O R I G I N A L P A P E R

Early Predictors of Communication Development in Young Children with Autism Spectrum Disorder: Joint Attention, Imitation, and Toy Play

Karen Toth Æ Jeffrey Munson Æ Andrew N. Meltzoff Æ Geraldine Dawson

Published online: 15 July 2006

� Springer Science+Business Media, Inc. 2006

Abstract This study investigated the unique contribu-

tions of joint attention, imitation, and toy play to language

ability and rate of development of communication skills in

young children with autism spectrum disorder (ASD).

Sixty preschool-aged children with ASD were assessed

using measures of joint attention, imitation, toy play, lan-

guage, and communication ability. Two skills, initiating

protodeclarative joint attention and immediate imitation,

were most strongly associated with language ability at age

3–4 years, whereas toy play and deferred imitation were

the best predictors of rate of communication development

from age 4 to 6.5 years. The implications of these results

for understanding the nature and course of language

development in autism and for the development of targeted

early interventions are discussed.

Keywords Autism Æ Language Æ Communication Æ Joint attention Æ Imitation Æ Play

Introduction

It is well established that there is tremendous variability in

outcome in autism. Long-term outcome studies have shown

that while a majority of individuals exhibit poor to very

poor outcomes, many individuals with autism go on to

achieve adequate levels of academic, social, and occupa-

tional functioning (Gillberg & Steffenburg, 1987; Lotter,

1978; Nordin & Gillberg, 1998; Sigman & Norman, 1999).

In a recent study that followed children with autism from

age 2 to 9, as many as 40% were found to have good

outcomes based on language and cognitive scores (Stone,

Turner, Pozdol, & Smoski, 2003). One of the strongest

predictors of positive long-term outcomes for children with

autism is the acquisition of spoken language (Bartak, Rutter,

& Cox, 1975; Gillberg, 1991; Gillberg & Steffenburg, 1987;

Lincoln, Courchesne, Kilman, Elmasian, & Allen, 1988;

Lotter, 1978; Rutter, 1970). Early language ability (i.e.,

meaningful speech by 5–6 years of age) has been associated

with both later academic achievement and social

competence in individuals with autism (Howlin, Mawhood,

& Rutter, 2000; Sigman & Ruskin, 1999; Venter, Lord, &

Schopler, 1992). Given the critical importance of early

language development for later prognosis, a better under-

standing of developmental factors that underlie, facilitate,

and predict language acquisition in autism would shed light

on the nature of this disorder and allow for the refinement

of targeted early interventions.

Early abilities that have been associated with the

development of language and communication skills both in

typically developing children and children with autism

include joint attention, imitation, and toy play. Joint

attention—shared attention between social partners

in relation to objects or events—typically emerges by

9–12 months of age (Adamson & Bakeman, 1985, 1991;

Adamson & Chance, 1998; Brooks & Meltzoff, 2002;

Bruner, 1983; Butterworth & Jarrett, 1991; Carpenter,

Nagell, & Tomasello, 1998), with some aspects emerging

as early as 6 months of age (Morales, Mundy, & Rojas,

1998). By 12 months of age, most typical infants display

all aspects of joint attention, including sharing attention

(e.g., through the use of alternating eye gaze), following

the attention of another (e.g., following eye gaze or a

K. Toth (&) Æ J. Munson Æ A. N. Meltzoff Æ G. Dawson Department of Psychology, UW Autism Center, CHDD,

University of Washington, 357920, Seattle, WA 98195, USA

e-mail: [email protected]

J Autism Dev Disord (2006) 36:993–1005

DOI 10.1007/s10803-006-0137-7

123

point), and directing the attention of another (Carpenter

et al., 1998). Through joint attention interactions, the infant

begins to link words and sentences with objects and events

(Baldwin, 1995). Importantly, it is within the context of

joint attention episodes that infants also begin to commu-

nicate intention by using sounds and gestures, such as

reaching to request objects, and pointing and vocalizing to

direct attention to objects. Joint attention skills correlate not

only with early language learning, but also with later lan-

guage ability in typically developing children (Carpenter

et al., 1998; Meltzoff & Brooks, 2004; Morales et al.,

1998, 2000; Mundy & Gomes, 1998).

Children with autism, however, show impairments in

joint attention skills as compared to children with delayed

and typical development (Bacon, Fein, Morris, Water-

house, & Allen, 1998; Charman, 1998; Charman et al.,

1998; Dawson, Meltzoff, Osterling, & Rinaldi, 1998;

Dawson et al., 2002a, 2004; Mundy, Sigman, Ungerer, &

Sherman, 1986; Sigman, Kasari, Kwon, & Yirmiya, 1992).

Impairments in protodeclarative joint attention behav-

iors—sharing attention for purely social purposes—appear

to be more severe than impairments in protoimperative

joint attention (e.g., requesting) behaviors in children with

autism (Mundy et al., 1986; Mundy, Sigman, & Kasari,

1990; Sigman, Mundy, Sherman, & Ungerer, 1986). Fur-

ther, in preschool age children with autism, joint attention

is predictive of both current language ability, and future

gains in expressive language skills (Bono, Daley, &

Sigman, 2003; Charman et al., 2003; Dawson et al., 2004;

Landry & Loveland, 1988; Mundy et al., 1990; Mundy,

Sigman, Ungerer, & Sherman, 1987; Rogers & Hepburn,

2003; Sigman & Ruskin, 1999; Toth, Dawson, Munson,

Estes, & Abbott, 2003). In a longitudinal study of social

competence and language skills in children with autism and

Down syndrome, Sigman and Ruskin (1999) found that

protodeclarative joint attention skills were associated with

early language ability for both groups, and predicted both

short-term (i.e., 1 year later) and long-term (i.e., 8–9 years

later) gains in expressive language ability for children with

autism. Initiating protodeclarative joint attention in early

childhood (3–6 years of age) was also correlated with later

peer interactions (10–12 years of age). Further, protoim-

perative joint attention skills correlated with early language

ability and short-term, but not long-term, gains in expres-

sive language for children with autism. In a recent inter-

vention study that targeted joint attention skills, young

children with autism showed greater gains in language

12 months post-treatment compared to controls (Kasari,

Freeman, & Paparella, 2004). It may be that joint attention

ability lays a foundation not only for the development of

language, but also other complex abilities such as pretend

play and theory of mind, as argued by developmental

theorists (Bruner, 1983; Carpenter et al., 1998; Meltzoff,

2005; Meltzoff & Brooks, 2001) as well as in the literature

more specifically focusing on children with autism

(Charman, 1997, 2003; Mundy & Crowson, 1997; Sigman,

1997).

Motor imitation ability has also been associated with the

development of language and social communication skills.

In typically developing infants, the ability to imitate is

present at birth. Neonates are able to imitate simple facial

movements, such as tongue protrusion and mouth opening

(Meltzoff & Moore, 1977, 1997). By 9 months of age,

infants are able to imitate actions on objects, both in

immediate and deferred contexts (Carver, 1995; Meltzoff,

1988a). Infant imitation appears to serve several general

functions, providing the child with shared social experi-

ences, a sense of mutual connectedness, and a means of

communication between social partners (Meltzoff, 2005;

Trevarthen, Kokkinaki, & Fiamenghi, 1999). Through

imitation, infants also learn about others’ actions and

intentions (Meltzoff, 1999; Uzgiris, 1981, 1999). Deferred

imitation serves to index infant recall memory and the

child’s ability to produce actions based on stored mental

representations of social events and action sequences (Klein

& Meltzoff, 1999; Meltzoff, 1988b). It has been theorized

that a failure to engage in early social imitative play may

interfere with the development of joint attention, social

reciprocity, and later theory of mind abilities (Dawson,

1991; Meltzoff, 1999, 2005; Meltzoff & Gopnik, 1993;

Rogers & Pennington, 1991). Imitation not only plays an

important role in early social development, but has also

been shown to predict language ability in typically devel-

oping children (Bates, Benigni, Bretherton, Camaioni, &

Volterra, 1979).

While typically developing children demonstrate the

ability to imitate others from birth, children with autism

demonstrate significant impairments in object imitation,

imitation of facial and body movements, and deferred

imitation of actions on objects (Charman, 1997; Dawson

et al., 1998; Rogers, Bennetto, McEvoy, & Pennington,

1996; Rogers, Hepburn, Stackhouse, & Wehner, 2003;

Sigman & Ungerer, 1984; Stone, Ousley, & Littleford,

1997). In children with autism, imitation skills have been

found to correlate with early language ability (Dawson &

Adams, 1984) and to predict later language ability (Charman

et al., 2000, 2003; Stone et al., 1997; Stone & Yoder,

2001). In a recent study, immediate imitation of actions on

objects at 20 months correlated with receptive language at

42 months in a small sample of children with autism

(Charman et al., 2003). In a similar study, motor imitation

at 24 months predicted expressive language ability at

48 months, even after controlling for initial language level,

in young children with autism (Stone & Yoder, 2001).

Play—both functional and symbolic—is a third skill

domain that has been associated with language and social

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123

communication ability. Play provides the child with

opportunities for social interaction and social communi-

cation, as well as a context for constructing representations

of intentional states and knowledge (Bloom, 1993; Lifter &

Bloom, 1989, 1998; Piaget, 1952). In typical development,

functional, or pre-symbolic, play emerges during the first

year, while symbolic play begins to emerge around 1 year

of age and becomes increasingly complex over the second

year of life. Both functional and symbolic play skills have

been shown to correlate with language ability in typical

children (Bates et al., 1979; McCune, 1995; Ungerer &

Sigman, 1984). Symbolic play is correlated with both

receptive and expressive language ability (Clift, Stagnitti,

& Demello, 1988; Doswell, Lewis, Boucher, & Sylva,

1994; Lewis, Boucher, Lupton, & Watson, 2000), while

functional play is correlated with expressive language level

in preschool age children (Lewis et al., 2000). Longitudinal

studies have also demonstrated a relation between early

play skills and later language ability (McCune, 1995;

Ungerer & Sigman, 1984). Ungerer and Sigman (1984)

demonstrated that functional play at 13 months correlated

with language ability at 22 months. Bates et al. (1979)

found that both combinatorial (i.e., manipulative) and

symbolic play correlated with gains in language from 9 to

13 months of age, with manipulative play predicting both

receptive and expressive language abilities through the

9–13 month period, while symbolic play was related more

to expressive language and was a stronger predictor toward

the end of the 9–13 month period. McCune (1995) dem-

onstrated that first word acquisition was associated with the

emergence of symbolic play, both self-pretend (e.g.,

drinking from an empty cup) and other-pretend play (e.g.,

giving a stuffed animal a drink), and that combining

actions in symbolic play (e.g., drinking from an empty cup,

then giving a doll a drink) was associated with the onset of

combining words.

In contrast to typically developing children, children

with autism show specific impairments in symbolic play as

early as 18 months of age relative to children with delayed

and typical development (Baron-Cohen et al., 1996;

Charman et al., 1998; Dawson et al., 1998; Mundy et al.,

1987; Ungerer & Sigman, 1981; Wing & Gould, 1979).

When children with autism do acquire symbolic play skills,

their level of symbolic play tends to remain below that of

their language level (Amato, Barrow, & Domingo, 1999;

Ungerer, 1989; Wing, 1978) and is often less diverse and

elaborate compared to that of developmentally delayed and

typical children (Ungerer & Sigman, 1981). Associations

between play and language have also been demonstrated in

young children with autism. Mundy et al. (1987) found

that, at 3–6 years of age, receptive language ability cor-

related with functional play involving a doll, and both

expressive and receptive language skills correlated with

symbolic play. Sigman and Ruskin (1999) demonstrated

that, in 3–6-year-old children with autism, both functional

and symbolic play in early childhood correlated with early

language ability, and functional play correlated with long-

term (i.e., 8–9 years later) gains in expressive language. A

recent intervention study that targeted symbolic play skills

found that young children with autism showed greater

gains in language 12 months post-treatment compared to

controls (Kasari et al., 2004).

Although correlational and longitudinal research have

demonstrated that joint attention, imitation, and play are

associated with the development of language and com-

munication skills in children with autism, the present

study represents a unique contribution in two ways: First,

the contributions of each of these three early abili-

ties—joint attention, imitation, and toy play—were

simultaneously examined as predictors of current lan-

guage ability in a large sample of preschool age children

with autism. Second, growth curve modeling was used to

examine the relationship between these early skills and

rate of development of communication skills across the

preschool and early school age years in children with

autism.

Method

Participants

Sixty children with autism spectrum disorder (ASD),

comprised of 42 children with Autistic Disorder and 18

children with Pervasive Developmental Disorder, Not

Otherwise Specified (PDD-NOS), participated in the study.

Participants were recruited from local parent advocacy

groups, public schools, clinics, hospitals, and the

Washington State Division of Developmental Disabilities.

Exclusionary criteria included the presence of a neurolog-

ical disorder of known etiology, significant sensory or

motor impairment, major physical abnormalities, and his-

tory of serious head injury and/or neurological disease.

Table 1 presents demographic and descriptive information,

including gender, socioeconomic status, chronological age,

composite mental age and IQ, and verbal age equivalents

for the children who participated in the study. At the

beginning of the study, children ranged in age from 34 to

52 months and were followed until 65 to 78 months of age.

Ethnicity for the sample was as follows: 43 European-

American, 3 African-American, 11 Multi-racial, and 3

Asian/Pacific Islander. Twelve children (20%) displayed an

expressive language age equivalence of 36 months or

higher on the Mullen Scales of Early Learning. Based on

the ADI-R, 20 children were reported to have lost some

level of spontaneous, meaningful communicative speech.

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Eighty-two percent of mothers had some college or a col-

lege degree.

Diagnosis of autism was based on the Autism Diag-

nostic Interview—Revised (ADI-R; LeCouteur, Lord, &

Rutter, 2003; Lord, Rutter, & LeCouteur, 1994) and the

Autism Diagnostic Observation Schedule (ADOS; Lord

et al., 2000; Lord, Rutter, DiLavore, & Risi, 1999; Lord,

Rutter, Goode, & Heemsbergen, 1989). Both instruments

assess the symptoms of Autistic Disorder listed in the

Diagnostic and Statistical Manual of Mental Disorders, 4th

ed. (DSM-IV; American Psychiatric Association, 1994). In

addition, clinicians made a clinical judgment of diagnosis

based on presence/absence of autism spectrum symptoms

as defined in the DSM-IV. Diagnosis of autism was defined

as meeting criteria for autism on the ADOS and autism

spectrum on the ADI-R and meeting DSM-IV criteria for

Autistic Disorder based on clinical judgment. In addition, if

a child received a diagnosis of autism on the ADOS and

based on DSM-IV clinical diagnosis, and came within 2

points of meeting autism spectrum criteria on the ADI-R,

the child was also considered to have autism. Diagnosis of

PDD-NOS was defined as meeting criteria for autism

spectrum on the ADOS and on the ADI-R, or missing

criteria on the ADI-R by 2 or fewer points, and meeting

DSM-IV criteria for PDD-NOS based on clinical judgment.

Procedure

The following measures were gathered over the course of

three or more sessions when children were 3–4 years old.

Each child was individually tested while seated at a table.

The child’s parent remained in the room, seated behind the

child or at the table with the child on the parent’s lap.

Children were given food snacks and praise as reward for

sitting at the table when necessary and provided breaks as

needed. The ADOS, ADI-R, and Mullen Scales of Early

Learning: AGS Edition (Mullen, 1997) were administered

during the child’s first laboratory visit, the Early Social

Communication Scales (ESCS) was administered during

the second visit, and experimental assessments of imitation

and functional and symbolic toy play were administered

during subsequent visits. The Vineland Adaptive Behavior

Scales: Survey Form (Sparrow, Balla, & Cicchetti, 1984)

was administered to the parent(s) in person when the child

was 3–4 years of age, and every 6 months thereafter by

phone up to 6 years, 6 months of age.

Predictor Variables

The Early Social Communication Scales (ESCS; Mundy,

Delgado, Hogan, & Doehring, 2003; Seibert & Hogan,

1982) was used to measure both protodeclarative and

protoimperative joint attention behaviors. In this proce-

dure, the child was seated at a table across from a familiar

examiner. A set of toys including a hat, comb, pair of

glasses, book, ball, car, wind-up and hand-operated toys,

and a plastic jar was in view, but out of reach of the child.

