119

Behavioural Neurology 16 (2005) 119–144
IOS Press

Multiple levels of letter representation in
written spelling: Evidence from a single case
of dysgraphia with multiple deficits
Marie-Pierre de Partza,b,∗ , Aliette Lochya,c,d and Agnesa Pillon a,c
a

Université Catholique de Louvain, Belgium
Centre de Revalidation Neuropsychologique des Cliniques Universitaires Saint-Luc, Bruxelles, Belgium
c
Fonds National de la Recherche Scientifique, Belgium
d
F.C. Donders Centre for Cognitive Neuroimaging, Nijmegen, the Netherlands
b

Abstract. In this paper, we report a detailed analysis of the impaired performance of a dysgraphic individual, AD, who produced
similar rates of letter-level errors in written spelling, oral spelling, and typing. We found that the distribution of various letter error
types displayed a distinct pattern in written spelling on the one hand and in oral spelling and typing on the other. In particular,
noncontextual letter substitution errors (i.e., errors in which the erroneous letter that replaces the target letter does not occur
elsewhere within the word) were virtually absent in oral spelling and typing and mainly found in written spelling. In contrast,
letter deletion errors and multiple-letter errors were typically found in oral spelling and very exceptional in written spelling. Only
contextual letter substitution errors (i.e., errors in which the erroneous letter that replaces the target letter is identical to a letter
occurring earlier or later in the word) were found in similar proportions in the three tasks. We argue that these contrasting patterns
of letter error distribution result from damage to two distinct levels of letter representation and processing within the spelling
system, namely, the amodal graphemic representation held in the graphemic buffer and the letter form representation computed
by subsequent writing-specific processes. Then, we examined the relationship between error and target in the letter substitution
errors produced in written and oral spelling and found evidence that distinct types of letter representation are processed at each
of the hypothetized levels of damage: symbolic letter representation at the graphemic level and representation of the component
graphic strokes at the letter form processing level.
Keywords: Acquired dysgraphia, graphemic buffer, letter substitution errors, grapheme, letter form, letter stroke

1. Introduction
What kinds of letter representation are involved in
the process of written spelling? That is, what kinds
of letter information have to be processed in order to
convert the knowledge of how a word has to be spelled
into actual lines and curves drawn on a piece of paper? At least two distinct levels of letter representation and processing are assumed within current cogni∗ Corresponding author: Marie-Pierre de Partz, Centre de revali-

dation neuropsychologique, Cliniques universitaires Saint-Luc, 10,
Avenue Hippocrate, 1200 Bruxelles, Belgium. Tel.: +33 2 764 17
76; Fax: +33 2 764 9046; E-mail: departz@orlo.ucl.ac.be.

tive models of the writing system [19,25,30,41]: first,
amodal (i.e., modality-independent) graphemic representations, subserving both written and oral spelling,
and including information about the identity and position of the graphemes within the word; second, abstract (i.e., effector-independent) representations of letter form, involved in written spelling only, and specifying information required to assign a specific form to
graphemes. Here we report the case study of a dysgraphic individual, AD, whose pattern of performance
and errors in written and oral spelling can be described
as resulting from damage to each of these letter representation levels, thus providing additional support for

ISSN 0953-4180/05/$17.00 © 2005 – IOS Press and the authors. All rights reserved

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M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

the representational distinction assumed within these
models.
The assumption that the writing system includes
multiple and distinct representations of letter information, is drawn from detailed analyses of the impaired
spelling performance of dysgraphic subjects. With reference to a hypothetical functional architecture of the
spelling process, such as the one depicted in Fig. 1,
these analyses first aimed at localizing the deficit of
the subjects to one or more components within the architecture. This was achieved by contrasting the subjects’ performance in several spelling tasks (e.g., copy,
writing on dictation, oral spelling, etc), each task being
supposed to recruit a distinct set of functional components. Then, the characteristics of the subjects’ errors
were used to draw inferences about the kind of representations that are processed at the level of the affected
component (see [9,45] for arguments in favour of this
methodological paradigm that uses data from impaired
performance to constrain normal processing theories).
The hypothetical functional model depicted in
Fig. 1 – which also informs the single-case study presented here – first distinguishes between the representations and processes involved in spelling familiar
words and those used to generate plausible spellings
for unfamiliar items. Thus, the spelling of familiar
words may be retrieved by first accessing their meaning and then their corresponding lexical orthographic
form stored in the orthographic output lexicon. Plausible spellings for unfamiliar items (for which there is
no stored orthographic representation) can be generated by relying on knowledge of phoneme-grapheme
correspondences and applying sublexical phonologyto-orthography conversion (POC) procedures. Representations resulting from either lexical or sublexical
POC processing are assumed to consist of a sequence
of amodal graphemes that are held in a temporary memory system – the graphemic buffer – while their corresponding letter forms or names are being processed by
the subsequent, modality-specific, mechanisms dedicated to either written or oral spelling [8,19,30,31,39].
Thus, in written spelling, the amodal graphemes are assigned a specific form (case, font, and shape), which are
then written down through execution of neuromuscular
commands. In oral spelling, the amodal graphemes are
converted into the phonological representations corresponding to their letter names, which in turn activate
articulatory programs to speak them aloud [31]. Let us
add that, although little is known in relation to typing,
modality-specific mechanisms dedicated to this modality of spelling output may be assumed, which would

specify, for example, information about the letter location on the keyboard together with, possibly, the appropriate digit to reach it.
Neuropsychological evidence supporting the existence of an amodal level of letter representation and
processing is provided by numerous reports of patients
producing similar rates and kinds of errors in both
oral and written spelling, for both words and nonwords (e.g. [2,5–7,11,13,17,26–28,32,34,35,37–39,43,
44,46]). These patients’ spelling errors in both modalities of spelling and for both words and nonwords were
analysable as the consequence of incorrect selection or
ordering of individual letters, i.e., letter substitutions
(e.g., STUDY → STUTY), deletions (e.g., DISCOVERY → DICOVERY), additions (e.g., PORCELAIN
→ PORCERLAIN), and transpositions (e.g., NIGHT
→ NIGTH). Moreover, in most of these case reports,
spelling accuracy was not affected by lexical factors
like word frequency, age of acquisition, imageability,
and orthographic neighbourhood size, which suggested
that the impairment was located at a representation
and processing level that follows access to the orthographic representations stored in the lexicon (but see,
for discussion [6,43]). This amodal letter representation and processing level was further conceived of as a
temporary memory system – a graphemic buffer – on
the basis of two characteristic features of the patients’
spelling performance: spelling errors occurred with increased frequency as a function of the stimulus length
and did not distribute evenly across the various letter
positions in the stimulus. In some patients, the errors
were mostly located at the end of the words, which
could reflect a left-to-right read-out process operating
over a too rapidly decaying memory trace [27,44]. In
other cases, the errors mostly involved letters in the
middle of the words [7], which was accounted for by
the letters in internal positions being subjected to interference from more neighbour letters than the letters
located at extreme positions [52].
Further to these patients whose pattern of spelling
performance suggested damage at an amodal level of
processing, patients have been reported with damage
likely due to modality-specific mechanisms dedicated
to either written or oral spelling: some patients were
unable to retrieve the name of the graphemes present
in a word or nonword, while being perfectly able to
write down the same items (e.g. [10]); others were
impaired in written spelling, while their performance
in oral spelling was relatively spared (e.g. [1,3,4,15,18,
22–24,29,36,40,42,49,53]).
As regards the specific mechanisms involved in written spelling, Ellis [19] and Margolin [30] put forward

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121

Auditory input

Phonological
Input Lexicon

Semantic
System

Phonological
Ouput Lexicon

Phonological
Buffer

Orthographic
Output Lexicon

Sublexical
POC

Graphemic
Buffer

Letter Form

Letter Name

WRITTEN
SPELLING

ORAL
SPELLING

Letter
Location

TYPING

Fig. 1. Schematic depiction of the cognitive architecture of the spelling system (POC = Phonology-to-orthography conversion procedures).

the hypothesis that amodal graphemes are assigned
form by two distinct and successive processes (Fig. 2).
First, letter shapes are retrieved from a long-term “allographic store” representing letter shapes in terms of
their visuospatial features. At that level, a specific
shape among the various variants or allographs of a
given grapheme is selected, for example, the lowercase
“a” or uppercase “A”, or the corresponding cursive or
print shape. It is at the subsequent level, the “graphic
motor pattern” level, that the sequence of strokes required to write down the selected allograph is retrieved.
Letter information, at this level, thus includes the direction, relative size, position, and order of strokes required to give a written form to a given allograph. The
authors motivated this distinction between two letterform representation levels, one specifying visual shape

and the other the sequence of graphic strokes, by cases
of patients whose contrasting patterns of writing errors
suggested damage to one or the other of these levels.
Patients who were unable to have a mental image of
the shape of letters and made, in written spelling, case
mixing errors or letter substitution errors between letters having a similar shape [15,23,24,36,48,49] would
have damage at the level of the allographic store. On
the other hand, patients who had no difficulty in selecting the appropriate case but made numerous wellformed letter substitution errors in written spelling only
(e.g. [18,20,22,29,48]) or wrote forms that were not
real letters [3,53] would have a deficit in retrieving the
appropriate sequence of letter strokes (but see [40] for a
discussion and an alternative account for such patterns).

