Phonological dyslexia and phonological impairment: An exception to the rule?

Neuropsychologia 44 (2006) 2861–2873

Phonological dyslexia and phonological impairment: An exception to the rule? Jeremy J. Tree ∗ , Janice Kay University of Exeter, United Kingdom Received 5 January 2006; received in revised form 6 June 2006; accepted 7 June 2006 Available online 1 August 2006

Abstract The condition known as phonological dyslexia involves very poor reading of non-words, with otherwise good word reading performance [e.g. Derouesn´e & Beauvois, 1979; Sartori, G., Barry, C., & Job, R. (1984). Phonological dyslexia: A review. In R. N. Malatesha & H. A. Whitaker (Eds.), Dyslexia: A global issue. The Hague: Martinus Nijhoff Publishers]. Theoretical accounts of this non-word reading impairment suggest disruption to either a component of a non-lexical orthographic-phonological reading route [that is specifically involved in reading non-words; Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Zeigler, J. (2001). A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108, 204–256] or to generalised phonological processes on which novel reading is heavily dependent [Farah, M., Stowe, R. M., & Levinson, K. L. (1996). Phonological dyslexia: Loss of a reading-specific component of cognitive architecture? Cognitive Neuropsychology, 13, 849–868; Harm, M. W., & Seidenberg, M. S. (1999). Phonology, reading acquisition, and dyslexia: Insights from connectionist models. Psychological Review, 106, 491–528]. The present paper questions the latter hypothesis: that phonological dyslexia always occurs in connection with some other form of phonologically based disruption (i.e. in a ‘cluster’ of impairments that are not necessarily reading-specific). Contrary to this view, several recent studies have reported that phonological dyslexia can occur without corresponding generalised phonological impairment [e.g. Caccappolo-van Vliet, E., Miozzo, M., & Stern, Y. (2004a). Phonological dyslexia without phonological impairment? Cognitive Neuropsychology, 21, 820–839; Caccappollo-van Vliet, E., Miozzo, M., & Stern, Y. (2004b). Phonological dyslexia: A test case for reading models. Psychological Science, 15, 583–590]. However, the work is subject to a number of criticisms. The following study examines performance of a phonological dyslexic case (JH) on a variety of phonological based tasks and, unlike many other studies, components of phonological short-term memory. Despite clear impairments in reading non-words, good performance on a variety of phonological tasks makes the possibility of generalised phonologically based disruption unlikely. The view that JH’s good phonological skill was dependent on the use of spelling based strategies was also excluded. As a result, JH’s pattern of performance provides clear evidence that phonological dyslexia can occur without any generalised phonological impairment. © 2006 Elsevier Ltd. All rights reserved. Keywords: Phonological; Dyslexia

1. Introduction Phonological dyslexia is an impairment of reading novel words (non-words) with otherwise good performance in reading familiar words (see Sartori, Barry, & Job, 1984, for a review). Although this condition has been widely documented in the neuropsychological literature in both acquired and developmental cases (e.g. Berndt, Haendiges, Mitchum, & Wayland, 1996;

∗ Corresponding author at: Washington Singer Laboratories, School of Psychology, University of Exeter, Perry Road, Exeter, Devon EX4 4QG, United Kingdom. Tel.: +44 1392 264693; fax: +44 1392 264623. E-mail address: [email protected] (J.J. Tree).

0028-3932/$ – see front matter © 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.neuropsychologia.2006.06.006

Caccappolo-van Vliet, Miozzo, & Stern, 2004a; Caccappolovan Vliet, Miozzo, & Stern, 2004b; Derouesne & Beauvois, 1979; Funnell, 1983; Patterson, 1982) there is considerable disagreement about the nature of the functional impairment that underlies poor non-word reading. Early accounts of phonological dyslexia were based on a ‘dual-route’ model of reading (Model A—see Fig. 1), in which non-words are read exclusively by using a non-lexical rule governed and piecemeal method of mapping orthographic information (graphemes) to phonological information (e.g. Coltheart, Curtis, Atkins, & Haller, 1993). This account for poor non-word reading was therefore straightforward; it must occur as a consequence of damage to the non-lexical route (since it is required to enable reading aloud of all novel words), with relative sparing of a separate lexical read-

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Fig. 1. Model A: The dual-route cascaded (DRC) model of reading (Note: A, non-lexical reading route; B(i) and B(ii), lexical reading route).

ing route (e.g. Derouesne & Beauvois, 1979). In recent times, this account has been outlined in a computational model known as the ‘dual-route cascaded model’ (DRC, Coltheart, Rastle, Perry, Langdon, & Zeigler, 2001), with phonological dyslexia occurring as a result of disruption to the grapheme–phoneme correspondence system (labelled A in Fig. 1), such that some aspect of this mechanism is disrupted. In fact using this computational model, Coltheart et al. (2001) successfully simulated the non-word reading impairment seen in two phonological dyslexics (LB—Derouesn´e & Beauvois, 1985; Melanie-Jane – Howard & Best, 1996) by increasing the parameter, which determines the number of cycles it takes before moving onto the next letter in a sequence. In effect, this manipulation to the model captured the proposal that poor non-word reading reflects the very weak activation of an otherwise normal non-lexical route. Nevertheless, despite the fact that this relatively simple manipulation has been successful in modelling previous published cases of phonological dyslexia, this is by no means the only way a non-word reading impairment could be potentially simulated. However, an alternative explanation suggests that phonological dyslexia is not a reading disorder per se, but occurs as a

result of disruption to phonological processes on which novel word reading is dependent. This is clearly illustrated in connectionist models in which no non-lexical reading route is assumed (e.g. Harm & Seidenberg, 1999, Harm & Seidenberg, 2001), and is also the basis for the view that, as reading is a relatively ‘new’ functional process in evolutionary terms, it must therefore be parasitic in some sense on existing phonological systems (Farah, Stowe, & Levinson, 1996). In line with this view, a majority of case reports of phonological dyslexia (including all 17 cases reported in a special issue of Cognitive Neuropsychology in 1996) have been shown to have subtle to severe phonological impairments. The present study addresses this ‘phonological impairment’ hypothesis of phonological dyslexia. We examine the performance of a neurological patient, JH, who presents with acquired phonological dyslexia, testing his ability on a variety of tasks that appear to tap both generalised phonological processing and phonological short-term memory. In this way, we have sought to determine whether his non-word reading impairment occurs in isolation or in conjunction with an additional phonologically based impairment.

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Fig. 2. Model B: The ‘triangle’ model (Note: A, O → S → P pathway; B, O → P pathway; each oval corresponds to a set of units and arrows denote interconnections).

