The British Journal of Psychiatry (2008) 193: 354-356. doi: 10.1192/bjp.bp.108.049387
© 2008 The Royal College of Psychiatrists
Digit symbol coding and general cognitive ability in schizophrenia: worth another look?
Dwight Dickinson, PhD
University of Maryland School of Medicine, VISN 5 Mental Illness
Research, Education and Clinical Center, Baltimore, Maryland, USA. Email:
Dwight.Dickinson{at}va.gov
Declaration of interest
None.
Dwight Dickinson (pictured) is Associate Professor of Psychiatry with the
University of Maryland School of Medicine and VISN 5 Mental Illness Research,
Education and Clinical Center.

ABSTRACT
For decades, schizophrenia researchers have sought to map specific
aspects
of cognitive performance onto specific neurobiological
systems in hopes of
dividing broad cognition and neurobiology
into more tractable components.
Recent findings from studies
using neuropsychological test batteries, in
combination with
emerging neurobiological evidence, argue for a complementary
focus on more generalised cognitive and biological dimensions.

INTRODUCTION
An article of faith in schizophrenia cognitive research is that
it should
be possible to link relatively specific behavioural
processes (e.g. executive
functioning performance as measured
by card sorting tasks) to relatively
specific neurobiological
substrates (e.g. activity in dorsolateral prefrontal
cortex
systems), and that such work will carve schizophrenia cognition
into
more discrete, genetically simpler, and potentially treatable
components. In
the face of complex neurobiology and significant
illness heterogeneity,
progress along this path has been slow.
Advances in genetics and new
electrophysiological and neuroimaging
technologies promise better defined and
ever more specific
targets on the biological side of the analysis. At the same
time, there are active efforts to translate precise experimental
paradigms
into user-friendly instruments for the clinical measurement
of
behaviour.
1 It seems
likely that these advances will yield
reliable and specific brain/cognition
associations, some of
which may be particular to subgroups within the
schizophrenia
spectrum. But will the associations prove as useful in
deciphering
schizophrenia as we hope? On the behavioural side, in particular,
the price of progress seems to be a focus on increasingly rarefied
behaviours.
2,3
Yet, it is not clear that cognitive functioning
can be parsed meaningfully to
the same degree as underlying
biology. It may be that, in the drive to
understand the illness
at a molecular and mechanistic level, the field will
lose its
focus on the complex systems of behaviour that are ultimately
the
heart of the illness and the keys to functioning in the
community.
Notwithstanding waves of exciting new work, it remains
the case that
schizophrenia impairs most complex cognitive
operations to a similar degree
with few exceptions, that the
largest documented effect sizes in the
schizophrenia cognitive
literature have been for traditional and often simple
neuropsychological
measures, and that this is the class of measures that is
most
clearly associated with functional outcome among people with
schizophrenia (reviewed by
Heinrichs
4). These
straight-forward
and persistent findings should raise questions among the
faithful.

Digit symbol coding in schizophrenia
Neuropsychological measures have been central to schizophrenia
cognitive
research for decades, and their wide use
continues.
5 Familiar
examples include word list learning (i.e. verbal memory),
card sorting (i.e.
executive functioning), and span tasks (i.e.
working memory). In contrast to
these measures, less attention
has been devoted to coding tasks, such as the
Wechsler Digit
Symbol Substitution
Test.
6 These tasks
– which have
not changed fundamentally since their introduction a
century
ago
7 –
reflect the coordination and speeded performance
of a number of uncomplicated
scanning, matching and motor operations.
Performance does not appear to be
associated with particular
regional or functional brain systems. However, the
measures
are extremely brief (5 min to administer and score), are more
reliable than other well-known neuropsychological measures,
are sensitive to a
wide variety of developmental and clinical
conditions, as well as normal
ageing, and are often present
in research batteries.
Surprisingly, a recent meta-analysis demonstrated that these simple
measures discriminate people with schizophrenia from comparison individuals
better than the more widely studied neuropsychological
instruments.8 Across
37 studies, 1961 people with schizophrenia and 1444 healthy controls, coding
tasks showed a schizophrenia impairment that was both substantial
(g=–1.57) and significantly larger than effects derived for
other measures. Indeed, only one of 36 comparison measures considered in the
meta-analysis showed a nearly comparable effect across studies (category
fluency, g=–1.45). The coding task effect was reasonably
homogeneous despite striking differences in samples and designs from study to
study (range g=–1.05 to –2.02). The magnitude of the
effect was not sensitive to medication status or symptomatology. The coding
task effect did differ in predictable ways as a function of
schizophrenia chronicity/severity groupings (i.e. first
episode<chronic<very-early onset). Still, these differences were modest,
and in each of these patient subgroups the coding task effect size was larger
than effects obtained for other cognitive variables. In addition, an offshoot
analysis revealed a substantial coding task effect size among unaffected
relatives of people with schizophrenia. Other studies have reported that
coding performance also predicts functional status. Overall, coding tasks
produce a robust impairment signal that differentiates healthy controls from
people with schizophrenia and their close relatives better than other
measures, and indexes poor prognosis and functional disability.
The meta-analysis also highlighted the generalised nature of cognitive
impairment in schizophrenia (see also Heinrich &
Zakzanis9). Across
all measures, the mean weighted effect size was g=–0.98, and a
number of familiar measures, including IQ, word list learning, story memory,
mental arithmetic, and the `AX' version of the continuous performance test,
showed values well above this average (range g=–1.10 to
–1.29). Thus, the review reaffirmed a broadly generalised cognitive
deficit in schizophrenia, and provided evidence of a small, disproportionate
effect on simple coding tasks and, to a lesser degree, on some other
measures.