Three wall posters hung 90 degrees to the child’s right and

left, and 180 degrees behind the child. The examiner pre-

sented a sequence of wind-up and hand-operated toys,

activating each three times per trial (6 trials). Intermit-

tently, the examiner attracted the child’s attention, then

turned to point and gaze at each poster while calling the

child’s name three times (2 trials of 3 probes each), made

simple gestural and verbal requests of the child (‘‘Give it to

me’’), and presented the child with turn-taking opportuni-

ties, consisting of a tickle game (2 trials), taking turns with

an object (2 trials), and taking turns wearing a hat, comb,

and glasses (3 trials). The examiner also gave the child the

opportunity to look at pictures in a book and follow the

examiner’s point (1 trial). This 20-min structured assess-

ment was videotaped from behind a one-way mirror to

include a full view of the child and a profile view of the

examiner. Behavioral ratings were made from the video-

tapes by trained observers blind with respect to diagnosis

(these same observers also coded tapes of children with

delayed and typical development as part of a larger study)

and hypotheses. A more complete discussion of the ESCS

procedure is available elsewhere (Mundy et al., 2003).

Initiating and Responding to Protodeclarative Joint

Attention

Behavioral observations from the 20-min ESCS procedure

yielded scores in two categories of protodeclarative joint

attention. Initiating Protodeclarative Joint Attention could

Table 1 Sample characteristics a

N M:F SES+ CA (mos) Mullen Composite MA (mos) Mullen Composite IQ Mullen Verbal AE (mos) b

60 51:9 46.2 43.6 25.4 58.1 22.9

SD (11.2) (4.3) (8.6) (19.8) (10.3)

Range 22–66 34–52 11.8–46.8 30–101 8–50

a Numbers in the first row represent means; second row, standard deviations (SDs) in parentheses; third row, range

b The Mullen verbal age equivalent is the average of the Mullen receptive language and Mullen expressive language age equivalents

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occur at any time during the assessment and consisted of

the number of times the child used eye gaze, alternating

eye gaze, showing, and/or pointing behaviors to direct and/

or share attention with the examiner with respect to an

active toy. Responding to Protodeclarative Joint Attention

was the percentage of six trials on which the child accu-

rately oriented with eyes and/or head turn beyond the

examiner’s finger and in the direction of the examiner’s

point and gaze to the posters.

Initiating Protoimperative Joint Attention

A frequency score was obtained for Initiating Protoim-

perative Joint Attention based on observations from the

ESCS, which could occur at any time during the assess-

ment and consisted of the number of times the child used

eye gaze, reaching with coordinated eye gaze, pointing,

and/or giving to request a toy or to request help. Dyadic

behaviors (e.g., a reach without coordinated eye contact)

were not included in this category.

Reliability of the behavioral coding of the ESCS task

occurred in two phases. First, initial reliability was

assessed by independent paired ratings using 15 taped

ESCS sessions provided by Peter Mundy. Each of five

raters (undergraduate research assistants) independently

coded the 15 tapes and these ratings were then compared to

those obtained by Peter Mundy using intra-class correlation

coefficients. The coefficients for the three variables used in

the present study—initiating and responding to protode-

clarative joint attention and initiating protoimperative joint

attention—ranged from .83 to .94. After achieving this

initial reliability, the five raters then began coding data for

the study using a detailed coding manual developed by the

first author based on conversations with Mundy and staff

that occurred during the process of obtaining initial reli-

ability. A second phase of reliability was assessed using

independent paired ratings made from videotapes for a

randomly selected group of participants (10% of total

sample). Intra-class correlation coefficients for this second

phase of reliability were .80 for initiating protodeclarative

joint attention, .75 for responding to protodeclarative joint

attention, and .86 for initiating protoimperative joint

attention.

Imitation and Deferred Imitation

Immediate and deferred motor imitation abilities were

assessed based on a battery developed by Meltzoff (1988a,

b) and previously used with children with autism (Dawson

et al., 1998) and Down syndrome (Rast & Meltzoff, 1995).

The battery consisted of 10 motor imitation items admin-

istered in 2 blocks, 5 immediate and 5 deferred. Items

involved simple actions on novel objects, such as pressing

a light panel with one’s forehead, hitting two red blocks

together, and inverting and collapsing a camping cup.

Block order was counterbalanced and order of presentation

of specific items within each block was randomly deter-

mined. The child was seated at a table across from a

familiar examiner. After gaining the child’s attention, the

examiner demonstrated each target action 3 times in about

20 s. In the immediate condition, after demonstrating all

5 actions, the examiner then handed the object(s) to the

child one at a time and said, ‘‘It’s your turn.’’ No other

verbal or physical prompts were used to elicit a response.

In the deferred condition, after demonstrating all 5 actions,

a 10-min delay was introduced during which the child was

escorted out of the test room. After the delay, the child

returned to the test room and the examiner handed the

object(s) to the child one at a time and said, ‘‘Here’s a toy

for you to play with.’’ In both conditions, the child’s

behavior was coded during a test period of 20 seconds,

which began from the time the child first touched the

object(s). Behavioral ratings were made live by a trained

clinician and from an immediate review of the videotapes

when a judgment could not be made live (this occurred

infrequently). The same clinician administered this mea-

sure to all children in the study. The dependent measure

was the total number of acts imitated, ranging from 0 to 5

for each condition. Intra- and inter-observer agreement

were both high. Intra-observer agreement was assessed by

having the initial coder rescore a randomly selected 10% of

the children from videotape. The coder waited more than

4 months after the first coding and was uninformed as to

the initial scoring. For the inter-observer assessment, a

second independent coder reviewed the videotapes of the

same randomly selected children, while remaining unin-

formed as to the initial scoring. There were few disagree-

ments: Intra- and inter-observer agreement, as assessed by

Pearson rs, were respectively .99 and .99 for immediate

imitation and 1.00 and .96 for deferred imitation.

Toy Play

In this structured assessment of functional and symbolic

toy play skills, the child was seated at a table across from

a familiar examiner. Six dolls and sets of stimuli, func-

tional and representational, were presented to the child

one at a time, with functional and symbolic conditions (3

dolls and sets of stimuli per condition) counterbalanced

across participants. Representational stimuli included a

block to represent a sandwich, a plastic lid and bag to

represent a blanket and pillow, a tongue depressor to

represent a comb, a small plastic object to represent a

cup, a shoebox to represent a bathtub, and a blue wooden

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cylinder to represent a toothbrush. Functional objects for

each of these (e.g., a plastic sandwich, a comb, etc.) were

also included. For each condition, the child was presented

with a doll and object(s) and told, ‘‘You can play with

these.’’ Every 20 seconds, if the child was playing with

only some of the toys or not at all, the examiner repeated

the statement, ‘‘You can play with all of these’’ and

gestured to all of the toys. No further verbal or physical

prompts were provided. After 1 min, the toys were

removed from the table and the next doll and object(s)

were presented. The dolls were first presented unprompted

for each condition. For any target actions not performed

by the child, prompted trials were then given. Prompted

trials consisted of a verbal and gestural prompt, such as

‘‘Wally is hungry, give him a sandwich’’ while the

examiner patted her own stomach, but the examiner did

not model the target action on the doll. The child’s re-

sponses were scored in the following way: target action

was performed on the doll, on self, or on another person

(both prompted and unprompted trials were credited a

score of ‘1’ if the target action was performed); another

symbolic action was performed to self or other (these

actions were not included in the score); target action was

not performed (score of ‘0’). Functional and symbolic

play were highly correlated in this sample (r = .68) and

were therefore summed together to create one total play

score ranging from 0 to 6 (score of 0–3 possible for

functional play acts and 0–3 for symbolic play acts). The

same clinician administered this measure to all children in

the study. Behavioral ratings were made live by a trained

clinician (and in a few instances of ambiguity from

immediate review of the videotapes). Intra-observer

agreement was assessed by having the initial coder re-

score a randomly selected 10% of the children from

videotape (more than 4 months after the first coding,

while remaining uninformed as to the first judgments).

For the inter-observer assessment, a second independent

coder reviewed the same videotapes while uninformed as

to the initial scoring. Intra- and inter-observer agreement

for the total play score were, respectively, r = .97and .96.

Language Measures

Mullen Scales of Early Learning: AGS Edition

Receptive and expressive language age equivalents and

standard scores were derived from subscales of the Mullen

Scales of Early Learning (Mullen, 1997), which is a stan-

dardized measure of cognitive function for infants and

preschool age children. The Mullen was administered to

each child at age 3–4 years to obtain a measure of overall

cognitive ability as well as separate scores for both

receptive and expressive language abilities.

Vineland Adaptive Behavior Scales: Survey Form

The Vineland Adaptive Behavior Scales (Sparrow et al.,

1984) is a standardized parent interview that includes

assessment of communication skills (i.e., receptive,

expressive, and written communication). The Vineland was

administered by phone every 6 months from age 3–4 to

6.5 years. Although the Vineland norms were based on in-

person administration of the instrument, the decision was

made to administer the Vineland by phone for this sample

in order to lessen the burden on parents. Interviewers were

blind to the Vineland responses obtained previously, and

each time the Vineland was administered, a new basal and

ceiling were obtained. In addition, the same parent was

interviewed at each time point. Interviewers followed the

procedure as outlined in the Vineland manual, beginning

with a broad interview format followed by more targeted

questions to gather the information necessary to score each

item. The overall communication subscale age equivalent

score every 6 months up to 6.5 years of age was used in

growth curve analyses, with an average of 6 data points per

child. Age equivalent scores were chosen over raw scores

as they provide a more meaningful metric with which to

interpret change over time (i.e., increase in months rather

than Vineland points). Communication ability as assessed

by the Vineland was highly correlated with language

ability as assessed by standardized language tests, both at

the outset of the study and at final follow-up at age 6 years.

This suggests that, for this sample, Vineland communica-

tion scores were a reasonably good measure of receptive

and expressive language ability. At age 3–4 years, the

Mullen verbal age equivalent and the Vineland communi-

cation age equivalent were correlated .78 (Vineland and

Mullen receptive language age equivalents were correlated

.48, and Vineland and Mullen expressive language age

equivalents were correlated .81). At age 6 years, the

Vineland communication standard score and the verbal

standard score as measured by the Differential Ability

Scales (DAS) were correlated .72.

Results

Means, standard deviations (SD), and ranges for the pre-

dictor variables are presented in Table 2. Correlations

among predictor variables were moderate, ranging from .20

to .67 (Table 3). The various language variables used in the

regression analyses were highly correlated with each other

(r = .89–.97 among Mullen variables, and .71–.79 between

Mullen and Vineland variables). Correlations between

predictor variables and initial language ability are shown in

Table 4. To determine the unique contributions of each of

the predictor variables to concurrent language, multiple

998 J Autism Dev Disord (2006) 36:993–1005

123

regression analyses were conducted. Although predictors

were moderately correlated with one another, multicollin-

earity diagnostics indicated adequate tolerance levels.

Contributions of Joint Attention, Imitation, and Toy

Play to Language Ability at Age 3–4 years

Multiple regression analyses were conducted with all of the

predictor variables entered in one step, in which case

the test of the partial regressions weight controls for all the

other predictors in the model. Results are presented in

Table 5 and indicate that across a range of language

variables—receptive and expressive language, parent

report and direct observation—initiating protodeclarative

joint attention and immediate imitation were most strongly

associated with concurrent language ability in 3–4-year-old

children with autism.

Predicting Rate of Communication Development

Next, to examine the degree to which these three early

abilities—joint attention, imitation, and toy play—

accounted for the variability in rate of communication

development over the preschool and early school age per-

iod, growth trajectories using repeated Vineland measure-

ments were modeled using Hierarchical Linear Modeling

(HLM; Raudenbush & Bryk, 2002) with two parameters,

an intercept (absolute communication level at 48 months)

and a linear slope. 1

Time was thus coded in months and

centered around 48. The six individual predictor variables

were standardized and entered as predictors of individual

differences in the growth trajectories (both intercepts and

slopes). As shown in Table 6, immediate imitation and toy

play abilities were significantly related to individual dif-

ferences in children’s communication ability at 48 months

as measured with the Vineland, partially replicating results

examining predictors of early language using the Mullen

language scores reported above. (Note that the correlations

with the Mullen Language Scores were computed at entry

into the study when children were slightly younger, 3–4

years of age). The coefficients at the intercept indicate that

children whose immediate imitation ability was 1 SD

above the mean had communication scores over 3 months

higher than those at the sample mean, and children with toy

play ability 1 SD above the mean had communication

scores 3 months higher than those at the sample mean.

Examining individual differences in the slope (rate of

change), it was found that both toy play and deferred

imitation were significantly and positively related to rate of

acquisition of communication skills over the next 2 years

(see Fig. 1). The average rate of change for the sample was

.75, meaning that the sample as a whole showed 3 4

of a

month’s growth in communication ability for each chro-

nological month that passed. Two skills, toy play and

deferred imitation, were related to rate of change. Children

who had toy play scores 1 SD above the sample mean

(while controlling for all other variables) showed a rate of

change of .91 month/chronological month (or 11 months

for every year), whereas children with toy play scores 1 SD

below the sample mean had a rate of change of only

.59 month/chronological month (7 months for every year).

Similarly, children with deferred imitation scores 1 SD

above the sample mean showed a rate of change of

.96 month/chronological month (11.5 months per year),

whereas children with deferred imitation scores 1 SD

below the sample mean had a rate of change of only

.54 month/chronological month (6.5 months per year).

Inasmuch as both these variables—toy play and deferred

imitation—predicted unique variability in the rate of

change, their additive effect was even greater. Thus, the

combination of better toy play ability and more developed

deferred imitation skills was associated with faster rates of

change in communication skills across the preschool and

early school age period. These positive associations

Table 2 Descriptive statistics for predictor variables

Predictor M (SD) Range

Init Protodecl JA a

7.9 (8.7) 0–43

Resp Protodecl JA (%) b

.51 (.35) 0–1 (%)

Init Protoimp JA c

11.2 (8.8) 0–36

Imitation-Immediate d

2.9 (1.7) 0–5

Imitation-Deferred e

1.9 (1.6) 0–5

Toy Play f

4.0 (2.2) 0–6

a Initiating protodeclarative joint attention was a frequency score

consisting of the number of times the child used eye gaze, alternating

eye gaze, showing, and/or pointing behaviors to direct and/or share

attention with the examiner with respect to an active toy b Responding to protodeclarative joint attention was the percentage of

six trials on which the child accurately oriented with eyes and/or head

turn beyond the examiner’s finger and in the direction of the exam-

iner’s point and gaze to the posters c Initiating protoimperative joint attention was a frequency score

consisting of the number of times the child used eye gaze, reached

with coordinated eye gaze, gave objects, and/or pointed to request a

toy or to request help d Immediate imitation consisted of the total number of immediate

imitation items imitated e Deferred imitation consisted of the total number of deferred imitation

items imitated f Toy play consisted of the number of functional and symbolic play

acts performed, prompted or unprompted

1 An unconditional model with both linear and quadratic terms was

also run. The quadratic term in this model was not significantly dif-

ferent from zero (coeff. = .001134, std error = .0031, t(59) = .365,

P = .716) and showed much less variability than the linear term

(variance component: linear term = .34247, quadratic term =

.00025), thus the model with the single linear slope was deemed most

appropriate for these data.

J Autism Dev Disord (2006) 36:993–1005 999

123

remained for deferred imitation (t = 2.07, P < .05) and

nearly so for toy play (t = 1.81, P = .076) even after

controlling for child IQ.

Discussion

One purpose of the present study was to better understand

the contributions of each of three early abilities—joint

attention, imitation, and toy play—to early language ability

in young children with autism. Previous studies have pri-

marily demonstrated correlations between each of these

skill domains, and early and later language ability in

children with autism. In the present study, when these three

abilities were examined simultaneously, initiating

protodeclarative joint attention and immediate imitation

abilities were most strongly associated with language skills

in 3–4-year-old children with autism.