1.1. Phonological dyslexia and the ‘triangle’ model of reading In a series of connectionist simulations that are often collectively referred to as the ‘triangle’ model of reading (Harm & Seidenberg, 2001; Harm & Seidenberg, 2004; Plaut, McClelland, Seidenberg, & Patterson, 1996), it is proposed (see Fig. 2) that non-words, along with words, are read aloud by a process that involves direct and dynamic connections from orthography to phonology. As is apparent from Fig. 2, this model effectively posits two types of reading pathway, one that involves semantic representations (the O → S → P pathway, marked A in Fig. 2) and the other which does not; given non-words have no meaning it is assumed that they heavily dependent on the ‘direct’ connections between orthography and phonology (referred to as the O → P pathway marked B in Fig. 2). In an early non-connectionist conception of such a model, Friedman (1995) argued that an impairment of reading nonwords could occur as a result of two possible loci of damage: (1) impairment to phonological representations; (2) impairment of direct connections between orthography and phonology (O → P connections see pathway B in Fig. 2)1 ; Friedman (1995) argued that impairment of phonological representations may stem from: (a) a problem with generating an internal abstract phonological code (i.e. within phonological representations), or (b) a problem with maintaining such codes in auditory-verbal short-term memory (note that while this can be characterised in terms of impairment to a ‘phonological output buffer’, this does not constitute part of the architecture of the triangle model). A third

1

It is important to note that the schematic model refers to a number of different simulations that have examined particular patterns of acquired reading impairment (Hinton & Shallice, 1991; Plaut & Shallice, 1993, deep dyslexia; Patterson, Seidenberg, & McClelland, 1989; Plaut et al., 1996, surface dyslexia; Harm & Seidenberg, 2001, phonological dyslexia). However it remains to be seen if all these reading impairments can be adequately simulated in a single unified model (Harm & Seidenberg, 2004).

possibility, not explicitly stated by Friedman (1995) is that the phonological impairment may reflect a combination of (a) and (b). On the basis of the proposals of (1) and (2) above, Friedman (1995) puts forward two quite different case profiles that may be observed in phonological dyslexia. Cases with an impairment of subtype (1) should show a generalised disruption of phonological processing, reflected by poor performance in a variety of tasks that are highly dependent on such processes, including difficulties in reading aloud non-words. Thus, these cases would be expected to perform poorly on tasks that involve the manipulation of phonology, such as segmentation (e.g. say ‘Cat’ without the first or last phoneme) or blending (e.g. /h/ + /æt/ = ?). Examples of such documented cases include, KT (Patterson, Suzuki, & Wydell, 1996), and the five cases (WBA, BBO, DPR, RTI and TWA) documented in Patterson and Marcel’s (1992) seminal paper that was the first to suggest a causal link between phonological impairment and non-word reading impairment. In a variant of subtype (1), one would also expect to observe cases of phonological dyslexia that are characterised by poor auditoryverbal short-term memory performance. Disruption to mechanisms implicated in the maintenance of phonological codes (described as, for example, an impairment of a phonological output buffer), have been held to account for the reading performance of RR (Bisiacchi, Cipolotti, & Denes, 1989), ML (Martin & Lesch, 1996) and MS/BR (Friedman, 1996). The latter two cases also presented with specific problems reading words in text (referred to as ‘phonological text alexia’). Most recently, Harm and Seidenberg (2001) argued on the basis of their ‘triangle’ model, that non-words are more likely to be impaired than words in cases of phonological disruption in phonological dyslexia because they do not activate the semantic system, and do not have well established connections between orthography and semantics (as words do) which can further support phonological activation. These two factors make non-word retrieval a less stable process. In an earlier paper, Harm and Seidenberg (1999) simulated patterns of performance seen in developmental

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phonological dyslexia, by disrupting their model in two ways: (a) mild phonological impairment (simulated by a slight degree of weight decay on phonological feature units throughout training); (b) moderate phonological impairment (in addition to weight decay, clean-up units were removed, as were 50% of interconnections between phonetic feature units). In sum, their version of the ‘triangle’ model appeared to be able to mimic the impairment seen in developmental phonological dyslexia on the basis of specific disruption to phonological units, indicating that generalised phonological disruption appeared to be sufficient to account for the poor non-word reading performance seen in these cases. According to Friedman (1995), cases with an impairment of subtype (2) would be highly dependent on reading via the semantic pathway (namely the O → S → P pathway marked A in Fig. 2), and therefore will show varying levels of word reading success, dependent on the strength or richness of corresponding semantic representations. Words with little associated semantic/conceptual information (such as many function words), and of course non-words, should therefore be read with less success than those with a great deal (such as concrete nouns). It is apparent that under Friedman’s (1995) proposals cases of this second type would not necessarily present with a generalised phonological impairment, but one would expect to see associated difficulties in comprehension and reading aloud of function words. It is of note that despite these initial proposals, subsequent computational work using versions of the ‘triangle’ model suggested that simulating poor non-word reading under this second impairment subtype is problematic. Plaut et al. (1996) preferred to explain the pattern of performance in the phonological dyslexic cases they considered with reference to the ‘triangle’ model using a generalised phonological impairment account, acknowledging that an O → P account (i.e. Friedman’s subtype (2) account) would be difficult to undertake. In later work, Harm and Seidenberg (2001) also rejected this second account as being feasible using their computationally implemented version of the ‘triangle’ model’, given that under their simulations disruption of the O → P pathway resulted in impairment of both non-word and irregular word accuracy (for similar conclusions see Harm and Seidenberg (2004)). As a result, we would conclude that although under Friedman’s (1995) early conception of a ‘triangle’ model (i.e. a model with no non-lexical reading route) there are two possible accounts of how a phonological dyslexic pattern of impairment may occur, on the basis of the most recent computationally implemented versions of the ‘triangle’ model the second of these two possible accounts (namely a disruption of the O → P pathway) is unlikely to be realised. As a result, the present work will focus on the ‘generalised phonological impairment’ account of phonological dyslexia in an effort to scrutinise the feasibility that the ‘triangle’ model can adequately account for the pattern of impairment seen in our own case.