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M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

Graphemic Buffer
(Graphemes)

Allographic Store
(Letter Shape)

Graphic motor
pattern
(Letter Strokes)

WRITTEN SPELLING

Fig. 2. Post-lexical components involved in written spelling, according to Ellis [19] and Margolin [30].

Thus, each of the three letter processing levels that
have been hypothetized to date are assumed to represent and process a specific content and type of letter information: the level of the graphemic buffer represents
letter identity (and position within the word) as amodal,
symbolic representations, the level of the allographic
store represents letter shape as visuospatial features,
and the subsequent level, letter form as a sequence of
strokes required to write down a specific letter form.
Rapp and Caramazza [40] evaluated these assumptions by contrasting the spelling error patterns of two
dysgraphic subjects with damage at the level of the
graphemic buffer, with that of two dysgraphic subjects
with damage at a postbuffer level. Focusing on the uppercase letter substitution errors made by these patients
in written spelling, they scored each of the target-error
letter pair as being either visuospatially similar (e.g.,
D → C), similar in terms of the features of their component strokes (e.g., L → T), ambiguous (similar according to both visuospatial and stroke features; e.g., F
→ T), or unrelated (no visuospatial nor stroke feature
similarity; e.g., B → C). The visuospatial similarity
metric was based on a confusion matrix obtained by
asking unimpaired individuals to identify briefly displayed uppercase letters and the stroke similarity metric was based on an analysis of the actual strokes produced by the patients for each uppercase letter. Results
indicated that letter substitution errors produced by the

patients with damage to the graphemic buffer displayed
no physical similarity to the intended target, whether
in terms of visuospatial or component stroke features.
On the other hand, erroneous letters produced by the
patients with a postbuffer deficit were physically similar to the target, and similarity was based on features of
the component strokes of the letters, not their visuospatial features. This study thus provides support for the
distinction between a symbolic representation of letters
at the graphemic buffer level and a representation of
letter form in terms of component graphic strokes at
a modality-specific level involved in written spelling.
Furthermore, although this study does not rule out the
existence of additional, visuospatial representations of
letter form at the level of a allographic store, for example, it nevertheless points to the type of evidence that is
needed to support this hypothesis. Since a significant
number of letter pairs that are visuospatially similar are
also similar in terms of their component strokes, analyses of letter substitution errors made by patients having
damage to the visuospatial “allographic store” (e.g. [20,
48,49]) should be able to show that the “shape similarity” observed between targets and errors is based on
visuospatial features, not on stroke features – evidence
that is still lacking to date.
Inspired by this work by Rapp and Caramazza, we
examined, in the case study reported below, the pattern of lowercase letter substitution errors produced by
a single patient in written and oral spelling and found
further evidence in support of the distinction between
symbolic letter representations and letter form representations specifying the component strokes required
to produce the written form. Although the present patient had impaired performance in both written and oral
spelling (and typing), the distribution of his letter-level
errors – especially when, among them, letter substitution errors were split into contextual and noncontextual errors – differed across both spelling tasks. This
pattern lead us to hypothesize two distinct loci of damage: the graphemic buffer, which impaired performance in both written and oral spelling (and typing),
and the letter-form processing level, which further impaired performance in written spelling. We then show
that in a specific type of letter errors found in written
spelling only, namely, the noncontextual letter substitution errors, target-error letter pairs were similar in
terms of their component strokes, whereas in the contextual letter substitution errors, found in written and
oral spelling, target-error letter pairs bore no physical
similarity. Thereby, we replicated the findings of Rapp
and Caramazza in the context of a study carried out

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123

Table 1
AD’s scores to standard neuropsychological tests
Neuropsychological test
ATTENTION
TEA [54]
Lateralised Reaction Time
Total space RT
Left RT
Right RT
Divided attention
RT
Errors
D2
Sustained attention
Total Raw Score
Errors
Total score minus errors
Fluctuation

AD’s score

Controls’ score
Mean (SD)

AD’s score
(z-score or percentile, P)

292 ms
296 ms
288 ms

307 ms (70)

0.21

842 ms
7

P. 5
P. 3

265
6 (2.3%)
259
11

P. 11
P. 90
P. 18
P. 50 – P. 75

MEMORY
Digit span – Forward
Digit span – Backward
Spatial span (Corsi)
Spatial span (Span Supra span test) [51]

6
5
5
7

6.27 (1.2)
4.18 (1.2)
8.88 (1.1)

− 0.22
0.68
P. 50
− 1.7

100%
100%
94.5%
88.9%

98.9% (3.5)
80.6% (15.3)
70.6% (24.7)
66.1% (17.5)

0.31
1.26
0.97
1.30

Buschke 16 items [47]
Free recall
Cued recall
Recognition

33
15
16

28.9 (6.8)
15.8 (5.1)
15.7 (0.5)

0.60
0.16
− 0.6

Span Supra-span test
Supra span

8

8 (4.5)

0

90/90

(0–7)

Perfect

39
26
63/64
118/120

36 (3.4)
16.5 (3.1)
61.8 (1.3)
116.2 (1.7)

0.88
3.22
0.92
1.05

Brown Petterson
0 sec
5 sec
10 sec
20 sec

LANGUAGE
Picture Naming
Verbal fluency
Semantic (Animals)
Letter (P)
Word-to-picture matching [16]
Synonym pointing (written version)
Sentence-to-picture matching
Reversible (active, passive, relative)
Non reversible (relative)

12/12
4/4

with a single patient, whose spelling errors were analysed with a different method for estimating visuospatial and stroke-feature similarity between letter pairs,
which were lowercase, instead of uppercase, letters.
2. Case report
AD, a right-handed French-speaking male with a
University degree in literature, was born in 1932. He
suffered an infarct in July 1999. Templates were used to
identify the lesion size and localization from the available CT-scan images (see Fig. 3) [14]. The lesion was

approximately 4 × 5 × 4 cm and involved Brodmann
area (BA) 39, the posterior part of BA 40, and the most
inferior part of BA 7 on the left side. Another smaller
lesion (about 1.5 cm) was observed in the left frontal
region (BA 6, mostly subcortical). This infarct resulted
in a Gerstmann syndrome. Signs of apraxia were also
reported such as difficulties in using real objects (e.g.,
cutlery and tools), facial, constructional, and dressing
apraxia. Furthermore, AD complained of difficulties in
writing and reading. These difficulties appeared very
mild, but the patient’s spouse asserted that AD was
previously a very competent reader and writer.

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Table 2
Composition of the eight lists of stimuli presented to AD in written spelling, oral spelling, and typing

N◦ List
List 1

Variable
Frequency

Number of items
112 words

Composition
56 high-frequency words (fq > 1000 per million)
56 low-frequency words (fq < 100 per million)
Matched for length (number of letters)

List 2

Imageability

60 words

30 high-imageability words
30 low-imageability words
Matched for length (number of letters and number of syllables),
frequency, and regularity of spelling

List 3

Spelling regularity

100 words
(repeated three times in written
spelling and twice in oral spelling)

− 20 regular words (Degree of Orthographic Ambiguity = 0)
− 40 orthographically ambiguous words
(one phoneme is not written in the most frequent way ; DOA = 1)
− 20 orthographically ambiguous words
(2 phonemes are not written in the most frequent way ; DOA = 2)
− 20 irregular words
(one phoneme is written in an exceptional way)
Matched for frequency and length (number of letters and number of
syllables)

List 4

Grammatical class

120 words

60 nouns – 60 verbs
Matched for frequency and concreteness

List 5

Length

146 words
(repeated twice in written spelling,
oral spelling, and typing)

73 short words (3–5 letters)
73 long words (10–12 letters)
Matched for frequency

List 6

Other

65 words

Very long words (13 to 15 letters)

List 7

Syllabic structure

210 words

105 words with single consonants (CV)
105 words with consonant clusters (CCV – CCCV)
Matched for frequency and length (all eight-letter words)

List 8

Lexicality

105 nonwords

Matched for length and syllabic structure with the set of 105
consonant-cluster words of List 7

