Neuropsychologia 38 (2000) 60±82
www.elsevier.com/locate/neuropsychologia
A progressive category-speci®c semantic de®cit for non-living
things
H.E. Moss*, L.K. Tyler
Centre for Speech and Language, Department of Experimental Psychology, University of Cambridge, Downing Street,
Cambridge CB2 3EB, UK
Received 19 May 1998; accepted 2 March 1999
Abstract
We report a longitudinal study of a patient, ES, with a progressive degenerative disorder resulting from generalised cerebral
atrophy. Across a range of tasks, ES showed a greater diculty in recognising and naming artifacts than living things. This
de®cit for artifacts emerged over time, as she became more severely impaired. In one task, picture naming, there was a crossover
from an initial de®cit for living things to the later artifact de®cit. All materials were carefully controlled to rule out potential
confounding factors such as concept familiarity or age of acquisition. There was no evidence that ES's de®cit for artifacts was
associated with a greater loss of functional than visual information. The pattern of results are consistent with a recently
proposed distributed connectionist model, in which a de®cit for artifact concepts can emerge as the result of severe, general
damage to semantic memory. # 1999 Elsevier Science Ltd. All rights reserved.
Keywords: Semantic memory; Naming; Comprehension; Correlation; Concepts
1. Introduction
Category-speci®c semantic impairments have created
a great deal of interest in neuropsychology because of
the insights that they may provide concerning the contents, organisation and neuroanatomical bases of
semantic memory. Several kinds of semantic dissociation have been reported in the literature, including de®cits for concrete words compared to abstract
words [3,63] and vice versa [59], de®cits for body parts
[10,55], and colour names [13]. But the most frequently
reported and widely studied dissociation has been that
between knowledge of living things and man-made
artifacts. Typically, the impaired category has been
living things [1,6,12,32,42,45,47,48,67] or a subset of
living things, such as fruit and vegetables [27,49] or
animals [4]. A rather smaller number of patients have
* Corresponding author.
E-mail address: [email protected] (H.E. Moss).
been reported with degraded knowledge for man-made
objects, with some or all living things relatively
preserved [28,34,47,65,70].
In the current study we focus on the dissociation
between living and non-living things. Five major types
of account have been suggested in the literature to
account for this kind of selective semantic impairment.
1. Domain-speci®c accounts in which evolutionary constraints have resulted in the development of distinct
neural systems that are specialised for di€erent
broad types of knowledge, such as that of animal
and plant life, and that of man-made objects [4].
2. The perceptual/functional hypothesis which claims
that semantic memory is organised according to
type of semantic information, rather than category
per se. Because our representations of living things
are more dependent on perceptual than functional
attributes, they will be more degraded when there is
damage to the store of perceptual information,
whereas man-made objects will be more a€ected by
0028-3932/99/$ - see front matter # 1999 Elsevier Science Ltd. All rights reserved.
PII: S 0 0 2 8 - 3 9 3 2 ( 9 9 ) 0 0 0 4 4 - 5
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
damage to the functional properties which are
critical to their meanings [15,52,66,67].1
3. Distributed accounts in which there are no explicit
boundaries within semantic memory according to
category or type of information, but where selective
impairments emerge as a result of the di€erent
structure of concepts within di€erent categories
[5,11,14,62].
4. An impairment to stored structural descriptions of
objects may lead to a de®cit for living things, since
items in this domain are more visually similar, and
therefore confusable, than are artifacts [18,49].
5. The prevalence of de®cits for living things may be
explained by their typically lower familiarity, which
may make them more vulnerable to damage [19].
Other `nuisance factors' have also been identi®ed,
such as the greater visual complexity of living things
[21,54] and the greater diculty of questions about
living things for normal subjects [4,54]. Similarly,
the reverse pattern of impaired artifact knowledge
could potentially be accounted for by a further
psycholinguistic variable, age of acquisition, which
favours living things over artifacts [33].
The accounts listed above all predict de®cits for living
things, but di€er in the extent to which they accommodate the rarer pattern of a selective de®cit for artifacts.
Hypotheses 4 (an impairment of structural descriptions) cannot provide an account of the double dissociation since it predicts a consistent e€ect in just one
direction: a disadvantage for living things. Two responses to this point are possible. The ®rst is to argue
that the existence of selective de®cits for man-made
objects is questionable, as there may be problems with
all of the small number of cases reported, and therefore that it is only necessary to explain the single dissociation of a living things de®cit. The second
possibility is that this account is intended to apply
only to de®cit for living things, and that a further,
di€erent kind of account will be required to cover the
reverse pattern. Hypothesis 5 (`nuisance variables') has
generally focused on living things de®cits, since most
1
This is a simpli®cation of the more sophisticated account developed by Warrington and McCarthy [66]. They suggested a more
®ne-grained distinction of di€erent kinds of sensory information (e.g.
shape, colour) that may be more or less important for di€erent categories. However, at the level of di€erences between the broad
domains of living and non-living things, the basic visual/functional
distinction is generally considered to be the most important. For a
related proposal concerning the di€erential weighting of information
for concepts in di€erent categories see Damasio and colleagues
[8,58].
2
However, unilateral left temporal involvement may be the case
for de®cits for living things that only a€ect naming abilities, rather
than a central semantic de®cit evident in all modalities of input and
output [9,45].
61
variables that have been investigated predict poorer
performance on living things (familiarity, visual complexity, diculty). However, the double dissociation
might be accommodated if apparent artifact de®cits
turn out to be reducible to an age of acquisition bias
in favour of living things (i.e. words for living things
are typically learned earlier than those for artifacts).
The question would remain open, however, as to why
some patients would be sensitive to one variable (e.g.
familiarity) and others sensitive to a di€erent variable
(e.g. age of acquisition).
The domain-speci®c account can accommodate
selective de®cits for artifacts, if it is assumed that one
of the specialised semantic stores that has evolved is
for the domain of man-made objects. Damage to part,
or all, of the neural substrate for this store would then
lead to selective loss of information in this domain.
This account predicts that it should be possible to
identify distinct distributions of lesion sites resulting in
de®cits for living and non-living things, since these are
supported by di€erent neuroanatomical structures or
sets of structures.
A review of neuropsychological studies [23]
suggested that there was a consistent correlation of
lesion site and impaired category, with de®cits for living things associated with bilateral damage to the
antero-medial parts of the temporal lobes and de®cits
for non-living things involving left fronto-parietal
damage. However, there are exceptions to this pattern
[28,34] and the picture is certainly more complex. A
recent large-scale study of patients with focal lesions
implicated the mesial occipital regions bilaterally
extending into the ventral temporal area on the left for
recognition de®cits for living things while a de®cit for
artifacts (or more precisely, tools) was associated with
lesions to the occipito-parietal temporal junction, [57].
PET imaging studies with normal subjects have also
provided evidence for the speci®c involvement of the
mesial occipital areas in the recognition of living things
[37,57] and indicate that areas of premotor cortex in
the left hemisphere and of the left middle temporal
gyrus are activated when people name pictures of tools
[37]. Two general points seem to emerge from these
results; (1) both lesion studies and imaging studies
have indicated that di€erent regions may be more or
less important for processing concepts in di€erent
semantic domains, although the precise distribution is
unclear; (2) de®cits for artifacts may arise as a result
of unilateral left hemisphere lesions, while de®cits for
living things generally involve bilateral damage.2
The perceptual/functional account also addresses
both sides of the dissociation. A de®cit for living
things is explained in terms of a greater loss of perceptual attributes, while a de®cit for artifacts involves
selective damage to functional properties. The perceptual/functional account has been widely embraced in
62
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
the literature, bolstered by the demonstration that a
category de®cit can emerge from selective lesions to
functional or perceptual information when the conceptual representations are appropriately weighted in a
computational simulation [15] and by reports of several patients with de®cits for living things who seemed
to have greater problems with visual than functional
knowledge [1,12,16,22,42,48,52].