order. However, there have been several reports of phonological dyslexia that directly challenge this pattern. Several recent studies have reported preserved phonological processing, in the context of impaired non-word reading (e.g. Caccappolo-van Vliet et al., 2004a,b) and well-preserved word reading, including of functors. However, it is important to ensure that all potential accounts (impaired phonological processing, impaired auditory verbal short-term memory, impaired word/functor reading) are excluded. And to do this convincingly, information should be gathered on a common series of phonological tasks, tapping both general phonological processing and output buffer impairment, and on function word reading and comprehension. Unfortunately, on re-examination, many previous studies have failed to provide this information comprehensively. For example, Caccappolo-van Vliet et al. (2004a,b) provide strong evidence that their cases (RG, MO and IB) have no apparent impairments on tasks of phonological processing (e.g. phonological segmentation/deletion and blending). However, as all of the cases had severe auditory verbal short-term memory and some comprehension impairments, no further testing could be undertaken, with the result that a short-term memory/output buffer account of their poor non-word reading cannot be excluded. The present study sought to address whether JH, who presented as an acquired case of phonological dyslexia, had any of the additional impairments expected under an account of phonological dyslexia in which a causally linked constellation of deficits co-occurs (as in the subtypes described above). As a final issue, Howard and Nickels (2005) make the important point that there can be orthographic (spelling) influences on some of the tasks assumed to tap “phonological manipulation/phonological skills”; indicating that good performance on such tasks may result from preserved orthographic rather than phonological processes. In line with this proposal, Castles, Holmes, Neath, and Kinoshita (2003) examined the relationship between phoneme deletion and spelling “transparency” (i.e. the degree to which an item has a direct letter-sound spelling correspondence). They report that healthy adults found deletion easier (better accuracy and faster reaction times) with transparent items (e.g. BUCKLE) relative to opaque items (KNUCKLE). Spelling skill also correlated with accuracy on transparent and not opaque items. Of particular relevance is that they suggest that a much better measure of ‘phonological skill’ would be to use opaque items (in order to rule out the use of an orthographic spelling strategy). Thus any study of a phonological dyslexic’s ‘phonological ability’ that claims that performance on tasks such as segmentation and blending are well preserved, must also determine that this is due genuinely to phonological rather than orthographic factors. The present work will therefore examine this issue in greater detail. 2. Case description

1.2. Phonological dyslexia—specific non-word reading impairment or generalised phonological disorder? Earlier we pointed out that the majority of cases of phonological dyslexia appear to have both a specific non-word reading impairment coupled with a more generalised phonological dis-

JH is a 62-year old, right-handed male who left full-time education at 16, joining the RAF and subsequently working as part of its Intelligence department. At the time of testing he had recently retired from a managerial post. JH’s medical history involves treatment for Lupus (which involves low thyroid func-

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tion). In December 2002, JH suffered a heart attack and was admitted to a local hospital. Subsequently, that evening, JH had a stroke and was eventually discharged 9 days later after having made some recovery. Speech and language was affected as a consequence of the stroke and he received speech and language therapy over several sessions in early 2003. At present, JH’s speech is well formed and fluent, with some hesitations and word finding problems. He currently walks with a cane, as he has some limited mobility on his right side. A CT scan conducted in July 2005 determined the presence of a mature left anterior circulation infarct. At the same period, neurological examination of JH was unremarkable and, apart from his mobility difficulty, there was no evidence of limb or speech apraxia. There was also no evidence of hearing loss or visual impairment. Three initial clinical testing sessions (October–November 2003) were conducted by the authors, during which JH’s performance on a variety of verbal and non-verbal tasks was examined (see Table 1). Subsequent testing was conducted over the folTable 1 Basic neuropsychological data Norms Mini-mental state—30/30 Raven’s progressive matrices—11/12 WCST—6/6 Benton—21/27

29 10 6 20

BORB Object decision test—124/128 Item match test—32/32 Foreshortened match test—25/25

115 30 22

WRMT Faces—39/50 Words—30/50

42 43

Fluency Spoken initial letter (FAS)—10 Spoken animals—5

36 17

Grammatical/syntactic processing TROG—75/80

78

Naming GNT—21/30

15

Semantics PPT—49/52 PALPA 50: synonyms—52/60 ADA: written word/pix matching—66/66

50 56 65

Reading NART—33/50 PALPA 36: non-words-length—13/24

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lowing 18 months (January 2004–June 2005), a period during which JH showed no changes in presentation. Despite impaired speech production, JH demonstrates normal abilities on routine domestic day-to-day activities such as cooking, cleaning, shopping, driving, etc. He is a very keen bridge player, and is more than capable of playing at a reasonable standard. 2.1. Summary of initial testing results JH’s overall cognitive profile was determined by thorough testing of his ability on a variety of cognitive tasks (see Table 1). His performance on measures of general cognitive function, executive function (all six categories were completed on the WCST, for example), and object and face recognition was normal, demonstrating little generalised cognitive impairment. Grammatical and syntactic processing (TROG), and measures of reading, repetition and naming ability, also showed little impairment. JH showed better recognition of non-verbal compared with verbal material (see WRMT) and some problems with semantic processing, but this disruption was also very mild (see synonym judgement). As an additional means of determining the quality of JH’s speech production, we asked him to provide an account of what is occurring in the “Cookie Theft” picture (May 2005): “The sink is overflowing but the the the er. the mummy is washing up alongside there and erm. and the boy is erm. erm. wanting to get cookie jar out but he’s er. he he he is er. climbing on top of the chair and the chair is tipping over and er. and in his hand he’s got some cookies to give to his daughter.. his his his erm. daughter, no..she’s ah! [laughs] you could find erm.. and erm.. (pauses 5 s) I think that’s all.” (total time—61 s). It is apparent from this example, and from the data in Table 1 indicating that word fluency is somewhat poor, that JH has mild difficulties in dynamic speech production (though given his relatively good performance on the Graded Naming Test, he is not classically anomic). His speech is well formed, however, and there was no evidence on any phonological output task of phonological errors. Initial screening also demonstrated that despite JH’s normal performance on word reading (NART), he was severely impaired at reading a list of non-words (PALPA 36). For this reason we sought to examine his word/non-word reading in greater detail to determine whether his profile was consistent with phonological dyslexia. 2.2. Summary of reading testing results

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Repetition PALPA 9: words/non-words—78/80 79 PALPA 7: syllable length—24/24 Gathercole et al. (1994): non-word repetition—35/40 33 N. Martin—minimal pairs; immediate: 32/32; filled delay: 32/32 BORB, Birmingham object recognition battery; NART, National Adult Reading Test; PALPA, psycholinguistic assessments of language processing in aphasia; TROG, test for the reception of grammar; WCST, Wisconsin card sorting test; WMS-III, Wechsler memory scale third edition; WRMT, Warrington’s recognition test; PPT, Pyramids & Palm trees test; Benton, Benton facial recognition test; ADA, action for dysphasic adults battery; GNT, graded naming test.

