COGNITIVE NEUROPSY CHOLOGY, 2000, 17 (6), 517–546
THE SELECTIVE IMPAIRMENT OF THE
PHONOLOGICAL OUTPUT BUFFER
Tim Shallice
University College London, UK and SISSA-ISAS, Trieste, Italy
Raffaella I. Rumiati
SISSA -ISAS, Trieste, Italy
Antonella Zadini
Ospedale Maggiore, Trieste, Italy
A single case study is presented of a patient, LT, with a reproduction conduction aphasic pattern of performance on word reproduction tasks; thus he made substitutions, insertions, deletions, and transpositions in reading, writing, and repetition of words and nonwords, as well as in sentence production, and
in spoken and written picture and action naming. Further analyses revealed that there was no effect of
semantic or syntactic structure on performance, and that reading was slightly better than repetition and
writing. Finally, the observed effects of lexicality, length, and word frequency were similar to those
found in other phonological output buffer patients. Overall, the pattern observed fits the characteristics
typical of phonological output buffer patients, as characterised by Caramazza, Miceli, and Villa (1986).
We discuss the implications of these results for understanding the role of the output phonological
buffer in neuropsychological and computational models of writing, reading, and repetition. From the
perspective of LT’s performance, the hypothesis suggested by Caramazza et al. (1986), and that of
Hartley and Houghton (1996), that word production in reading and repetition uses an additional route
to access articulatory or phoneme-level representations from the phonological output lexicon, is unnecessary; instead, word-nonword differences in other patients can be attributed to resource demand differences between the two types of stimuli. LT’s preserved span fit with the assumption that two
phonological buffers exist, one for input and the other for output. Results from a word repetition experiment, in which word syllable structure was manipulated, are in conflict with one further noncentral
aspect of the Hartley and Houghton’s model, which otherwise fits the results well.
INTRODUCTION
The existence of a phonological output buffer holding the extended phonological representation of an
intended utterance has long been a well-established
concept in studies of the short-term memory performance of normal subjects (e.g., Ellis, 1979;
Monsell, 1984; Morton, 1969; Sperling, 1967).
Indeed, early versions of the working memory
model had presupposed that such a speech output
Requests for reprints should be addressed to Tim Shallice, Institute of Cognitive Neuroscience, University College London,
Gower Street, London WCIE 6BT, UK, (Email: [email protected]) or Raffaella Rumiati, Cognitive Neuroscience Sector, Scuola
Internazionale Superiore di Studi Avanzati (SISSA), Via Beirut 2-4, Trieste, Italy (Email: [email protected]).
We would like to thank Randi Martin and two referees for their very helpful comments on an earlier version of the paper and LT for
his kind collaboration. We are also grateful to Claudio Luzzatti for his comments on the patient’s CT scan and to Emanuela Bricolo for
computer assistance. The research was assisted by support from grants EC PSS* 0859 and MURST.
Ó 2000 Psychology Press Ltd
http://www.tandf.co.uk/journals/pp/02643294.html
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SHALLICE, RUMIATI, ZADINI
buffer was the auditory-verbal short-term store
linked to the articulatory loop slave system
(Baddeley & Hitch, 1974). Mechanisms that hold
phonological information for the order of a clause
have also been postulated in research with a more
linguistic orientation focusing on speech errors
(e.g., Fromkin, 1973). These have included a buffer
and related hypothetical mechanisms (scan copier,
checkoff monitor, etc.) in Shattuck-Hufnagel’s
(1979) account or the phonological assembly system in Butterworth’s theorising (1980). The representations being retained are generally assumed to
be at the positional level on Garrett’s (1980) model
(Buckingham, 1992; but see Pate, Saffran, & Martin, 1987).
From a neuropsychological perspective, a disorder of a phonological output buffer has been held
responsible for conduction aphasia of the “reproduction” variety and contrasted with conduction
aphasia of the repetition variety, which was linked
to damage to an input auditory-verbal short-term
store (Shallice & Warrington, 1977). On this
approach the reproduction and repetition varieties
of conduction aphasia are empirically distinguishable according to whether the patient’s difficulty in
repeating an utterance occurs principally for individual longer, less familiar words—the “reproduction” variety—or for strings of short familiar words
(span)—the “repetition” variety. The “reproduction” variety then corresponds to the classical form
of the conduction aphasia syndrome, in which
patients are fluent but make literal paraphasic errors
both in spontaneous speech and in the reproduction
of single words (e.g., Dubois et al., 1964). The
errors of this form are characterised in terms of substitutions, insertions, deletions, and moves of phonemes, often resulting in a “doublet” (Buckingham,
1992; Lecours & Lhermitte, 1969), and occasionally a full exchange.
The first detailed analysis of the impairment of a
patient who was characterised as having an output
phonological buffer disorder was that of patient
IGR by Caramazza, Miceli, and Villa (1986). Their
paper was of considerable methodological as well as
empirical and theoretical interest. In general conduction aphasics perform more poorly in nonword
than word production but the performance is
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COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
qualitatively equivalent (see Caplan & Waters,
1990). IGR, however, showed the conduction
aphasia pattern, but only for nonwords. He did not
produce paraphasias in spontaneous speech or in
the reproduction of single long words. Instead a difficulty was apparent in the reproduction of pronounceable nonwords. Thus 61% of IGR’s errors
could be explained in terms of a single substitution,
insertion, deletion of a phoneme, or a transposition
of two phonemes. The others were either combinations of the more basic error types or “fragments.”
Moreover, 82% of the errors fell in the same phonological category, defined by manner of articulation.
The methodological and theoretical importance
of the paper was, however, derived from the relation
between these findings and those in two other
tasks—the reading aloud and the writing of
pronounceable nonwords. The characteristics
described earlier for the reproduction of nonwords
were also basically found in these other two tasks:
The single letter/phoneme error type comprised
83% of the reading errors and 75% of the writing
errors. The similarity in the pattern of errors across
tasks also extended to three other characteristics.
Thus the relative rates of single substitution (S),
single insertion (I), and single deletion (D) and
transposition (T) errors are remarkably similar: repetition 81% (S), 11% (I), 3% (D), 5%(T); reading
81% (S), 13% (I), 6% (D) 0% (T); writing: 68% (S),
13%(I), 17% (D), 2% (T).) Moreover, the errors
occur in a roughly comparable fashion across different letter positions within the nonwords and the
errors were nearly all on consonants for all three
tasks.
The key methodological innovation of the paper
was that this common pattern of characteristics in
the errors produced by a patient was used to support
the assumption of the existence of a common system or common set of subsystems utilised in the
three tasks. Although inferences from a common
quantitative pattern of impairment across different
basic tasks was considered in principle appropriate
evidence for supporting the assumption that the
same system or set of systems was used in performance of the tasks, unlike mere association of deficits (see Shallice, 1979a), no systematic and
detailed application of the principle were available
THE PHONOLOGICAL OUTPUT BUFFER
until this and a related group of papers were produced in the mid-1980s by Caramazza, Miceli, and
their colleagues (see also Caramazza & McCloskey,
1985; Caramazza, Miceli, Silveri, & Laudanna,
1985; Caramazza, Miceli, Villa, & Romani, 1987;
see also for metatheoretical polemic McCloskey &
Caramazza, 1991) and by Caplan, Vanier, and
Baker (1986) on reproduction conduction aphasia.
Moreover, the procedure clearly demonstrated the
power of error analysis, which had previously been
held to be unreliable for discovering theories about
the functional organisation of the normal system
when contrasted with dissociations (see, e.g.,
Shallice, 1979a).
Theoretically, the findings of Caramazza et al.
(1986) were basically explained by assuming that
the phonological output buffer was utilised for a
variety of purposes in speech production, repetition, reading aloud, and writing. In these respects
this neuropsychological evidence was fully consistent with theoretical claims about the operation of a
phonological buffer drawn from other sources of
evidence (e.g., Ellis, 1980; Morton, 1969). Minor
differences between the three basic tasks could be
easily explained by particular characteristics of one
of them. Thus writing and repetition show major
effects of the length of the nonwords but reading
does not; this is presumably because reading does
not require all of a nonword to be maintained in the
buffer before production begins (see Coltheart,
Curtis, Atkins, & Haller, 1993; Làdavas, Shallice,
& Zanella, 1997).
However, Caramazza et al. (1986) made an
additional novel theoretical claim, which puts their
position in conflict with accounts of “reproduction”
conduction aphasia where that is seen as a disorder
of the phonological buffer. They argued that for all
operations that required spoken output, the use of
the phonological buffer was critical in only one
respect for the ecologically most important output:
spoken words. The critical aspect was word order, it
being held that the processing of single words and
even words in short sentences could be achieved by
the use of a route from the phonological output lexicon to the “lexicon-articulatory system,” which
bypassed the phonological output buffer. They
made this assumption to explain the fact that IGR
was 100% correct at repeating words, 98% correct at
reading them, and 97% correct at writing them.
The syndrome of phonological agraphia
(Shallice, 1981) indicates that word writing can be
carried out independently of sound-to-spelling
translation, which would require the use of the representation stored in the phonological output
buffer. However, Caramazza et al. argue that a second route which did not utilise the phonological
output buffer was necessary to explain the intact
repeating and reading aloud of words by IGR.
Detailed investigations on two similar patients
from a related perspective are known to us (a third
patient, that of Romani, 1992, also appears to be
similar). Bub, Black, Howell, and Kertesz (1987)
carried out a detailed analysis of the reading and
repetition impairments of a phonological alexic
patient, MV. The patient differed from IGR in
being severely agraphic, so no analogous study of
writing could be carried out. Again, errors in reading or repeating a nonword were very similar in
nature. They tended to differ from the target by a
single distinctive feature with substitutions being
much more frequent than omissions or additions of
a phoneme. Words were virtually perfectly read and
repeated except for the repetition of three syllable
words. Bub et al. (1987) came to a different theoretical conclusion to Caramazza et al. (1986), arguing
that the contents of the response buffer of MV were
limited in capacity and subject to abnormally rapid
decay. They argue: “… incompletely specified
traces … trigger a higher-level interpretative mechanism which evaluates the response options. Since
the potential candidates at this level of representation are morphemes that provide the best possible
fit to the description in the response buffer, the output selected will be a word that is a close phonological approximation to the target” (p. 95). Thus, they
argue, word performance will be better than performance with nonwords.