However, there has recently been something of a
backlash against the perceptual/functional hypothesis;
it has been claimed that many of the patients would
not have shown a disadvantage for visual properties if
familiarity and question diculty had been appropriately matched [4,32]. Moreover, several patients with
living things de®cits have now been shown to have an
equal impairment for functional and perceptual/visual
information within that domain [4,32,34,43]. The association of visual information and living things de®cits has been further questioned by a recent report by
Lambon Ralph et al. [34] of a patient, IW, with a
clear problem with visual properties who nevertheless
showed no speci®c de®cit for living things; in fact, she
showed a signi®cantly greater de®cit for artifacts on
several of the tests. Returning to the issue of the
reverse dissociation, the perceptual/functional hypothesis predicts that such patients should have more diculty with functional information. Most patients with
de®cits for man-made objects have not been tested in
enough detail to determine the relative integrity of perceptual and functional semantic knowledge. However,
in the case of IW, mentioned above, a greater de®cit
for artifacts than living things was found in the context of degraded knowledge for visual rather than functional information, clearly inconsistent with the
perceptual/functional hypothesis.
Finally, the ®fth type of account is that selective deficits arise from damage to a unitary semantic system
in which concepts in di€erent categories are structured
in di€erent ways. These accounts can accommodate
selective de®cits for both living things and artifacts,
with the di€erent patterns emerging as a function of
severity of the overall damage. Devlin et al. [11] implemented their model in a connectionist network,
which was trained on representations of living and
3
Devlin et al.'s model also accounts for selective de®cits that arise
from focal lesions, since they represent visual and functional features
in topographically distinct stores. If the lesion is simulated by selective damage to one or other of these stores, then category de®cits are
produced, since living things and artifacts are weighted towards
visual and functional properties, respectively. This aspect of the
model is essentially the same as the Farah and McClelland [15]
model and incorporates the perceptual/functional hypothesis.
However, the important point for our current purpose, is that Devlin
et al. [11] show that such selective lesions are not necessary to produce category e€ects, since they also emerge when there is random
damage to their network, corresponding to di€use brain damage.
non-living things with the following characteristics: living things had many shared, intercorrelated semantic
properties (i.e. properties that regularly co-occur, such
as has eyes, has ears, can see, has legs ), while artifact
concepts had a greater proportion of distinctive properties, and these were less densely correlated. The network was then `lesioned' by randomly removing
increasingly large proportions of its connections. They
demonstrated that when damage to the network was
mild, there was a greater de®cit for artifacts than living
things. This was because individual distinctive properties of artifacts could be damaged, but the densely
inter-correlated properties of living things supported
each other with mutual activation, compensating for
any damage to a few properties. However, with
increasing damage, the representations of living things
start to su€er disproportionately, as clusters of correlated properties can no longer withstand the damage,
and large numbers of living things that share those
properties are a€ected. The impact on artifacts is a
more gradual, linear decline, such that they are preserved relative to living things, except at the most mild
level of lesioning.
The advantage of this kind of model is that it can
account for the existence of category-speci®c de®cits in
patients who do not have a focal lesion that could
a€ect a speci®c store of knowledge, but who have
more widespread or patchy damage. For example,
there have been several reports of selective impairments for living things in patients with DAT
[25,26,51].3 Gonnerman et al. [26] provided some evidence in support of the prediction that a de®cit for
artifacts will give way to a de®cit for living things, as a
functional of severity. A group of DAT patients were
tested on naming tasks, and there was a trend for
those patients with milder naming impairments to be
more impaired for artifacts than living things.
However, this conclusion has been questioned in a second large cross-sectional study by Garrard et al. [24],
who found no correlation between disease severity and
category e€ects for their group of DAT patients.
A di€erent distributed model has recently been
developed by Durrant-Peat®eld et al. [14,62]. This has
many characteristics in common with the model of
Devlin et al. [11], in that living things have more
shared, intercorrelated properties, while artifacts have
more distinctive properties that are true of only a few
members of the category. The major advance on the
earlier model is that we speci®ed in more detail the
nature of the properties that were intercorrelated for
living and non-living things. Drawing on previous suggestions in the neuropsychological [5,12], developmental [36,58] and linguistic [69] literature, we
hypothesised that the key correlations are those
between form (visual properties) and function, and
that these correspondences are learned by the develop-
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
ing infant or, in the case of the computational simulation, by the network during the training phase.
However, the nature of these form-function correlations is di€erent for living things and artifacts. For
living things, there are many correlations among the
shared, biological functions and the shared perceptual
properties that support them; that is between what
they do and what they look like (e.g. can see > has
eyes; can ¯y > has wings ). Living things also have
some distinctive properties (e.g. has a mane, is pink,
chases mice ) but these tend to be weakly correlated,
and therefore very vulnerable to damage. In contrast,
artifact concepts tend to have strong correlations
between pairs of individual, distinctive form and function properties (e.g. has a serrated edge > used for sawing ) whereas the shared properties are fewer and more
weakly correlated than those of living things [60]. This
means that the distinctive properties of artifacts will be
relatively more robust to damage than those of living
things.4
When we instantiated these assumptions in a connectionist model and then lesioned it by the random
removal of connections, it generally showed a de®cit
for living things [14,62]. This is due to the loss of the
weakly correlated distinctive properties, which means
that the model cannot tell the di€erence between one
living thing and another. However, at the most severe
levels of lesioning, artifacts were more a€ected. This is
because, when the model has lost so many connections
that it is only able to operate on shared properties
(because these are more frequent and so more robustly
learned) the greater number and density of correlations
for the shared properties of living things supports better performance than for artifactsÐalthough overall
performance is generally poor.
Therefore, our model predicts the opposite pattern
to that of Devlin et al. [11]: an impairment for artifacts
emerging when damage is at its most severe. As we
4
Like most other accounts, in its current form, our model only
accounts for domain-level di€erences between living and non-living
things, and does not distinguish among categories within those
domains. In principle, our model should also be able to account for
dissociations within those domains, most importantly between plant
and animal life, since these patterns have been reported in the neuropsychological literature [4,27,28,49]. Such dissociations are quite
possible in our model, to the extent that the internal structure of
concepts in these categories di€ers in systematic ways, and this will
be explored in future research. However, the current focus is on the
broad domain-level dissociation.
5
Gonnerman et al. [25] include longitudinal data for two single
cases, one of whom shows a consistent de®cit for natural kinds and
the other a more variable de®cit for artifacts. Although this avoids
many of the problems of cross-sectional comparisons, it is still the
case that the decline in performance over time for DAT patients as
measured by cognitive estimates or naming tests may not accurately
re¯ect the level of semantic memory de®cit, which is often mild in
comparison to other cognitive domains.
63
mentioned above, data concerning the relationship
between severity and category e€ects in the DAT
population is mixed, with the Gonnerman et al. [25,26]
study suggesting artifact de®cits for more mildly
impaired patients and Garrard et al. [24] claiming no
correlation. In fact, when we examine the data
reported by Garrard et al. [24] there is some evidence
of artifact de®cits for the most impaired patients, at
least when performance was measured over all semantic tasks rather than just naming. Similarly, a study by
Tippett, Grossman and Farah [56], shows a tendency
for artifact de®cits to emerge in patients with moderate
rather than mild dementia. Overall, data concerning
the severity by category interaction is inconclusive, and
this may be due to the diculty of assessing severity
of semantic impairment in a population of patients
who have the wide range of other cognitive de®cits associated with DAT. A more appropriate testing
ground would be individual longitudinal studies of
patients with more circumscribed linguistic/semantic
impairments, an approach we take in the current
study.5
In addition to the severity e€ect, the DurrantPeat®eld et al. [14] model makes predictions about the
properties that will be more or less a€ected in di€erent
categories. Patients who have de®cits for living things
should show a profound loss of distinctive properties
making it very dicult to tell one living thing from
another, but they should have relatively preserved
knowledge of the shared properties of living things. In
the few cases where distinctive and shared properties
have been directly contrasted, this has proved to be
the case [4,43]. The other side of this coin, is that we
predict that patients with de®cits for artifacts should
not show such a marked loss of distinctive relative to
shared information. A simplistic interpretation of our
model might suggest that distinctive information
should be better preserved than shared properties for
artifacts, as they are more strongly correlated.
However, this is unlikely to be the case, since the
weaker correlational strength of these shared properties will be partially compensated for by their greater
frequency. By de®nition, shared properties occur for
more items than do distinctive properties, and this will
give some degree of protection to damageÐcertainly
in a connectionist model, and plausibly for the
damaged human system too, since we know that familiarity of both objects and their properties can be an
important predictor of loss and preservation [19,20].
The more plausible prediction then, is that a patient
with a de®cit for artifacts will have a profound impairment, with few distinctive properties left intact for any
category, but with a greater preservation of the shared
information of living things, which supports better performance for these items than for artifacts. However,
64
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
Fig. 1. MRI scan for ES, 1996.
none of the reported patients with an artifact de®cit
has been tested in ways that could address this issue.
