Q0421–CN2299 / Jan 7, 02 (Mon)/ [29 pages, 3 tables, 3 figures, 11 footnotes] – Disk edited- Phonetics COGNITIVE NEUROPSYCHOLOGY, 2002, 19 (1), 1–29 THE INTEGRATION OF INFORMATION ACROSS LEXICAL AND SUBLEXICAL PROCESSES IN SPELLING Brenda Rapp and Cathy Epstein Johns Hopkins University, Baltimore, USA Marie-Josèphe Tainturier University of Wales Bangor, UK We report on a brain-injured subject, LAT, who made phonologically plausible errors in word spelling (e.g., “bouquet” spelled as BOUKET). Although many of his errors are phonologically plausible they contained low-frequency (yet lexically correct) spellings (/ei/ spelled as ET in BOUKET). Because these errors are phonologically plausible they do not appear to have been generated by the lexical process, yet because they contain low probability, lexically correct elements they do not appear to be have been generated by the sublexical process. We present analyses that specifically support the conclusion that many of LAT’s phonologically plausible responses to word stimuli consist of the integrated output of elements generated by both the lexical and sublexical processes. This evidence constitutes strong support for the notion that lexical and sublexical processes share information during the course of spelling a familiar word. INTRODUCTION It is generally assumed that spelling involves (at least) two major sets of processes or “routes” for translating between phonology and orthography (e.g., Caramazza, 1988; Tainturier & Rapp, 2000). Typically one of these routes is referred to as the lexical process and the other as the sublexical or nonlexical process (see Figure 1). The former is assumed to contain the information required to relate phonological, semantic, and orthographic representations of words to one another, whereas the latter is assumed to encode the systematic relationships between phonemes and graphemes. Thus, lexical processes can be used to retrieve the spellings of familiar words, and sublexical processes can be used to assemble spellings for unfamiliar ones. Lexical processes operate over units at least the size of a morpheme, sublexical processes are generally thought to operate over smaller units. Although the existence of two systems with these general characteristics has been assumed in most written language research, there has been less consensus on questions concerning the specific nature of these systems and the relationships between them. In this paper we will be specifically concerned with the following question: Do lexical and sublexical processes interact or integrate information during the course of spelling? Requests for reprints should be addressed to Brenda Rapp, Cognitive Science Dept, Johns Hopkins University, Baltimore, MD 21218, USA (Email: [email protected]). This work was made possible with the support of NIMH grant R29MH55758 awarded to the first author as well as with the support of a grant from the Programme de Recherche de l’Agence pour les Sciences Sociales et Humaines, Région Rhone-Alpes (ARASSH) awarded to the first and third authors. We are grateful for the many very helpful comments and feedback on earlier drafts of this paper provided by Michael McCloskey and Jocelyn Folk. Our deepest appreciation goes to LAT and his wife, from whom we have learned many lessons, the least of which concern spelling. 2002 Psychology Press Ltd http://www.tandf.co.uk/journals/pp/02643294.html 1 DOI:10.1080/0264329014300060 RAPP, EPSTEIN, TAINTURIER Figure 1. Schematic representation of the functional architecture of the spelling system. The subject of this report, LAT, made phonologically plausible errors in word spelling; examples include: “bouquet” BOUKET; “certain” SERTAIN, “knowledge” KNOLIGE. This type of error is generally taken as an indication of failure of the lexical system and is considered to be the product of sublexical processing. In spelling to dictation, the lexical process is assumed to first map from lexical phonological representations to lexical semantic representations and then on to lexical orthographic ones. It is further assumed that the lexical system can retrieve the correct spelling of all familiar words, whether the phonemegrapheme relationships contained within the word are common (/t/ T as in CAT) or uncommon (/t/ BT as in DEBT). Difficulties with word spelling are an indication of a breakdown somewhere in the lexical system. It is worth noting that some investigators have posited an additional lexical process that is “direct and nonsemantic” and which maps phonology directly unto orthography with no semantic involvement (e.g., Patterson, 1986)1. Whether one or two lexical processes are 1 posited, what is important (for our purposes) is that although the lexical process/es will be sensitive to the frequency with which an individual has experienced a word-spelling as a whole, it/they should be insensitive to the frequency of phonemegrapheme mappings of which a word’s spelling is composed. Sublexical processes in spelling are thought to proceed from a segmentation of the phonological input to its translation into a plausible spelling via the application of stored knowledge of the regularities between phonology and orthography. This system outputs phonologically plausible spellings and is generally assumed to be more likely to produce common rather than uncommon spellings. As a result, the sublexical system is more likely to produce correct spellings for words with common (or high probability) phoneme-grapheme mappings than for words with uncommon (or low probability) mappings. Thus, “cat” is more likely to be spelled correctly by the sublexical system than is “debt.” Furthermore, debt is likely to be spelled by the sublexical system in a phonologically plausible manner (e.g., DET, DETT, or DEAT). What is interesting about LAT’s case is that he produced phonologically plausible errors that often contained elements that, at least at first glance, seemed unlikely to have been generated by the sublexical process. The italicised portions of the following errors—BOUKET, SERTAIN, KNOLIGE—correspond to very low-frequency (yet lexically correct) spellings of the phonemes in the target word. In brief, the puzzling aspect of many of LAT’s responses is that they do not appear to have been generated by either the lexical or sublexical process alone. In this report we will present analyses that specifically support the conclusion that many of LAT’s phonologically plausible responses to word stimuli consist of the integrated output of graphemic elements generated by the lexical and sublexical processes. In this way we provide support for the notion that lexical and sublexical processes share information during the course of spelling a familiar word (see also Ellis, 1982). In Figure 1 this would correspond to direct connections between entries in the Phonological Input Lexicon and the Orthographic Output Lexicon. 2 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) LEXICAL AND SUBLEXICAL PROCESSES Relationship between lexical and sublexical processes Various strands of evidence from normal and impaired spelling performance have been interpreted as indicating that lexical and sublexical processes are not entirely independent from one another. We review this evidence here (for a discussion of similar evidence in reading see Rapp, Folk, & Tainturier, 2000). Consistency effects Kreiner (1996) and Kreiner and Gough (1990) reported evidence of an interaction between “polygraphy” (the number of possible spellings of a word) and word frequency such that subjects had more difficulty with and took longer to spell highpolygraphy words (that often included lowprobability phoneme-grapheme mappings) vs. low-polygraphy words, but only when words were of low frequency. Such results have been considered to be problematic for an account that assumes two independent spelling processes because, it has been reasoned, if words can be spelled through the lexical process alone, then word spelling should not exhibit effects of variables such as polygraphy, to which the lexical system should be insensitive and which are typically assumed to be the hallmark of the sublexical process. To account for such findings, several authors (e.g., Barry, 1988; Kreiner, 1992, 1996; Kreiner & Gough, 1990) have made the general suggestion that lexical and sublexical processes, although not directly influencing each other, may interact at an output level. The higher difficulty in spelling high polygraphy would arise as a consequence of the fact that lexical and sublexical processes may derive conflicting responses when words have several plausible spellings. This conflict would increase the probability of errors and its resolution would increase spelling latencies. This would be particularly likely for low-frequency words if it is assumed that their lower frequency translates into slower lexical processing times which, in turn, provides more time for the sublexical process to generate conflicting outputs. Lexical influence on nonword spelling Several studies have shown that the specific spellings that subjects provide for unfamiliar spoken stimili (e.g., nonwords or pseudowords) can be influenced by the spellings of phonologically similar familiar words. For example, nonword spellings can be “primed” by the prior presentation of a rhyming word (Barry & Seymour, 1988; Burden, 1989; Campbell, 1983). That is, a spoken nonword such as /pri:t/ is more likely to be spelled PREET following the spoken word «sweet» and PREAT following «meat» than when it is presented following an unrelated word such as /k o t/. Similar results have been obtained in languages with almost entirely transparent orthographies like Spanish (Cuetos, 1993) and Italian (Barry & de Bastiani, 1997). Furthermore, this finding has been shown to hold even under more indirect priming conditions where the nonword is primed by a word that is only semantically associated with a potential prime (Dixon & Kaminska, 1994; Seymour & Dargie, 1990). For example, /b o p/ is more likely to be spelled as BOPE when it is preceded by «Vatican» (a semantic associate of POPE) and as BOAP when preceded by «detergent» (a semantic associate of SOAP). The fact that specific nonword spellings can be influenced by prior word processing has been interpreted as evidence that lexical and sublexical processes must interact in some way. Converging results supporting integration were obtained in French with unimpaired adults (Tainturier, Bosse, Valdois, & Rapp, 2000) and children of various ages (Bosse, Valdois, & Tainturier, 2001) using a paradigm that did not involve priming. In these studies, only nonwords were presented and participants were simply requested to write down each nonword using the first spelling that came to mind. Nonwords varied according to whether they did or did not have a close phonologically similar word neighbour with a low-probability mapping. Results showed that low-probability mappings were used more often in spelling nonwords with a close phonological neighbour than in spelling nonwords with no close neighbours. These results were interpreted as indicating that the presentation of a nonword stimulus serves to activate the spellings of close phoCOGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 3 RAPP, EPSTEIN, TAINTURIER nological word neighbours; these lexically generated spellings are then integrated with sublexically generated spellings in producing a response. Evidence of “summation” from patterns of impaired performance Hillis and Caramazza (1991, 1995) presented results from four brain-damaged subjects who showed better oral reading and/or spelling to dictation performance than would have been expected based on the level of functioning of either their lexical or sublexical processes alone. For example, JJ (Hillis & Caramazza, 1991) made 30–40% errors in spoken and written naming (and comprehension) of pictures from all semantic categories (except animals). His naming and comprehension