lntraub
-
close-up
Visual
scenes
scenes J. Exp. Psycho/.
27 Intraub,
H., Bender,
but remembering 28 Intraub,
scenesJ.
H. and Bodamer,
aspect
of plctorlal
Learn.
Mem.
29 Intraub,
Mem.
representation
Cogn.
Cogn. 15. 179-187
J.A. (1992) Boundary
Cogn. 18, 180-191 Fundamental
artifact?
1. Exp. Psycho/.
or encoding
33 Finke, 34 Farah, from
Boundary
extension
for
briefly
result
in
R.A. (1985)
glimpsed
M.J. (1988)
35 Kosslyn. Science:
unexpected
and imagining
objects and scenesJ. Exp. Psycho/. Learn. Mem. Cogn. (in press) 31 Intraub, H. and Berkowits, D. (1996) Beyond the edges of a picture
relating
mental
imagery
C. Olson
and Glyn
Artificial
neural
systems.
But does studying
understand recent
networks
cognitive
37
really
visual?
Overlooked
attempts
K. and
in An invitation S. and Orherson,
Coll~nr,
W. (1984)
across eye movementsJ.
Ramachandran. et al. Perception
models
with
evaluate
simulated
some
concerning
VS. (1995) 24, 841-845
more
double
We also
impaired
can incorporate strategies.
Ar
tificial an intuitive
dissociations
forms
within
of internal
questions these
Filling
tasks
models,
with
chronometric
connectionist
that
and possible
research,
patterns
the utility
model
ought
models
of the models of internal
can be generalized higher-order
ing may therefore
be
rehabilitation
development
to larger-scale
linguistic
provide
within what might artificial. Moreover, help to constrain
of
can sometimes connectionist
of different
the models
In addition,
help us to
Here we review
can be used to
between
we discuss
can accommodate
data).
to Durgln
of
using
like humans,
Finally
the role
neural networks (‘connectionist models’) have appeal that is grounded in their neuron-like
comparison
reply
of real neuronal
damage?
studies
and demonstrate
structure. For example, connectionist models typically depend on interactions between many processing units, and the algorithms involve processing states that evolve over time (allowing
pictorial
Gen. 113. 426-442
in gaps I” logic:
in neuropsychological
associations
structure.
whether
they
brain
such lesion made
and
concern
aspects
disorders
the effectiveness
models,
and whether
how
lesioned
of two
and predicting
Future
simulations,
We show
how
to Cognitive D.N., eds),
Integrating
Exp. Psycho/.
in such models
following
neuropsychological
assumptions
illustrate
on the easier
for understanding structure
lesions.
embody
of performance
in humans
different
of the standard
both
impairment.
models’)
the breakdown
to capture
evidence
W. Hwmphreys
(‘connectionist
impairments
to perceptlo”
Rev. 95, 307-317
Connectionist models neuropsychological disorders Andrew
and of
MIT Press A., Rayner.
information Am.
imagery
Psycho/.
M.K. (1995) Mental imagery, Visual Cognition (Kosslyn,
36 Pollatsek,
109, 581-598
Is visual
neuropsychology
pp. 267-296,
C.V. and Bills, A. Remembering
Theorles
for size of drawings
Psychof. Bull. 98, 236259
19, 1387-1397
H., Gottesman,
J. Psycho/.
32 Legault, E. and Standing, L. (1992) Memory photographs Percepr. Mot Skills 75, 12,
at pictures
extension:
Do common perceptual processes distortions? 1. Mem. Lang. 35, 118-134
30 Intraub,
Looking
Exp. Psycho/. Learn. Mem. J.A. (1993)
H et al. (1996)
pictures: memory
Learn.
R.S. and Mangels,
disorders.
a way to understand
the workings
otherwise be a black box, whether real or studies of brain-damaged patients may theoretical development, since a valid
CO break
down
in a way that is consistent
with
the learning of new states is based on changes to weighted connections between processing units. These properties hold for real neural sysrems too, even if rhere are differences in the
the empirical data. The other side of this relationship is that the development of a model can also help us to understand what might otherwise be a confusing pattern of behavioural data. Here we review attempts to apply connectionist mod-
particular learning or in the operation
els to neuropsychological insights that this form
algorithms used by individual modellers, of processing units in their models’. Also,
like real neural systems, specific parts of a network can be identified that perform specific functions (such as representing a particular form of knowledge), and their behaviour can break down when the system is damaged. Selective lesion-
CopyrIght
0 1997, Elsevier
Trends
in
Cognitive
Science
Ltd. All rights
Sciences
-
Vol.
reserved. 1,
1364.6613/97/117.00 No.