This review of the possible accounts of categoryspeci®c de®cits has highlighted a number of questions
that can be addressed by a detailed study of a patient
with a semantic de®cit for artifacts relative to living
things.
1. Can we detect a genuine selective de®cit for artifacts, when factors such as familiarity and visual
complexity are adequately controlled?
2. Is there a clear di€erence in the distribution of
lesion sites resulting in de®cits for living and nonliving things, as predicted by the domain-speci®c
account?
3. Do patients with de®cits for artifacts show a greater
problem with functional than visual properties
(either for artifacts speci®cally or across the board)
as is predicted by the perceptual/functional hypothesis, or will we ®nd further support for the surprising ®nding of a greater impairment of visual
knowledge associated with an artifact de®cit as
reported by Lambon Ralph et al. [34]?
4. Do we generally ®nd de®cits for artifacts when
6
We are very grateful to Richard Wise at The Charing Cross
Hospital, London, who referred ES to us.
damage to the semantic system is mild, as predicted
by Devlin et al. [11] or when damage is most severe,
as predicted by Durrant-Peat®eld et al. [14]?
5. Do patients with a selective de®cit for artifacts
show less erosion of distinctive relative to shared
information than we typically see in patients with
de®cits for living things, as predicted by DurrantPeat®eld et al. [14]?
In this report we present a detailed study of patient
ES, who developed a greater de®cit for artifacts than
living things in the course of a progressive disorder
which primarily a€ected her language abilities.
Although ES was initially diagnosed as possibly having
semantic dementia, this was later revised to a probable
global cerebral degenerative disorder.
2. Case history
ES is a 67-year-old left-handed woman who has previously worked as a sales assistant and clerk.6 She was
born in Ireland and her ®rst language was Gaelic,
although she learned English from school age, since
when it has been her dominant language. She reported
in 1993 with a two-year history of word-®nding diculties and problems remembering the ends of sentences. She was ®nding it more dicult to have
Fig. 2. MRI scan for ES 1996, with damage identi®ed by voxelÐbased morphometry.
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
65
66
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
Table 1
ES's scores on a range of tests of memory and cognitive function
WAIS-R(scaled scores)a
Verbal
Information
Digit span
Vocabulary
Arithmetic
Comprehension
Similarities
Total
Performance
Picture completion
Picture arrangement
Block design
Object assembly
Digit symbol
Total
Warrington Recognition Memory Test b
Words
Faces
MMSE c
Judgement of line orientation d
Autobiographical Memory Interviewe
Personal semantic
Childhood
Early adult
Recent
Autobiog. Incidents
Childhood
Early adult
Recent
Raven's Coloured Progressive Matricesf
Rey Figureg
Copy
Immediate Recall
a
September 1994
December 1995/January 1996
5
6
1
5
2
2
21
3
4
3
3
2
4
19
4
2
5
2
4
17
5
6
5
3
3
22
35/50 (5th%ile)
41/50 (25±50th%ile)
±
21/50 (<5th%ile)
31/50 (<5th%ile)
19/30
19/30 (9th%ile)
±
±
±
14.5/21 (borderline)
15/21 (prob.abnormal)
not tested
±
±
±
June 1993
2/12 (reduced set)
6/9 (acceptable)
6/9 (borderline)
not tested
February 1996
18/36 (5th%ile)
±
±
27.5 (<10th%ile)
6
[68]; b[64]; c[17]; d[2]; e[31]; f[46]; g[35].
conversations, especially by telephone. However, she
was running her household, and by late 1994, she was
still doing all the housework, shopping and paying
bills herself. She was also able ®nd her way around
London by bus on her own. When we saw her most
recently in December 1996, she was still able to do
shopping and cooking. In contrast to her day-to-day
abilities, ES showed a range of cognitive and linguistic
impairments when tested in 1993, and these have continued to deteriorate, at varying rates over the last
four years. There is some indication of a family history
of similar problems with her father and one of her
brothers apparently having progressive speech problems. An MRI scan in 1996 showed cerebral atrophy
but no focal lesion, and the diagnosis was a possible
global cerebral degenerative disorder, but not thought
7
We are grateful to Cathy Price of the Wellcome Institute for
Cognitive Neurology for providing this analysis.
to be Alzheimer's disease (see Fig. 1). An analysis of
the MRI scan using voxel-based morphometry con®rmed the widespread patchy damage and also that
there was substantial damage to the inferior temporal
lobes bilaterally, more extensive on the right than the
left (see Fig. 2).7
2.1. Cognitive tests
ES's performance on a range of tests of memory
and cognitive function is shown in Table 1. Most of
the tests reported in the table have been administered
on two occasions, to illustrate the change in performance over time. Some tests, however, have been administered only once, but are included to give an idea of
ES's pro®le on a wide range of skills. The scores
reported in Table 1 clearly show that ES has a range
of cognitive impairments, including reasoning, memory
and arithmetic. However, it is not clear to what extent
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
her abilities have declined over the years. Although
there has been a marked decrease in her scores for
both words and faces in the Warrington Memory Test,
she has remained remarkably stable on the WAIS-R
IQ test (especially for the performance subtests) and
on the Raven's progressive matrices.
2.2. Language tests
ES's initial complaints concerned problems with
remembering words and understanding conversations.
When she was assessed by Dr Richard Wise at the
Charing Cross Hospital in June 1993, she showed clear
problems with picture naming (38/48) and semantic
processing (7/10 on a subset of the Pyramids and
Palmtrees Test). Matching a word to the correct picture in an array was perfect for written words (30/30)
but a little less accurate for spoken words (28/30).
Repetition of single spoken words was perfect (32/32),
while reading of single words was slightly impaired
(44/48). Spelling of single spoken words was correct on
21/28 trials. ES's spontaneous speech was generally ¯uent but contained some word-®nding diculties and
circumlocutions, especially for nouns, as this sample
from April 1994 illustrates:
(discussing ES's grandchildren )
ES: Yes, ah, the oldest one, he is the nicest
EXP: Is he?
ES: Mmmm. He is the nicest . . . err . . . football
. . . it stops then . . . and then, then it goes to the
Irish one then and he's a boxer, and err, err. At the
school there are two hundred in the same . . . and
he's in three of them, and he is one of the three at
the top.
EXP: At what?
ES: In the school.
EXP: So is he taking his exams this term or is it
next year?
ES: Next year, yeah. He has been saying it all the
time but he is going to be a solicitor.
Over the subsequent years up until December 1996
we have tested ES on a range of language tests, and
these show the extent to which her abilities have
8
ES also shares some characteristics with patients described as
having a non-¯uent progressive aphasia; she made some repetition
errors and phonological errors in speech output, as well as having
diculty with tests of comprehension of syntax. However, she could
not be described as having `severe distortion of speech output with
phonological errors and agrammatic sentence structure' which has
been given as a characterisation of non-¯uent progressive aphasia
[29] even by 1996 (see her de®nitions in Appendix 1), and her semantic comprehension problems were more marked than would be
expected for a non-¯uent patient. Rather, ES shows a pattern of de®cits that crosses the ¯uent/non-¯uent boundary, in a similar manner
to patient FM, whom we described in an earlier paper [61].
67
declined since the initial assessment in 1993. For
example, her reading of single words had deteriorated
to 37/60 by February 1996 (PALPA Spelling-sound
Regularity Reading task, [30]), while spelling to dictation was down to 11/40 correct (PALPA Regularity &
Spelling Test, [30]), and her repetition of single words
was no longer perfect (148/180 correct). ES's speech
has also become more e€ortful and empty as illustrated by this sample from December 1996:
EXP: Can you tell me about what you would do on
a normal day at home?
ES: I/b//b/ all six, six, I go to bed and ®ve, ®ve, tis,
tis enough I have to, God, nobody, /ti/tin the other
so some/somemmer/of them, my sister/de/they, she,
she, got a, she does the same, she said she go, she
didn't start/f//f/forty till over forty too.
3. Experimental investigation
The language tests administered at ES's initial
assessment suggested that she had some degree of
impairment in several tasks, including those tapping
naming and semantic processing. Her relatively
impaired language performance compared to other
tasks, along with her reported symptoms of naming
and comprehension de®cits in the context of good
everyday memory and orientation led to an initial
diagnosis of possible semantic dementia.8 We therefore
investigated the nature of ES's semantic impairments
across a range of tasks, and tracked their progression
over almost three years, by repeating some or all of
the tests at approximately 6-monthly intervals between
May, 1994 and December, 1996. Many of the tests
included a contrast between living and non-living concepts, and so we were able to compare her knowledge
of these two domains over time, thus enabling us to
address the issues raised in the introduction.