Table 6 HLM growth curve analyses predicting rate of

acquisition of communicative

skills in young children with

autism

Intercept is Vineland

communication score at

48 months; *P < .05,

**P < .01

Intercept (48 mos.) Slope (Rate of change)

Coeff t Coeff t

Constant 22.61 27.95** .75 14.34**

Joint attention—protodeclarative

Initiate 1.10 1.20 –.06 –1.27

Respond 1.30 1.10 .03 .38

Joint attention—protoimperative

Initiate –1.28 –1.29 –.01 –.11

Imitation objects

Immediate 3.20 3.47** –.01 –.80

Deferred 2.08 1.61 .21* 2.61*

Toy Play 3.02 2.54* .16* 2.34*

Table 3 Correlations among predictor variables: joint attention, imitation, and toy play

Init Protodecl JA Resp Protodecl JA Init Protoimp JA Symbolic Play Imitation immediate Imitation deferred

Functional Play .31* .51*** .23 .67*** .43** .41**

Init Protodecl JA .43** .39** .48*** .28* .45***

Resp Protodecl JA .38** .58*** .44*** .66***

Init Protoimp JA .24 .20 .20

Symbolic Play .37** .50***

Imitation-Immediate .53***

*P < .05, **P < .01, ***P < .001

Table 4 Relations between joint attention, imitation, and toy play, and language ability

Init Protodecl JA Resp Protodecl JA Init Protoimp JA Toy Play Immediate imitation Deferred imitation

Mullen Verbal AE .53** .60** .23 .54** .66** .67**

Mullen Rec Lang AE .49** .58** .20 .50** .64** .66**

Mullen Expr Lang AE .53** .59** .25 a

.56** .64** .63**

Vineland Comm AE .53** .62** .30* .51** .56** .65**

*P < .05, **P < .001 a P = .05

Table 5 Relations between joint attention, imitation, and toy play, and current language ability in 3–4-year-old children with autism

Mullen Verbal AE Mullen Rec Lang AE Mullen Expr Lang AE Vineland Comm AE

Init Protodecl JA .25* .23* .25* .25*

Resp Protodecl JA .16 .16 .15 .23

Init Protoimp JA –.06 –.08 –.04 .02

Toy play .08 .03 .12 –.02

Imitation immediate .39*** .38** .37** .26*

Imitation deferred .22 .26* .17 .26

Total R 2

.65 .62 .62 .58

Numbers are standardized betas; *P < .05, **P < .01, ***P < .001

1000 J Autism Dev Disord (2006) 36:993–1005

123

A second aim of this study was to better understand the

relationship between these early skills and rate of acqui-

sition of communication skills during the preschool and

early school age years in children with autism. Using

growth curve modeling, it was found that toy play and

deferred imitation were associated with higher rates of

acquisition of communication skills between 4 and

6.5 years of age. That is, children with autism who had

better toy play and deferred imitation abilities at age 4

acquired communication skills at a faster rate than those

with less developed toy play and deferred imitation skills.

For example, children who performed 1 SD above the

sample mean in both toy play and deferred imitation skills

had communication acquisition rates that were comparable

to typical children (13.4 months of communication growth

per 1 year of chronological age). (However, because the

children with autism started out at a lower level, their

language skills were still below age level at outcome.) In

comparison, children who performed 1 SD below the mean

in both toy play and deferred imitation skills acquired

communication skills at a rate of only 4.5 months per

1 year of chronological age.

These findings have important implications for under-

standing the nature and course of language development in

autism, and for designing targeted early interventions.

While initiating protodeclarative joint attention and

immediate imitation contributed to language ability at the

outset, toy play and deferred imitation were predictive of

rate of development of communication skills over the next

few years. These findings suggest that while all three

abilities might be important for laying a foundation for

language development in autism, toy play and deferred

imitation skills might contribute to the continued expansion

of language and communication skills over the preschool

and early school age period. This is not to suggest that joint

attention is not related to later language ability in autism.

Children with stronger joint attention skills also began with

better language at 3–4 years of age. That is, our findings

showed that children with better-developed initial joint

attention skills also had better-developed initial language

ability, and these children continued to show higher lan-

guage and communication skills across the preschool and

early school age years. Overall, however, when joint

attention was examined together with imitation and toy

play, only deferred imitation and toy play remained sig-

nificantly associated with rate (i.e., slope) of change in

communication skills over time.

We can speculate that joint attention and immediate

imitation are important ‘‘starter set’’ skills that set the

stage for social and communicative exchanges in which

language can develop, as described in the introduction.

Once this stage is set and the child begins to learn to use

language in a communicative manner, representational

skills become important in the continued acquisition of

words and phrases during the preschool and early school

age period. Toy play and deferred imitation abilities often

involve shared attention, but they also index higher level

cognitive skills that are important for the continued

development and expansion of language and social com-

munication abilities: an active interest, curiosity in, and

exploration of the environment; representational thought,

memory; and cognitive planning. While joint attention

episodes occur in a social context, both toy play (particu-

larly as it was measured here with dolls) and deferred

imitation require that the child actively attend to the

immediate environment, observe the events and actions

taking place, then reproduce these events and socially-

mediated actions at a later time. The ability to demonstrate

these skills requires an active interest in people and/or

things (capturing the child’s attention), representational

thinking (forming and storing a mental representation),

intact recall memory (calling up that representation at a

later time), and both cognitive and motor planning skills in

order to reproduce the action or event (Klein & Meltzoff,

1999; Meltzoff, 1988b, 1999). Additionally, the child’s

ability to reproduce actions at a later time reflects not only

symbolic thinking and intact recall memory, but also a

‘‘shared attitude toward objects,’’ as the child demonstrates

the same actions on objects that he has witnessed of others

(Meltzoff, 2005; Meltzoff & Gopnik, 1993). Thus, through

toy play and imitation, the child not only comes to an

understanding of the world around him—what people do

and think and how objects work—but also has the oppor-

tunity to demonstrate that understanding.

The results of the present study also have implications

for early intervention. All three skill domains—joint

attention, imitation, and toy play—are related to the

development of language and communication abilities in

young children with autism and are therefore important

Child's Age in Months

45 50 55 60 65 70 75 80

V in

e la

n d

C o

m m

u n

ic a

tio n

A g

e E

q u

iv a

le n

ce

10

20

30

40

50

60

70

Mea n tra

jecto ry

Toy Pla

y, D efe

rred Imi

tati on

+1 SD

Toy Play , Deferre

d Imitatio n -1 SD

Nor mat

ive gro

wth

Fig. 1 Comparison of rates of acquisition of communication skills in children with autism who have toy play and imitation skills either

1 SD above, or 1 SD below, the sample mean

J Autism Dev Disord (2006) 36:993–1005 1001

123

targets for early intervention. A number of studies have

shown promising results in facilitating the development of

joint attention in children with autism (Klinger & Dawson,

1992; Siller & Sigman, 2002; Whalen & Schreibman,

2003). Kasari et al. (2004) recently conducted a treatment

study that examined two interventions, one that targeted

joint attention skills and one that targeted play skills. The

play intervention focused not only on symbolic acts, but

also overall level of play. Children with autism were ran-

domly assigned to one of three groups—the joint attention

treatment group, the play treatment group, or the control

group—upon admission to the program. The control group

participated in a general early intervention program.

Results showed that children in the joint attention inter-

vention group showed significantly more pointing and

showing, more responses to joint attention, and more child-

initiated joint attention in mother–child interactions than at

pre-treatment. Similarly, children in the play group showed

significantly greater frequencies and types of play acts and

higher play levels on both a structured play assessment and

during mother–child interactions than at pre-treatment.

Further, over a 14-month period, the two experimental

groups showed an average of 15–17 months gain in

expressive language ability compared to only 7.5 months

for the control group. Although this study did not examine

pre-treatment differences among groups on a range of

variables, the results demonstrate that skills such as joint

attention and play may be modified and may contribute to

gains in other skill areas, such as expressive language

ability, in children with autism.

Another treatment study examined the behavioral pro-

files of responders and non-responders to Pivotal Response

Training (PRT) (Sherer & Schreibman, 2004 in press).

Children with responder profiles tended to have better-

developed toy play skills at pre-treatment, demonstrated

greater gains in language, play, and social skills during

treatment sessions than non-responders, and also general-

ized these skills to no-treatment environments and

untrained stimuli. Although the study design used in the

Sherer and Schreibman study precludes conclusions as to

whether improvement occurred in response to treatment or

in response to treatment plus other factors, it does tell us

that certain skills, such as toy play skills, might influence

the acquisition of language and other abilities that are

targeted in the treatment of children with autism.

It should be noted that due to the wide heterogeneity in

language skills in autism, meaningful speech, that is,

speech that is frequent or consistent, referential, and

communicative, is difficult to assess with any one measure.

Standardized cognitive tests sample behavior over the

course of 1 h, while parent report measures such as the

Vineland provide a summary of behavior over a broader

time frame and range of settings. Each of these measures

captures some, but not all, aspects of meaningful commu-

nication. In the current study, the Vineland was shown to

be highly correlated with direct assessment of language in

this sample, and was therefore deemed a suitable measure

of rate of language acquisition over time in young children

with autism. The Vineland also allowed for a repeated

measure appropriate for growth curve analysis that was not

confounded by test practice effects. The broader issue of

what measure best captures meaningful or useful speech

remains an important one, but one that lies outside the

scope of this study.

In summary, the results of the present study shed light

on the relationship between early skill domains and the

development of language and communication in young

children with autism, and suggest specific targets for early

intervention. Early abilities involved in social exchange

and communication, namely, joint attention and immediate

imitation, appear to be important for setting the stage for

early language learning in autism, while representational

skills, demonstrated through toy play and deferred imita-

tion, contribute to the continued expansion of language and

communication skills over the preschool and early school

age years. Each of these skill areas represents an important

target for early intervention programs that promote com-

municative competence and improved outcomes for young

children with autism.

Acknowledgments This research was funded by a program project grant from the National Institute of Child Health and Human

Development and the National Institute on Deafness and Communi-

cation Disability (U19HD35465), which is part of the NICHD/NID-

CD Collaborative Program of Excellence in Autism and by a center

grant from the National Institute of Mental Health (U54MH066399),

which is part of the NIH Studies to Advance Autism Research and

Treatment (STAART) Centers Program. We gratefully acknowledge

the contributions of the parents and their children who participated in

this study and several other people who made significant contributions

to this research: Craig Harris and several undergraduate research

assistants.

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Working Memory and Specific Language Impairment: An Update on the Relation and Perspectives on Assessment and Treatment

James W. Montgomery Beula M. Magimairaj Mianisha C. Finney Ohio University, Athens

Purpose: Children with specific language im- pairment (SLI) demonstrate significant language impairments despite normal-range hearing and nonverbal IQ. Many of these children also show marked deficits in working memory (WM) abilities. However, the theoretical and clinical character- ization of the association between WM and language limitations in SLI is still sparse. Our understanding of this association would benefit greatly from an updated and thorough review of the literature. Method: We review the newest developments in these areas from both a theoretical and clinical perspective. Our intent is to provide researchers and practicing clinicians (a) a conceptual frame- work within which the association between WM and language limitations of children with SLI can be understood and (b) potentially helpful

suggestions for assessing and treating the memory-language difficulties of children with SLI. Conclusions: In the past 10 years, important new theoretical insights into the range and nature of WM deficits and relation between these limitations and the language difficulties in SLI have occurred. New, robust diagnostic assess- ment tools and computerized treatment methods designed to enhance children’s WM functioning have also been developed. The assessment, diagnosis, and treatment of the language diffi- culties in SLI should consider the potential influence of WM.

Key Words: children, specific language impairment, working memory, language

M any children with specific language impairment (SLI) exhibit significant working memory (WM) deficits relative to same-age peers. In 2002,

Montgomery published a review article on what was known about the WM deficits of children with SLI and the relation of these deficits to these children’s language problems. Since then, new and important insights into WM and language in children with SLI and typically developing (TD) children have occurred. We review these new developments. We cast the WM deficits and their relation to SLI in broad theoretical terms, which allows us to contextualize the WM issues defining the current SLI literature. During this same period, new WM assessment tools and computerized training meth- ods designed to remediate the WM deficiencies of children have been developed. Many of these tools are available to the practicing speech-language pathologist (SLP). These new developments and their clinical relevance to SLI will be reviewed.

Children with SLI demonstrate normal-range hearing and nonverbal intelligence and an absence of developmental

disability (e.g., autism or fragile X syndrome) yet marked expressive and/or receptive language difficulties for their age. Many children with SLI also exhibit limitations in WM. WM refers to the mental processes allowing limited infor- mation to be held in a temporary accessible state during cognitive processing (Cowan, Nugent, Elliott, Ponomarev, & Saults, 2005); that is, WM involves concurrent informa- tion processing and storage. Because WM is considered a primitive of higher level cognition (e.g., Unsworth & Engle, 2007), including fluid intelligence, language learning/ performance, and academic learning, it is important to un- derstand its nature. The WM system includes various mech- anisms and properties. Over the past decade, the range of WM problems exhibited by children with SLI has broadened, and the evidence implicating an association between the WM and language difficulties in children with SLI has grown. This said, it should be noted that children with SLI repre- sent a heterogeneous population not only with respect to the linguistic deficits they exhibit (Leonard, 1998) but also as to whether they demonstrate WM limitations. Although WM

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American Journal of Speech-Language Pathology • Vol. 19 • 78–94 • February 2010 • A American Speech-Language-Hearing Association78

limitations characterize many children with SLI, not all chil- dren with SLI evidence such deficits (Archibald & Joanisse, 2009). The information in the present article reflects what is known about children with SLI who do demonstrate WM problems.

WM in TD Children A Theoretical Backdrop

To better understand the SLI literature, it is important to have some familiarity with the key issues defining the re- cent developmental memory literature. The majority of WM research has been conducted within Baddeley’s original tripartite framework (Baddeley & Hitch, 1974). This model describes WM as a multidimensional system comprising three separable yet interactive mechanisms (Bayliss, Jarrold, Baddeley, Gunn, & Leigh, 2005; Gathercole, 1999; Gavens & Barrouillet, 2004; Towse, Hitch, & Hutton, 1998). One is a domain-general central executive responsible for coordi- nating and controlling the different activities within WM. The executive has finite attentional resources (mental energy/ capacity) that are controlled in a flexible manner. Attentional control is key, and its regulatory functions include such things as allocation (the ability to devote mental energy to different levels of a task), updating (changing the contents of WM through attention switching), sustained attention (the ability to attend selectively to a stimulus in the midst of interference), and inhibition (the ability to block irrelevant stimuli from WM or focus of attention; Baddeley, 1996; Barkley, 1996; Lehto, Juujarvi, Kooistra, & Pulkkinen, 2003). The executive is roughly similar to the view of WM espoused by Cowan (Cowan, 1997; Cowan et al., 2005) as the acti- vation of a subset of representations (e.g., words) stored in long-term memory that momentarily occupy the focus of attention, and by Engle (Engle & Kane, 2004; Unsworth & Engle, 2007) as attentional capacity and control.

The second and third mechanisms correspond to two domain-specific storage devices, one devoted to the tempo- rary retention of verbal material, the phonological loop, and the other to visuospatial input, the visuospatial sketchpad. In this article, we focus on the loop, hereafter referred to as phonological short-term memory (pSTM). Recently, Baddeley (2000, 2003) proposed a fourth mechanism, the episodic buffer. The buffer is assumed to function as a temporary storage device and a processing system capable of integrating inputs from pSTM and the visuospatial sketchpad into a coherent episode/representation. It is thought to be important to the processing and retention of large chunks of language material such as connected speech. Because the buffer is a newly proposed mechanism, it does not enjoy the same theo- retical specificity and empirical validation as the other com- ponents (Baddeley, 2003). Finally, though not a mechanism, developmental memory researchers have begun to examine processing speed as an important property of WM and a potential factor in defining the capacity limits of WM (Bayliss et al., 2005; Towse & Hitch, 1995; Towse et al., 1998). In- terest in speed derives from earlier work revealing reliable intercorrelations among processing speed, short-term mem- ory (STM), chronological age, and higher level cognitive

abilities (Fry & Hale, 1996, 2000; Gathercole & Baddeley, 1993; Kail, 1991). We are interested in processing speed because of its emerging association with WM and central focus in the SLI literature.

