tween the piriform cortex of Alzheimer and elderly controls during

odor identification (Kareken et al., 2001), adding further weight to

the argument that impairments arise primarily from damage to

olfactory cortex in the medial temporal lobe.

Some studies have revealed reduced sensitivity in Korsakoff

patients (e.g., P. B. Jones, Butters, Moskowitz, & Montgomery,

1978; Potter & Butters, 1980), but others have not (e.g., Mair,

Capra, McEntree, & Engen, 1980). However, in all of these studies

patients demonstrated reduced discriminability. The study by Mair

et al. (1980) is of particular interest because it also controlled for

more generalized memory deficits. In this study normal controlsand Korsakoff patients performed three short-term recognition

tests, each including several retention intervals. One test used

odors, one used visual stimuli (faces), and one used auditory

stimuli.

In the odor test, at the start of a trial the first odor was presented,

and a second odor followed after a variable delay; the task was to

judge whether this was the same or different from the first odor.

When different from the first, this second odor could be either

similar or dissimilar to the first. There were two main findings.

First, participants in the Korsakoff group were uniformly poorer

than control participants at all time intervals on the odor test —

more so for similar than for dissimilar odor pairs.

Second, on the visual and auditory tests, Korsakoff patients and

controls performed at comparable levels when the comparison was

immediate. However, performance of the Korsakoff group

dropped markedly as the retention interval increased, whereas

performance of the control group was unaffected over the range of

intervals tested. These results imply that damage to the thalamus

(and possibly piriform cortex from damage to the medial temporal

lobes) adversely affects discrimination— consistent with the

present theory. They also suggest that memory and perception

cannot be dissociated as easily for odor perception as they can be

for vision and audition.

The effects of unilateral and bilateral temporal lobectomy have

also been studied. H.M., who received bilateral surgical resection

of the medial temporal lobe (Eichenbaum, Morton, Potter, &

Corkin, 1983), showed broadly normal sensitivity on a range of tests but performed at chance levels when identifying whether two

odors were the same or different and in a matching-to-sample task.

These deficits appear to be limited to olfaction, in that H.M. could

discriminate objects visually and by touch and identify them

(Eichenbaum et al., 1983). Because H.M. lost sizable parts of his

piriform cortex during his resection, these deficits may be attrib-

utable to a loss of the olfactory processing module, insofar as it is

located there.

A further investigation of temporal lobectomy patients was

undertaken by Eskenazi et al. (1983). In Eskenazi et al.’s study

patients with unilateral lobectomies were compared with normal

controls. As with H.M., temporal lobectomy was associated with

significantly impaired discrimination and identification but in this

case with some retained capacity, a probable consequence of

having one intact temporal lobe. There were no differences in

performance between participants with left or right temporal ab-

lations. One should note that we have not discussed hemispheric

differences in olfactory information processing, because the find-

ings to date are inconsistent (see Brand, Millot, & Henquell, 2001)

and differences are small (e.g., Herz, McCall, & Cahill, 1999;

Homewood & Stevenson, 2001).

Damage to prefrontal areas also produces deficits in discrimi-

nation, as reported from at least two studies. Potter and Butters

(1980) tested prefrontal lesioned participants, together with several

comparison groups. The latter was composed of 1 thalamic lesion




patient, a Korsakoff group, brain damaged controls, and normal

controls. Sensitivity testing revealed some deficits in the Korsakoff

group and enhanced sensitivity in the prefrontal group but no other

difference between groups. All participants were given both a

graded (easy to hard) hue-discrimination test and a graded odor-

discrimination test that was matched for difficulty with the hue

test. Hue discrimination was excellent in all groups, with only aslight deficit being observed in the Korsakoff patients. However,

olfactory discrimination was at chance level for thalamic (except

on the easiest test), prefrontal, and Korsakoff groups but was well

above chance in normal and brain-damaged controls. These find-

ings suggest that loss of discriminative ability in olfaction is not a

consequence of general deficits in performance or sensitivity but is

more likely to reflect the inability of participants to perceive odor

quality following thalamic or prefrontal damage.

In the second study of unilateral cortical lesions, Jones-Gotman

and Zatorre (1988) used the UPSIT to assess odor identification.

