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Hearing Research 309 (2014) 94e102

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Hearing Research
journal homepage: www.elsevier.com/locate/heares

Research paper

Sustained attention, selective attention and cognitive control in deaf

and hearing children
Matthew W.G. Dye a, *, Peter C. Hauser b
a
Department of Speech and Hearing Science, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
b
Department of American Sign Language and Interpreting Education, National Technical Institute for the Deaf, Rochester, NY 14623, USA

a r t i c l e i n f o a b s t r a c t

Article history: Deaf children have been characterized as being impulsive, distractible, and unable to sustain attention.
Received 1 October 2013 However, past research has tested deaf children born to hearing parents who are likely to have expe-
Received in revised form rienced language delays. The purpose of this study was to determine whether an absence of auditory
27 November 2013
input modulates attentional problems in deaf children with no delayed exposure to language. Two
Accepted 5 December 2013
Available online 16 December 2013
versions of a continuous performance test were administered to 37 deaf children born to Deaf parents
and 60 hearing children, all aged 6e13 years. A vigilance task was used to measure sustained attention
over the course of several minutes, and a distractibility test provided a measure of the ability to ignore
task irrelevant information e selective attention. Both tasks provided assessments of cognitive control
through analysis of commission errors. The deaf and hearing children did not differ on measures of
sustained attention. However, younger deaf children were more distracted by task-irrelevant information
in their peripheral visual field, and deaf children produced a higher number of commission errors in the
selective attention task. It is argued that this is not likely to be an effect of audition on cognitive pro-
cessing, but may rather reflect difficulty in endogenous control of reallocated visual attention resources
stemming from early profound deafness.
Ó 2013 Elsevier B.V. All rights reserved.

1. Introduction such studies have lead to theories that articulate the role of audi-
tion in shaping those cognitive processes (Conway et al., 2009). This
Recently, there has been much interest in the relationship be- has lead to the claim that the deleterious effect of profound deaf-
tween audition and cognition. The new field of cognitive hearing ness on spoken language development is compounded e deafness
science (Arlinger et al., 2009) has highlighted the important role of makes access to the sound structure of the language difficult, and at
domain-general cognitive processes, such as working memory the same time leads to deficits in the cognitive skills needed to
(Rönnberg et al., 2008), attention (Wild et al., 2012), and sequence support spoken language comprehension under adverse conditions
processing (Conway et al., 2009) in supporting spoken language (Conway et al., 2009).
comprehension and production. In instances where auditory sys- However, there are some profoundly deaf children who do not
tems are compromised (for example, in age-related hearing loss, or struggle to acquire language. These are deaf children born into
noisy environments), these cognitive systems have been shown to culturally Deaf families where they are exposed in infancy to a
play a pivotal role in supporting successful spoken language pro- natural signed language such as American Sign Language (ASL).
cessing. One approach to identifying which cognitive processes Sign languages are the natural languages of Deaf communities and
support auditory processing in the context of language compre- possess phonological systems, morphological systems and syntac-
hension is to study individuals who are profoundly deaf. Indeed, tic rules, operating within complex grammatical systems (Sandler
and Lillo-Martin, 2006). Whatever cognitive processes are
required for modality-independent language processing are clearly
Abbreviations: ADD/ADHD, Attention Deficit Disorder/Attention Deficit- not impaired by deafness in these children, who achieve typical
Hyperactivity Disorder; ANCOVA, Analysis of Covariance; ASL, American Sign Lan- language and social milestones in infancy (Bonvillian et al., 1983;
guage; CI, cochlear implant; CPT, continuous performance task; GDS, Gordon Marschark, 1993; Peterson and Siegal, 2000; Petitto and
Diagnostic System; SES, socio-economic status; SLI, Specific Language Impairment;
Marentette, 1991). However, it is remains possible that the cogni-
T.O.V.A., Test of Variables of Attention
* Corresponding author. Tel.: þ1 217 244 2546. tive processes required to support spoken language are negatively
E-mail address: mdye@illinois.edu (M.W.G. Dye). impacted by a lack of auditory stimulation. One such process that

0378-5955/$ e see front matter Ó 2013 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.heares.2013.12.001
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M.W.G. Dye, P.C. Hauser / Hearing Research 309 (2014) 94e102 95