The basic architecture of the tripartite model—that is, central executive, pSTM, and visuospatial STM—seems to be developed by about age 6 (Gathercole, Pickering, Ambridge, & Wearing, 2004). The capacity of each component increases from early childhood into adolescence (Gathercole, 1999; Gathercole et al., 2004). The executive is significantly linked to both storage devices beginning in early childhood. This finding indicates that the executive is associated with the coordination of the flow of information throughout WM (Baddeley, 1996; Gathercole et al., 2004), and different WM mechanisms develop in an integrated fashion from an early age. Finally, pSTM and visuospatial STM appear to develop relatively independently of each other, revealing their domain- specificity (Gathercole et al., 2004; Jarvis & Gathercole, 2003).

WM capacity is assessed using various concurrent processing-storage tasks. In listening span tasks, children listen to sets of sentences that increase in number (e.g., “Pumpkins are purple” and “Fish can swim”) and are asked to respond to the truth value of each sentence (processing component) and recall as many sentence-final words from each set (storage component; Gathercole et al., 2004; Pickering & Gathercole, 2001). In counting span tasks, children count arrays of dots while remembering the sums of dots on each array; at the end of a set, they recall the sums from each array. In operation span tasks, children perform multiple arithmetic problems, store the answer to each problem or a separate word presented after each problem, and then recall all the answers or words at the end of the set. The developmental pattern is that processing accuracy is high while storage significantly improves. WM capacity is typically indexed by item recall—that is, availability of storage in the face of processing/interference.

Much developmental work has focused on explaining increases in children’s WM capacity, examining the roles of the central executive and STM (Barrouillet & Camos, 2001; Barouillet, Gavens, Vergauwe, Gaillard, & Camos, 2009; Bayliss et al., 2005; Bayliss, Jarrold, Gunn, & Baddeley, 2003; Gathercole et al., 2004; Irwin-Chase & Burns, 2000; Karatekin, 2004). Research has shown that gains in capacity are associated with increases in both of these mechanisms. Some researchers have investigated the impact of processing speed/efficiency (Bayliss et al., 2005; Towse & Hitch, 1995; Towse et al., 1998). The idea behind the association between speed and WM capacity centers on the possibility that the slower the processing activity of a WM task is completed, the greater the opportunity for the stored items to decay or be forgotten. Only recently have researchers begun to investi- gate the collective contributions of STM and processing speed on WM performance (Bayliss et al., 2003, 2005; Magimairaj, Montgomery, Marinellie, & McCarthy, 2009). Bayliss et al. (2005) examined the individual and combined contributions of storage and processing speed on 6–10-year- old children’s WM capacity. Hierarchical linear regression and structural equation modeling showed that age-related increases in STM and processing speed contributed to

Montgomery et al.: Working Memory and Language in SLI 79

developmental changes in WM capacity, with STM ac- counting for greater variance than speed. Magimairaj et al. (2009) replicated these findings in 6–12-year-old children.

Some have argued that increases in WM capacity may also be driven by changes in attentional control. As children grow older they become better at rapidly switching their attention between the processing part of the task and remem- bering the items in STM (Barrouillet et al., 2009; Conlin, Gathercole, & Adams, 2005; Portrat, Camos, & Barrouillet, 2009). It is not difficult to see that attentional control (Engle, 2002; Unsworth & Engle, 2007) is closely related to the idea of scope or focus of attention (Cowan, 1997; Cowan et al., 2005) in that only a small bit of information can oc- cupy the focus of attention at any given moment.

Relation of WM to Spoken Language Development and Functioning

Lexical learning. Much developmental work investigat- ing the relation between WM and language has centered on word learning (Avons, Wragg, Cupples, & Lovegrove, 1998; Gathercole & Baddeley, 1990b; Gathercole, Willis, Emslie, & Baddeley, 1992). Most of this work has focused on pSTM, which has been argued to function as an important language learning device (Baddeley, Gathercole, & Papagno, 1998; Gathercole, 2006; Gathercole & Baddeley, 1990b). Word learning involves mapping sound to meaning. Using a variety of methods, robust associations between pSTM and new word learning have been reported for preschool-age children through about age 8 (Bowey, 2001; Gathercole & Baddeley, 1989, 1990b; Gathercole, Service, Hitch, & Martin, 1997; Jarrold, Thorn, & Stephens, 2009). The ability to hold novel speech material in pSTM presumably permits children to establish stable, long-term phonological representations of new words in long-term memory (e.g., Jarrold et al., 2009). As the lexicon grows, word entries become more phonolog- ically refined and better organized, with one organizational scheme involving words beginning with the same sound being stored together (Luce & Pisoni, 1998). Phonological STM and the ability to temporarily store new sound pat- terns may be an important factor in young children’s lexical learning and organization. Although the relation of pSTM and word learning weakens after age 8 (Gathercole, 1995; Gathercole, Tiffany, Briscoe, Thorn, & the ALSPAC Team, 2005), there continues to be a significant link through ado- lescence into adulthood (Atkins & Baddeley, 1998; Gupta, 2003).

Morphological and syntactic learning and functioning. Some researchers (Plunkett & Marchman, 1993; Tomasello, 2000) argue that young children do not possess morpho- logical rules (e.g., past tense), grammatical categories (e.g., subjects, verbs, and objects), and syntactic structure (e.g., subject-verb-object [SVO] and passive). Rather, children initially learn whole phrases and only later discover under- lying rules, categories, and structures by using the distribu- tional properties/regularities of the input (Nelson, 1987; Plunkett & Marchman, 1993; Tomasello, 2000). Phonolog- ical STM may serve as a mediating or moderating mecha- nism for this analytic process. Some support for this idea comes from Adams and Gathercole (1995), who reported

that pSTM predicts quantity and quality of spontaneous speech in 3-year-old children. They showed that high- pSTM capacity children, compared with low-capacity chil- dren, produced longer utterances containing a greater range of syntactic structures and lexical diversity. Blake, Austin, Cannon, Lisus, and Vaughan (1994) showed that STM is a better predictor of mean length of utterance in preschoolers than chronological or mental age. Because morphological and syntactic learning entails building relational knowledge, it is likely that several executive functions are involved; however, little empirical work has directly addressed the issue.

The influence of WM capacity in language comprehen- sion is only beginning to receive attention. At the sentence level, the more controlled studies have focused on the relation of WM and complex sentence comprehension. WM has been linked to the comprehension of object relative clause forms (e.g., “The hippo that the lion kissed on the nose was running into the jungle”) in young children (Roberts, Marinis, Felser, & Clahsen, 2007). Children with greater WM capacity show more accurate comprehension than low-capacity children. Comprehension minimally involves storing a prior element (noun phrase [NP] 1) in WM while processing new, incoming input. However, WM capacity is likely just one important mechanism. Being able to reactivate a stored element and then integrate it into a developing local structure in a timely manner are other WM-related skills underlying complex sentence comprehension (Lewis, Vasishth, & Van Dyke, 2006; McElree, Foraker, & Dyer, 2003; Van Dyke, 2007). Support for this wider view comes from a recent study by Montgomery, Magimairaj, and O’Malley (2008). These authors showed that 6–12-year-old children’s spoken com- prehension of verbal be passives (“The little girl was kissed by the woman”) is associated with WM capacity and pro- cessing speed. At a more global level, children’s comprehen- sion of narrative is predicted by WM capacity and processing speed (Montgomery, Polunenko, & Marinellie, 2009). Be- cause narratives entail large amounts of input and keeping track of many representations, developing a coherent mental model requires the storage, retrieval, and rapid integration of multiple representations across large stretches of input.

WM and Speed of Processing in SLI Relative to age peers, many children with SLI show

significant limitations in nearly all WM mechanisms as well as speed of processing (see Table 1). Appreciation of these limitations and the relation of these limitations to the lan- guage deficits of these children have important practical implications. Such knowledge may translate into building more informed clinical profiles of these children’s cognitive- linguistic strengths and weaknesses. Such knowledge, in turn, may help inform clinical assessment, diagnosis, and treatment.

STM Storage Many children with SLI show marked limitations in STM

capacity. Gathercole and Baddeley (1990b) proposed the phonological storage deficit hypothesis of SLI, claiming that

80 American Journal of Speech-Language Pathology • Vol. 19 • 78–94 • February 2010

the language impairment in SLI is secondary to a deficit in phonological storage. Phonological STM is assessed using various tasks such as digit span, word span, and nonword repetition. In digit and word span, children are presented increasingly longer lists of items and recall each list in serial order. In nonword repetition, children imitate nonwords varying in length. Regardless of task, children with SLI gen- erally exhibit reduced pSTM relative to age peers (Archibald & Gathercole, 2006; Ellis Weismer et al., 2000; Gathercole & Baddeley, 1990b; R. Gillam, Cowan, & Day, 1995; Montgomery, 2004; Montgomery & Evans, 2009).

Whether children with SLI evidence a developmental increase in STM capacity has been little studied. Gray (2004) reported an increase in capacity between 3 and 6 years. How- ever, capacity may level off by about 11 years, as suggested by findings of a longitudinal study by Conti-Ramsden and Durkin (2007). Their findings are inconsistent with the de- velopmental literature showing that pSTM capacity does not asymptote until about 14–15 years in TD children (Gathercole, 1999; Gathercole et al., 2004). Finally, there is evidence that the STM deficit of children with SLI may be confined to the verbal modality, as children with SLI and age peers tend to perform similarly on visuospatial STM tasks (Alloway & Archibald, 2008; Archibald & Gathercole, 2006, 2007).

Central Executive It has only been recently that SLI researchers have begun

to study the central executive, primarily in the context of WM tasks. Aspects of the executive that have been assessed include attentional capacity and several attentional functions—

that is, allocation, inhibitory control, updating, and sustained attention.

Attentional capacity. Attentional capacity refers to the limited mental activation/energy available to a person to perform a given task (Just & Carpenter, 1992). Most SLI studies have tested attentional capacity using verbal tasks (Ellis Weismer, Evans, & Hesketh, 1999; Mainela-Arnold & Evans, 2005; Montgomery, 2000a), but some investigators have also begun to include nonlinguistic tasks (Alloway & Archibald, 2008; Archibald & Gathercole, 2006, 2007; Windsor, Kohnert, Loxtercamp, & Kan, 2008). Irrespective of the nature of the task, many children with SLI show re- duced performance relative to age peers.

Ellis Weismer et al. (1999) compared the attentional capacity of children with SLI and age peers. Using the Competing Language Processing Task (CLPT; Gaulin & Campbell, 1994), these investigators reported that both groups yielded similar comprehension, but the SLI group yielded significantly poorer word recall. Similar results have been reported by others (Archibald & Gathercole, 2006, 2007; Mainela-Arnold & Evans, 2005; Marton & Schwartz, 2003; Montgomery, 2000a, 2000b; Montgomery & Evans, 2009). Because all these studies show that children with SLI can manage both comprehension and recall when the demands for recall are light (i.e., few items need to be recalled), the interpretation has been that children with SLI have reduced attentional capacity compared to age peers. Archibald and Gathercole (2006, 2007) and Windsor et al. (2008) have extended these findings and interpretation to the nonlinguistic domain. Im-Bolter, Johnson, and Pascual-Leone (2006) cor- roborated the capacity limitation hypothesis using a variety

TABLE 1. Working memory (WM) and processing speed of children with specific language impairment (SLI) relative to age-matched peers.

WM/speed Relative to age peers

Short-term memory capacity Verbal storage Poor

(Archibald & Gathercole, 2006, 2007; Ellis Weismer et al., 2000; Gathercole & Baddeley, 1990b; Montgomery, 1995, 2004)

Visuospatial storage Similar (Alloway & Archibald, 2008; Archibald & Gathercole, 2006, 2007)

WM capacity Concurrent processing stor- age

Poor (Archibald & Gathercole, 2006, 2007; Ellis Weismer et al., 1999; Marton &

Schwartz, 2003; Montgomery, 2000a, 2000b; Montgomery & Evans, 2009)

Central executive Attentional capacity Poor

(Archibald & Gathercole, 2006, 2007; Ellis Weismer et al., 1999; Im-Bolter et al., 2006; Mainela-Arnold & Evans, 2005; Montgomery & Evans, 2009)

Attentional allocation/shift- ing

Similar (Montgomery, 2000a, 2000b; Im-Bolter et al., 2006)

Updating Poor (Im-Bolter et al., 2006)

Inhibition Poor (Im-Bolter et al., 2006; Marton et al., 2007; Seiger-Gardner & Schwartz, 2008)

Sustained attention Poor (Finneran et al., 2009; Montgomery, 2008; Montgomery, Polunenko,

& Marinellie, 2009; Spaulding et al., 2008)

Processing speed Poor (Leonard et al., 2007; Miller et al., 2001; Windsor & Hwang, 1999; Windsor

et al., 2008)

Montgomery et al.: Working Memory and Language in SLI 81

of independent measures of attentional capacity. Collectively, such findings and interpretation are consistent with the gen- eral WM literature characterizing attentional capacity as a domain-general cognitive attribute (Baddeley, 1996; Cowan, 1997; Cowan et al., 2005; Unsworth & Engle, 2007). Finally, it is not clear whether children with SLI exhibit develop- mental increase in attentional capacity, as there are no studies directly addressing the issue.

Attentional control. Im-Bolter et al. (2006) evaluated three attentional control functions in children with SLI. Using a variety of independent tasks, they assessed shifting, updating, and inhibitory control. Shifting, which is roughly analogous to Baddeley’s (1996) resource allocation, is the ability to devote attention between two different levels of a task (e.g., the processing and storage parts of a WM task) or to two different tasks (Im-Bolter et al., 2006). Updating refers to maintaining focus at a given level of a task and adding new content to the focus of attention (e.g., adding to a list of to-be- remembered items in storage in a WM task). Inhibition refers to preventing irrelevant stimuli from entering WM or focus of attention. Three key findings emerged: Relative to age- mates, children with SLI exhibited comparable shifting, poorer updating of WM, and poorer inhibitory control. Such findings advance the SLI literature in two important ways. First, they offer independent evidence that children with SLI have re- duced attentional capacity, not poor allocation, and poor in- hibitory control (also see Bishop & Norbury, 2005; R. Gillam et al., 1995; Lum & Bavin, 2007; Mainela-Arnold & Evans, 2005; Marton, Kelmenson, & Pinkhasova, 2007; Seiger- Gardner & Schwartz, 2008). Second, children with SLI have trouble updating the contents of WM.

One other executive function has begun to be studied in SLI—sustained attention, which is the ability to maintain attention over time to identify a target in the midst of a stream of nontargets (Awh, Vogel, & Oh, 2006). Emerging data indicate that many children with SLI have trouble sustaining attention (Finneran, Francis, & Leonard, 2009; Montgomery, 2008; Montgomery, Evans, & Gillam, 2009; Spaulding, Plante, & Vance, 2008). Brain mechanisms responsible for attention, including sustained attention, appear to be the same as those supporting WM (Jonides, Lacey, & Nee, 2005; Silver & Feldman, 2005). This proposal is important because Ellis Weismer, Plante, Jones, and Tomblin (2005) provide functional magnetic resonance imaging data showing that the coordinated pattern of activation of brain regions asso- ciated with attentional control, memory processes, and lan- guage encoding and retrieval are different in adolescents with SLI than in age peers. Adolescents with SLI show an over- reliance on a less functional network of brain regions subserving these mental functions and overall lower levels of neural activation.

Speed of Processing Processing speed in SLI has been studied from two per-

spectives: a rapid rate temporal processing point of view (Stark & Tallal, 1988; Tallal & Stark, 1981; Tallal et al., 1996; Tallal, Stark, & Mellits, 1985a, 1985b) and, more recently, a generalized cognitive slowing perspective (Kail, 1994; Miller, Kail, Leonard, & Tomblin, 2001; Windsor & Hwang, 1999;

Windsor, Milbrath, Carney, & Rakowski, 2001). Tallal and associates have claimed that children with SLI have special trouble processing rapidly presented information, linguistic or nonlinguistic, and that this difficulty directly hinders their language processing and language learning. A generalized slowing perspective takes a broader view. This account suggests that many children with SLI are slower at all mental processes, including perceptual, cognitive, and linguistic, by a proportional amount relative to age peers, irrespective of the nature and modality of the task (Kail, 1994; Leonard et al., 2007; Miller et al., 2001; Windsor & Hwang, 1999; Windsor et al., 2001). Processing speed within this frame- work emphasizes the amount of cognitive work that can be completed in a given unit of time (Kail & Salthouse, 1994; Salthouse, 1996, 2000). The assumption is that if information is not processed with sufficient speed it is vulnerable to decay and/or interference. Although many children with SLI are slower processors than age-mates through adolescence, they do appear to show developmental improvement in linguistic/ nonlinguistic processing speed between 6 and 11 years (Montgomery, 2005).