6,
September
Modelling
Over
and
the
results, and consider of modelling may offer.
use of neuropsychological
the past 10 years or so, a substantial
nectionist
models
have
PI,: S1364m6613(97)01072-3 1997
been
developed
the special
data
number and applied
of conto a
Olson
and
variety of neuropsychological disorders cognition, including: reading*-j, visual
in many areas of attention’-“), face
recognition”
spelling’3m’5.
speech
emerging
body
nectionist brain
of work
models
injury
production”
that occur
after brain
may
have
systems. normal
damage.
The
is composed
assumption
we shall
models
with
and
discuss
specific
neuropsychology
the application
regard
they are particularly Double
to their
of connectionist
ability
to predict
effec-
Since connectionand generalization,
promising
for this last topic.
case
of acquired
is that the
processing trasting
affected
occur
studies
neuropsychological
ble dissociations
and anatomi-
that can be selectively
dissociations:
One fundamental
of breakdown
of functionally
components
of
cognitive
the patterns
Finally,
Connectlonism
for our
seeks to understand
by studying
system
cally specialized
this
-
tive therapies for cognitive rehabilitation. ist models have mechanisms for learning
to assess how con-
of normal
research
This
to our understanding
and modelling systems
cognitive
it possible
the implications
Neuropsychological cognitive
makes
can contribute
and
understanding
and
Humphrey5
can imply
components
the presence
I’ . This
some of the different after
brain
is that dou-
of two independent
can be illustrated
forms
damage.
dyslexia
inference
of acquired
In surface
by con-
dyslexia
dyslexia”~“,
that
patients
by brain damage. Thus, an adequate model of the normal system must allow a variety of disruptions that will produce
have difficulty in reading words with irregular spellingsound correspondences (for example ‘yacht’) but can read
all of the relevant
impair-
regular
detailed
errors
ment
observed
discussion
patterns
within
of neuropsychological
the clinical
(for a more
data
of this logic see Refs 16 and 17).
nouncing
One complication of this logic is that neuropsychological disorders need not exclusively reflect the functional ganization
of the brain.
aspects of a patient’s
There
implementational,
aspects
the quantitative
distribution
affected by factors that are vulnerable of brain
is no a priori
behaviour
of the cognitive
organization
Identifying
ficult
system.
to
Indeed,
impairment
will
may be orthogonal
be
factors
to read
for a system’s
letter
(or
Assuming
of pro-
words
be peripheral units
learning aspect
(for
example,
used in a model,
algorithm
used).
it can provide
the exact number or perhaps
If a model
valuable
characteristics
mance,
and this uncertainty
why
central
can increase
the
perfor-
data provide
tease apart
the functional
the brain,
an important
powerful
and anatomical part
of linking
neurobiological theories of the mind. Space precludes a discussion of models that
have
a small
been number
studied.
tools for trying
Consequently,
of examples
(from
particular)
can constrain
will consider sociations within necessary
how inferences between
patients; ro infer
patients we examine
modelling
(and
can be drawn and from how
the functional
associated
patterns
of
double
phonological
representations forms
successfully
surface
on
regular
significant
that originally
irreguchallenged
was Seidenberg and to generate distributed
for both
(see Fig.
network
capture
regular
and irregular
on the corresponding 1). This
distributed
model
the details of either
and
phonological
dyslexia.
logic
was unable
to
reading’,
or
normal
be put in doubt. In introducing the model,
they
highlight
features
that
We
original
dis-
eralize
over
different
it is relevant surface
decide
that
‘r’ is pronounced
by completely
instances
may be
coded
and we
rounding context (for ‘grab’, and ‘barn’ could
deficits in which by a brain lesion.
units:
in
Cognitive
validity
of
dissociations ro note adjust-
surface
dyslexia,
since
dyslexia
reveals
about
in humans. One change inused by the model. In the
the representations
of error
double
to simulate
the underlying reading system volved the form of representation model
If so, the
concerning
ments that were necessary
behaviours
Trends
and non-
A single
not only
of reading which learned
locus of damage;
ask if models can capture counter-intuitive the easier of two tasks is most affected
separated. may
but may also represent
neuropsychological
and that data (in
vice versa). from
words
and colleagues*, and our interest is in whether one component of the new model can be damaged to produce both
and agnosia)
that test standard neuropsychological inferences demonstrate the ways in which neuropsychological
used
irregular
accounts modelah
could
dyslexia
is the
models of readir$‘,“. framework the procedures words,
trained
process
based on the in the language.