has been demonstrated to play a role in audio-visual speech distracted by the flanking digits; in other words, a failure of visual
comprehension (Kushnerenko et al., 2013) and word-to-world selective attention. In studies using these tasks, deaf children have
mapping (Yu and Smith, 2011) is visual attention. Here we focus been reported to have poorer cognitive control (Quittner et al.,
upon two aspects of visual attention thought to be compromised in 1994) and to suffer from an inability to select targets appropri-
deaf children: the ability to sustain attention over a significant ately (Mitchell and Quittner, 1996) relative to hearing age-matched
period of time, and the ability to select task-relevant stimuli and controls. Furthermore, Smith et al. (1998) reported data suggesting
avoid distraction e selective attention. that cochlear implantation alleviates these deficits, although the
children with cochlear implants (CIs) did not achieve the perfor-
1.1. Attentional deficits in deaf children mance levels of hearing controls. The authors suggested that their
data indicate a deficit in visual selective attention stemming from
Deaf children have been reported to have behavioral problems poor multimodal sensory integration as a result of early, profound
related to impulse control, distractibility, and an inability to sustain hearing loss. Such a position can be termed a deficiency hypothesis
attention in the visual modality. Quittner et al. (1990) reported that and, generally stated, it proposes that integration of information
parents of deaf children indicated that their children had greater from the different senses is an essential component to the devel-
distractibility-hyperactivity problems compared with the parents opment of normal attentional functioning within each individual
of hearing children. In a study of teacher-identified problem be- sensory modality.
haviors in deaf children, Reivich and Rothrock (1972) suggested An alternative view holds that attention-related deficits in deaf
that impulsivity and a lack of inhibitory control accounted for a children may be related to their limited exposure to language and
significant amount of the problem behaviors reported. Chess and impoverished social communication early in life (Dye and Bavelier,
Fernandez (1980) reported elevated levels of impulsive behavior 2013). Whether auditory loss, delays in language exposure, or
in deaf children manifest as aggressive acts such as kicking, hitting, abnormal socio-emotional development leads to attention deficits
and biting. Theirs was a study of deaf children whose mothers had in deaf children remains a poorly understood issue. Other con-
Rubella during gestation, and the aggressive behaviors were more founds are also worthy of consideration. For example, Parasnis et al.
prevalent in those with multiple disabilities, than in the healthy (2003) administered the Test of Variables of Attention (T.O.V.A.;
children with deafness alone. Leark et al., 1999) to deaf and hearing college students. Their data
Parental and teacher reports, however, are by nature a subjec- suggested that deaf observers had decreased cognitive control
tive approach. Other researchers have adopted clinical measures when selecting the appropriate response, accompanied by
that assess cognitive control by measuring how long it takes a child decreased perceptual sensitivity. Parasnis et al. (2003) argued that
to complete a task, and how many errors they make e fast this reflected appropriate adaptations to the environment for
completion coupled with a large number of errors is taken as an someone who cannot hear and was not an attentional pathology.
indicator of an impulsive response style. Several studies have Specifically, they argued, a less conservative response criterion re-
shown that deaf children of hearing parents perform more poorly flects reliance upon vision for alerting in the absence of auditory
than hearing children on these types of clinical measures, including input. The decreased perceptual discrimination ability, they argued,
the Porteus Maze Test (Best, 1974; Eabon, 1984; O’Brien, 1987), the resulted from redistribution of attention away from the center and
Matching Familiar Figures Test (Eabon, 1984; O’Brien, 1987), and toward peripheral vision, as initially proposed by Neville and her
the Draw-a-Man Test (Harris, 1978). Interestingly, the study by collaborators (Neville and Lawson, 1987a, 1987b; Neville et al.,
Harris (1978) revealed an effect of parental hearing status on the 1983). In the absence of audition, a key modality in the detection
Matching Familiar Figures and Draw-a-Man Test, with deaf children of events in an individual’s immediate environment, visual selec-
born to deaf parents outperforming those born to hearing parents. tion attention becomes enhanced in deaf individuals in the pe-
riphery of their visual field (Bavelier et al., 2006). This possibility
1.2. Continuous performance tests should also be entertained when considering the Mitchell and
Quittner (1996) findings. In sum, the existing body of evidence
More recently, deficits in visual continuous performance tasks points to weaker cognitive control and poor visual selective
(CPTs) have been reported in deaf children (Horn et al., 2005; attention in deaf individuals, but the source of these effects remains
Mitchell and Quittner, 1996; Quittner et al., 2004, 1994; Smith controversial.
et al., 1998; Yucel and Derim, 2008). CPTs are computerized mea-
sures of attention that typically require children to attend to a 1.3. Continuous performance tests and cochlear implantation
rapidly changing stream of stimuli. They have advantages over the
clinical measures discussed in the previous section, including less Horn et al. (2005) reported a retrospective longitudinal study of
subjectivity in the rating of performance and determination of er- CPT performance in deaf children who had undergone CI surgery.
rors, ease of administration, and the existence of large data sets These implanted children demonstrated poor sustained attention,
providing norms across a large range of ages. which improved little with increasing years of CI use. A study by
In one commonly used CPT, the Gordon Diagnostic System (GDS; Yucel and Derim (2008) looked at the effect of age of implantation
Gordon and Mettleman, 1987), digits appear rapidly, one at a time, on sustained attention in 6e11 year old deaf children. They re-
in the center of an LED display. Children are usually required to ported elevated levels of inattention and impulsivity in deaf chil-
make a response to a target digit or to a specific sequence of target dren compared to hearing controls, with performance poorer in
digits. The GDS can be administered as a visual task, with no those deaf children who received CIs after the age of 4 years
auditory component, and has therefore been used with deaf chil- compared to those who received their implants at a younger age.
dren. In one version of the task, correctly pressing a button in Interestingly, Shin et al. (2007) reported the opposite in a pro-
response to the digit 9, but only when a 1 precedes it, is an index of spective longitudinal study of Korean deaf children receiving a CI at
sustained attention. Pushing the button at any other time (a com- 6e7 years of age: they demonstrated more inattention and
mission error) is taken as being indicative of impulse control impulsivity following surgery than they did pre-implant.
problems, reflecting poor cognitive control. In another version, In studies of recovery of function following cochlear implanta-
irrelevant digits appear to the left and right of the central target tion there is a confound between restoration of auditory input, age
digit stream. Poor performance is attributed to the child being of implantation, and the acquisition of language. It is unclear to
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96 M.W.G. Dye, P.C. Hauser / Hearing Research 309 (2014) 94e102

