Differing profiles of face and scene discrimination deficits in semantic dementia and Alzheimer's disease

Neuropsychologia 45 (2007) 2135–2146

Differing profiles of face and scene discrimination deficits in semantic dementia and Alzheimer’s disease Andy C.H. Lee a,∗ , Netali Levi a , R. Rhys Davies b , John R. Hodges a,b , Kim S. Graham a a

MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge, UK b University Neurology Unit, University of Cambridge, Box 165, Addenbrooke’s Hospital, Hills Road, Cambridge, UK

Received 26 June 2006; received in revised form 9 January 2007; accepted 11 January 2007 Available online 18 January 2007

Abstract Recent work in Alzheimer’s disease (AD) and semantic dementia (SD) has reported a double dissociation in AD and SD on tests of visual discrimination, with poor performance on spatial tests in AD and impaired face discrimination in SD. This pattern has been attributed to the different patterns of atrophy seen in the medial temporal lobe (MTL) in these two neurodegenerative conditions. To investigate whether this functional distinction would extend to another task that employed different types of spatial and object stimuli, two groups of AD and SD patients were assessed on a simple test involving discriminations between blended stimuli. While neither group showed impairment when asked to discriminate objects and colour patches, the SD patients showed a selective deficit in the discrimination of faces whereas the AD patients had significant difficulties discriminating landscapes. These findings extend existing theoretical accounts of MTL function, and challenge current concepts of cognitive impairment in dementia. © 2007 Elsevier Ltd. All rights reserved. Keywords: Memory; Perception; Dementia; Medial temporal lobe; Hippocampus; Perirhinal cortex

1. Introduction The diagnosis of Alzheimer’s disease (AD) requires a primary deficit in episodic memory and at least one other significant impairment in a different cognitive domain, such as attention or language (Grady et al., 1988; McKahnn et al., 1984; Perry & Hodges, 1996; Welsh, Butters, Hughes, Mohs, & Heyman, 1992). In contrast, semantic dementia patients show a progressive, cross-modal loss of semantic knowledge, while other cognitive domains, including day-to-day memory are relatively preserved (Edwards-Lee et al., 1997; Hodges, Patterson, Oxbury, & Funnell, 1992; Snowden, Goulding, & Neary, 1989; Warrington, 1975). These two patient groups also show distinct neuroanatomical profiles, in particular in the medial temporal

∗ Corresponding author at: Department of Experimental Psychology, Oxford University, South Parks Road, Oxford OX1 3UD, UK. Tel.: +44 1865 271419; fax: +44 1865 310447. E-mail address: [email protected] (A.C.H. Lee).

0028-3932/$ – see front matter © 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.neuropsychologia.2007.01.010

lobe (MTL), a region of the brain that includes the hippocampus proper, subiculum, perirhinal, entorhinal and parahippocampal cortices. Although there is significant MTL volume loss in both SD and AD (Chan et al., 2001; Davies, Graham, Xuereb, Williams, & Hodges, 2004; Galton et al., 2001), SD is associated with disproportionate atrophy and cell loss of the perirhinal cortex compared to other regions, whereas AD causes significant cell loss throughout the hippocampus but less so in the perirhinal cortex (Davies et al., 2004, 2005; Lee, Buckley et al., 2006). It seems likely that the differential patterns of MTL atrophy in SD and AD (greater perirhinal compared to hippocampal atrophy in SD; greater hippocampal compared to perirhinal atrophy in AD) hold true throughout disease progression, although no longitudinal comparisons are available. Nonetheless, marked atrophy of the hippocampus is seen in late SD (Broe et al., 2003), and significant perirhinal cortex damage in late AD (Braak & Braak, 1991). The finding that AD and SD have differential involvement of MTL structures is important both theoretically and clinically. Although it was once thought that the MTL comprises

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a single system important for the acquisition of long-term memories (Squire, Stark, & Clark, 2004; Zola-Morgan, Squire, & Ramus, 1994), there is increasing evidence to suggest that MTL structures have dissociable functions (Aggleton & Brown, 1999; Mishkin, Suzuki, Gadian, & Vargha-Khadem, 1997). One account proposes that the various MTL structures may be specialised for different stimulus types within long-term memory, with the hippocampus playing an important role in spatial memory (Maguire et al., 2003; Morris, Garrud, Rawlins, & O’Keefe, 1982; Murray, Davidson, Gaffan, Olton, & Suomi, 1989; O’Keefe, Burgess, Donnett, Jeffery, & Maguire, 1998; Spiers, Maguire, & Burgess, 2001; Vann, Brown, Erichsen, & Aggleton, 2000) and the perirhinal cortex in object memory (Brown & Aggleton, 2001; Eacott, Gaffan, & Murray, 1994; Meunier, Bachevalier, Mishkin, & Murray, 1993; Murray & Mishkin, 1998; Winters, Forwood, Cowell, Saksida, & Bussey, 2004; Zhu, McCabe, Aggleton, & Brown, 1996). A recent debate is whether this involvement of the hippocampus and perirhinal cortex in spatial and object memory extends beyond the domain of long-term memory. In particular, it has been suggested that these structures may be critical to short-term memory (Hasselmo & Stern, 2006; Ranganath & Blumenfeld, 2005; Ranganath & D’Esposito, 2001; Stern, Sherman, Kirchhoff, & Hasselmo, 2001) or higher-order perceptual processes (Barense et al., 2005; Buckley & Gaffan, 2006; Bussey & Saksida, 2005; Lee, Barense, & Graham, 2005). In support of this view, a recent investigation found evidence of a double dissociation in performance on a scene and face visual discrimination task in patients with AD and SD (Lee, Buckley et al., 2006). In Lee, Buckley et al. (2006) participants were presented with an array of four faces or virtual reality rooms on each trial and asked to select the odd-one-out. Crucially, this task did not contain a long-term declarative memory demand as there was no requirement for subjects to remember stimuli across trials. Whereas the AD cases showed difficulties with oddity judgement for scenes, but not faces, presented from different views, the SD patients were impaired at faces, but not scenes presented from different views. In contrast, when faces and scenes were presented from the same view (subsequently reducing the demand on object and scene perception, respectively) the SD patients performed normally on oddity judgement for both stimulus types, while the AD patients showed a mild deficit with scenes. Similar impairments on oddity judgement have been reported in individuals with non-progressive MTL involvement (Lee, Buckley et al., 2005) and taken together, these studies highlight the possibility that the MTL may mediate processes beyond long-term declarative memory with the hippocampus and perirhinal cortex specialised for processing scenes and objects, respectively. Notably, a number of recent studies have failed to replicate these findings, demonstrating intact visual discrimination following MTL damage (Levy, Shrager, & Squire, 2005; Shrager, Gold, Hopkins, & Squire, 2006; Stark & Squire, 2000). For example, in Stark and Squire (2000), patients with damage to the hippocampus and perirhinal cortex per-

