Read the following three research articles and complete written response to the readings. Write a page and a half synthesis of the three articles plus 1 discussion question per article.

The following factors will be considered in grading: relevance, accuracy, synthetization of the reading materials, degree to which the responses show understanding/comprehension of the material, and quality of writing.  

· Questions must be original, thoughtful and not easily found in the readings.

· Quality of Synthesis

· Follows APA Rules

· Use proper citations 

· Use past tense when discussing the studies (the research was already conducted).

· Avoid the use of the following words: me, you, I, we, prove, proof

· Refer to the articles by their authors (year of publication) (not by the title of the article or the words first, second, or third)

· Do not just summarize the articles. Dig deeper!


Two Factor Model of ASD Symptoms

One of the key factors in determining whether an individual has Autism Spectrum Disorder (ASD) is in their social and communication skills. Individuals who are diagnosed with ASD have delayed joint attention, eye gazing, and other social interactions such as pointing (Swain et al., 2014).

Joint attention is an important social skill to master because it is a building block for developing theory of mind which, helps us to understand other’s perspectives. Korhonen et al. (2014) found that individuals with autism have impaired joint attention. However, some did not show impairment in joint attention, which lead to evidence that suggests there are different trajectories for joint attention. One suggestion as to why Korhonen et al. (2014) found mixed results, is that there is evidence that joint attention may not be directly linked to individuals with ASD since they were unable to find a difference in joint attention between ASD and developmentally delayed (DD) individuals. Another suggestion for the mixed results, is individual interest in the task vary. Research has found that while individualized studies are beneficial in detecting personal potential and abilities, it would be difficult to generalize the study in order to further research to ASD as a whole (Korhonen et al., 2014). In addition to joint attention, atypical gaze shifts is a distinguishing factor in individuals with ASD. Swain et al. (2014) found the main difference between typically developing (TD) and ASD individuals in the first 12 months of life is in gaze shifts. Individuals that were diagnosed with ASD earlier had lower scores on positive affect, joint attention, and gaze shifts, however those diagnosed later differed from typically developing (TD) only in gaze shifts. It is not until 24 months that later onset ASD individuals significantly differ from their TD peers, by displaying lower positive affect and gestures (Swain et al., 2014). These findings may lead to other ASD trajectories.

Another defining characteristic of ASD is the excess of restrictive patterns of interest and repetitive motor movements. These patterns and movements often impaired the individual from completing daily tasks. Like joint attention and gaze shifts, these repetitive movements and patterns of interest have different trajectories (Joseph et al., 2013). Joseph et al. (2013) found that individuals with high cognitive functioning ASD engage in more distinct and specific interests and less in repetitive motor movements than individuals with lower cognitive functioning ASD. Another finding showed that at the age of two, repetitive motor and play patterns were more common than compulsion. By the age of four all these behaviors increased however, repetitive use of specific objects was found to be less frequent in older children than younger children. This finding suggests that the ritualistic behaviors and motor movements may present themselves differently based on the age of the individual (Joseph et al., 2013).

Joseph et al. (2013), Korhornen et al. (2014), and Swain et al. (2014) all defined key characteristics of an ASD individual and explains the different trajectories of each characteristic. The difficulty with the trajectories is that it is specific to each individual, some symptoms may worsen while others remain stable. It is also difficult to generalize finding with small sample sizes (Joseph et al., 2013).

Discussion Questions:

1. Korhonen et al. (2014) did not use preference-based stimuli to look for joint attention and did not separate high- from low-functioning ASD individuals. Do you think that there could be a difference in level of motivation from each group? If so, how do you think this could change the results?

2. Swain et al. (2014) found that early and late onset of ASD did not differ in their social skills scores at the age of 12 months. If we know that their social skills do not differ then, is there another factor that would allow diagnosis of late onset ASD to be diagnosed at an earlier point in development?

3. Joseph et al. (2013) explains that it is difficult to assess the trajectories of ASD with a small sample size however, how do you think that their findings still help advance the research on ASD?