Subsequent to the initial screening, further testing of JH’s reading and spelling was undertaken (see Table 2). JH showed no impairment of recognising familiar words, discriminating letters or naming letters. However, he was very impaired at ‘sounding out’ letters, and such impairment has been reported in several other phonological dyslexic cases. Patterson and Marcel (1992) argued that an impairment of ‘sounding out’ letters reflected an inability to extract the appropriate sounds corresponding to letters by referring to previously learnt words (i.e. to sound out the letter ‘C’ you would simply say the first phoneme in CAT). In effect, this proposal suggests that a task like ‘sounding out’

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Table 2 Test data relating to reading and spelling Lexical decision PALPA 25: visual—118/120 Letter processing PALPA 21: letter discrimination—60/60 PALPA 22: letter naming—26/26 PALPA 22: letter sounding—15/26 Reading—words Weekes (1997): frequency vs. length—198/200 PALPA 30: syllable length—24/24 PALPA 31: frequency vs. imageability—79/80 PALPA 32: grammatical class—80/80 PALPA 33: grammatical class—39/40 PALPA 34: morphology—90/90 PALPA 35: regularity—60/60 Reading—non-words Weekes (1997): length—session 1: 64/100; session 2: 66/100 Palpa 36: length—14/24 Howard and Best (1996): complexity—92/132 Short/simple: 38/45 Long/simple: 29/44 Long/complex: 25/43 Writing to dictation PALPA 39: letter length—23/24 PALPA 40: imageability vs. frequency—73/80 PALPA 44: regularity—33/40 PALPA 41: grammatical class—16/20 PALPA 43: morphology—24/30 PALPA 45: non-words—20/24 PALPA, psycholinguistic assessments of language processing in aphasia.

letters is analogous to a segmentation task and as such poor performance is likely to reflect a generalised impairment of the phonological system (Patterson et al., 1996). However, later evidence will show that this proposal is unlikely given JH is very able to segment and blend words. We would contend that it is more likely that JH’s impairment in providing sounds to letters reflects specific disruption to letter sound correspondences (e.g. to ‘phoneme assignment’ in which grapheme–phoneme correspondence rules play a part; Coltheart et al., 1993). 2.3. Reading aloud words and non-words JH performed with ease all the tests of word reading, showing no effects of length, frequency, imageability or regularity (see Table 2). Reading aloud was swift and accurate. Of critical importance, JH showed no part of speech effects or difficulties with morphology. This clearly demonstrates that his profile is not consistent with an impairment of ‘direct’ orthographic-phonological connections (i.e. subtype 2 of phonological dyslexia discussed earlier), as he shows no evidence of poorer performance reading words with low semantic/conceptual content (i.e. poor function word reading or imageability effects). In addition, we tested JH’s reading of words in text (using the “Grandfather passage”, taken from the Apraxia Battery for Adults, Dabul, 1979). Consistent with his single word reading, JH performed flawlessly with a rapid rate of production (51 s to read the entire passage).

In stark contrast, JH’s performed consistently poorly when reading lists of non-words. On an initial non-word list manipulating length, JH showed poorer performance on longer relative to shorter non-words (PALPA 36—3 letter, 6/6; 4 letter, 4/6; 5 letter, 4/6; 6 letter, 0/6). In a subsequent nonword test devised by Weekes (1997), JH again showed clear effects of letter length, observed consistently over two sessions a year apart (Session 1 (April 2004)—3L = 25/25, 4L = 10/25, 5L = 15/25, 6L = 14/25—Wald(1) = 6.88, p = 0.009; Session 2 (April 2005)—3L = 23/25, 4L = 16/25, 5L = 13/25, 6L = 14/25—Wald(1) = 7.97, p = 0.005). Weekes (1997) demonstrated an effect of letter length in non-word reading speed in healthy adults, and interpreted this effect as being consistent with the serial nature of the non-lexical reading route. The present study provides further evidence that impairment of this route can have a consequential impact of letter length on non-word reading accuracy. An additional test of non-word reading using stimuli provided by Howard and Best (1996), examined whether letter length or complexity had a greater impact on JH’s non-word reading accuracy (longer strings may in fact be more complex orthographically). In this case an effect of letter length remained (Wald(1) = 3.94, p = 0.05), and there was no effect of complexity (Wald(1) = 0.566, p = 0.46). This length effect will be considered further, below. Overall, across the three non-word reading tests, JH scored 236/356 (0.66) correct. This places his non-word reading impairment at the milder end of the continuum of reported cases. Nonetheless, other cases of phonological dyslexia have been reported to perform in the same range (RR (0.63), Bisiacchi et al., 1989; WE (0.65), Berndt et al., 1996; BR (0.66), Friedman, 1996; AG (0.69), Caramazza, Miceli, Silveri, & Laudanna, 1985). Most importantly, JH performs at an equivalent level to case WBA (0.77 accuracy) who was amongst five cases of phonological dyslexia with additional generalised phonological impairments reported by Patterson and Marcel (1992). JH’s errors on non-words were responses corresponding to real words (e.g. BORTH—“Broth”); a phenomenon referred to ‘lexicalisation’ or as ‘lexical capture’ (Funnell & Davison, 1989), and typically reported in cases of phonological dyslexia. Across all three non-word reading tasks, 60% (72/120) of error responses were ‘lexicalisations’, a proportion in a similar range to that seen in other reported cases. Overall, then, JH’s performance in reading aloud non-words in terms of accuracy and error type is comparable to that observed in other cases of phonological dyslexia. 2.4. Spelling words and non-words JH’s spelling ability with familiar words was examined. Overall, he showed a mild impairment, compared with reading aloud the same words, although there was no evidence of effects of length or regularity. All errors JH made on a test manipulating frequency versus imageability (PALPA 40) were with items that were both low frequency and low imageability. Importantly, there was no evidence of poorer spelling performance on function words or particular difficulties with morphology. However, in contrast to his non-word reading, JH’s spelling of non-words

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was substantially better. This clearly demonstrates that in this case his poor performance with non-words was specific to reading (and that his non-word processing was not generally poor). JH’s relatively well-preserved spelling performance therefore shows some dissociation between the phonological processes underpinning reading and spelling. 2.5. Phonological processing Having determined that JH’s reading impairment was consistent with phonological dyslexia, we examined his ability on a variety of phonological based tasks to determine the presence of any ‘generalised’ phonological impairment. 2.6. Segmentation and blending Previous studies of phonological dyslexia have claimed that there is a link between poor non-word reading and impairments on measures of segmentation and blending (e.g. Patterson & Marcel, 1992). Testing of JH’s segmentation ability involved both initial and final phoneme segmentation (i.e. “please say CAT without the first sound” versus “please say CAT without the last sound”). Several versions of this task were used. Across all tests, JH performed well (see Table 3). It is especially noteworthy that although these tests included both word/non-word stimuli, there was no evidence of a lexicality effect. One auditory segmentation test (taken from the Phonology Resource Pack for Adults, Morrison, 2001) was included in which JH had to identify the two out of three items that shared the same final phonemes. Such a task was administered to determine whether JH’s performance on segmentation tasks declined as a function of processing load. However, as with all earlier testing, JH performed well. He also performed well on the auditory version of the initial phoneme segmentation test devised by Patterson and Marcel (1992): JH: 45/48; Controls 45/48. He was impaired, however, when these items (words and non-words) were presented in the written modality (JH: 31/48; Controls: 45/48). JH’s performance on tasks of phonological blending/assembly (e.g. AT plus K makes what?) was examined. In both cases JH performed well (Patterson & Marcel, 1992: JH 45/48, Controls 43/48; Nickels—JH 42/46, Controls 42/46) and there was no evidence of any lexicality effect. We described earlier that Howard and Nickels (2005) have suggested that orthographic (spelling) influences may mask good performance on segmentation and blending tasks, such that good performance may involve particular orthographic strategies (i.e. good spelling ability), rather than phonological ability per se. In order to determine if this underlay JH’s good performance on earlier testing, we made use of a set of stimuli (taken from Castles et al., 2003) that manipulates spelling ‘transparency’ (i.e. the degree to which an item has a direct lettersound spelling correspondence). Overall, JH performed within the normal range (relative to the young controls tested by Castles et al.) on this task: initial phoneme: JH 26/30, Controls 25/30; final phoneme: JH 23/30, Controls 20/30. Of critical importance is the finding that JH showed no greater impairment with opaque relative to transparent items: initial phoneme errors: 3, transpar-