In July 2001, AD suffered a second transitory stroke
that caused a transitory left hemiparesia without other
neurological signs (the neuropsychological examination carried out at that moment showed no peculiarity in
comparison with that carried out after the first infarct).
Our experimental investigation was conducted between October 1999 and December 2000, except that
one stimulus list (List 7, see description below) was
administrated to AD in December 2001. During this
period, AD’s cognitive status remained stable.
The results of the standard neuropsychological exams carried out in October 1999 (i.e., when our investigation began) are summarized in Table 1. Although
previous signs of apraxia had largely resolved, occasional hesitations in right-left distinction and residual
difficulties in mental calculation were still noted. Selective and sustained attention was normal but divided
attention was impaired. There was no evidence of
unilateral neglect. Phonological and visual short-term
memory and working memory were normal. Verbal
long-term memory (recognition, free and cued recall)
and visuospatial long-term memory (Span and Supraspan test) were also normal.
AD’s performance on tests of language was normal,
except for reading and spelling. Spontaneous speech

was fluent with normal intonation, articulation, and lexical production. Grammatical complexity and vocabulary were within normal limits for his age and education. Repetition of words and sentences was intact.
Visual confrontation naming, synonym production and
word fluency tasks were all performed perfectly. In
spoken and written word-to-picture matching tasks and
in a synonym pointing task with concrete and abstract
(spoken and written) nouns and verbs, AD responded
quickly and accurately. In an auditory sentence-topicture matching test, he demonstrated normal comprehension of reversible active, passive, and relative
sentences.
Evaluation of reading performance revealed that AD
read aloud letters, isolated words, and pseudowords
rapidly and perfectly. There were no effects of frequency, imageability, grammatical class, or spelling
regularity on performance. However, in reading aloud
text, he produced occasional substitutions of function
words, visual, and exceptionally semantic errors. Nevertheless, he spontaneously corrected most errors. On
some occasions, AD had to read again previous portions of the text in order to achieve understanding, especially when he read quickly. On the whole, in spite

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125

105 nonwords. He was presented with 1059 words and
105 nonwords for oral spelling, and with 617 words for
typing. Because AD had a peripheral auditory deficit,
largely but not completely corrected by prosthesis, he
was asked to repeat the stimuli that were dictated to
him before writing them, in order to ensure he had correctly perceived them. In all the tasks, the patient was
allowed to produce more than one response, that is, to
self-correct a response if he wished to.
3.1.2. Spelling accuracy

Fig. 3. CT-Scan image for AD.

of the very good reading performance demonstrated by
AD in these tests, it was probably not as good as his
premorbid reading skill.
AD’s writing was fluid and without lexical, orthographic, or grammatical errors. However, the patient produced letter substitutions, deletions, additions,
and transpositions in various spelling tasks: written
spelling, oral spelling, written naming, and delayed
copy. Given the similar letter error rates observed
across the various modalities of spelling output, we at
first hypothetized that AD’s writing deficit was located
at the level of the graphemic buffer. However, as we
will show in the following section, a detailed investigation of his spelling uncovered a number of observations that were not fully consistent with this hypothesis,
which we therefore qualified subsequently.

3. Experimental investigations
3.1. Analysis of AD’s performance in written spelling,
oral spelling, and typing
3.1.1. Materials and procedure
AD’s performance in written spelling, oral spelling,
and typing was assessed with eight lists of stimuli. Each
list was designed to evaluate the effect of a specific variable on his spelling performance (see Table 2). In total,
AD was asked to write on dictation 1159 words and

3.1.2.1. Scoring procedure
When more than one response was produced, only
the first one was scored as correct/incorrect. When
the first response was an aborted response, it was always considered as an incorrect response, even when
the patient then restarted and produced a full and correct response, and whether the fragment produced was
correct (e.g., CONTR ÔLER (to check) → CONTR
. . . CONTRÔLER) or not (e.g., BAPT ÊME (baptism)
→ P . . . BAPTÊME). However, just pausing within a
word was not considered an aborted response and hence
was scored as a correct response (e.g., CONTR ÔLER
(to check) → CONTR . . . ÔLER); in these cases, the
patient stopped after having spelled a correct fragment
and then went on spelling, but he did not restart from
the beginning as in the cases of aborted responses.
3.1.2.2. Results
As indicated in Table 3, AD’s spelling accuracy was
similar in written spelling (89%), oral spelling (87%),
and typing (85%). AD was generally aware of his
errors. He self-corrected most written spelling and
typing errors (respectively, 91% and 84% of errors were
self-corrected), but he self-corrected less often in oral
spelling (only 44% of the errors were self-corrected).
After self-correcting, the percentage of AD’s correct
responses was 98% in written spelling, 91% in oral
spelling, and 97% in typing.
Given the high rate of AD’s correct responses, one
question could be raised about whether his performance
was impaired at all in comparison with control subjects.
Therefore, a subset of 669 word stimuli from the various
lists was presented in oral and written spelling to a
control group composed of eight right-handed subjects
(five men and three women), matched to the patient
for age (mean = 65.8 years) and education level (all
had a University degree in literature). These control
subjects had a MMSE score equal or higher than 27/30
and performed within the normal range at the digit span

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Table 3
Number (and percentages) of AD’s correct responses in written and oral spelling and
typing, in the various lists of stimuli contrasting word frequency, imageability, spelling
regularity (DOA = Degree of Orthographic Ambiguity), length, grammatical class,
syllabic structure, and lexicality
List of stimuli (variable)
List 1 (Word frequency)
High Frequency
Low Frequency

Written spelling

Oral spelling

Typing

51/56 (91)
46/56 (82)

46/56 (82)
49/56 (87)

n.a.

29/30 (97)
27/30 (90)

21/30 (70)
25/30 (83)

28/30 (93)
27/30 (90)

List 3 (Spelling regularity)
DOA 0
DOA 1
DOA 2
Irregular

57/60 (95)
113/120 (94)
55/60 (92)
46/60 (77)

38/40 (95)
74/80 (92)
38/40 (95)
32/40 (80)

31/40 (77)
70/80 (88)
37/40 (92)
29/40 (72)

List 4 (Grammatical class)
Nouns
Verbs

54/60 (90)
50/60 (83)

53/60 (88)
56/60 (92)

n.a.
n.a.

List 5 (Length)
3–5 letters
10–12 letters

137/146 (94)
120/146 (82)

141/146 (96)
117/146 (80)

141/146 (96)
111/146 (76)

List 6
13–15 letters

49/65 (75)

41/65 (63)

49/65 (75)

94/105 (89)
100/105(95)

92/105 (88)
95/105 (90)

n.a.

List 2 (Imageability)
High Imageability
Low Imageability

List 7 (Syllabic structure)
CV
CCV/CCCV
List 8 (Lexicality)
Nonwords
TOTAL

94/105 (92)

96/105 (91)

n.a.

1122/1264 (89)

1014/1164 (87)

523/617 (85)

and the Brown-Peterson tests. They were tested in the
same conditions as AD, by alternating oral and written
spelling but during two sessions of three hours. The
scoring procedure was the same as that used for AD.
With this subset of words, AD scored 87% and 85%
correct in written and oral spelling, respectively; the
mean score of the control subjects was respectively
97% and 94%. A first set of analyses revealed that the
control subjects performed significantly better in written than oral spelling (t = 3.63, p < 0.01, df = 6),
whereas no significant difference was noted between
both tasks in AD’s performance (χ 2(1) < 1).1 That the
normal advantage of written over oral spelling was not
found in the patient’s performance might indicate that,
in spite of his similar error rates in both tasks, he was
more impaired, in fact, in written than oral spelling.
The results of the data analyses performed with Crawford and Garthwaite’s modified t-test [12] supported
this conjecture: AD’s performance was significantly
1 When appropriate, the correction of Yates was applied in all χ2
reported in the paper.

impaired in comparison with the controls’, both in written spelling (one-tailed t = − 4.42, p < 0.0001, df =
7) and oral spelling (one-tailed t = −1.98, p < 0.05, df
= 7), and significantly more impaired in written than
oral spelling (two-tailed t = 4.06, p < 0.005, df = 7).
3.1.3. Effect of different variables on spelling
accuracy
In the three spelling tasks (see Table 3), AD’s performance did not significantly vary as a function of lexicality (List 8), word frequency (List 1), imageability (List
2), or grammatical class (List 4) (all χ 2 < 1). This pattern points to a post-lexical locus for the deficit. However, AD’s performance in written spelling was significantly better with regular than irregular words (List 3;
χ2(1) = 6.85; p < 0.01), which is unexpected within this
context. This effect is probably not, however, a genuine regularity effect. All but two errors AD produced
with irregular words were in fact letter substitution errors, exactly like the errors he produced with regular
words. Thus, for example, in the word CHORALE
(choir), the irregularity in phonology-to-orthography
mapping lies in the first two letters “CH”, which are an