to sound
after being
entries for uses a non-
the full range of reading impairments”‘. A revised (and more successful) version of the model has been proposed by Plaut
and
focus
regular
to
One
processes
dual route McClelland’s
in all of the areas we will
words.
correspondences
of this kind
capture
to
organization behavioural
of perfor-
conversion
network
orthographic
characteristics of the model and can relate these characteristics to the model’s performance. Despite these difficulties, and patient
One
words
if the way a model
pattern
ways of reading
need not be functionally
larities.
functions is opaque18. This problem becomes less important if the modeller can identify specific peripheral and central
models
feature of dual route Within a connectionisr
correspondences,
or pe-
for a model’s
in
and non-lexical
lexical
that maps spelling
attributable to be so relevant.
clear whether
are responsible
of the
in a central
about
deficiencies may not
it is not always
ripheral
is deficient
information
theory is inadequate; however, aspects of the implementation Unfortunately,
the nature
(pro-
and has been taken
for nonwords
letter-sound
for pronouncing
will
of the
forms
Conversely,
opposite
grapheme)-to-sound
separate
aspects
cessing
Many
‘cave’).
dissociation
pronunciations
be central
and other
with
This
a double
that constructs
main
they implement
well. irregular
procedure uses a lexicon, which has whole-word both regular and irregular words; the other
behaviour is important for computer modellers as well as neuropsychologists. Some aspects of computer models will to the theories
nonwords.
most common
are responsible
to rhyme
mance is termed
lexical
to the
of the system.
which
‘have’
relatively
of ‘regularizing’
show that there are two possible
like vascular architecture, the cell types to disease and the anatomical proximity
areas, and these factors
functional
or-
as opposed
and nonwords
phonological dyslexia”-a5 patients may have little problem in reading irregular as well as regular words, but find it dif-
way of assigning
to functional, of a given
words
take the form
different
made it difficult of a letter
(for
/r/),
a letter
since
units
example, be coded
to gen-
example,
according
to
could
be
to its sur-
the ‘r’ in ‘red’, ‘guard, by 1 I different processing
#re, red, uar, ard, rd# etc.; see Fig. 1). The new model
Sciences
-
Vol.
1,
No.
6.
September
1997
Output phonology middle front middle
back nasal interrupted
a preponderance words.
-‘Wickelfeatures’
# liquid low
continuant vowel voiced
In contrast
front high unvoiced
short stop #
potted
reading
system
the double
dissociation
units
Within
that words
uar ard lad #PO men rd# #to #re quo
1 Architecture McClellandzB.
orthography resentations features hidden
of the ‘single-route’ This model was trained
and phonology used random (for units
phonology). and both
to simulate sets of letter
removing hidden units5. In other or reducing weights on connections vation (units), changing
function+‘~“. dendrites
letter triples-word
Plaut
instances, between
These manipulations (connections), reducing
neurotransmitter
function
by Seidenberg representations
model
‘lesioned’ random
noise)34.
At present
functionally of lesioning
whether
question
parts
of
and surface as well as a
testing
to read using
separate
(1) The tional
for prodissoci-
the revised
to available
pathway whether,
is damaged), for example, connections
results embodied
implicate
in surface
two
and the computer
within
a single,
fully
are
are consistent
separate
simulations
for the logic of neuropsychological
sociations
and
before func-
of dyslexias.
connected
and func-
provide
inferences
on double-dissociations. At least in relatively models, it has not been possible to produce
contrasting effects (in some cases they is the most appropriate for different
who
routeL5,
but non-semantic
does
of
dyslexia
patients
but non-semantic
dissociation
model
neuropsychologi-
of both
the full pattern
dyslexia
components,
support
route
by double
phonological
these modelling conclusions:
double
phonological
these
lexical
two com-
a traditional
lexical
allowed
is required
a lexical
to explain
component This
from
whether
comparable
Nevertheless, three general
with
by adding noise noise to the acti-
it is unclear
a direct
be able to simulate
Detailed
also needed
of the connections between (phonological) units, and by
networks have been units and by adding
(adding
to a single
a semantic
in its details,
(involving
et al. would
tionally
of
can be thought analogous to removing neurons the number of synapses (connection weights), or
different forms of lesioning can produce are clearly equivalent), and which form forms of neuropathology.
