Category specific semantic loss in dementia of ... - CiteSeerX

Brain (1998), 121, 633–646

Category specific semantic loss in dementia of Alzheimer’s type Functional–anatomical correlations from cross-sectional analyses Peter Garrard,1 Karalyn Patterson,2 Peter C. Watson2 and John R. Hodges1,2 1University 2MRC

Neurology Unit, Addenbrooke’s Hospital and Applied Psychology Unit, Cambridge, UK

Correspondence to: Professor John R. Hodges, MRC Applied Psychology Unit, 15 Chaucer Rd, Cambridge CB2 2QQ, UK

Summary In the context of focal brain injury, selective loss of semantic knowledge in the domain of either natural kinds or artefacts is usually considered to reflect the differential importance of temporal and frontoparietal regions to the representations of perceptual and functional attributes, respectively. It is harder to account for as a feature of a more diffuse process, and previous cross-sectional analyses of patients with dementia of Alzheimer’s type (DAT) have differed over whether category effects occur. In our series of 58 patients with probable DAT, we demonstrated a significant group advantage for artefacts, and explored possible reasons for the inconsistency of this finding in other studies. A multiple single-case strategy revealed not only individuals with consistent advantages for

artefacts but also individuals with consistent advantages for natural kinds. By ranking the individuals according to measures of naming performance and global intellectual ability, we showed that the strength of the group advantage for artefacts was dependent on the former but not the latter variable. The findings are discussed in the context of two competing theories of semantic breakdown in DAT. One differentiates between domains of knowledge in terms of the structure of semantic representations within a single distributed network; the other emphasizes the importance of different brain regions in the category distinction. We conclude that our findings are in keeping with the predictions of the latter hypothesis.

Keywords: category specificity; dementia of Alzheimer’s type; semantic memory Abbreviatons: DAT 5 dementia of the Alzheimer’s type; MMSE 5 Mini-Mental State Examination

Introduction It is now well established that brain-damaged individuals may show a loss or breakdown of specific categories of semantic knowledge (Patterson and Hodges, 1995). The most frequently documented dissociation is between the broad classes of natural kinds and artefacts. The majority of reported cases have shown a selective loss of knowledge in the domain of natural kinds (Warrington and Shallice, 1984; Hart et al., 1985; Basso et al., 1988; McCarthy and Warrington, 1988; Pietrini et al., 1988; Sartori and Job, 1988; Silveri and Gainotti, 1988; Farah et al., 1989; Hillis and Caramazza, 1991; Silveri et al., 1991; Hart and Gordon, 1992; Sartori et al., 1993; Sheridan and Humphreys, 1993) but the fact that the reverse dissociation has also been reported (Warrington and McCarthy, 1983, 1987; Sacchett and © Oxford University Press 1998

Humphreys, 1992) probably rules out an artefactual explanation (Shallice, 1988). The basis of this finding remains controversial, but it is now widely accepted that the living/ man-made dichotomy captures a fundamental difference in the nature of the representations underlying different semantic categories, rather than simply reflecting the presence of two distinct knowledge systems; knowledge about one class of objects (dominated by natural kinds) is thought to be encoded principally in terms of perceptual features (size, shape, colour, etc.), while functional attributes are more salient for another class of objects (dominated by artefacts). Thus, damage to the neural systems critical for the representation of perceptual attributes will result in disproportionate loss of knowledge of natural kinds. This explanation, first advanced by Warrington

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(1982), accounts for some apparently anomalous findings in the experimental literature, such as the fact that parts of living things (i.e. body parts) tend to cluster with artefacts, while certain inanimate subgroups (fabrics, precious stones and musical instruments) segregate with natural kinds. It has also received support from the recent application of computational neural network models of semantic memory (Farah and McClelland, 1991). The neuroanatomical substrate of this distinction also remains a subject of debate. An advantage for artefacts is typically associated with an aetiology of Herpes simplex virus encephalitis (which predominantly affects temporolimbic structures) whilst the opposite pattern more often follows damage to frontoparietal regions (Gainotti, 1990). This combination suggests that the two patterns might correspond to a broad anatomical divide between two streams of post-striate visual processing, as postulated by Mishkin et al. (1983) on the basis of behavioural experiments in selectively lesioned Rhesus monkeys. According to this proposal, a ventral pathway, incorporating the anterior-inferior portion of the temporal lobes, is essential for object recognition while a dorsal pathway, involving inferior parietal regions, subserves object localization. More recently, PET activation studies on cognitively normal volunteers have added weight to this idea (Mummery et al., 1996) by demonstrating distinct regions of brain activation during semantic tasks based on categories from each domain. A different, but related dissociation has been documented by Goodale et al. (1991): a patient with limited occipital cortical damage secondary to carbon monoxide intoxication was unable to make visual judgements about line orientation but could perform highly accurate visually guided hand movements in response to the same stimuli. The richness of corticocortical interconnections in the inferior parietal lobes has led to the hypothesis that this region serves a supramodal sensory function by which visuospatial, tactile and kinaesthetic information is integrated, and would therefore be a likely substrate for the representation of functional knowledge. More directly perceptual features, such as colour and shape, are believed to be separately represented in the temporal lobes (Warrington and McCarthy, 1987). It is thus a plausible extrapolation from both neuropsychological and anatomical data that different aspects of object knowledge, supported by separate brain regions, underlie the categorical fractionation of semantic knowledge. Although some degree of semantic impairment is commonly seen in the early stages of dementia of the Alzheimer’s type (DAT) (Bayles and Tomoeda, 1983; Martin and Fedio, 1983; Chertkow and Bub, 1990; Hodges et al., 1990; Nebes and Brady, 1990; Hodges et al., 1991; Hodges and Patterson, 1995; Patterson and Hodges, 1995; Gonnerman et al., 1997) it is not yet clear whether this deficit is characterized by category specificity. Some cross-sectional studies have demonstrated no overall category specificity (Hodges et al., 1992b; Gonnerman et al., 1997); others have documented a degree of selective loss of knowledge of