Bisiacchi, Cipolotti, and Denes (1989) reported
a patient, RR, who had a very similar pattern of
errors in reading, writing, and repeating nonwords
to IGR, even down to the relative ratios of transpositions, insertions, deletions, and transpositions.
RR, like IGR, had a greatly reduced auditoryverbal span and Bisiacchi et al. raise the question of
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
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SHALLICE, RUMIATI, ZADINI
whether the deficits in phonological nonword processing and span arise due to an impairment of different functional systems, a common system, or
partially overlapping systems. They do, however,
point out the existence of short-term memory
patients, namely patients with a much reduced span
without problems in word comprehension or production, who can read nonwords, e.g., JB (Shallice
& Butterworth, 1977), and PV (Vallar & Baddeley,
1984) (Vallar, personal communication). However,
reading is the least demanding of the three basic
tasks as far as the use of the phonological output
buffer is concerned, as PV might have read syllableby-syllable, using the phonological reading route.
Both Bub et al. (1987) and Bisiacchi et al. (1989)
essentially adopt the same overall interpretation of
the syndrome as Caramazza et al. (1986), namely an
impairment to an (output) phonological buffer.
However, neither Caramazza et al. nor Bisiacchi et
al. label their patients as conduction aphasic and
indeed their patients do not show phonemic
paraphasias in spontaneous speech. However,
many characteristics of the reproduction of
nonwords in patients IGR and RR had previously
been described in word reproduction in conduction
aphasic patients (e.g., Blumstein, 1973; Lecours &
Lhermitte, 1969; Pate et al., 1987). One possibility,
to be considered further in the Discussion, is therefore that the impairment of IGR, MV, and RR was
merely a mild one and if it had been quantitatively
more severe but qualitatively identical, then it
would have also affected word reproduction and
spontaneous speech; their patients would have presented as typical reproduction conduction aphasics.
The argument of Caramazza et al. that word repetition does not involve the phonological output
buffer would be contaminated by what has been
called a “resource artefact” (Shallice, 1979a).
A second alternative possibility that none of the
studies considered is provided by the hypothesis of
McCarthy and Warrington (1984) to explain the
impaired repetition performance of two conduction
aphasic patients ORF and RAN. The hypothesis
was that in their patients there was a disconnection
of input orthographic and phonological processors,
including the auditory-verbal short-term store, the
(input) phonological buffer in the terminology of
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COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
Baddeley (1986), from output phonological processes including the phonological output buffer.
On this view, the phonological output buffer would
receive inadequate input from the phonological
input system unless the information were routed via
the semantic system; indeed, in ORF and RAN
forcing the patient to use a semantic processing
strategy improved word reproduction. Such a
hypothesis would account for the findings obtained
on IGR, MV, and RR as information about visually
or auditory presented words could be routed
through the semantic system to the output system,
but this would not be possible for nonwords, which
lack a semantic representation. The disconnection
hypothesis did not raise any novel possibilities
about the organisation of the normal language
system.
The impairments of IGR and RR have recently
become of key theoretical interest because they have
provided major neuropsychological support for a
model of phoneme selection and retention in
speech developed by Hartley and Houghton (1996)
in the context of a novel theory of the serial ordering
of speech (see Figure 1). The starting point of their
theory is a class of neural network models of serial
order known as “competitive queuing” (CQ) models (Houghton, 1990). CQ models are activationbased models in which order is represented by associations between localist nodes representing item
(in this case phoneme) identity and other nodes
that contain some abstract representation of an
item’s positions, called context nodes. Item selection for each position is effected through lateral
inhibitory competition between activation within
item nodes. The simplest form of context nodes is a
pair, one representing distance from the beginning
of the sequence and the other distance from the
end. The activation of each changes over time in a
complementary fashion in an initial (Hebbian)
learning phase and in the same way when the
sequence is retrieved.
Models of this type have been applied to auditory-verbal short-term memory phenomena (e.g.,
Burgess, 1995; Burgess & Hitch, 1992) and to the
sequencing of letters in spelling (e.g., Houghton,
Glasspool, & Shallice, 1994; Shallice, Glasspool, &
Houghton, 1996). In the Hartley and Houghton
THE PHONOLOGICAL OUTPUT BUFFER
Temporally Correlated Internal Context
ll
Novel
Phonological
Content
Pathway
l l l l l l l l l l
Forms
l
ll
l l l l l l l
l l l l
Structural
Pathway
ll
ll
ll
ll
ll
Familiar
Phonological
l l l l
l
ll
l
ll
Forms
Template
lll
lll
ll
l
Phonemes
Figure 1. The basic components of the Hartley-Houghton (1996) model of speech production and short-term memory. The phonological
form representations contain two nodes, one corresponding to the onset and the other to the rhyme. The template representation has five
nodes, each corresponding to the position of a phoneme in the syllable. The phoneme representation has a node for each phoneme in the
language. The shaded area represents structures not included in the implementation. The dashed lines represent pathways made up of
temporary weights, the solid lines represent connections which do not decay over time (from Hartley & Houghton, 1996, p.22).
quencing of phonemes in word production the context nodes are more complex. Indeed, they have two
levels. A syllable template is created that is intended
to approximate to the structure of a putatively universal generalised syllable and is based around the
concept of sonority. The syllable template consist of
five nodes, two for the initial consonant cluster, the
third for the vowel, and two for the coda, only one
of which is activated for each input phoneme.
Above this set of phoneme nodes are a string of four
syllable position nodes, with again only one being
activated at a time. Again, the same sequence of syl-
lable and phoneme position nodes occurs in the
learning phase and when the information is
retrieved. A further complexity of the Hartley and
Houghton model is that there are held to be two
sets of connections between the syllable representations and the phoneme identity and context representations. They explain the performance of
aphasic patients by increasing the weight-decay
parameter within the model.1
Hartley and Houghton situate this specific
model in a broader model, which makes two further
commitments, neither in our view derived from the
1
An unfortunate aspect of the Hartley and Houghton simulation is that the impairment is simulated by an increase in the general
level of noise throughout the network. In our view it is preferable to increase the noise in a particular layer, as done in the Houghton,
Glasspool, and Shallice simulation.
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
521
SHALLICE, RUMIATI, ZADINI
basic logic of the approach. The first is that no distinction at the level of short-term retention of phonological information is made between the input
and the output phonological systems; their model
in this respect is in the same spirit as another
connectionist model of repetition, that of Martin
and Saffran (1992). The second, which has some
relation to the position of Caramazza et al. (1986),
is that a partially separate pathway where the connections are permanent can carry out single word
production. These permanent connections can be
used in isolation. Hartley and Houghton do not
provide an independent justification for this last
assumption and ironically a contrasting assumption
was made in a related model of spelling (Houghton
et al., 1994).
Given this second assumption, they naturally
based their model neuropsychologically not on
reproduction conduction aphasia in general but on
IGR and RR. They use parameters previously
employed in simulations of findings on normal
subjects and with only one arbitrary parameter
change—of the half-life of weight-decay, which is
reduced from 5.0 s to 3.5 s—a good quantitative fit
is obtained to the performance of IGR and RR.
The incidence rates of certain error types, which
will be discussed in more detail later (single deletions, single insertions, single substitutions, multiple substitutions, substitution and insertions,
substitutions and deletions and transpositions), are
reproduced accurately. The largest discrepancy is
over multiple substitution errors, which the simulation predicts to occur for 0.67% of responses, but
IGR produces them on 3.52% of trials. However,
this is clearly acceptable within-syndrome variability as RR produces 0/130 such responses in repetition but makes 2/130 in reading and 6/130 in
writing. To our knowledge no quantitative predictions of comparable accuracy exist in
neuropsychology.
We present in this paper a fourth patient, LT,
who would be classified as a reproduction conduction aphasia as his disorder involves both word and
nonword processing. Our principal aim is to show
that there are no good grounds for assuming that he
has a different functional syndrome (in the sense of
Plaut & Shallice, 1993) from IGR, MV, and RR.
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COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
We then consider the performance of LT in the
context of those of IGR, MV, and RR with respect
to four theoretical issues. For the first three issues
we use the concept of the “phonological output
buffer.” By this we refer to the mechanisms by
which information is retained in any form of
sublexical phonological code, within the speech
production system over short intervals of time (i.e.,
less than 10 seconds, say). We do not intend the
concept to refer to any specific architecture such as a
store with a fixed number of slots. In the fourth
issue we are more specific about how the system
retains such information.
1. How does LT’s performance speak to the
hypothesis of Caramazza et al. of a separate output
route for word production that bypasses the phonological output buffer?
2. Is the disorder, at least in LT, best captured
by an impairment of the phonological output buffer
or by disconnection between input and output phonological systems?
3. How does LT’s performance relate to the
issue of the separability or identity of the phonological input and output buffers?
4. How does LT’s performance relate to the
predictions of the Hartley and Houghton model?
CASE HISTORY
A right-handed Italian male patient, LT, born in
1932, who had 8 years of schooling was studied.
During his working life he had held several jobs
such as waiter, barman, and telegraph operator on
ships. For a number of years before retiring, he
worked as a secretary in a transport company. LT
was admitted to the hospital of his hometown on
March 1, 1995, with weakness to the right side of
the body and global aphasia. A CT scan (23/10/96)
revealed two hypodense areas in the left hemisphere: an older superior fronto-parietal area and a
more recent perisylvian area (see Figures 2a and
2b). Broca’s area is spared, but Wernicke’s area, the
inferior parietal lobule, the lateral area 7, and probably also the insula are affected. After having been
discharged from hospital, LT began to attend a
THE PHONOLOGICAL OUTPUT BUFFER
Figure 2. Two horizontal sections: (a) z = + 4.0; (b) z = + 24.0; showing the lesion that affects the left superior temporal and inferior
parietal lobes.
speech and physiotherapy programme in the Rehabilitation Unit of the Ospedale Maggiore in
Trieste. The present study was carried out between
November 1995 and April 1997, during which time
LT was always collaborative and aware of his difficulties. During the testing period his general
neuropsychological condition remained unchanged.