no rewas able
both
in particular).
the model (when the semantic we can judge more adequately
spelling-to-sound conversion in reading. These reptriples (for orthography) and triplets of phonetic by removal and output
may differ,
at a level of detail
is ‘red’
reading model proposed to map between distributed
Dyslexia was simulated input (orthographic) units
lesions
phonological
containing
nonwords
It is an empirical
arn ogh ed#
appear
Fig. and
a model
system
cal data.
Input orthography-
between
nunciation), but the conclusions ations remain in force.
0 a “’ red ffi ord
Thus,
not able to produce
may be read) and the spelling-sound
dual-route
#re eet alk
words.
were
(affecting
ponent
ast ier #br #bo ed# sp#
dyslexia,
of the model
spelling-sound component, phonological dyslexia would presumably result if the semantic component is spared (so impaired
#ba dea thr
on irregular
associated with phonological word reading together with im-
of novel
component dyslexia.
Intermediate
of surface
to a single component
to produce the pattern dyslexia: spared irregular
lesions:
&Remove connections &Remove Units Add noise to weights Reduce weights
responses
to the simulation
lesion
paired
Possible
of regularization
based
large-scale double dis-
network
(see also
Ref. 34). had
syllable-specific
vowels,
slots
about
letter-sound
since, for example,
and McClelland orthographic
higher-level
In addition, required meaning
the successful from
whole word phonological Essentially, the semantic the correct
input
of irregular
network
Cognitive
Sciences
-
Vol.
models
model),
leaving usual
a full setrain-
etal.,
presence dyslexic
of a symp-
route was removed: and nonwords and
1,
Even when sound
words,
in the
over letters between
of
the more
led to surface
model
was, at least
and phonological
distinguish
via
Although by Plaut
rams being captured when the semantic there were few errors on regular words
in
izations
activation
from semantics). take responsibiliry
free to learn
correspondences. was not implemented
additional
NO.
6,
September
models
are able to simu-
in part,
due to the
representations
it used. The
models demonstrate that successful modelling of reading disorders requires representations that can support general-
for reading
involves
pathway
that computer
appearing
(3) Neuropsychological
pathway
which
to phonology
are de-
of surface dyslexia
representations pathway could
the spelling-to-sound
‘semantic’
simulation
pronunciation
the spelling-sound grapheme/phoneme mantic pathway
pronunciations
and phonology,
pathway,
For exam-
(see Refs 31-33). a reading
orthography
(a semantic
generalizations.
that vowel
coda context
a contribution
to that between
both
the
to combuilding
on their
now
(2) The patterns
late are directly related to the representations and processes the models embody. The failure of the initial Seidenberg
onset units, and the ‘r’ in ‘guard’ and ‘barn’ coda units. It also provided appropriate
pendent
Trends
consonants,
generalizations to com-
for encoding
would
ple, it has been argued
ing
allowed
be assigned
blocks
for
to onset
This
correspondences
‘r’ in ‘red’ and ‘grab’ mon mon
devoted
and coda consonants.
component
in different
specific
models
are quite
powerful
of
neuropsychological
contexts.
cases can provide
the
data that can
of cognitive
Seidenberg
and
port
McClelland
data will enable us to make cru-
cial distinctions between alternative models suggesting the need for at least two processing These modelling
systems.
(as was the spelling-
(in this routes).
case
conclusions do not derive exclusively from the process. In this example, modelling provides sup-
for a methodology
in general,
and for the conclusions
in particular, that originated in studies of neuropsychological cases. Modelling is not a requirement for drawing valid inferences case studies time,
from
an exciting
1997
neuropsychological
in these areas of dyslexia prospect
data,
as the
show.
for these modelling
detailed
At the same efforts
is that
Olson
they
offer
garding
the possibility
the form
other
language
of investigating
of representations
Humphreys
-
Connectionism
and
neuropsychology
issues re-
reading
(and
- Semantic units
Output
abilities).