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Table 3 Test data relating to phonological processing Rhyme judgement—(auditory presentation) Hanley et al. (2004): words—16/16 PALPA 15: words—52/60 PALPA 15: words (no orthographically similar pairs)—29/30 Best (unpublished): non-words—47/50 Morrison (2001): words—143/144 Morrison (2001): three word odd one out—23/24 Rhyme judgement—(written presentation) PALPA 15: words—40/60 Best (unpublished): non-words—31/50 Tree and Kay (unpublished) Words—38/40; non-words—36/40 Homophone judgement PALPA 28—53/60 (all errors on non-words) Coltheart—homophone test Regular—47/50 Irregular—46/50 Non-words—37/50 Tree and Kay (unpublished) Words—38/40; non-words—35/40 Segmentation PALPA 16: initial sound—44/45 PALPA 17: final sound—44/45 Hanley et al. (2004): initial sound—16/16 Hanley et al. (2004): final sound—16/16 Patterson and Marcel (1992) Initial sound (auditory): 45/48 Initial sound (written): 31/48 Nickels (unpublished): final sound—45/46 Morrison (2001)—three word odd one out: final sound—25/26 Castles et al. (2003) Initial sound (auditory): 26/30 Final sound (auditory): 23/30 Blending Patterson and Marcel (1992): initial sound—45/48 Nickels (unpublished): final sound—42/46

ent; 2, opaque; final phoneme errors: 3, transparent; 5, opaque, which clearly demonstrates that JH’s good segmentation performance is not dependent on an orthographic strategy. 2.7. Rhyme/homophone judgement Two initial tests of word and non-word rhyme judgement were administered in auditory and written versions. While for written items, JH performed very poorly (at 66% correct), he was also mildly impaired in making auditory rhyme judgements (85% correct), both for words and non-words (McNemar change test indicated a significant difference between performance on auditory and written versions, χ2 = 7.21, d.f. = 1, p = 0.004). For written word rhyme judgement, error responses demonstrated a strong tendency to accept visually similar non-rhyme items (i.e. saying ‘yes’ to the items, CHEAT-SWEAT; 17 false positive errors, 12 visually similar items, 5 visually dissimilar items), and interestingly, a similar pattern of selecting visually similar non-rhyme items was observed when the materials were presented aurally (6/8 errors). This finding was curious given subsequent testing of the PALPA 15 stimuli showed JH was

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very capable of reading aloud all these items without problem. As it was possible that JH was incorrectly choosing to base his decision on visual ‘rhyme’, we re-administered this test aurally without the visual foils, and, in addition, tested his auditory performance on a large set of visually dissimilar rhyme/non-rhyme items (Morrison, 2001). In both cases, JH performed well (see Table 3). He was also able to detect pairs of aurally presented rhyming (e.g. CAR – STAR) and non-rhyming (e.g. CHAIR – TICK) items, using a set devised by Hanley, Masterson, Spencer, and Evans ( 2004) when instructed to ignore visually similar pairs that do not rhyme. Finally, he was also able to perform well on an auditory segmentation test (Morrison, 2001) that required the identification of two out of three items that rhymed. Therefore, on the basis of these findings we would argue that JH can perform normally at these tasks when aurally presented. We also re-explored JH’s ability at written rhyme judgement using an additional test constructed by ourselves. This tests included 40 word and 40 non-word items (10 visually similar rhymes, 10 visually similar non-rhymes, 10 visually dissimilar rhymes and 10 visually dissimilar non-rhymes) and we tested these items on 15 older adults (50+). Testing indicated that JH’s score of 38/40 on word rhyme judgement was within normal range (Controls—mean = 38.5, S.D. = 0.75, zscore = −0.66, n.s.) but with non-words JH’s score of 36/40 was below normal range (Controls—mean = 38.2, S.D. = 1.06, z-score = −2.07, p = 0.02). Thus, consistent with his phonological dyslexia, these results indicated that JH was only impaired at written word rhyme judgement with non-word items. In summary, then, we would conclude that, although he initially demonstrated a degree of poor performance on rhyme judgement (particularly visual rhyme judgement), subsequent testing (which importantly includes age-matched norms) suggests that he can perform well on these tests provided they utilise words. It is curious that our earlier testing showed that JH was inclined to make false positive errors on orthographically similar foils, and this clearly indicates that he utilises orthographic information when deciding rhyme status. Previous work has demonstrated a similar effect in healthy adults in that it has been shown that orthographic similarity/dissimilarity can have an impact both on visual (Johnston & McDermott, 1986; Polich, McCarthy, Wang, & Donchin, 1983) and auditory rhyme judgement (Seidenberg & Tanenhaus, 1979), such that reaction times and errors rates were lowest with orthographically similar rhymes and highest for orthographically similar non-rhymes. The fact is that our earlier testing showed that this effect was exaggerated in JH’s case, and this may indicate a particular ‘strategy’ on his part. However, subsequent testing would suggest that he is not dependent on utilising this strategy, and perhaps experience on such tasks warranted his abandoning it. JH’s ability to make written homophone judgements was also examined (e.g. do SUN and SON sound the same?), with both words and non-words. Homophone judgement clearly differs from written rhyme judgement in that no segmentation of the written form is needed. Rather, success requires comparison of whole word phonological forms. Our initial test-