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

exceptional mapping for /k/, usually wrote “C” or “K”.
The error AD committed in writing this word, namely,
CHORALE (choir) → CHOL . . ., did not consist in a
regularization error (e.g., CHORALE → CORALE or
KORALE), but in a substitution affecting another letter
in the word. In fact, as we will see, control subjects
produced more regularization errors than AD.
More importantly, it appeared from the results obtained for List 5 that stimulus length affected AD’s
spelling accuracy in the three tasks. AD’s performance
was significantly better with short than long words in
written spelling (χ2(1) = 8.31; p < 0.005), oral spelling
(χ2(1) = 17.71; p < 0.0001), and typing (χ 2(1) = 24.46;
p < 0.0001). However, when responses were scored
as the number of correctly spelled letters over the total
number of letters in the stimulus, the effect of stimulus
length was no more significant in written spelling (98%
correct letters in short words vs. 98% correct letters in
long words; χ2(1) < 1), while it was still significant in
oral spelling (99% vs. 97%; χ 2(1) = 4.80; p < 0.03) and
failed to reach significance in typing (99% vs. 98%;
χ2(1) = 2.50; p = 0.11).
The evidence so far points to a post-lexical locus
for AD’s deficit in spelling: AD was similarly impaired for words and nonwords, and lexical variables
such as word frequency, imageability, and grammatical class did not affect his performance in the three
spelling tasks. By reference to the functional architecture of the spelling system schematised in Fig. 1,
the similar error rates observed in written spelling, oral
spelling, and typing suggest the hypothesis that AD’s
impaired performance in these three tasks originated
from damage to the graphemic buffer. However, there
are a number of observations that make this hypothesis unsatisfactory. First, written spelling was relatively more impaired than oral spelling when compared
to the control subjects’ performance. Second, stimulus length did not similarly impact on AD’s performance in the three spelling tasks. In particular, stimulus length had a highly significant effect on performance in oral spelling, which is consistent with the hypothesis that errors in that task are the result of damage to the graphemic buffer, but no significant effect
in written spelling, which is inconsistent with the hypothesis that writing errors originated from the same
locus of damage. These discrepant patterns suggest the
possibility that AD’s errors in written and oral spelling
(and typing) in fact arose from a combination of distinct deficits. Two reasonable hypotheses might be entertained. The first is that AD’s impaired performance
in the three spelling tasks results from damage to all

127

of the modality-specific mechanisms involved in written spelling, oral spelling, and typing. The second
hypothesis is that AD’s impaired performance results
from damage to a common functional component involved in the three spelling tasks and impairing performance in these three tasks – the graphemic buffer –
plus additional damage to a functional component specific to writing and further impairing performance in
written spelling. A qualitative analysis of AD’s errors,
presented in the next section, will help us to choose
between these two alternatives.
3.1.4. Qualitative analyses of AD’s errors
The error corpus submitted to the following analyses
included all the erroneous responses produced by AD
(that is, not only his first responses, as in the previous
quantitative analyses). Thus, in total, there were 157 errors in written spelling, 146 errors in oral spelling, and
99 errors in typing. In the three tasks, most erroneous
responses were word or nonword letter sequences that
did not correspond to the pronunciation of the stimulus word (i.e., so-called phonologically implausible
responses) and that could be described as letter-level
errors.
3.1.4.1. Distribution of the various error types
We distinguished three main kinds of errors: singleletter errors, multiple-letter errors and other errors (see
examples of each error type in Table 4). Single-letter
errors include letter substitutions, additions, deletions,
and transpositions. Letter transposition errors concern
misplaced letters, such as letter exchanges, in which
two letters exchange their position, and letter shifts, in
which one letter moves from one position to another.
Importantly, among letter substitutions, we separated
contextual from noncontextual errors:
– In contextual letter substitution errors, the letter
that replaces the target letter occurs elsewhere in
the stimulus, either later (anticipation errors, like,
TAPAGE (noise) → P . . .), earlier (perseveration errors, like VETERINAIRE (veterinarian)
→ VÉTÉVINAIRE), or both (ambiguous errors:
COQUELICOT (poppy) → COCUELICOT).
– In noncontextual letter substitution errors, the letter that replaces the target letter does not occur
elsewhere in the stimulus (TRONC (trunk) →
TRANC).
Multiple-letter errors consist of responses in which
more than one letter was erroneous. Other errors include (i) orthographic errors, namely, errors reflecting

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M.-P. de Partz et al. / Multiple levels of letter representation in written spelling
Table 4
Examples of AD’s spelling errors
ERROR TYPE

EXAMPLES
TARGET

ERROR

SINGLE-LETTER ERROR
SUBSTITUTION
Contextual
Anticipation
Perseveration
Noncontextual
Erroneous letter
Non-letter

TAPAGE (row)
VÉTÉRINAIRE (veterinarian)

P ...
VÉTÉVINAIRE

TRONC (trunk)
PATTE (leg)

TRANC
PA / / E

ADDITION

VICTUAILLE (food)

VINCTUAILLE

TRANSPOSITION
Exchange
Shift

TRANSPLANTATION (transplantation)
AUTHENTIQUE (authentic)

TAR ...
AUTENHTIQUE

DELETION

SYMPTÔME (symptom)

SYMPÔME

MULTIPLE-LETTER ERROR

SALAMANDRE (salamander)

ALAG ...

OTHERS
ORTHOGRAPHIC
RESTART
AMBIGUOUS

AGRAFEUSE (stapler)
CONTRÔLER (to check)
QUARANTE (forty)

AGRAFFEUSE
CONTR ... CONTRÔLER
QUARENTE

lack (or loss) of knowledge about how a word is spelled
(e.g., AGRAFEUSE (stapler) → AGRAFFEUSE,
with AD commenting “I don’t remember the correct
spelling, one or two F”); (ii) restarts, namely, aborted
responses in which the patient correctly spelled a portion of a stimulus, then stopped and spelled it again from
the beginning without any error (e.g., CONTR ÔLER
(to check) → CONTR . . . CONTRÔLER); and (iii)
ambiguous errors, which could be classified in more
than one error type (e.g., in QUARANTE (forty) →
QUARENTE, the error could be classified either as a
contextual letter substitution error or an orthographic
error).
The results of the error analysis for word stimuli (Table 5) indicated that single-letter errors were the most
frequent type of errors in the three spelling tasks. They
amounted to 87%, 72%, and 79% of total errors in
written spelling, oral spelling, and typing, respectively.
More importantly, it appears that the error distribution
differs between written and oral spelling (and typing).
In written spelling, the majority of errors were contextual (37%) and noncontextual (29%) letter substitution
errors; letter deletions were exceptional (6%). On the
other hand, in oral spelling, the predominant types of
errors were letter deletions (34%) and contextual letter substitutions (22%), noncontextual letter substitutions being very exceptional (1%). Moreover, in written spelling, a few instances (9%) of distorted letters
were produced. These non-letters could be described
as resulting from the omission of a stroke (5 instances

of omission of the horizontal line in the letter “T”),
addition of a stroke (4 instances, all at the beginning
of the letter “Y”), substitution of a stroke (2 instances),
or as distorted letters (3 instances, where the origin of
the errors was unclear). Production of non-letters like
these suggests that a post-graphemic, modality-specific
level of letter processing was mildly impaired in AD.
The distribution of AD’s errors for nonword stimuli
was very similar to that observed for word stimuli. In
written spelling, most errors were letter substitutions
(8/11), in particular noncontextual letter substitutions
(6/11) whereas, in oral spelling, most errors were letter deletions (8/11) and no one letter substitution was
noted.
So far the data analyses for the written spelling task
include responses in cursive lowercase script only. To
have a more complete picture of AD’s performance
in written spelling, we asked him to write in uppercase the words from List 5 (twice) and List 3, which
made a total of 392 words. The results are presented
in Table 6. The patient produced 26% of errors when
writing in uppercase. The distribution of these errors
across the different error types was not significantly
different from the error distribution observed for lowercase script (χ(3) < 1): the majority of errors were
contextual (38%) and noncontextual (24%) letter substitutions, letter deletions being exceptional (7%).
Finally, we compared the distribution of AD’s errors
with that of the controls, for the subset of 669 word
stimuli presented both to AD and the controls in written

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

129

Table 5
Distribution of AD’s errors in written spelling, oral spelling, and typing, for word stimuli
ERROR TYPE

Written spelling
N
%

Oral spelling
N
%

N

Typing
%

SUBSTITUTION
Contextual
Anticipation
Perseveration
Anticipation or perseveration
Noncontextual
By a non-letter

117
58
50
5
3
45
14

74
37
32
3
2
29
9

32
32
22
3
7
2
−

23
22
15
2
5
1
−

43
38
25
4
9
5
−

43
38
25
4
9
5
−

ADDITION
TRANSPOSITION
Exchange
Shift

7
4
4
−

4
3
3
−

14
8
6
2

10
5
4
1

14
8
8
−

14
8
8
−

DELETION

SINGLE-LETTER ERROR

9

6

49

34

13

13

MULTIPLE-LETTER ERROR

6

4

28

19

15

15

OTHERS
ORTHOGRAPHIC
RESTART
AMBIGUOUS

14
6
7
1

9
4
4
1

13
5
6
2

9
3
4
1

6
3
−
3

6
3
−
3

TOTAL ERRORS

157

100

146

100

99

100

Table 6
Distribution of AD’s errors in writing in lowercase and uppercase script
ERROR TYPE

Lowercase script
N
%

Uppercase script
N
%

117

74

76

74

58
50
5
3
45
14

37
32
3
2
29
9

39
37
2
−
25
12

38
36
2
−
24
12

SINGLE-LETTER ERROR
SUBSTITUTION
Contextual
Anticipation
Perseveration
Anticipation and/or perseveration
Noncontextual
By a non-letter
ADDITION