formed within the control range on face oddity judgement tasks similar to those subsequently modified by Lee, Buckley et al. (2005). It is possible that these discrepancies across experiments may be explained by fundamental experimental differences, for example, differences in the types and number of stimuli used and the kinds of patients assessed. It also highlights, however, the need for further studies in different cohorts of patients, preferably using different measures of perceptual discrimination, to provide further convergent evidence of the role of the MTL in short-term working memory or perception. The aim of the present study, therefore, was to ask whether a double dissociation similar to that found in Lee, Buckley et al. (2006) would be present in a new group of AD and SD patients on a different experimental task. This test was designed to measure fine visual discrimination and is a version of an experimental paradigm that has been used with non-human primates (Bussey, Saksida, & Murray, 2003). Furthermore, it has been shown to be sensitive to static hippocampal and perirhinal cortex lesions in amnesic patients (Lee, Bussey et al., 2005) and has a number of advantages over the Lee, Buckley et al. (2006) oddity paradigm. First, the present test assessed visual discrimination by manipulating the feature overlap between stimuli. This differs from the use of viewpoint processing (i.e. same views versus different views) since feature overlap offers a means by which the demands on scene/face processing can be varied over a range of difficulties. For instance, in two studies (one in non-human primates using black and white photographs of common objects and outdoor scenes, Bussey, Saksida, & Murray, 2002, and one in amnesic individuals using schematic diagrams of insects and animals, and abstract patterns, Barense et al., 2005), it was found that as feature overlap was increased (and thus a greater demand was placed on object processing) the increase in errors in perirhinal cortex lesioned subjects was greater than that for control participants, thus supporting a role for the perirhinal cortex in object processing. Second, the current task used real world landscapes, as opposed to virtual reality rooms, and provided an opportunity to investigate object discrimination beyond faces. Lastly, performance on the critical experimental conditions could be contrasted with a simple control condition (colour discrimination) in order to assess whether the amnesic subjects possessed a basic perceptual deficit. Given the findings from Lee, Buckley et al. (2006), we predicted that the AD patients would show a selective deficit in discriminating scenes compared to controls and the SD patients, with normal performance on all other task conditions. By contrast, the SD group was expected to be impaired on face, and possibly object, discrimination relative to the other two subject groups, with normal scene and colour processing. In line with previous studies that assessed feature overlap (Barense et al., 2005; Bussey et al., 2002, 2003; Lee, Bussey et al., 2005), we also predicted that the patients would exhibit a significantly greater increase in errors on these conditions relative to healthy participants (i.e. AD on scenes; SD on faces and objects) when a greater demand was placed on stimulus processing by increasing feature overlap between stimuli.

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2. Methods 2.1. Subjects Three different subject groups participated in this study, including 7 semantic dementia (SD) patients (age range 55–78 years; mean age 64.86 years, S.D. = 7.54; mean education 12.57 years, S.D. = 3.64), 9 Alzheimer’s disease patients (age range 55–78 years; mean age 64.89 years, S.D. = 8.07, mean education 13.89 years, S.D. = 3.30) and 13 age-matched healthy controls (age range 60–78 years; mean age 66.54 years, S.D. = 4.39, mean education 11.92 years, S.D. = 2.82). All the patients presented through the Memory Clinic at Addenbrooke’s Hospital, Cambridge, UK, and have been longitudinally assessed on an extensive neuropsychological battery. The diagnosis of AD was based on inclusion and exclusion criteria (McKahnn et al., 1984) developed by the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and the Alzheimer’s disease and Related Disorders Association (ADRDA). All the SD patients recruited for the study fulfilled the Lund–Manchester consensus criteria for frontotemporal lobar degeneration (Neary et al., 1998) and had a deficit in semantic knowledge, combined with relative preservation of syntax, phonology, perceptual and visuospatial abilities, non-verbal episodic memory and non-verbal problem solving (Garrard, Perry, & Hodges, 1997; Hodges et al., 1992; Perry & Hodges, 1996; Snowden et al., 1989; Snowden, Neary, & Mann, 1996; Warrington, 1975). The cognitive abilities of the patients were quantified with standardised neuropsychological tests assessing a variety of cognitive functions. 2.1.1. Tests of visual perception (1) The Rey Figure Copy (Osterrieth, 1944), in which subjects were asked to draw a copy of a complex black and white line figure; (2) two object and two space perception tests from the Visual Object Space Perception (VOSP) battery (Warrington & James, 1991). The object tests included incomplete letters, in which the ability to name degraded alphabetic letters was assessed, and object decision, in which participants had to select the real object from three foils. The space tests were dot counting, in which subjects were instructed to determine the number of dots presented on a page and number location, in which subjects had to identify a specified position from an array of foils.