what extent any remediative effects of cochlear implantation are and/or teacher reports). Due to reports of elevated attentional
due to improved access to audition or to exposure to (spoken) abilities in children who play action video games (Dye and Bavelier,
language, with earlier implantation leading to better language 2010b; Dye et al., 2009a), children who reported playing such
development than later implantation (Niparko et al., 2010; Tomblin games were also excluded from the study. Testing time did not
et al., 2005). Interestingly, a study by Tharpe et al. (2002) failed to permit the administration of tests of non-verbal IQ or language
find any differences in sustained visual attention between hearing skill. However, no general cognitive or language difficulties were
children and deaf children who either used hearing aids or CIs. reported for any of the children by their parents or teachers. More
Whilst they did not find any group differences as a function of detailed demographic data for the children are reported in Table 1.
preferred communication mode, their sample sizes were relatively
small. Tharpe et al. (2002) concluded that further research was
needed to determine how preferred communication mode shapes 2.1.1. Hearing children
the relationship between hearing status and performance of tests Sixty hearing children were recruited from public schools in
of visual attention. Champaign, Illinois in the United States. This included 29 boys and
31 girls, all aged between 6 and 13 years of age, None of these
1.4. Deafness, audition and language delay children had a diagnosed hearing loss, learning disability, or any
other sensory impairment. Hearing status and the presence or
Deafness cannot be easily separated from social and linguistic absence of learning disabilities was ascertained via parent or
experience (Dye and Bavelier, 2013). All of the studies that report teacher report. All were monolingual native speakers of English,
attentional deficits as a consequence of deafness are based upon and had no knowledge of ASL. Socio-economic status (SES) was
deaf children born to hearing parents, many of whom received CIs, assessed using the Hollingshead four-factor method (Hollingshead,
and most of whom are taught spoken language or a form of manual 1975) that weights paternal and maternal occupation and educa-
communication based upon a visual representation of spoken tion levels to derive a single SES score that can range from 8 to 62.
language that is co-produced with speech. This latter mode of Higher scores indicate a higher socio-economic status. The mean
communication is sometimes called Total Communication, and has SES score for the hearing children was 55.5 (SD ¼ 9.3), which can be
been reported to limit spoken language acquisition due to seg- interpreted as having parents with a college degree and a profes-
mentation difficulties (Ting et al., 2012) and limit sign language sional occupation.
acquisition due to input that cannot be nativized (Wilbur, 2008).
Without confirmation from studies recruiting deaf children born to
Deaf parents, who acquire ASL and achieve typical language and 2.1.2. Deaf children
social milestones in infancy, it is possible that the attentional Thirty-seven deaf children were recruited from residential
problems indicated in deaf children are the result of early schools for the Deaf in Texas, California, Maryland, and Indiana. All
communicative deficits stemming from language acquisition of these schools employed a bilingual-bicultural approach to deaf
delays. education. There were 17 boys and 20 girls, all with at least a
In this study, we administered two forms of the GDS CPT to 37 severe-to-profound hearing loss (HL > 75 dB PTA in the better ear).
deaf children born to Deaf parents from whom they acquired ASL as Hearing status was ascertained via parent or teacher report. All had
a native language, and to 60 hearing children born into hearing acquired ASL as infants from their Deaf parents, and none had
families. Deficit hypotheses (Conway et al., 2009; Mitchell, 1996) received a CI. As with the hearing children, none had any other
predict weaker sustained attention, less ability to allocate selective diagnosed sensory impairment or learning disability. Their mean
attention, and decreased cognitive control in deaf children SES computed using the Hollingshead method was 50.0 (SD ¼ 9.8),
compared to hearing peers of the same age, regardless of age of interpretable as having parents with a college degree and mana-
exposure to natural language and early socio-communicative en- gerial/administrative occupations.
vironments. Thus any observed differences in performance be-
tween our groups, all exposed to a natural language from birth but
Table 1
differing in access to audition, could be attributed to the effects of Demographic characteristics of hearing and deaf children.
auditory deprivation per se and not to language delay. The GDS has
Hearing Deaf
been used in previous studies of attention in deaf children (see
above). It presents target stimuli at a fixed spatial location, 6e8 years 9e13 years 6e8 years 9e13 years
requiring temporal sequence processing in order to successfully N 19 41 12 25
respond to the 1e9 target sequence. As a task that imposes few Age M (SD) months 89 (11) 133 (18) 90 (7) 138 (18)
spatial demands but which has high temporal demands, it is an Age Range 74e106 109e167 77e101 109e165
# males (%) 12 (63%) 17 (41%) 7 (58%) 10 (40%)
ideal instrument to test the types of deficit predicted by hypotheses
SES M (SD) 56 (8) 55 (10) 51 (11) 49 (9)
such as the auditory scaffolding hypothesis (Conway et al., 2009). SES Range 39e66 22e66 22e64 28e61
Racial identity
2. Materials and methods White 14 30 12 25
Black 1 2 0 0
Asian or PI 3 8 0 0
2.1. Participants No response 1 1 0 0
Ethnicity
The Institutional Review Board at the University of Illinois at Non-Hispanic 17 39 9 20
