Connectionist models of neuropsychological disorders

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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