The patient was well oriented in time and space.
He scored 23 (50th percentile) on Raven’s Coloured Progressive Matrices. However, his performance on the WAIS was clearly below that level.
His verbal IQ was 88, and nonverbal IQ 89, with
subtests ranging from above average (Digit Span)
to borderline defective (Comprehension, Digit
Symbol, and Picture Arrangement). Of importance
is that his digit span was 6 forwards and 3
backwards.
A general neuropsychological assessment
revealed no evident agnosic problems. He was at
ceiling on a shortened version of the Efron Test (6/
6) and the Object Decision task (10/10) and on
matching pictures on the basis of their meaning (5/
5), and identity (5/5). A test of utilisation apraxia
on verbal instructions (16/20, 80%) indicated a
mild deficit only with the left limb. However, when
he was asked to imitate gestures made by the examiner, left limb performance improved (19/20, 95%).
LT was not tested with his right limb because he
had a motor difficulty. No buccofacial (20, normal
mean = 19.8, see Spinnler & Tognoni, 1987) or
constructional apraxia (14, normal mean = 12.5, see
Spinnler & Tognoni) was present. On the Corsi
block tapping test he showed a span of 6 forwards
(control mean = 5, see Spinnler & Tognoni), and 5
backwards.
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
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SHALLICE, RUMIATI, ZADINI
LANGUAGE EVALUATION
LT’s language abilities were evaluated using
BADA (Batteria per l’Analisi dei Deficit Afasici),
devised by Miceli, Burani, and Laudanna (1991).
The patient’s spontaneous speech displayed a
somewhat impoverished use of morphological and
syntactic structures and showed the classical conduction aphasic pattern of fluent but paraphasic
speech with the individual phonemes normally produced. The simple argument structure subjectverb-object was often present in his utterances and
the prosody was appropriate.
Comprehension of sentence material was also
mildly impaired. In a task in which he was asked to
match a sentence said by the examiner to one of two
pictures, LT scored 54/60 (90%) and he scored similarly when judging whether a spoken sentence was
grammatically correct (41/48, 85%). He also
showed a deficit on a written version of the sentence
comprehension task (23/30, 77%) and on the written version of the grammatical judgement task (20/
24, 83%). Finally, on a shortened version of the
Token Test (De Renzi & Faglioni, 1978) he
obtained 16/36.2
However in tasks in which input processing was
required of only single lexical items or smaller units,
he always scored at above 90%. Thus LT scored 76/
80 (95%) in auditory lexical decision (with
nonwords being made from words by changing one
phoneme) and his comprehension of single words
was virtually normal both for auditory and written
inputs. When asked to match a spoken word to one
of two pictures, when the distractor was phonologically similar to the target (e.g., treccia [plait] and
freccia, [arrow]), he made only three errors (37/40,
92.5%, controls matched for age and education
scored 38 or 39, mean = 38.6). In an analogous version in which the word to be matched was written,
he again made only three errors (37/40, 92.5%). In
2
an additional task, LT was asked to say whether two
phonemes spoken by the experimenter were the
same or different; he was able to discriminate correctly 56/60 (93.3%) pairs of phonemes differing on
a single feature (e.g., ta/da).
However, when production was required his
performance was much worse. Thus LT’s naming
performance was impaired both with line drawings
of objects (14/30, 47%) and of actions (4/28, 14%)
as stimuli. When asked to give a written response
rather than a spoken one, LT scored 16/22 with
objects (73%), and 11/22 with actions (50%).
Lastly, the patient named correctly 9/16 (56%) definitions of objects described by the examiner. No
dysarthria or difficulty in individual phoneme production was noted. However, he showed the
reproduction conduction aphasic pattern of substitutions, deletions, insertions, and transpositions of
phonemes within words.3
A similar pattern occurred in reading aloud,
writing, and repetition. He read aloud promptly all
letters of the Italian alphabet presented in random
order (21/21, 100%) and performed at a similar
level when required to write letters to dictation.
Moreover, he read 61/63 (97%) syllables with a CV
structures (e.g., ba, ta, etc.) correctly. However, his
reading, writing, and repetition of real words were
affected. He correctly repeated only 10 words out of
45 (22%), read 56 out of 92 (61%), and wrote 23 out
of 46 (50%). The ability to perform a delayed copy
of words was almost spared (9/10). Finally, he spelt
aloud correctly 16/20 (80%) words (including
nouns, verbs, adverbs, and prepositions). LT also
had difficulties in repeating, reading, and writing
nonwords (19/36, 28%; 24/42, 57%; and 8/25,
32%, respectively). However, the delayed copy of
nonwords (5/6, 83%) was again almost spared. The
errors of word and nonword production were again
of a reproduction conduction aphasic type, as will
be discussed later.
It is conceivable that an inability to effectively rehearse material resulting from his speech production problem may be contributing to his mild impairment on some comprehension tasks. This possibility was not investigated further.
3
It is conceivable that his output problems may have led to an apparent input problem through his recycling information inappropriately. For simplicity we have ignored this possibility, which if it were true would merely simplify the argument presented in the
paper.
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COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
THE PHONOLOGICAL OUTPUT BUFFER
Comment
LT principally had problems in two domains—syntactic processing and in word production. His
problems in word production were, however, of a
specific sort. He made substitutions, insertions,
deletions, and transpositions in reading, writing,
and repetition of words, nonwords, and sentences.
These problems were also found in spoken and
written picture and action naming, where his difficulties arose from production rather than agnosic
problems. In the following section we examine in
greater detail the nature of LT’s pattern of errors in
writing, reading, and repetition and also in object
naming. His syntactic processing problems will be
treated as an additional deficit not relevant to the
theoretical purpose of the paper.
EXPERIMENTAL STUDIES OF
WORD REPRODUCTION
Study 1: Basic analyses of repetition,
reading, and writing
LT was asked to repeat, read, and write (using his
right hand) words and nonwords. There were two
sets of words (set A, N =203, and set B, N=104) and
Table 1. Percentages of correct responses made by LT in repetition,
reading, and writing words (set A and set B) and nonwords (set
C)
Repetition
Reading
Writing
Words
Set A (N = 203)
Test 1
Test 2
Total
65.0%
74.0%
69.5%
77.0%
78.0%
77.5%
48.0%
63.0%
55.5%
Set B (N = 104)
Test 1
Test 2
Total
50.0%
55.0%
52.5%
80.0%
73.0%
76.5%
60.0%
55.0%
57.5%
Nonwords
Set C (N = 192)
Test 1
Test 2
Total
27.0%
32.0%
29.5%
44.0%
46.0%
45.0%
24.5%
32.0%
28.0%
one of nonwords (set C, N=192). Since set A
included mostly short words, of which most were
nouns, we also administered a set B that contained
three- and four-syllable verbs and adjectives.
Nonwords were partly taken from Caramazza et al.
(1986), and partly made by substituting one letter in
a real word. All sets (A, B, C) were presented in
blocked fashion in two different sessions to allow a
consistency analysis of his responses to be made.
Each session required 2 months to be completed
and the two sessions were 1 month apart. Tasks
(repetition, reading, and writing) were counterbalanced for each set of stimuli.
A hierarchical fully saturated loglinear analysis,
with tests of partial associations, was applied to the
data. The factors were task (repetition, reading, and
writing), test (first and second sessions), set (A, B,
and C), and correct/error. An appropriate model of
the data does not require three-way and higher
interactions (c 2 (16) = 23.8, p > 0.05). The model
did require significant effects on correct/error of
task c 2 (2) = 99.1, p < .001, set, c 2 (2) = 320.7, p <
.001, and test, c 2 (1) = 7.3, p < .01, indicating some
improvement with practice.
Further analyses
Words (sets A and B) were categorised on several
dimensions: (1) concreteness; (2) part of speech (noun,
non-noun, and verb); (3) frequency, using a cut-off
of 25 occurrences per million in the CNR dictionary of frequencies (Dizionamo di Frequenze,
1990), and (4) number of syllables (ranging from 1 to
4). These variables are considered in turn.
Concreteness
LT’s repetition, reading, and writing responses
were analysed according to whether the referent of
the target word was concrete or abstract. The analysis was carried out on two subsets of pairs of concrete and abstract words drawn from sets A and B
respectively. The subsets were made by matching to
each member of the smaller sets (either of abstract
or of concrete words) one from the larger set of
words (either concrete or abstract) according to the
following criteria applied in order:
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
525
SHALLICE, RUMIATI, ZADINI
1. if a member of the larger set is chosen then it
cannot be chosen again;
2. the pair is the same part of speech (adverbs
were not differentiated from verbs);
3. the pair is from the same frequency band,
with all non-nouns with frequency values above 534
per million eliminated;
4. the pair has the same length in syllables;
5. when there is more than one candidate match
on the first four criteria, then the nearest in the
alphabet is chosen.
A, we compared nouns with other parts of speech
(non-nouns); in the second, selected from set B,
verbs were compared with adjectives. An analogous
procedure was used to the previous analysis, with
the selection from larger sample sizes using the
same criteria as before omitting criterion (2). The
results are shown in Table 3. There was no significant effect of part of speech for any of the three
tasks.
Frequency and length
LT’s performance with words was analysed according to their written frequency values and length.
Words were divided into high frequency and low
frequency sets. Word length was analysed in terms
of number of syllables (two, three, and four). Tables
4 and 5 show the numbers of words that LT wrote,
read, or repeated correctly, differentiated in terms
of word frequency and word length. A hierarchical
fully saturated loglinear analysis, with tests of par-
As shown in Table 2, there is no effect of concreteness on any of the three tasks for either of the
word sets.