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2.1.2. Tests of episodic memory (1) The Recognition Memory Test (RMT) (Warrington, 1984) assessed subjects’ recognition memory for 50 faces and words; (2) the Rey Figure Delayed Recall (Osterrieth, 1944), in which the participants were asked to recall the figure they had copied in the copy condition (see Section 2.1.1) after a delay of 20 min. 2.1.3. Tests of semantic memory (1) The words version of the Pyramid and Palm Trees (PPT) Test (Howard & Patterson, 1992), in which subjects were presented with a triad of words and asked to identify the two that were semantically related; (2) Picture Naming, in which the ability to name line drawings of objects was assessed; (3) Category Fluency, in which subjects were required to generate as many words as possible to a given semantic category (i.e. animals); (4) Word–Picture Matching, in which participants were required to match object names with their respective drawings. The control subjects were recruited from the healthy volunteer panel of the Medical Research Council Cognition and Brain Sciences Unit, Cambridge, UK. Since these subjects were not assessed on the background tasks described above, the possibility that one or more of these subjects were in the early stages of dementia cannot be definitively rule out. This possibility, however, is highly unlikely since (1) none of the subjects complained of or exhibited any cognitive or emotional difficulties symptomatic of early dementia and (2) many of these participants have been assessed on other experimental tests used in our laboratory and performed at least two standard deviations within the control range. In order to analyse the background neuropsychological data of the SD and AD patients in this study, normative data from Bozeat et al. (2000) was used (N = 31; mean age 68.48 years, S.D. = 7.14; mean education 11.15 years, S.D. = 1.46). Table 1 provides the mean scores for each subject group on these tests. Statistical analyses on the background neuropsychological data are provided in Section 3. Critically, the standardised neuropsychological tests indicated that all patients demonstrated cognitive profiles that were characteristic of their respective disease at the time of experimental testing. Fig. 1a and b show a coronal slice from the structural MRI scans of the brain of a SD and AD patient in this study, taken within 6 months of behavioural testing. As suggested by previous studies (Chan et al., 2001; Davies et al., 2004; Galton et al., 2001), the SD scan indicates greater atrophy to the perirhinal cortex and anterior entorhinal cortex in comparison to other MTL structures, whereas the

Table 1 Mean background data for each subject group (standard deviation) significant differences between a patient group and Bozeat et al. (2000) control group were only found for those scores highlighted with an asterisk Group Controla

AD

SD

General MMSE/30

25.11 (2.75)

22.43 (3.95)

Perceptual RCF copy/36 VOSP letters/20 VOSP object/20 VOSP dot/10 VOSP position/20

30.31* (7.35) 19.11 (0.93) 19.00* (1.32) 9.56 (0.73) 19.63 (0.52)

35.00 (1.91) 17.43* (2.07) 16.86 (2.41) 9.71 (0.76) 19.50 (1.22)

34.21 (1.59) 19.21 (0.82) 16.92 (2.34) 9.93 (0.26) 19.79 (0.62)

Episodic RCF delayed recall RMT words (%) RMT faces (%)

5.79* (5.89) 68.89* (11.96) 78.22* (7.24)

15.29 (8.56) 64.29* (7.87) 64.29* (14.40)

18.28 (5.23) 98.07 (3.90) 97.66 (2.51)

Semantic PPT words/52 Naming (%) Cat flu (total of eight categories) Word–Picture Matching/64

51.00 (0.82) 97.74 (1.58) 68.33* (22.44) 63.25 (0.71)

36.86* 31.61* 18.14* 47.71*

(7.38) (25.36) (18.54) (10.97)

51.11 (1.10) 97.28 (2.52) 115.16 (19.56) 63.78 (0.42)

Key: MMSE, Mini Mental State Examination; RCF, Rey Complex Figure (Osterrieth, 1944); VOSP, Visual Object Space Perception battery (Warrington and James, 1991); letters, incomplete letters; object, object decision; dot, dot counting; position, position discrimination; RMT, Recognition Memory Test (Warrington, 1984); PPT, pyramids and palm trees (Howard and Patterson, 1992); Cat flu, category fluency. a Control subjects for background neuropsychological tasks (Bozeat et al., 2000).

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Fig. 1. A coronal slice for one (a) SD and (b) AD patient assessed in this study (both taken within 6 months of testing). The arrows indicate predominant damage within the MTL (SD, perirhinal cortex; AD, hippocampus). AD scan shows damage to the hippocampus but less so to the perirhinal cortex. Other than three of the AD cases (two of which could not be scanned due to medical reasons), all of the remaining AD and SD patients had received structural MRI scans as part of their clinical follow-up. Importantly, the neuropathology that was evident from these scans was typical of the diagnosis (AD/SD) for each patient. Unfortunately, not all of these scans were taken around the period of this study and thus, it was not possible to acquire detailed volumetric information on the brain damage in each patient that would have been relevant to the current experimental data. This study received approval from the Cambridge Health Authority Local Research Ethics Committee (UK) and all participants provided informed consent.