errors were semantic errors (a picture of grapes named as “banana”). Yet, JJ’s ability to read words aloud and to spell them to dictation was largely preserved; crucially, this was true even for words with lowprobability spellings (e.g., sweater, stomach, moustache, etc.). The similarity in JJ’s comprehension and naming indicated that semantic processing was damaged in such a way that a set of semantically related responses rather than a single unique response was generated (e.g., a picture of a pear or the word PEAR may have yielded a semantic representation that was equally consistent with bananas, grapes, or pears). Given that in the task of written picture naming only the lexical process can be engaged (and in JJ’s case this was damaged at the semantic level), JJ erroneously named a picture of a pear as a banana. However, spelling to dictation differs from written naming in that both lexical and sublexical processes can be engaged. If, in dictation tasks, JJ relied only on the lexical process, he should have produced as many semantic errors as in written naming. Alternatively, if he relied only on the sublexical process, he should have produced phonologically plausible errors (e.g., “phone” spelled FONE). Hillis and Caramazza accounted for the absence of semantic errors in JJ’s writing to dictation (and oral reading) by assuming that JJ was able to combine the outputs of lexical and sublexical processes to eliminate semantic errors. They proposed that the information provided by the damaged lexical process 4 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) “summated” with information from the sublexical process to provide correct responses. For example, for the stimulus “pear” a sublexically generated output (e.g., PARE) could serve to select the most compatible item among a set of lexically generated candidates (e.g., banana, grapes, pear, etc.) (see also Miceli, Capasso, & Caramazza, 1994, 1999; Miceli, Giustolisi, & Caramazza, 1991). Further support for the summation hypothesis is provided by the performance of dysgraphic subject RCM, described in Hillis, Rapp, and Caramazza (1999). RCM produced semantic errors in spelling that were attributed to a post-semantic deficit that affected access to the Orthographic Output Lexicon. Consistent with a post-semantic (rather than a semantic) locus of impairment was the fact that RCM made no semantic errors in the spoken modality and had preserved word comprehension. RCM’s word and nonword spelling abilities were evaluated at two different times. At Time 1, she produced many semantic errors in both writing to dictation and in written picture naming. According to the summation hypothesis, semantic errors in spelling to dictation should have been eliminated (or nearly eliminated) by input from the sublexical system. Hillis et al. claimed that in RCM’s case this possibility was severely reduced because her sublexical spelling abilities were extremely poor. In fact, at Time 1 she spelled no nonwords completely correctly and only 42% of the individual target letters of the nonwords were present in her spelling responses. In contrast, by Time 2, RCM’s nonword spelling had significantly improved such that 67% of target segments were correctly spelled. Furthermore, by Time 2 she had started producing phonologically plausible responses to word targets (“leopard” LEPORD). Crucially, as predicted by the summation account, the improvement in sublexical spelling was accompanied by a reduction in semantic errors. RCM’s overall semantic error rate in spelling dropped from 56% (at Time 1) to only 10% (at Time 2). These results constitute strong evidence of some sort of interaction between lexical and sublexical processes. Hillis and colleagues did not propose a specific mechanism for lexical/sublexical interaction, they simply made the general claim that the LEXICAL AND SUBLEXICAL PROCESSES interaction is such that it allows for the information from the sublexical process to contribute to the correct selection in the Orthographic Output Lexicon (for spelling) among multiple candidates generated by the faulty lexical process. Evidence of “partial” lexical knowledge in spelling errors Several studies have reported the occurrence of spelling errors that were interpreted as showing access to “partial” lexical knowledge, suggesting some integration of lexical and sublexical knowledge. Seymour and Porpodas (1980) reported on a developmentally dyslexic adult who occasionally produced errors that were phonologically plausible yet contained a lexically appropriate, lowprobability element. For example, “hasten” spelled as HAISTEN or “muscle” spelled as MUCLE (the italic elements correspond to those elements with a possible lexical origin). Hanley, Hastie, and Kay (1992) presented a more detailed study of an adult developmentally dysgraphic subject who, they argued “relies upon the combination of sublexical phonology and a lexicon that contains only partial information about the way in which words are spelt” (p. 285). Although only a very few examples are presented, they include “autumn” spelled as AGHTUMN, “colonel” as CERONAL, “ought” as OGHT. Baron, Treiman, Wilf, and Kellman (1980) and Sloboda (1980) also reported a few such responses in normal spellers: “colonel” as COLORNEL, “pneumonia” as PNEWMONIA. With regards to acquired dysgraphia, a number of authors have reported errors that they argue indicate partial lexical knowledge, although they do not specifically propose lexical-sublexical integration (but see Ellis, 1982). Ellis, Miller, and Sin (1983) and Miller and Ellis (1987) described a subject whose errors, they claimed, resulted from a “ weak activation of lexical nodes”: “thumb” THUNB, LEOPALD, “scissors” SICESSE. “leopard” Similarly, patient TP (Hatfield & Patterson, 1983) produced errors such as “cough” COUFE; “sword” SWARD, and “shove” as SHROVE. In addition, Hughes, Graham, Patterson, and Hodges (1997) described DAT (Dementia of the Alzhei- mer’s Type) patients who primarily produced PPEs and occasionally produced responses that suggested partial lexical knowledge (e.g., “yacht” spelled as YATCH, “debt” as DEPT) (see also Beeson, 1998). Although at least some of these errors are indeed suggestive of an interaction between lexical and sublexical processes in spelling, there are a number of reasons why such a conclusion would be premature. A first concern regarding subjects with developmental disorders is that their errors may not be relevant to the study of the competent adult spelling system, nor even of normal spelling acquisition. A related concern is that some subjects with acquired deficits may have had developmental difficulties such that their spelling systems were abnormal before they suffered brain damage. For this reason it is important to have data regarding premorbid spelling abilities. Second, there is the possibility that errors that seem to reflect “partial lexical knowledge” may actually result from the disruption of orthographic representations at a late, post-lexical stage of processing. For example, damage to the graphemic buffer would give rise to letter substitutions, deletions, transpositions, and/or additions (Caramazza, Miceli, Villa, & Romani, 1987). Of the errors listed earlier, many of those that are not phonologically plausible are consistent with this type of deficit (e.g., transposition; “yacht” YATCH, substitution: “debt” DEPT). Note that under this alternative interpretation, the orthographic lexicon may have generated a fully correct spelling that was only subsequently altered, eliminating the reason to posit any kind of lexical/sublexical interaction. Third, in order to support a lexical-sublexical integration hypothesis, it is crucial to establish that the low-probability, yet lexically correct, elements that are observed in these spellings actually have a lexical origin. That is, it is necessary to establish that these elements could not have been generated by the sublexical process alone. For example, under some accounts the sublexical process occasionally generates low-probability spellings such as PN for the phoneme /n/ in initial position (as in pneumonia) or OU for the phoneme /O/ (as in cough). COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 5 RAPP, EPSTEIN, TAINTURIER Specifically, this would be expected under the position that the sublexical system encodes multiple spellings for each phoneme and that these are produced depending on their frequency of occurrence in the language (Goodman & Caramazza, 1986; Sanders & Caramazza, 1990). If so, then in some of the errors we may be seeing spellings produced entirely by the sublexical process rather than spellings that are a product of the integration of lexical and sublexical information. Summary of the literature review Our review of the literature reveals that several strands of evidence support the integration of information across lexical and sublexical processes in spelling. The finding of errors containing lowprobability elements of a lexical origin constitutes the most direct evidence for the integration of lexical and sublexical processes. However, none of the studies that report such errors have ruled out various alternative accounts of the findings they report. In the case study that follows we document an extensive number of PPEs containing lowprobability, lexically correct elements and also address the issues of: (a) premorbid writing status, (b) lexical vs. post-lexical locus of impairment, and (c) lexical vs. sublexical origin of low-probability elements. By addressing these issues in a satisfactory manner we are able to present a strong case for the integration of information from lexical and sublexical processes in spelling. CASE STUDY At the onset of this investigation (9/1994) LAT was a 78-year-old, right-handed man who had been diagnosed 2 years earlier with probable Alzheimer’s Disease (as defined by the NINCDS-ADRDA research task force; McKhann et al., 1984)2. LAT was a college graduate and a retired engineer. MRI scans at the time of diagnosis showed diffuse cortical atrophy and prominent ventricles as well as increased signal intensity in the periventricular 2 6 Pathological confirmation of the diagnosis was not available. COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) white matter. A SPECT scan showed generalised cortical hypoperfusion, especially affecting both temporoparietal regions, which was interpreted as consistent with AD rather than multi-infarct dementia. LAT lived at home with his wife until 8/ 1998; at that time he was placed in a nursing home where he remained until his death in 10/1998. Our investigation took place between 9/1994 and 5/ 1998; within this time we carried out a 10 month period of intensive testing from 9/1994 to 7/1995, which will be referred to as the “primary testing period.” General cognitive abilities Hillis, Benzing, Epstein, and Lyketsos (1995) evaluated and reported on LAT’s general cognitive abilities and other language skills. For the Hillis et al. project, LAT was evaluated repeatedly on a set of tasks over a 10-month period (5/1994–3/1995) that began 4 months before the onset of our investigation and ended before the end of the primary testing period. During the period of the Hillis et al. investigation LAT’s performance on the Mini-Mental Status Examination (MMSE; Folstein, Folstein, & McHugh, 1975) ranged from a high of 24/30 at the beginning of their study to a low of 21/30 at the end. During the subsequent 3 years, LAT’s general cognitive abilities, although not assessed formally, declined steadily and severely (as reported by family members and observed by BR). Overview of language comprehension and production abilities For the experimental investigation, LAT’s spelling abilities were studied intensively for the 10–months of the primary testing period (9/1994–7/1995) and were then re-evaluated yearly in 7–8/96, 4–6/1997, and 1–5/1998. Additionally, a number of other language tasks were