Urbana-Champaign approved this study. Written, informed con- Hispanic 1 1 3 5
No response 1 1 0 0
sent was obtained from both parents and children before data
Reported language fluency
collection procedures were initiated. Inclusion/exclusion criteria English 19 41 2 9
and sample characteristics for deaf and hearing children are sum- ASL 0 0 12 25
marized below. All participants were required to have normal or Spanish 0 1 0 0
corrected-to-normal vision, no reported learning disability (such as Hebrew 1 0 0 0
Mandarin 0 1 0 0
SLI or ADD/ADHD), nor any cognitive deficits (based upon parental
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The deaf and hearing children differed significantly on this SES other than a 1 preceded it. The test consisted solely of visual stimuli,
measure: F (1, 93) ¼ 6.38, p ¼ .013, partial h2 ¼ 0.06. Due to the with no auditory component. Children were seated with their eyes
significantly lower SES of the deaf children, this measure was used approximately 30 cm from the LED display, such that each digit was
as a covariate in all analyses. 1.9 degrees of visual angle high and 0.95 degrees of visual angle
wide. A total of 540 digits appeared at a rate of 1 per second. These
2.2. Design digits appeared in 3 blocks of 180 digits (although children were
unaware of this) and the target sequence (1 / 9) occurred 15 times
Measures were obtained of sustained attention, selective within each block.
attention, and cognitive control from all children using the vigi- D-prime scores were computed using the method reported by
lance and distractibility forms of the GDS CPT. Children were Green and Swets (1966). Children who did not make any misses
divided into younger and older groups based upon previous find- were assigned a hit rate of 44/45, and those who made no false
ings in the literature (Quittner et al., 1994; Smith et al., 1998). The alarms were assigned a false alarm rate of 494/495. The vigilance d-
effect of age group (6e8 years, 9e13 years) and hearing status prime scores were negatively skewed, and therefore a log-
(hearing, deaf) was determined for each of the three dependent transformed variable for this measure was computed to allow
measures. parametric statistical analysis. These log-transformed d-prime
scores were used as an index of sustained attention. Failure to
2.3. Procedure sustain attention to the target stream would result in an increase in
the number of misses, which would not be offset by a higher overall
Children were tested individually and in a quiet setting free from response rate.
auditory and visual distraction, either at home or in their school.
After explaining the study to children in their preferred language 2.3.2. Cognitive control e sustained attention task
and obtaining written consent, the experimental procedures were To obtain a measure of cognitive control, the total number of
explained. A native hearing speaker gave instructions in spoken commission errors in the sustained attention task was computed
English to hearing children, and a native ASL signer gave in- for each child. These errors included responses to the first digit of
structions in ASL to deaf children. No practice trials were given. For the target sequence (XX1 or X1X responses), or responses to the
all children, the vigilance test was administered first, followed by a second digit of the sequence (9) when it was not in a target
5-min break and then the distractibility test. sequence (XX9 and X9X responses). Errors that were considered to
be due to a delayed response (19X responses) were not included.
2.3.1. Sustained attention Due to experimenter error, commission error data for the sustained
The children were shown the GDS CPT apparatus (Fig. 1) and told attention task was not collected for 5 deaf children (one 6e8 year
that they were required to watch a stream of digits appearing on old, and four 9e13 year olds). The number of commission errors
the red LED display. Their task was to look for a specific sequence of was compared to published norms (Gordon and Mettleman, 1987)
digits e a 9 preceded by a 1 (see Fig. 2A for a diagrammatic rep- in order to determine the proportion of children in each group who
resentation of the sustained attention task). They were instructed were normal or borderline-abnormal.
to rest their hand on a blue button below the red LED display, and to
press that blue button as quickly as possible whenever they saw a 9 2.3.3. Selective attention
that was preceded by a 1. Children were specifically instructed not After completing the sustained attention task, children per-
to press when they saw a 1, and not to respond to a 9 if any digit formed the selective attention task. They were instructed to
respond in the same way as in the sustained attention task,
ignoring flanking distractor digits that appeared to the left of right
of the central target digits. Again, there were a total of 540 digits
appearing in the center of the display at a rate of 1 per second and
subtending 1.9 by 0.95 degrees of visual angle. The sequence of
digits was identical to that presented in the sustained attention
task. Distractor digits appeared randomly 1.9 degrees of visual
angle to the left or right of the central target digits. See Fig. 2B for a
diagrammatic representation of the selective attention task.
To compute an index of selective attention, each individual’s d-
prime score from this task was subtracted from their d-prime score
for the sustained attention task. In the GDS, the stream of central
digits is identical in both tasks. This subtractive measure therefore
provides an index of the extent to which the flanking distractor
digits impaired performance.1 The selective attention measure was
normally distributed and therefore not subjected to a trans-
formation prior to parametric statistical analysis.