2.2. Procedure and tasks The patients were assessed either at their own home or at the Early Dementia Clinic at Addenbrooke’s Hospital, Cambridge, UK. Testing was conducted on a 15 in. SVGA LCD touchscreen (1024 × 768 pixel resolutions) attached to a computer laptop. Subjects were seated in front of the screen so that they could comfortably touch it during the computerised task with the index finger of their dominant hand and were allowed to familiarise themselves with the screen prior to the start of testing. The experimental test in this study was a version of a concurrent discrimination paradigm that was used in a previous study (Lee, Bussey et al., 2005), adapted from one developed in non-human primates (Bussey et al., 2003), in which subjects were required to discriminate between a pair of visual stimuli over 53 successive trials (see Fig. 2). In the first three trials, the subjects were shown a pair of stimuli from one of four stimulus categories (faces, objects, spatial scenes, colour) and were required to identify the target stimulus by touching one of the stimuli. On selection, the target stimulus produced a high tone, whereas the distracter was associated with a low tone. These first three trials were implemented for the subjects to learn the target stimulus and were not used for statistical analyses. If it was clear to the experimenter that the subject had failed to identify the target stimulus (i.e. by achieving less than two out of three on the initial learning trials or due to the continuous selection of the non-target image) then trials 1–3 were repeated. From trials 4 to 53, the morphed versions of the same pair of stimuli were presented. The two stimuli were morphed together using commercially available computer software (Morpheus Photo Animator, ACD Systems Ltd., Saanichton, Canada) to create 50 new trial unique pairs with five different levels of feature overlap in which the stimuli shared 0–9% (Level 1), 10–19% (Level 2), 20–29% (Level 3), 30–39% (Level 4) or 40–49% (Level 5) features. For example, a Level 1 pairing could consist of one image that was composed of 91% of the original target stimulus and 9% of the original distracter, and another image that was 9% of the original target stimulus and 91% of the original distracter. There were 10 trials for each level of feature overlap and these were pseudo-randomly ordered such that 2 trials from each level were presented for each block of 10 trials. The subjects were required to select the picture that contained a greater proportion of the original target stimulus. Auditory feedback was provided throughout each task condition (trials 1–53) and on each trial, the stimuli remained on the screen until the subjects made a decision and touched one of the images.

Importantly, a full practice condition with a separate stimulus set (black and white photographs of two different indoor scenes) was administered prior to any experimental data collection to ensure that the subjects understood the task. Instructions were given along the following lines: “you will be presented with a pair of images over a large number of trials—one of the images will produce a high tone when touched (the target), whereas the other image will produce a low tone (the distracter). Your aim is to identify the image that produces the high tone and to keep selecting it throughout the task. On some trials, however, the two images will be blended with one another although one image will always contain more of the original target image. Your task is to select the image that you think looks more like the original target image. This will be easier on some trials compared to others.” Stimulus materials were eight-bit bitmap files presented on a grey background. There were two to four sets of images per stimulus category as detailed below. All subjects were assessed on all stimulus sets and the administration of these was randomised within and across subjects. 2.2.1. Faces Four black and white pairs of images of faces with a neutral expression (two females, two males, each 250 × 250 pixels) were used. All faces were presented without hair and all conspicuous facial features, for example, skin blemishes, were removed to prevent the subjects from discriminating the images using a single feature. The faces were all looking directly ahead and within each pair, faces of a similar appearance in terms of age and skin tone were selected. 2.2.2. Objects Two black and white pairs of images of objects (one living pair consisting of a lion and a dog, 220 × 300 pixels; one non-living pair consisting of a guitar and a cello, 150 × 370 pixels) were used. Objects were selected on the basis that they could be effectively morphed with one another in order to discourage stimulus discrimination using a single visual feature. 2.2.3. Scenes Two black and white pairs of images of outdoor scenes (300 × 300 pixels and 300 × 250 pixels) were used. 2.2.4. Colour Two pairs of coloured rectangles (red with blue, and green with orange) and one black and white pair (each 230 × 280 pixels) were used.

3. Results 3.1. Background neuropsychology 3.1.1. Age, years of education and MMSE A series of one-way ANOVAs revealed that the three subject groups did not differ significantly in age (F(2,28) = 0.24, p > 0.7) or years of education (F(2,28) = 1.03, p > 0.3). Thus, any group

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Fig. 2. One trial from each level of feature overlap from the four conditions of the visual discrimination task. (+) Correct stimulus; (−) incorrect stimulus.

differences on the experimental tasks could not be due to these factors. There was also no significant difference between the two patient groups on MMSE score (t(14) = 1.60, p > 0.1). 3.1.2. Tests of visual perception A one-way ANOVA indicated that there was a significant group difference on the Rey Figure Copy (F(2,43) = 4.82, p = 0.01). Post hoc t-tests (Bonferroni corrected for multiple comparisons) revealed that this was due to the AD group performing significantly poorer in comparison to the SD and control groups (both p > 0.02), with half of the AD patients performing beyond the normal control range. In terms of the VOSP, there was a significant group difference on the incomplete letters and object decision conditions (both F > 3, p ≤ 0.05) but not on any of the other conditions (all F ≤ 2, p > 0.1). The group difference on the incomplete letters condition was due to the SD group performing significantly poorer compared to the AD and control groups (both p ≤ 0.01) whereas the group difference on the object decision condition reflected a trend towards the AD group performing significantly better than the control group (p = 0.06). It must be noted, however, that on both these conditions all groups performed within the standardised normal range of performance for subjects over 60 years old (incomplete letters, 16–20 out of 20; object decision, 14–20 out of 20).