3.1. Experiment 1: picture naming
Verbal naming of pictures has been widely used in
the study of patients with category-speci®c impairments. Some patients have been found to have an
impairment that is restricted to naming tasks, while for
others, naming is a sensitive index of an underlying
semantic de®cit that is also apparent in other tasks
that require access to conceptual knowledge but which
do not require a naming response.
ES was asked to name the 260 black and white pictures in the Snodgrass and Vanderwart [50] set, on ®ve
occasions between June 1994 and December 1996.
Over this time, ES's overall naming accuracy decreased
from 70% to 18%. As shown in Fig. 3, the rate of
decline was not the same for the broad domains of
68
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
Fig. 3. Picture naming accuracy (percent correct) for ES between June 1994 (t1) and December, 1996 (t5).
living and non-living things. At the ®rst two testing
sessions, ES correctly named more non-living things,
but there was then a steep decline for this domain, so
that by the last testing session, ES was able to name
more of the living things (24%) than the non-living
things (15%), which was a marginally signi®cant di€erence (w 2=3.2, P < 0.1). Errors included `don't knows'
and correct circumlocutions (e.g. crownÐI know, put it
on head; tigerÐbig cat ) or correct gestures, with occasional phonological errors (e.g. windmillÐmill, millho€ ).
However, as is now well-known, naming of living
things in this set may be signi®cantly underestimated,
because they tend to be less familiar and more visually
complex than the non-living things [19]. To examine
the independent e€ects of semantic category and other
variables such as familiarity, on ES's naming performance, we entered her naming data at each time slice
into a simultaneous logistic regression analysis.9 In addition to category (living/non-living) we included the
variables of rated familiarity, word frequency, imagability, naming agreement, objective age of acquisition
(75% rule) and visual complexity [39] and length in
9
We are grateful to Matt Lambon Ralph for his invaluable help
with these analyses.
phonemes. These analyses showed an independent
e€ect of category over and above the other variables
at three of the time slices. At the ®rst two test sessions,
ES was poorer at naming living than non-living things
(Wald=6.6, P < 0.05 and 3.01, P < 0.09, respectively). In the next two sessions, there was no di€erence
between living and non-living things, and by the ®nal
test session the e€ect had reversed, with poorer naming
for the non-living things (Wald=3.97, P < 0.05). To
con®rm the cross-over from an initial de®cit for living
things to a de®cit for artifacts at the more severe end
of the continuum, we carried out an additional logistic
regression analysis, in which the naming data for all
®ve time slices were included, coded by the variable,
time, along with all of the psycholinguistic variables
listed above for the original analysis. In addition to
the main e€ect of time, showing that ES's naming
overall declined signi®cantly from the ®rst to last test
session (Wald=135, P < 0.001), and the main e€ect of
category (in the direction of poorer naming overall for
living things: Wald=14.1, P < 0.001), there was also a
signi®cant interaction between time and category over
and above the other variables (Wald=12.19,
P < 0.001). This interaction re¯ects the cross over
from the earlier advantage for non-living things to an
advantage for living things, as naming becomes more
impaired.
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
The regression analyses revealed that several other
variables were signi®cant predictors of ES's naming accuracy, in addition to semantic category. The major
variable was objective age of acquisition, which was
signi®cant at each time slice, and in the overall analysis (Wald=62.4, P < 0.001). In the overall analysis,
there was also an e€ect of word length as measured by
number of phonemes, with shorter words named more
accurately (Wald=45.7, P < 0.001) and of visual complexity, with naming poorer for more complex pictures
(Wald=12.6, P < 0.001). Surprisingly, there was no
e€ect of concept familiarity (Wald=0.26, P > 0.6).
However, familiarity was a signi®cant predictor if age
of acquisition was removed from the analysis
(Wald=22.3, P < 0.001). This indicates that there was
also an e€ect of familiarity, but that it was weaker
than that of age of acquisition and so failed to be signi®cant when both variables, which are correlated to
some degree, are included in the analysis. We return to
the e€ect of age of acquisition on ES's naming in the
General Discussion.
3.1.2. Summary of naming results
The naming data show that ES developed a signi®cantly greater de®cit for non-living things as the severity of the naming impairment increased over time. At
earlier testing sessions, when the disorder was more
mild, living things were more a€ected. This is the pattern of results predicted by the Durrant-Peat®eld et al.
[14] model, but it is not consistent with the prediction
of Devlin et al. [11] that an impairment for artifacts
will be found when the naming impairment is at its
mildest.
3.2. Experiment 2: property veri®cation
Our next question was whether ES would also show
an emergent de®cit for non-living things relative to living things when the task did not involve verbal naming. Is there a category-speci®c central semantic de®cit,
or is this a category-speci®c anomia, such as recently
reported for non-living things [53]. Our ®rst test of this
question was a spoken property veri®cation study, in
which ES was asked whether attributes were true or
false of concepts within either the living or non-living
domain.
3.2.1. Method
The test consisted of questions in 16 property conditions. Half the items were living things and half were
artifacts. Across these sets, properties were divided
into shared (true of all members of the category) and
10
These ®gures are based on the data available for 109/152 non living things and 144/170 living things.
69
distinctive (true of only one or a few members of the
category) and this variable was crossed with whether
the properties were perceptual or functional. Finally,
half of the trials were true, and half were false. In the
case of the distinctive properties, a true statement was
®rst created for an item (e.g. kettleÐused to boil
water ), and then a false trial was made by pairing the
property with a similar member of the same category,
which did not have that distinctive property (e.g. teapotÐis used to boil water ). The contrasts between true
and false properties were deliberately designed to
require ®ne-grained distinctions among close category
co-ordinates. There were 22 items in each of the eight
distinctive property conditions. For both living and
non-living things, the same items were used in the perceptual and functional property conditions where possible, so that familiarity was held constant. However, in
a few cases it was not possible to generate suitable
properties for the same items and so they were alternated with di€erent items of a similar familiarity level.
The familiarity of items in the living and non-living
categories was also matched, such that the mean familiarity rating for living things was 4.9 in the perceptual
property condition and 5.1 in the functional property
condition. For non-living things, the means were 5.4
and 5.3, respectively ([7] and our own familiarity rating
norms).
Because of the shortage of suitable shared properties
it was not possible to use all the items that had been
in the distinctive conditions; we used a subset of 19
items in the shared visual property condition for living
things and 10 items in the shared visual property condition for non-living things. As in the case of the distinctive properties, false trials were created by repairing each property with another item. For shared
properties, this was not a close category co-ordinate,
but a member of a di€erent semantic category (e.g. the
shared property of bicycleÐis used for transportÐwas
paired with the item cabbage to give the false trial cabbageÐis used for transport ).
We did not initially match living and non-living
items on age of acquisition, since the materials were
devised before we discovered the impact of this variable on ES's accuracy in the naming task. However,
we subsequently looked up objective age of acquisition
[39] for these items and found that the categories were
in fact well-matched on this variable (mean for living
things 46.86, mean for non-living things, 44.8, collapsing over all conditions).10
For all conditions each property appeared in one
true and one false trial. These were counterbalanced
over two versions of the materials. Trials were presented in pseudorandom order within each version.
The experimenter read out the item of interest, and
then the property in question form (e.g. Kettle. Is it
used to boil water? Hen. Does it live on rivers and
70
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
Table 2
Results for ES and the control group in the property veri®cation task
Percent correct
Living things
Shared properties:
visual
functional
Distinctive properties
visual
functional
Artifacts
Shared properties
visual
functional
Distinctive properties
visual
functional
Controls Mean (min±max)
ES
June 1994
July 1995
November 1996
94.4 (86.8±100)
98.3 (95.5±100)
89
93
95
98
70
70
95.4 (93.2±100)
96.6 (90.9±100)
86
84
82
84
73
68
97.5 (90±100)
99.2 (97.7±100)
85
91
80
95
75
64
92.9 (88.6±97.7)
98 (95.5±100)
91
91
86
77
59
52
lakes?) Subjects were instructed to respond YES or
NO to each question.