CURRENTOPINION Autism spectrum disorder in infancy: developmental
considerations in treatment targets


1350-7540 Copyright � 2015 Wolte

a b c

Jessica A. Brian , Susan E. Bryson , and Lonnie Zwaigenbaum

Purpose of review

This review explores recent literature to prioritize aspects of development to be targeted by intervention for
infants and toddlers with autism spectrum disorder (ASD).

Recent findings

Recent investigation of early development in ASD, including prospective studies of infants at increased risk
(i.e., those with an affected older sibling) identifies impairments in four key developmental domains that are
predictive of ASD. These domains are early attentional control, emotion regulation, social orienting/
approach, and communication development. Reciprocal relationships exist among these domains, both in
ASD and in typical development. Thus, these domains represent key intervention targets, informing
treatment models under investigation in recent clinical trials.


By targeting the earliest and foundational manifestations of atypical development, we can capitalize on
neural plasticity and build skills that are most likely to have scaffolding effects on development. The optimal
timing and procedures of intervention remain empirical questions, but as the field moves toward earlier
identification of risk, we are now poised to evaluate the impact of tailored approaches before the
developmental cascade that leads to ASD is fully manifested. Consideration regarding community
translation of ASD-specific interventions for infants and toddlers is also needed, with a focus on feasibility,
cost-effectiveness, and sustainability.


attention, autism, communication, early intervention, emotion regulation

aBloorview Research Institute, University of Toronto, Ontario,
bDepartments of Pediatrics and Psychology, Dalhousie University, Halifax
and cDepartment of Pediatrics, University of Alberta, Edmonton, Canada

Correspondence to Dr Jessica A. Brian, Bloorview Research Institute,
150 Kilgour Rd, Toronto, Ontaio M4G 1R8, Canada. Tel: +1 416 425
6220 x3716; fax: +1 416 422 7045; e-mail: [email protected]

Curr Opin Neurol 2015, 28:117–123



Remarkable progress has been made in early detec-
tion and diagnosis of autism spectrum disorder
(ASD), particularly in high-risk samples (e.g.,
younger siblings of children with ASD; see [1


for a recent review). This, in turn, has highlighted
the need for developmentally appropriate interven-
tion for infants and toddlers with suspected or diag-
nosed ASD. Information on the nature and efficacy
of such interventions is beginning to emerge [2–4].
However, to date there has been little discussion of
what should constitute the main targets of inter-
vention, and why. Knowing that resources are
limited and time is precious, it is critical to focus
on targets that yield the greatest benefits. Such
endeavors are limited by current knowledge about
early development of ASD, and therefore should be
considered ‘moving targets’ to be refined as knowl-
edge accumulates. Nonetheless, we argue that a
focus on empirically and theoretically relevant
targets (and associated outcomes) is warranted. This
approach differs from that traditionally adopted in

ht © 2015 Wolters Kluwe

rs Kluwer Health, Inc. All rights rese

intervention for preschoolers with ASD, wherein the
focus has been on the model or techniques adopted
(i.e., applied behavior analysis, naturalistic and/or
developmental), and on the intensity of interven-
tion. Although our choice of key targets depends
heavily on normative development, our operating
assumption is that all of these approaches have
merits, and thus an integrated model of interven-
tion is warranted.

We begin by identifying early signs of ASD that
might serve as intervention targets. Then, upon
considering the relative precedence and putative
benefits of each to overall development, we argue

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� Prospective, longitudinal studies of high-risk infants
indicate early impairments in four broad domains of
development that are predictive of ASD: sensory-motor,
attentional, social-emotional, and communication.

� We argue for reciprocal relationships among early
attentional control, emotion regulation, social
orienting/approach, and early communication
development in the emergence of ASD.

� With the goal of optimizing development as efficiently
as possible, we propose that very early intervention
should target attentional control, positive effect, social
orienting/engagement, and communication.

� By targeting the earliest and foundational
manifestations of atypical development, we can
capitalize on neural plasticity and build skills that are
most likely to have scaffolding effects on development.

� As the field moves toward earlier identification of risk,
we are now poised to evaluate the impact of tailored
interventions before the developmental cascade that
leads to ASD is fully manifested.