3.1.3. Test of episodic memory One way ANOVAs revealed that there was a significant group difference on the Rey delayed recall condition (F(2,42) = 12.56, p < 0.0001) and both the words (F(2,42) = 114.14, p < 0.0001) and faces (F(2,44) = 85.45, p < 0.0001) version of the RMT. Post hoc tests (Bonferroni corrected) showed that the group deficit on the Rey recall task was due to the AD group performing significantly poorer in comparison to the SD (p = 0.01) and control groups (p < 0.0001). In contrast, on both the RMT words and faces tasks, there were significant differences between the AD group and control group (both p < 0.0001) and the SD group and control group (both p < 0.0001). There was also a significant difference between the AD and SD patients on the RMT face task (p = 0.003), with better performance by the AD group (Table 1). 3.1.4. Tests of semantic memory There was a significant group difference on the word version of the PPT (F(2,41) = 63.35, p < 0.0001), Category Fluency (F(2,46) = 74.94, p < 0.0001), object naming (F(2,46) = 139.29, p < 0.0001) and Word–Picture Matching (F(2,41) = 39.67, p < 0.0001). In accordance with semantic knowledge loss in SD, post hoc tests (Bonferroni corrected) revealed that there was a significant difference between the SD patients and the AD and control groups on all of these tasks (all p < 0.0001), with

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Fig. 3. z-Score plot for the two patient groups when compared to the control group on the four task conditions (scores beyond z = −1.96 indicate significant impairment).

the SD group performing poorer. The only significant difference between the AD patients and the control group was on the Category Fluency task (p < 0.0001). 3.1.5. Main statistical analyses In order to explore any group differences in performance accuracy on the visual discrimination task (see Fig. 3), a repeated measures ANOVA was conducted on trials 4–53 of each condition. All data for stimulus sets within the same category (e.g. all four face pairs) were combined for this analysis. This revealed a significant within-subjects factor of ‘task condition’, reflecting the varying difficulties of the different stimulus categories (F(3,78) = 35.04, p < 0.0001), as well as a significant between-subjects factor of ‘subject group’ (F(2,26) = 5.71, p = 0.009), revealing that overall, the three subject groups performed differently from one another. There was also a significant ‘task condition’ × ‘subject group’ interaction (F(6,78) = 3.83, p = 0.002) and a series of one-way ANOVAs to investigate this interaction further revealed a significant group difference on the faces (F(2,28) = 4.02, p = 0.03) and scenes (F(2,28) = 5.48, p = 0.01) conditions, but not on the objects (F(2, 8) = 3.14, p > 0.06) or colour (F(2,28) = 2.35, p > 0.1) conditions. For the face and scene conditions, post hoc analyses corrected for multiple comparisons (Bonferroni) were then conducted to analyse differences between individual groups. Given our a priori predictions on the basis of previous studies (Bussey et al., 2003; Lee, Buckley et al., 2006; Lee, Bussey et al., 2005) a one-tailed level of significance was adopted. In particular, we expected SD patients to be poorer than both the AD cases and controls on the face task, whereas the AD patients would perform worse compared to the SD and control groups on the scene condition. In contrast, the SD group was predicted to perform within the control range on the scene task, whereas the AD group was expected to perform normally on the face tasks. The post hoc tests revealed that the group effect on the face condition was due to a significant difference between the SD and control groups (p = 0.02, one-tailed), although there was no significant difference between the SD and AD patients (p > 0.2, one-tailed). The AD group did make a greater number of errors compared

to the controls (see Fig. 4) but this difference was not significant (p > 0.3, one-tailed). In contrast, post hoc analyses indicated that on the scene task, there was a significant difference between the AD patients and the control subjects (p = 0.005, one-tailed) and SD patients (p = 0.05, one-tailed) but not between the SD and control groups (p = 0.5, one-tailed). On an individual subject level, 4 out of the 7 SD patients performed 1.96 standard deviations from the control mean on the face condition (indicating significant impairment), whereas 5 out of 8 AD patients met the same criteria on the scene condition. In order to investigate the effect of difficulty level in the two tasks on which there was a significant group difference (Faces and Scenes), additional repeated measures ANOVAs were conducted for these conditions, with a within-group factor of ‘difficulty’ (with five levels of feature overlap) and a between-group factor of ‘subject group’. These analyses revealed that although there was a significant effect of ‘difficulty’ on both tasks (Faces, F(4,104) = 111.69, p < 0.0001; Scenes, F(4,104) = 88.98; p < 0.0001), there was no significant ‘difficulty’ × ’subject group’ interaction in the Faces and Scenes conditions (Face, F(8,104) = 1.65, p > 0.1; Scene, F(8,104) = 1.32; p > 0.2). This indicated that the patient groups’ errors did not increase at a greater rate compared to the control group when the level of stimulus blending was increased (see Fig. 4). Importantly, all the subjects performed well above chance (50%) at the lowest level of difficulty for each condition (and indeed all difficulty levels). This rules out the possibility that any poor performance on a condition was due to a failure to initially learn the target stimulus at the early stages of each condition. It is possible that the observed patient deficits could be explained by: (a) accelerated forgetting of the target stimuli across trials in the patients or (b) subtle learning effects that were present only in the control group, which resulted in improved performance across blocks (see Shrager et al., 2006). To assess these possibilities, we compared the mean performance of the subjects in blocks 1 and 2 with their mean performance in blocks 4 and 5 for faces (SD and controls), and scenes (AD and controls). In the faces condition, it was found that the performance of the SD patients (t(6) = 0.25, p = 0.8) and control subjects (t(12) = 1.29, p = 0.2) remained similar across the duration of the trial blocks. Moreover, there was a significant difference between the SD and control groups in almost all blocks of the face task (see Fig. 5a), including the very first block of 10 trials (t(18) = 2.24, p = 0.04), block 3 (t(18) = 2.67, p = 0.02), block 4 (t(18) = 2.10, p = 0.05) and block 5 (t(18) = 2.29, p = 0.03). This suggests that neither rapid forgetting in the SD patients nor an improvement in performance in the controls over time can fully explain the face discrimination deficits in the SD patients. With respect to the scenes condition, the AD group did not show a deterioration in performance across blocks (t(8) = 0.16, p = 0.9), once again suggesting that rapid forgetting in these patients did not contribute to their impairment. In contrast, rather than improving in performance across trials in the scenes task, the controls showed a significant decrease (t(12) = 3.59, p = 0.004) in performance in the scenes condition. This suggests that any learning by the controls in this condition may