natural kinds (Silveri et al., 1991; Montanes et al., 1995) and ascribed this to the predilection of pathological changes for temporal lobe structures in the early stages of DAT. Gonnerman et al. (1997) found no significant category specificity in a group of DAT patients as a whole, but the application of a multiple single-case approach identified not only individuals with consistent advantages for artefacts but also individuals with consistent advantages for natural kinds. This finding sits uneasily with the notion that the disturbance of semantic knowledge in early DAT reflects a predominance of temporal lobe pathology, and points instead either to a greater heterogeneity in the spectrum of pathological loci in early DAT, or to a revision of our notion of how categories of knowledge may be selectively disrupted. Gonnerman et al. (1997) rejected the explanation based on the spread of pathology to different specialized anatomical regions and proposed instead that the cognitive structure of representations in the semantic network will make certain categories of knowledge more vulnerable to the initial ravages of a diffuse neurodegenerative disorder. This hypothesis assumes that the semantic impairment in DAT is caused by a diffuse disease process affecting many parts of a distributed network of semantic representations simultaneously and that, by virtue of a difference in their structures, representations of natural kinds and artefacts should disintegrate at different rates. Gonnerman et al. (1997) based their proposal on the following specific premises. (i) Most concept representations contain groups of features that characteristically occur together; these features may therefore be regarded as being ‘intercorrelated’ (Keil, 1987, 1989). (ii) Perceptual features of objects intercorrelate to a greater degree than functional features. (iii) Mental representations of natural kinds are dominated by perceptual features, while functional features contribute more heavily to the representations of artefacts. (iv) Similarly, the distinguishing features unique to a concept (i.e. those which allow it to be differentiated from other exemplars of the same category) tend to be functional features in the case of artefacts and perceptual features in the case of natural kinds. Gonnerman et al. (1997) argued that the larger number of intercorrelated attributes contributing to the conceptual representation of natural kinds will make these less vulnerable in the early stages of DAT. On the other hand, with more severe deterioration of features associated with advanced disease, the collapse of this correlational structure should yield exaggerated deficits for natural kinds. By contrast, according to this hypothesis, semantic representations of artefacts will be equally vulnerable at all stages of the disease, and so deteriorate in a linear fashion. The resulting profile of any given DAT patient over time should, therefore, show an early tendency towards a natural kinds advantage, followed at a later stage by a catastrophic loss of natural kind categories and hence a reversal of the pattern to an advantage for artefacts. A stylized representation of this putative profile is shown in Fig. 1. Clearly, variations in the rate of accumulation of

Category specificity in DAT

Fig. 1 Profile of longitudinal changes in semantic knowledge for artefacts and natural kinds according to the model of Gonnerman et al. (1997). (Reproduced with permission of the authors.)

pathological changes in DAT as well as in the precise structure of each individual’s knowledge representations will render the time course of this process unpredictable, and variations in the duration of disease before diagnosis will result in the profiles of individual patients beginning at different points along the curve. However, three testable predictions about individual profiles do follow from this model. The first is that, in any cross-sectional analysis of a reasonably large-sized group of DAT patients, there will be some individuals who show advantages for one category and others with advantages for the other category. The second is that, on measures of disease severity, patients showing a significant advantage for artefacts will be at a more advanced stage of disease progression than those showing a natural kinds advantage. The third is that, for patients studied longitudinally, a change from a natural kinds to an artefacts advantage may be seen, but not the reverse. By contrast, a more neuroanatomical account of category specificity in DAT is based on the observation that the earliest cortical changes selectively involve the transentorhinal zone of the temporal lobes (Braak and Braak, 1991), thereafter the changes evolve to incorporate the temporal neocortex proper and, typically, only spread to inferior parietal regions still later in the disease. The notion that the temporal region is especially important in the representation of perceptual attributes yields the prediction that the earliest and most predominant pattern will be one of disproportionate loss of knowledge about natural kinds. However, the existence of atypical cases in which other areas of association cortex, including frontoparietal regions, are affected early in the disease (Ross et al., 1996) does allow for the appearance of occasional patients with an advantage for biological kinds. The accumulated data on semantic performance from our large series of DAT patients has allowed us to test some of the predictions made by these two hypotheses.