2.3.4. Cognitive control e selective attention task

To obtain a measure of cognitive control, the total number of
commission errors in the selective attention task was computed for
each child. These errors included responses to the first digit of the
Fig. 1. The Gordon Diagnostic System has an LED display upon which stimuli are
presented, and a large blue button for making responses. The red and green lights do
1
not provide feedback on performance, but only indicate whether a data collection This may be an underestimate of actual distractibility, as order of test admin-
session is ready to proceed or has terminated. (For interpretation of the references to istration was fixed and thus distractibility test performance may have been influ-
colour in this figure legend, the reader is referred to the web version of this article.) enced by a learning effect.
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98 M.W.G. Dye, P.C. Hauser / Hearing Research 309 (2014) 94e102

Table 2
Performance measures on (a) sustained attention and (b) selective attention forms
of the Gordon Diagnostic System continuous performance test.

Hearing Deaf

6e8 years 9e13 years 6e8 years 9e13 years

(a) Sustained attention

N 19 41 12 25
Mean (SD) sensitivity (dʹ) 3.47 (0.78) 4.36 (0.55) 3.18 (0.75) 4.09 (0.66)
Mean (SD) criterion (c) 0.59 (0.25) 0.45 (0.17) 0.51 (0.21) 0.37 (0.21)
Median (Range) 2 (0e12) 1 (0e11) 4 (0e28) 2 (0e20)
commission errors
Percentage with 68.4% 78.0% 54.5% 61.9%
commission
errors in normal range

(b) Selective attention

N 19 41 10 20
Mean (SD) sensitivity d’ 3.07 (0.90) 3.90 (0.76) 2.11 (1.15) 3.70 (0.87)
Mean (SD) criterion (c) 0.79 (0.27) 0.64 (0.21) 0.81 (0.48) 0.49 (0.20)
Median (Range) 2 (0e20) 2 (0e39) 10 (2e39) 5 (0e18)
commission errors
Percentage with 78.9% 90.2% 33.3% 50%
commission
errors in normal
range
Selective attention scorea 0.40 (0.76) 0.46 (0.68) 1.01 (0.91) 0.42 (0.91)
a
Computed as (sustained dʹ  selective dʹ).

children (M ¼ 4.26). In addition, boys (M ¼ 3.74) appeared to

display weaker sustained attention than girls (M ¼ 4.18). However,
no large differences were apparent between the performance of
deaf and hearing children, despite a sample size significantly larger
than that used in previous studies reporting sustained attention
differences on the basis of hearing status.
In order to assess these observations, log-transformed d-prime
scores from the sustained attention task were entered into a three-
Fig. 2. (A) Schematic representation of sustained attention task. Digits appeared one at way ANCOVA, with hearing status (hearing, deaf), age group (6e8
a time in the center of the LED display at a rate of one digit per second. The observer years, 9e13 years) and gender (female, male) as between subject
was required to respond to a target sequence (here, a 9 preceded by a 1), and withhold
factors, and SES as a covariate. This revealed significant main effects
responses to non-target sequences (here, a 9 preceded by a 6); (B) Schematic repre-
sentation of selective attention task. The central digit sequence is identical to that in of age group (F (1, 88) ¼ 31.14, p < .001, partial h2 ¼ 0.261) and
the sustained attention task. However, distractor digits appear to the left and right of gender (F (1, 88) ¼ 4.79, p ¼ .031, partial h2 ¼ 0.05). No other main
the LED display, sometimes concurrently with the central target. Dashed boxes indicate effects or interactions reached the criterion for statistical signifi-
the target stream, and were not visible to participants in the task. cance (all F < 1, except hearing status: F (1, 88) ¼ 1.59, p ¼ .211,
partial h2 ¼ 0.018). SES was not a significant covariate in the anal-
ysis (F (1, 88) ¼ 3.85, p ¼ .053, partial h2 ¼ 0.042).
target sequence (XX1 or X1X responses), or responses to the second
digit of the sequence (9) when it was not in a target sequence (XX9
and X9X responses). Errors that were considered to be due to a
delayed response (19X responses) were not included. Due to
experimenter error, commission error data for the selective atten-
tion task was not collected for 13 deaf children (four 6e8 year olds,
and nine 9e13 year olds). The number of commission errors was
compared to published norms (Gordon and Mettleman, 1987) in
order to determine the proportion of children in each group who
were normal or borderline-abnormal.