Recall that developmental memory researchers regard processing speed as an important property of the WM system and have begun to examine its potential influence in defining the capacity limits of WM. Its inclusion in SLI research has only been recent. Archibald and Gathercole (2007) examined whether the WM deficit in SLI is related to limitations in STM and processing speed. Children with SLI were com- pared to age peers and to younger children matched for recep- tive vocabulary. Children completed separate verbal and visuospatial tasks related to storage, processing speed, and WM capacity. The four WM tasks crossed verbal and visuo- spatial processing and storage (i.e., verbal processing + verbal storage, verbal processing + visuospatial storage, visuospatial processing + verbal storage, visuospatial processing + visuospatial storage). For the STM tasks, the SLI group performed like age peers in both domains but better than language controls. For processing speed, the SLI group was significantly slower in both domains than age peers but faster than younger children. On the WM tasks, the SLI group performed significantly worse than age controls on both WM tasks but only for those involving verbal storage. Relative to language controls, the SLI group performed significantly better on the WM tasks requiring visuospatial storage and comparably on the tasks involving verbal storage. This pat- tern of results was interpreted to mean that, relative to age peers, the limited WM capacity of children with SLI was due to a combination of a verbal-specific storage deficit and slower domain-general processing. Importantly, as pointed out by the authors, it is likely that deficits in executive- attention mechanisms also had a negative impact on the WM capacity of the children with SLI—for example, sustained attention (Montgomery, 2008; Spaulding et al., 2008), in- hibitory control (Im-Bolter et al., 2006; Marton et al., 2007), and updating (Im-Bolter et al., 2006).

Linguistic Influences on WM Capacity The WM capacity of children with SLI is influenced not

just by WM-related factors but also by linguistic factors.

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Mainela-Arnold and Evans (2005) showed that, relative to age peers, word recall on the CLPT by children with SLI was significantly affected by the frequency of the words, with low-frequency items being recalled with less accuracy than high-frequency items. These findings led to a different theo- retical description of the WM capacity deficit in SLI. The authors argued that WM capacity and linguistic knowledge are not separable mental constructs. Rather WM capacity reflects the activation of specific representations in long-term memory (Cowan, 1997; Cowan et al., 2005; MacDonald & Christiansen, 2002). In this view, limited WM capacity in SLI is a reflection of weak linguistic representation (Bishop, 2000; Dollaghan, 1998; Mainela-Arnold, Evans, & Coady, 2008), with the strength, access, and retrieval of represen- tation being dependent on input frequencies (MacDonald & Christiansen, 2002). Low-frequency words reflect a case of weak representation driving poor WM storage and re- trieval because such words are experienced less often and hence are subject to slower/less accurate processing and retrieval than high-frequency words (Juhasz, 2005).

WM and Language in SLI Deficits in WM and processing speed in children with SLI

could lead to widespread negative effects in language learn- ing and functioning, including partial processing of words, grammatical forms, and syntactic structures. Poor ability to process input could lead to protracted language learning during which children need more exposures to the words and structures of the language before they are integrated into the language system (Leonard et al., 2007). Limitations might affect not only acquisition of representation but also language process, that is, the efficiency with which children store, access, retrieve, and coordinate stored representations in the moment-to-moment input and output processing of language. While claims of cause-and-effect relations between the WM, processing speed, and language limitations in SLI await data from psychometric, developmental, and intervention studies, there is mounting evidence of an association.

WM and Lexical Learning Relative to age peers, children with SLI show slower vo-

cabulary growth (Paul, 1996; Rescorla, Roberts, & Dahlsgaard, 1997) and smaller lexicons (Watkins, Kelly, Harbers, & Hollis, 1995). Gathercole and Baddeley (1990a) proposed in a seminal article that the language difficulties in SLI may be secondary to a deficit in pSTM capacity. In this hypoth- esis, these children should have trouble learning new words because of a difficulty encoding and/or storing novel phono- logical material in pSTM, and consequently establishing long-term phonological representations of new words. Early anecdotal evidence suggested this might be the case (Oetting, Rice, & Swank, 1995; Rice, Cleave, & Oetting, 2000; Rice, Oetting, Marquis, Bode, & Pae, 1994). Oetting et al. (1995), in a quick incidental word-learning study, found that a group of 6–8-year-old children with SLI learned fewer unfamiliar words than age peers as these words appeared in brief video stories containing simple, familiar language structures. Rice et al. (1994, 2000) showed that children with SLI, compared

with age peers, learned fewer unfamiliar words. In each of the above studies, learning was indexed by comprehension performance.

Remarkably few studies have directly investigated the above-mentioned relation of pSTM and word learning. Gray (2004) asked whether pSTM would predict novel word learn- ing in a group of 3–6-year-old children with SLI and age peers. Children completed nonword repetition and digit span tasks and a fast mapping task in which they heard names of eight novel two-syllable words three times. Learning was assessed via comprehension and production. The SLI group performed worse than age controls on both pSTM tasks and the comprehension and production measures. No signifi- cant correlation emerged between pSTM and comprehension or production in the SLI group. Gray interpreted the lack of correlation to mean that a pSTM deficit does not constrain the word learning of children with SLI.

Two different possibilities exist that might explain the lack of correlation reported by Gray (2004). First, children with SLI represent a heterogeneous population. For many chil- dren with SLI, vocabulary represents a relative strength (cf. Leonard, 1998). Inspection of the scores of the SLI group in the Gray study revealed that the SLI group performed within the normal limits on the Peabody Picture Vocabulary Test, an index of receptive vocabulary knowledge. Also, not all children with SLI have memory problems (Archibald & Joanisse, 2009). An absence of correlation appears con- sistent with the possibility that the SLI group, although attaining lower word-learning and STM scores than age peers, had no marked lexical or pSTM deficits. Alternatively, Gathercole (2006) recently modified the original pSTM def- icit hypothesis. She argued that a pSTM deficit alone was insufficient to cause language problems. Instead, a combina- tion of memory deficits places children at risk for language difficulties. In this view, a WM deficit, for example, may be more influential than a pSTM weakness in defining an association between memory and vocabulary in SLI.

WM and Morphological Learning and Processing The relation of WM and grammatical morpheme learn-

ing and processing in SLI has received surprisingly little research attention. Ellis Weismer (1996) examined the impact of WM capacity on the morphological learning of a group of children with SLI and age-matched children. Children com- pleted the CLPT and a fast mapping task in which they were exposed to two novel morphemes (a vowel) appended to words embedded in a short carrier phrase presented at normal, fast, and slow rates. Ellis Weismer reasoned that morpheme learning, indexed by comprehension and production of the novel inflected words, should correlate with WM. Relative to age peers, the SLI group yielded significantly reduced word recall on the CLPT. On the morpheme learning task, both groups showed comparable comprehension. By contrast, the SLI group produced fewer inflected words in the fast rate condition than age peers. Morpheme production in the fast rate condition in the SLI group was also moderately corre- lated with CLPT score. The good comprehension by the SLI group should come as no surprise. The morphemes were vowels and were likely easily detectable in the input, thus

Montgomery et al.: Working Memory and Language in SLI 83

freeing up attentional resources allowing the children to glean the grammatical function of the segment. The produc- tion and correlation findings suggest that the production of newly learned grammatical morphemes stretches the WM and processing speed of children with SLI. The need to ac- cess a newly learned inflection and append it to a verb while simultaneously formulating and producing the rest of the sentence in a timely fashion apparently exceeds the overall processing capacity of children with SLI.

One might argue that the morpheme learning (comprehen- sion, production) that took place in Ellis Weismer’s explicit learning task is fundamentally different than the learning that occurs in natural language environments. Clearly, there are differences in the structure of the learning contexts, but there are important similarities between the two in terms of the mental operations underlying morpheme learning. According to the processing capacity account of Leonard and colleagues (Leonard, 1998; Leonard, Eyer, Bedore, & Grela, 1997), morpheme learning involves children (a) perceiving an in- flected word and comparing it with its bare stem counterpart, (b) hypothesizing the grammatical function of the marker, and (c) placing it in a morphological paradigm. Moreover, these operations must be completed in a timely way to ensure correct morphological analysis. Such a learning process relies on WM in that children must be able to store the novel in- flected word, retrieve from long-term memory its bare stem counterpart, and simultaneously perform a morphological analysis of the novel inflected word before the marker decays. Inflectional learning in the children with SLI in the Ellis Weismer (1996) study, as indexed by production, was likely hindered because of limitations in WM capacity and speed of processing (Leonard et al., 1997).

Many children with SLI also have trouble processing per- ceptually weak inflections during running speech (Montgomery & Leonard, 1998, 2006). These investigators, using a word- monitoring reaction time task, contrasted the online process- ing of perceptually nonsalient markers (past tense –ed, third person singular –s) with a perceptually stronger marker (present progressive –ing). In both studies, relative to age peers, the SLI group showed no sensitivity to the presence of the –ed and –s markers. However, the SLI group, like age peers, showed sensitivity to the -ing marker. These results suggest an interaction between the nature of the input and SLI processing capacity. Poor processing capacity would entail slower access and retrieval of perceptually weak mark- ers from long-term memory and slower integration of in- flected words into a developing sentence meaning. The implication of poor processing is that many children with SLI are at risk for constructing incomplete/inaccurate rep- resentations of the speaker’s input.

WM and Sentence Comprehension Children with SLI exhibit poorer sentence comprehension

than age peers, including understanding lengthy SVO sen- tences containing dependent clause material (“The little boy who is standing is hugging the girl who is sitting”) and sen- tences that violate SVO order such as passives (“The girl was kissed by the lady on the head”) and object relative sen- tences (“The dog that the cat bit was running away”). The

latter sentences are especially difficult because a word or phrase occupies a syntactic position that is different from the position that determines its semantic role, thus requiring complex syntactic processing (Friedman & Novogrodsky, 2004; van der Lely, 1996, 1998). In the sentences above, NP1 appears in a subject position but functions as a patient. To recover the SVO order of such sentences, children must move NP1 behind the verb (gap) using a “syntactic movement” operation. Researchers ascribing to a syntax-specific view to explain such SLI comprehension problems (Friedman & Novogrodsky, 2004; Marshall & van der Lely, 2006; van der Lely, 2005) argue that the comprehension deficits are due to a syntax problem. Those who argue from a more domain- general perspective (Bishop, 1997, 2006; Montgomery & Evans, 2009) propose that the comprehension problems are secondary to general cognitive processing limitations (e.g., WM and speed of processing).

Phonological STM and sentence comprehension. Several studies have examined the role of pSTM in SVO sentence comprehension by children with SLI (Montgomery, 1995, 2000a, 2000b, 2004; Montgomery & Evans, 2009). Few studies have examined its role in complex structures such as passives (Montgomery & Evans, 2009; Norbury, Bishop, & Briscoe, 2002). Evidence supporting the role of pSTM in SVO comprehension is mixed. Montgomery (1995) revealed a correlation between pSTM and the comprehension of SVOs containing embedded clause material (e.g., “The girl who is laughing is touching the boy” or “The little boy who is standing is hugging the girl who is sitting”). Montgomery and Evans (2009) likewise reported a significant correlation be- tween pSTM and SVO comprehension in children with SLI, but not in age peers or younger memory-matched children. Results suggest that comprehension of simple grammar in- volves significant mental resources by children with SLI but not TD children. However, other studies have reported no correlation in children with SLI (Montgomery, 2000a, 2000b, 2004). With respect to passives, the two studies investigating the association between pSTM and passive comprehension have yielded mixed results. Whereas Norbury et al. (2002) reported a significant correlation, Montgomery and Evans (2009) reported no correlation.

WM capacity and sentence comprehension. We exam- ined the role of WM capacity in children’s online sentence processing (Montgomery, 2000a) and offline comprehension (Montgomery, 2000b; Montgomery & Evans, 2009). In both studies, children completed a concurrent verbal processing- storage task. In the online study, children with SLI who were age-matched and younger syntax-matched children com- pleted a WM task and a word-monitoring task (Montgomery, 2000a) in which they pressed a button upon hearing a target word in the sentence. Results showed that (a) the SLI and younger groups performed similarly across tasks but worse than the CA group and (b) WM did not correlate with simple sentence processing (word recognition) in any group. The findings were interpreted to mean that the immediate pro- cessing of simple SVO forms does not entail significant WM, even for children with SLI. SVOs place little demand on WM presumably because (a) there is no need to hold NP1 in WM since it occupies a preverbal position and receives its agent role directly from the verb and (b) NP2 appears in a

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postverbal position and receives its patient assignment. We also examined the relation of WM and offline comprehension of short and long SVOs in the same three groups of children in another study (Montgomery, 2000b). Results showed that (a) the SLI and younger groups yielded similar scores on the WM task but worse scores than the CA group and (b) the SLI group comprehended fewer long sentences than either control group. Because the SLI and younger groups were not memory matched, we concluded that the SLI group’s WM deficit hindered their comprehension because the additional information processing demands inherent in such offline comprehension paradigms exceeded their WM abilities.

Sustained auditory attention and sentence comprehension. To our knowledge, only two studies have examined the relation of sustained attention and sentence comprehension (Montgomery, 2008; Montgomery et al., 2009). In both stud- ies, 6–11-year-old children with SLI and age peers com- pleted a continuous performance task. In the online sentence processing study (Montgomery, 2008), children responded to a target word appearing at the beginning, middle, or end of the sentence. In the offline sentence comprehension study (Montgomery et al., 2009), children selected a picture corre- sponding to the sentence they heard. We predicted that a correlation should occur between sustained attention and sentence processing/comprehension on the assumption that accurate sentence processing/comprehension requires main- taining attention over the course of the sentence. Relative to age peers, the SLI group in each study showed (a) signif- icantly poorer sustained attention, (b) poorer sentence process- ing (slower word recognition reaction time to target words) and poorer sentence comprehension, and (c) a correlation between attention and comprehension. We interpreted such results to mean that the immediate processing and compre- hension of simple grammar involves significant mental effort by children with SLI but not age peers, suggesting that simple grammar is not yet processed automatically by chil- dren with SLI.

WM and Standardized Language Performance The issue of how WM and processing speed might relate to

SLI performance on standardized language tests has begun to be addressed (Leonard et al., 2007; Montgomery & Windsor, 2007). Interestingly, data from both studies mirror the devel- opmental WM literature showing the relative importance of STM over processing speed (Bayliss et al., 2005; Magimairaj et al., 2009). Leonard et al. (2007) conducted a large-scale study in which multiple measures of WM, processing speed, and language were administered to large samples of children with SLI and age-matched peers. Factor analytic techniques were used to determine how much variance in composite language score could be accounted for by WM and pro- cessing speed in the combined samples. Results showed that significantly more variance in language was accounted for by WM capacity than processing speed, suggesting that WM plays a predominant role in children’s standardized language functioning. By extension, WM capacity limitations play a stronger role than processing speed in explaining the poor language test scores of children with SLI. Montgomery and Windsor (2007) reported similar findings. They examined the

contribution of pSTM and processing speed on the receptive and expressive scores of a group of children with SLI and age peers. Regression analyses showed that for the SLI group pSTM accounted for more variance than processing speed in both the receptive and expressive scores. They argued that the language tests were especially taxing of pSTM. For the age peers, neither pSTM nor speed accounted for any unique variance in language, suggesting that the language measures fell within the limits of these children’s pSTM and processing speed.