administered at various points during the investigation. This paper will not be concerned with changes over time in LAT’s spelling abilities because (as will be seen below) these did not decline substantively until the final set of evalu- LEXICAL AND SUBLEXICAL PROCESSES ations in 5/1998. Nonetheless, before turning to a discussion of his spelling abilities, and in order to provide a broader picture of his various language abilities over the time-course of the investigation, we provide a brief overview of LAT’s spoken and written language production and comprehension performance (see Table 1). experienced some difficulties, particularly in the repetition of pseudowords. Regarding tasks specifically assessing comprehension, at the onset of the investigation LAT made no errors (42/42) on a task that required him to match a spoken word with one of three morphologically related written forms (e.g., “accumulated”: accumulated, accumulation, accumulate). Two years later (8/1996), LAT scored 94% (730/775) correct in a spoken word/picture verification task in which he simply had to say whether or not a spoken word matched with a (line drawing) picture. Although this score was only just below the normal range of elderly control subjects (95–100%), some of LAT’s errors were confusions concerning very common items (comb/brush, kite/balloon). Thus his performance at that point in time probably represented a diminution from premorbid levels of functioning. A subset of this task was readministered in 3/1998, by which time his performance had dropped substantially to 87% (223/257) correct. At this later time, LAT often struggled in coming up with a correct response and was often confused about part/whole, superordinate/subordinate relations. For example, when shown a picture of a fox and presented with the word “lips” he indicated that they matched and pointed to the animal’s mouth. Only if explicitly asked: “Does this entire Written language comprehension LAT’s written word comprehension was good whenever assessed although it was not evaluated beyond 7/1996. During the primary testing period LAT was administered: a written synonym matching task (N = 48), a written sentence comprehension task (N = 21), and written lexical decision (on three occasions, N = 140, 155, 273). His scores ranged from 90-99% on all of these tasks. In addition, when he was evaluated 2 years later (7/1996) with another written synonym matching task, his performance continued to be very good (96%, 115/ 120). Spoken language comprehension LAT’s ability to repeat single words and pseudowords was excellent (e.g., 60/60 in repeating morphologically complex words in 1/95) up until the final set of evaluations in 5/1998, at which time he Table 1. LAT’s performance on a range of tasks across the entire period of experimental testing Task Written comprehension Synonym match Sentence completion Written lexical decision Spoken comprehension Spoken/written word match Word/pix verification Defining spoken words Spoken production Pix naming Oral reading Words Pseudowords Written production Writing to dictation Words Pseudowords Hillis et al. Primary testing period 5/1994–3/1995 9/1994–7/1995 98 90 96–99 100 7–8/1996 4–5/1997 1–5/1998 96 94 87 93–97 90–98 98–100 90–98 72 67 96 90 46 52 70 88–93 93–98 83 95 86 91 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 65 61 7 RAPP, EPSTEIN, TAINTURIER picture correspond to the word lips?” was he able to respond correctly. Finally, LAT was asked to provide verbal definitions of a set of 97 words on eight occasions during the primary testing period. On each trial, he first had to repeat the word, then provide a definition, and finally he was asked to write the word down (see Experimental Study for details on the stimuli used and the spelling data). As indicated earlier, his repetition abilities were excellent, but if he did make an error, the stimulus was presented until he was able to correctly repeat it. Three independent judges scored his definitions as good, fair, or poor. Definitions that at least two of the three judges gave a rating of “poor” to were considered to be incorrect. LAT provided excellent definitions for almost all of the words. As indicated in Table 1, across the eight test administrations (N = 776), 95% of his definitions were scored as correct. His definitions were not simply adequate: they were, in fact, remarkably good, for example: “A martyr is someone who will sacrifice himself for a particular concept,” “Knowledge is the accumulation of important information,” “A faucet is a device for controlling the flow of liquids.” Of the small number of items scored as incorrect, half were vague definitions (survey: “survey is to develop the size or ability of an object”), one fourth were definitions in which the target word itself was used in the definition (straight: “straight indicates movement from one place to another on a straight line”), and the remaining errors consisted of trials on which he said he didn’t know, simply repeated the target word or provided information that the judges deemed to be clearly wrong (autumn: “autumn is spring time of the year”). These clearly incorrect responses occurred on only four items. Oral reading During the primary testing period LAT was asked to read regular words, irregular words, and pseudowords. LAT scored 96% (43/45) correct in reading words, making one visually similar word confusion (FRAUD ”Freud”) and one regularisation error (THESE / iz/). With pseudowords he was 90% (45/50) correct, making only visually similar word confusions (e.g., GREE “green”). This same list 8 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) was readministered 3 years later (4/1998). By that time his performance had worsened markedly: word reading accuracy was 52% (23/45) and pseudoword reading accuracy was 70% (35/50). His error profile remained quite similar, however, with mostly visually similar word responses and only three regularisation errors. At this later date there was a clear effect of lexical frequency, highfrequency words 73% (11/15) correct vs. lowfrequency 40% (12/30); 2 = 4.45, p < .05, but no effect of regularity, regular: 53% (16/30) vs. exceptional: 47% (7/15); 2 = 0.18, p > .05. It is noteworthy that LAT’s reading contrasted markedly with his spelling. In particular, the regularisation errors that were the hallmark features of his spelling were largely absent from his reading. In this regard, LAT was different from a number of DAT subjects who have been described as manifesting characteristics of both surface dyslexia and surface dysgraphia (Graham, Patterson, & Hodges, 1997). Spoken naming Hillis et al. (1995) reported relatively stable accuracy rates (90–98%) for LAT in spoken picture naming during 1994-95. Errors were predominantly other items from the same semantic category as the target (pix orange “apple”; pix sheep “cow”) with occasional “don’t know” responses accompanied by the target’s superordinate (pix snail “some kind of animal, can’t think of it”). However, his naming accuracy had deteriorated to 72% (182/254) when we tested him 2 years later with a large set of line drawings taken from Snodgrass and Vanderwart (1980); his errors were similar to those observed earlier. One year later (5/1997), his performance had further deteriorated to 67% accuracy (173/258). Errors again largely consisted of superordinate responses and coordinate errors, although the rate of circumlocutions and vague responses had considerably increased. Finally, LAT was tested with a subset of these items during the last evaluation period (3/1998). At that point his performance was only 46% correct (52/114) and, in addition to the types of errors made in earlier sessions, LAT also produced phonologically similar word and LEXICAL AND SUBLEXICAL PROCESSES nonword responses (pix kite /g aI t/; pix chisel “chicken”) and a number of perseverative responses. Written production LAT wrote with his dominant right hand, and he was asked to print in upper case, something he did fluently and extremely legibly. On each trial, LAT was asked to repeat a dictated stimulus before and after spelling it. On the few occasions when he apparently misheard a stimulus, it was repeated by the tester. As mentioned earlier, his repetition was excellent (until the final test administration, at which time he sometimes incorrectly repeated pseudowords or apparently forgot a stimulus by the time he had finished spelling it). Typically, LAT produced written responses without struggle or hesitation; he seemed confident of his responses and would rarely change them (again, except during the final testing sessions). He would often orally spell as he was writing and during the primary testing period LAT’s oral and written spelling responses were almost always identical. At later testing dates, however, he would occasionally make letter substitutions in written spelling while simultaneously correctly spelling the target orally (e.g., for the word “twin” he correctly said T-W-I-N while writing T-W-I-M). When this occurred he was given credit for his correct oral spelling responses. Presumably these errors in written spelling were due to occasional difficulties in retrieving the forms of letters—difficulties at the level of converting abstract grapheme representations to letter form representations (see Rapp & Caramazza, 1997). Consistent with this, LAT’s written letter substitutions typically involved letters with similar forms (M/N, W/Y, F/T, H/E). By the last testing evaluation in 5/1998, written spelling had become so difficult that LAT switched entirely to oral spelling. Effects on spelling of lexicality, grammatical category, word frequency, and PG probability LAT’s initial spelling evaluation with the JHU Dysgraphia Battery (Goodman & Caramazza, 1986) indicated that there were no significant effects of grammatical category, abstractness, or word length. However, there appeared to be effects of word frequency and PG probability. These effects were examined by administering the Phoneme-Grapheme Probability List of the JHU Dysgraphia Battery 3 times during the Primary Testing Period and yearly in the subsequent 3 years (for a total of six administrations). This list consists of 30 words containing only high-probability phoneme-grapheme mappings (mean mapping probability = 66.3; Hanna, Hanna, & Hodges, 1966) and 80 words containing at least one low probability mapping (mean mapping probability = 3.63). Half of the words in each list are high-frequency words (mean = 195; Carroll, Davies, & Richman, 1971) and half are low-frequency words (mean = 7) and lists are matched for mean letter length. LAT’s overall spelling accuracy for these words remained relatively stable (83–93% correct) until the final test administration in 3/1998, when accuracy dropped to 65% correct. At all individual administrations of this list, LAT spelled words containing only high PG probability spellings better than words containing low PG probability spellings (80–100% correct vs. 59–90% correct). In addition, high-frequency words were spelled better than low frequency words on five of six administrations (67–96% vs. 72–94%). When the data are combined across all six administrations (see Figure 2), there is a highly significant overall effect of regularity, X2 = 21.08, p < .05, but not of frequency, X2 = 3.38, p >.05. There is an interaction between word frequency and probability such that low-frequency, low-probability words were always spelled with lowest accuracy. Interestingly, the interaction was such that probability effects were significant for both high and low-frequency words, respectively X2 = 6.06 and 17.70, p <.05, but frequency effects were significant only for low-probability words, X2 = 4.25, p < .05. Quite striking was LAT’s high rate of phonologically plausible errors (PPEs). A response was scored as phonologically plausible whenever the spelling assigned was a possible spelling of the phoneme according to Hanna et