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mean age 68 years (SD 8.8), mean years of education 11.6 (SD 3.3), mean Mini-Mental State Examination (MMSE) score 19.9 (SD 7.3)], and (ii) 46 normal control subjects [34 females and 12 males, mean age 72.9 years (SD 9), mean years of education 10.42 (SD 2), mean MMSE score 28.9 (SD 1.3)]. Written informed consent had been obtained from all subjects, or the caregivers where appropriate. The study was approved by the Ethics Committee of The Addenbrooke’s Hospital, Cambridge. The DAT group was drawn from an unselected consecutive series of 60 patients who presented to a Memory Disorder Clinic at Addenbrooke’s Hospital in 1991–2, and who were willing to be enrolled into a longitudinal study of semantic memory and related cognitive deficits in DAT. The diagnosis of probable DAT was made according to the criteria developed by the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association, which consist of inclusion and exclusion criteria (McKhann et al., 1984). All patients presented with progressive cognitive impairment, predominantly affecting memory, with a history of between 1 and 4 years. In all cases there has been a decline in performance affecting two or more areas of cognition, as assessed by a wide range of neuropsychological measures. As well as those described in detail below, these included the following standard clinical tests: the MMSE (Folstein et al., 1975); the Dementia Rating Scale (Mattis, 1992); Judgement of Line Orientation (Benton et al., 1983); Complex Figure Test (Lezak, 1983); object matching (unusual views) (Humphreys and Riddoch, 1984); and digit span. Patients with a past history of known or suspected transient cerebral ischaemic event or stroke, alcoholism, head injury or major medical illnesses (e.g. cancer or thyroid dysfunction) were excluded, as were those with major depression. All patients were examined by a senior neurologist (J.R.H.) and by a senior psychiatrist (Dr G. Berrios) at entry to the study. In addition to a clinical assessment, all patients were administered a number of standard psychiatric rating scales, including the Beck Depression Inventory (Beck et al., 1961), to exclude significant psychiatric disorders. All underwent CT or MRI scanning together with the usual battery of screening blood tests to exclude treatable causes of dementia. Also excluded were patients with either semantic dementia or primary progressive non-fluent aphasia as defined in previous studies by our group (Hodges et al., 1992a; Hodges and Patterson, 1996). Normal control subjects were members of the MRC Applied Psychology Unit subject panel, matched with the DAT patients on the basis of age and education level. Subjects with a history of alcoholism, drug abuse, learning disability, neurological or psychiatric illness were excluded, as were subjects with clinically apparent hearing and/or visual handicaps liable to affect their performance.

Methods Subject group

Semantic memory test battery

Data from two groups were used for this study: (i) 58 patients with a diagnosis of probable DAT [31 females and 27 males,

This battery of tests, all employing one consistent set of stimulus items, and designed to assess input to and output

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from central representational knowledge about the same group of items via different sensory modalities, has been described in detail elsewhere (Hodges et al., 1992b). It contains 48 items chosen to represent three categories of natural kinds (12 land animals, six sea creatures and six birds) and three categories of artefacts (12 household items, six vehicles and six musical instruments) matched for category prototypicality and word frequency. The order of item administration is randomized across tests but is consistent across subjects. The items were chosen from the corpus of line drawings by Snodgrass and Vanderwart (1980). The following tests were used for the present analysis. (i) ‘Category fluency’ for each of the six categories, with 1 min allowed per category. (ii) ‘Naming’ of all 48 line drawings without cueing. (iii) ‘Naming in response to verbal description’ (e.g. ‘what do we call the small green animal that leaps around ponds?’, or ‘what do we call a small vehicle with runners used on snow or ice?’) for 24 of the 48 items (four from each of the six categories). (iv) ‘Word–picture matching’ in response to a spoken word using within-category arrays for all 48 items. Subjects are presented with picture arrays consisting of eight items from the same category (e.g. land animals) and asked to point to the item named by the examiner (the original battery used arrays of six pictures, but in the subsequent version we now use arrays of eight, each containing two foils not otherwise included in the test battery). The subject thus views 48 arrays; these consist of only eight different combinations of items (one for each category such as land animals), but for each array the position of the target and foil items is varied. The test sequence is consistent across subjects and is arranged so that each item is followed by one from a different category. Because of the anomalous findings that have been reported when considering the category of musical instruments within the domain of artefacts, scores relating to this group of stimulus items were excluded from the present analysis. The category of water creatures was excluded from the natural kinds set to preserve the numerical balance. Maximum scores for the above tests are therefore 36 for picture naming and word–picture matching (18 per domain), and 16 for naming to description (eight per domain). Category fluency data were available for the four remaining categories (household items, vehicles, land animals and birds).

Analysis 1: overall category specific effects Method To determine whether the patient population exhibited any overall advantage in the direction of either natural kinds or artefacts, the probability of correct identification of each item in the semantic battery at the initial evaluation was calculated for picture naming, naming to description, and word–picture matching. All these tests are assumed to require semantic knowledge, and all contain equal subsets of natural kind and artefact stimuli. Category fluency was examined separately, as there is no defined maximum score.