ing indicated that JH showed good performance on this task (see Table 3), with both regular and irregular words. Homophone detection accuracy was impaired only with non-word items, consistent with his poor non-word reading ability. In line with our testing of visual word rhyme judgement, we also administered an additional test constructed by ourselves. As with the word rhyme judgement task this homophone task included 40 word/non-word items (10 visually similar homophones, 10 visually similar non-homophones, 10 visually homophones and 10 visually dissimilar homophones) and as before we also tested these items on 15 older adults (50+). For homophone judgement with JH scored 38/40 with words which was within normal range (Controls—mean = 38.5, S.D. = 0.84, zscore = −0.83, n.s.), but only 35/40 with non-words which was impaired (Controls—mean = 37.4, S.D. = 0.99, z-score = −2.42, p = 0.01). Thus these data are again consistent with his phonological dyslexic impairment, in that poor performance is contingent on the utilisation of non-word items. In sum, these data indicate that JH has little general impairment in the extraction and manipulation of phonology. In particular, our findings are consistent with a reading impairment specifically affecting non-words. 2.8. Auditory verbal short-term memory (AVSTM) We next sought to determine whether JH’s pattern of performance is linked in some way to an underlying impairment of AVSTM. It is apparent that many cases of phonological dyslexia present with a concurrent impairment of AVSTM (Friedman, 1996), and as a result, several authors have attributed a role of an impaired phonological ‘output’ buffer to their patients’ poor non-word reading (Caramazza, Capasso, & Miceli, 1996). In the case of the three Alzheimer’s disease cases (RG, MO and IB) reported by Caccappolo-van Vliet et al. (2004a,b), all presented de facto with impairments of auditory verbal short-term memory. The authors argue that if this impairment had a role to play in the patients’ non-word reading, a length effect should be present. However, it is unclear how thoroughly effects of length were explored in non-word reading, and the nature of the stimuli that were selected (e.g. whether factors such as visual complexity were controlled). As a result, we must accept the conclusions of Caccappolo-van Vliet et al. (2004a,b) regarding the potential role of AVSTM in their patients’ non-word reading with some caution, particularly as no other measures of output buffer impairment were taken. In the case of JH, our testing of AVSTM (see Table 4) demonstrated: (1) an auditory digit span of six (consistent with normal performance, see Lezak, 1995); (2) poorer span for visual relative to auditory presented items (a reverse pattern is typically reported in cases of AVSTM impairment, see Vallar & Baddeley, 1984); (3) normal span performance on a spatial span task (suggesting no generalised span impairments). It should be noted, however, that backwards span (for both aural/visual presented items) is impaired, but, given the additional processing demands implicated in performing this task, this is likely to reflect some disruption of working memory (Gathercole, 1997) that is unlikely to have a substantial role in the reading of single non-words.

J.J. Tree, J. Kay / Neuropsychologia 44 (2006) 2861–2873 Table 4 Test data relating to auditory verbal short-term memory function Short term memory Digit span—(auditory) Forward: 6 Backward: 3 Digit span—(visual) Forward: 4 Backward: 2 Spatial span Forward: 5 Backward: 4 Word span (Auditory)—four items (Visual)—two items Rhyme span: (Martin et al., 1994)—6 Length effects—(four words) Auditory short: 0.77 Auditory long: 0.62 Visual short: 0.55 Visual long: 0.30 Phonological similarity effect—(four words) Auditory phonological similar: 0.45 Auditory phonological dissimilar: 0.83 Visual phonological similar: 0.33 Visual phonological dissimilar: 0.55 Non-word reading—phoneme length manipulated Three phoneme items—9/30 (0.30) Four phoneme items—6/30 (0.20) Five phoneme items—8/30 (0.27)

A final test devised by Martin, Shelton, and Yaffee (1994) was used to examine JH’s auditory rhyme span. In this task, a sequence of words is read out and after a pause a probe word is read and the participant must decide if the probe rhymes with any of the items in the previously presented sequence. There were 24 trials for each sequence length (three to seven items), with each serial position being probed equally often. In this task, span is considered the optimal length by which a participant gets at least 75% of trials correct. Despite the clear difficulty of this task, JH performed very well, achieving a span of six items, which is within normal range. This excellent performance, requiring a rhyme judgement after a substantial delay, is clearly inconsistent with a generalised phonological impairment. As a further examination of the status of JH’s AVSTM, we additionally examined whether he showed effects of length and phonological similarity on immediate serial recall of aurally and visually presented items. Typically, patients with impairments of AVSTM show no such effects (see Vallar & Papagno, 2002, for a review) and we therefore wished to see what would happen with JH. 2.9. Length effects in immediate serial recall Research on AVSTM has determined that accuracy is typically better for sequences containing phonemically short compared with long words (e.g. Baddeley, Thomson, & Buchanan, 1975; Baddeley, Lewis, & Vallar, 1984). This result has been argued to reflect the maintenance of phonological codes (e.g.

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Howard & Franklin, 1988), and typically a ‘phonological loop’ is attributed to this maintenance process (e.g. Baddeley, 1966, 2004). As a result, we sought to determine whether a similar effect was present in JH’s serial recall. A set of 12 phonologically short and 12 long items were selected (all items were taken from a set constructed by Mueller, Seymour, Kieras, and Meyer (2003) which constitute a set of stimuli that have been rigorously controlled for confounding variables such as complexity; see Baddeley, 2004). A series of 10 trials (consisting of four items in each sequence, each individual item being presented an equal number of times) were constructed for auditory presentation and visual presentation. Entire lists were presented to JH (in four blocks—two sets of short words and two sets of long words) in eight testing sessions (five auditory presentation and three visual presentation sessions, spanning May–June 2005). Overall accuracy is presented in Table 4. It is apparent that JH performed better with lists of short versus long items, both when items were presented aurally (means—short: 3.1, long: 2.5; t(18) = 2.65, p = 0.016) and visually (means—short: 2.2, long: 1.2; t(10) = 6.50, p = <0.0001). These data provide further evidence of normal AVSTM function in JH’s case, suggesting that he is able to use a ‘phonological loop’ to support sequences of short relative to long words. This is a pattern that is never reported in cases of impaired AVSTM (Vallar & Papagno, 2002). 2.10. Phonological similarity effects in immediate serial recall Both auditory and visual immediate serial recall performance is modulated by the degree to which list items are phonologically similar (e.g. Baddeley, 1966, 1968; Levy, 1971; Luce, Feustel, & Pisoni, 1983). In patients with impairments of AVSTM, it is typically reported that phonological similarity effects can be present for aurally presented stimuli, but not for visually presented items (Vallar & Papagno, 2002). As a further means of determining whether AVSTM impairment was present, we examined whether JH showed differences in recalling phonologically similar/dissimilar lists. A set of 12 phonologically similar (e.g. cat, gap, cap, rat) and 12 phonologically dissimilar items were selected (e.g. wig, pen, car, jug, lot). A series of 10 trials of each (with four items in each sequence, each individual item being presented an equal number of times) were constructed for auditory and visual presentation. Entire lists were presented to JH (in four blocks—two phonologically similar (PS) and two phonologically dissimilar (PDS)) in two separate testing sessions (run in parallel with the length immediate serial recall testing in May–June 2005), with the order of visual versus aural presentation counterbalanced. Overall accuracy is presented in Table 4. It is clear that a phonological similarity effect was present with both auditory (mean: PDS: 3.3/4, PS: 1.8/4; t(6) = 5.89, p = 0.001) and visually presented items (mean: PDS: 2.2/4, PS: 1.3/4; t(6) = 4.14, p = 0.006). Overall accuracy was also poorer for the visually presented items (consistent with our earlier testing of span across modalities). As a final examination of AVSTM performance in JH, we collapsed his performance across all ISR testing and