7

4

2

2

TRANSPOSITION
Exchange
Shift

4
4
−

3
3
−

−

−

−

−

DELETION

9

6

7

7

6

4

10

10

14
6
7
1

9
4
4
1

8
1
4
3

8
1
4
3

157

100

103

100

MULTIPLE-LETTER ERROR
OTHERS
ORTHOGRAPHIC
RESTART
AMBIGUOUS
TOTAL ERRORS

and oral spelling. In both tasks, AD’s error distribution differed strikingly from that of the control subjects
(Fig. 4). In particular, in comparison with the control subjects, AD produced a higher proportion of letter substitution errors in written spelling (AD: 71% vs.
controls: 22%) and a higher proportion of letter deletion (AD: 36% vs. controls: 7%) and multiple-letter

errors (AD: 21% vs. controls: 11%) in oral spelling; in
both tasks, AD produced instead a smaller proportion
of orthographic errors than the control subjects (AD:
8% and 9% vs. controls: 63% and 34%, in written and
oral spelling, respectively). This finding of qualitative
differences between the errors produced by AD and the
controls undermines an account of the mild impairment

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M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

observed in AD’s spelling performance merely in terms
of a non-specific effect of brain damage and strengthens the view that, in spite of relatively good spelling
accuracy, AD did have damage to spelling processing
component(s).
3.1.4.2. Error rates as a function of letter position
Only single-letter errors were included in this analysis. We used the procedure proposed by Wing and
Baddeley [52] to normalize the distribution of errors
across the various stimulus length. According to this
procedure, each stimulus is divided into five positions:
A, B, C, D, E. Each position contains one letter or
more, depending on the number of letters that exceeds
five or multiples of five in the stimulus. The letters in
excess are distributed across the five positions so as to
maintain a symmetrical structure in this reconstructed
stimulus.2 Then, each position was assigned one point
or half a point per error, following the procedure described by Caramazza and Miceli [8]: (i) the position
involved in a letter substitution or deletion error was
assigned one point; (ii) in the case of a letter addition,
half a point was assigned to each position adjacent to
the added letter; (iii) in a letter exchange error, both
letter positions involved were assigned one point; (iv)
for letter shifts, the position which the letter was moved
from was assigned one point and the position to which
the letter moved to was scored like a letter addition
error.
Figure 5 displays the combined serial position curve
for written spelling, oral spelling, and typing. A contrasting distribution of error positions appears across
the three tasks (χ2(8) = 26.14; p < 0.001), with the
distribution noted in written spelling being significantly different from both the distribution noted in oral
spelling (χ2(4) = 22.33; p < 0.0001) and typing (χ 2(4) =
13.81; p < 0.01), whereas the distribution noted in oral
spelling and typing did not significantly differ one from
another (χ2(4) < 1). In oral spelling, the error rate was
higher in the middle positions B and C than in the positions A, D, E (for all comparisons between B and C
and the other positions: χ 2(1) > 15; p < 0.0001; for
all comparisons between A, D, and E: χ 2(1) < 1). The
same pattern was found in typing, with more errors in
the middle positions B and C than in positions A, D,
E (for all comparisons between B and C and the other
2 Stimuli of three and four letters were also included in this analysis

(161 in written spelling, 159 in oral spelling, and 136 in typing). The
letters of the three-letter stimuli were assigned the positions A, C, E
and the letters of the four-letter stimuli, the positions A, B, D, E.

positions: 5 < χ2(1) < 13.5; 0.01 < p < 0.001; for
all comparisons between A, D, and E: 0.2 < χ 2(1) <
1.3; 0.27 < p < 0.65). Thus, both in oral spelling and
typing, letters located at the middle of the stimuli were
subjected to more errors than letters at the initial or final
positions – a pattern that strongly suggests the involvement of a memory component at the processing level
affected by the deficit. This pattern was not found in
written spelling, where the error rates were not significantly different across stimulus positions (0.5 < χ 2 <
2.9 and 0.24 < p < 0.95), with the exception of the
error rate in the final position, which was smaller than
the error rate in the middle position C(χ 2(1) = 4.61;
p < 0.05).
In sum, the results show that AD’s errors in oral
spelling and typing exhibit the characteristic features of
errors resulting from damage to the graphemic buffer:
errors tended to increase with the stimulus length and
mostly affected the letters at the middle positions within
the stimuli. Also, AD produced a high rate of letter
deletion and multiple-letter errors in oral spelling, and
previous studies have shown that those particular kinds
of letter errors were strongly correlated with the severity
of damage to the graphemic buffer [8]. None of these
features was found in the errors AD produced in written
spelling and, in addition, one particular type of letter
error – noncontextual letter substitution errors – was
frequently noted in written spelling and virtually absent
in oral spelling (and typing).
3.1.4.3. Features of noncontextual letter substitution
errors
Since noncontextual letter substitution errors were
found in AD’s written spelling and not in oral spelling
(and typing), one can put forward the hypothesis that
they were caused by damage to a mechanism specifically dedicated to written spelling. If this hypothesis
is correct, these errors should not show the same characteristics as the letter errors found in oral spelling. In
particular, assuming that noncontextual letter substitution errors in written spelling reflects damage to letter
form processing, and given that there is no theoretical
reason to assume that the mechanisms at that level have
a memory component, these errors are not expected to
show the typical distribution of error position found in
oral spelling. Figure 6 shows the serial position curves
for the noncontextual letter substitutions (N = 45) produced in written spelling and the letter errors (singleand multiple-letter errors) produced in oral spelling (N
= 131). Both distributions were significantly different (χ2(4) = 23.65; p < 0.0001) and this difference

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

a) Written spelling

131

AD
Control subjects

Percentage of errors

80
70
60
50
40
30
20
10

O
th
er
s

O
rth

ee

rr.
og
ra
ph
ic

n
tio

M
ul
tip
l

D
el
e

tio
Tr
n
an
sp
os
iti
on

A
dd
i

Su
bs
ti

tu
tio
n

0

Error Type

b) Oral spelling

AD
Control subjects

Percentage of errors

80
70
60
50
40
30
20
10

O
th
er
s

c
og
ra
ph
i

O
rth

M
ul
tip
l

ee

rr.

n
tio
D
el
e

n
Tr
an
sp
os
iti
on

tio
A
dd
i

Su
bs
ti

tu
tio
n

0

Error Type
Fig. 4. Distribution of the various error types made by AD and the control subjects in written spelling (a) and in oral spelling (b). (Note: Here,
the error type “Others” refers to restart and ambiguous errors).

was due to the noncontextual letter substitution errors
occurring significantly more often at the first stimulus
position (χ2(1) = 14.69; p < 0.0001) and less often at
the last position (χ2(1) = 3.87; p < 0.05) than the letter
errors found in oral spelling (the occurrence of both
kinds of errors at the other stimulus positions was not
significantly different).
Moreover, it has been found that patients with damage at a post-graphemic level of the writing processes
tend to substitute target letters with more frequent let-

ters [4]. We looked at the frequency 3 of the target and
erroneous letter in the noncontextual letter substitution
errors produced in written spelling and the letter errors
produced in oral spelling. We found that the erroneous
letter was of higher frequency than the target letter in
75% of the noncontextual letter substitution errors produced in written spelling and in only 53% of the letter
3 In this analysis, we considered the frequency of occurrence of each letter in the 31 million word corpus of Frantext
(http://www.lexique.org).

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M.-P. de Partz et al. / Multiple levels of letter representation in written spelling
60

Written spelling
Oral spelling
Typing

Percentage of errors

50

40

30

20

10

0

A

B

C

D

E

Position within the stimulus
Fig. 5. Distribution of AD’s single-letter errors across five stimulus positions, in written spelling, oral spelling, and typing.

errors produced in oral spelling, a significant difference
(χ2(1) = 4.12; p < 0.05).
3.2. Interim summary and discussion
The analysis of AD’s spelling performance indicated
that he was impaired in the three modalities of spelling
output, that is, in written spelling, oral spelling, and
typing and that his error rate was also similar in the
three tasks. Moreover, in the three tasks, AD’s level
of performance was unaffected by the stimulus being
a familiar word or a nonword, nor by lexical variables like word frequency, imageability, or grammatical class. These aspects of AD’s pattern of performance point to a deficit located at a post-lexical level
of processing within the functional architecture of the
spelling system. Given that most of AD’s errors in the
three tasks were letter-level errors, the most straightforward hypothesis regarding the damaged processing
level responsible for the impaired performance in the
three tasks is the graphemic buffer.
However, aspects of AD’s pattern of performance are
not consistent with this hypothesis. First, compared to
the controls, AD’s performance in written spelling was
more impaired than his performance in oral spelling.
Second, the two hallmarks of damage to the graphemic
buffer – i.e., the increase of letter error rates with stim-

ulus length and the relative increase of error rates at the
middle positions of the stimulus – were noted in oral
spelling and typing only, not in written spelling. Third,
the distribution of the letter error types differed between
written and oral spelling and typing. In particular, one
error type, the noncontextual letter substitution errors,
was frequent in written spelling and virtually absent
in oral spelling and typing. Fourth, some instances
of distorted letters were observed in written spelling,
which suggests at least mild damage to writing-specific
processes.
From this contrasting pattern of performance and error distribution in written and oral spelling and typing,
we propose that AD’s impaired performance in these
tasks resulted from a combination of distinct deficits.
We mentioned earlier the two most plausible combinations of deficits that could be entertained. Now we
must reject the first one, namely, the hypothesis that
AD’s impaired performance in three spelling tasks resulted from damage to each of the modality-specific
mechanisms involved in written spelling, oral spelling
and typing. We indeed found converging pieces of evidence that AD’s impaired performance in oral spelling
and typing resulted from damage to a post-lexical component of the spelling system that is shared by both
modalities of output. AD’s performance was similarly
impaired in both tasks in comparison with the con-