Results Table 1 presents the mean probabilities of correct identification of natural kind and artefact stimuli by patients and control subjects on each of the three stimulus-based semantic tests. After arcsine transformation of the data [recommended by Howell (1992, p. 315) for data of this kind], a repeated measures ANOVA with two within-item factors (patients versus control subjects and confrontation naming versus naming to description versus word–picture matching) and one between-items factor (natural kinds versus artefacts) was used to analyse these results. Because of the possible importance of concept familiarity to the phenomenon of selective impairment of semantic categories (Funnell and Sheridan, 1992), the familiarity rating (published by Snodgrass and Vanderwart, 1980) of each item was entered as a covariate. Significant main effects of group [F(1,33) 5 61.55, P , 0.001] and test [F(2,66) 5 6.04, P , 0.01] emerged, but there was no significant effect of domain (i.e. natural kinds versus artefacts). There were no significant interactions. Post hoc comparisons of the scores for each test on the natural kind and artefact subsets revealed no significant differences in either subject group (Table 1); the slight numerical artefact advantage in item identification did not differ significantly between the two subject groups [F(1,33) 5 3.15, P 5 0.09]. Mean fluency scores are presented separately in Table 2; they show the expected difference between patients and control subjects [t(102) 5 8.24, P , 0.001], but no difference between the two semantic domains.

Comment The absence of a domain-specific impairment across the whole group is in keeping with the results of Gonnerman et al. (1997) and Hodges et al. (1992b), but it contrasts with the artefacts advantage reported in DAT by both Silveri et al. (1991) and Montanes et al. (1995). Of the possible explanations for this discrepancy, two can be specifically addressed using the present data. (i) The average stage of disease progression of the patients may not be precisely equivalent in all the studies. Gonnerman’s (1997) study population had a mean MMSE score of 19 and Hodges’ a mean MMSE score of 20.7 with a range of 14–26 (both very similar to the mean MMSE of 19.9 in the present sample), while that of the Montanes et al. (1995) patients ranged from 17 to 26, with no mean score quoted. MMSE was not used in the selection of patients for the Silveri et al. (1991) analysis. It is therefore possible that the two pairs of patient populations may have differed significantly on this measure. (ii) The different stimulus sets used in these studies may have introduced unwanted and differing biases. Although both Gonnerman et al. (1997) and Silveri et al. (1991) matched their two sets for item prototypicality, and Silveri matched additionally for frequency, Montanes et al. (1995)

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Table 1 Comparisons of the mean probabilities of correct identification of items in the natural kinds and artefacts subsets, on three tests from the semantic battery Test

Mean P(correct) 6 SD Natural kinds

Artefacts

t Tests

DAT patients (n 5 58) Picture naming Naming to description Word–picture matching

0.75 6 0.22 0.64 6 0.19 0.93 6 0.05

0.79 6 0.15 0.71 6 0.12 0.94 6 0.1

t34 5 0.60 (n.s.) t14 5 0.97 (n.s.) t34 5 0.91 (n.s.)

Control subjects (n 5 46) Picture naming Naming to description Word–picture matching

0.93 6 0.10 0.98 6 0.03 1.00 6 0.02

0.97 6 0.05 0.95 6 0.05 0.99 6 0.01

t34 5 1.60 (n.s.) t14 5 1.08 (n.s.) t34 5 0.59 (n.s.)

n.s. 5 not significant.

Table 2 Comparison of mean fluency scores Group

DAT patients (n 5 58) Control subjects (n 5 46)

Mean fluency 6 SD Natural kinds

Artefacts

t tests (two-tailed)

20.3 6 14.3 39.7 6 9.7

21.2 6 14.0 40.0 6 11.3

t57 5 –0.94 (n.s.) t45 5 –0.18 (n.s.)

n.s. 5 not significant.

matched only for visual complexity; none of these studies controlled for concept familiarity, which may be an important determinant of differential performance for the two conceptual domains (Funnell and Sheridan, 1992). Additional analyses of the present data were performed to examine these possibilities.

Analysis 2: effect of non-semantic variables Method First, to examine whether the absence of a category specific effect in Analysis 1 might have derived from the overall level of disease progression in the population, we divided the group into two equal halves on the basis of MMSE score (median split). The first group (n 5 29) had a mean MMSE score of 25.5 (range 23–30), and the second (n 5 29) a mean MMSE score of 14.31 (range 2–22). The above analyses were repeated using these two subsets of cases. Secondly, to test the hypothesis that a category effect may have been present, but was eliminated by the partialling out of familiarity in our initial analysis, the original analysis was repeated with the concept-familiarity ratings omitted from the statistical model.

Results Table 3 displays the mean probabilities of correct identification of items in the natural kind and artefact subsets for each of the three stimulus-based tests, using data from mild and severe subgroups of patients as defined above. A

two (group) by three (test) by two (domain) ANOVA again revealed significant main effects of group [F(1,33) 5 18.35, P , 0.001] and test [F(2,66) 5 40.19, P , 0.001], but there was no main effect of domain. There was a significant interaction between test and group [F(2,66) 5 6.05, P , 0.01], but no interactions involving semantic domain. The omission of the familiarity ratings from the statistical model had very little effect on the contribution of domain to explaining the variation in P(correct) (r2 5 0.017 with familiarity; r2 5 0.014 without familiarity).