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plotted a serial position curve, this demonstrated the typically ‘bow shaped’ function, with better accuracy at both the first and last serial position points, showing normal primacy and recency effects in his case (average auditory accuracy = 0.66; Pos 1 = 0.74, Pos 2 = 0.52, Pos 3 = 0.57, Pos 4 = 0.82; average visual accuracy = 0.43; Pos 1 = 0.56, Pos 2 = 0.32, Pos 3 = 0.26, Pos 4 = 0.60). 2.11. Phonological “output” buffer function We reported earlier that JH showed a letter length effect in non-word reading. Such an effect could be considered to reflect an ‘output’ buffer impairment, as items with more letters will typically have more phonemes (although our earlier testing of his homophone judgement performance and AVSTM do not support this account). Nonetheless, to test the possibility that JH’s non-word reading impairment was related to an output buffer impairment, we examined his performance with a set of nonwords that manipulated phoneme length, while keeping letter length constant. In this test, the non-word items varied from three to five phonemes, but all were five letters long. None of the items had orthographic neighbours (all items were taken from the online ARC Non-word Database, Rastle, Harrington, & Coltheart, 2002). JH’s non-word reading performance is presented in Table 4. Although overall accuracy was poor (24/90 correct), there was no evidence of greater accuracy with three phoneme relative to five phoneme items. This finding clearly demonstrates that JH’s non-word reading impairment is unlikely to be due to an ‘output’ buffer impairment. Overall, our testing of JH’s AVSTM function showed: (1) superior auditory versus visual span; (2) the presence of length effects for auditory presented items; (3) the presence of phonological similarity effects for both auditory and visually presented items; (4) no effect of phoneme length on non-word reading accuracy. These findings would suggest that JH’s has no impairments to the functional components of an AVSTM system (i.e. a normal phonological input/output and rehearsal system) and by extension rules out the possibility that such impairment (particularly an output buffer impairment) may in some way underpin his poor non-word reading performance. 3. General discussion In the Introduction to this paper, we discussed the two ‘subtypes’ of phonological dyslexia outlined by Friedman (1995) as being consistent with a ‘triangle’ model account of this disorder (i.e. a model with no non-lexical reading route): (1) a generalised disruption of phonological processing; reflected by impairments of phonological manipulation (i.e. segmentation/blending tasks) and/or impairment on measures of phonologically based shortterm memory (i.e. span and rhyme judgement tasks); (2) an impairment of the O → P reading pathway (see pathway B in Fig. 2); reflected by a deficit in function word reading. Only the second of these accounts can be construed as an impairment that is reading-specific, and earlier we pointed out that this account remains problematic for the most recently implemented versions of the ‘triangle’ model.

Our subsequent testing of JH did not find impairments in reading function words suggesting that it is unlikely that his reading performance is consistent with (2). He also showed no impairments in segmentation, blending, rhyme and homophony tasks, and normal functioning of phonological based short-term memory (i.e. normal auditory digit span, length/phonological similarity effects, no phonemic length effects in non-word reading), inconsistent with (1). As a result, this study provides the clearest evidence thus far that the non-word reading impairment in phonological dyslexia is reading specific. The fact that JH’s reading impairment is specific to non-words (and word reading, especially of functors, is well preserved) is consistent with an explanation in terms of a disrupted non-lexical route (labelled A in Fig. 1). Thus although JH’s good reading of functors is potentially problematic for a ‘triangle’ model account of his impairment, it is entirely consistent with the proposals of the DRC model (Coltheart et al., 2001). In this model given functors are largely considered to be low in semantic quality, normal performance with such items is considered to indicate preserved processing of a direct lexical (non-semantic) reading route (marked B(ii) in Fig. 1) also known as the ‘third’ reading route (see Coslett, 1991; Wu, Martin, & Damian, 2002). Hence it is apparent that not only is JH’s normal reading of functors consistent with a DRC account, but it is in fact predicted by such an account given that the mechanisms involved in accurate responding to such items are independent from those involved in reading non-words. 3.1. JH and other critical cases of phonological dyslexia While it is apparent that the proposal that JH has a readingspecific difficulty contrasts with the notion that there is a causal link between phonological impairment and poor non-word reading (the phonological impairment hypothesis of phonological dyslexia; Patterson & Marcel, 1992), it is consistent with the reports of other cases of phonological dyslexia who perform well on tasks of phonological processing (e.g. LB, Derouesn´e & Beauvois, 1985; RG, MO and IB, Caccappolo-van Vliet et al., 2004a,b). It is interesting to note that these cases differ from JH in terms of aetiology: LB had a right hemisphere CVA, and RG, MO and IB all had Alzheimer’s disease. JH provides evidence that a similar behavioural profile can occur in conjunction with a left hemisphere focal lesion, and thus rules out the possibility that such performance only occurs in patients who are in some manner neurologically unrepresentative of the typical phonological dyslexia patients reported in the literature (Coltheart, 1996). It is also important to emphasise that JH’s pattern of performance is different from those other reported case studies in that, (a) LB had some impairment in reading words (in particular, function words) and (b) RG, MO and IB were not tested sufficiently to rule out the possibility that an ‘output’ buffer impairment may have underpinned their poor non-word reading. As a result, all of these cases could be argued to have non-word reading impairments that are consistent with one of the subtypes set out above. We would suggest that the present study is therefore unique, given the thoroughness of phonological based testing in our particular case (including, for example, testing orthographic

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‘transparency’ to exclude the use of orthographic strategies in phonological segmentation and blending tasks). It is of note that although for the most part studies of phonological dyslexia have typically omitted to examine in any detail the role of a disruption to phonological short-term memory, case ML (Lesch & Martin, 1998; Martin & He, 2004; Martin & Lesch, 1996) has been examined in a manner by which we can draw comparisons with JH. Case ML is reported to have a reduced short-term memory in conjunction with phonological dyslexia. In a series of experiments, Martin and co-workers demonstrated that ML like JH performed at a similar level on measures of immediate serial recall (average span = 2.3 items for word lists), had a superior auditory versus visual span and demonstrated a phonological similarity effect with aurally presented items. As a result, Martin and Lesch (1996) argued that despite ML’s reduced span, his capacity to retain phonological information was intact. However, despite the fact that ML has features in common with JH, these cases differ on a number of important dimensions: (1) ML appeared to have problems reading function words (see Martin & Lesch, 1996), (2) ML showed no phonological similarity effect with written input, and (3) ML’s span on the rhyme probe task constructed by Martin and co-workers was only three (see Martin & He, 2004). Whereas, JH’s span on the same task was six and it is of note that on consideration of published norms (Martin & He, 2004) his performance was within normal range (5–10) and (4) JH showed a length effect with both aurally and visually presented items a pattern that is never reported in patients with impaired phonological short-term memory (see Vallar & Papagno, 2002). As a result, we would argue that although both JH and ML share features in common, JH constitutes a ‘cleaner’ example of a case that refutes the potential accounts provided by the ‘triangle’ model. As a final point, we note that evidence of a letter length effect was consistently observed in JH’s non-word reading accuracy (but not in word reading). Which begs the question, is the presence of a length effect contingent on lexical status a finding that is consistent with an impairment of a non-lexical reading mechanism? Using his dual-route cascaded model, Coltheart (personal communication) provides evidence that supports such a possibility via manipulation of the parameter (known as the grapheme–phoneme-correspondence interletter interval) that dictates processing of the non-lexical route. For example, using the set provided by Weekes (1997), when this parameter was set at its default value (13 cycles), the model accurately read all word and non-word items. However, when this parameter was increased (20 cycles); (1) word accuracy remained 100%, but non-word accuracy dropped to 83%, (2) errors on non-words increased as a function of length (3 letters = 100%, 4 letters = 92%, 5 letters = 84%, 6 letters = 56%) and (3) a high proportion of these errors were lexicalisations (12/17).2 These data are therefore a good illustration of the fact that the kind of length effects seen in JH are at least in principle consistent with the predictions indicated by disruption of the serial non-lexical reading