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling
60

Non contextual errors in written
spelling
Other single-multiple letter
errors in oral spelling

50

Percentage of errors

133

40

30

20

10

0

A

B

C

D

E

Position within the stimulus
Fig. 6. Distribution of AD’s noncontextual letter substitution errors produced in written spelling and letter-level errors produced in oral spelling
across five stimulus positions.

trols’ performance. In both tasks, the patient produced
mostly letter-level errors which exhibited the characteristic features of errors resulting from damage to the
graphemic buffer: errors tended to increase with stimulus length and mostly affected middle positions within
the stimuli. Thus, results indicate that AD had damage
at the level of the graphemic buffer, which impaired
his performance in oral spelling and typing, and thus
also, according to our model, in written spelling. In
order to account for contrasting patterns of AD’s performance in oral spelling and typing on the one hand,
and written spelling on the other, additional damage to
a writing-specific component has to be assumed, which
further impaired performance in written spelling only.
Given the type of errors produced in written spelling,
this damaged component is most probably a component
dedicated to letter form processing.
Furthermore, we found evidence that the noncontextual letter substitution errors produced by AD in written spelling did not show the features expected from
errors resulting from damage to the graphemic buffer.
We propose that the noncontextual letter substitution
errors produced by AD in written spelling originate
from damaged mechanisms distinct from those causing
other letter errors in oral spelling and typing. These

other errors (i.e., contextual letter substitutions, letter
additions, deletions, and transpositions and multipleletter errors) would mainly reflect a deficit in the mechanisms assigning position to the graphemes held in the
graphemic buffer. Because these mechanisms are common to all modalities of spelling output, these letter errors were found both in AD’s written and oral spelling
and typing. As for noncontextual letter substitution errors, they would reflect a deficit in the mechanisms that
assign form to graphemes during written spelling. Admittedly, noncontextual errors might theoretically originate from damage to the graphemic buffer, since that
level is supposed to hold information about grapheme
identity, not only position within a word. Thus, a noncontextual letter substitution could arise from information about the identity of a given grapheme being lost
and replaced by an incorrect one. However, such an
account could not explain why this kind of error was
virtually absent from AD’ errors in oral spelling (and
typing). Finally, we suggest that the few distorted letters produced by AD in written spelling could be ascribed to the same impaired mechanisms as those causing noncontextual letter substitution errors. Whereas
a noncontextual letter substitution would result from a
failure in selecting the appropriate letter form among

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M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

similar letter forms, a distorted letter would reflect incomplete retrieval of the form of a given grapheme or
blending of two similar letter forms.
A possible alternative account for the noncontextual
letter substitution errors produced by AD needs to be
addressed. In fact, these errors might originate from
perseverations of letters occurring in the preceding trials of the stimulus list. Therefore, we examined the 45
noncontextual letter substitutions produced in written
spelling in relation to letters included within the three
immediately preceding trials (trials N-1, N-2 and N-3)
and the sixth preceding trial (trial N-6) [50]. According
to the perseveration account, the number of erroneous
letters identical to letters included in preceding trials
should be the highest when the immediately preceding
trials (trial N-1) are considered and it should progressively decrease when the other previous trials are examined. This pattern was not found: 38%, 40%, 38%
and 42% of the erroneous letters in noncontextual letter
substitution errors were present in trials N-1, N-2, N-3
and N-6, respectively. Thus, it is unlikely that noncontextual letter substitution errors produced by AD in
written spelling were perseverations of letters he wrote
in previous items of the stimulus list.
Having reached a motivated hypothesis about the
processing levels of the spelling system that are damaged in AD, the next step is to address the issue of
the kinds of letter representation that are processed at
these levels. In this perspective, we examined the kind
of relationship between target and error in AD’s letter
substitution errors.

level, is assumed to specify grapheme identities, without reference to their name, shape, or font (symbolic
representation of letter identity). On the other hand,
if two letter representations were confused during processing at the level of a (damaged) component assigning form to graphemes, these two letters should be similar in form, that is, “physically” similar. Therefore,
if the assumption of multiple and distinct representations of letter information is correct, we should observe
distinct patterns of similarity within the letter substitution errors produced by AD: only in the noncontextual
letter substitution errors produced in written spelling
should the target and erroneous letter be physically similar. Then, the question raised is whether “physical”
similarity would be in terms of visuospatial or stroke
feature similarity. Exploring this question should reveal whether the letter form information represented at
the writing-specific processing level that is damaged in
AD provides a description of the shapes of letters in
terms of their visual features or of their form in terms
of the characteristics of the graphic strokes required to
produce the specific form.
We addressed these issues by examining the nature
of the similarity between the target and erroneous letters in the letter substitution errors produced by the patient in written and oral spelling (typing errors were not
analysed). For the purpose of this analysis, we developed both a visuospatial and a stroke feature similarity
metrics on the basis of the patient’s own handwriting.
3.3.1. Method

3.3. Analyses of the target-error relationship in AD’s
letter substitution errors
According to our hypothesis, the noncontextual letter substitution errors produced by the patient in written spelling originated from damage to the component assigning form to graphemes. On the other hand,
the other letter errors, noted both in written and oral
spelling, result from damage to the graphemic buffer.
As we mentioned in the Introduction, distinct kinds
of letter representation are assumed at these levels:
amodal, symbolic letter representations at the level of
the graphemic buffer, and modality-specific representations of letter form at the subsequent level of the writing processes. On the basis of these assumptions, one
can predict that if two letter representations were confused during processing at the level of the (damaged)
graphemic buffer, then these two letters should bear no
physical similarity, since letter representation, at this

3.3.1.1. The visuospatial similarity metric
Instead of using a standard visual confusion matrix [21], we developed a visual similarity metric based
on the patient’s own handwriting. Thus, he was asked
to write successively and in lowercase script the 26
letters of the alphabet on a sheet of paper. These 26
written letters were then arranged by pairs (i.e., 325
letter pairs) and subdivided into two sublists. The letter
pairs were then presented horizontally on a cardboard,
one pair at a time, to two groups of 30 subjects (one
group per sublist), who were asked to rate each letter
pair on overall visual similarity, with “1” representing
low visual similarity and “5” high visual similarity. On
the basis of these ratings, a visual similarity matrix was
prepared, which provides the mean rated value for each
of the 325 letter pairs. We set the cut-off for visual
similarity at a mean rated value ⩾ 2.8; this criterion
was reached for 33 letter pairs (10%).

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

135

A. Direction of line
1
2

8

7

é

3

0

6

4
5

B. Localisation

A

B
C

C. Size
According to the zone covered, size : 0.5 - 1 - 2 - 3
D. Starting point
a
b
c
d
e

E. Curvature
1. Line ; 2. Counterclockwise curve ; 3. Clockwise curve ;
4. Jump ; 5. Point.
Fig. 7. The five features used to describe each component stroke of each letter, with their various possible values.

3.3.1.2. The stroke feature similarity metric
The patient was asked to write in lowercase script,
successively and in isolation, the 26 letters of the alphabet on a digitising tablet. Each written letter was then
decomposed into its component strokes, according to
Meulenbroeck and Van Galen’s criteria [33]. Thus, a
stroke was defined as a written segment between two
direction changes. “Invisible” strokes, that is, movements in the air that are part of the sequence of gestures required to produce the letter were also considered. This procedure resulted in letters being decomposed into 3, 4, 5, or 6 strokes. Letter l, for instance,
was decomposed into three strokes (see Table 7).

In the next step, each component stroke of each letter was described according to five characteristics (see
Fig. 7): direction of line, localization, size, starting
point, and curvature (adapted from Rapp and Caramazza [40]). In this way, 43 distinct strokes were identified and then assigned a given label (using uppercase
letters). For example, the first stroke of l was described
as follows: direction of lines = 2, localization = AB,
size = 2, starting point = c, and curvature = counterclockwise curve, and labelled “ZK” (the labels assigned
to the component strokes of each of the 26 letters of the
alphabet are given in Appendix A).