3.2.2. Results
The results for a group of nine unimpaired elderly
control subjects (age range 67±79 years) are shown in
Table 2, alongside the results for ES at three time
slices (June 1994, July 1995 and November 1996). The
table shows that ES was slightly impaired on this task
at the ®rst two time slices, with scores just within or a
little below the control range. By the end of 1996,
however, she was doing very poorly, with accuracy
well below the normal range. This shows that ES's
semantic impairment was not con®ned to naming
tasks, although at the earlier time slices her anomia
was more severe than her comprehension de®cit.
Fig. 4. Property veri®cation accuracy (percent correct) for ES in June, 1994 (t1), July, 1995 (t3) and November, 1996 (t5).
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
To address the question of whether ES was signi®cantly poorer for artifacts than for living things, we
compared overall accuracy at each of the three testing
sessions. There was no di€erence at the ®rst time
(w 2 < 1) or at the second time (w 2 < 1), but by the
last test session, ES's accuracy for artifacts had
declined, leading to a marginally signi®cant e€ect
(w 2(1)=3.73, P < 0.1). The emergence of the de®cit
for artifacts over time is plotted in Fig. 4.
Our next question was whether ES's de®cit for artifacts was associated with a de®cit in her knowledge of
functional properties, as predicted by the perceptual/
functional hypothesis. We compared accuracy on perceptual and functional properties, both within the artifact domain speci®cally, and for the total set, at each
time slice, as well as collapsing over all time slices.
There was no hint of a di€erence between the two
kinds of information (w 2 < 1 in all cases). Across all
time slices, ES correctly veri®ed 81% perceptual properties and 80% functional properties.
We also examined ES's responses to determine
whether the advantage for living things over artifacts
was associated with better knowledge of shared information for living things than artifacts, as predicted by
Durrant-Peat®eld et al. [14]. There was little support
for this prediction: at the ®nal test session, ES's overall
accuracy for shared properties was 70% for living
things and 69% for non-living things. The artifact de®cit was entirely due to her relatively poor performance
for distinctive properties of non-living things. We
return to the issue of shared versus distinctive properties after presenting the data for the following experiment.
3.3. Experiment 3: semantic priming
As a further test of ES's semantic representations of
concepts in the living and non-living domains, we carried out an on-line semantic priming study. It has been
frequently shown that prior presentation of a semantically related word can facilitate a reaction time response to a target word, compared to a baseline
condition in which it is preceded by an unrelated word
[44]. Any facilitation from prime to target relies on
semantic information for both words being activated,
although it does not necessarily mean that the representations for both words are completely intact [41].
We compared ES's ability to show a priming e€ect for
words in the living and non-living domains. If the
semantic representations of living things are better preserved, then we expect to see greater facilitation when
the primes are living things than non-living things. We
also compared a range of di€erent target types to see
whether there were particular kinds of semantic relation that were more or less preserved for each category. The motivation for the priming experiment was
71
to see whether there were any di€erences between ES's
semantic knowledge when accessed via controlled processes, as in the naming and property veri®cation
tasks, and when it was probed in a more automatic,
implicit way. The combination of these two types of
task is valuable in further determining the nature of
the de®cit.
3.3.1. Method
The prime words were 24 living things and 24 nonliving things, matched for word familiarity (living,
mean=4.98,
SD=0.81;
non-living
mean=5.1,
SD=0.73: Coltheart, 1981 and ratings collected at the
Centre for Speech and Language, Birkbeck). The
primes were also matched for concreteness and word
length. Age of acquisition [39] was also similar for living and non-living primes (mean of 48.3 vs 51.8,
t(1,37)=0.39, P > 0.5). Each prime was paired with
four di€erent target words, one of each of the following types; superordinate (e.g. fox-animal ), category coordinate (e.g. fox-dog ), a perceptual property (e.g. foxred ) and a non-perceptual property that could loosely
be de®ned as functional (e.g. fox-sly ). The property
targets were selected from a pre-test in which subjects
listed the properties of the prime words, and the production frequency, or percentage of subjects listing the
property, was matched, as was familiarity, word frequency, length and semantic relatedness for all target
conditions as closely as possible. For further details of
the materials, and a listing of the items, see Moss,
Tyler and Jennings [42]. Each target was presented following the related prime, or following an unrelated
word to serve as a baseline. The unrelated words were
matched to the primes in length and familiarity. The
targets in di€erent conditions were rotated over eight
counterbalanced experimental lists, so that repetition
within a single test list was minimised. Unrelated
word-word ®ller pairs were added to reduce the proportion of related items to 33%. Because subjects were
required to make a lexical decision to the target words,
it was also necessary to add unrelated word-non-word
®ller pairs (e.g. table-hiction ), such that on half the
trials the correct response was yes, and on the other
half it was no.
All materials were recorded by a female native
speaker of British English. They were then digitised
onto computer and the acoustic onsets and o€sets
marked with a speech editing system. The experiment
was run under computer control. The prime word was
played out over headphones. At an interval of 200 ms
from the prime o€set, the target was played out. A
timer started at the beginning of the target and was
stopped by the subject pressing a button marked yes
or no to indicate their lexical decision, and response
latencies were recorded. There was an interval of 3 sec
before the next trial.
F(1,124)=3.32, P = 0.07
Degrees of freedom change over time as more items are removed from the analysis due to lexical decision errors.
F<1
Priming Liv/Non-liv
a
F(1,138)=139, P < 0.001
F<1
F<1
F(1,115)=25, P < 0.001
F<1
1288
1357
69
5
F(1,124)=15, P < 0.001
1160
1274
114
9
964
1156
192
17
F(1,110)=108, P < 0.001
865
1111
247
22
a
F(1,162)=153, P < 0.001
645
694
49
7
F1(1,5)=40.5, P < 0.01
F2(1,168)=138, P < 0.001
F1(1,5)=4.8, P = 0.08
F2(1,168)=2.9, P = 0.08
854
1070
216
20
1199
1369
170
12
1064
1185
121
10
869
1064
195
18
807
1014
207
21
808
1034
226
22
t4
t3
t2
t1
ES
700
758
58
8
Living
Related RT
Baseline RT
Priming RT
Priming %
Non-living
Related RT
Baseline RT
Priming RT
Priming %
Priming
11
In general, ES was able to do the task quite well, with up to 15±
20% data being lost due to lexical decision errors or outlying reaction times in each condition in each test session. This re¯ects a high
level of performance for patients with progressive language disorders,
who usually ®nd this task very dicult. Error data were generally
consistent with priming data, with fewer errors on related than unrelated trials. At the last time slice, the di€erence between living things
and artifacts found for the reaction times was mirrored in the error
data, with fewer errors in the related than unrelated condition for
living things (4.5 vs 9%) but no di€erence for artifacts (6.8% for related and unrelated). These small di€erences do not reach statistical
signi®cance, but illustrate that the pattern reported for the reaction
time data was not undermined by accuracy e€ects in the opposite
direction.
Controls Mean
3.3.2. Results
A group of six elderly unimpaired subjects were
tested as the control group (mean age 66 years, range
63±70 years). As shown in Table 3, control subjects
showed signi®cant priming overall, F1(1,5)=40.5,
P < 0.01; F2(1,168)=138, P < 0.001. There was a
slight tendency towards more facilitation for living
than non-living primes (58 ms and 43 ms, respectively;
F1(1,5)=4.8, P = 0.08; F2(1,168)=2.9, P = 0.08).
Priming was however, reliable for both living and nonliving things when analysed separately (F1(1,5)=33.9,
P < 0.005;
F2(1,84)=71,
P < 0.001
and
F1(1,5)=43.4, P < 0.005; F(1,84)=69.8, P < 0.001,
respectively). For further details of the results for this
control group see Moss et al. [42].
We tested ES on the semantic priming experiment at
®ve time slices from August 1994 to December 1996.
In each time slice, the experiment was split over two to
four days to avoid repetition of items and fatigue. As
we have found with many patients, ES found the lexical decision task dicult when she had to make a response to non-words as well as real words, and
therefore she did a go/no-go version in which only a
`yes' response was made to real words.11 Values above
or below two standard deviations of the mean were
replaced with the cut-o€ value. In the ®rst test session,
ES's reaction times were around 900±1000 msÐonly a
little longer than the control range (598±827 ms).
These increased gradually over the years, until they
were averaging 1300 ms at the last testing session.