3. Results

For all statistical analyses, an alpha criterion of 0.05 was used to

determine statistical significance. All p-values reported below are
two-tailed and uncorrected for multiple comparisons unless
otherwise stated.

3.1. Sustained attention

Means and standard deviations for sustained attention perfor- Fig. 3. Number of commission errors made by each child during performance of the
mance are reported in Table 2. As expected, younger children sustained attention task. Solid lines indicate the median number of errors for each
(M ¼ 3.36) demonstrated poorer sustained attention than did older group.
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M.W.G. Dye, P.C. Hauser / Hearing Research 309 (2014) 94e102 99

3.2. Cognitive control (sustained attention task)

The number of commission errors was highly positively skewed

for the sustained attention task (see Table 2 and Fig. 3). In addition,
closer inspection of the data revealed that some deaf children made
an unusually large number of commission errors. Rather than
rejecting data as outliers, the number of commission errors for each
child was categorized as normal or abnormal-borderline, based
upon age norms published in Gordon and Mettleman (1987). Chi-
squared analyses revealed no differences in vigilance commission
error classification as a function of hearing status (c2 ¼ 2.41, df ¼ 1,
p ¼ .121) or age group (c2 ¼ 0.82, df ¼ 1, p ¼ .366).

3.3. Selective attention

Deaf 6e8 year olds (M ¼ 1.01) appeared less able to selectively

attend to the target stimulus stream than 9e13 year olds
(M ¼ 0.42), who had similar selective attention scores to hearing 9e
13 year olds (M ¼ 0.46; Table 2; Fig. 4). In order to confirm this
observation, selective attention scores were entered into a three- Fig. 4. Mean distractibility effect by hearing status and age group. Higher values
way ANCOVA, with hearing status (hearing, deaf), age group (6e8 indicate poorer selective attention (more distraction by task-irrelevant flankers). Error
years, 9e13 years) and gender (female, male) as between subject bars represent þ/ 1 S.E.M.
factors, and SES as a covariate. This revealed significant main effects
of age group (F (1, 81) ¼ 6.67, p ¼ .012) and gender (F (1, 81) ¼ 8.11,
p ¼ .006, partial h2 ¼ 0.091). The main effect of gender reflected abnormal for their age, suggesting weaker cognitive control in the
better selective attention for boys (M ¼ 0.35) than for girls selective attention task in deaf children (see Table 2 and Fig. 5).
(M ¼ 0.642). The main effect of age group was qualified by a sig-
nificant two-way interaction between hearing status and age group 4. Discussion
(F (1, 81) ¼ 6.59, p ¼ .012, partial h2 ¼ 0.075).
The main effect of hearing status was not statistically significant A cross-sectional sample of 6e13 year old hearing and deaf
(F (1, 81) ¼ 2.41, p ¼ .124, partial h2 ¼ 0.029), and nor were the two- children performed two versions of a visual CPT. The first assessed
way interactions between hearing status and gender (F (1, their ability to sustain attention over a 9 min time period. The
81) ¼ 2.64, p ¼ .108, partial h2 ¼ 0.032) and between age group and second measured the extent to which their attentional system was
gender (F (1, 81) ¼ 3.73, p ¼ .057, partial h2 ¼ 0.044). Finally, the able to ignore task-irrelevant stimuli in the near periphery e se-
three-way interaction between hearing status, age group and lective attention. Previous studies using such tests have led to the
gender was not statistically significant (F (1, 81) ¼ 2.40, p ¼ .125, suggestion that deaf children are inattentive, distractible, and
partial h2 ¼ 0.029). impulsive (Quittner et al., 1994; Smith et al., 1998; Yucel and Derim,
In order to unpack the two-way interaction between hearing 2008), or that they are unable to process sequences as well as
status and age group, separate ANOVAs were conducted for each hearing children (Horn et al., 2005). This has lent some support to
participant group. This revealed a significant effect of age group for deficit theories which propose that deaf children distribute their
deaf children (F (1, 25) ¼ 7.21, p ¼ .013, partial h2 ¼ 0.224) but not attention widely across the visual field in an unfocussed manner
for hearing children (F (1, 55) ¼ 0.001, p ¼ .982, partial h2 < 0.001), (Mitchell, 1996), or that they have impaired domain-general
confirming the poorer selective attention performance in deaf 6e8 sequencing skills (Conway et al., 2009). In this study, deaf
year old children.