136

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling
Table 7
The three strokes identified in the letter l produced by AD

Stroke 1

Stroke 2

Stroke 3

Finally, in order to draw a stroke feature similarity
matrix for all possible letter pairs (N = 325), the sequence of component strokes of each letter was compared with that of every other letter in the alphabet and
the number of strokes (from 0 to 4) shared by each letter pair, irrespective of whether they were in the same
position, was counted. For example, letter l has the
following sequence of strokes: “ZK-A-L” and letter
b the following: “ZK-A-E-P”. They thus shared two
strokes. Letter pairs were deemed to be similar in terms
of stroke features if they shared 2, 3, or 4 strokes. This
was the case for 32 letter pairs (10%): 27 pairs (8%)
shared 2 strokes, 2 pairs shared 3 strokes, and 3 pairs,
4 strokes.
3.3.1.3. Scoring similarity of target-error letter pairs
Following Rapp and Caramazza [40], we considered
four categories of similarity between letter pairs: a) Visuospatially similar only: when the target and error had
a value of visuospatial similarity ⩾ 2.8 and no stroke
in common; b) Similar in stroke features only: when
target and error shared at least two strokes and had no
visuospatial similarity (⩽ 1.5); c) Ambiguous: when
target and error both had a value of visuospatial similarity ⩾ 2.8 and shared at least two strokes; d) Other
pairs: this category includes unrelated pairs (the target
and error had a value of visuospatial similarity ⩽ 1.5
and no stroke in common) and unclassifiable pairs (the
target and error had a value of visuospatial similarity
included in 1.6 to 2.7 and 0 or 1 stroke in common).
These criteria resulted in all possible letter pairs characterized as displayed in Table 8. On this basis, we
then classified each target-error pair noted in the letter
substitution errors produced by AD in written and oral
spelling in one of the four categories of similarity.
3.3.2. Results
The list of all target-error pairs noted in AD’s letter
substitution errors, classified into the various categories
of similarity, are displayed in Appendix B. The results
(summarized in Table 9) revealed that in written and
oral spelling the majority of target-error pairs in AD’s
letter substitution errors were “other pairs” (i.e., un-

related or unclassifiable). Importantly, no target-error
pair was observed that was “visuospatially similar only”. Moreover, a first data analysis revealed that the
distribution of target-error pairs across the four categories of similarity significantly differed between the
noncontextual letter substitutions and the contextual
letter substitutions produced in written (χ 2(3) = 14.21;
p < 0.0001) or oral spelling (χ 2(3) = 5.81; p = 0.05),
whereas the distribution of target-error pairs did not
significantly differ between the contextual letter substitutions produced in written and oral spelling (χ 2(3) =
1.41; p = 0.49). Decomposing the significant effect indicated that (i) the rate of “other pairs” was significantly
lower in the noncontextual errors than in the contextual
errors produced in written (χ 2(1) = 11.87; p < 0.001)
or oral spelling (χ 2(1) = 4.71; p < 0.05); (ii) there
were significantly more “ambiguous” target-error pairs
in the noncontextual errors than in the contextual errors
produced in written (χ 2(1) = 5.55; p < 0.02) or oral
spelling (χ2(1) = 3.74; p = 0.05); (iii) there were also
more target-error pairs “similar in stroke features only”
in the noncontextual errors than in the contextual errors
produced in written spelling (χ 2(1) = 3.71; p = 0.05)
but not in oral spelling (χ 2(1) < 1); (iv) when the categories “similar in stroke features only” and “ambiguous” were merged, a reliable difference was observed
between the noncontextual errors and the contextual
errors produced in written spelling (χ 2(1) = 11.87; p <
0.0001) or oral spelling (χ 2(1) = 4.71; p < 0.05), although no significant difference emerged between the
contextual errors produced in written and oral spelling
(χ2(1) = 1.41; p = 0.49).
Furthermore, we evaluated the possibility that the
observed rates of target-error pairs in each category
of similarity could have resulted from a mere random
association of target and erroneous letters (see [40]).
For this purpose, each target and error letter was randomly re-paired 1,000 times and the resulting targeterror pairs then classified in one of the four categories
of similarity. The results (see Fig. 8) indicated that
for the contextual errors produced both in written and
oral spelling, the observed rates of target-error pairs
that were similar in “stroke features only” lie within
the chance region. On the other hand, for the noncontextual errors, the observed rates of target-error pairs
that were similar in “stroke features only” were never
generated in 1,000 random re-pairings of the target and
error letters. Moreover, for the noncontextual errors,
the observed rates of pairs classified as ambiguous were
far outside the chance region, whereas for the noncontextual errors, they only just exceeded the chance level
rates.

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

137

Table 8
Distribution of all possible letter pairs across the four categories of similarity

Category

Letter pairs

of similarity

(N = 325)

Visuospatially

13 letter pairs (4%)

similar only

Similar in

11 letter pairs (3%)

stroke features only

Ambiguous

9 letter pairs (3%)

Other pairs

292 letter pairs (90%)

Table 9
Distribution of the letter substitution errors produced by AD in written and oral spelling, across the four
categories of target-error pair similarity
TYPE OF SUBSTITUTION ERROR

Visuospatially
similar only

Similar in stroke
features only

Ambiguous

Others

Written spelling
Noncontextual substitution errors (N = 45)
Contextual substitution errors (N = 58)

0%
0%

13%
2%

36%
14%

51%
84%

Oral spelling
Contextual substitution errors (N = 32)

0%

6%

16%

78%

3.3.3. Discussion
In sum, in spite of the relatively small corpus of errors included in both the data analyses above, the results converge in showing distinct patterns of similarity
between target and error within the letter substitution
errors produced by AD. In particular, the noncontextual letter substitution errors bore a physical similarity
to the intended target significantly more often than the
contextual letter substitutions produced in both written
and oral spelling. That physical similarity was based, at
above chance levels, on features of the graphic strokes
composing the letters rather than visuospatial features.
Moreover, we found no target-error pair similar in terms
of visuospatial features only, whether in the noncontextual or in the contextual errors. On this basis, we sug-

gest that the above chance level proportion of “ambiguous” target-error pairs found in the noncontextual errors
were likely genuine stroke-feature similar pairs which
happen, by chance, also to be visuospatially similar. As
for the contextual errors produced by AD, the results
indicated that they present a similar pattern whether
they were produced in written or oral spelling and, in
particular, that the erroneous letters bore no physical
similarity to their targets. Given the hypothesis we put
forward about the distinct origin of the noncontextual
and the contextual errors, these results support the distinction between symbolic letter representation at the
level of the graphemic buffer and letter representation
in terms of the component letter strokes at the level of
letter form processing.

138

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

Percentage of errors

a) Written Spelling: Noncontextual Errors
40

Observed values
Mean of random re-pairings

30
20

Max value of random re-pairings
Min value of random re-pairings

10
0

Visuospatial

Stroke

Ambiguous

Type of target-error pair similarity

Percentage of errors

b) Written Spelling: Contextual Errors
40

Observed values
Mean of random re-pairings

30

Max value of random re-pairings
Min value of random re-pairings

20
10
0
Visuospatial

Stroke

Ambiguous

Type of target-error pair similarity

c) Oral Spelling: Contextual Errors

Percentage of errors

40

Observed values
Mean of random re-pairings

30
20

Max value of random re-pairings
Min value of random re-pairings

10
0
Visuospatial

Stroke

Ambiguous

Type of target-error pair similarity
Fig. 8. Observed and randomly generated values for the various categories of similarity between target and error letter, for the noncontextual
letter substitution errors (a) and the contextual letter substitution errors produced in written spelling (b) and the contextual letter substitution
errors produced in oral spelling (c).