WM Limitations and Language-Based Learning Disabilities

Robust evidence indicates that WM supports the acqui- sition of complex academic skills and knowledge across a variety of language-based literacy areas, including reading, writing, and mathematics (Bull & Scerif, 2001; Cain, Oakhill, & Bryant, 2004; Seigneuric, Ehrlich, Oakhill, & Yuill, 2000; Swanson & Berninger, 1996a). A separate literature shows that students with WM deficits exhibit various learning disabilities (i.e., reading, writing, and mathematics; DeJong, 1998; Swanson & Beebe-Frankenberger, 2004; Swanson & Berninger, 1996a, 1996b). Relatedly, large-scale studies show that individual differences in WM relate to variation in academic achievement among school-age children, with low-WM students attaining lower achievement (Gathercole, Brown, & Pickering, 2003; Gathercole et al., 2004). Because of the relation of WM and language difficulties in SLI and the presence of language-based academic deficits in SLI (Catts, Adlof, & Ellis Weismer, 2006; Silliman, Butler, & Wallach, 2002), the SLP should have some familiarity with these associations to better inform her or his clinical assessment and treatment of the memory-language problems in school- age children with SLI.

Clinical Implications As Johnston (1999) stated, even though the interpretation

of the evidence for a connection between the cognitive and language deficits in SLI may not be definitive, treatment of children with SLI is ultimately guided by our theoretical commitment and a cost-benefit analysis of assuming or not assuming a link. Assuming a link has the lower immediate clinical cost, as clinicians have the option of broadening the scope of treatment if language-based approaches yield min- imal outcome (see below for more on this point). Our belief in the existence of a connection is guided by our theoretical orientation and interpretation of the extant literature.

Assessment Suggestions Central to the assessment process is determining to what

extent a student’s language problems and academic struggles are related to a deficit in linguistic knowledge, deficient WM abilities, slower processing speed, or a combination of fac- tors. Regarding linguistic competence, it is critical to deter- mine the range and level of linguistic knowledge of the student using various standardized language tools as well as performing systematic task analyses. While performance on

Montgomery et al.: Working Memory and Language in SLI 85

standardized tests is generally taken as an index of language knowledge, performance may be affected by poor general processing abilities (Leonard et al., 2007; Montgomery & Windsor, 2007). Through careful and systematic task anal- ysis and observation, it may be possible to identify perfor- mance patterns within and across tests that implicate WM and speed of processing issues; we discuss this below.

The SLP should be able to estimate and infer students’ WM and processing speed based on performance on various standardized and nonstandardized tools and their ability to manage these abilities in the service of language-based prob- lem solving. With respect to standardized measures, WM problems can be identified in two ways: (a) screening using subtests from IQ tests and (b) performance on specific mem- ory tests. The various subtests from IQ tests are not available to the SLP to administer. Importantly, however, several mem- ory tests have become available for use by the SLP.

It has been suggested that the diagnosis of memory impair- ment should be based on inclusionary and exclusionary criteria, and should be made independent of other cognitive abilities (Gathercole & Alloway, 2006). An inclusionary criterion entails students attaining a score that falls greater than 1 SD below the mean on a standardized memory mea- sure, irrespective of IQ. Exclusionary criteria involve the absence of hearing and articulation deficits (Gathercole & Alloway, 2006). The reader is referred to Gathercole and

Alloway (2006) for an in-depth discussion of the diagnostic process and use of various assessment tools. Table 2 lists a variety of standardized tools and informal methods available to all licensed SLPs to assess school-age children’s WM and processing speed.

Estimating STM capacity. The digits forward subtest from the Wechsler Intelligence Scale for Children—Third Edition (Wechsler, 1991) and the Test of Memory and Learning (Reynolds & Bigler, 1994) as well as the word order sub- test from the Kaufman Assessment Battery for Children (Kaufman & Kaufman, 1983) are three screening measures that can provide an estimate of STM. Each test requires children to recall a series of digits or words in the order they have been presented. Although the SLP is not licensed to administer these measures, the results from such tests often can be made available to the SLP to incorporate into her or his clinical profile of a student.

Several standardized memory tests are available to prac- ticing SLPs for clinical use. One is the Automated Working Memory Assessment (AWMA) by Alloway (2007). The AWMA, appropriate for ages 4 to 22 years, has several STM tests, including digit recall, recalling words, recalling non- words (assessing verbal STM), block recall, and visual matrix memory (assessing visual STM). An important companion measure is the Working Memory Rating Scale (WMRS; Alloway, Gathercole, & Kirkland, 2008 ), a 22-item behavioral

TABLE 2. Standardized tools and informal assessment methods available to the speech-language pathologist to assess WM and processing speed in children with SLI.

Mechanism/property Assessment method

Short-term memory (STM) capacity Verbal STM Automated Working Memory Assessment (Alloway, 2007) Visuospatial STM Working Memory Rating Scale (Alloway et al., 2008)

The Children’s Test of Nonword Repetition (Gathercole & Baddeley, 1996)

Working Memory Test Battery for Children (Pickering & Gathercole, 2001)

Nonword Repetition Task—nonstandardized (Dollaghan & Campbell, 1998)

WM capacity Verbal WM capacity Automated Working Memory Assessment (Alloway, 2007) Visuospatial WM capacity Working Memory Rating Scale (Alloway et al., 2008)

Working Memory Test Battery for Children (Pickering & Gathercole, 2001)

Recalling Sentences subtest of the CELF–4 (Semel et al., 2003)

Test of Narrative Language (Gillam & Pearson, 2004) Understanding Spoken Paragraphs subtest of the CELF–4

(Semel et al., 2003)

Central executive properties and functions Attentional capacity Task analyses Attentional allocation

Processing speed Word level Test of Word Finding, Second Edition (German, 2000)

Rapid Automatic Naming subtest of the CELF–4 (Semel et al., 2003)

Rapid Automatized Naming and Rapid Alternating Stimulus Tests (Wolf & Denkla, 2005)

Sentence and discourse levels Task analyses

Note. CELF–4 = Clinical Evaluation of Language Fundamentals, Fourth Edition.

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rating scale designed for teachers to help identify children with WM problems. The WMRS has been conormed with the AWMA, thus providing a reliable tool to screen children’s memory abilities. A low score on the WMRS in combination with a low score on the AWMA or another standardized mem- ory measure would provide converging evidence that a student has memory problems.

A second test is the Working Memory Test Battery for Children (WMTB–C; Pickering & Gathercole, 2001). The WMTB–C (appropriate for ages 5 to 15 years) includes four subtests of verbal STM (digit recall, word list matching, word list recall, and nonword repetition) and two visuospatial sub- tests (block recall and mazes memory). A third test is the Children’s Test of Nonword Repetition (Gathercole & Baddeley, 1996), appropriate for 4–8-year-old children. Although not a normed test, the Nonword Repetition Task by Dollaghan and Campbell (1998) is also available.

Estimating WM capacity. Students’ WM capacity may be estimated by using various subtests from the AWMA (Alloway, 2007) and WMTB–C (Pickering & Gathercole, 2001). The AWMA includes a verbal WM subtest and a visuospatial WM subtest. The WMTB–C includes three sub- tests (listening span, backward digit recall, and counting span). The listening span task invites students to perform concurrent verbal processing and storage. Backward digit recall asks students to repeat increasingly longer lists of digits in the reverse order they heard them. The storage com- ponent entails remembering the digits, and the processing component involves reversing the order of the numbers. In counting span, children count the number of dots on a stim- ulus page and then recall the number of dots from each page of dots that was presented. The SLP may also wish to ad- minister a sentence repetition task such as the one from the Clinical Evaluation of Language Fundamentals, Fourth Edi- tion (CELF–4; Semel, Wiig, & Secord, 2003). Children are asked to repeat verbatim a range of sentences varying in length and complexity. The task has been shown to reliably identify children with SLI who have memory difficulties (Archibald & Joanisse, 2009; Conti-Ramsden, Botting, & Faragher, 2001; Stokes, Wong, Fletcher, & Leonard, 2006). Some authors argue that the task assesses WM capacity and linguistic knowledge (Conti-Ramsden et al., 2001), but others suggest that it taps the episodic buffer (Gathercole & Alloway, 2006). While the underlying mechanism support- ing sentence repetition needs resolving, the clinical use of sentence imitation in identifying children with memory problems appears strong.

The SLP may also wish to perform careful task analyses (e.g., Lahey & Bloom, 1994) of standardized language tests and error analyses of children’s performance to gain impor- tant clues about whether weak WM abilities may have contributed to their poor language performances. Take, for example, the Word Classes Receptive subtest of the CELF–4 (Semel et al., 2003) for children 9 years and older. Some children may have trouble with this task not because of a lack of familiarity with the lexical material but because of the WM demands of the task. For instance, they may have trouble remembering the four stimulus words that are pre- sented (e.g., fence, window, glass, and rug) while simulta- neously comparing the semantic association among the words

to decide which two are related in some fashion. These com- parison and decision-making processes must be completed in a timely manner before any of the words are forgotten. At the sentence level, SLPs may administer the Recalling Sen- tences subtest of the CELF–4 as an output measure and perform a pattern analysis to determine the nature of chil- dren’s errors (e.g., primarily ill grammatical repetitions or loss of information).

Assessing school-age children’s memory for narrative is also critical given the importance of narrative in children’s social and academic development (Hicks, 1991; Paul & Smith, 1993; Peterson, Jesso, & McCabe, 1999). Clinicians may wish to administer the Test of Narrative Language (R. Gillam & Pearson, 2004) and/or the Understanding Spoken Paragraphs subtest of the CELF–4. The Test of Narrative Language is appropriate for 5–11-year-old children, and the CELF–4 subtest is appropriate from 9 to 21 years of age. Poor memory may be inferred based on the children’s performance on the various probe questions asked, while story retelling can be evaluated in terms of whether their responses may reflect a loss of information.

Estimating speed of processing. There are few commer- cially available standardized tests designed to assess chil- dren’s speed of input and/or output processing. There are, however, tests designed to examine the rate and accuracy of lexical access/retrieval, that is, rapid automatic naming tests, including the Rapid Automatized Naming and Rapid Alternating Stimulus Tests (Wolf & Denkla, 2005); Test of Word Finding, Second Edition (German, 2000); and the Rapid Automatic Naming subtest of the CELF–4 (Semel et al., 2003). Each of these tests requires children to name pictures such as colors, objects, and numbers as quickly and accurately as possible.

Beyond the word level, however, there are no standardized instruments to evaluate the speed at which students are able to process language. Importantly, though, clinicians may be able to draw reasonable inferences about the speed of students’ input and output processing by engaging in careful and sys- tematic observation of students’ language performance under different “loading” conditions during various language ac- tivities. On the input side, clinicians may systematically vary their speaking rate as they present language material that varies in volume and complexity. Presenting variable amounts of simple and complex language material at different speaking rates can allow the clinician to observe to what degree the memory and comprehension of material are affected by input rate. It would be predicted that increases in language com- plexity and volume would lead to decreased comprehension (Leonard et al., 2007; Montgomery, 2005, 2006; Montgomery & Windsor, 2007). On the output side, systematically vary- ing the time children have to complete various language production tasks (e.g., single word retrieval, sentence pro- duction, narrative, description, and explanation) may pro- vide clinicians information about how children manage the multiple memory and language demands under different output requirements. From these observations, clinicians may gain a sense of the conditions under which children have trouble coordinating their language and memory functioning, information that may be valuable in planning intervention.

Montgomery et al.: Working Memory and Language in SLI 87

Intervention Suggestions

The intervention techniques SLPs use to remediate the language and cognitive deficits in school-age students with SLI should be grounded in the principles of evidence-based practice (EBP). The clinical decision-making process should be informed by a combination of scientific evidence, expe- rience of the clinician, and the client’s (and parents’) needs (S. Gillam & Gillam, 2006). The present article focuses on the relation of cognition and language in students with SLI. Ac- cordingly, the focus of intervention centers on remediating the weak cognitive processing of these children with the intent of promoting stronger language abilities.

Structuring intervention with students with SLI to include training of cognitive processes would seem to be important for four reasons. First, students with SLI, especially those with receptive impairments, show resistance to language intervention (Bishop, Adams, & Rosen, 2006; Law, Garrett, & Nye, 2004) and inconsistent response to treatment de- signed to ameliorate their syntactic processing deficit (Ebbels, 2007). It would seem that non-language-based treatments should begin to be considered.

Second, there exist no intervention studies focusing on improving the language abilities of students in the middle grades and beyond (Cirrin & Gillam, 2008). Third, there are no published EBP guidelines for providing language inter- vention to school-age children with SLI (S. Gillam & Gillam, 2006). In the absence of such guidelines, Gillam and Gillam offer a seven-step clinical decision-making process in which SLPs integrate research evidence with their own clinical expertise/experience and training, and the needs of the student (and parents). Given this state of affairs, we propose that this process should consider other reliable sources of emerging evidence, particularly from psychology, to support the use of alternative treatment approaches such as memory training with students with SLI.

Fourth, it has been suggested by some SLI researchers (Bishop et al., 2006) that failure to factor into language intervention the cognitive processing limitations of students with SLI will likely lead to poor outcomes. The suggestions for cognitive training offered below clearly must undergo rigorous and systematic investigation with children with SLI before EBP acceptance can be established. Finally, readers may wish to refer to Gathercole and Alloway (2006) for additional treatment suggestions.

Phonological STM training. Teaching verbal rehearsal strategies may prove helpful to children with SLI for certain language situations. One strategy involves more efficient use of the phonological loop. The phonological loop not only involves storage but also includes a rehearsal process (Baddeley, 1996) designed to refresh and maintain the con- tents of STM. Maintaining the contents of STM is important in a variety of everyday situations, including remembering instructions, new names, and phone numbers, as well as ver- bally directing attention from one element of a task to another element. Age-related improvements in rehearsal strategies begin in the elementary school years (Gathercole, 1998; Lehmann & Hasselhorn, 2007; Ornstein & Naus, 1985; Schneider & Sodian, 1997) and show qualitative shifts from labeling (using a single item name only once) or passive

rehearsal (single item rehearsals) to cumulative rehearsal (consisting of multi-item rehearsal). These strategies benefit from explicit training, with evidence indicating that train- ing can enhance STM capacity (Kail, 1990), metacognitive functioning (Siegler, 2000), and WM capacity (Lehmann & Hasselhorn, 2007). Critically, there is emerging evidence that rehearsal training can enhance the STM storage/recall of children with SLI (Gill, Klecan-Aker, Roberts, & Fredenburg, 2003), as well as other children with language problems (Loomes, Rasmussen, Pei, Manji, & Andrew, 2008).

WM capacity training. The adult and childhood literatures are rich with examples of robust correlations between WM performance and higher order cognitive functioning, includ- ing fluid intelligence, reading comprehension, and mathe- matics. Important new developments have also taken place in the experimental psychology literature regarding the impact of explicit training of WM capacity. There is strong emerging evidence that training WM capacity leads to increases not only in WM capacity but also in fluid intelligence in adults (Jaeggi et al., 2007; Jaeggii, Buschkuehl, Jonides, & Perrig, 2008; Westerberg & Klingberg, 2007). Even more important, there are emerging and robust developmental data showing similar training effects in children, both TD children and children with various learning difficulties. For instance, WM capacity training has been shown to lead to improved WM capacity as well as reading comprehension accuracy and reading speed in young elementary school–age children (Loosli, Buschkuehl, Perrig, & Jaeggi, 2008). Training in WM has also been shown to transfer to improvements in sustained attention in TD preschool-age children (Thorell, Lindqvist, Nutley, Bohlin, & Klingberg, 2009). Finally, simi- lar WM capacity training has been shown to lead to signifi- cant increases in WM capacity, nonverbal reasoning, and attention functioning in children diagnosed with attention deficit/hyperactivity disorder (Klingberg, Forssberg, & Westerberg, 2002; Klingberg et al., 2005). Collectively, the findings from the basic and applied psychology literatures suggest that training WM capacity may hold promise with children with SLI.

The purpose of training WM capacity is to help students with SLI enhance their WM capacity, thereby allowing them to better manage the dual demands of information processing and storage during the solving of various language-related activities. There are now several available computerized pro- grams that may be beneficial to children with SLI. We should note that we are not advocating for one program or another, as there are no comparative data showing the efficacy of any given program. Rather, our intent is to provide SLPs a starting point to identify and evaluate on an ongoing basis potentially appropriate programs for use with children with SLI. Table 3 presents a list of some available programs.