Developmental disorders

for the importance of some over others (i.e., ‘key
targets’). This analysis considers potential ramifica-
tions of very early intervention for both psychologi-
cal and neurological development in ASD. Finally,
we conclude by discussing approaches and tech-
niques that might be most effective in enhancing
key target skills. With an eye to community trans-
lation of ASD-specific interventions, we end by
discussing practical issues related to feasibility,
cost-effectiveness, and sustainability.

Prospective, longitudinal studies of high-risk infants
indicate that early impairments in four broad
domains of development – sensory-motor, atten-
tion, social-emotional, and communication – are
predictive of later ASD diagnoses. Atypical develop-
ment in each of these domains has the potential to
disrupt early interactions with the social and non-
social world, with cascading effects as development
unfolds. As the field moves toward ever earlier
detection of ASD risk, we are afforded the opportu-
nity for earlier intervention, possibly before the full-
blown syndrome has emerged and associated dys-
functional neural pathways become engrained.

Sensory-motor development
Although relatively little is known about sensory-
motor development in infants with ASD, early

Copyright © 2015 Wolters Kluwer


differences have been reported based on retrospec-
tive video review in the first year of life [5,6]. Pro-
spective findings from high-risk infants include
reduced motor activity [7], delayed motor mile-
stones or atypical developmental trajectories
[8–10], unusual mannerisms/repetitive behaviors,
and various sensory sensitivities or interests
[11 –14]. Atypical visual exploration of toys (and
spinning and rotating) has been demonstrated as
young as 12 months in infants later diagnosed with
ASD [15]. In a study of grasping behavior, the com-
ponent process, starting at 12 months, that distin-
guished high-risk infants later diagnosed with ASD,
was difficulty in disengaging visual attention from
the object to be grasped [16]. Subtle motor delays
and sensory issues have been reported as early as
6 months in babies later diagnosed with ASD (e.g.,
reduced motor control [11,15], protracted head lag

To date, the sensory-motor domain has not been
addressed specifically in infant and toddler interven-
tions for ASD, although its potential importance is
underscored by theoretical links between sensory-
motor and cognitive development [18,19]. Based
on recent findings [16], interventions aimed at
improving coordination of movement with atten-
tion (e.g., reaching/grasping with coordinated eye
gaze to an object) may be beneficial, although the
impact of such strategies in infancy has yet to be
systematically evaluated.


Deficits in attentional control, and related influences
on emotion regulation, may play a central role in the
emergence of ASD. The ability to disengage attention,
which typically develops by 4–6 months, allows
infants to move attention away from arousing events,
and thereby to regulate their state [20]. Attention is
largely reflexive (or involuntary) early in life, but
toward the end of the first year, voluntary, or exec-
utive, control over visual attention emerges, at which
point emotion regulation also improves [21,22]. A
selective deficit in attentional disengagement is
well documented in ASD [23,24


,25] and has been
demonstrated by age 12 months in high-risk infants
later diagnosed with ASD [26


,27]. The relative
absence of attentional control might explain the
intense, prolonged negative emotional states and
reduced social approach reported in infants later
diagnosed with ASD [28] (S.E. Bryson, N. Garon, T.
McMullen, et al., unpublished observation). Dimin-
ished attentional control and difficulty regulating
emotional state may together negatively impact
social approach and reduce infants’ opportunities
to experience positive associations from interactions

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Volume 28 � Number 2 � April 2015

Autism spectrum disorder in infancy Brian et al.

with caregivers. Impaired attentional disengagement
may also impact the development of other important
functions, including joint attention and early recep-
tive language (S.E. Bryson, N. Garon, T. McMullen,
et al., unpublished observation). Schietecatte et al.
[29] have demonstrated a relationship between atten-
tional disengagement and initiating joint attention
in 3-year olds with ASD; disengagement from an
object of interest is arguably necessary to move atten-
tion to a person. As well, early language acquisition
requires flexible attention to objects or events to
which others are referring when using linguistic
terms. We thus argue for reciprocal relationships
among early attentional control, emotion regulation,
social orienting/approach, and early communication
development in the emergence of ASD (cf, [30]).