al. (1966). Scoring was lenient with respect to context such that a spelling was considered to be phonologically plausible if it was plausible within some orthographic context COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 9 RAPP, EPSTEIN, TAINTURIER implausible pseudowords such as “snoy” S-O-N-I-A; “ghurb” J-E-R-B; “murnee” N-U-R-N-I-E. Figure 2. Effects of frequency and PG mapping probability on the Phoneme-Grapheme Probability List of the JHU Dysgraphia Battery (collapsed across six administrations). (e.g., “kept” spelled as CEPT would be acceptable because /k/ C is acceptable ignoring the context of the subsequent vowel). Examples of LAT’s PPEs include: “pursuit” P-E-R-S-U-T-E; “pretty” P-R-I-T-Y; “leopard” L-E-P-E-R-D. PPEs (as a proportion of his total errors) decreased across the 6 administrations—from 100, 92, 90, 84, 73, to 61%. It is likely that, in the later stages of the illness, additional spelling mechanisms were affected by the disease as indicated by the fact that he increasingly produced errors other than PPEs; these included letter deletions, substitutions, and transpositions as well as perseverations of single and multi-letter groups from earlier responses. He made no semantic or morphological errors and only two similar word errors were produced (e.g., “flat” FLAP) during the entire period. As can be seen in Table 1, in contrast to his spelling of words, LAT’s spelling of pseudowords (the characteristics of the pseudoword stimuli are reported under the description of the experimental task) remained excellent until the very final testing session (see Table 1). His errors in pseudoword spelling consisted entirely of phonologically 3 Locus of impairment As indicated in the Introduction, with respect to the question of lexical/sublexical integration, it is important to establish a lexical locus of damage. Spelling performance with the characteristics exhibited by LAT—good pseudoword spelling accompanied by regularity and frequency effects in word spelling as well as PPEs—indicates damage somewhere along the lexical procedure (see Figure 1). Specifically, damage to the sublexical procedure is ruled out by the good nonword spelling. Furthermore, LAT’s excellent nonword spelling also makes it unlikely that post-lexical processes, such as the graphemic buffer, contributed significantly to the PPEs observed in word spelling. Although it is admittedly extremely difficult to assess the integrity of semantic representations, LAT’s excellent definitional skills strongly suggest that his semantic representations were largely intact (at least during the primary testing period when definitional skills were assessed). This indicates that his PPEs in spelling arose primarily, if not exclusively, from difficulties in making contact with stored lexical graphemic representations in the Orthographic Output Lexicon. As would be expected under a deficit locus involving the Orthographic Output Lexicon, LAT typically provided an excellent definition followed by a PPE. For example, “Seize is to grab. S-E-A-Z-E”; “Knowledge is the accumulation of important information. K-N-O-L-E-G-E”; “Bouquet is a group of flowers. B-O-U-K-E-T”. This inability to retrieve stored lexical spellings could result from damage at the level of the Orthographic Output Lexicon itself or from a failure in getting from fairly intact lexical semantic representations to this lexicon3. In conclusion, we can be confident that, at least until the final testing admin- In a theory that assumes an additional direct, nonsemantic lexical spelling route there could be an (additional) deficit affecting his ability to go from an intact phonological lexicon to the orthographic lexicon. Alternatively, since the Orthographic Output Lexicon is shared by both lexical routes, damage to the Orthographic Output Lexicon would affect spelling through either route; in that case, a second lesion would not need to be posited. 10 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) LEXICAL AND SUBLEXICAL PROCESSES istration in 5/1998 (when LAT’s pseudoword spelling abilities declined significantly), LAT’s PPEs mainly resulted from a deficit to the lexical system, in all likelihood affecting his ability to gain normal access to information in the orthographic lexicon. Premorbid spelling In the Introduction we indicated that it is essential to establish that spelling errors result from the neurological damage rather than premorbid lack of knowledge of word spellings. In order to make this determination, we examined several pages of notes LAT had taken concerning jobs and errands from 1992 and earlier. These pages only contained 1 error out of 206 words (a transposition: STRIAGHTEN), a clear indication of LAT’s good premorbid spelling abilities. In order to specifically determine if the spelling errors we observed during this investigation reflected a change in LAT’s spelling abilities, we asked him to spell subsets of the words (many containing low-probability PG mappings) from this premorbid corpus. He was tested on one subset early in the investigation and on another at the very end in 7/1998. LAT was 85% correct (17/20) on the first list, with two of the three errors being phonologically plausible spellings of words that he had correctly spelled in the premorbid corpus (e.g., “addition” A-D-I-T-I-O-N). By the later testing date, LAT’s spelling had deteriorated considerably and he was only 55% accurate (36/65). Although by this time the error types were more varied, nonetheless 12 out of 29 of the errors were PPEs (e.g., “letter” L-E-A-T-E-R; “stuff ” S-T-U-F). In sum, these results indicate that the spelling errors observed during the investigation are not likely to have originated in a pre-morbid lack of knowledge of the spellings of words but were largely, if not entirely, attributable to the neurological damage LAT suffered. EXPERIMENTAL STUDY As indicated in the Introduction, LAT produced a number of PPEs that seemed unlikely to have been the product of the sublexical process alone because they included low probability yet lexically correct segments: “bouquet” spelled as BOUKET, “autumn” as AUTOMN, “knowledge” as KNOLIGE4. We argued that errors of that sort would constitute strong evidence of the integration of lexical and sublexical processes, if the following were established: (a) intact premorbid writing, (b) a lexical locus of impairment, and (c) a lexical origin for the low-probability elements. Having dealt with the first two issues, we are now in a position to turn to the third and primary question: What is the source of the lexically correct, low-probability elements in LAT’s phonologically plausible errors? As indicated earlier, the fact that LAT’s PPEs included mappings that are very frequent in the language (/k/ K in BOUKET/) is unsurprising, because it is expected from a sublexical process. It is unsurprising given either the assumption that the sublexical process generates only the most frequent PG mappings or that it generates PG mappings probabilistically in accordance with their frequency in the language (Goodman & Caramazza, 1986; Sanders & Caramazza, 1990). What is more surprising, under either view of the sublexical process, is the frequent production of PG mappings (such as /ei/ ET—“bouquet” BOUKET) that have a far lower frequency in the English language than other mappings (such as /ei/ AY). Under an integration hypothesis, the low-probability mappings (/ei/ ET ) originate largely within the lexical process, whereas the higher probability mappings (/k/ K) are generated by the sublexical process. The alternative to the integration account is that the sublexical process generated both the low and the high PG mappings. In order to rule this out, it is not enough to simply show that LAT employed low-probability mappings in his PPEs more fre- 4 Other examples include: “sergeant” -> SERGENT; “vein” -> VEIGN, VEINE; “kayak” -> CAYAK; “shrewd” -> SCHREWD; “ceiling” -> SEILING; “caught” -> COUGHT; “echo” -> ECHOE. COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 11 RAPP, EPSTEIN, TAINTURIER quently than would be expected given the published frequencies of mappings. One reason why this is insufficient is that it is possible that LAT’s sublexical process might have had frequency “settings” that were different from those reported in the norms. The norms are based on sampling different types of texts (e.g., science fiction, novels, newspapers, etc.) to varying extents. This allows for the possibility that the normative data may not accurately characterise an individual’s exposure to text. One could imagine that an individual might have had a somewhat different exposure to text types than that presupposed in the norms (e.g., engineers to math and physics texts and journals) or have been subjected to other idiosyncractic influences (exposure to foreign languages). Whether or not such experiences would alter the PG mapping probabilities is not known, but it is something one could be concerned about. More importantly, it is also not enough to simply show that LAT used low-probability mappings more often in his PPEs than in his pseudoword spellings. Although this would certainly be an interesting finding 5, it would not specifically support a lexical origin for the low-probability segments. Clear support for a lexical origin requires establishing that the PPEs are more likely than pseudowords to contain lexically correct, low-probability mappings. That is, both EA (as in BREAK) and EI (as in VEIN) are lower probability spellings for the sound /ei/ than is AI (as in PAIN) (p = .01 for EA and EI vs. p = .18 for AI). However, only EI would be the lexically correct spelling of the phoneme in a word such as WEIGH. To determine if LAT’s sublexical process could have been the source of the low-probability mappings observed in his PPEs, we compared LAT’s use of low-probability mappings in his PPEs with their use in his spellings of matched pseudowords. To do so we administered a list of words and matched pseudowords that was designed so that LAT’s spellings of the pseudowords could serve as an index of the rate at which his sublexical process generated specific low-probability pho5 neme-grapheme correspondences. We reasoned as follows: If LAT’s PPEs were generated entirely by the sublexical process, mappings such as /ei/ ET should be produced at comparable rates in his spelling of pseudowords such as /l u k ei/ and in his PPEs for words such as “bouquet.” If, on the other hand, LAT’s PPEs were generated from some combination of the outputs of the lexical and sublexical spelling processes, then we would expect that spellings such as /ei/ ET should be produced at higher rates in his PPEs than in his spellings of matched pseudowords. Stimuli A list of matched word and pseudoword stimuli was developed. The word list included 97 stimuli, 37 monosyllabic and 60 multisyllabic. Each word contained at least one low probability PG mapping (e.g., /n/ KN as in KNOWLEDGE; /f/ GH as in LAUGH; /i/ EO as in PEOPLE; /E/ AI as in CERTAIN; /EI/ ET as in BOUQUET). High-probability PG mappings were considered to be those that occurred with a probability of .9 or higher in Hanna et al. (1966); low PG mappings were those with a probability lower than .9. The PG mapping probabilities used were Hanna et al.’s (1966) position-specific probabilities. This measure corresponds to the probability with which a phoneme is spelled in a particular manner given the syllable position (initial, medial, final) of the phoneme. For each one-syllable word stimulus, there was a matched pseudoword that differed from the word by only one phoneme (e.g., “heart”/h Ar t/ matched with /l Ar t/; “seize”/s i z/ matched with /m i z/). For each two-syllable word stimulus, there were two matched pseudowords, each differing from the word by only one phoneme. For one of the two pseudoword control items, the first syllable was identical to that of the target word; for the other, the second syllable was identical to the second syllable of the target word (e.g., “knowledge” /n O - l @ dZ/ matched with /n O -p @ dZ/ and It might suggest that the person has encoded the word as having some unusual spelling although information regarding the particular spelling was unavailable. 