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

3.4. Additional analyses of AD’s written spelling
errors
In this section, we provide additional details about
the pattern of letter substitution errors produced by AD
in written spelling. One striking feature is that some
letters are particularly vulnerable in the noncontextual
letter substitution errors, namely, the vowel o substituted by a and the consonants t and d substituted one
by the other (see Appendix B). In the “o − a” targeterror pair, AD tended to produce the stroke “ZG” before the stroke “Y”, shared by both letters. When he
had to produce d (substituted by t), he did not produce the first stroke “Y”. It is worth noting that these
target-error pairs were never observed when AD wrote
in uppercase script. In that case, the more frequently
involved letters were the consonants N and L, which
were substituted one by the other, and T substituted by
L. Thus, AD encountered particular difficulties with
some letters, and not the same letters when writing in
lowercase and uppercase, which suggests that his writing difficulties were genuinely related to the specific
sequence of the strokes composing the letter form to be
produced.
Second, it appeared that the nine instances of contextual errors being similar in terms of strokes to the
intended letters (“stroke-feature similarity only” and
“ambiguous”) all concerned the letters that were the
most often confused in the noncontextual errors (that
is, o and d). This might reflect the inherently ambiguous nature of the errors scored as “contextual”. Thus,
a number of them could have resulted in fact from the
same error mechanism than the one giving rise to the
noncontextual errors. In an unknown number of cases,
it might happen, just by chance, that a letter substituted
by that mechanism occurred elsewhere in the word. In
other words, one cannot rule out that a number of errors scored as “contextual letter substitutions” in written spelling were in fact caused by damage to the letter
form processing level, like the errors scored as “noncontextual letter substitutions”, while others reflected
damage to the graphemic buffer.
That some letters appeared particularly vulnerable in
written spelling might (at least partly) account for the
relatively higher rate of letter substitution errors noted
at the beginning of the words in written spelling (in
comparison with the rate of letter substitution errors in
that position in oral spelling and typing). Indeed, we
found that the letters o, d, t, j and v, which were involved in 49% of the noncontextual letter substitution
errors, were not evenly represented across all stimulus

139

positions within the word lists presented to AD in written spelling (total words = 1,159). As shown in Fig. 9,
vulnerable letters appeared more often in position A
and C than in the positions B, D and E (A-B: χ 2(1) =
13.93; p < 0.0002; A-D: χ 2(1) = 67.13; p < 0.0001;
A-E: χ2(1) = 35.06; p < 0.0001; but A-C: χ 2(1) < 1).
4. General discussion
In this study, we examined the case of a patient whose
performance in written spelling, oral spelling, and typing was mildly impaired. We showed that his pattern
of errors in oral spelling and typing was consistent with
the hypothesis that errors were caused by damage to
the graphemic buffer, i.e., a working memory component that holds information about grapheme identity
and position during output processing. Furthermore,
we found evidence that impaired performance in written spelling reflected additional damage to a writingspecific component, i.e., a component assigning form
to graphemes.
Evidence of additional damage to a writing-specific
component mainly stemmed from the distinction we
drew between contextual and non contextual letter substitutions in the classification of the patient’s errors. To
the best of our knowledge, this distinction has not been
considered in previous studies of dysgraphic patients. 4
Thus, one question is to what extent neglect of this distinction may have been responsible for the contradictory patterns in the performance of patients that were all
supposed to have damage to the graphemic buffer [11].
For example, when it turned out that the patient’s performance in written spelling did not conform to the
pattern expected in case of damage to the graphemic
buffer (e.g., as regards the effect of stimulus length or
the distribution of the errors across stimulus positions),
it is an open question whether drawing a distinction between contextual and noncontextual letter substitution
errors would help to resolve the inconsistencies. In
the present case study, at least, this distinction did help
understand the origin of apparent inconsistencies and,
eventually, of the patient’s errors in written spelling.
4 The sole exception we noted is in the paper of Rapp and Caramazza [40]. In a footnote (p. 1137), these authors mentioned that,
for the analysis of the error types produced by a patient with an impairment specific to writing, they put together both kinds of errors
into a single category of “substitution”, because “separate analyses
on the different types revealed no difference”. However, they did not
report the relative proportion of each error type.

140

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

60

Percentage of occurence

50

40

30

20

10

0

A

B

C

D

E

Position within the stimulus
Fig. 9. Combined distribution of letters o, d, t, j, and v across various stimulus positions in the 1159 word stimuli presented to AD in written
spelling.

Once evidence was found of damage to two distinct levels of letter processing within the spelling system, we sought evidence for the hypothesis that distinct types of letter representation are processed at each
of these damaged levels – symbolic letter representations at the graphemic level and representations of letter strokes at the letter-form level. On the basis of
a visuospatial and a stroke-feature similarity metrics
developed from patient’s own handwriting, we found
that the noncontextual letter substitution errors produced in written spelling were similar to the target letters in terms of component strokes. This is consistent with the pattern of similarity found between target
and error in two cases described by Rapp and Caramazza [40], JGE and HL, who had impairment specific
to written spelling. Their patients showed letter substitution errors in writing uppercase letters that were
similar in component strokes to the targets. On the
other hand, for the contextual letter substitution errors
produced by our patient in written and oral spelling,
we found no physical similarity between target and error. This result is consistent with the analysis of letter
substitution errors produced in written spelling by two
other patients described by Rapp and Caramazza [40],

LB and HE, whose pattern of impaired performance
in written and oral spelling pointed to damage to the
graphemic buffer: in these cases, no physical similarity
was found between target and error neither. Thus, in
the context of a single case study, we found evidence
that converges with evidence from patients with distinct deficits, supporting the assumption that letter information processed at the graphemic level and at the
letter-form processing level are of distinct types.
Let us make clear, however, that we are not arguing
that contextual and noncontextual letter substitution errors could be taken as reliable and direct reflections of
damage to the graphemic buffer or to a writing-specific
component, respectively. As mentioned earlier, noncontextual errors could also be expected from damage to the graphemic buffer, when information about
grapheme identity has been lost or confused and, on the
other hand, errors scored as contextual might well be
instances of errors originating from mis-selection of the
appropriate stroke sequence for a target letter. In our
view, both kinds of error can be given a reliable interpretation only by reference to the patient’s performance
and error distribution across the different modalities of
spelling output.

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

Acknowledgements
This paper is dedicated to AD, who died in April
2005. We are grateful to Brenda Rapp for her insightful comments and recommendations on this case study.
We also owe thanks to Adam Buchwald for having very
kindly provided us with the program for randomly pairing letters. Thanks to Marie Van Reybroeck and Delphine Guitton for their assistance in testing the control
subjects, Eva Turconi for her help in statistical analyses, and Doctor Adrian Ivanoiu for his advice on interpreting the medical records of the patient. We are
also grateful to Brendan Weekes and two anonymous
reviewers for their useful suggestions on an earlier version of this paper.

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M.-P. de Partz et al. / Multiple levels of letter representation in written spelling
Appendix A
Sequence of the component strokes for the 26 letters produced by AD in lowercase script. The
capital letter(s) is (are) a label assigned to a given stroke after having been described according to
five features (direction, localization, size, starting point, and curvature of the stroke; see text)

Letter

Stroke 1

Stroke 2

ZG

Y

ZK

A
Y

G

Stroke 3
E

Stroke 4
Q

E

P

J

ZE

Stroke 5
L
L

Y

ZJ

B

L

M

U

L

ZK

ZF
C

ZN

ZP

G

Y

F

ZL

ZK

B

K

Q

O

Y
ZM

L

ZH

D

O

ZO

ZH

D

ZK

B

J

ZB

T

ZK

A

L

N

N

Z

N

N

Z
Z

N

Z

Y

M

ZF

Q

O

ZL

ZQ

P

Y

F

ZL

I

P
W
L

ZA

L

X

ZC

ZI
M

P

Y

O

P

O
B

ZR

Z

ZF

H

U
V

H

V

L

R

O

H

O

W

S

U

ZD
M

ZL

ZN

ZP

I

P

ZA

L

ZM

O

Stroke 6

P

ZO

143

144

M.-P. de Partz et al. / Multiple levels of letter representation in written spelling

Appendix B
List of all target-error letter pairs noted in AD’s letter substitution errors according to the category of similarity between letter pairs (the number
of occurrences of each target-error letter pair is given in parentheses)
CATEGORY OF SIMILARITY BETWEEN LETTER PAIRS
TYPE OF SUBSTITUTION ERROR
Visuospatially
Similar in stroke features only
Ambiguous
Unrelated
Unclassifiable
similar only
Noncontextual substitution errors
−
d-t (2)
o-a (15)
b-s (1)
a-u (1)
produced in written spelling
j-z (1)
v-w (1)
o-r (1)
b-f (2)
(N = 45)
t-d (3)
p-c (1)
b-t (1)
p-l (1)
c-o (1)
y-i (2)
d-l (1)
g-n (2)
i-u (3)
l-t (1)
s-j (1)
s-r (2)
u-i (1)
y-u (1)
Contextual substitution errors
produced in written spelling
(N = 58)

−

d-t (1)

o-a (5)
o-e (3)

a-p (1)
b-e (1)
b-s (2)
e-n (1)
g-a (3)
h-r (2)
m-g (1)
o-t (1)
t-g (1)
u-l (1)
y-i (1)

a-b (1)
a-e (3)
a-h (1)
a-t (1)
b-f (1)
b-p (2)
b-r (1)
c-t (3)
d-g (1)
e-l (2)
e-r (1)
h-l (2)
i-e (1)
i-r (1)
i-f (1)
l-o (1)
n-i (2)
p-t (1)
r-n (1)
r-v (1)
t-a (1)
t-b (1)
t-l (1)
t-p (1)
u-i (1)
v-s (1)

Contextual substitution errors
produced in oral spelling
(N = 32)

−

c-g (1)
t-r (1)

e-o (1)
o-a (3)
o-e (1)

e-n (1)
h-e (1)
n-c (1)
t-n (1)
u-l (1)

b-p (1)
c-i (1)
d-g (1)
e-r (1)
i-e (2)
l-o (1)
n-i (1)
o-y (1)
q-c (2)
r-c (1)
r-l (2)
r-u (1)
s-a (1)
s-c (1)
t-a (1)
t-l (1)
u-i (1)

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