Deficits in attentional control have yet to be
targeted systematically in any known infant/toddler
interventions for ASD, although recent work with
symptomatic high-risk infants as young as 9 months
has begun to encompass attention and engagement
[2]. Fostering attentional control will likely be best
addressed via both structured and naturalistic inter-
vention methods. Wass et al. [31] have successfully
used a series of computerized gaze-contingent
orienting tasks with typically developing 11-month
olds, with evidence of enhanced cognitive control,
sustained attention, and attentional disengage-
ment. Attention-training programs such as this
clearly hold promise for use with high-risk infants.
However, given documented challenges generaliz-
ing from contrived to real-world situations in ASD
[32], the inclusion of training in a naturalistic con-
text may be a critical addition. Gains in attentional
control could lead to downstream effects on
emotion regulation, social engagement, and joint
attention, which in turn might further foster com-
munication development.

Social-emotional development
Early social-emotional deficits in ASD include
reduced positive affect and reciprocal social smiling,
reduced social orienting, and atypical face process-

Positive facial affect (i.e., smiling) is thought to
have innate hedonic value that serves to motivate
the development of very early social-communi-
cation skills such as eye gaze and reciprocal social
smiling [33 –35]. These very early interactions are
also essential to the development of the emotional
connectedness (or inter-subjectivity) required for
understanding others, which is impaired in ASD
[36 –38]. The putative significance of shared positive
emotion to subsequent communicative and social
development, together with converging evidence of
its early impairment in ASD, argues for targeted

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interventions. Reduced facial expressiveness,
particularly smiling, is well documented in pre-
schoolers with ASD [39,40], and reduced smiling
has been reported by 12–18 months in infants sub-
sequently diagnosed with ASD [7,10,12,41], but not
earlier (e.g., [42]). The possibility remains that
diminished social smiling is a consequence of earlier
deficits in orienting to others.

Early home videos of infants later diagnosed
with ASD initially revealed reduced social orienting
toward the end of the first year of life [5,43]. Evi-
dence of even earlier deficits in attention to faces
comes from high-risk samples, although discrepan-
cies exist as to the timing of its emergence, the
specific facial regions involved, and even specificity
to ASD. Some studies fail to find group differences
until 12 or 18 months [10,44], whereas others
have reported differences as early as 6 months [45].
Chawarska et al. [45] reported reduced attention to a
video-displayed static face in 6-month-old infants
later diagnosed with ASD; however, diminished
attention to the video screen also distinguished
this group, suggesting that attentional control may
be the more primary issue. Selective deficits in
orienting to faces have not been replicated consist-
ently in experimental paradigms. For example,
Elsabbagh et al. [46] did not report a difference in
looking time toward eyes of static faces between
low-risk controls and high-risk infants (including
those later diagnosed with ASD) at 6–10 months,
although there were differences in evoked responses
related to ASD outcome. In a related study, high-risk
infants (aged 6�10 and 12�15 months) were shown
displays containing faces and nonsocial stimuli. This
task also failed to distinguish infants who went on to
have ASD [44]. Instead, a nonspecific effect emerged,
whereby high-risk infants (regardless of ASD out-
come) spent marginally more time looking at faces
and less time sampling other items in the visual
display. Based on infants’ eye gaze while watching
videos of actors looking directly into the camera and
making age-appropriate social overtures, Jones
and Klin [47] reported a declining trajectory of
eye-looking time in high-risk infants later diagnosed
with ASD relative to high-risk and low-risk controls
beginning at 2 months of age, although cross-
sectional differences were not detectable until
9 months of age. This body of work highlights the
importance of controlling carefully for stimulus
characteristics such as face region assessed and the
nature of the display (dynamic vs. static). It also
remains possible that other features can account
for differences in looking time. For example, one
possibility is that motion is the critical variable in
observed differences between response to eyes and
mouths in dynamic displays.