3.4. Cognitive control (selective attention task)

The number of commission errors was also highly positively

skewed for the selective attention task. In addition, as for the sus-
tained attention task, closer inspection of the data revealed that
some deaf children made an unusually large number of commission
errors. Rather than rejecting data as outliers, the number of com-
mission errors for each child was again categorized as normal or
abnormal-borderline, based upon age norms published in Gordon
and Mettleman (1987).
For commission error classifications on the selective attention
task there was an effect of hearing status (c2 ¼ 16.75, df ¼ 1,
p < .001) but not age group (c2 ¼ 2.10, df ¼ 1, p ¼ .147). Deaf
children were more likely than hearing children to make enough
commission errors to be classified as abnormal or borderline

Fig. 5. Number of commission errors made by each child during performance of the
2
As this is a difference score, a higher value reflects greater distractibility in the selective attention task. Solid lines indicate the median number of errors for each
face of competing distractor digits. group.
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100 M.W.G. Dye, P.C. Hauser / Hearing Research 309 (2014) 94e102

children from Deaf families were recruited. Unlike deaf children attention or problems processing sequential or numerical infor-
who have hearing parents, deaf children from Deaf families are mation e the groups performed at similar levels on the sustained
exposed to their native language from birth, and are therefore likely attention task.
to achieve normal language development. We reasoned that if One hypothesis is that the younger deaf children struggle on this
auditory experience is important for the development of domain- task because of an inability to control the allocation of their visual
general abilities such as attention and sequence processing, then attention. Several studies have now shown that deaf individuals
these deaf children from Deaf families should demonstrate signif- have greater visual attention to the periphery than do hearing in-
icant impairment in those functions. dividuals (Buckley et al., 2010; Chen et al., 2006; Codina et al., 2011;
On the sustained attention task, the performance of deaf and Dye et al., 2007; Dye and Bavelier, 2010a; Dye et al., 2009b; Loke
hearing children was comparable across the age range tested, and Song, 1991; Proksch and Bavelier, 2002; Sladen et al., 2005).
despite a sample size larger than in previous studies that reported This neural plasticity can be seen as adaptive for an organism that
differences between deaf and hearing children in the same age must rely upon vision to monitor events in its periphery, and which
range. This indicates that there is no evidence to suggest sustained cannot use audition to locate events or interlocutors. However, to
attention deficits in deaf children born to Deaf parents who started be successful in navigating its environment, the organism must be
to acquire ASL in infancy as a first language. However, the addition able to employ the enhanced peripheral attention in a goal-directed
of task irrelevant stimuli to the left and right of the target sequence manner. It is possible that, by the age of 9e13 years, deaf children
location (the selective attention task) was particularly disruptive have enhanced attention to their peripheral visual field (relative to
for the younger deaf children, for whom task-irrelevant stimuli in hearing peers). However they can inhibit that process when a task
the near periphery were more likely to impair performance. In the requires attention to the central visual field and the processing of
selective attention task, deaf children also demonstrated a greater peripheral visual stimuli is detrimental to performance. The fronto-
tendency to make impulsive responses - responding either pre- parietal cognitive control network has been shown to improve
emptively to the first digit of a two-digit sequence, or responding to across the age range tested here (Fair et al., 2007; Hwang et al.,
the second digit when the preceding digit was not part of the target 2010; Wendelken et al., 2011). On the other hand, 6e8 year olds
sequence. This weaker cognitive control was particularly evident in combine the enhanced peripheral attention with an inability to
6e8 year old deaf children. selectively attend to the central visual field and ignore the pe-
riphery when the task requires them to do so. In other words, the
4.1. Sustained attention neuroplastic changes that shape the spatial allocation of visual
attention interact with the development of inhibitory processes
The failure to replicate previous findings on sustained attention and other executive functions to determine performance.
may be indicative of the important role language plays in the
shaping of attentional processes. Indeed, poor performance on this 4.3. Cognitive control
form of CPT has been reported in hearing children with specific
language impairments (Ebert and Kohnert, 2011; Finneran et al., Deaf children appeared to demonstrate weaker cognitive con-
2009; Spaulding et al., 2008) and children with poor social inter- trol than the hearing children. This was only observed for the se-
action skills such as those with autism (Corbett and Constantine, lective attention task, where only 33.3% of deaf 6e8 year olds and
2006; Garretson et al., 1990). Both spoken and signed interactions 50% of deaf 9e13 year olds performed within the range considered
typically require sustained joint attention with the sender, and typical for hearing children. The fact that cognitive control was
caregivers are known to shape the attentional behaviors and gaze similar for hearing and deaf children in the vigilance test suggests
direction of their infants during interactions (Chavajay and Rogoff, caution in considering the deaf children to be more impulsive per
1999; Loots and Devisé, 2003). This raises the possibility that pre- se. The relatively large number of commission errors seen in these
vious demonstrations of apparent inattentiveness in deaf children children may be, at least in part, driven by an inability to ignore the
may reflect poor early communicative environments, and delays in distractor digits in their near periphery due to enhanced peripheral
the acquisition of language needed to support those interactions. visual attention. This may particularly be the case for the younger
None of the children recruited in previous studies had deaf parents, deaf children.
and none had been exposed to a natural signed language, such as
ASL, from infancy. Indeed, the improvements in sustained attention 4.4. Limitations
performance seen in young deaf children with CIs (Horn et al.,
2005) may reflect increased communicative and linguistic While there is no reason to believe that the IQ of the kind of deaf
competence afforded by the implant and speech-listening training, children enrolled in the study would be different from that of
rather than remediation of hearing loss per se. If this is the case, hearing children, this cannot be ruled out conclusively. However,
then it further suggests clinical benefit from early implantation as none of the deaf children in this study were reported to have lin-
well as early introduction of natural language e either spoken or guistic or cognitive disabilities, and all were exposed to natural
signed. language from birth. Racial and ethnic factors could also have
played a role in the pattern of data observed. The deaf sample was
4.2. Selective attention exclusively white Caucasian, with some Hispanic children included,
whereas the hearing sample had greater racial diversity and fewer
The younger deaf children performed very poorly on the se- Hispanic children (see Table 2). However, race and ethnicity were
lective attention task e poorer than their hearing peers of similar well matched across age groups in the sample of deaf children, and
age. However, in 9e13 year olds, these differences were no longer thus unlikely to explain any age group differences within the
evident. Importantly, these older deaf children were similar to the sample of deaf children.
younger children, in that none had received a CI, all were re- Where there does appear to be a systematic difference between
ported to have severe-to-profound hearing losses, and all the deaf and hearing is in their language background. Whereas the
preferred to receive test instructions in ASL. Furthermore, the vast majority of the hearing children were monolingual English
selective attention differences between deaf and hearing children speakers, several of the deaf children were reported to be fluent in
at 6e8 years of age could not be attributed to weaker sustained ASL and English. Indeed, perhaps unsurprisingly, the older deaf
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M.W.G. Dye, P.C. Hauser / Hearing Research 309 (2014) 94e102 101