12 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) LEXICAL AND SUBLEXICAL PROCESSES /p O - l @ dZ/; “people” /p i - p @ l/ matched with /p i - f @ l/ and /f i - p @ l/). There were a total of 157 pseudowords (37 monosyllabic and 120 multisyllabic), bringing the list total to 254 word and pseudoword stimuli. Procedures This list of 254 items was administered 14 times during the primary testing period and 4 times in the subsequent 3 years (see Appendix A for specific dates). Words and pseudowords were presented in mixed lists that were constituted such that matched words and pseudowords (“knowledge” and /n O -p @ d Z) were never presented in the same testing session. Testing sessions were separated by a minimum of 3 days and most typically by a week. LAT was asked to repeat each stimulus before writing it. As indicated earlier, his repetition abilities were excellent, but if he did make an error, the stimulus was presented again until he was able to repeat it correctly. Additionally, on 8 of the first 10 test administrations (administrations 2, 3, 4, 6, 7, 8, 9, and 10) LAT was asked to define each stimulus after repeating, but before spelling, it (the results of the definition task were presented earlier). General results In Appendix A we present word and pseudoword accuracy rates for each of the 18 test administrations as well as the rate of PPEs as a proportion of total errors. Because LAT’s performance was relatively stable until the final test administration, we exclude administration 18 from all further analyses and collapse data across the remaining 17 administrations. Throughout the 17 test administrations, LAT’s pseudoword accuracy remained high, with a mean of 95% and a range of 90–99%. His word accuracy remained fairly stable, with a mean of 53% and a range of 37–62%. As was already seen earlier, LAT’s errors were overwhelmingly phonologically plausible, with PPEs making up 91% of his errors to word stimuli (range: 82–98%). In fact, LAT’s PPE rates mirrored his pseudoword accuracy rates quite closely. It is important to note that throughout the entire testing period LAT’s PPEs were produced in a seemingly effortless manner. That is to say, he did not struggle over these responses, nor did he leave gaps that were later filled in. The errors that were not PPEs were almost entirely phonologically implausible pseudowords (“shrewd” SCHUDE; “knuckle” KNUCKE). During the entire testing period he produced only four semantic errors (e.g., “knowledge” INFORMATION) and three formally similar word errors (e.g., “scheme” SCENE). In addition, LAT’s spelling of the words in this experimental list exhibited the same overall effects of frequency and PG probability as were observed in his spelling of the PG list from the JHU Dysgraphia Battery, reported earlier. The data from the experimental list were scored according to the accuracy individual phoneme spellings (rather than the accuracy of the entire word, as was done earlier). Results reveal that phonemes in highfrequency words (mean word frequency = 142) were spelled significantly more accurately than phonemes in low-frequency words (mean word frequency = 3.3): 89% vs. 82%, X2(1) = 32.4, p < .001. Furthermore, high-probability PG mappings (mean mapping probability = .97) were spelled more accurately than low-probability PG mappings (mean mapping probability = .25): 98% vs. 77%, X2 (1) = 246.4, p < .001. Despite the fact that LAT’s performance was fairly stable in terms of overall accuracy and rate of PPE production, there was nevertheless a high degree of variability when responses to individual items are considered. With regard to word stimuli, LAT’s spelling performance was variable across items both in terms of accuracy as well as in terms of the particular PPEs that he produced. In terms of accuracy, each word was produced correctly on an average of 8.7/18 occasions (5 words were correct 18 times, 11 were correct 17 times, 12 were correct 16 times, and 13 were never spelled correctly; there was a fairly even distribution for the remaining 56 items that were spelled correctly between 1 and 15 times). In terms of the consistency of the specific PPEs, LAT produced an average of 4.1 different spellings for the 75 words for which he produced more than COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 13 RAPP, EPSTEIN, TAINTURIER one PPE. For example, LAT produced 15 PPEs in response to “knowledge.” These PPEs included 10 different spellings: NOWLIGE, KNOWLIGE (4 times), KNOLIGE (2 times), KNOLIDGE, NOLIGE (2 times), KNOLEDGE, NOLIDGE, NOLAGE, KNOWLIDGE, and KNOWLAGE. With regard to pseudoword stimuli, LAT’s spelling was highly accurate but there was, nonetheless, considerable variability in the specific responses produced. For each pseudoword stimulus LAT produced an average of 4.1 different responses. For example, /s i r s/ was spelled correctly 16 times, with 9 different spellings: SEIRCE (2 times), SERSE (2 times), CEARCE, CERSE (3 times), CIRCE, CERCE, SEARCE (2 times), SEERS, SERES (2 times). Relationship between comprehension and spelling accuracy As indicated earlier, comprehension and spelling of words was assessed on eight of the test administrations. His comprehension of these words, as indicated by his definitions, was excellent (95% correct). If we specifically compare comprehension accuracy for words misspelled vs. words correctly spelled we find that they did not differ: There were 5.1% errors for words spelled incorrectly and 5.6% errors on words spelled correctly. Results regarding the integration hypothesis In this analysis we compared LAT’s spelling of each of the phonemes within each of his PPEs with his spelling of the identical phonemes in each of the matched pseudowords in terms of whether or not they conformed to the lexical spelling. For monosyllabic stimuli we compared the specific spellings LAT produced for those portions of the words and pseudowords that were identical and for multisyllabic stimuli we compared the spelling of identical syllables. For example, if LAT generated a PPE for the word /s i z/ (e.g., SEAZE) we compared his spellings of the phonemes in the word that overlapped exactly with the phonemes of the matched pseudoword (e.g., /si z/ SEAZE vs. /m i z/ MEESE). For multisyllabic stimuli, 14 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) we only compared the spellings of phonemes in identical syllables. For example if “knowledge” resulted in a PPE (e.g., /n O - l @ dZ/ KNOWLIGE) we compared LAT’s spelling of the first syllable of the PPE (/n O - l @ dZ/ KNOW) with the spelling of the first syllable of the matched nonword (/ n O - p @ dZ/) and we compared the spelling of the second syllable of the PPE (/n O - l @ dZ/ -LIGE) to the spelling of the second syllable of the other matched nonword (/p O - l @ dZ/). In this way with multisyllabic stimuli we were able to compare the spelling of identical phonemes in identical syllables in PPEs vs. pseudowords. For this analysis we only included PPE and pseudoword responses produced on the same test administration (recall also that words and their pseudoword controls within the same test administration were never presented within the same testing session). In examining LAT’s spellings we categorised all of the PG mappings according to whether they corresponded to high- or low-probability mappings in the word stimuli. PG mappings with a probability of .9 or higher were considered to be highprobability mappings and those with a probability lower than .9 were considered to be low-probability mappings. For example, the PG mapping probabilities for each of the phoneme-grapheme mappings in “knowledge” (/n a- l @ dZ/ are as follows: /n/ KN (p = .3); /a/ OW (p = .003); /l/ L (p = .94); /@/ E-E (p = .03); /dZ/ DG (p = .13) Thus, whereas the mapping of /n/ KN has the probability .03 (low), the mapping of /l/ L has the probability of .94 (high). An architecture that allows for the integration of information between lexical and sublexical processes (1) predicts similar use of high probability, lexically correct spellings (such as /l/ L) in both PPEs and pseudowords (which would be expected under an integration or a nonintegration hypothesis) and (2) makes the specific prediction that the use of low probability, lexically correct spellings (e.g., /ei/ ET) might be greater in PPEs than in pseudowords. Table 2 illustrates our scoring procedure and provides specific examples of LAT’s apparently differential use of low-probability lexically correct mappings in PPEs and pseudowords. For instance, LEXICAL AND SUBLEXICAL PROCESSES Table 2. Examples of LAT’s PPE and pseudoword responses Lexical base PPE: “bouquet” (b) o (B) k Pseudoword: ei (B) OU QU ET | | | lp lp lp “certain” (s) 2 t @ n (C) ER | hp T | hp AI | lp N | hp “militia” (m) l I S a (M) I | lp L | hp I | lp TI | lp A | hp (S) (M) (L) OU | K | ET | ER | T | AI | N | L | I | TI | A | hp = high probability mapping (>.9); lp = low probability mapping (<.9); we see that both in the PPE he produced in response to the word /b ou k ei/ (BOUKET) as well as in his spelling of the matched pseudoword /l ou k ei/ (LOKAY), LAT spelled the phoneme /k/ as K, using a high-frequency mapping that is not “lexically correct”.6 In contrast, he spelled the phoneme /ei/ with the low-probability, lexically correct spelling of ET in the PPE, but used the higher probability mapping, “lexically incorrect” AY to spell the pseudoword. The results of the analysis are very clear (see Table 3). LAT’s use of high-probability lexically correct PG mappings for high-probability targets (e.g., /l/ L) occurred at similar rates in his PPEs and in his spelling of matched pseudowords, 96% vs. 95%; 2 (1) = 0.80, p >.36. Crucially, however, he was significantly more likely to use low probability, lexically correct spellings (e.g., /n/ KN) in his PPEs than in matched pseudowords, 51% vs. 36%; A | O K | | AY | (F) ER | T | I | N | (K) A | L | I | SH | = correct lexical spelling; A | = incorrect lexical spelling. X2 (1) = 65.6, p < .0001.7 These results were very stable across the 17 testing sessions (see Appendices B and C for the results of individual test administrations). Importantly, further analyses reveal that this difference between PPEs and pseudowords is robust across a wide range of low PG mapping probabilities. Recall that the data from low-probability mappings reported in Table 3 corresponds to phoneme-grapheme mappings whose “lexical” spellings have PG probabilities of less than .90. However, if we consider PG mapping probabilities of less than .20, we also see the same significant difference between PPEs and pseudowords. At this level, LAT’s PPEs contain 30% lexically correct, low-probability elements, whereas matched pseudowords contain only 14% of these elements, X2 = 58.9, p <. 0001, N = 1689. We again observe the same results if we drop down to mapping probabili- 6 Of course, pseudowords do not have “lexically correct” spellings; we refer to the specific spelling that appears in the lexical base as the lexically correct spelling. 