Part of speech
In this section we examine whether LT’s difficulties
in repetition, reading, and writing are influenced by
part of speech. An analysis was carried out on two
subsets of words. In the first subset, drawn from set
Table 2. LT’s performance on repetition, reading, and writing using matched subsets of stimuli
Concrete
Abstract
Set A
—————————————
Repetition Reading
Writing
Set B
—————————————
Repetition Reading
Writing
19/36
(53%)
24/36
(67%)
16/36
(44%)
17/36
(47%)
26/36
(72%)
24/36
(67%)
18/36
(50%)
19/36
(53%)
26/36
(72%)
25/36
(69%)
18/36
(50%)
15/36
(42%)
Samples from set A include an equal number of two-, three-, and four-syllable concrete and
abstract words. Samples from set B contain an equal number of three- and four-syllable
concrete and abstract words. In both samples words are matched for part of speech,
frequency, and word length.
Table 3. LT’s performance on repetition, reading, and writing as a function of
grammatical categories using matched subsets of words (set A and set B, test 1 plus test 2)
Subset
Part of Speech
Syllables
Repetition
Reading
Writing
Set A
Nouns
2, 3, & 4
Non-nouns
2, 3, & 4
33/52
(63%)
28/52
(54%)
38/52
(73%)
35/52
(67%)
30/52
(58%)
24/52
(46%)
Verbs
3&4
Adjectives
3&4
24/60
(40%)
31/60
(52%)
43/60
(72%)
47/60
(78%)
36/60
(60%)
32/60
(53%)
Set B
Five monosyllabic words were not included.
526
COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
THE PHONOLOGICAL OUTPUT BUFFER
Table 4. LT’s performance on set A and set B, administered twice
Words
Length
Set A
Set B
Frequency
Repetition
Reading
Writing
2
High
3&4
High
2
Low
3&4
Low
101/124
(81%)
33/46
(72%)
93/134
(69%)
42/90
(47%)
107/124
(86%)
30/46
(65%)
110/134
(82%)
59/90
(66%)
90/124
(73%)
18/46
(39%)
66/134
(49%)
38/90
(42%)
3
High
4
High
3
Low
4
Low
36/52
(63%)
30/54
(56%)
21/46
(46%)
22/56
(39%)
47/52
(90%)
44/54
(81%)
34/46
(74%)
34/56
(61%)
40/52
(77%)
39/54
(72%)
17/46
(37%)
23/56
(41%)
Five monosyllabic words and one without a frequency value were not
included.
Table 5. The number of words from sets A and B and of nonwords (set C) (all administered twice) that LT repeated,
read and wrote correctly
Length
2 (N = 258)
3 (N = 210)
4 (N = 134)
Total (N = 602)
Words
————————————–
Repetition Reading Writing
194/258
(75%)
124/210
(59%)
60/134
(45%)
378/602
(63%)
217/258 156/258
(84%)
(65%)
160/210 105/210
(76%)
(50%)
88/134 70/134
(66%)
(52%)
465/602 331/602
(77%)
(55%)
Length
2 (N=136)
Nonwords
—————————————
Repetition Reading Writing
55/136
(40%)
3 (N=194)
52/194
(27%)
4 (N=52)
4/52
(8%)
Total (N=382) 111/382
(29%)
87/136
(64%)
74/194
(38%)
10/52
(19%)
171/382
(45%)
57/136
(42%)
47/194
(24%)
4/52
(8%)
108/382
(28%)
Five monosyllabic words and one without frequency value (robot) were not included. Length is measured in
terms of syllables.
tial associations, was applied to the data from sets A
and B. The factors were task (repetition, reading,
and writing), frequency (high or low),4 length (two,
three, and four syllables), test (first and second sessions), and correct/error. An appropriate model of
the data does not require three-way and higher
interactions, c 2 (45) = 34.46, p > .05. The model
did require significant effects on correct/error of
frequency, c 2 (1) = 59.1, p < .0001, length c 2 (1) =
46.9, p < .0001, task c 2 (2) = 73.8, p < .0001, and
test, c 2 (1) = 5.2, p < .05.
Both word frequency and length had a strong
effect on probability of correct performance and the
two variables did not interact with other variables in
the most appropriate model. Table 5 shows that for
all Task x Length combinations performance with
4
For set A, high-frequency words had a mean of 533 (SD 1479), whereas low-frequency words had a mean of 7.9 (SD 6.8). For set
B, high-frequency words had a mean of 89.6 (SD 62.2), whereas low-frequency words had a mean of 10.3 (SD 6.9).
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
527
SHALLICE, RUMIATI, ZADINI
words are much better than with nonwords.
Finally, most of LT’s responses were themselves
nonwords: in repetition 66%, in reading 75%, and
in writing 71%.
Summary
The main findings from previous sections are as follows. First, there was no effect of semantic or syntactic structure on performance. Second, LT
showed a somewhat superior performance with
reading over repetition and writing. Third, the
observed effect of lexicality, length, and word frequency were similar to those found in other phonological output buffer patients. Overall, the pattern
observed fits the characteristics typical of phonological buffer patients, as specified by Caramazza et
al. (1986). By contrast the reproduction conduction
aphasic studied by Pate et al. (1987) did not show a
word frequency effect; it seems probable that this
patient’s impairment was at a more peripheral stage
of processing.
Error Analysis
In the present section a more fine-grained classification analysis is presented. The following classification was used.
Single errors, generally involving one phoneme
(or letter) (either consonant or vowel), or geminate
are categorised as one of the following:
1. Deletion (D).
2. Insertion (I).
3. Substitution (S).
4. Move (an error in which a phoneme/letter
moves from its original position within the word).
5. Transposition (T) (an error in which phonemes/letters exchange places within the word).
6. Stress (an error in which a word is read or
repeated with the accent on the incorrect syllable).
We called double errors any combination of two
such errors involving two phonemes/letters (either
consonants or vowels), irrespective of their positions within the word.
Errors affecting more than two phonemes of a
word are called:
528
COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
1. Fragment: an error in which more than one
syllable is omitted.
2. Complex: a response that includes more than
two errors.
3. Omission: a failure to give any response.
However, omissions and fragments have been
ignored because they comprised less than 1% of all
responses.
A quantitative comparison between the magnitude of the errors in the different types of task is
shown in Table 6. It is clear that quantitatively repetition and writing are remarkably similar with
reading errors being generally quantitatively somewhat smaller, which fits with the relative success
rates in the three tasks overall.
A more detailed analysis is shown in Table 7.
Two conclusions may be drawn from it. First there
is a remarkable quantitative and qualitative similarity in error types both between nonwords and words
and, to a lesser extent, across tasks. The slight
reduction in insertion and deletion errors for reading can again be explained by the fact that reading
can be carried out on smaller units than repetition
or writing. This is confirmed by the analysis of error
position within the word given in Table 8. For
reading there is no change with the syllable position, but for all eight repetition and writing comparisons except one there is a consistent increase in
error rate through the word. A final analysis concerned the phonological relation between target
phoneme and error phoneme in the case of substitutions. The sub-tables for repetition, reading, and
writing of words (Table 9 a, b, c) and nonwords
(Table 9 d, e, f) again show a related pattern with a
significant tendency for phonologically similar
errors to occur in all cases but one: rf = .56, c (1) =
11.89, p < .001 for repetition of words; rf = .87,
Fisher Exact Test p < .005 for reading words; rf =
.61, c (1) = 15.47, p < .001 for writing words; rf =
.54, c (1) = 19.88, p < .001 for repetition of
nonwords; rf = .46, Fisher Exact Test p < .005 for
reading nonwords; rf = .16, c (1) = 1.56, p > .25 for
writing nonwords; in all cases comparing stop consonants against nasals plus liquids; considering only
errors where the stimulus and responses were stops,
nasals, and liquids (so as to retain a sufficiently large
cell size). This fits with an explanation in terms of
THE PHONOLOGICAL OUTPUT BUFFER
Table 6. Percentages of single, double letter, and complex errors (including
fragments and omissions) out of the total errors that LT made in repeating,
reading, and writing words (set A and set B) and nonwords (set C)
Words
Set A (N = 406)
Tests 1 & 2
Total Errors
Set B (N = 208)
Tests 1 & 2
Error Type
Repetition
Reading
Writing
Single
Double
Complex
54.0%
25.0%
21.0%
30.5%
62.5%
26.5%
11.0%
22.5%
51.0%
24.5%
24.5%
44.5%
Single
Double
Complex
45.0%
25.5%
29.5%
47.5%
66.0%
20.0%
14.0%
23.5%
56.0%
20.0%
24.0%
42.5%
Single
Double
Complex
44.0%
27.0%
32.0%
70.5%
59.0%
26.0%
15.0%
55.0%
34.5%
28.0%
37.5%
72.0%
Total Errors
Nonwords
Set C (N = 384)
Tests 1 & 2
Total Errors
Table 7. Percentages of individual types of errors as well as their combinations, out of the total number of single and double
errors, that LT made in repeating, reading, and writing words (set A and set B) and nonwords (set C)
Error Type
Repetition
—————————
Words
Nonwords
Reading
—————————
Words
Nonwords
Writing
—————————
Words
Nonwords
Single Errors
Substitutions
Deletions
Insertions
Transpositions
Moves
Stress
46%
7%
8%
4%
1%
1%
45%
4%
5%
5%
1%
–
57%
3%
2%
2%
1%
7%
53%
7%
5%
3%
1%
1%
46%
6%
10%
5%
1%
1%
38%
6%
9%
2%
–
–
Double Errors
Multiple Substitutions
Multiple Deletions
Multiple Insertions
Multiple Transpositions
Multiple Moves
16%
8%
8%
2%
1%
21%
7%
5%
5%
2%
14%
5%
4%
4%
1%
20%
5%
2%
4%
1%
16%
5%
6%
4%
1%
24%
9%
5%
6%
2%
Total
168
184
124
182
201
171
For double errors, the error is counted as half in each of the basic types. Thus a double error Substitution
counts one half as a Multiple substitution, one half as a Multiple insertion.