In the ®rst four time slices, ES showed reliable and
equal priming e€ects for all target types. In each case;
there was a signi®cant overall priming e€ect, with no
interaction between the amount of priming and the living/non-living variable or between amount of priming
and the target type (superordinate/co-ordinate/perceptual/functional). These priming e€ects, along with the
results of the overall analyses of variance are shown in
Table 3 and Fig. 5. Since there were no interactions
with the type of target, results have been collapsed
over this variable to show only the living/non-living
contrast. Priming e€ects (that is, the di€erence between
t5
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
Table 3
Results for ES and the control group in the semantic priming task
72
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
73
Fig. 5. Semantic priming (Unrelated-related di€erence) for ES between August, 1994 (t1) and December, 1996 (t5).
the related condition and the unrelated baseline) are
shown as percentages of the baseline, as well as raw
reaction time di€erences, to account for the fact that
ES's overall reaction times increased over the testing
sessions.
At the last testing session in December 1996, ES
started to show a di€erent pattern of priming. For the
living things primes, there was still robust priming of
the related targets (170 ms). However, the priming for
non-living things was much reduced (69 ms), leading
to a marginally signi®cant priming by category interaction, F(1,124)=3.32, P = 0.07. Priming was highly
signi®cant for the living things, F(1,66)=16.7,
P < 0.001, but was not signi®cant for non-living
things, F(58)=1.7, P > 0.1.
To examine the source of this reduced priming, we
looked at the breakdown of the priming e€ects for
each target type, and found that there was signi®cantly
greater priming for taxonomic relations (co-ordinate
and superordinate: 177 ms) than property relations
(perceptual and functional: 46 ms, F(1,124)=5.21,
P < 0.05). This was true for both living and non-living
things, but priming overall was smaller for the nonliving things. The control group did not show this
di€erence with equal priming for taxonomic and
property relations (F1(1,5)=5.8, P = 0.06; F2 < 1).
Although there was a slight tendency over the group
for more priming for taxonomic than property relations, as revealed by the marginal e€ect in the bysubjects analysis, separate ANOVAs for each control
subject showed that none of them individually showed
the signi®cant priming by relation type e€ect that we
found for ES (P > 0.1 in all cases).
In contrast, ES showed no di€erence in priming for
the functional (26 ms) and perceptual properties (10
ms) of non-living things, con®rming our ®nding from
the property veri®cation test that ES's de®cit for
artifacts is not associated with speci®c damage to
functional information.
3.3.3. Summary of priming results
ES shows gradually less priming over the course of
time, but the e€ects are identical for living and nonliving things up until the last testing session, when
priming for non-living things drops o€ more steeply,
so producing a category by priming interaction. We
found no evidence of a selective problem with functional semantic properties, but there was signi®cantly
less priming for relations relying on speci®c semantic
properties than on taxonomic connections such as
between a category member and its superordinate, or
between two members of the same category. The
greater amount of priming for taxonomic relations
than property relations at the last time slice is consistent with the prediction of the Durrant-Peat®eld et al.
[14] model, that shared properties will be better preserved at severe levels of lesioning (especially for living
things), as we can assume that priming of co-ordinates
and superordinates is supported by the properties
shared by the prime and target (e.g. the properties
74
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
Table 4
Results for ES and control subjects in the de®nition generation task
Mean number of properties
Controls
ES
Mean
Range
T1
T3
T4
Living
Non-living
ES's mean number of properties as a proportion of control mean
Living
Non-living
8.96
6.46
5.1±12.3
3.8±7.6
2.8
2.1
2.1
0.6
11
0.4
0.31
0.32
0.24
0.08
shared by fox and dog or fox and animal ), while priming of perceptual and functional properties requires
more distinctive information to be intact (e.g. that a
fox is red or sly ). As mentioned in the previous section, there was no signi®cant advantage for shared
properties in the property veri®cation task. It may be
that the speeded, automatic nature of the priming task
makes it more sensitive to the di€erence between
shared and distinctive information, than the property
veri®cation task, or that the manipulation of sharedness was more successful.
scores for ES at the three time slices between June,
1994 and March, 1996.
As shown in Table 4, ES gave fewer properties than
control subjects in all testing sessions, but the pattern
of performance over categories changes over time. She
gave similar numbers of properties for living and nonliving things at the ®rst testing session (t(1,18)=1.54,
P > 0.1), but then the amount of information for nonliving things declined steeply over the following two
sessions, such that there are signi®cantly fewer properties given than for living things (t(1,18)=4.23,
P < 0.001 and t(1,18)=1.82, P = 0.08, respectively).
However, the paucity of information for non-living
things must be considered in the context of the control
results, which indicate that they too were able to generate signi®cantly fewer properties for non-living than
living things (means of 6.46 vs 8.96 properties, respectively; t(1,18)=4.15, P < 0.001). To evaluate the size of
the category di€erence for ES against the normal
e€ect, we re-calculated the number of properties that
ES gave for each item as a proportion of the control
mean for that item. These proportional scores are
given in the second part of Table 4 and in Fig. 6.
Comparing living and non-living categories, the result
was the same as for the raw scores. ES's proportional
scores were the same for living and non-living things
at the ®rst time slice (t(1,18)=0.23, P > 0.1), but the
score was signi®cantly lower for artifacts at the second
test session (t(1,18)=3.18, P < 0.01). The score was
still lower for artifacts at the third test session,
although the di€erence was no longer signi®cant
(t(1,18)=1.71, P > 0.1). When baseline di€erences are
taken into account, ES is still giving less information
for artifacts than living things, apart from at the ®rst
test session.
The materials in the de®nition task were matched
for familiarity, but living things had a lower mean age
of acquisition. It is possible that ES's apparent impairment for artifacts is in fact reducible to an age of acquisition e€ect. To check this, we entered ES's
proportional scores into a regression analysis including
age of acquisition for each item. Age of acquisition
was not a signi®cant predictor of performance at any
of the testing sessions, both with and without famili-
3.4. Experiment 4: de®nitions
Over the ®ve testing sessions we asked ES to give
verbal de®nitions of a large number of words. The
content of such de®nitions and the way that they
change over time can provide a rich source of data
about the kinds of information that someone is able to
retrieve for words in di€erent categories.
3.4.1. Method
The experimenter read each word out to ES and
asked her to explain what it meant as fully as possible.
No structured probes for particular kinds of information were given. Responses were recorded and later
transcribed from tape. From the overall set of de®nitions, we present analyses for a subset of 10 living
things (all animate) and 10 artifacts that are closely
matched for familiarity, as described in an earlier
study [42]. The mean object familiarity [49] was 2.5
and 2.4 for living things and artifacts, while the mean
word familiarity [38] was 2.2 and 2.1, respectively.
Although closely matched on familiarity these items
were not matched for age of acquisition, and is it considerably higher for the non-living things (living
mean=48.7, non-living, mean=68.7). Six age-matched
controls were also tested (mean age 65 years).
3.4.2. Results
De®nitions were analysed by computing the total
number of correct properties given for each word. The
mean and range for controls in the living and non-living conditions are given in Table 4, alongside the
0.13
0.05
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
75
Fig. 6. Number of correct properties given by ES as a proportion of the control mean in the de®nition task in June, 1994 (t1), July, 1995 (t3)
and March, 1996 (t4).
arity variables added into the model (P > 0.1 in all
cases). However, living/non-living category was a signi®cant predictor at the second test session (t=3.053,
P < 0.01). As we would expect, there was no signi®cant e€ect at the ®rst time slice where ES's de®nition
scores for living and non-living things were similar,
and the e€ect at the last test session also failed to
reach signi®cance.
We conclude therefore that ES was showing a genuine category-speci®c de®cit for artifacts in the de®nition task, at least on the second testing session. By
the third test session, she was giving very little information for any of the items, and the artifact de®cit
was only marginally signi®cant. Some examples of
ES's de®nitions are given in Appendix 1. These
examples illustrate how ES's de®nitions of living things
are often quite consistent over the three testing sessions, while those for artifacts start out being quite
detailed at the ®rst time slice, but many properties
then drop out at subsequent points.