General cognitive ability in schizophrenia
Other work with collaborator Jim Gold suggests a `general cognitive
ability' framework for understanding these results. In schizophrenia
investigations, generalised cognitive impairment has often
been treated as a
nuisance variable or artefact that obscures
more cognitive domain-specific
effects (e.g. in domains of
verbal memory or executive functioning; see Albus
& Hubmann
10).
However, the general ability findings are robust and similar
across
heterogeneous schizophrenia subgroups and very different
sorts of analyses,
suggesting that they should not be dismissed
as artefact. We have used
statistical modelling to characterise
the structure of cognitive performance
within the schizophrenia
group,
11 and of the
cognitive deficit in affected persons
relative to healthy
controls.
12,13
The latter studies were
consistent in suggesting that about two-thirds of the
diagnosis
effect on cognitive performance was mediated through a general
ability factor, with a limited number of small effects (notably,
in the
processing speed
domain)
12,13
(
Fig. 1).
More generally, the factor-analytic literature argues for a
hierarchical
model of cognitive test performance – with
individual tests loading on
first-order cognitive domain factors,
and these factors loading in turn on a
single, higher-order
general cognitive ability factor. The heart of the
hierarchical
model is the idea that generalised cognitive ability or
`
g'
underlies much, but not all, of performance in different
cognitive
domains and on individual cognitive
measures.
14
Thus, our modelling work and meta-analytic results converged on key points:
first, highlighting the prominence of the generalised cognitive impairment in
schizophrenia; and second, showing that certain measures and domains,
including coding tasks, were disproportionately impaired to a small but
significant degree. It seems to follow from the findings regarding generalised
cognitive structure in schizophrenia that much of what is measured by
traditional neuropsychological assessment measures – whether they are
generally held to tap verbal memory or executive functioning or some other
domain – is broad cognitive ability, not independent, domain-specific
performance.

Significance of findings from neuropsychological battery studies
These lines of research frame a critical question: do general
cognitive
ability interpretations of neuropsychological findings
in schizophrenia mainly
reflect limitations of existing measures
or do they reveal something
fundamental about the structure
of cognition in this disorder? One possibility
is that coding
and most other neuropsychological tasks are so inherently
multifactorial
that their utility for probing specific biological or treatment
effects in schizophrenia is sharply
limited.
1 If so,
then
measurement techniques adapted from cognitive neuroscience,
serving as
intermediate phenotypes for genetically defined
targets, may finally enable
researchers to carve schizophrenia
cognition `at its
joints'.
2,3
However, this outcome is uncertain.
Even assuming further progress in
isolating discrete behaviours
in schizophrenia and connecting them with
biological markers,
it could turn out that the target behaviours have been
stripped
down to a degree that leaves their relationships to important
everyday outcomes obscure.
Another possibility is that the generalised cognitive deficit is a
fundamental manifestation of schizophrenia. If so, then one path to improved
understanding of the pathophysiology of cognitive impairment may emerge from a
fresh look at the neurobiological associations of general ability. Several
lines of evidence emerging in the field are consistent with the hypothesis
that the neurobiology underlying generalised cognitive dysfunction is likewise
general in nature. Examples include: (a) broadly reduced grey matter and
neuronal arborisation; (b) diminished myelin density and fibre coherence in
major white matter tracts; (c) poor signal integration at the level of the
cell and the network due to cortical background noise and reduced neural
synchrony; and (d) abnormalities associated with the brain's main excitatory
and inhibitory neurotransmitters, glutamate and
-amniobutyric
acid.12
Importantly, related findings are emerging in healthy groups and among
unaffected relatives of people with
schizophrenia.12
Some have hypothesised roles for even more general biological processes, such
as oxidative stress, inflammation and energy
metabolism,15
possibilities that might begin to recast schizophrenia as a general, systemic
disorder, rather than a focal brain disease. Findings from outside the
schizophrenia literature supporting `generalist genes' for cognitive
development, performance and impairment also seem
relevant.16
Neuropsychological measures show an excellent ability to discriminate
affected individuals and their relatives from controls and to index disability
among those
affected.4 This may
be precisely because they are sensitive to such generalised biological
effects. Coding tasks, in particular, appear to measure impairment in
integrating or coordinating distributed brain networks, more so than failures
connected to specific sub-processes. This `systems' level is a potentially
critical level of analysis for schizophrenia and, therefore, the relatively
diffuse measurement focus of coding tasks and other similar measures might be
seen as a strength of the instruments rather than a
weakness.1 In sum,
emerging evidence provides a basis for renewed interest in the generalised
cognitive deficit in schizophrenia and suggests that investigation of
associations at more integrated levels of cognition and neurobiology should be
pursued in balance with more mechanistically targeted research.

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Received for publication January 4, 2008.
Revision received June 18, 2008.
Accepted for publication June 24, 2008.
Related articles in BJP:
- From the Editor's desk
- Peter Tyrer
BJP 2008 193: 434.
[Full Text]