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rved. 119

Developmental disorders

Thus, despite early evidence of reduced social
orienting in ASD, findings remain somewhat incon-
sistent when examined experimentally in very
young babies. Further research is needed to more
fully understand the nature, timing, and specificity
of this phenomenon. Moreover, competing views
remain as to the primacy of a basic attentional vs.
social interpretation of atypical social orienting in
ASD. Elsabbagh et al. [44] interpret their findings as
evidence of deficient attentional control, conclud-
ing that ‘cortical mechanisms mediating efficient
selection and distribution of attention appear to
modulate infants’ early responses to faces’
(p. 153). Nonetheless, both basic attention and
social orienting deficits appear to index early-
developing challenges in brain and behavioral func-
tioning, which may, at a minimum, interact in a
cascading manner to contribute to ASD outcomes.
As such, both can be argued to be critical targets for
intervention in infants and young toddlers with
emerging ASD.

Interventions aimed at fostering early social-
emotional development in ASD may need to focus
first on increasing child orienting to a social partner
and parent responsiveness [4,48]. Some existing
parent- or teacher-mediated approaches with tod-
dlers have yielded gains related to social orienting
or engagement [49 –51]. Through increased social
orienting, opportunities arise to foster positive
affect sharing through approaches that capitalize
on the child’s motivation and interests, and on
building positive, reciprocal interactions with social
partners. Moreover, given the relationship between
positive affect and both learning in general [52], and
social engagement specifically [35,53], learning may
be enhanced by targeting positive affect directly.
Whether this is accomplished best by directly
targeting child and/or caregiver smiling (e.g., via
parent-mediated interventions) remains an empiri-
cal question, but evidence suggests that this is best
accomplished through the use of naturalistic behav-
ioral procedures that capitalize on the child’s motiv-
ation, such as those of Pivotal Response Training


Early communication differences in ASD include
reduced nonverbal and verbal communication such
as lack of eye gaze and pointing to share interest (i.e.,
joint attention), diminished use of gestures, reduced
babbling and reduplication, delayed receptive
word learning, and few if any words used mean-
ingfully [1



]. Most communication deficits are
not clearly apparent until the end of the first
year and usually manifest as the absence of typical

Copyright © 2015 Wolters Kluwer


development (vs. deviance, which tends to emerge
later; e.g., idiosyncratic or repetitive language in the
second year).

Impairments in joint attention are well docu-
mented in ASD [29,56,57]. Because joint attention
typically develops within the first year, this has been
an area of considerable interest in early ASD detec-
tion research [58 –61]. However, despite the widely
held view that joint attention deficits are universal
in ASD, variances in task demands can yield differ-
ent effects. An intriguing phenomenon highlighted
by Jones et al. in their review [1


] is that orienting to
a proximal target may be relatively less impaired in
ASD than orienting to a more distal target. They
posit that joint attention to near objects may occur
via reflexive orienting mechanisms, whereas distal
orienting may require greater motivation and
understanding of the referential nature of the
orienting cue. Selective deficits in distal orienting
are consistent with an attentional interpretation
whereby executive, or voluntary, control of atten-
tion is needed for distal, but not more proximal (i.e.,
reflexive), orienting.

Some of the earliest communication impair-
ments in ASD may emerge in response to deficits
in attentional control and its impact on skills like
joint attention. However, regardless of whether
communication deficits are primary or at least par-
tially secondary to more basic deficits in attention,
communication development (including within the
context of overall intelligence [62]) has taken pre-
cedence as a target in ASD-specific interventions for
toddlers, for several reasons. First, communication
deficits remain among the most easily detected first
signs in clinical contexts, leading to the bulk of
referrals for assessment. Moreover, communication
may be viewed as a key target because it lays the
foundation for meaningful interactions with care-
givers and others, prevents or reduces behavioral
agitation, and remains the best predictor of positive
outcomes in ASD [63].

As the next generation of infant intervention
programs are developed, the challenge will be to
design strategies that address the earliest manifes-
tations of communicative deficits in ASD. These will
ideally include methods for fostering nonverbal
communicative acts such as eye-to-eye gaze, gesture
use, and functional vocal output, prior to the devel-
opment of verbal language. Such skills will be most
appropriately taught in naturalistic contexts,
capitalizing on highly motivating interactions
and social routines (thereby optimizing positive
effective states), with tight, but developmentally
appropriate contingencies between the babies’
communicative acts and responses from communi-
cation partners (e.g., primary caregiver, therapist).

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Volume 28 � Number 2 � April 2015

Autism spectrum disorder in infancy Brian et al.