2

We are very grateful to Prof. Max Coltheart for these illustrative data.

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mechanism in the dual-route cascaded model (Coltheart et al., 2001). The main point is that under the principles of the DRC model, length effects in word reading are by definition implicated by the non-lexical reading route. Hence, any disruption to the non-lexical mechanism will clearly result in a reduction of a length effect seen with words. The same would not be true of non-words, since they remain entirely dependent on the nonlexical reading route.3 It is also noteworthy that this is not the only way a pattern of phonological dyslexia can potentially be simulated within this model, other manipulations include, (a) delaying the onset of operation of the non-lexical route or (b) reducing the strength of activation of activation of the phoneme level. As a result, we intend to undertake further work, using behavioural testing and simulation studies, to explore the nature of JH’s non-word reading impairment with reference to the DRC model. This aspect has been somewhat neglected in investigations of phonological dyslexia (i.e. whether length effects are absent or present in non-word reading has not generally been tested). 3.2. Falsification of theories on the basis of single cases: the search for the ‘black swan’ One particular pursuit of Cognitive Neuropsychology has been the identification of cases with profiles that contradict those predicted by current theories; the detection of a so-called ‘black swan’ (referring to the axiom that “all swans are white” can be robustly falsified once one sees a single non-white swan). Nonetheless, the identification of such cases is for the most part a considerable challenge, given individual variability in premorbid performance, and the diffuse nature of the brain damage, with variable functional impairment as a consequence. Despite these challenges, we have argued that our findings do not fit the claim of a causal link between phonological impairment and poor non-word reading (the phonological impairment hypothesis) in phonological dyslexia and that JH is indeed a ‘black swan’. One criticism of the data may be that JH’s phonological dyslexia can be considered to be ‘mild’ (although as we have pointed out, his profile, both in terms of level of accuracy and type of non-word error is not out of line with some other cases of phonological dyslexia). Could it be that JH’s poor non-word reading is therefore a result of a phonological impairment that is so mild as to be undetectable on our tests? We have carried out a variety of segmentation, blending, rhyme and homophony tasks using materials that were at least as complex as those used in non-word reading, yet nonetheless we could find no evidence for a phonological impairment that might account for his non-word reading problem. These tests are ones that are in common currency and have been used to demonstrate phonological impairment in patients with phonological dyslexia whose 3

The reverse would be true in the event of word reading being dependent on the non-lexical reading route (as seen in surface dyslexia). In this case the DRC account would predict an increase in length effects for regular word reading relative to controls, such a pattern of performance has been reported in the literature (see Gold et al., 2005).

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non-word reading ability is commensurate with that of JH. We contend that the challenge for those supporters of the phonological impairment hypothesis is to clarify whether there are further tests that might be used with JH, and cases like him, otherwise the phonological impairment hypothesis becomes effectively unfalsifiable. The fact remains that JH is impaired at non-word reading, and therefore some kind of functional account must explain why he is poor at this task, but otherwise so good at a variety of other tasks that involve novel phonological codes. At present, no theoretical model provides a sufficiently fine-grained account of the relationship between degree of generalised phonological impairment (on the basis of measures like segmentation/blending) and consequential non-word reading impairment. This study demonstrates the importance of such a challenge for future models of reading and phonology.4 Acknowledgements We are most grateful to both JH and his wife for consenting to participant in this research, it was a pleasure and privilege to work with them both. We would like to thank Max Coltheart, Kathy Rastle and two anonymous reviewers for their helpful advice and comments relating to a previous version of this manuscript. We would also like to thank Wendy Best, Jess Craib, Rick Hanley, David Howard, Nadine Martin, Randi Martin, Lyndsey Nickels, Jo Walford and Brendan Weekes for providing the stimulus materials and data relating to various tests utilised with JH. References Baddeley, A. D. (1966). Short-term memory for word sequences as a function of acoustic, semantic, and formal similarity? Quarterly Journal of Experimental Psychology, 18, 362–365. Baddeley, A. D. (1968). How does acoustic similarity influence short-term memory? Quarterly Journal of Experimental Psychology, 20, 249–264. Baddeley, A. D. (2004). Working memory: Looking back and looking forward. Nature Reviews: Neuroscience, 4, 829–839. Baddeley, A. D., Lewis, V. J., & Vallar, G. (1984). Exploring the articulatory loop. Quarterly Journal of Experimental Psychology, 36, 233–252. Baddeley, A. D., Thomson, N., & Buchanan, M. (1975). Word length and the structure of short-term memory. Journal of Verbal Learning and Verbal Behaviour, 14, 575–589. Berndt, R. S., Haendiges, A. N., Mitchum, C. C., & Wayland, S. C. (1996). An investigation of non-lexical reading. Cognitive Neuropsychology, 13, 763–801. Bisiacchi, P. S., Cipolotti, L., & Denes, G. (1989). Impairment in processing meaningless verbal material in several modalities: The relationship between short-term memory and phonological skills. Quarterly Journal of Experimental Psychology, 41A, 293–319. Caccappolo-van Vliet, E., Miozzo, M., & Stern, Y. (2004a). Phonological dyslexia without phonological impairment? Cognitive Neuropsychology, 21, 820–839.

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It is noteworthy that the proposal of a theoretical model that posits a relationship between degree of impairment on segmentation, blending and non-word reading may already seem unlikely on the basis of the current facts. For example, returning to the original study by Patterson and Marcel (1992), on the basis of the case series they present, it is apparent that no such relation appears to exist (e.g. WBA their least impaired non-word reader was severely impaired on their segmentation and blending tasks).

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