+ Insertion
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
529
SHALLICE, RUMIATI, ZADINI
Table 8. Number of words (set A and set B administered twice) and
nonwords (set C, administered twice) that LT failed to repeat, read and
write as a function of error position within the word
Length
Type
2
3
Syllable
Repetition
Reading
Writing
Words
I
Words
II
Nonwords
I
Nonwords
II
Words
I
Words
II
Words
III
Nonwords
I
Nonwords
II
Nonwords
III
12/258
(5%)
32/258
(12%)
7/136
(5%)
41/136
(30%)
21/210
(10%)
8/210
(4%)
20/210
(10%)
12/194
(6%)
12/194
(6%)
41/194
(21%)
14/258
(5%)
13/258
(5%)
22/136
(16%)
15/136
(11%)
12/210
(6%)
11/210
(5%)
11/210
(5%)
37/194
(19%)
25/194
(13%)
21/194
(11%)
19/258
(7%)
40/258
(16%)
21/136
(15%)
23/136
(17%)
12/210
(6%)
20/210
(10%)
25/210
(12%)
8/194
(4%)
10/194
(5%)
43/194
(22%)
This table contains only errors (single or double) affecting only one
syllable in the word.
Table 9. Substitution errors made by LT in repeating, reading, and writing both words (a, b, c) and
nonwords (d, e, f) in terms of the phonemic category of the stimulus and response: Stimuli are plotted by
row, responses by column
Words
Nonwords
a. Repetition
Stops
Nasals
Liquids
Stops
11
2
2
d. Repetition
Nasals
1
7
4
Liquids
3
3
5
b. Reading
Stops
Stops
Nasals
Liquids
530
Stops
36
4
2
Nasals
4
5
5
Liquids
5
7
1
Nasals
26
–
1
Liquids
5
1
–
7
5
2
Stops
22
6
6
Nasals
4
3
1
Liquids
6
5
2
e. Reading
Nasals
5
1
–
Liquids
–
4
–
1
5
–
c. Writing
Stops
Nasals
Liquids
Stops
Nasals
Liquids
Stops
Stops
Nasals
Liquids
f. Writing
Stops
13
3
3
Nasals
–
5
5
Liquids
2
6
4
COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
Stops
Nasals
Liquids
THE PHONOLOGICAL OUTPUT BUFFER
loss of information in the phonological buffer for
repetition and writing, with a reduced effect by use
of a different strategy in reading.
Experiment 2: Picture naming compared
with repetition
In this experiment we compared LT’s ability to
name pictures to confrontation with his ability to
repeat the corresponding names. LT was asked to
name 34 line drawings and to repeat the corresponding 34 names, counterbalancing the 2 tasks in
an ABBA design. Pictures and words were presented one at a time. On the picture naming task
LT scored 19/34 (56%) and on the repetition task
27/34 (79%). In picture naming he made nine single phoneme errors (seven substitutions, one insertion, and one transposition) and three double
phoneme errors (substitution plus substitution,
substitution plus insertion, and transposition plus
substitution), and three complex errors. In the repetition task LT made four single errors (three substitutions, one insertion), two double errors (two
insertions plus substitutions), and one complex
error. The types of errors LT made in naming pictures are qualitatively similar to those made in
repetition.
Summary
The pattern of errors produced by LT is remarkably
similar across reading, writing, and repetition. The
basic errors are substitutions, deletions, insertions,
transpositions, and phoneme/letter moves. They
occur at a similar rate across tasks and in single
error, double error, and complex error combinations, with slight differences in reading which are
explicable in terms of a more serial/ sequential
mode of processing being applied. In phoneme substitutions, the response phoneme tends to be phonologically similar to the target. Overall the pattern
is strikingly similar to that obtained in the output
phonological buffer patients described in the
Introduction.
PHONOLOGICAL MANIPULATION
AND SHORT-TERM MEMORY
Given the relevance for the present study of demonstrating that LT’s errors in repetition are not secondary to a phonological short-term memory
deficit, we further investigated his ability to temporarily hold phonological information in a series of
digit and word span tasks.
Experiment 3: Phonological manipulation
Bisiacchi et al. (1989) argued that their patient’s
poor reading of nonwords might conceivably have
been caused by an inability to manipulate phonemes. They tested this ability by asking him to
count sounds in spoken words and nonwords. Since
in Italian there is a very high correspondence
between graphemes (number of letters) and phonemes (number of sounds), this task could well be
carried out using orthographic strategies. They
took this possibility into account by comparing performance on items in which the number of sounds
corresponds to the number of letters with performance on items in which it does not (e.g., in Italian,
ch and sc followed by i or e, gl followed by i, and gn,
can correspond to only one phoneme). If a patient
were to use orthographic strategies for counting
phonemes, then performance should be better with
the former set of items.
LT was asked to count the phonemes in 30
words and 30 nonwords. Half the words and half
the nonwords were characterised by a one-to-one
correspondence between letters and sounds. He
counted phonemes correctly for 15/15 words and
14/15 nonwords. For the remaining words and
nonwords there were more letters than sounds. He
counted phonemes correctly for 13/15 of both
words and nonwords. Overall, LT’s ability to
manipulate phonemes was spared. No significant
differences between words and nonwords, or
between the same or different number of sound to
letter correspondences were observed.
Experiment 4: Digit span test
In the neuropsychological evaluation LT’s digit
span appeared normal. However, very few trials
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
531
SHALLICE, RUMIATI, ZADINI
were used. In order to provide further evidence on
the integrity of his phonological short-term memory, we ran an additional experiment where 10 trials
for each span length, ranging from 4 to 8, were
used. The stimuli were presented auditorily by the
experimenter and the patient was required to repeat
them aloud in the same order in which he heard
them. The experiment was replicated 2 months
later.
As shown in Table 10, LT’s scores confirmed
earlier results. To be counted as correct, the digit
had to be accurately produced. LT’s performance
on this test was not dissimilar to that of five control
subjects without history of brain damage and
matched for age and education (mean age = 68
years, range 63–74). He made slightly more errors
at short span lengths, which is hardly surprising
given his speech production problem, but he is
insignificantly above the mean at lengths six and
seven (it should be noted that Italian digits have two
syllables and so span is slightly less than in English).
Experiment 5: Probe recognition using
words and nonwords
To assess the efficiency of auditory-verbal short
term memory in LT when speech production problems were eliminated, we carried out a probe recognition task. In this task LT was required to
recognise whether a word or a nonword had been
previously said by the experimenter. We ran three
versions of this task. In the first version, LT had to
decide on every trial whether a target word, or a
Table 10. The performance of LT and controls on a digit span test
No. of
Digits
4
5
6
7
8
532
LT
—————————–
1st Session 2ndSession
9/10
(90%)
6/10
(60%)
6/10
(60%)
2/10
(20%)
0/5
7/10
(70%)
6/10
(60%)
6/10
(60%)
2/10
(20%)
0/5
Controls
—————————
Mean
Range
9.6
9–10
8.2
7–10
5.0
2–7
1.4
0–3
0.0.
–
COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
nonword, was one of four just said by the examiner,
at the rate of one each second. In the second version
we used six words (or nonwords), and eight in the
third. When the probe word occurs in the list, its
position within the set of the words (or nonwords)
to be recognised was varied.
LT performed well on this task with both words
and nonwords, irrespective of the number of alternatives among which he had to recognise the target
(see Table 11). His performance on this test was
similar to that of five control subjects without history of brain damage and matched for age and education (mean age = 68 years, range 57–74).
Experiment 6: Span and syllable structure of
words and nonwords
On the Hartley and Houghton (1996) model an
improvement in span should be obtained if all
words have the same syllabic structure. In order to
assess whether his performance was affected by syllable structure, LT was required to repeat triplets of
words. The words used had three different types of
syllable structure: CCVCV (from now on called
(SS1), CVCCV (SS2), and VCCCV (SS3). All the
words had the same length (five letters). Words
were presented at the rate of one per second.
The experiment, which involved two blocks, was
run twice. In each block, two kinds of triplets were
used. Half of the triplets (N=12) comprised words
(N=36) having the same syllable structure (three
triplets with SS1, three with SS2, and three with
SS3). These triplets of words were called “identical
structure.” For the other half, each triplet (N=12)
contained words (N=36) each of which had a different syllable structure (SS1, SS2, and SS3). These
triplets of words were called “mixed structure.”
In the second block, the design and procedure
were the same as in the first block. Words contained
in the identical triplets were taken from mixed triplets in the first block, while those used in the mixed
triplets were taken from the identical triplets of the
first block. The presentation of sets of identical and
mixed triplets of words was alternated within each
block. The first block began with the identical triplets and the second with the mixed ones. Using the
same design and procedure, a second experiment
THE PHONOLOGICAL OUTPUT BUFFER
Table 11. Results obtained by LT on a probe recognition test together with the mean
and range of five control subjects
Length
4
6
8
Words
————————————
Controls
———————–
LT
Mean
Range
Nonwords
————————————
Controls
———————–
LT
Mean
Range
22/24
(92%)
19/24
(79%)
22/24
(92%)
21/24
(92%)
20/24
(83%)
18/24
(75%)
23.0
22–24
21.4
20–23
21.2
20–23
22.4
21–24
21.6
20–23
20.0
18–22
was carried out in which words were replaced by
nonwords. Nonwords were obtained by substituting only a single phoneme in each of the words used
in the previous experiment. As Table 12a shows, no
differences in performance were found between the
identical and the mixed conditions for either words
or nonwords. A detailed analysis of different error
types showed them to be virtually identical both
quantitatively and qualitatively across conditions,
with no significant differences between them. It is
clear from these results that span performance is not
affected by repetition of the structure of the syllable
involved, in conflict with predictions derived from
the model put forward by Hartley and Houghton
(1996).
Twelve control subjects, matched for age and
education to LT, performed clearly better than LT
on Experiment 6. However, the prediction derived
from the Hartley and Houghton model that repetition of mixed syllable nonwords should be more
taxed than repetition of identical syllable nonwords
was not supported (see Table 12b).
Table 12. Performance on repeating three words of “identical” or
“mixed” structure
(a) The mean of LT’s correct responses across two testing sessions
involving both word and nonword stimuli
DISCUSSION
Words
Correct
—————————
Responses Identical
Mixed
LT is a patient with a number of aphasic problems.