Evidence is beginning to emerge regarding the effi-
cacy of such strategies used with infants in the first
year of life [2], revealing that such interventions
have the potential to positively affect outcomes in
a meaningful way.


Although several systems have been implicated,
findings on early development in ASD most consist-
ently point to poor attentional control, reduced
positive emotion, and delayed nonverbal and verbal
communication skills, atypical development in any
of which has the potential to disrupt early inter-
actions with the world, contributing to cascading
effects as development unfolds. Findings on social
orienting and attention to faces are less consistent,
especially with respect to timing, but important,
given the nature of the social challenges in ASD.
With the goal of optimizing development as effi-
ciently as possible, we thus suggest that very early
intervention should target attentional control,
social orienting/engagement, positive affect, and
communication. By targeting the earliest and
foundational manifestations of atypical develop-
ment, we can capitalize on neural plasticity
[64,65] and build skills that are most likely to have
scaffolding effects on development. Evidence dis-
cussed above also implicates complex interactions
between the earliest-developing deficits in ASD,
highlighting the potential for wide-reaching,
collateral effects of intervening in key domains.
The optimal timing and procedures of intervention
in these domains remain empirical questions,
but as the field moves toward earlier identification
of risk, we are now poised to evaluate the impact of
tailored interventions before the developmental
cascade that leads to ASD has the opportunity to
take hold.


Given current prevalence [66], future intervention
efforts must focus on community translation of
ASD-specific interventions, with a focus on feasible,
cost-effective, and sustainable programs. Current
evidence supports the efficacy of resource-intensive
(i.e., 1 : 1), comprehensive, behaviorally based
approaches for use with preschoolers [67]. As we
move to earlier, publicly funded models, creative
approaches are needed to maintain efficacy with
more children in need and fewer resources.
Parent-mediated approaches that capitalize on the
principles of applied behavior analysis as well as
those of naturalistic learning are gaining traction

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with infants and toddlers [3], often with a focus on
child-directed and highly motivating activities.
These are appealing because they are a natural fit
for this age group, and because they afford the
opportunity for intensive intervention by teaching
parents skills that can be integrated into everyday
caregiving interactions. By identifying key targets
that are likely to have collateral effects on multiple
domains and by capitalizing on evidence-based
intervention methods, we will be poised to deliver
efficient and effective intervention very early in
development in a sustainable way.


Evidence from high-risk longitudinal cohorts
indicates that atypical development may first appear
in the sensory-motor system, with deficits in atten-
tional control by the latter part of the first year. Such
deficits are associated with concomitant impair-
ments in emotion regulation, possibly affecting
social approach and joint attention, and negatively
impacting the development of positive associations
required to fuel the social reward system [68].
Moreover, basic deficits in attentional control
may result in reduced social orienting, also nega-
tively affecting infants’ opportunities to learn from
and about social partners. Deficits in attentional
control may also impact important foundational
social communicative interactions such as joint
attention and affect sharing. Mounting evidence
points to a cascading effect of these differences over
the first year of life and into the second year. By
carefully considering the nature by which these
differences unfold, we have the opportunity to
develop very early interventions targeted to key
processes that have the potential to have a scaffold-
ing influence on development. Intervention at
the earliest possible time points, if appropriately
targeted, has the potential for significant down-
stream effects including secondary prevention of
suboptimal outcomes.



Financial support and sponsorship

Our research is supported by the Canadian Institutes of
Health Research, Autism Speaks Canada, the Simons
Foundation, the Sinneave Family Foundation and
NeuroDevNet. L.Z. is supported by the Stollery Child-
ren’s Hospital Foundation Chair in Autism.