Associations
and error
types:
deep
Another set of recent computer ferent type of neuropsychological associated
detailed
mediating
and
deficits.
ment,
associations
ciated
deficits
neuropsychological
argu-
For traditional have
been
may occur
components
a diffrom
treated
because
are, by chance,
with
two
caution.
separate
affected
l
0.00
dyslexia
models has examined inference, drawn
0000a00
Clean-up units implement
‘attractors’ Ul
Asso-
Intermediate
functional
by a single
units
lesion.
Some have claimed that associations can only support relatively weak conclusions because symptoms thar associate in one patient Others
may be found
have said there
inferences ations.
to dissociate
in future
is no principled
that can be drawn If an association
from
associations
extends
patients”.
distinction
beyond
between
Position 1
and dissoci-
comparable
0000 BCDG
levels
of performance, to details of types and distributions of errors, for example, associations may provide good evidence that two
tasks depend
Two
recent
damage about
on the same
models
illustrate which
modelling
associations
will
Fig. 2 Architecture ing. ‘Input’ units tic microfeatures
brain
can lead to expectations occur
(in this
case, associ-
Seidenberg
types of error in reading), and we can play a valuable role when com-
neuropsychological
data with
data from
semantics (modified Ref. 3). This model
proposed
a model
for reading
and extended by Plaut and Shallice, see maps letter strings to sets of semantic
to this system would
produce
the set of associated
that has been termed
deep dyslexia.
fied as deep dyslexics
typically
reading errors, including: visual errors (idiot-idol),
Patients
symptoms
who are classi-
implement with known
High
low imagery
words,
In standard
dual-route
attributed
words are read more accurately
and nonwords
are particularly
models of reading, to more
than one deficit
‘attractors’that words. These lesioned
1). this
which
we describe
the model
that are not the most highly
model
has a feedback
loop
in the text.
allows
activity
to be transmitted activated
even
by
at a given level
(we will follow others in calling this cascade processing”). (2) Activation is governed by ‘attractors’ which push actitowards
states
conforming
representations
to known
for abstract
for concrete
words
stimuli.
(3)
are sparser than
words.
Plaut and Shallice lesioned the model by removing a variable proportion of connections at a variety of locations
than
between
the units
representing
of errors
to independent
representing
phonology
(Fig.
orthography
that a combination
of visual
wherever
was lesioned.
the model
and the units
2). One significant and semantic Semantic
result
was
errors
occurred
errors
occurred
parts of the reading system - for example, to a non-lexical spelling-sound route (affecting nonwords), to a lexical spelling-sound route (affecting all words) and to the seman-
even when the model was lesioned close to the units that encoded orthography, and visual errors occurred even when the model was lesioned close to the semantic units. Semantic
tic system(affectinglow imagerywordsin particular)36. A
errorscould resultfrom an early lesionif the lesionde-
multiple-lesion these lesions
creased how strongly or allowed incorrect
suggest
account must attribute the co-occurrence of to anatomical factors; however, ocher authors
this error
pattern
has functional
significance?‘.
The
case, a semantic
some semantic features were activated features to become active. In either
neighbour
may be chosen
by the network.
Hinton and Shallice and Plaut and Shallice models are relevant to this issue because single lesions to these models produce
This is possible partly because semantic featural information is activated directly from letter-level information
an association
and partly because semantic representations sets of features. Mixed visual-and-semantic
between
in deep dyslexia
several of the main error types observed
(although
they, too, must assume that an in-
dependent lesion impairs phoneme-to-grapheme Plaut and Shallice list several characteristics cial to their mantic
model.
For example:
representations
semantic
features.
(1) orthographic
are distributed
Visually similar words units and semantically Along
conversion). that are cru-
within
and se-
with
this,
their domain.
we consider
it crucial
Trends
these factors
more clearly.
that is both
visually
When
a word
and semantically
are based on errors highlight
has a neighbour(s) similar,
the network
will need to use a small number of letter differences to select distinguishing semantic features. In this case, whether lesions
activate overlapping orthographic similar words activate overlapping
I”
affect activation
of semantic
uation,
or both,
the result
visually
and semantically
Cognitive
Sciences
oa EK
is ‘back’
-
features, is likely
related
Vol.
1.
in which
initial
acti-
(and passed through a further set of weights) to proThe weights on the connections of this feedback
push initial semantic states towards attractors have an important influence
units
representations
problematic.
this pattern
when
Semantic
semantic errors (thermos+lask), mixed visual and semantic errors
imagery
(Fig.
is re-cycled activations.
that
vation
show a range of co-occurring
and visual rhen semantic errors (sympathy+
(favour-taste), orchestra)‘5.