However, his difficulties in single word production
tasks can be accounted for by a specific deficit
within the production system. Thus his performance on single word tasks that did not involve
production was far better than if production was
required, and when the ability to retain input phonological information was stressed, performance
was normal (see Experiment 5). More critically, his
error production was quantitatively and qualitatively equivalent, in all conditions, whether the
input was presented auditorily (repetition, writing
to dictation) or visually (reading, object naming).
The one minor exception is that reading performance was quantitatively slightly better for the second and later syllables in a word than in the other
conditions (see below), but there was still no quali-
3
2
1
0
2.0
8.0
10.0
4.0
4.5
6.0
10.5
3.0
Nonwords
—————————
Identical
Mixed
0.0
1.0
11.5
11.5
0.0
2.0
12.5
9.5
(b) The mean number of correct responses involving words and
nonwords of 12 control subjects (mean age = 72.8 years, range of
education 3–8 years)
Words
Correct
—————————
Responses Identical
Mixed
3
2
1
0
17.7
4.9
1.4
0.0
18.2
4.4
1.2
0.2
Nonwords
—————————
Identical
Mixed
4.3
8.8
7.6
3.4
4.1
7.8
6.9
5.2
Basic pattern of performance
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
533
SHALLICE, RUMIATI, ZADINI
tative difference. Thus, there is no major influence
on the pattern of errors from any impairment to a
particular input system.
Turning to the nature of the production difficulties, a number of properties were listed in the Introduction which Caramazza et al. (1986) showed to
hold for the nonword production of IGR and which
they argued could result from an impairment to the
phonological buffer. All were also shown by RR
(Bisiacchi et al., 1989) and also by MV (Bub et al.,
1987) (except for writing). These properties are all
also shown in LT in nonword production tasks and
in word production tasks too.
5. For all three basic tasks the predominant error
types are single substitution errors and multiple errors
containing a substitution. Table 7 also shows that
this property holds for LT.
6. The ratio of consonant-vowel errors on substitutions is comparable across all three basic tasks. For LT,
62% of all single substitution errors for nonword
repetition were consonants, 57% were for reading
nonwords, and 59% were for writing them. While
the rate is rather lower than for IGR (repetition
81%, reading 81%, writing 68%), the critical point
that there is a close similarity across the three basic
tasks.
1. Repeating, reading and writing all produce
many errors which have a common pattern. Tables 6,
7, and 9 clearly indicate that this is also true for LT.
2. There is a marked effect of length in all basic
tasks. This is also found in LT (see discussion of
Table 4). The somewhat better quantitative level
of performance on reading fits with Caramazza et
al.’s findings, which they interpret in terms of a
“part-by-part processing strategies,” which in turn
fit with ideas that the phonological reading route
can operate on less than a whole-word entry
(Coltheart et al., 1993; Làdavas et al., 1997). This
is further supported by the relative decrease in
substitution errors in reading compared with repetition, and by the reading not showing an increase
in errors for later syllables in the word (see Table
8).
3. Error phonemes tend to bear a phonological relation to the target phoneme in all basic tasks. Table 9
shows that this is also true for LT in all three basic
tasks.
4. Errors are predominantly phoneme/letter substitutions, insertions, additions, and transpositions or
pairs of such errors. Evidence that this is so for LT is
presented in Tables 6 and 7. While more complex
and omission errors are made by LT than by IGR
and RR, at least 60% of his errors in all conditions
fit with the prototypic types.
The similarity in pattern of performance both
across patients and across tasks raises two issues.
The first is whether the patients have the same functional syndrome in the sense of Plaut and Shallice
(1993), 5 that is whether the nature of the impairment of the functional architecture is qualitatively
equivalent for each. Such a hypothesis can never be
proved. However, given the controversial nature of
the concept of syndrome even in the above sense (see
Caramazza, 1986; Shallice, 1988, 1991, for discussion), it is worth considering whether the qualitative
similarities extend to quantitative ones. Figure 3
shows the probability of an error involving only a
single letter/phoneme plotted against the probability of a correct response.6 In fact, while LT’s score
must be to the left of the other patients as he has a
generally poorer performance, there is no a priori
reason why it should lie on the same curve as those of
the other patients. It can be seen that LT’s scores fit
well to the same curve as the other patients’.
The quantitative similarity can be extended to
the rate of substitution errors. Figure 4 shows the
probability of a single error being a substitution also
plotted against the probability of a correct response.
There is a gentle decline with reduction in percentage correct. However, the critical point is that the
values of all patients fit the pattern well. Thus LT’s
pattern of performance fits with those of the other
5
It should be underlined that a functional syndrome may refer to only part of a patient’s overall impaired performance—see
Beauvois et al. (1978) for discussion.
6
For LT as for RR, the only other patient who provides useful data, the word values lie somewhat below the nonword curve. An explanation for this can be given from the attractor-basin account developed later.
534
COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
THE PHONOLOGICAL OUTPUT BUFFER
Figure 3. Percentage of single phoneme/letter errors made by the four patients on nonwords: LT; IGR (Caramazza et al., 1986); MV
(Bub et al., 1987); RR (Bisiacchi et al., 1989); plotted against their corresponding correct rate. For all patients the values for repetition,
reading and writing are plotted separately (except for patient MV—writing). The best fitting quadratic curve is given passing through
(0,0).
patients quantitatively as well as qualitatively. It
may provisionally be assumed that their functional
syndrome is the same.
The second conclusion concerns the relation in
the pattern of performance across the three tasks
within each patient. LT, like the other three
patients, shows not only qualitative similarities
across tasks, but also quantitative ones (see Tables
13 and 14). There are some differences between
patients as to which of repetition and reading they
find easiest. In addition, writing is considerably
worse than other tasks in MV and RR. Moreover
there appear to be differences between the three
other patients, for instance in the rates of insertions
by comparisons with deletions. However, for IGR,
the prototypical output phonological buffer
patient, and for LT, the differences in pattern
across tasks in Tables 13 and 14 are really minor. By
an analogous logic to that used for similarity of performance across patients, the similarity in pattern
of performance across tasks provides evidence that
we are not dealing merely with associated deficits.
Therefore following the theoretical inference procedure of Caramazza et al. (1986), this implies that
a common (set of) component(s) (X) is used in the
performance of the three basic tasks—at least in
patients like LT—and that they are impaired in
LT, or that they are operating normally in LT but
damage to another more powerful procedure has
left him reliant on them. This second possibility
seems implausible, except possibly for writing,
where a lexical writing route (see Shallice, 1981)
exists for English patients; its status for Italian
patients is less clear.
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
535
SHALLICE, RUMIATI, ZADINI
Figure 4. Percentage of single errors for nonwords that are substitutions for each of the four patients. For all patients the values for
repetition, reading, and writing (if more than 10 single errors) are plotted separately.
Table 13. The percentages of single or double or complex errors made by LT and by three other patients: IGR (Caramazza et al., 1986),
MV (Bub et al., 1987), and RR (Bisiacchi et al., 1989) for nonword and word stimuli
Error
Rates
Nonwords
Single
Double
Complex
% correct
Words
Single
Double
Complex
% correct
Repetition
———————————————
IGR
MV
RR
LT
Reading
———————————————
IGR
MV
RR
LT
Writing
———————————
IGR
RR
LT
61
18
21
76
69
31
–
53
95
5
–
87
44
27
32
30
83
17
–
85
71
29
100
?
?
?
90
–
100
–
98
50
25
25
61
*
*
*
98
42
83
17
–
63
59
26
15
45
77
18
5
71
58
35
7
40
35
28
37
28
?
?
?
91
*
*
*
97
64
24
12
77
76
24
–
97
36
55
9
86
53
23
24
56
* = too few observations to be useful; ? = the values are not given by the authors.
536
COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
THE PHONOLOGICAL OUTPUT BUFFER
Table 14. The percentages of different types of single errors—involving only one phoneme/letter—made in repeating, reading, and writing
nonwords and words by LT and by three other patients: IGR (Caramazza et al., 1986), MV (Bub et al., 1987), and RR (Bisiacchi et al.,
1989)
Single Errors
Nonwords
Substitution
Insertion/Add.
Deletion
Transposition
Total
Words
Substitution
Insertion/Add.
Deletion
Transposition
Total
Repetition
——————————————
IGR
MV
RR
LT
81
11
3
5
(63)
*
80
8
12
–
(114)
80
–
13
7
(15)
*
Reading
——————————————
IGR
MV
RR
LT
75
8
7
9
(110)
81
13
6
–
(70)
71
12
10
6
(108)
*
62
12
23
3
(50)
*
74
6
21
–
(34)
79
7
10
4
(122)
88
4
5
1
(81)
Writing
——————————–
IGR
RR
LT
68
13
17
2
(114)
83
7
10
–
(41)
68
17
11
4
(94)
91
9
75
16
10
8
(122)
–
–
(11)
Only conditions where 10 or more errors were made are included.
* = too few observations to be useful.
As argued by Caramazza et al., the obvious
locus for a component common to the three basic
tasks is the phonological output buffer. Thus it is
in the appropriate part of the speech production
system; it is “below” the level of semantic processing and also of any output phonological lexicon, as
the findings in LT are similar for words and
nonwords. Moreover it is “above” any phonetic
processing level and the stage at which the writing
process diverges from speech production. Error
phonemes tend to bear a phonological relation to
their targets.
Could the results be explained by a difficulty in
generating a phonetic code from a phonological
code, independent of short-term memory aspects?
These are three characteristics of LT’s impairment
that argue against such an account. One is the
strong effect of word length. A second related effect
is the way that most errors occur in the last syllable
in repetition and writing. This fits with a simple
trace decay or interference hypothesis. Interestingly, the pattern differs from that typically
observed in graphemic output buffer patients where
a bow-shaped serial position curve is generally
found for errors (e.g., Caramazza et al., 1987;
Shallice et al. 1996, but see Badecker, Hillis, &
Caramazza, 1990, for an exception) but is more
similar to that in short term memory patients
(Saffran & Martin, 1990). Finally there is the existence of transposition errors, which are well above
the level expected from the base rate of multiple
substitutions. However, as will be apparent when
we discuss the CQ model, in using the term “output
buffer” we do not want to argue for a separable unit
with a fixed set of slots.