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Fig. 4. Mean percentage error for each subject group for the five levels of feature overlap (1 = 0–9%, 2 = 10–19%, 3 = 20–29%, 4 = 30–39% and 5 = 40–49%) on each condition of the visual discrimination task.

have inhibited, rather than enhanced, task performance. In keeping with this, there was a significant difference between the AD patients and controls in blocks 1 (t(20) = 3.47, p = 0.002), 2 (t(19) = 2.94, p = 0.008), and 3 (t(19) = 2.64, p = 0.02) of the scenes condition, but not in the final two blocks (both t < 1.7, p > 0.1) (see Fig. 5b). 4. Discussion Using a discrimination paradigm based on non-human primate work (Bussey et al., 2003) and previously shown to be sensitive to hippocampal and perirhinal cortex damage in amnesics (Lee, Bussey et al., 2005), a dissociation in scene and face processing between patients with semantic dementia and those with Alzheimer’s disease was demonstrated. More specifically, while the SD patients exhibited difficulties in the visual discrimination of faces but not spatial scenes compared to controls, the patients with AD showed a deficit in scene, but not face, discrimination compared to healthy participants. This finding extends that reported by Lee, Buckley et al. (2006) by confirming that the difficulties seen in oddity judgement for faces and virtual reality rooms can be extended to stimuli that do not stress viewpoint independent representations. Contrary to prediction, the present task did not demonstrate additional impairments in

the SD group for objects, as well as faces. Moreover, unlike in Lee, Buckley et al. (2006) a full double dissociation between AD and SD was not found: while the AD patients were significantly poorer than the SD patients in scene discrimination, the SD patients did not exhibit a significant deficit compared to the AD patients in face discrimination. Critically, both groups of patients showed no statistically significant impairment on the colour control condition. The observations outlined above suggest that AD and SD patients may have distinct difficulties in the processing of spatial scenes and faces and add to our current understanding of the profiles of impairment that accompany SD and AD. The lack of patient brain scans in the current study prevents any firm anatomical conclusions from being made on the basis of this investigation alone. Distinct profiles of MTL involvement in AD and SD have, however, been reported previously (Chan et al., 2001; Davies et al., 2004; Galton et al., 2001), with predominant perirhinal cortex damage in SD and predominant hippocampal atrophy in AD compared to other MTL regions. Moreover, the present experimental findings replicate those described for oddity judgement by Lee, Buckley et al. (2006), in which MRI data were available and in agreement with the aforementioned anatomical studies (Chan et al., 2001; Davies et al., 2004; Galton et al., 2001). Taken together, therefore, these studies support the

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Fig. 5. Mean percentage error for: (a) the SD and control groups across the faces condition and (b) the AD and control groups across the scenes condition. Asterices indicate level of significance of group difference (* p < 0.05; ** p ≤ 0.01).

idea that structures in the MTL may play unique roles in processing spatial scenes (hippocampus, particularly posterior regions) and faces (perirhinal cortex). Given the lack of MRI data in this study, one may suggest that the patient deficits seen here may reflect parietal lobe dysfunction in AD causing widespread attention deficits, or lateral temporal lobe involvement in the SD cases (e.g. fusiform gyrus, areas TE/TEO). This, however, does not appear to be likely. First, our findings agree with a number of existing studies indicating that the hippocampus and perirhinal cortex are specialised for the processing of spatial scene and object memory, respectively (Barense et al., 2005; Brown & Aggleton, 2001; Buckley, Booth, Rolls, & Gaffan, 2001; Maguire et al., 2003; Morris et al., 1982; Murray et al., 1989; O’Keefe et al., 1998; Spiers, Maguire et al., 2001; Vann et al., 2000). Second, if the observed dissociation between scene and face discrimination deficits is caused by parietal or lateral temporal lobe dysfunction, one would expect the patients to demonstrate more widespread discrimination deficits. For example, potential difficulties in attention in the AD group or lateral temporal lobe damage in SD may be expected to impact all task conditions. Third, and perhaps most importantly, recent functional neuroimaging studies have demonstrated MTL involvement during visual discrimination tasks. For instance, posterior hippocampal activity has been observed during spatial scene discrimination, whereas perirhinal cortex activity