Comment These findings lend no support to the notion that the presence of a category specific effect is contingent on the overall disease progression of the population, and in this regard they run counter to the theory of Gonnerman et al. (1997) which predicts that an advantage for artefacts is likely to be observed only at more advanced stages of the disease. Nor do our results favour an explanation based on inadequate matching between stimulus sets, according to which category effects result from the unequal representation of highly familiar items in the relatively preserved domain of artefacts. It is also possible that variation in the size of the patient groups in the various studies is an important factor. Despite the lack of an overall group effect, the profile of individual patients reported by Gonnerman et al. (1997) showed some individuals with an advantage for artefacts, and others with an advantage for natural kinds. If an artefacts advantage were relatively more frequent but of smaller magnitude than a

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P. Garrard et al. Table 3 Comparisons of the mean probabilities of correct identification of items in the natural kinds and artefacts subsets, on three tests from the semantic battery, in two subpopulations of DAT patients selected on the basis of MMSE Test

Mean P(correct) 6 SD Natural kinds

Artefacts

t Tests

Mild (n 5 29) Picture naming Naming to description Word–picture matching

0.85 6 0.18 0.69 6 0.19 0.98 6 0.04

0.88 6 0.11 0.77 6 0.12 0.99 6 0.03

t34 5 0.67 (n.s.) t14 5 0.93 (n.s.) t34 5 1.16 (n.s.)

Severe (n 5 29) Picture naming Naming to description Word–picture matching

0.66 6 0.25 0.61 6 0.15 0.87 6 0.08

0.69 6 0.20 0.67 6 0.10 0.89 6 0.09

t34 5 0.32 (n.s.) t14 5 1.01 (n.s.) t34 5 0.56 (n.s.)

n.s. 5 not significant.

natural kinds advantage, then a group advantage for artefacts would be expected to be reported in smaller samples, but to be balanced out over larger populations. We adopted a multiple single case approach in order to look in detail at the distribution and nature of category specific impairments in individual patients.

Analysis 3: patterns of category specific dissociation in individual cases Naming scores Method Gonnerman et al. (1997) attributed the absence of an overall category effect in their series to the presence of two subgroups of patients, one showing an advantage for artefacts and the other an advantage for natural kinds, effectively cancelling out any overall category effect. As well as predicting the presence of both types of dissociation, Gonnerman et al. (1997) argued that there should be a principled relationship between type of advantage and stage of disease, with the cases showing an advantage for natural kinds at a relatively earlier stage of disease progression than those showing an advantage for artefacts. This prediction was supported in the Gonnerman study by the demonstration that cases with a natural kinds advantage clustered at the beginning of a series rank ordered on the basis of success on naming natural kinds. On the other hand, the hypothesis was challenged in our Analysis 2 by the finding that both the less and the more severe halves of our sample, as defined by the MMSE score, exhibited a slight numerical (but not statistically reliable) advantage for artefacts. For a further evaluation of this issue, we applied an analysis similar to Gonnerman’s, by ranking cases according to naming performance on natural kinds.

Results Figure 2 displays the differences between the percentage naming scores on the natural kind and artefact subsets (excluding musical instruments and water creatures) of the

entire population of 58 DAT patients, with cases rank ordered by success on naming of natural kinds. The mean 6 2 SD for the control population is also shown (dotted lines). Although the majority (n 5 39) of cases showed no significant advantage for one category or the other, it is clear that there are some individual patients who show advantages for artefacts and others who show advantages for natural kinds. A stringent criterion of significance was applied to these cases, requiring an excess advantage of at least one item (5.6%) correct over the values at the extremes of the central 95% of control data (dotted lines). This condition was met by 11 cases, of which eight showed an advantage for artefacts and three an advantage for biological kinds. Examining the distribution of these cases, it is apparent that all those with a significant artefacts advantage scored below the median for the naming of biological kinds (15 out of 18), while two out of the three with a significant biological kinds advantage scored at this level. There thus appears to be a small trend in keeping with the findings of Gonnerman et al. (1997). This trend was subjected to formal statistical analysis as follows. The population was divided into two halves, one scoring above and the other at or below the median for the naming of natural kinds (15 out of 18). For each subject, the datum of interest was the excess of correctly named natural kinds or artefacts, but for the sake of consistency with Analyses 1 and 2 we wanted to continue examining the responses item-by-item. We therefore looked at the responses (i.e. correct or incorrect) to all possible natural kind–artefact pairs. By this method, the hypothesis of no domain effect can be formulated using only natural kind–artefact pairs with unequal scores (i.e. either natural kind correct and artefact incorrect, or vice versa) (McNemar, 1955). The statistical technique recommended for a categorical outcome is the hierarchical loglinear model, which is accessibly described in, for example, Knoke and Burke (1983 passim) or Boniface (1995, p. 115). This technique was used to fit ability group and semantic domain, with item familiarity entered as covariate. (We argued earlier that familiarity was not important in explaining the variation in item identification,

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Fig. 2 Differences between naming scores (percentage correct) for biological kinds and artefacts in all 58 DAT patients. Cases are ranked in descending order of success on naming natural kinds. Reference lines denote control mean 6 2 SD.