At this point it is useful to consider the disorder
in relation to two other putative buffer disorders—
the short-term memory syndrome (e.g., Vallar &
Shallice, 1990; Warrington & Shallice, 1969) and
the graphemic buffer syndrome (Caramazza et al.,
1987; Shallice et al., 1996). Thus, characteristic 4 is
the complementary characteristic to that occurring
for letters (not phonemes) in the graphemic buffer
syndrome. Characteristic 5, however, although not
being in any sense a difficulty for the phonological
buffer hypothesis, is not simply explained by it.
Thus, the 15 values for substitutions errors in Table
14 lie between 62% and 91% of all errors. In
graphemic buffer patients, for instance, the rate of
substitution errors is considerably lower and the
rate of such substitution errors lies between 30%
and 50%. In Table 15 the maximum rate of transposition errors is 9%. In the graphemic buffer
patients reviewed by Shallice et al. (1996), with the
exception of one patient with a very mild impairment, all patients made more than 15% transposiCOGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
537
SHALLICE, RUMIATI, ZADINI
Table 15. A comparison of the rate of single and double phoneme errors in repeating multisyllabic nonwords of LT, IGR, and RR (16 errors only) with that produced by Hartley and
Houghton’s (1996) simulation, in which 2–6 syllable nonwords are presented to their model
with its time decay parameter reduced in half-life
Single Phoneme Errors
Substitution
Deletion
Insertion
Transposition
Multiple Phoneme Errors
Double substitutio n
Substitution & Deletion
Substitution & Insertion
Other double transpositions/insertions
Expected on
Simulation
LT
IGR
RR
55
21
1
0.3
47
4
4
6
62
2
8
4
75
13
0
6
6
8
9
0
16
4
4
13
18
1
2
1
0
6
0
0
Each column gives the percentages of the overall number of single and double phoneme
errors.
tion errors. There is thus almost no overlap in these
rates between the two syndromes. In STM patients
too, substitutions would also be considerably lower
and deletions higher. We will return to this issue
later.
The separability of input and output
phonological processes and buffers
The findings obtained with LT are relevant to two
issues concerned with the relation between input
and output phonological processes. Classically,
within cognitive neuropsychology the two processing systems and related buffers were held to be different (e.g., Howard, 1993; Howard & Franklin,
1990; Patterson & Morton, 1980; Shallice &
Warrington, 1977; Monsell, 1987). However, this
view has been increasingly criticised (e.g., Allport,
1984; Campbell, 1990; Martin & Saffran, 1992).
One type of support for the separability of input
and output phonological processing systems comes
from descriptions of patients whose impairment is
best described by a disconnection of the two (see
Shallice, 1988, Chapter 7 for discussion). One possible interpretation of the pattern of performance
observed in IGR and RR is that it results from a disconnection of input and output phonological systems, in other words it corresponds to a classical
conduction aphasia (Lichtheim, 1885; McCarthy
538
COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
& Warrington, 1984). To account for the overall
pattern of reading nonwords one would need to
assume that the disconnection also affects the phonological reading route; anatomically such a combination of deficits seems quite possible (see
McCarthy & Warrington, 1984; Paulesu, Frith, &
Frackowiak, 1993). However, this is not a plausible
explanation for LT’s difficulties as he shows the
same error pattern in object naming (see Experiment 2), where the phonological output buffer
must be accessed from the phonological output lexicon and the semantic system and not from the phonological input buffer, as in repetition of nonwords.
Thus the disconnection account is not a strong
candidate.
In another respect LT’s overall performance
strongly supports the existence of both input and
output phonological buffers. The pattern of performance shown in certain output phonological buffer
patients described earlier has been used to support
the position that “the phonological buffer system
occupies space within the short-term phonological
store” (Bisiacchi et al., 1989). Thus Bisiacchi et al.
point out that their patient RR had an auditoryverbal short-term memory impairment. Her digit
span was only 3; IGR and MV also had reduced
spans. So did the patient GC of Romani (1992),
who had an apparently similar spontaneous speech
difficulty. However, Romani convincingly shows
THE PHONOLOGICAL OUTPUT BUFFER
that if GC does not have to produce speech, as for
instance in probe tasks, his performance is normal.
She therefore argues that GC’s pattern of impairments supports the two-store position. Moreover, a
reproduction conduction aphasic of Wilshire and
McCarthy (1996) had a relatively normal span
performance.
This is also the case for LT, whose phonological
output buffer deficit was considerably more severe
than that of any of the other patients discussed and
yet he performed normally on a word probe span
task and had a digit span of 6.25, a normal level in
Italian speakers. The most critical result is his performance above the mean level for longer strings, as
for shorter strings, where normal subjects are at
ceiling, the unreliability of an impaired output system will almost inevitably lead to below-normal
performance. When considered in the context of
patients such as JB (Shallice & Butterworth, 1977;
Warrington, Logue, & Pratt, 1971) and PV (Vallar
& Baddeley, 1984), who have phonological store
impairments and yet can speak normally and can
also reproduce single words virtually normally, one
has a classic double dissociation. Given the argument presented earlier that LT has an impairment
of a phonological store, this supports the assumption that there are (at least) two quite distinct forms
of syndrome within the conduction aphasia complex (Shallice & Warrington, 1977)7 and that these
correspond to impairments of two quite different
stores. In this respect the investigation supports the
conclusions drawn from the patients of Romani
(1992) and Wilshire and McCarthy (1996). The
results do not fit with theories that essentially collapse the two stores into one (e.g., Martin &
Saffran, 1992).
If LT has a phonological output buffer impairment, why does this not lead to a lower digit span?
The presupposition is that the phonological input
buffer has much greater capacity than the phonological output buffer (see Shallice, 1975, 1979b)
and is no more affected by interference or decay.
Then if the relative vulnerability of items in the end
and middle positions is roughly comparable across
the two stores, when information is lost from the
7
input store it will no longer be represented in the
output store. Digits, being very high-frequency
items, can in general be output satisfactorily or
rehearsed using the damaged phonological output
buffer. However this does not apply to words,
which leads to a reduced span for such material in
LT even though his digit span is intact. Thus the
sole role of the output buffer in span is to act as a
conduit for the rehearsal or production of each
word in turn.
One surprising aspect of this theoretical conclusion is the localisation of the lesion. The lesion
spares Broca’s area but involves parts of both the
supramarginal gyrus (Brodmann area 40) and
Wernicke’s area. As the best estimate of the location of the (input) phonological buffer is left hemisphere Brodmann area 40 (Paulesu, et al., 1993), it
is possible that we are seeing an example of minor
re-localisation of a function into the region adjacent
to the lesion.
The hypothesis of a route bypassing the
phonological output buffer
Caramazza et al. (1986), Bub et al. (1987), and
Bisiacchi et al. (1989) all interpreted their patients
as having a problem essentially limited to
nonwords. This led Caramazza et al. to use the syndrome to support a novel architectural proposal.
They suggested that a transmission route existed
from the phonological output lexicon to a “lexicalarticulatory representation system” that could
bypass the phonological output buffer in the production of known words. This hypothesis led to an
apparent contradiction, because in normal sentence
production the phonological buffer appears to be
involved because of the existence of phoneme
exchange errors (e.g., Garrett, 1980). Yet IGR did
not make the types of errors he made in nonword
reproduction when repeating short sentences and a
complex ad-hoc explanation had to be produced for
the lack of such errors.
However, Bub et al., (1987), starting from similar findings, do not make the assumption of a separate route for lexical information. Instead they
A third type has also been discussed by McCarthy and Warrington (1984).
COGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
539
SHALLICE, RUMIATI, ZADINI
argue that “lexical levels of representation could be
used to compensate for the impoverished quality of
traces in the buffer” (p. 105). From the perspective
of LT’s performance the Caramazza et al. hypothesis of a bypass procedure is unnecessary. As Table 7
indicates, LT shows just the same quantitative and
qualitative pattern of different error types in repeating, reading, and writing words as he does for
nonwords. This strongly suggests that whatever
impairment affects the processing for nonwords
also affects that of words. In addition, LT shows a
considerably higher basic level of performance with
words than nonwords. Thus the obvious explanation for LT’s pattern of performance is that the two
types of stimuli differ in the quantitative amount of
the damaged resource they require for adequate
production (Shallice, 1979a), which relates to the
position advanced by Bub et al. of word representations being less vulnerable than those of nonwords.
Would such an explanation also work for IGR,
MV, and RR?8 First, their nonword results lie
roughly on the same overall functions as those for
LT for two variables relating to task performance
(see Figures 3 and 4) but are higher on the curves
than the results of LT. Thus placing the patients on
a single dimension of impairment to an unidimensional resource fits the gross aspects of their
performance well. Moreover, from Tables 13 and
14 it can also be seen that their performance with
nonword stimuli is qualitatively similar to that of
LT with words. One small difference is that single
phoneme errors are somewhat less likely in all three
patients at a given level of performance for words
than for nonwords. This will be discussed later.
However, overall it is clear that for all patients their
performance is also qualitatively similar for words
and nonwords.
Most critically, the absolute difference between
word and nonword performance for LT is 28–34%
across the three basic tasks. The performance of
IGR and RR for nonwords on three of the six basic
tasks lies between 76% and 87%, so the fact that
their performance on words for these tasks is virtually 100% is hardly surprising when considering the
resource hypothesis. For the other three tasks, their
8
improvement in performance for words by comparison with nonwords is 34% (RR—reading); 26%
(IGR—writing); and 46% (RR—writing), while
MV shows 37% and 49% improvements, much the
same magnitude on average (38%) as the superiority
for words over nonwords shown by LT (32%).
Without a quantitative theory of the relation
between resource loss and performance, it would be
premature to treat this rough equality as strong evidence for the resource position. However it shows
that it would be premature to draw any theoretical
conclusion from the qualitative dissociation shown
by IGR, RR, and MV. The use of the concept
resource, moreover, undermines the claim of the
philosopher of science, Glymour (1994), that the
concept has no utility in the drawing of inferences
from neuropsychological evidence to the organisation of normal cognition.