7 The Ns were not always identical for the PPEs and the pseudowords because the matched pseudowords were occasionally misspelled. However, as indicated earlier, such errors were rare and this had no effect on mean PG mapping probabilities for the two categories. COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 15 RAPP, EPSTEIN, TAINTURIER Table 3. LAT’s use of high-probability (mean probability = .97) and low-probability (mean probability = .28) lexically correct PG mappings in his PPEs and pseudoword spelling Lexically correct mappings High Probability PPEs Pseudowords Low Probability PPEs Pseudowords TOTAL Syllable 1* Syllable 2 (N = 4551) (N = 2092) (N = 2459) 96% 95% 97% 99% 95% 94% 51% 36% 50% 34% 52% 38% N equals the number of phoneme-grapheme elements analysed. * This category collapses all monosyllabic stimuli as well as the first syllable of multisyllabic stimuli. ties below .10. Within this range, LAT’s PPEs contained 27% lexically correct, low-probability elements, while his pseudowords contained only 13%, X2 =48.1, p < .0001, N =1514. Thus, although as PG mapping probabilities fall the overall rate of lexically correct, low-probability elements drops in both PPEs and pseudowords, the PPEs nonetheless retain their advantage over pseudowords. It is also worth noting, as can be seen in Table 3, that we also observe the same results whether we consider the spellings in syllable 1 or syllable 2. Syllable 1 combines spelling responses from monosyllabic stimuli with the first syllable of multisyllabic stimuli. The results here are virtually identical to those obtained for the data set as a whole, with lexically correct, high-probability spellings occurring at comparable rates for PPEs and pseudowords, X2 = 2.3, p >.1, whereas lexically correct, low-probability spellings occur at significantly higher rates for PPEs vs. pseudowords, X2 = 36.6, p < .0001. More importantly, syllable 2 data allow us to compare LAT’s spelling choices in identical syllables: the second syllable of his PPEs (/s2 - t n -/ SERTAIN) vs. the same phonemes in identical syllables in matched nonwords (/f2 - t n / FERTIN). The syllable 2 results reveal that, even for phonologically identical syllables, LAT’s PPEs were more likely to include low-probability, lexically correct spellings than were his pseudowords, X2 = 29.2, p < .0001. In sum, we see that LAT used low-probability, lexically correct mappings approximately 15% more 16 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) often in his PPEs than he did in his spellings of pseudowords (regardless of how we define low probability). With regard to our question: What is the source of the apparently lexically correct, lowprobability elements in LAT’s PPEs?, the answer seems to be: These spellings originate outside the sublexical process and, presumably, within the lexical spelling process. GENERAL DISCUSSION Our analyses show that LAT was more likely to include lexically correct, low-probability PG mappings in his phonologically plausible spellings of words than in his phonologically plausible spellings of pseudowords (e.g., “bouquet” BOUKET, but “louquet” LOKAY). To account for this phenomenon, we have proposed an architecture of the normal spelling system in which lexical and sublexical processes both contribute to the spelling of a stimulus. We further assume that, in LAT’s case, his neurological condition has resulted in a weakened contribution of the lexical process. Specifically, we assume that the contribution of the lexical process is sufficiently weak that PPEs are produced yet, nonetheless, sufficiently strong that it allows lexically correct elements to sometimes emerge within the PPEs. We now turn to considering the mechanisms that might underlie this integration. Mechanisms of integration Although the findings we have reported strongly support the notion of lexical/sublexical integration, they do not reveal the details of the mechanism/s that allows for this combination of information from these two processes. The data would seem to be generally consistent with various accounts. For example, acccording to one possible class of accounts (which we can refer to as the “fill in the gap” type accounts) the lexical system first produces a graphemic representation that is incomplete (with gaps) and the sublexical process then provides plausible content for these gaps (e.g., Miceli, Silveri, & Caramazza, 1987). Although it is worth noting that LEXICAL AND SUBLEXICAL PROCESSES LAT never overtly produced this type of response (leaving gaps that were later filled in), this does not rule out the possibility that the internal processes operate in a gap-filling manner and that LAT simply produced the output that was generated after the internal gap-filling had been completed. Another class of accounts (that we can refer to as “simultaneous activation” type accounts) assumes that both lexical and sublexical processes simultaneously activate candidate graphemes, that their activation summates, and that the most strongly activated candidates are selected for output. Under such an account, if lexical activation is weak relative to sublexical activation, then the candidates activated by the sublexical system may sometimes be selected. Presumably, other approaches to the integration issue are also possible. In the following section we will develop one version of the “simultaneous activation” type account. We should make it clear that we pursue this particular approach to integration not because the data specifically support it over an alternative (such as the “fill in the gap” approach), but because we find it computationally appealing and because one instance of this approach has been implemented and explored in computer simulation work by Houghton and Zorzi (2001). A specific proposal Our proposal for a specific mechanism of integration is represented schematically in Figure 3. In order to account for a range of facts relating to integration we make two critical assumptions: (1) along with Houghton and colleagues (Glasspool, Houghton, & Shallice, 1995; Houghton & Zorzi, 1998, 2001), we propose that lexical and sublexical processes integrate information at a grapheme layer and (2) that there is feedback from the graphemic layer to the lexeme nodes of the orthographic output lexicon (McCloskey, Macaruso, & Rapp, 1999). The first assumption will form the basis for our interpretation of LAT’s performance; the two assumptions jointly will provide an interpretation of the results reported by Hillis and Caramazza (1991, 1995) and Hillis et al. (1999), which were reviewed in the Introduction. Integration at the graphemic layer We assume that the graphemic layer consists of a structured array of graphemic elements that encode grapheme identities, number (doubling information), and order (and possibly other features such as CV status, syllable position, etc.) (for empirical justification see Caramazza & Miceli, 1990, and McCloskey, Badecker, Goodman-Shulman, & Aliminosa, 1994). These graphemic elements may correspond to single letters and/or digraphs—the empirical data are unclear regarding unit size and our claims about the integration mechanism do not depend on a particular position on this question. At the heart of the account is the proposal that in spelling to dictation, both the lexical and sublexical processes are simultaneously engaged by a phonological stimulus and that both “vote for”—or activate—candidate graphemic elements from a common pool of elements. The fact that both processes activate the very same set of elements allows for a relatively straightforward mechanism for integration of information from the two processes. This mechanism has been implemented computationally in Houghton and Zorzi (2001) and we describe the implementation in somewhat greater detail later. This differs somewhat from the usual interpretation of the relationship between the Orthographic Output Lexicon/PG Conversion System/ Graphemic Buffer as presented in Figure 1. The architecture in Figure 1 is usually taken to represent the position that the Orthographic Lexicon and the PG Conversion System respectively address and assemble orthographic representations that are then maintained active by the Graphemic Buffer while subsequent processes work on the information in a serial manner. Specifically, the Graphemic Buffer is seen either as a working memory structure to which orthographic information is sent or, alternatively, as a shared process that serves to maintain the activation of orthographic representations, whether they are generated by the Orthographic Output Lexicon or the PG Conversion System (Caramazza et al., 1987; Ellis, 1982). Our proposal differs from these interpretations in that, although the graphemic layer serves the buffering function of the Graphemic Buffer, the COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 17 RAPP, EPSTEIN, TAINTURIER Figure 3. Schematic representation of the proposed functional architecture of the spelling system that allows for lexical/sublexical integration. graphemic layer is not a structure to which orthographic representations are sent, nor is buffering seen as a process shared by the lexical and sublexical processes that acts over their individual and independent outputs. According to our proposal, the Orthographic Output Lexicon of Figure 1 would correspond in Figure 3 to the orthographic lexeme nodes and their relationships with the 18 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) graphemes—thus, in Figure 3, the Orthographic Lexicon is embodied in the connections between the two layers. In turn, the Graphemic Buffer of Figure 1 would correspond to the process/processes that maintain/s the activation of the graphemic layer of Figure 3 during the course of subsequent processing. One might argue that this constitutes a possible interpretation of the theory depicted in LEXICAL AND SUBLEXICAL PROCESSES Figure 1. If so, then Figure 3 simply serves as a depiction that renders this particular interpretation somewhat more explicit. Integration at the graphemic level raises significant questions concerning the manner in which activation from the two processes is combined and how correct outputs are generated. One important consideration is that, in the undamaged system, the lexical source of activation must prevail. This may be accomplished by having the lexical system cast a stronger “vote” or a more rapid vote (Houghton & Zorzi, 2001) or it may be accomplished through the grapheme-lexeme feedback connections that may serve to stabilise and amplify lexical contributions over sublexical ones. In a system with these characteristics, if damage is such that the lexical contribution is weakened, we may see the pattern reported for LAT. We assume that in such a case, the deficient lexical activation may be insufficient to boost the activation of all of a word’s graphemes. Whether a grapheme will be activated sufficiently for selection will depend on the degree of the lexically-based “support” for the grapheme, the degree of sublexical support, and the strength of competing graphemes. Importantly, the weaker the lexical contribution, the less likely we are to observe low-probability, lexically correct elements in a subject’s PPEs. Thus, this proposal predicts that individuals with mild damage to the lexical process may produce PPEs containing considerable lexically generated content and which differ substantially from comparable pseudowords (as in LAT’s case). In contrast, individuals with very severe damage to the lexical process should produce PPEs containing precisely the same range of mappings observed in their responses to pseudowords. In this way, the proposed mechanism of integration not only accounts for the previously reported results but also makes predictions concerning the characteristics of PPEs that should be produced under different conditions of damage. At least in some cases it may be possible to have an independent measure (aside from the spelling performance itself) of the extent of damage to the lexical process. For example, when the lexical deficit arises from damage to the semantic system, measures of semantic integrity may serve to index the integrity of the lexical route—greater semantic damage should be accompanied by a lower rate of low-probability, lexically correct elements in the PPEs . Further studies will be required to determine if these predictions are, in fact, supported. Simulation exploration As part of a far larger project, Houghton and Zorzi (2001), tested this proposed account of LAT’s errors using a PDP connectionist simulation of a spelling theory. The implemented