They found deficits in groups with frontal and temporal lesions but

not in those with parietal lesions, whose performance was compa-

rable to that of normal controls. There were no group differences

in sensitivity. Identification was typically reduced by about 20% in

the frontal and temporal groups. The relatively small size of this

loss, when compared with H.M.’s total loss, is probably a conse-

quence of the unilateral nature of these lesions.

Two conclusions can be drawn regarding the predictions made

at the start of this section. First, broadly similar brain regions

appear to participate in olfactory information processing in hu-

mans and animals. Second, damage to any of these structures, and

by implication their proposed correlates in the theory, typically

results in a loss of odor-quality perception (discrimination and

identification), often without affecting detection (sensitivity and

intensity). The neuropsychological data also suggest three further

conclusions pertinent to the theory:

1. Disorders of odor-quality perception (discrimination and

identification) are typically comorbid with disorders of

explicit memory (see Commentary on Assumption 3 for

implications).

2. Deficits in the perception of odor quality are not easily

dissociated from deficits in odor memory (this is in

marked contrast to vision and audition and again suggests

the reliance of olfactory information processing on

memory).

3. The only dissociation to emerge (a partial one at that) is

between the perception of odor quality and detectability

(see Commentary on Assumption 2 for implications; butsee West & Doty, 1995, for a contrary view).

Discussion

In this article we present a theory of odor-quality perception that

we believe to be more consistent with the various domains of

recent olfactory research than the stimulus-problem approach that

has driven psychological research for much of the last 100 years.

The nature of the theory and the evidence for it are discussed in

earlier parts of the article and we now turn to a more general

theme, namely, the implications that the theory has for the widely

held view that olfactory perception differs in some fundamental

ways from the other exteroceptive senses.

Emphasis on the unique aspects of olfaction has been common

in recent reviews of research on psychological aspects of odors

(e.g., Herz & Engen, 1996; Richardson & Zucco, 1989; Schab,

1991). We feel that this is wholly justified and that three further

implications from the theory add to this conclusion. In total, sixfeatures of olfaction appear to set it apart from the other senses:

1. Olfaction is primarily a synthetic sense rather than an

analytic sense.

2. Olfaction does not appear to allow imagery.

3. Odor perception relies more heavily on experience than

do other senses.

4. The properties of olfactory memory differ in many ways

from those of other memory systems.

5. The relationship between language and olfaction is far

more constrained than in the other senses.

6. Olfaction has several unusual neuroanatomical features.

Because the last three items in this list have seen fairly extensive

discussion elsewhere (see Herz & Engen, 1996; Richardson &

Zucco, 1989; Schab, 1991), we briefly examine the first three,

which are those derived from our theory.

1. Olfaction as a Synthetic Sense

Both vision and audition are characterized by the ability to

analyze the component features of a complex stimulus, a facility

that improves with practice in both modalities (e.g., Gibson, 1953).Olfaction is different from this in two respects. First, the informa-

tion needed to distinguish between the components of an odor

mixture may not be available, because of the nature of olfactory-

information processing. In contrast, the visual system, for exam-

ple, contains a wide variety of cells in the lateral geniculate

nucleus and striate cortex that are differentially sensitive to a large

range of specific features in the visual world (e.g., Hubel &

Wiesel, 1959). To date, there appears no obvious analogy to these

type of cells in olfaction, and even if they exist, their output does

not appear accessible to consciousness in the same way as visual

information. This is because in the olfactory system there are strict

limits on the number of stimuli that can be identified in an odor

mixture (see Commentary on Assumption 4). Presumably, if fea-

ture information were accessible, such limits would not be in

evidence.

A second and related difference concerns the impact of expertise

on feature detection. In the most careful study of this issue,

Livermore and Laing (1996) observed that experts with many

years experience in perfume and flavor design were no better than

novices in identifying the component parts of odor mixtures (con-

trast this for example with visual feature detection, which mark-

edly improves with practice; see, e.g., Myles-Worsley, Johnston,

& Simons, 1988). This suggests that real physical constraints are

imposed on feature detection in olfaction in a way not encountered

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Received June 6, 2001

Revision received June 13, 2002

Accepted June 16, 2002


Theory of Odor Perception

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