McClelland2*
via
features (and, in Plaut and Shallice, semantic features to phonology). They were interested in seeing whether damage
is often
and
performs
and Shallice’
oao BCD
of the Hinton and Shallice’ model of a semantic route in readcorresponded to letter triplets and ‘output’ units corresponded to seman(for example, living, has-legs, sweet...). Note that, unlike the model of
vation at the semantic level duce a final set of semantic loop ated
computer
models. Hinton
Position 3 Position 4
moo AEI
Input - Position-specific letter units-word
component’“.
that have been used to simulate how
ations between different will see that associations paring
processing
Position 2
orthographic to be production
individof a
word.
No.
6.
September
1997
the final states associon the way the model
Olson
and
Humphrey5
-
Plaut and Shallice
Connectionism
attribute
and
visual
errors
late lesions to the influence
of the ‘attractors’
Their
similar
claim
is that visually
items
neuropsychology
resulting
predicted
from
in their model. generate
initial
se-
and can be understood
effects of damage
to various
input
attractor
and lexical
rors always
co-occur
mantic representations that are not clearly distinguished. Attractors then push initial activations toward distinct sets
currently
of semantic
tween
the imageability
errors,
results from
features.
When
the attractor
by a late lesion,
initial
activation
wrong
direction,
toward
the semantics
similar
word. ways that lexical
are important
early lesions hand,
is affected
be pushed
in the
of a nearby
visually
selection
for creating
and visual
errors
a lack of lexical
both
from
selection
operates
semantic
in the
errors
late lesions.
from
On the one
from
late lesions.
of whether
(which
such
This
‘implicit’
raises the interesting lexical
influences
will
ability
On the
the
Plaut
and
remains
as some recent
analyses
understanding
have shown”“2).
ally better
also accounts
with
high than with
performance
low imagery
words,
low
imagery
sparser They
words
semantic
emerge
representation
will be more
to ‘work
affected
and why
than
into
states
words. Even following suffer because sparser to recover
these words
have
high
words.
imagery
low imagery
corresponding
words
to visually
the correct‘word
given
reading
raises questions
impoverished
models,
about
pattern,
we can question
fine the functional the model, fective ologists. reading, tients
error
lesion
whether
locus of a patient’s types, per se, are poor
site. This
is a salutary
to sevsimilar
According
indicators
lesson
to
of error
types
deficiti’.
pending on whether level of orthographic semantic
features.
is quantitatively
different
de-
the model is damaged closer to the representations or closer to the level of More
visual
errors
accompany
when
for
of the pattern
types can help diagnose
Associations
are sometimes
and by the strength
inferences they
in other
make
and detail
words,
are judged
by the
generally,
based
Models
can provide
useful
detailed
predictions
sioning
goes first? Grouping
hardest
even
earlier
le-
in visual
we have considered
a network
about attention
has been to disrupt
in an unlesioned
agnosia
so far the effect
of le-
the task that was found
state.
However,
in human
neuropsychology some of the most interesting examples occur where patients find an easier task harder than a more difficult
task. These
a lesion
has not simply
tient.
counter-intuitive
It has affected
degraded
patterns cognitive
indicate
function
a process (or module)
that
in a pa-
that is used in the
easy but not the difficult task. A model is most interesting it, too, demonstrates some form of differentiated function. An example and grouping
Even where the separation into components is fairly indistinct (as in the Plaur and Shallice model), however, the distribution
from
can be informative
which associations to expect, provoking empirical to new aspects of neuropsychological data.
of the ef-
for neuropsych-
It shows that the appearance of semantic errors in though seductive, does not mean that all such pahave the same underlying
information
In the examples
types can de-
deficit.
(as
or simply
and details
error
of the evidence.
The hardest
methodol-
error
on the strength
similar
the Plaut and Shallice
ogy. If it is possible to build a system where damage eral different components leads to a qualitatively
is more
properties
less
input.
neuropsychological
atten-
pattern
suggests)
that are associated;
tend to
an early lesion, low imagery words semantic representations are less able
Like the previous
error
a
The
prompts
functional
system,
by its status in theory
same means by which
by lesions and give attractors
on’. As a consequence,
be pushed
model
because
from
of associated
is generto be with
repre-
words).
predictions
locus of a deficit.
of the patterns
imageability interacts with error type (errors tending more concrete than the correct responses). Problems
of visual
a precarious status in neuropsychological inference. likely an association is to stand, however, can be
judged
for why
be-
of the semantic
errors
the reading
the functional
This
and the presence
model
be suffi-
an active area of investigation.