theory is similar to that represented in Figure 3 although, most relevant for our purposes here, their simulation does not include grapheme-lexeme feedback connections. Houghton and Zorzi assumed two routes— lexical and phonological (PG)—that both activate a common set of graphemic elements. The graphemic elements correspond to the single and multi-letter graphemes that map onto the phonemes of English (e.g., C, H, W, T, O, I, etc. as well as CH, WH, OO, IE, QU, TCH, etc.) The graphemic elements are grouped into onset, vowel, and coda categories (with three onset positions, one vowel position, and three coda positions). The response of the network involves selecting the most active grapheme at each position. The sublexical route is a two-layer network that is trained (in isolation form the lexical route) on all monosyllabic uninflected words of English. After training, the network’s performance on the training set yielded 81% correct performance, with errors occurring only on exception and inconsistent words, which were regularised. In addition, testing with nonwords yielded only plausible spellings. The lexical route was implemented simply as a modified Orthographic Output Lexicon in that one lexical unit (the target) is selected and sends activation to all graphemes that it contains and inhibition to those it does not. Lexical frequency is implemented by differences in the speed with which lexical nodes send activation to their constituent graphemes. Grapheme nodes sum, over time, the inputs they receive from the two routes and there is also lateral inhibition among grapheme nodes competing for the same output position. Using an intact simulation of both routes working simultaneously, the authors were able to obtain the frequency by regularity interaction effects COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 19 RAPP, EPSTEIN, TAINTURIER reported for unimpaired subjects (Kreiner, 1996; Kreiner & Gough, 1990). In addition, Houghton and Zorzi simulated a damaged lexical system by running the simulation with the two routes but reducing the asymptotic strength of the lexical activation. Under those conditions, they observed errors similar to LAT’s phonologically plausible errors that included lowprobability, lexically correct elements. For example “tough” was spelled as TUGH, “lymph” as LYMF, etc. They determined that these spellings were not the product of the PG system by comparing the responses produced when the two routes were running simultaneously with the lexical route damaged, to the responses that were generated when the simulation was run with the PG system operating in total isolation. When the PG system operated in total isolation, the phonologically plausible responses consisted of high-probability graphemes—“tough” spelled TUFF, “lymph” spelled LIMF, etc. Although this indeed shows that the phonological route, acting alone, does not select lowfrequency, lexically correct graphemes, it could still be the case that the low-probability elements (/f/ GH) were, nonetheless, more strongly activated by word stimuli than by matched pseudowords in an isolated PG system. To evaluate this possibility, Houghton and Zorzi compared the activation levels of low-frequency, lexically correct graphemes, for word vs. matched pseudoword stimuli, in the isolated PG system. They found no differences. This provides further support for the claim that, in the damaged system, the low-frequency, lexically correct elements (in responses such as TUGH) originated in the lexical route. Thus, this computational work serves to confirm our prediction that a dual-route spelling system that assumes a “simultaneous activation” type account of the integration of lexical and sublexical outputs will, at least under certain circumstances, generate the types of errors produced by LAT. Grapheme-lexeme feedback connections The second modification to the architecture in Figure 1 that we propose is the incorporation of feedback connections from the grapheme layer to the 20 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) lexemes (depicted in Figure 3). It is beyond the scope of this paper to review in any detail the independent empirical motivation for positing these connections (but see McCloskey et al., 1999). Briefly, however, the evidence and arguments presented by McCloskey et al. are similar to those that have been put forward in support of feedback in the context of lexical bias effects in normal spoken word production (Baars, Motley, & MacKay, 1975; Dell & Reich, 1981). Briefly, McCloskey et al. report on a brain-damaged subject with a deficit that was identified as originating at the grapheme level. Specifically, the deficit involved the persistence of graphemes beyond the trial on which they were produced. Interestingly, this individual produced a great number of incorrect spelling responses that were other real words (e.g., “blow” BOLT, “fit” FILTER). The crucial aspect of the pattern is that analyses revealed that such real word responses occurred at rates much higher than would be expected by random errors at the grapheme level in a system lacking grapheme-lexeme feedback. Thus, in order to account for the errors, McCloskey et al. posited grapheme-lexeme feedback connections. For our purposes here, what is relevant is that the joint assumptions of integration at the grapheme level and feedback from graphemes to lexemes allow us to provide a specific account of the spelling results reported by Hillis and Caramazza (1991, 1995) and Hillis et al. (1999) that were described in the Introduction. Recall that subject JJ (Hillis & Caramazza, 1991) produced many semantic errors in written picture naming (a task that relies on the lexical process) but was able to spell correctly many of the same words in writing to dictation (a task that allows for integration between lexical and sublexical processes). Hillis and Caramazza showed that JJ’s ability to spell highly irregular words was modulated by the extent of the contribution of the lexical process, as independently indexed by his comprehension level of stimulus words. Irregular words that he understood well were spelled correctly and irregular words that were not comprehended at all were spelled incorrectly. Crucially, however, irregular words that were only partially comprehended were, nonetheless, spelled correctly. Hillis and Caramazza (1991) claimed that as long as the lexi- LEXICAL AND SUBLEXICAL PROCESSES cal and sublexical processes were somewhat intact, then “summation” of information from these two sources allowed for the selection of the correct orthographic lexeme8. Similar evidence for the contribution of sublexical processes to lexical selection was provided by RCM (Hillis et al., 1999). Recall that in this case, it was shown that the number of semantic errors in spelling decreased as RCM recovered her sublexical spelling abilities. According to the integration-feedback proposal just described, orthographic lexeme selection may be influenced both by semantically driven activation and by activation from the feedback grapheme-lexeme connections. In certain cases of lexical damage, semantically based activation may create a situation in which multiple, semantically related orthographic lexemes are activated without any clear “leader” (a picture of a leopard leads to lexeme-level activation of LEOPARD, LION, TIGER, JAGUAR). In that case, the activation of graphemes by the sublexical process may play a decisive role. In this example, the sublexical process is likely to have activated the graphemes L-E-P-ER-D. If this graphemic activation is fed back to the orthographic lexeme level, then it will tip the activation balance in favour of the correct lexeme— LEOPARD. In summary, the dual assumptions of lexical/ sublexical integration at the grapheme level combined with grapheme-lexeme feedback allow us to account for a wide range of observations and make a number of predictions. We are not claiming that other accounts might not do as well, however we have not attempted to contrast the adequacy of our account with others because specific alternative accounts have not yet been proposed. Additional relevant findings Other subjects exhibiting possible “integration” effects LAT is the first case that has been studied specifically to determine if PPEs may include a combina- tion of elements generated by both the lexical and sublexical spelling processes. However, a closer examination of some of the other published cases suggests that others may have produced errors similar to those of LAT. In addition to the cases reviewed in the Introduction where the authors explicitly mentioned the possibility of partial lexical knowledge, other reports include examples of PPEs that look as though they might contain elements generated by both lexical and sublexical processes. For example, MW (Goodman & Caramazza, 1986) produced the following responses: “while” WHYLE; “caught” COUGHT; “pirate” PYRATE; “typhoon” TYPHUN. Similarly, JJ (Hillis & Caramazza, 1991) spelled “whale” WHAYLE; “thief” THIEFE. Another case is that of the French subject RG, whose nonword spelling was 100% correct (Beauvois & Derouesné, 1981). Consistent with a deficit affecting stored lexical orthographic knowledge, RG’s comprehension was good, his word spelling exhibited an effect of orthographic ambiguity and word frequency, and his errors to words were always PPEs. RG also produced errors that suggest lexical-sublexical integration: “gentil JENTIL; “éléphant” ELEPHAN. In addition, a reanalysis that we carried out on the published data suggests that RG’s use of lexically correct, lowfrequency PG mappings in his PPEs was higher than would have been expected based on their frequency of occurrence in French words. For example, the mapping /a/ EN was used in 18/19 of RG’s PPEs (.94) in response to words whose spellings including this mapping, whereas its probability of use in the French language is only .47. We also found this to be true of various other phonemegrapheme mappings that occurred frequently in RG’s PPEs. Although these various results are clearly expected under an integration account, in none of these cases were sufficient data available to permit the analyses required to determine if the lowprobability elements actually had a lexical origin. 