has been found during the discrimination of everyday objects and faces (Lee, Bandelow, Schwarzbauer, Henson, & Graham, 2006; Lee, Scahill et al., 2006). These studies support the idea that MTL regions may contribute to tasks such as that used here. Interestingly, recent investigations have found hypometabolism in the posterior cingulate in AD, with some suggestions that this may contribute to the episodic memory problems seen in this condition (Chetelat et al., 2003; Minoshima et al., 1997; Nestor, Fryer, Smielewski, & Hodges, 2003; see also Boxer et al., 2003). From the present data it is unclear whether this could underlie the AD patients’ deficit in the scene discrimination task. Considering the evidence for a role of the hippocampus in scene memory, however, in particular from static lesion hippocampal cases (Bohbot, Iaria, & Petrides, 2004; King, Burgess, Hartley, Vargha-Khadem, & O’Keefe, 2002; Spiers, Burgess, Hartley, Vargha-Khadem, & O’Keefe, 2001; Spiers, Maguire et al., 2001), and the neural connectivity between the hippocampus and the posterior cingulate (Baleydier & Mauguiere, 1980), it is conceivable that some form of impaired interaction between these two structures may underlie the scene discrimination deficit observed here in AD. Future studies of scene memory and cortical metabolism in both AD and static hippocampal lesion cases will be necessary to clarify this issue. It is important to note that in our previous experiment a group of patients with large, static MTL lesions (MTL group) that involved the hippocampus, parahippocampal cortex, and lateral and medial banks of the collateral sulcus (including the perirhinal cortex) demonstrated a mild deficit in discriminating objects (in addition to a deficit in face discrimination) (Lee, Bussey et al., 2005). In the current study, there was only a trend towards a group difference on the object condition (p = 0.06), although it is possible that with greater subject numbers and increased statistical power that this would reach significance. Contrary to prediction, however, it was the AD patients who performed numerically poorer than the SD cases on object discrimination (Fig. 3). It is unknown why this is the case although it is interesting to note that the AD group’s performance on the object condition (relative to controls) was at a similar level to that on the face and colour tasks. Thus, it appears that beyond the scenes condition the AD group performed similarly across the other conditions at a level below the mean control performance. This may reflect the general cognitive impairment that is often associated with AD. Although both the MTL and SD groups were impaired in the discrimination of faces, the effect size of the MTL group was far greater than that for the SD group observed here (MTL zscore = −5.9; SD z-score = −3.2). Thus, overall the SD group possess a relatively milder impairment in comparison to the MTL group from our earlier study (Lee, Bussey et al., 2005). Indeed, whereas all three MTL patients in Lee, Bussey et al. (2005) performed below the healthy participant mean on the faces condition, three of the seven SD cases here performed above the healthy average score. These different levels of impairment may reflect the different amounts of damage to perirhinal cortex sustained by each group, as the MTL cases typically have greater loss of perirhinal tissue than seen in SD (the latter

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reported to have 40% of control volume remaining in (Davies et al., 2004). One suggestion that may be made on the basis of the present study and Lee, Buckley et al. (2006) is that SD patients possess a specific discrimination deficit that is restricted to face stimuli and which does not extend to other objects. For example, this may be due to dysfunction in face processing brain regions beyond the MTL such as the fusiform face area (FFA) (Kanwisher, McDermott, & Chun, 1997; McCarthy, Puce, Gore, & Allison, 1997). To undermine this, however, other data from our laboratory have demonstrated that SD cases can exhibit difficulties in general object discrimination, for example, oddity judgement for novel (i.e. unfamiliar) objects (Lee, Buckley et al., 2003; Lee, Rahman, Hodges, Sahakian, & Graham, 2003). In addition to this, Lee, Buckley et al. (2006) demonstrated that SD patients were able to perform oddity judgement for same views faces, suggesting that the FFA is functionally intact in this disease. Critically, the perirhinal cortex (damage to which is proposed to underlie the SD discrimination deficits) is known to be involved in general object memory (Brown & Aggleton, 2001; Eacott et al., 1994; Meunier et al., 1993; Murray & Mishkin, 1998; Winters et al., 2004; Zhu et al., 1996) and has been implicated in the visual discrimination of objects other than faces in oddity judgement and feature overlap paradigms (Barense et al., 2005; Buckley et al., 2001; Bussey et al., 2003; Lee, Buckley et al., 2005). Surprisingly, we found that the errors made by the SD and AD patient groups did not increase at a significantly greater rate relative to controls when the discriminations were made more difficult by increasing the degree of blending between the pair of stimuli presented in the faces and scenes conditions, respectively (i.e. no difficulty × group interaction effect). Instead it appears that the patient groups were impaired relative to controls at all difficulty levels and that the degree of impairment was similar irrespective of the level of stimulus blending used (see Fig. 4). This pattern is inconsistent with recent studies that assessed perirhinal cortex lesioned monkeys and amnesic individuals on a similar discrimination task in which the subjects had to select the rewarded stimulus from a pair of stimuli that shared a varying degree of features (Barense et al., 2005; Bussey et al., 2002). In brief, it was found that when there was a higher degree of feature overlap between the two stimuli, participants with perirhinal damage made more errors relative to controls. Thus, in these studies the perirhinal damaged participants were not impaired at discriminating stimuli with a low degree of feature overlap, but had difficulties discriminating stimuli that shared an intermediate or high level of features. Moreover, the participants made a greater number of errors on the high compared to intermediate feature overlap conditions (see Barense et al., 2005; Bussey et al., 2002 for further details). It is unclear why we failed to replicate this result, although it is possible that even at the lower levels of stimulus blending here there was a high degree of feature overlap inherent in the stimuli, leading to difficulties in discrimination across all blending levels. The current experimental paradigm contained two clear mnemonic demands that may have influenced performance (see Levy et al., 2005; Shrager et al., 2006). For instance, to carry