3.5. Experiment 5: naming to description
Several other tasks were carried out with ES, which
show a pattern consistent with the emergence of an
artifact de®cit. For example, in the naming to descrip-
tion task, ES was asked to provide the name of an
item, given a verbal de®nition. The description always
gave the superordinate category of the item, and then
a set of two to four properties. For half the items the
properties were visual (e.g. Aeroplane: A vehicle that
has wings and a tail and many seats inside ) and for the
other half the properties were non-visual (e.g. Cat: An
animal that likes to catch mice and drink milk ). There
were 30 trials in the living and 30 in the non-living category. A group of six elderly control subjects found
the living things slightly more dicult (mean 88.5%
correct) than the artifacts (91% correct). See Moss et
al. [43] for further details of this task. This task was
not available until the third testing session for ES, and
she was tested at this time and the two subsequent sessions. As shown in Fig. 7, on the ®rst two occasions
she found the artifact items more dicult (23% and
13% correct) than the living things (37% and 20%
correct). By the last testing session she was essentially
at ¯oor on this task. However, the di€erences between
the non-living and non-living conditions were not signi®cant (w 2 < 1 in all cases). As in the property veri®cation and priming tasks, ES did not show any
di€erence in accuracy for visual and functional semantic properties.
Although ES did not show a signi®cant advantage
76
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
Fig. 7. Percentage of correct responses for ES in the naming to description task between July, 1995 (t3) and November, 1996 (t5).
for living things over artifacts in this task, the pattern
is consistent with the emergence of an artifact de®cit,
when taken together with the data from the previous
four experiments.
4. General discussion
The series of experiments reported above all converge on the conclusion that ES has a progressively
worsening semantic de®cit that is more severe for the
broad domain of artifacts relative to living things.12
Because the same pattern was observed over a range
of tasks, we conclude that this is a central semantic
de®cit, not restricted to any speci®c modality of input
or output. We now consider these data in the light of
the issues raised in the introduction.
12
ES did not show any obvious dissociation among individual categories within domains, so we continue to discuss her de®cit at the
domain level. Most of the tests included fruit and vegetables as well
as animals in the living category, but there were too few appropriately matched items to carry out meaningful comparisons. In those
tests where fruit and vegetables were not included (de®nitions, naming to description), the pattern of results were not di€erent.
4.1. Domain-speci®c account
The domain-speci®c account suggests that there are
speci®c neural subsystems responsible for the representation of concepts in di€erent broad domains such as
animals, plants and artifacts. This kind of account predicts that there will be strong associations between the
regions of the brain that have been damaged and the
domains of knowledge that are more or less impaired.
As discussed in the introduction, there is con¯icting
evidence on this issue from cases studies of neuropsychological patients; it has been suggested that bilateral
temporal lobe lesions give rise to de®cits for living
things, and left fronto-parietal lesions are associated
with de®cits for artifacts, although several cases have
been reported that seem to be inconsistent with these
claims. The data for ES can now be added to this list,
since she shows a category-speci®c de®cit for artifacts
in the context of general cerebral atrophy. This pattern
of atrophy makes it implausible that there has been
selective damage to a speci®c neural system dedicated
to the representation of artifact concepts.
4.2. Familiarity and other `nuisance variables'
Several authors have suggested that many reported
cases of de®cits for living things may be accounted for
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
in terms of the typically lower familiarity of those
items. However, this account cannot accommodate the
current ®nding of the reverse pattern; poorer performance for artifacts than living things. The same is true
of other potential nuisance variables such as visual
complexity. In the picture naming task, category e€ects
remained signi®cant when they were entered into a
logistic regression analysis alongside familiarity and
several other potential confounding variables such as
visual complexity, age of acquisition concreteness and
word length.13 Familiarity was found to have no independent e€ect on ES's naming performance in the
main analysis, although a weaker e€ect did emerge
when the age of acquisition variable was removed.
Although visual complexity, age of acquisition and
length did have e€ects, these did not fully account for
the results and the category e€ect was still signi®cant.
In all of the other tasks reported, familiarity and the
other potential nuisance variables were closely matched
across living and non-living things, and so we can conclude that the de®cit for artifacts relative to living
things was a genuine category e€ect and did not arise
as a result of other confounding factors. It is, in fact,
surprising that familiarity had so little e€ect on ES's
performance, given that familiarity has been found to
be a major predictor of performance for many patients
with progressive semantic disorders [19,33].
The strongest predictor of naming accuracy for ES
was objective age of acquisition; she was more likely
to name an early acquired than a late acquired word.
Several studies have indicated that age of acquisition is
an important determinant of naming performance for
normal subjects [40] and it also has an e€ect for many
patients with semantic impairments (for example, all
patients in the Lambon Ralph, Graham and Ellis
study [33] showed an e€ect of age of acquisition in addition to that of familiarity). However, it cannot be
claimed that ES's de®cit for artifacts reduces to an
age-of acquisition e€ect, since there were independent
e€ects of category and age of acquisition in the regression analysis. Moreover, in the property veri®ca-
13
We did not control for the variable of visual similarity among
category members (structural similarity, 31; degree of homomorphy,
60). However, this has been demonstrated to be greater for living
things than artifacts, so any e€ect of this variable would predict an
e€ect in the direction of an impairment for living things, not for artifacts. Moreover, it should have relatively little in¯uence on tasks
that do not involve the recognition of objects or pictures.
14
It may be that age of acquisition e€ects will be the same in a ®rst
and second language as long as both languages are learned as young
child within some `critical period' for forming phonological representations, but that this will not necessarily be the case for a second
language learned as an adult (C. Morrison, personal communication).
77
tion and priming experiments, materials were closely
matched for age of acquisition and the de®cit for artifacts was still found. Indeed, it is unclear that we
would expect to ®nd age of acquisition e€ects in tasks
which do not involve word production, since it is generally held to be a factor that a€ects output at the
phonological (lexeme) level [40]. We do not have an
explanation as to why age of acquisition and not familiarity should have in¯uenced ES's naming. Given that
ES learned English as a second language as a child,
the fact that age of acquisition predicts her naming accuracy in English is perhaps more surprising, and may
have implications for accounts of how the age of acquisition e€ect comes about; it suggests that what matters is the order of acquisition of words, not the
speci®c developmental state of the learner when a
word is acquired.14
4.3. Perceptual/functional hypothesis
Warrington and colleagues' hypothesis that living
things are particularly dependent on visual semantic
knowledge and that artifacts depend on functional information has been an in¯uential one [65±67]. Until
recently, none of the previous patients reported to
have de®cits for artifacts had been tested to determine
whether this is associated with a greater loss of functional than visual information, as would clearly be predicted by this account. Patient IW, reported by
Lambon Ralph et al. [34] showed the opposite of the
predicted pattern, with a de®cit for artifacts accompanied by greater problems with visual than nonvisual information. We examined this question for ES
by comparing perceptual and functional information
in the semantic priming, property veri®cation and
naming to description tasks. In all cases, ES's performance was no worse for functional properties. This lack
of a speci®c impairment for functional properties adds
weight to the several recent demonstrations of patients
with de®cits for living things who have no speci®c diculty with visual information, and suggests that category-speci®c de®cits are not reducible to greater
damage to either visual or functional semantic information. Although concepts may vary in their weighting towards di€erent sensory and motor channels [57],
it cannot be the case that a lesion to a store of functional or visual information per se is an adequate
account of category-speci®c de®cits. Nevertheless, it
remains plausible that di€erential weighting of properties will play a part in a more complex account, such
as the distributed models discussed in the following
section.
4.4. Distributed accounts and the severity e€ect
As mentioned above, ES had widespread cerebral
78
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
atrophy rather than a focal lesion. This is consistent
with an account in which semantic memory has been
damaged in a global and random fashion, rather than
in such a way that a certain localised category of information could be selectively a€ected. Two models that
can account for the emergence of category-speci®c de®cits as a result of global damage are that of Devlin et
al. [11] and Durrant-Peat®eld et al, [14]. Both models
suggest that the patterns of intercorrelation among
semantic properties within concepts lead to di€erent
patterns of impairment when the system is damaged.
Durrant-Peat®eld et al. [14] specify the nature of intercorrelated properties; for living things shared biological functions and the perceptual properties that
support them are most strongly correlated, while for
artifacts speci®c forms and functions are correlated.
These speci®c claims are not made in the Devlin et al.
[11] model, where living things simply have a greater
number of intercorrelated properties overall.
The most obvious di€erence in the behaviour of the
two models is that Devlin et al. [11] found a greater
de®cit for artifacts at the most mild levels of lesioning,
then giving way to a living things de®cit with increased
severity, while Durrant-Peat®eld et al.'s [14] simulation
showed the reverse pattern. ES's pattern of results is
clearly more consistent with the Durrant-Peat®eld et
al. [14] account. In all our tasks, the artifact de®cit
emerged over time, as the overall impairment became
more severe. In the naming task, the signi®cant artifact
de®cit was preceded by a signi®cant de®cit for living
things, giving rise to a reliable category by time interaction in the regression analysis. In the other tasks, ES
did not show the initial living things de®cit, but a signi®cant (in the case of priming, property veri®cation
and de®nition tasks) de®cit for artifacts did emerge in
the later stages of the disease. It is possible that the
greater sensitivity of the naming task to the early living
things de®cit is due to the picture recognition aspects
of that task which were not present in the other tasks.