8 They argued that it was not necessary to postulate a third direct route for spelling since the full pattern of results could be understood within a dual-route account that allows for some sort of summation of information from the two routes. COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 21 RAPP, EPSTEIN, TAINTURIER Lexical influences on pseudoword spelling The proposal just outlined, which allows for the activation of lexical information to influence phonologically plausible responses to word stimuli, can also account for the lexical influence on the spelling of pseudowords in unimpaired spellers that was described in the Introduction. However, in order to account for these results we require two additional assumptions: First, that hearing a pseudoword activates phonologically similar words in the Phonological Input Lexicon (although not as much as hearing an actual word) and, second, that the activation generated by these word neighbours can be transferred down to the grapheme level. Given these two assumptions, a pseudoword stimulus may yield lexically based activation of graphemes that will be available for integration with PG-based activation. This provides a mechanism for the “lexical” influence on the spelling of pseudowords. For example, when the pseudoword “lokay” is heard it will activate the sublexical system which, in turn, may strongly activate the graphemes LOKAY and weakly activate the graphemes of LOQUET, LOUKET, etc. In addition, the auditory stimulus “lokay” may also activate phonological word neighbours in the Phonological Input Lexicon such as “bouquet.” This (presumably relatively weak) lexically based activation would favour the graphemes BOUQUET. Typically the strongest grapheme candidates will be selected for output and LOKAY should be produced; occasionally, however, the lexically based activation might tip the balance in favour of some of the lower-frequency spellings and LOQUET may be produced. This lexical influence should be most evident with pseudowords that are highly similar to other words of the language—the finding reported by Tainturier et al. (2000). Thus, the architecture we propose predicts that the spelling of pseudowords that are highly similar 9 to words may be influenced by the spelling of close word neighbours. In our analyses of the origin of low-probability, lexical correct elements in LAT’s PPEs, we assumed that the spelling of the pseudowords is carried out by the sublexical process alone. We did so because this assumption worked against our test of the integration hypothesis9. We should, however, also be able to find some evidence of lexical influence on LAT’s pseudoword spellings—just as was found for the unimpaired subjects in Tainturier et al. (2000). We examined this with a task adapted from that of Tainturier and colleagues. A list of 60 triplets was developed, each triplet consisted of: (a) a word containing one or more low-probability PG mappings (e.g., ELITE) (for a total of 70 target low PG mappings), (b) a “near” pseudoword that differed from the word by only one phoneme (e.g., /ou l i t/), and (c) a “distant” pseudoword that differed from the near pseudoword by only one phoneme but which did not have any close word neighbours (e.g., /æ r i t/). Given the results of the experimental task reported earlier, we, of course, should expect the low-probability “lexical” elements to be more frequent in LAT’s PPEs than in his spellings of the near pseudowords. Additionally, this list allowed us to examine if these elements would also be more frequent in near vs. distant pseudowords. The results we obtained indicate that lowprobability, lexically correct elements were observed in 14 of LAT’s PPEs and in only 6 of his responses to the “near pseudowords” (/ou l i t/ OLITE)—replicating the results reported for the experimental task. In addition, the low-probability, lexically correct elements appeared in only 2 of his responses to “distant” pseudowords (e.g., /æ r i t/ ARITE)—contrasting with the 6 occurrences in response to the near pseudowords. Although the sample size is small, these findings are like those reported by Tainturier and colleagues with unim- That is, if the lexical process actually makes some contribution to the spelling of pseudowords then the rate of /n/ KN in PPEs to “knowledge” and in pseudowords very similar to “knowledge” should be more similar than if the lexical process made no such contribution. Therefore the finding of greater use of lexically correct, low-probability PG mappings in PPEs than in pseudowords could only lend support to the integration hypothesis. 22 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) LEXICAL AND SUBLEXICAL PROCESSES paired subjects, and would be expected under an integration account10. Could the low-probability mappings observed in LAT’s PPEs have originated within the sublexical process? The last issue we will consider is the possibility that the low-probability mappings observed in LAT’s PPEs could have somehow originated within the sublexical process, despite the fact that they were produced more frequently in his PPEs than in his pseudoword responses. To examine this it will be useful to consider a spelling system “equivalent” of the theory of reading proposed by Plaut, McClelland, Seidenberg, and Patterson (1996). Following up on work by Seidenberg and McClelland (1989), Plaut and colleagues proposed a theory of reading (sometimes referred to as the “triangle model”) that assumes distributed representations and posits two reading “routes”—a “semantically mediated” one that maps orthographic inputs through semantics and then on to phonology and a “phonological” route that maps orthography onto phonology. In contrast to the more traditional accounts of reading (e.g., Coltheart, Curtis, Atkins, & Haller, 1993), Plaut et al. proposed that in the “normal” unimpaired reader the phonological route (in many ways comparable to the PG conversion system) encodes the information necessary for reliably generating correct pronunciations for irregular words. However, they also proposed that the accuracy of the phonological route with irregular words will decrease with decreasing lexical frequency. This conclusion was driven by the need to account for the performance of individuals exhibiting severe difficulties in correctly reading low-frequency, irregular words who were, nonetheless perfectly able to read pseudowords—surface dyslexics11. If we draw an analogy to spelling from this work in reading, we might be concerned that in LAT’s case the lexically correct, low-probability elements actually originated from the sublexical system and were available only for the higher-frequency irregular words and not for lower-frequency ones. In order to examine this we computed LAT’s rate of lexically correct, high and low PG mappings in his PPEs in response to high- and low-frequency words (mean lexical frequency of 142 and 3.3, respectively) and matched pseudowords. The results were identical to those observed for the data set as a whole: (1) regardless of word frequency, PPEs and pseudowords do not differ in the percentage of lexically correct, high-probability PG elements they contain, 91% for both PPEs produced in response to high-frequency words and matched pseudowords; 98% and 96% for PPEs produced to low-frequency words and matched pseudowords; X2 = 0.13, p > .05 and X2 = 3.3, p > .05, and (2) lexically correct, low-probability PG elements are observed more often in PPEs vs. pseudowords; this difference was observed whether the PPEs were produced in response to low- or high-frequency words, 46% vs. 31% for high-frequency words vs. matched pseudowords and 53% and 38% for lowfrequency words vs. matched pseudowords; X2 = 18.3, p < .0001 and X2 = 47.1, p < .0001. A potentially more important concern, given the distributed nature of the representations in the Plaut et al. proposal, is the possibility that the sublexical process may be sensitive to a fairly wide “contextual window” in its representation of phoneme-grapheme relationships. At one end of the space of possibilities regarding contextual window size is a window size of one phoneme, at the other end is a window size of an entire word. With a window size of a single phoneme the sublexical process maps single sounds onto corresponding letter/s (e.g., /k/ K, /ei/ AY). In that case it should produce the same spelling for a letter whether it is in 10 Again,we do not mean to suggest that our proposed architecture is the only one that could account for such effects, simply that it does predict the findings that we observed. 11 This pattern is understood by assuming very severe damage to the semantic route, revealing the activity of an “isolated” phonological route. COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 23 RAPP, EPSTEIN, TAINTURIER a word (“bouquet”) or a pseudoword (/l o k ei/). At the other extreme, if the sublexical process is highly sensitive to the entire string context then it should come up with the correct spelling of even highly irregular words (e.g., it will know that /t/ is spelled CHT in the context /y a t/). An intermediate possibility regarding window size, however, is that the sublexical process is sensitive to contexts larger than the single letter and yet smaller than the entire word. Thus, perhaps the sublexical system encodes mappings for units such as /k ei/ QUET (as in “bouquet” or “parquet”). If so, it may represent not only /k/ K and /ei/ AY but also /k ei/ QUET. In that case, the sublexical process may produce different spellings for the same phonemes when they occur within word vs. pseudoword stimuli. The critical question becomes: How large a contextual window is necessary in order to account for the differences in LAT’s spelling of PPEs and matched pseudowords? Recall that the effect is observed even if we only consider PPEs containing syllables identical to the syllables of the control pseudowords (Table 3, Syllable 2). Furthermore, in the pseudoword controls not only are the critical syllables identical, but the other syllables are identical except for one phoneme. In order to argue that the low-probability, lexically correct elements within LAT’s PPEs are generated by the sublexical process, one would have to argue for a window size larger than a single syllable and virtually the size of the entire word. There are several problems with this proposal. First, there are no computationally explicit theories of spelling that process multisyllabic words. In the context of reading, the Plaut et al. simulation only operates over monosyllabic words. Indeed, there is only one theory of reading that proposes a specific solution to the problem of multisyllabic words (Ans, Carbonnel, & Valdois, 1998). Second, and more importantly, if we assume a window size that encompasses the entire word, then we are left without an explanation of LAT’s errors: If his sublexical system encodes the spelling of words with lowfrequency PG mappings, then why/how does LAT produce PPEs at all? In this regard it is worth remembering that (again, in the context of reading) 24 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) Plaut and colleagues specifically concluded that the GP system does not encode the spellings of lowfrequency, irregular words precisely because such a system could not be damaged in a way that maintained accurate processing of pseudowords. The remaining possibility, therefore, is a contextual window size that is just slightly smaller than the whole word. Although this is a logical possibility, clearly further work—most likely computational work—will be required to investigate it. CONCLUSIONS In summary, we have documented a pattern of spelling performance in which lexically correct, low-probability spellings appear at higher rates in a neurologically injured subject’s phonologically plausible spellings of words than in his spellings of highly similar pseudowords. In documenting this pattern we have been able to dismiss concerns raised regarding previous similar reports. That is, we have established that LAT had good premorbid spelling, a lexical-level deficit and that, indeed, the source of these low-probability elements is likely to have been lexical. These findings are consistent with, and in many ways stronger than, various other lines of evidence supporting the notion of lexical/ sublexical integration. 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APPENDIX A Accuracy and word errors LAT’s accuracy on words and nonwords as well as the proportion of his word errors that were PPEs for each of the 18 administrations of the experimental list. COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 27 RAPP, EPSTEIN, TAINTURIER APPENDIX B Use of high-probability PG mappings The percentage of times that LAT used lexically correct, highprobability PG mappings in his spelling of the phonemes of the pseudoword stimuli and in his phonologically plausible errors to the matched word stimuli. Results are presented for each of the 17 administrations of the experimental list that were included in the overall analysis. 28 COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) LEXICAL AND SUBLEXICAL PROCESSES APPENDIX C Use of low-probability PG mappings The percentage of times that LAT used lexically correct, lowprobability PG mappings in his spelling of the phonemes of the pseudoword stimuli and in his phonologically plausible errors to the matched word stimuli. Results are presented for each of the 17 administrations of the experimental list that were included in the overall analysis. COGNITIVE NEUROPSYCHOLOGY , 2002, 19 (1) 29
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