We will return later to the issue of how the
resource requirements placed on a supposedly
nonlexical output buffer can be affected by the lexical status of the stimulus. However, it should be
noted that a similar qualitative and quantitative
relation between performance on nonword and
word stimuli in the graphemic buffer domain has
been generally accepted as indicating that both
types of stimuli are processed using the same buffer
(e.g., Caramazza et al., 1987). Thus there seems to
be no neuropsychological justification to propose a
route bypassing the phonological output buffer.
Expectations based on “Competitive
Queuing Theories”
The Hartley-Houghton theory is a hybrid between
a connectionist model and a symbolic one. It is a
localist model trained by Hebbian learning, but also
containing much internal structure so as to realise
the innate specificity of the speech production system. Such a model transcends the barren ideological debates between supposedly innate structuralist
positions and supposedly tabula rasa connectionist
ones. It may be seen as a detailed model of how
phonological information is temporarily retained in
No attempt was made by Hartley and Houghton to fit MVs results, but they do not seem likely to present a problem for the theory.
540
COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
THE PHONOLOGICAL OUTPUT BUFFER
the speech production system; in other words it can
be viewed as one type of implementation of the
phonological buffer model, but one where part of
the concept of “buffer” disappears. It does not retain
the sense of copying temporary representations into
a separate store. Indeed, from another perspective,
it could be viewed as a more detailed implementation, with respect to its phoneme ordering and
short-term storage aspect, of a model such as that of
Dell (1986) or with somewhat more licence as to
how a phonemic code is generated from higherlevel one.
The other great advantage of the HartleyHoughton theory, as mentioned in the Introduction, is its quantitatively accurate predictions of the
rates of the different error types in patients IGR and
RR, in particular the high rate of substitution
errors. How does the theory fare with respect to
LT’s errors? Given our previous analysis one would
expect to use a different weight-decay parameter
from that used to fit the results of IGR and RR.
Table 15 compares LT’s performance with the
model’s predictions when one uses the same parameter values as in Houghton and Hartley’s fit to IGR
and RR’s data. In fact the basic single substitution
rate is fitted as well for LT by this parameter as for
IGR and RR. However, the addition of LT’s result
underlines certain deviations between the patients
and the model. The very low predictions for insertions and, in particular, for transpositions suggest
that the way the architectural constraints, which are
a key part of the model, are realised may make it a
little too inflexible as far as variations in phoneme
order are concerned. Whether the model would
perform better with different weight-decay parameters remains a challenge to the theorist. In any case
we assume that with minor alterations the model
should be able to deal with all aspects of the
findings.
One other aspect of LT’s behaviour that needs to
be considered with respect to the model is his performance in word reproduction. It is argued by
Hartley and Houghton that: “A global increase in
the rate of decay in the temporary weights of the
network will cause more phonological misorderings
for unfamiliar materials,” which fits the findings
well. However, they also say: “Familiar materials
(words) will not be similarly affected, because the
connections in this pathway are permanent. However a general reduction in memory span is to be
expected because the connections between the
internal content units and syllable units representing both words and nonwords are temporary ones.”
This fits well with findings both from IGR and RR
in the sense that they both have reduced spans and
their performance with word stimuli appears to be
qualitatively different from their nonword performance. However, neither of these predictions made
by Hartley and Houghton fits with the word production results of LT. In our view the model needs
to be revised by separating phonological input
buffer processes from phonological output buffer
ones. This will mean that under some circumstances memory span performance per se is not relevant to the model.
A possible advantage of the competitive queuing
approach, however, arises when one compares
“phonological buffer” patients such as those discussed in this paper with “graphemic buffer”
patients. The two types of patients perform qualitatively very similarly in their respective domains.
However, there are interesting quantitative differences. Thus, as discussed earlier, for every phonological buffer patient who performed in the 20–90%
correct range for repetition, reading, and writing,
over 60% of the single phoneme errors were substitutions (see Table 13). However, for graphemic
buffer patients the equivalent rate of substitutions
of single letters is 30–55% (see Shallice et al., 1996).
Why do these differences occur? One possible
explanation, based on the competitive queuing
(CQ) model, comes from the assumption of parallel
activation of the set of phoneme/letter nodes
involved in producing the word and of the internal
word structure. The Hartley-Houghton model of
spoken word production—a hybrid between a symbolic and a connectionist model—incorporates a
complex structure having both between- and
within-syllable constraints. This has the effect of
“fixing” the ordinal position of a phoneme in the
word fairly efficiently—deletions, insertions, and,
in particular, transpositions becoming relatively
infrequent. For writing, on the Houghton et al.,
(1994) model, position context constraints are limCOGNITIVE NEUROPSYCHOLOGY , 2000, 17 (6)
541
SHALLICE, RUMIATI, ZADINI
ited to representations of each letter’s distance from
the word’s beginning and distance from the word’s
end; this is a development of the assumptions
involved in the typing model of Rumelhart and
Norman (1982). The “weaker” structure presumed
for the writing process allows more opportunities
for errors where the ordinal position of a letter is not
maintained, so substitution errors become, relatively speaking, a smaller proportion of all single
element errors. However, the existence of the end
distance node present in the spelling simulations
lead to a bow-shaped pattern of errors in the writing
model.
Whether other aspects of the graphemic buffer
syndrome fit with the idea that it has a less complex
internal structure than the phonological output
buffer remains a matter of debate. That letter gemination is realised by a separate process is generally
agreed (Caramazza & Miceli, 1990; Jonsdottir,
Shallice, & Wise, 1996; Miceli, Benvegnu, &
Caramazza, 1995; Tainturier & Caramazza, 1996).
Moreover, there are strong arguments for the
existence of vowel/consonant distinctions (Cubelli,
1991;
McCloskey,
Badecker,
GoodmanSchulman, & Aliminosa, 1994; Miceli et al., 1995).
However, the critical issue is whether syllabic
organisation is realised though a specific orthographic symbolic structure; here there is a clear
conflict of interpretations of empirical evidence
(see Jonsdottir et al., 1996, for discussion and
Caramazza & Miceli, 1990; McCloskey et al., 1994
for a conflicting perspective).
The word-nonword qualitative differences
The key empirical results of the present paper are,
however, those that support the idea that the production of nonwords and words involves the same
mechanisms at the level of phonological buffer processes, and that apparent dissociations between
them can be explained in terms of resource differences in the processing of nonword and word
stimuli. It should be noted that the quantitative
differences in performance comparing word and
nonword stimuli is much less in the output buffer
case than in, say, phonological alexia (see, e.g., RG,
542
COGNITIVE NEUROPSY CHOLOGY , 2000, 17 (6)
Beauvois & Derouesné, 1979; GRN, Shallice &
Warrington, 1980; AM, Patterson, 1982). Hartley
and Houghton presuppose that there are two types
of input to the phoneme nodes, which carry the
content information: one for “novel phonological
forms” and one for familiar phonological forms,
which can be used in isolation from each other. If
one accepts the conclusions of the present paper,
that the lexical/nonlexical differences at the “phonological buffer” level involve resource rather than
structural differences, then how should the lexical/
nonlexical difference be modelled?
An alternative to the localist approach adopted
by Houghton et al. (1994), however, is to assume
that the lexical representation is provided by an
attractor structure, as in reading models (e.g.,
Hinton & Shallice, 1991; Plaut & Shallice, 1993).
Then, the existence of learned attractors in the language processing system at a particular level will
allow words and nonwords to use the same processing route and yet to show performance differences
following lesions. As an analysis by Plaut and
Shallice (1993, see p. 411) shows, the existence of
attractors “protects” words, but not nonwords, from
some of the impairing effects of a lesion, given that
the lesion precedes or is at the stage in the processing system which has attractor characteristics. If
one assumes that the depth of the attractor is influenced by word frequency, which is natural given
that increased word frequency is realised on a model
by an increase in training trials (see, e.g., Plaut et al.
1996), then the word frequency effect found would
be predicted. Its virtual absence in IGR, RR, and
MV would arise through the much smaller degree
of impairment in their cases and their being at
ceiling.
Localist connectionist networks do not naturally
have attractor characteristics. However, within the
writing domain, Glasspool, Shallice, and Cipolotti
(1999) have investigated a multi-level distributed
net which has attractor properties realised at the
output (letter) level representation, in an analogous
way to that of the output phoneme level of Plaut
and Shallice (1993). However the Glasspool et al.
net attempts to realise a number of characteristics of
the localist competitive queuing models by having
input units that represent the distance of letter posi-
THE PHONOLOGICAL OUTPUT BUFFER
tions relative to key points (beginning, end) and by
having processes analogous to the suppression of
activation following selection of a letter. In the
writing domain such a model shows somewhat similar “breakdown” characteristics to that found in the
graphemic buffer patients and by the localist competitive queuing model. Moreover, the differences
in the behaviour of the model between how it processes word and nonword stimuli are quantitative
rather than qualitative. A similar model could in
principle be developed as a distributed version of
the Hartley-Houghton model and would be
expected to show similar properties to that model
with respect to the effect of lesions except that the
effect would apply to a reduced extent for words and
for nonwords. This would therefore fit the pattern
shown in LT.
Conclusions
In this paper we have considered the performance
of a patient who, in his nonword performance, was
similar to patients who have been characterised as
having an “output phonological buffer disorder” in
that the effects were qualitatively equivalent for
repetition, reading, and writing, with a quantitatively reduced impairment in reading. Moreover, in
the pattern of errors produced, the patient essentially resembled these output phonological buffer
patients. However, in LT the properties of word
processing were qualitatively and in many respects
quantitatively equivalent to those for nonword processing. It was argued that the dissociations
between the two in the output phonological buffer
domain were better explained by “resource” differences between the processing of the two types of
stimuli than by qualitative differences in the processing procedures. It was speculated that the overall pattern could be produced by a model that
combined an attractor architecture and distributed
representations with aspects of the competitive
queuing architectures developed by Houghton
(1990). However, it remains to be seen whether
such a model could be effectively implemented in
the speech output domain.
Manuscript received 24 July 1998
Revised manuscript received 4 August 1999
Revised manuscript accepted 13 August 1999
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