but our finding did not relate to a specific semantic test. Since there is independent evidence to suggest that concept familiarity may be differentially important in name retrieval, we decided to include it here.) A significantly greater likelihood of correct identification of artefacts than natural kinds was found in the low scoring group [χ2(1) 5 89.21, P , 0.001], with no difference seen in the high scoring group [χ2(1) 5 0.05, P . 0.8]. The interaction between domain and ability group approached, but did not reach, statistical significance [χ2(1) 5 3.48, P 5 0.062]. Since rank ordering according to success at naming living things could produce a rather biased picture (specifically, a significant artefacts advantage is numerically impossible if the score on natural kinds is .15 out of 18), we also examined the pattern of category specificity when the cases were ordered according to each patient’s overall naming performance. Inspection of Fig. 3 reveals that all but one of the cases with a significant category advantage in either direction are in the lower half of the overall naming distribution (i.e. at or below the median naming score of 30 out of 36). This would suggest that category effects are more likely to become apparent when anomia is relatively severe, but that the direction of such effects is independent of the severity. Formal statistical analysis by the method described earlier showed a significant artefacts advantage in both groups [for the high scoring group, χ2(1) 5 7.99, P , 0.01; for the low scoring group, χ2(1) 5 8.48, P , 0.01], but there was no significant group by domain interaction [χ2(1) 5 1.51, P . 0.2]. While semantic memory impairment (as assessed by a range of tests including object naming) is a virtually universal finding in patients with advanced DAT, in patients with mild to moderate disease there is considerable variability in the degree of semantic memory impairment. We therefore

examined the relationship between category specificity in naming and disease severity based on MMSE (Fig. 4). The population was divided about the median MMSE score for the group (MMSE 5 23), and the analysis repeated. In this case, both high and low MMSE groups again showed a significant artefacts advantage [for the high MMSE group, χ2(1) 5 6.98, P , 0.01; for the low MMSE group, χ2(1) 5 31.73, P , 0.001], but the trend towards an interaction between group and semantic domain that was observed when the cases were ranked by naming of biological kinds did not even approach significance [χ2(1) 5 0.13, P . 0.7].

Overall performance on tests of semantic knowledge Methods It was observed earlier that a majority of the cases showed no significant advantage for naming in either direction. Although this finding is neutral with respect to the predictions of Gonnerman et al. (1997), it is conceivable that the stimulus set (36 line drawings for naming) is too restricted to reveal all cases in which a category effect is present. Therefore, it is possible that, if a more global estimate of semantic knowledge were used, a larger number of category specific cases might emerge, with a distribution more in keeping with the predictions of the model of Gonnerman et al. (1997). A composite score was therefore derived by summing the percentage correct scores for naming, word–picture matching and naming to description, together with fluency scores expressed as a percentage of the control mean scores for fluency. The composite score for artefacts was then subtracted from the score for natural kinds, and the difference obtained (semantic index) was expressed as a proportion of the combined scores. Thus a positive index indicates an advantage

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Fig. 3 Differences between naming scores (percentage correct) for biological kinds and artefacts in all 58 DAT patients. Cases are ranked in descending order of success on naming overall. Reference lines denote control mean 6 2 SD.

Fig. 4 Differences between naming scores (percentage correct) for biological kinds and artefacts in all 58 DAT patients. Cases are ranked in descending order of MMSE score. Reference lines denote control mean 6 2 SD.

for natural kinds and a negative index an advantage for artefacts.

Results Figure 5A displays the semantic index in the 58 patients ranked in order of MMSE score, with the control mean 6 2 SD indicated on the figure as before. The number of cases with a semantic index of at least 60.1 (n 5 15, 26%), i.e. those showing a significant category advantage, was greater than that found in the naming analysis; of these cases, 12 showed an advantage for artefacts. Figure 5B demonstrates the absence of any extreme deviations from baseline in the control group on the same measure. When we took those

cases who had produced some degree of advantage for one or other of the categories on the naming test (Fig. 4) and assessed their status on composite score (Fig. 5A), none shifted from an advantage for natural kinds to artefacts or vice versa, and a previous category effect disappeared in only three cases (Cases 46, 52 and 53 in the rank ordering of Fig. 4). There was thus a broad degree of consistency between these two measures. Because of the composite nature of the index it is not possible to perform multiple pairwise comparisons on these data, but in line with the earlier results, unpaired t tests showed that, irrespective of direction, the dissociations observed in the lower MMSE group were larger [t(56) 5 3.91, P , 0.001] but that the direction was not dependent on the degree of dementia, as determined by

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Fig. 5 (A) Semantic index for all 58 DAT patients, with cases ranked in descending order of MMSE score. Reference lines denote control mean 6 2 SD. (B) Semantic index for all 46 control subjects. Subjects are arranged in alphabetical order.

MMSE-group membership [χ2(1) 5 1.97, P . 0.1]. Furthermore, the three patients with a significant advantage for natural kinds were all at the more severely impaired end of the MMSE distribution, which is the opposite of the pattern predicted by Gonnerman et al. (1997).

examined their performance across each of the four subtests. As shown in Figs 6 and 7, in the majority of cases each patient performed better (or at least as well) on the same category (natural kinds or artefacts) in each of the tasks.