children were more likely to be bilingual than the younger deaf put forward a similar argument from the perspective of research on
children. An alternative interpretation, therefore, is that a lack of children with autism and ADHD. Many studies have reported an
audition impairs performance on these tasks, but cognitive benefits enhanced ability to attend to the visual periphery following early,
stemming from sign-print bilingualism offset this impairment in profound deafness. However, little is known about how a deaf child
older deaf children. It has been suggested that bilingualism has an is able to endogenously control this ability in a task-driven manner.
effect on executive function skills (Barac and Bialystock, 2012). Thus, the development of fronto-parietal attentional networks is
Interestingly, however, it remains unclear whether such advantages likely to interact with cross-modal changes in the visual dorsal
accrue to sign-print bilinguals in the same way (Emmorey et al., stream to produce a different developmental time course for
2008; Kushalnagar et al., 2010), and it has been reported that any attentional behavior in the deaf child. Longitudinal studies that
bilingual advantages may not generalize to measures of impulse combine behavioral assessment with structural and functional
control (Carlson and Meltzoff, 2008). This study cannot address neuroimaging have the potential to shed light on how these neural
these issues as we did not collect measures of language proficiency systems develop and interact across the school-aged years.
across the necessary domains; for now an effect of bilingualism is
purely speculative. Further research is required, alongside more Acknowledgments
detailed characterization of the multilingual abilities of deaf chil-
dren in bilingual-bicultural settings. This research was supported by NSF awards SBE-0541953 and
SBE-1041725 to the Science of Learning Center on Visual Language
5. Conclusions and Visual Learning at Gallaudet University, and grant NIDCD R01
DC004418 to Daphne Bavelier and PH. We wish to thank Geo Kar-
Previous research has suggested that deaf children suffer from theiser, Rupert Dubler, Kim Scanlon, and Dani Hagemann for
elevated inattentiveness, distractibility, and impulsiveness. We recruitment and data collection efforts.
sought to extend and refine that research by testing deaf children
born to Deaf parents from whom they acquired ASL as a first lan-
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