the integration of information across lexical and sublexical

Q0421–CN2299 / Jan 7, 02 (Mon)/ [29 pages, 3 tables, 3 figures, 11 footnotes] – Disk edited- Phonetics
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.
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
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
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”
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
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
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
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.
Relationship between lexical and sublexical
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)
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
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
“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
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
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
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
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”
LEOPALD, “scissors”
Similarly, patient TP (Hatfield & Patterson, 1983)
produced errors such as “cough”
“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,
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
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).
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.
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
Pathological confirmation of the diagnosis was not available.
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
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-
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/
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
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
Written production
Writing to dictation
Hillis et al.
Primary testing period
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
”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
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,
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
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
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
implausible pseudowords such as “snoy”
S-O-N-I-A; “ghurb”
J-E-R-B; “murnee”
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”
(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
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.
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
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.,
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.
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
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
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-
Other examples include: “sergeant” -> SERGENT; “vein” -> VEIGN, VEINE; “kayak” -> CAYAK; “shrewd” -> SCHREWD;
“ceiling” -> SEILING; “caught” -> COUGHT; “echo” -> ECHOE.
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
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
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.
/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.
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
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”
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
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
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),
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
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/
vs. /m i z/
MEESE). For multisyllabic stimuli,
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,
Table 2. Examples of LAT’s PPE and pseudoword responses
Lexical base
(s) 2
(C) ER
(M) I
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%;
= correct lexical spelling;
= 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
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-
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.
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
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
correct mappings
High Probability
Low Probability
Syllable 1* Syllable 2
(N = 4551) (N = 2092) (N = 2459)
N equals the number of phoneme-grapheme elements
* 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
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.
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
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
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,
Our proposal differs from these interpretations
in that, although the graphemic layer serves the
buffering function of the Graphemic Buffer, the
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
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
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
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
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
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-
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—
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”
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”
COUGHT; “pirate”
TYPHUN. Similarly, JJ (Hillis &
Caramazza, 1991) spelled “whale”
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.
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.
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
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
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.
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
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.
This pattern is understood by assuming very severe damage to the semantic route, revealing the activity of an “isolated”
phonological route.
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
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)
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.
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.
Although we have proposed a mechanism for
lexical/sublexical interaction in spelling, our proposal is, as yet, only a sketch and a great deal of work
has yet to be done in understanding how lexical and
sublexical processes interact in spelling.
Manuscript received 3 June 1999
Revised manuscript received 6 April 2001
Revised manuscript accepted 9 April 2001
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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.
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.
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.