The model
Shallice
anatomical accident. In summary, associated
given How
challenging
is
association,
the deep dyslexic
to result
question
be particularly
predicts)
is sparser for low imageability
of whether
morphological
will
of words
the characteristics
considered
and distribution
processing
A second
to make detailed
the question
cient to capture the wider aspects of human linguistic performance (for example, extending the account to include and syntactic
these er-
(as the model
of debate43.
cascaded
Whether
tion to the details of neuropsychological cases including distributions of errors, and converging evidence should resolve properly
ar the visual level is necessary
to produce visual and semantic errors from early lesions. the other hand, lexical attractors are crucial to produce errors
sentation
of the functional
mechanisms.
in patients
a matter
model’s
The different model
network
may
in terms
parts of a system with
comes from processes.
mented
a connectionist
arranged
units
coded
the modelling
Humphreys model
successively
of visual
in
which
units
at lower
inhibited
layers in the model identical
junctions
support, tected more
rapidly
than
to influence
dissimilar
aspects
of
of edges, and by allowing
supported
other incompatible junctions. identical items that grouped
imple-
hierarchically
complex
visual form: simple edges, then combinations so forth (Fig. 3). Grouping was introduced for example,
search
and Miiller44 more
if
one another;
one another
and
Due to this mutual together were deitems
that
did
not
sions. Neuropsychologists, then, need to attend to the distribution, as well as the occurrence, of particular error types.
group. If an item was detected that did not correspond to the target, it was inhibited along with its associated lower-
Conclusions
level
should from
concerning
the functional
also be verified other
edge using
tasks (for stimuli
by means example,
other
than
locus
of a lesion
of converging
assessing printed
evidence
semantic
words),
knowl-
since
error
units,
items.
The
search when (‘serial’)
leading model
to iterative successfully
non-target
search
when
stimuli non-targets
search
are identical, differ,
types are, at best, rough indicators of the locus of damage. The associated patterns of errors made by the model (in
ations were required in the latter case4s. Lesioning involved adding fluctuating
particular
vation
Trends
the occurrence
in
Cognitive
of visual
Sciences
and semantic
-
Vol.
1,
NO.
errors)
6,
are
September
1997
functions
between
units’.
of the remaining
simulated
efftcient
human
and inefficient since
more
iter-
noise to the acti-
This disrupted
search that
relied
on efficient
grouping
After the lesion, coded as different
over time as features more
affected
different
identical
were processed).
As a result,
in the easier condition disorder
when
recognition
rather
than
with
the
patients
visual
agnosia
breaks
show
down
‘Retina’
search was
(identical
Interestingly,
neuropsychological
non-targets.
non-targets were sometimes en(though this coding could change
non-targets).
pattern
between
identical stimuli
Feature
the same
because
there
is
impaired grouping of visual elements”“~“‘. The grouping process that is crucial to efficient search is limited by the accuracy
of the initial
tive (‘inefficient’) (being
more
coding
of local forms
search (with affected
neuropsychological
differing
by the later disorder
whilst
non-targets)
coding
l5
serial iterais not
of items).
can be understood
The
in terms
of
impairment to a process that is differentially responsive to stimuli that can be grouped versus those that cannot. Provided that a lesion
selectively
be more affected
affects
this process,
than difficult models
and rehabilitation
models
are adaptive.
ferent
strategies
They
can change
a study
effects
on the model
varied
around
by Plaut4R. He examined
and
variations
that
Connections trained
a prototype
of semantic
were
correspond lesioned
on words
(for
far from
dog
breeds).
Fig. 3 The
was re-
represent horizontal units is transmitted
on nonprotoand on proto-
words.
After
formance
reduced
performance
re-training
with
on prototypes
cross-talk
non-prototypical
items,
because
their
recovered.
However,
with
from
training
the representations the (central)
so training
not help non-prototypical This
simulation
can provide regimes
items suggests
a framework
that could
for
per-
map), when
represen-
optimize
ent),
that connectionist exploring
maximize
materials
does
modelling
different therapy;
training
how
(for
connectionist
chology.