Comment Consistency of the semantic category advantage We have established that 15 cases showed a significant category effect, as judged by a semantic index clearly .2 SD either side of the control mean. The question then arises, in respect of these cases: how many of the tests used to calculate the semantic index showed a dissociation in the same direction? Does the overall advantage reflect one large difference in a single test or an accumulation of perhaps smaller but consistent differences? To answer these questions we selected the six patients with the largest difference in performance between natural kinds and artefacts and

The above patterns of data suggest that the prevalence of some degree of category specificity in a population may be underestimated if it is based on analysis of naming performance alone, and this is likely to be a further factor contributing to its variable appearance in cross-sectional studies. Our findings fit the first prediction of the model of Gonnerman et al. (1997), that any cross-sectional analysis of a DAT patient series will reveal the presence of semantic category advantages in both directions. This is confirmed by the finding of six individuals within our cohort whose

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Fig. 6 Comparison of scores on individual semantic tests in the three patients with the strongest artefacts advantage (case numbers are based on position in Fig. 5). wpm 5 word–picture matching; pn 5 picture naming; nd 5 naming to verbal description; cf 5 category fluency. Closed bars, natural kinds; open bars, artefacts. *Category fluency scores are expressed as a percentage of the control subject mean.

Fig. 7 Comparison of scores on individual semantic tests in the three patients with the strongest natural kinds advantage (case numbers are based on position in Fig. 5). wpm 5 word–picture matching; pn 5 picture naming; nd 5 naming to verbal description; cf 5 category fluency. Closed bars, natural kinds; open bars, artefacts. *Category fluency scores are expressed as a percentage of the control subject mean.

category specific anomia was accompanied, with almost complete consistency, by a similar pattern on the remaining semantic tests (including category fluency in four out of the six cases). However, the model of Gonnerman et al. (1997) also predicts that those patients showing an artefacts advantage will be at a more advanced stage of disease progression than those showing a natural kinds advantage. This prediction is not supported by our findings. Using the technique of multiple pairwise comparisons we showed that, as a group, patients were significantly more successful at naming artefacts, and that this difference was particularly marked in patients with low naming scores. Naming ability is, however, a poor index of general disease severity, and when a more reliable estimate

(MMSE) is used, this difference between high and low ability groups is no longer seen. In other words, the rank orderings created by these two methods are rather different, and this result is also consistent with the finding of other studies, that the relationship between disease severity and anomia is nonlinear (Bayles and Trosset, 1992; Price et al., 1993). Some patients with DAT exhibit marked word-finding problems (consequent upon semantic impairment) early in the course of the disease, whereas in others this deficit is only a late manifestation (Hodges and Patterson, 1995). Such a disparity between semantic and global impairment in DAT seems difficult to reconcile with the idea that the former is the product of a diffuse disease process, which is an important premise of the model of Gonnerman et al. (1997). By

Category specificity in DAT contrast, the relative independence of the two deficits can be accommodated within anatomical models which seek to explain global impairment on the basis of total disease load, and semantic impairment on the basis of disproportionate involvement of infero-lateral temporal lobe structures. Furthermore, the relationship between the size of the artefacts advantage and the degree of anomia, suggested by Fig. 3, is consistent in this context with the notion that a predominance of temporal lobe involvement will produce a disproportionate degradation of knowledge about natural kinds. The corollary of this, namely that extensive pathology elsewhere, possibly involving parietal areas, would produce a disproportionate impairment for artefacts, is not clearly demonstrated by our data. It is worth noting, however, that one of the three patients with a significant deficit in the artefact domain has recently been reported by our group as one of a series of four atypical DAT patients with a biparietal syndrome at presentation and disproportionate atrophy and hypoperfusion of both parietal lobes on neuroimaging (Ross et al., 1996).

Discussion Our analyses of the results of tests of semantic knowledge in this large cohort of DAT patients have shown, first, that within such a cohort some individuals display a degree of category specific semantic impairment. In the majority of these cases the advantage is for artefacts, but in a small number, an advantage for natural kinds is seen. This heterogeneity is reflected in the fact that, across the whole population, the difference fails to achieve statistical significance. The trends in the data can, however, be amplified by looking for category differences between all possible pairs of individual stimuli. Using this technique we revealed first an overall group advantage for artefacts and second a significant correlation between the degree of anomia and the strength of this advantage. However, a parallel correlation with disease stage (as measured by MMSE) was not apparent. We have examined these findings from the point of view of two different perspectives on the organization of semantic knowledge in the brain: one which emphasizes the importance of distinct brain regions in the representation of perceptual and functional features and another which additionally postulates differences in cognitive architecture between biological kinds and artefacts concepts. The latter hypothesis has been most explicitly expressed by Gonnerman et al. (1997). The important differences between these two hypotheses can be summarized as follows. (i) Perceptual and functional attributes in the model of Gonnerman et al. (1997) are distinguished in terms of their respective internal correlational structure, whereas the neuroanatomical account places much greater weight on separate brain regions. (ii) For the purposes of the hypothesis of Gonnerman et al. (1997), the accumulation of pathological changes in DAT must be regarded as a diffusely distributed phenomenon, whilst the neuroanatomical hypothesis requires a systematic spread of pathological changes to discrete areas. (iii) Gonnerman et al.