One such training program can be found as part of the AWMA battery of Alloway (2007). The AWMA includes an interactive training component (i.e., “Jungle Memory”) in which children play a variety of games designed to enhance WM capacity in the context of reading and math. The online Web site “Soak Your Brain” offers WM training that uses an n-back task. In an n-back task, an individual is presented variable length series of items (digits, words, pictures) in which an item is repeated at specific intervals relative to other

88 American Journal of Speech-Language Pathology • Vol. 19 • 78–94 • February 2010

stimuli. In a two-back letter task, for example, a listener would respond each time he or she hears the same letter (sound) appearing two letters ago. The task relates to WM because successful performance relies on the listener holding short sequences of letters in memory (storage) while count- ing back one, two, or three letters (processing) to identify a letter match. Cogmed Working Memory Training also offers WM training. The activities require users to remember a sequence of numbers, letters, or patterns in increasingly chal- lenging conditions. Common attributes of each of these programs are that the activities are adaptive to individual users’ ability level and progress, and users are provided clear feedback about their performance.

Findings that children with SLI seem to struggle with verbal storage more than visuospatial storage (Archibald & Gathercole, 2006, 2007) would suggest that the SLP begin WM training in the visuospatial domain. Visual stimuli might afford the children maximum opportunity to begin to learn how to manage their WM resources under more storage- friendly conditions. Once children demonstrate good response from training under these conditions, clinicians could switch to auditory stimuli. Stimulus type selection should be possible because some of these programs (e.g., n-back training from Soak Your Brain) offer this flexibility. The SLP may dis- cover that training in the visuospatial domain transfers to the auditory-verbal modality such that children will need less training to reach a similar criterion level. Importantly, find- ings reported by Thorell et al. (2009) indicate that such trans- fer occurs in preschool TD children. A final strategy could be to combine verbal and visual input during training to help children manage the demands of cross-modal information processing and storage that are common to academic learning (e.g., listening/reading language material that also includes corresponding graphics).

Compensating for slower processing speed. Many stu- dents with SLI tend to reveal significantly slower processing than age peers. The Fast ForWord Language intervention program (FFW-L; Scientific Learning Corporation, 1998) is a popular computerized program designed to improve the processing speed and language processing abilities of chil- dren with SLI (Merzenich et al., 1996; Tallal et al., 1996). The FFW-L program is designed to change the rate of processing and subsequently the language abilities of children with SLI by providing them practice with processing acoustically/ temporally modified syllable, word, and sentence material.

Children begin by listening and responding to acoustically exaggerated stimuli. As stimulus recognition and comprehen- sion improve, the acoustic properties of the stimuli are modified to approximate normal speech rate.

At least two large-scale randomized controlled trials have compared the efficacy of FFW-L and traditional language intervention approaches at improving the general language abilities of students with SLI (Cohen et al., 2005; R. Gillam et al., 2008). Results of both studies indicate that FFW-L and traditional interventions are equally effective (effect size ranging from small to large) in bringing about immediate gains in general language abilities of students with SLI. The results of Gillam et al. further showed that the gains were maintained 6 months after training. Such findings are impor- tant because they indicate that traditional, lower tech, lower priced interventions can yield comparable gains in the gen- eral language abilities of students with SLI as higher tech, more expensive interventions such as FFW-L.

Concluding Remarks In this article, we reviewed the new developments that

have occurred in the childhood memory and SLI literature regarding the association between WM, processing speed, and language. We also reviewed the new developments that have taken place in the childhood memory literature regard- ing the development of new robust diagnostic assessment tools to assess children’s WM abilities. Critically, several of these tools are available for use by licensed SLPs. By com- pleting standardized and/or nonstandardized targeted mem- ory and processing speed assessments, coupled with careful cognitive-linguistic analyses of the language and academic tasks performed by students, the SLP should be in a stronger position to build a profile of cognitive-linguistic strengths and weaknesses of children with SLI. Information about new computerized methods from the childhood memory literature that might be potentially useful in remediating the memory problems of children with SLI was also provided. Hopefully, the information provided in this article will provide SLPs with a new framework and tools to include in their clinical arsenal to aid in the diagnosis and treat- ment of the cognitive-linguistic limitations of children with SLI.

Finally, though important gains have been made in the past 10 years, much remains to be learned about the (a) WM

TABLE 3. Potential WM training and informal techniques to address the slower processing speed in children with SLI.

WM/speed Treatment approach Available tools

Phonological STM capacity Verbal rehearsal training WM capacity Computerized WM capacity training Automated Working Memory Assessment

(Alloway, 2007) Cogmed Working Memory Training

(www.neurodevelopmentcenter.com/index.php?id=128) Soak Your Brain (www.soakyourhead.com/)

Processing speed Computerized training Fast ForWord Language (Scientific Learning Corporation, 1998; Acoustic manipulation of input to children

Use exaggerated speech Provide additional processing time

Note: Fast ForWord Language proves no more effective than traditional language interventions in improving language skills.)

Montgomery et al.: Working Memory and Language in SLI 89

and processing speed of children with SLI, (b) the associa- tion of these abilities with the language learning and perfor- mance of children with SLI and TD children, and (c) best practices regarding the diagnosis and treatment of the memory-language limitations of children with SLI.

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Received April 11, 2009 Accepted September 27, 2009 DOI: 10.1044/1058-0360(2009/09-0028)

Contact author: James Montgomery, Ohio University—Hearing, Speech & Language Sciences, Grover Center W218, Athens, OH 45701-2959. E-mail: [email protected].

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Restorative Neurology and Neuroscience 28 (2010) 157–165 157 DOI 10.3233/RNN-2010-0522 IOS Press

Effects of congenital hearing loss and cochlear implantation on audiovisual speech perception in infants and children

Tonya R. Bergeson∗, Derek M. Houston and Richard T. Miyamoto Department of Otolaryngology-Head and Neck Surgery, Indiana University School of Medicine, Indiana, IN, USA

Abstract. Purpose: Cochlear implantation has recently become available as an intervention strategy for young children with profound hearing impairment. In fact, infants as young as 6 months are now receiving cochlear implants (CIs), and even younger infants are being fitted with hearing aids (HAs). Because early audiovisual experience may be important for normal development of speech perception, it is important to investigate the effects of a period of auditory deprivation and amplification type on multimodal perceptual processes of infants and children. The purpose of this study was to investigate audiovisual perception skills in normal-hearing (NH) infants and children and deaf infants and children with CIs and HAs of similar chronological ages. Methods: We used an Intermodal Preferential Looking Paradigm to present the same woman’s face articulating two words (“judge” and “back”) in temporal synchrony on two sides of a TV monitor, along with an auditory presentation of one of the words. Results: The results showed that NH infants and children spontaneously matched auditory and visual information in spoken words; deaf infants and children with HAs did not integrate the audiovisual information; and deaf infants and children with CIs initially did not initially integrate the audiovisual information but gradually matched the auditory and visual information in spoken words. Conclusions: These results suggest that a period of auditory deprivation affects multimodal perceptual processes that may begin to develop normally after several months of auditory experience.

Keywords: Audiovisual speech perception, cochlear implants, hearing aids, hearing loss, infants, children

1. Introduction

In typically developing infants, the auditory system is well developed at birth whereas the visual system takes several months to fully develop (Bahrick and Lickliter, 2000; Dobson and Teller, 1978; Gottlieb, 1976). Nevertheless, infants are capable of integrating auditory and visual speech information at a very young age (Kuhl and Meltzoff, 1982; Patterson and Werk- er, 2003). There is debate as to what role experience plays in acquiring early audiovisual integration skills

∗Corresponding author: Tonya R. Bergeson, Indiana University School of Medicine, Department of Otolaryngology-HNS, 699 West Drive RR044, Indianapolis, IN 46202, USA. Tel.: +1 317 274 8466; Fax: +1 317 274 4949; E-mail: [email protected].

for speech. Some researchers have proposed that ac- quiring complete representations of audiovisual speech gestures requires extensive experience listening to, ob- serving, and perhaps even producing speech. One way of measuring the effects of such experience is to com- pare audiovisual speech perception skills in normal- hearing infants and deaf infants who receive hearing aids or cochlear implants to restore maximal hearing capabilities. The purpose of the present study is to investigate the development of audiovisual perception of spoken words in infants with normal hearing and hearing loss who vary in chronological age, duration of deafness, and duration of audiological device use.

Young infants are capable of matching auditory and visual information that is naturally coupled in the en- vironment (Bahrick and Lickliter, 2000; Lewkowicz

0922-6028/10/$27.50  2010 – IOS Press and the authors. All rights reserved

158 T.R. Bergeson et al. / Audiovisual speech perception in children with hearing loss

and Kraebel, 2004). In one of the first studies of in- fants’ perception of audiovisual synchrony, for exam- ple, Spelke (1976) simultaneously presented two films, one portraying a woman playing peek-a-boo and the other portraying a hand playing percussion instruments, to 4-month-old infants. She then measured infants’ looking time to each of the films while a soundtrack corresponding to only one of the films was played, and found that the infants preferred to watch the film that matched the sound track. Several studies have more specifically explored infants’ perception and in- tegration of auditory and visual information in speech (Aldridge et al., 1999; Dodd, 1979; Lewkowicz, 2000; Walton and Bower, 1993). In a seminal study of in- fant audiovisual speech perception, Kuhl and Meltzoff (1982) presented 18- to 20-week-old infants with two faces visually articulating the vowels /a/ and /i/ and one sound track synchronized with one of the articulating faces. They found that the infants looked longer at the matching face than the nonmatching face. More recent studies have also shown that infants as young as 2.5 months of age successfully integrate audiovi- sual steady-state vowels (Patterson and Werker, 1999, 2003). Finally, infants as young as newborns prefer au- diovisually matched presentations of nonnative vowels (Aldridge et al., 1999; Walton and Bower, 1993).

Although infants show remarkable audiovisual matc- hing skills of simple speech stimuli like steady state vowels, other research has shown some limitations on their matching of more complex stimuli. When pre- sented with consonants or combinations of consonants and vowels, infants must correlate the visual and audi- tory signals that change rapidly over time as they are articulated by the talker. Mugitani, Hirai, Shimada, and Hiraki (2002) found that 8-month-olds had difficulty matching audiovisual information in consonants. On the other hand, MacKain, Studdert-Kennedy, Spieker, and Stern (1983) found that 5- to 6-month-old infants preferred to look longer at matching CVCV displays, but only when attending to the right side. Although they interpreted these results as indicative of left hemi- sphere speech processing, the results could also suggest that infants do not integrate audiovisual information in complex stimuli as easily as in steady-state vowels.

Despite being capable of matching audiovisual speech information, it remains possible that infants and children still have incomplete representations of the au- ditory and visual components in speech. Lewkowicz (2000) presented 4-, 6-, and 8-month-old infants with audiovisual syllables (/ba/ and /sha/) and measured their perception of auditory, visual, or audiovisual changes to

these syllables. They found that all age groups detect- ed auditory and audiovisual changes to the syllables, but only the 8-month-olds detected visual changes, un- less presented in an infant-directed speech style. These results suggest that infants’ perception of the visual components of AV speech may develop more slowly than their perception of the auditory components. In fact, there is still evidence of less visual influence on perception of audiovisual speech, compared to adults, by the time children reach preschool (Desjardins et al., 1997; McGurk and MacDonald, 1976; van Linden and Vroomen, 2008).

Several researchers have related infants’ uneven de- velopment of auditory and visual perception to their early experiences with listening, observing, and pro- ducing speech (e.g., Desjardins et al., 1997; Mugitani et al., 2008). In a study of preschoolers’ perception of congruent and incongruent audiovisual syllables, Des- jardins et al. (1997) found that the perception of the visual speech gestures was more adult-like in children who had more experience correctly producing conso- nants such as “th” compared to children who had diffi- culty producing such consonants. The authors further suggest that the representation of the visible articula- tion is built up by not just correctly producing conso- nants but also by the length of time correctly producing consonants. This notion has important implications for infants and children with congenital profound hearing loss who receive cochlear implants, who have no au- ditory experience prior to cochlear implantation, and who typically do not correctly produce consonants until several months or years following implantation.

One factor that is extremely important for early audi- tory experience in deaf children is age at implantation. Infants and children who are implanted at an earlier age thus have a shorter duration of deafness and a longer duration of experience with spoken language. In re- cent analyses of spoken word recognition and sentence comprehension in children with cochlear implants en- rolled in a longitudinal study of speech perception and language development, we found that prelingually deaf children showed more improvement in audiovisual and auditory-alone comprehension skills than visual-alone skills over a period of five years following cochlear implantation (Bergeson et al., 2003, 2005). We also found that children who were implanted under the age of 5 years performed better in the auditory-alone and audiovisual conditions than children implanted over the age of 5 years, whereas children who were implanted later had better visual-alone scores than children who were implanted earlier. Finally, pre-implantation per-

T.R. Bergeson et al. / Audiovisual speech perception in children with hearing loss 159

formance in the visual-alone and audiovisual condi- tions was strongly correlated with performance 3 years post-implantation on a variety of clinical outcome mea- sures of speech and language skills.

These results suggest that infants and children with hearing loss learn to utilize any speech information they receive, regardless of the modality. That is, children with less early auditory experience (i.e., implanted af- ter the age of 5 years) actually appear to be more influ- enced by the visual component of spoken language than children with more early auditory experience. Simi- larly, in a study of McGurk consonant perception in deaf children with cochlear implants, Schorr, Fox, van Wassenhove, and Knudsen (2008) found that children implanted after the age of 2.5 years were more influ- enced by the visual component of incongruent syllables than children implanted before the age of 2.5 years. Thus, early auditory and audiovisual experience seems to delay processing of the visual components of au- diovisual information, whereas early visual-only expe- rience serves to increase dependence upon the visual components of audiovisual information.

One main goal of the present study is to investi- gate audiovisual speech perception in normal-hearing infants and children and hearing-impaired infants and children who use hearing aids or cochlear implants. Recent studies have shown that hearing-impaired in- fants may be able to perceive and integrate audiovi- sual speech stimuli after approximately 12 months of cochlear implant experience, but audibility plays a role in successful audiovisual integration (Barker and Bass- Ringdahl, 2004; Barker and Tomblin, 2004). Thus, we hypothesize that infants and children with severe-to- profound hearing loss prior to receiving hearing aids and infants and children with profound hearing loss prior to receiving cochlear implants will have difficulty matching auditory and visual signals in a replication and extension of Kuhl and Meltzoff’s (1982) audiovi- sual speech perception task.

Another goal of this study is to investigate the ef- fects of duration of severe-to-profound hearing loss on audiovisual speech perception. If longer durations of early auditory deprivation lead to increased difficul- ty acquiring audiovisual speech integration skills, then earlier implanted infants and children should perform better on audiovisual speech perception tasks than later implanted infants and children.

The majority of previous studies of infants’ percep- tion of audiovisual speech have used isolated steady- state vowels as test stimuli, even though those sounds rarely occur in everyday speech to infants and children.

It is important to measure audiovisual speech input that infants and children experience in their natural environ- ment. Compared to isolated steady-state vowels, spo- ken words encode highly distinctive auditory and visual phonetic information such as rapid spectrum changes and dynamic movements of the articulators over time. Therefore, a third goal of the present study is to measure the development of audiovisual perception of words in normal-hearing infants and hearing-impaired infants with hearing aids or cochlear implants across a variety of ages.

2. Method

2.1. Subjects

Normal-hearing infants and children (n = 20; 11 fe- males) ages 11.5–39.5 months (m = 23.9) were recruit- ed from the local community. Any infants with three or more ear infections per year were administered a tym- panogram and otoacoustic emission testing to insure normal hearing.