The models
instance)
models
and how typically
can show selective
easier of two tasks if they have internal
units. Outputs to T-junctions
maps,
this
of visual
being
is occupied). when there
gated
that
search to continue on the remaining identical), they are detected quickly among is slow
themselves
and
several
during
grouping
network
(for
iterations
example,
may be required
are particularly
On
symptoms
top
affected
these models
of this,
models
may occur,
within
by brain
can suggest
and can direct
the empirical
learn,
and theorists.
we may
In the future
search which explores studies which examine
can be used to
ation
impairments
on the
models
specialization
and if
disorders.
Trends
processes
atten-
data. By examinbe able to predict
which rehabilitation strategies are most likely to prove successful. Thus, modelling is of considerable utility for both
the models can be made in neuropsy-
that arise in networks
Cognitive
to simulate
Sciences
we look forward
to re-
the role of structure in networks, to how the forms of internal organiz-
by neuropsychological
in
units operates
in ‘location
the location for something
are by units’
units allow present in
items. If distractors group (for example, and inhibited by their template. If dis-
dissociations.
ing how
units
in these to par-
at a location being considered for grouping. Targets are detected when the map competition increments a target template past a detection threshold. passes the threshold and is detected, it is inhibited (along with its match
tion to new patterns
will
Input
Activation that respond
by activity
Essentially is evidence
double
associated
searcha.
of L-junction and edge-terminator (termed ‘match maps’). Grouping
activation
location maps only
locations. units
The development of internal structure is also imif the models are to successfully simulate classical
why
modelling
remarks
simulate cognitive disorders used to evaluate assumptions
match
model
damage. portant
therapists Concluding
the
compete selection
the specialized
recovery.
We have shown
of edge respond
that
(SERR)
at particular retinal and edge-terminator
re-established
on prototypes
to improve.
be used in cognitive
stimulus
enabling they are
tractors
may therefore help us to understand why therapy works on some occasions and why it does not on others, and it may help
Rejection
Recursive
and vertical edges through to L-junction
of non-prototypical
representations
on prototypes,
within
the retinal input winner of match Once a template
tations comprise the average of (trained) non-prototypical items, enabling appropriate semantic representations to be items differ
via
(which code whether a particular grouping to occur via the match
on non-prototypical
improved
Search
ticular configurations combined in maps
dogs) or repre-
Re-training
words
Detected
dog
prototypical words improved reading of both non-prototypical words; in contrast, re-training typical
_------__ -___---__-_---$ I
representations
typical
the prototype.
the
The model for items
the model
had semantic example,
Competition to increment toward detection threshold
reading
of an average
to different and then
that either
close to the prototype sentations
(think
Templates
dif-
An exam-
originally proposed by Hinton and Shallice’. was trained to generate semantic representations that
map
their
connections between this property is of
may be developed.
ple of this comes from of re-learning
1
easier tasks can
because it offers a means by which
rehabilitation
Terminator and 1 Junction maps
Gates flow of information to templates
by altering the weighted units. For neuropsychologists, interest,
-
t
Location
Connectionist
considerable
-
tasks.
Connectionist behaviour processing
maps
Horizontal/vertical
resemble
studies, higher-order
-
Vol.
organization
and to work linguistic
1,
No.
6,
which
revealed extends
processing
September
and
1997
when
they
to detect
are differthe target.
Olson
and
Humphreys
-
Connectlonlsm
and
neuropsychology
17 Shallice,
Outstanding
questions
T . (1988)
Cambridge 18 McCloskey,
l
l
l
l
l
Can connectionist models that use distributed representations simulate higher-order linguistic abilities (and disorders, following brain damage), for which human performance seems constrained by a rule-based system? What are the effects of using learning algorithms that alter the structure of networks, as learning takes place? For instance, algorithms can be used which ‘prune’ the connections within networks, so that the structure of the network itself adapts to the learning required by the task. Do networks trained using such algorithms develop ‘modules’ that resemble those revealed by neuropsychological studies with humans? What are the implications of using multiple networks, which interact to perform different tasks? Can connectionist models be used to help us understand developmental disorders in children, where an underlying impairment may be affected by ongoing learning (often with the result that subsequent deficits differ from those found after a brain lesion in adulthood)? What are the functional effects of different types of lesions, and can different types of lesions in models be linked to different types of neuropathology?
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