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(1997) accept an anatomical account of category specificity in Herpes simplex virus encephalitis and MCA territory infarction, but reject it for DAT, while we are attempting to provide a single explanation, applicable to all instances of this phenomenon, regardless of aetiology. We replicated the finding by Gonnerman et al. (1997) of some degree of dissociation of semantic categories within the patient population. In keeping with their study, we also found that our cohort contained a few individual patients with a significant advantage for natural kinds, and rather more with the opposite advantage. Although there is some evidence to support the idea that familiarity biases which are inherent in the test materials produce a ‘natural’ advantage for artefacts, even in the normal population (Funnell and Sheridan, 1992), we would none the less argue for the presence of a genuine neuropsychological effect. This conclusion is based upon the consistency of the advantage over a range of measures seen in individual cases, as well as the fact that the contribution of concept familiarity to the overall artefact advantage was partialled out in the analysis. Since a complete assessment of semantic knowledge depends upon more than naming scores (Garrard et al., 1997), we extended our analysis to incorporate the results of other relevant tests. In doing so, we showed not only that the domain advantages demonstrated in the naming analysis were largely maintained, but that several previously undetected dissociated cases also came to light. The resulting, more comprehensive, analysis still failed to reveal any interaction between disease stage and direction of dissociation—one of the most important predictions of the model of Gonnerman et al. (1997). The second major finding was that the degree of category specificity observed in our sample was highly dependent upon the overall level of anomia and presumed semantic impairment. The generally characteristic trend towards an advantage for artefacts was significantly enhanced in cases with more severe anomia. In order to interpret this finding as evidence for diffusely distributed pathological involvement in DAT, it must be assumed that the degree of anomia is a reliable measure of overall disease burden, and therefore correlated in a linear fashion with other such measures. It has been suggested before that there is no such correlation (Bayles and Trosset, 1992; Price et al., 1993), and this suggestion is given further support by our finding that the strength of the artefacts advantage did not vary between groups of patients defined as milder or more severe on the basis of their MMSE scores. If degree of anomia does not reflect overall disease burden, then we must ask what it does reflect. It is well established that the naming disorder in DAT results, very largely, from a breakdown in the semantic, rather than pre-semantic (visuoperceptual) or post-semantic (speech production) stages of picture processing (Chertkow and Bub, 1990; Hodges et al., 1991). Moreover, it has been hypothesized (Hodges and Patterson, 1995) that the semantic deficit associated with DAT is caused by the spread of disease from its typical

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earliest sites in the transentorhinal region to temporal neocortex proper (Braak and Braak, 1991). However, the clinical variability associated with the early stages of the disease suggests that occasionally the earliest neocortical involvement may occur in other areas of association cortex, accounting for the biparietal presentation seen in a minority of cases (Ross et al., 1996). The further assumption that temporal regions are especially important in the representation of perceptual knowledge, and frontoparietal regions in the representation of functional knowledge (Gainotti et al., 1995), extends this prediction: one group should show an advantage for artefacts and another, smaller subset of patients, the opposite dissociation. These predictions are upheld by the results reported here, and by those of Gonnerman et al. (1997). Since all these particular individuals are semantically impaired, they would be expected to cluster at the severe end of the spectrum of anomia. Our analysis suggests that loss of natural kinds knowledge is disproportionate in Alzheimer’s disease (as proposed by Silveri), but is particularly pronounced in more anomic individuals. This is accounted for almost entirely by the clustering of significant domain effects (mainly showing an advantage for artefacts) at the severe end of the spectrum of anomia, rather than by the segregation of the few individuals with a natural kinds advantage at the mild end (see Fig. 3). The latter pattern is predicted by a distributed hypothesis which assumes that natural kinds and artefacts advantages represent early and late stages, respectively, in the accumulation of disease load. The distributed model is also open to question on conceptual grounds. Gonnerman et al. (1997, p. 273) explain the mechanism by which the distinguishing features of biological kinds are relatively ‘protected’ from randomly occurring damage as arising from the greater density of intercorrelated features contributing to biological kinds concepts. It is not clear from their account what makes a distinguishing feature less likely to be a target in the presence of other intercorrelated features. If it is simply the number of such features, then the same argument could be made without introducing the concept of intercorrelation at all, so ‘protection’ must depend crucially upon the fact that such features are intercorrelated as well as more numerous. In other words, intercorrelation must somehow render the features that participate in it preferentially vulnerable, or even somehow ‘attractive’, to randomly occurring damage. The model of Gonnerman et al. (1997) fails to specify how this kind of differential vulnerability might be instantiated in neural terms. In conclusion, the data presented in this study lend no support to the hypothesis that category specific semantic impairment in DAT can be explained solely in terms of the differential vulnerability of individual components of a widely distributed feature network. They do, however, provide evidence compatible with the alternative notion, that category specificity in DAT simply reflects selective involvement of either temporal or frontoparietal brain regions. This position would clearly be strengthened by corroborative evidence from further large scale studies, particularly if they could

incorporate analysis of data from longitudinal patient assessments.

Acknowledgements This research was supported by means of a Medical Research Council project grant to J.R.H. and a Medical Research Council clinical training fellowship award to P.G.

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Received March 6, 1997. Revised July 23, 1997. Second revision October 10, 1997. Accepted November 17, 1997