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out the task appropriately, subjects had to memorise the appearance of the original rewarded image throughout the 53 trials of each task condition. Consequently, it is possible that the observed deficits in the patients, especially the AD group, could be attributed to difficulties in remembering the target stimulus across each task condition. In addition to this, although no stimulus pair was presented more than once, all 50 stimulus pairs within each task condition from trials 4 to 53 were created by blending the same two stimuli to varying degrees. As a result, the control group may have benefited from subtle learning due to the repetition of components of the stimuli across trials. To undermine these possibilities, however, we found that neither the controls, nor the patients, improved in performance in the faces and scenes conditions as the task progressed, suggesting that the patients’ difficulties with these two stimulus conditions could not be easily explained by poor learning (at least compared to controls). Secondly, since the performance of the patients did not deteriorate significantly across the test conditions, their poor performance was unlikely to be due to rapid forgetting of the original target stimulus. Indeed performance was above chance for all groups across all conditions and difficulty levels. Finally, the data reported here replicate those reported in a study in which there was no overt longterm declarative demand (Lee, Buckley et al., 2006), a finding that is consistent with non-human primate work suggesting the hippocampus and perirhinal cortex may subserve higher-order spatial scene and object perception, respectively (Buckley et al., 2001; Bussey et al., 2002, 2003; Gaffan, 2001; Murray & Bussey, 1999). It has been suggested controversially that a primary deficit in higher-order perception may underlie the memory problems seen after MTL damage (Gaffan, 2001; Horel, 1978). To support this, the AD and SD groups reported here showed profiles of performance on a face recognition memory test that mirrored their face discrimination abilities (Table 1). More specifically, in line with their poorer performance on the face discrimination condition, the SD group demonstrated poorer RMT face recognition compared to the AD patients, despite the fact that AD is often associated with poorer episodic memory in comparison to SD. Furthermore, it has been previously shown that AD cases show poorer recognition memory for scene stimuli compared to SD patients, in line with the difficulties AD cases demonstrate in scene discrimination (Lee, Buckley et al., 2006; Scahill, Hodges, & Graham, 2005). A review of the literature, however, reveals a more complicated story and the challenge of future research would be to explain how the simple discrimination deficits evident in the patients can explain the profile of memory deficits typically reported in AD and SD. For example, while AD patients are typically impaired on all anterograde memory tests, particularly recollection but also recognition memory (albeit with better performance for faces), SD patients perform significantly better on tests of autobiographical and visual recognition memory (Nestor, Graham, Bozeat, Simons, & Hodges, 2002; Simons, Graham, & Hodges, 2002), with striking deficits on verbal memory tasks (Graham, Patterson, & Hodges, 1999; Hodges et al., 1992). Consistent with the good spatial discrimination evident here, SD patients perform well on object-in-place memory tasks,

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when simple stimuli are involved (Lee, Rahman et al., 2003), but show deficits when more complex stimuli such as faces are presented (Clague, Dudas, Thompson, Graham, & Hodges, 2005), presumably because of their underlying difficulties with discriminating between face stimuli. This pattern contrasts with AD, in which tests of object-in-place memory are highly sensitive (irrespective of object type), and may predict the likelihood that an individual with questionable dementia will develop AD (Blackwell et al., 2004; Swainson et al., 2001). In summary, the current study assessed the fine discrimination of various stimulus categories in groups of AD and SD patients. The AD group was significantly impaired in discriminating scenes only, in support of other studies that have implicated a specific role for the hippocampus in processing spatial scenes, whether in the context of long-term memory, working memory, or perception (Lee, Buckley et al., 2005; Lee, Bussey et al., 2005; Maguire et al., 2003; Morris et al., 1982; Murray et al., 1989; O’Keefe et al., 1998; Spiers, Maguire et al., 2001; Vann et al., 2000). In contrast, the SD group demonstrated a deficit in face, but not scene, discrimination. This observation agrees with other findings of impaired face discrimination in patients with perirhinal cortex damage (e.g. Lee, Buckley et al., 2006) and suggests that SD patients can have problems in the processing of faces. This impairment may be in the context of a general object discrimination deficit, as suggested by previous studies that have demonstrated that perirhinal cortex lesions can lead to deficits in object discrimination (Barense et al., 2005; Buckley et al., 2001; Bussey et al., 2002, 2003; Lee, Buckley et al., 2005). Acknowledgements The authors thank the participants in this study for their time and patience; T. Emery, M. Hornberger, V. Scahill and H. Spiers for assistance with data collection; and T. Bussey, L. Saksida, E. Murray, D. Gaffan and M. Buckley for feedback on these experiments. This work was funded by the Alzheimer’s Research Trust, UK, the Medical Research Council, UK, the Wellcome Trust, UK, and a Royal Society Relocation Fellowship to A. Lee. References Aggleton, J. P., & Brown, M. W. (1999). Episodic memory, amnesia and the hippocampal-anterior thalamic axis. Behavioral and Brain Sciences, 22, 289–425. Baleydier, C., & Mauguiere, F. (1980). The duality of the cingulate gyrus in monkey. Neuroanatomical study and functional hypothesis. Brain, 103(3), 525–554. Barense, M. D., Bussey, T. J., Lee, A. C. H., Rogers, T. T., Davies, R. R., Saksida, L. M., et al. (2005). Functional specialization in the human medial temporal lobe. Journal of Neuroscience, 25(44), 10239–10246. Blackwell, A. D., Sahakian, B. J., Vesey, R., Semple, J. M., Robbins, T. W., & Hodges, J. R. (2004). Detecting dementia: Novel neuropsychological markers of preclinical Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders, 17(1–2), 42–48. Bohbot, V. D., Iaria, G., & Petrides, M. (2004). Hippocampal function and spatial memory: Evidence from functional neuroimaging in healthy participants and performance of patients with medial temporal lobe resections. Neuropsychology, 18(3), 418–425.

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