Pictures of living things (in the Snodgrass and
Vanderwart, [50] set) tend to be more visually complex
and confusable, and so this could lead to a disadvantage for living things that shows up until the
semantic de®cit for artifacts becomes severe enough to
outweigh the e€ect of these variables. This is plausible
given that visual complexity was one of the signi®cant
predictors of ES's naming accuracy in the regression
analysis.
4.5. Shared and distinctive properties
The explanation for ES's greater de®cit for artifact
concepts according to the Durrant-Peat®eld et al. [14]
model is that when there is extensive generalised
damage to semantic memory, the best preserved type
of semantic information will be the shared properties
of living things. These properties are well learned
because they occur for many di€erent concepts, and
they are densely intercorrelated (e.g. has eyes, has legs,
can see, can move ). Both of these factors contribute
towards the robustness of these properties in the face
of damage. In the case of artifacts, the distinctive
properties are correlated in form-function relations
such as can cut-has a serrated edge, and this gives them
an initial advantage over the distinctive properties of
living things. But these distinctive properties, by de®nition, do not occur for many concepts. When damage
becomes severe these properties will be degraded.
When the system can rely only on shared properties,
artifacts are at a disadvantage, because their shared
properties are fewer in number and less densely intercorrelated than those of living things.
These assumptions lead to the prediction that a
patient like ES, who has a de®cit for artifacts, will
show greater preservation of shared than distinctive
properties, especially for living things. The evidence
with respect to this prediction is rather mixed. In the
priming task, ES showed greater priming for relations
depending on shared than distinctive information at
the last time slice. In the property veri®cation task, ES
was also slightly more accurate on the shared (69%)
than the distinctive (63%) properties, although this
was not a signi®cant di€erence. However, the data in
Table 2 reveal that this was largely due to ES's poor
performance on the distinctive properties of artifacts.
Contrary to our prediction, she was not showing signi®cantly better performance on the shared properties
of living things relative to all the other conditions. It is
possible that the lack of e€ect in this task was due to
the fact that the shared/distinctive manipulation in
these materials was not suciently strong. This was
because the property veri®cation test was constructed
at a stage in the development of our theoretical
account, before we had identi®ed the biological functional properties of living things and their correlated
perceptual attributes as being especially important.
Therefore the shared condition for living things
included properties that are true of many category
members but are not biological properties, and so may
not be so densely correlated (e.g. lives in a zoo ).
Moreover, we did not have a measure of the degree of
sharedness to ensure that this was matched for living
things and artifacts. We have recently developed more
relevant property tests, but not in time to test ES at a
point when she could still understand a veri®cation
task.
Some independent support for the prediction that
ES will show greater preservation for the shared than
distinctive properties of living things, comes from a
separate priming experiment. In this study all the
primes were living things and the targets were either
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
distinctive properties (e.g. camel-humps ) or shared
properties (camel-legs ). The degree of distinctiveness
was determined by a pre-test in which subjects rated
how many items in a category had each property. For
control subjects we found that priming for distinctive
properties emerged earlier in the duration of the prime
and was more robust than that for general properties.
We assume that this e€ect is due to the greater salience
and cue validity of distinctive properties in the normal
system. ES (tested in March 1996) showed the reverse
pattern, with signi®cant priming only for the general
properties (94 ms, F(1,36)=4.9, P < 0.05) but no
priming for distinctive properties (31 ms, F < 1).
Although this di€erence did not give rise to a signi®cant interaction between feature type and priming, the
fact that it is in the opposite direction to the normal
pattern suggests that for ES, there has been a great
deal of erosion for distinctive properties, while the
shared properties of living things remain intact, supporting greater priming than they would in the normal
semantic system.
5. Conclusion
We have shown that ES develops a signi®cant de®cit
for artifacts relative to living things in the course of a
progressive dementia that involves an important
semantic memory component. Previous cases of progressive semantic decline have usually shown no category e€ectsÐas in most reported cases of semantic
dementiaÐor a disadvantage for living things, which
has been reported for a few semantic dementia patients
and for some patients with Alzheimer's disease. One
semantic dementia patient with a greater de®cit for
artifacts than living things has also been reported
recently [34].
The current case adds to the short list of patients
with artifact de®cits reported in the literature
[28,34,47,65,66]. We have also been able to investigate
the nature of preserved and impaired knowledge for
living and non-living categories in a way that has not
previously been reported, and found that there was no
di€erence between ES's knowledge of perceptual and
functional information, but there was some evidence
that shared information was intact relative to distinctive information. Finally we have demonstrated the
emergence of a category-speci®c de®cit as a function
of severity, and a cross over from a de®cit for living
things to artifact in the naming task. This is consistent
with the predictions of the computational model of
Durrant-Peat®eld [14] concerning the progression of
semantic breakdown as a result of global, random
damage to a distributed semantic memory system.
However, it is somewhat unclear at this stage whether
the data fully support the predictions of this model
79
concerning the pattern of preservation for shared and
distinctive properties. Further investigation of this
issue is underway, involving more sophisticated computational simulations and the development of new
tests of knowledge of shared and distinctive properties
for use with future patients.
Acknowledgements
We are very grateful to ES for her generous
participation in these studies over the years. We would
also like to thank Elaine Bunn, Julie Morris and
Kate Voice for their help with testing and analyses
and Joe Devlin for helpful discussions of this work
Finally, we are grateful to Matt Lambon Ralph and
Eleanor Sa€ran for their valuable comments on the
earlier version of the paper. This research was
supported by an MRC programme grant to Lorraine
K. Tyler and William Marslen-Wilson and a Wellcome
Trust Career Development Research Fellowship to
Helen Moss.
Appendix A
Examples of ES's de®nitions of living and non-living
things at three time slices from June 1994 to March
1996
Mouse
T1 A mouse are dirty little things and er and then if
you get them in the house it is hard to get them out.
They are just dirty and they are €f. They are just dirty
and crowds of little ones, lots of them.
T2 It's a, it's a small, a small little thing and and
and the the the, you know and it's a dirty little
(laughs) don't like them, I don't like them.
T3 A mou- yeah, they ge, they get in into the house
o€, and they're dirty things.
Fox
T1 FoxÐyou do not see many of them around.
They go and take away chickens and that and take
them away.
T2 Er, they, they come down and and and they'll
take away chickens and some things like that.
T3 Yeah, er er they would, they would take away
the hens and you know, yeah.
Peacock
T1 A peacock, er, a peacock, a big dog, a big bird,
nice feathers one, they can run very quick too.
80
H.E. Moss, L.K. Tyler / Neuropsychologia 38 (2000) 60±82
T2 Yeah, it's a big one, big one, in the back there,
they go on, the feathers, all the way up, yeah.
T3 Yeah, yeah the big one, yeah and the big ones
around the back (gestures).
Swan
T1 A swan, oh they are nice, some are white and
some are grey. See them in big ponds.
T3 A sw- what? A swan, yeah, they're white and
they're in, or some, some of them are grey, some of
them and they're always in the water.
T4 A what? A swan, yeah, yeah, well it goes, it
goes, it goes in, in the water, and he can, and he can,
and they come out.
Bike
T1 Bike, yeah, that's for riding, lots of boys going
to school ride bikes.
T2 Bike, yeah, you go on it.
T3 A what? A bike? Yeah, well you go on them, but
that's about all, yeah, you can go on but yeah,
quicker, yeah.
Harp
T1 A harp, well, it's just music, I don't know much
about it. Strings.
T2 Harp? Yeah. I don't, I don't know I don't know.
T3 A what? A harp yeah, for er, oh I can't, I know
what they would be doing but I can't.
Couch/settee
T1 A couch you sit on, or if you are sleepy you can
lie on it for an hour or so. Two or three people can sit
on it.
T2 Sit on, yeah.
T3 A what? No, ah, to to sit down.
Hammer
T1 A hammer, well for hammering nails, for breaking stones and things like that.
T3 hammer, yeah, to, doing somethings, like like
doing these things would they need it.
T4 The hammer, the breaks o€ . . . yeah.
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