Infants and children with bilateral hearing loss were recruited from Indiana University School of Medicine (see Table 1). Hearing Aids: Twenty children (9 fe- males) received hearing aids between the ages of 2– 19 months (m = 6.2 months) and were 8–28 months of age (m = 15.6 months) at time of testing. Their pre-amplification unaided pure tone averages ranged from 38–120 dB (m = 61.5 dB). An additional three children with hearing aids were excluded because they did not complete testing. Cochlear Implants: Nineteen children (5 females) received a cochlear implant be- tween the ages of 10–24 months (m = 15.6 months) and were 16–39 months of age (m = 26.6 months) at time of testing. Their pre-amplification unaided pure tone averages ranged from 67–120 dB (m = 112.0 dB). An additional eight children with cochlear implants were excluded because they did not complete testing. Hearing-impaired subjects were tested at 3–20 months post-amplification; some were tested at more than one post-amplification interval.

All subjects had normal vision, as reported by their parents. The families were paid $10/hour for their par- ticipation. Families of hearing-impaired infants were also reimbursed for transportation and lodging costs when traveling from long distances.

160 T.R. Bergeson et al. / Audiovisual speech perception in children with hearing loss

Table 1 Participant demographics

Age at Pre-amplification Device

amplification (mos) unaided PTA (dB)

Cochlear Implant Group CI15 13.8 102 Nucleus 24 Contour CI19 10.3 67 Med-El C 40+ CI22 22.1 97 Nucleus 24 Contour CI25 16.1 118 Nucleus 24 K CI28 16.8 118 Nucleus 24 Contour CI29 16.5 118 Med-El C 40+ [L] Advanced Bionics HiRes 90K [R] CI34 10.4 112 Nucleus 24 Contour CI35 16.7 120 Nucleus Freedom–Contour Advance CI39 17.9 97 Nucleus Freedom–Straight CI40 13.2 118 Nucleus Freedom–Contour Advance CI42 12.8 117 Nucleus Freedom–Contour Advance CI48 20.5 118 Nucleus Freedom–Contour Advance CI49 20.5 118 Nucleus Freedom–Contour Advance CI51 10.2 118 Nucleus Freedom–Contour Advance CI53 11.9 118 Nucleus Freedom–Contour Advance

CI3029 14.5 118 Advanced Bionics HiRes 90K CI3058 24.2 112 Nucleus Freedom–Contour Advance CI3307 9.9 118 Advanced Bionics HiRes 90k focus CI3374 13.6 107 Nucleus Freedom–Contour Advance Hearing Aid Group

HA03 2.2 . Phonak Naida 111 UP HA07 4.6 41 Oticon Gaia BTEs HA08 6.2 48 Phonak Maxx 311 BTE HA09 19.6 46 Phonak Maxx 311 BTEs HA10 10.6 64 Oticon Gaia BTEs HA11 6.6 53 Phonak Maxx 211 BTE HA12 8.4 43 Unison 6 BTEs HA13 2.0 44 Unitron Unison 6 BTE HA14 4.7 47 Oticon Gaia BTEs HA16 14.1 118 Phonak Power Maxx 411 BTEs HA17 3.4 120 Phonak Maxx 311 BTEs HA18 4.1 47 Phonak Maxx 311 BTEs HA20 1.4 120 Phonak Maxx 311 BTE HA22 8.8 45 Phonak Maxx 311 BTEs HA24 5.2 38 Oticon Gaia VC BTEs HA25 6.4 80 Oticon Sumo BTE [L] Oticon Tego Pro BTE [R]

HA3029 3.9 120 Oticon Tego Pro BTEs HA3551 2.3 104 Oticon Sumo DM HA3664 7.1 39 Oticon Safran BTEs HA3699 2.5 76 Oticon Tego Pro BTEs

2.2. Stimulus materials

Audiovisual test stimuli were drawn from the Hoosier Audiovisual Multitalker Database of spoken words, in which a female talker produced CVC mono- syllabic words in a natural adult-directed manner using neutral facial expressions (Lachs and Hern ández, 1998; Sheffert et al., 1996). The words “judge” and “back” were used in this study. These two words were select- ed because their articulations are visually distinctive and the durations of the audiovisual clips are closely matched (“judge” = 0.595 s; “back” = 0.512 s). The auditory stimuli were presented at 65–70 dB HL, well within the audible range for all groups of infants.

2.3. Apparatus and procedure

Testing was conducted in a custom-made, double- walled IAC sound booth. Infants sat on their caregiver’s lap in front of a large 55-inch wide-aspect TV monitor. The experiment was conducted using HABIT software (Cohen et al., 2004). Video clips of the two test words (“judge” and “back”) were presented simultaneously on the left and right sides of the TV monitor. Visu- al presentation of the test words was counterbalanced across testing sessions (judge-left, back-right versus judge-right, back-left). During the pre-test phase, two silent trials were presented to determine whether indi- vidual infants exhibited a response bias for the visual

T.R. Bergeson et al. / Audiovisual speech perception in children with hearing loss 161

NH-1 NH-2 HA-1 HA-2 CI-1 CI-2

L oo

ki ng

t im

e (s

ec )

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Target Nontarget

1st Block 1st Block 1st Block2nd Block 2nd Block 2nd Block

Normal Hearing Hearing Aid Users Cochlear Implant Users

Fig. 1. Total looking time at the matching and nonmatching faces in the first and second blocks of the experiment across hearing status. Error bars indicate standard error.

articulation of one word over the other. During the test phase, the same video clips were presented in each of 16 trials (8 repetitions of the words per trial). Half of the trials were also accompanied by the sound track from one of the spoken words (e.g., “judge”) and half of the trials used the other spoken word (e.g., “back”), in random order. Prior to each trial the infant’s atten- tion was drawn to the TV monitor using an “attention getter” (i.e., a video of a laughing baby’s face).

Each trial was initiated when the infant looked at the attention getter and continued until all 8 repetitions of the word were completed. To assess the direction and durations of the infants’ looking behavior during the test phases, we coded the infants’ looking responses offline using the digital video tape recordings of the testing sessions. All coding was performed by trained research assistants who were blind to the stimulus con- ditions and experimental hypotheses. All coders were trained on a subset of previously coded videos until they consistently achieved greater than 95% consisten- cy with previous codings.

3. Results

None of the groups of infants and children showed a looking time preference for either word (“judge” or “back”) during the visual-only pre-trial presentations. Because infants and young children often have diffi-

culty maintaining attention for a period of time, we analyzed the results for the first block of trials (trials 1–8) and the second block of trials (trials 9–16) to track children’s attention and interest levels over the course of the experimental session. Moreover, it could also be the case that infants and children with hearing loss might not immediately detect the audiovisual corre- spondence and instead need extra time to learn that the auditory signal matches only one of the visual signals. Total looking times (s) – averaged across trials in each condition for each block and for each individual group of infants and children – are presented below.

3.1. Normal hearing infants and children

As shown in Fig. 1, normal-hearing infants prefer to look longer at the matching face (m= 3.78, s.d. = 0.55) than the nonmatching face (m = 3.42, s.d. = 0.55) in the first block of trials, t(19) = 2.15, p = 0.045. In the second block of trials, normal-hearing infants did not show a looking time preference for either the matching face (m = 3.18, s.d. = 0.87) or the nonmatching face (m = 3.17, s.d. = 0.57) face, t(19) = 0.03, p = 0.973.

3.2. Deaf infants and children with hearing aids

Because hearing-impaired subjects with hearing aids were tested at more than one post-amplification inter- val, we completed linear mixed-model analyses (SPSS

162 T.R. Bergeson et al. / Audiovisual speech perception in children with hearing loss

Fig. 2. Looking time differences (looking time to matching face minus looking time to nonmatching face) across levels of pre-amplification unaided hearing thresholds (below and above 70 dB) in infants who use hearing aids. Error bars indicate standard error.

16). Figure 1 shows that hearing-impaired infants with hearing aids did not prefer to look longer at the match- ing face (m = 3.69, s.d. = 0.62) than the nonmatching face (m = 3.55, s.d. = 0.78) in the first block, F(1, 30) = 0.554, p = 0.467. In the second block, hearing- impaired infants with hearing aids again did not show a looking time preference for either the matching face (m = 3.29, s.d. = 0.76) or the nonmatching face (m = 3.26, s.d. = 0.79), F(1, 30) = 0.014, p = 0.906.

To investigate the effects of pre-amplification unaid- ed pure tone averages on audiovisual speech perception, we compared looking time preferences across children with mild-to-moderate hearing loss (hearing thresholds of 25–70 dB, n = 12) versus those with severe-to- profound hearing loss (hearing thresholds over 70 dB, n = 7) for each block of test trials (see Fig. 2). Lin- ear mixed-model analyses revealed that looking pref- erences in children with mild-to-moderate hearing loss and in children with severe-to-profound hearing loss differed significantly in Block 1, F(1, 16.4) = 4.87, p = 0.04, but not in Block 2. Further analyses revealed that only the children with mild-to-moderate hearing loss looked significantly longer at the matching than non- matching face (F(1, 8.1) = 10.90, p = 0.01) in Block 1, whereas those with severe to profound hearing loss did not show any statistically significant looking pref-

erences in Block 1 or Block 2. These results suggest that, like NH infants and children, children with mild- to-moderate hearing loss are able to match auditory and visual speech information.

3.3. Deaf infants and children with cochlear implants

Because hearing-impaired subjects with hearing aids were tested at more than one post-amplification inter- val, we completed linear mixed-model analyses (SPSS 16). Figure 1 shows a pattern of preferences across the two experimental blocks that is in direct contrast to the pattern of preferences in the normal-hearing infants and children. In the first block of trials, linear mixed- model analyses revealed that hearing-impaired infants with cochlear implants actually looked slightly longer at the nonmatching face (m = 3.93, s.d. = 0.54) than the matching face (m = 3.66, s.d. = 0.55), although the difference was not statistically significant, F(1, 27) = 2.46, p = 0.128. On the other hand, in the second block of trials, hearing-impaired infants with cochlear implants looked significantly longer at the matching face (m = 3.67, s.d. = 0.85) than the nonmatching face (m = 3.05, s.d. = 0.62), F(1, 27) = 13.56, p = 0.001.

An ANCOVA with face type (matching vs. mis- matching) as the independent variable, looking time (s)

T.R. Bergeson et al. / Audiovisual speech perception in children with hearing loss 163

Fig. 3. Looking time differences (looking time to matching face minus looking time to nonmatching face) for infants who received cochlear implants prior to 14 months of age (Early) and after 14 months of age (Late). Error bars indicate standard error.

as the dependent variable, and pre-amplification PTA (dB) as a covariate revealed no effects or interactions with pre-amplification hearing level. To investigate the effects of age at cochlear implant stimulation and dura- tion of cochlear implant use on audiovisual speech per- ception, we compared looking time preferences across the first and second experimental blocks in infants and children who received cochlear implant stimulation be- fore the age of 15 months (Early, n = 10) and af- ter the age of 15 months (Late, n = 9) at 3, 6, 12, 18, and 20 months after implantation. Fig. 3 shows that the children in both groups initially looked longer at the nonmatching than the matching face, but then switched preferences to look longer at the matching than the nonmatching face in the second block of tri- als. Linear mixed-model analyses revealed that per- formance between groups did not differ significantly in Block 1 but did differ significantly in Block 2, F(1, 12.7) = 7.40, p = 0.02; only the Late group looked sig- nificantly longer at the matching than the nonmatching face, F(1, 6.5) = 11.41, p = 0.01. There was also a significant effect of post-implantation interval during Block 2, F(4, 8.3) = 6.80, p = 0.01. Post-hoc anal- yses revealed significantly worse performance at the 3-month post-implantation interval than the 6-month post-implantation interval (p= 0.04, Bonferroni adjust- ment for multiple comparisons). These findings sug- gest that performance was influenced by both age at im-

plantation and duration of cochlear implant experience. However, the effect of age at implantation was opposite than predicted – earlier implanted children performed worse than later implanted children.

4. Discussion

Based on previous studies of audiovisual speech per- ception in normal-hearing infants and hearing-impaired infants and children with cochlear implants (Barker and Tomblin, 2004; Bergeson et al., 2003, 2005; Kuhl and Meltzoff, 1982; Patterson and Werker, 2003), we pre- dicted that audiovisual speech perception skills would be influenced by hearing impairment. However, we found that infants and children in all three groups (those with normal-hearing, hearing aids, or cochlear im- plants) did not look significantly longer at the matching versus nonmatching face while listening to the words “judge” or “back.”

Nevertheless, interesting patterns of performance emerged when comparing looking time preferences across the first and second blocks of the experiment. Normal-hearing infants and children with mild-to- moderate hearing loss initially preferred to look longer at the matching face than the nonmatching face. Dur- ing the second block of the experiment, however, they looked approximately the same amounts at both the

164 T.R. Bergeson et al. / Audiovisual speech perception in children with hearing loss

matching and nonmatching faces. It is possible that once they have successfully matched up the auditory and visual signals they become equally bored with the matching and nonmatching faces. In fact, their looking times do decrease somewhat across the two blocks of trials. Interestingly, infants and children with greater hearing loss prior to receiving their hearing aids did not show the ability to match auditory and visual speech information during either block of trials. Thus, it ap- pears that auditory experience plays a role in audiovi- sual speech perception.

Additional evidence for this notion is that deaf in- fants with cochlear implants could not successfully match the auditory and visual information in the spo- ken words until the second block of trials and that per- formance was worse at the earliest post-implantation interval. An ANCOVA also revealed that the amount of pre-implantation hearing loss did not affect these results, likely because there was little variance in the levels of hearing loss. Interestingly, infants and chil- dren who were implanted earlier did not do as well as those who were implanted later on the audiovisu- al speech perception task. Recall that Bergeson et al. (2003, 2005) found that children implanted later per- formed better on the visual-only task of speech com- prehension measures, whereas children implanted ear- lier performed better on the auditory-only and audiovi- sual portions of the speech comprehension measures. Moreover, Schorr et al. (2008) found similar effects of age at implantation in a replication of the McGurk audiovisual speech perception test (McGurk and Mac- Donald, 1976). They suggest a sensitive period of ap- proximately 2.5 years for bimodal fusion. After this sensitive period, deaf children with cochlear implants are influenced more by the visual input rather than the auditory input. In the present study, it is possible that the children implanted later process the visual compo- nents but must learn the correspondence between the visual and auditory signals, as evidenced by the prefer- ence for matching audiovisual stimuli only in Block 2. Moreover, the present results on duration of device use suggest that early-implanted infants and children might eventually show the same bimodal fusion in Block 1 as normal-hearing infants and infants with mild-moderate hearing loss after a sufficient period of cochlear implant experience.

Evidence from studies with animals and studies of human neural responses suggests that the absence of sound during the first several months of life affects neu- ral development at several points along the peripheral auditory pathway and other higher-level cortical areas

(Kral et al., 2000; Leake and Hradek, 1988; Neville and Bruer, 2001; Ponton et al., 1996; Ponton and Eg- germont, 2001; Ponton et al., 2000; Ponton et al., 1999; Sharma et al., 2002). Connections between the audi- tory cortex and other brain structures may not develop normally in congenitally deaf infants, and, as a result, their visual, attentional, and cognitive neural networks may not be strongly linked to their auditory process- ing skills after receiving a cochlear implant. Moreover, early experience and activities with multimodal stimu- lus events appear to be necessary for the development of auditory and visual sensory systems and the inte- gration of common “amodal” information from each modality (Lewkowicz and Kraebel, 2004). It is possi- ble, then, that children who have been deprived of au- ditory sensory input before and immediately following birth because of a hearing loss may not acquire spo- ken language through normal auditory-visual sensory means.

In summary, the results of the present study reveal that level of hearing loss and age at cochlear implan- tation do in fact affect the development of audiovisual speech perception. Normal-hearing children, children with more hearing prior to receiving hearing aids, and children who received a cochlear implant later rather than earlier were the most successful at matching au- ditory and visual components of spoken words. These findings suggest that early auditory experience is very important for developing normal audiovisual speech perception abilities. However, infants and children with hearing loss may learn to rely on the visual modality to aid audiovisual speech perception.

Acknowledgements

This research was supported by the American Hearing Research Foundation, NIH/NIDCD Research Grant R21DC06682 and NIH/NIDCD Training Grant T32DC00012. We gratefully acknowledge Carrie Han- sel, Kabreea York and the Babytalk Research research assistants for their help testing the participants and cod- ing the data. Finally, we thank the participants and their families, some of whom traveled great distances, for their participation.

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