Conflicts of interest

There are no conflicts of interest.

r Health, Inc. All rights reserved.

rved. 121

Developmental disorders

Papers of particular interest, published within the annual period of review, have
been highlighted as:

& of special interest
&& of outstanding interest


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after. Annu Rev …


CURRENTOPINION Motor development and delay: advances
in assessment of motor skills in autism
spectrum disorders


a b b

Rujuta B. Wilson , Peter G. Enticott , and Nicole J. Rinehart

Purpose of review

Motor impairments in neurodevelopmental disorders, specifically autism spectrum disorder (ASD), are
prevalent and pervasive. Moreover, motor impairments may be the first sign of atypical development in
ASD and likely contribute to abnormalities in social communication. However, measurement of motor
function in ASD has lagged behind other behavioral phenotyping. Quantitative and neurodiagnostic
measures of motor function can help identify specific motor impairments in ASD and the underlying neural
mechanisms that might be implicated. These findings can serve as markers of early diagnosis, clinical
stratification, and treatment targets.

Recent findings

Here, we briefly review recent studies on the importance of motor function to other developmental domains
in ASD. We then highlight studies that have applied quantitative and neurodiagnostic measures to better
measure motor impairments in ASD and the neural mechanisms that may contribute to these abnormalities.


Information from advanced quantitative and neurodiagnostic methods of motor function contribute to a
better understanding of the specific and subtle motor impairments in ASD, and the relationship of motor
function to language and social development. Greater utilization of these methods can assist with early
diagnosis and development of targeted interventions. However, there remains a need to utilize these
approaches in children with neurodevelopmental disorders across a developmental trajectory and with
varying levels of cognitive function.


autism spectrum disorder, motor control, motor function


aUCLA Semel Institute of Neuroscience and Human Behavior, David
Geffen School of Medicine, UCLA Division of Pediatric Neurology, Los
Angeles, California, USA and bDeakin Child Study Centre, School of
Psychology, Faculty of Health, Deakin University, Geelong, Victoria,

Correspondence to Rujuta B. Wilson, MD, 760 Westwood Plaza, Room
A7-420, Los Angeles, CA 90095, USA. Tel: +1 310 825 1746;
fax: +1 310 206 4245; e-mail: [email protected]

Curr Opin Neurol 2018, 31:134–139



The development of the motor system is critical for an
individual to engage with the environment. As a
child gains the ability to crawl, point, and ambulate,
new opportunities arise for social interactions with
caregivers and peers [1]. Neurodevelopmental disor-
ders (NDDs) are a heterogeneous group of conditions
that are characterized by delays or abnormalities in a
variety of developmental domains, including delays
in motor skills [Diagnostic and Statistical Manual of
Mental Disorders Fifth Edition (DSM-5)]. Within the
group of NDDs, autism spectrum disorder (ASD) is
diagnosed based on core impairments in social com-
munication skills. However, motor impairments are
particularly prevalent in ASD, and they can be the
first sign of atypical development [2,3]. With advan-
ces in genetic testing, there has also been an increased
identification of copy number variants and single
gene disorders that confer elevated risk for ASD

© 2018 Wolters Kluwer

[4,5 ]. Motor impairments are often the first sign
of abnormal development in these genetic variants
and may be more common in children with syn-
dromic forms of ASD [5


,6]. Thus, the identification
of early motor delays might be indicative of an indi-
vidual at higher risk for a genetic disorder. Despite
their clinical relevance, quantification of motor skills
in ASD has been hampered by the use of standardized

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Volume 31 � Number 2 � April 2018


� Motor impairments are prevalent in autism spectrum
disorder and are related to overall development.

� Quantitative measures of motor function can aid in
identifying specific and subtle motor impairments
in ASD.

� Neurodiagnostic measures of motor function can better
elucidate aberrant underlying neural mechanisms
contributing to motor impairments in ASD.

� Early identification of motor impairments in ASD can
aid in early intervention and improved long term

Autism spectrum disorders Wilson et al.

assessments that mostly capture developmental mile-
stones and rely on an individual’s ability to under-
stand complex tasks [7,8]. These assessments often
lead to results that do not adequately capture a child’s
motor abilities or impairments. This has led research-
ers to develop and utilize quantitative measures of
motor function to better identify motor impairments
in ASD to aid in earlier diagnosis and development of
individualized interventions. In this review, we
briefly discuss new findings on the relationship
between motor skills, core ASD features, and cogni-
tive function, and then review recent advances in
quantitative and measures of motor function in ASD.


The development of motor function is linked to a
child’s capacity for language, cognitive, and social
development, and may serve as an indication of emer-
gent developmental psychopathology [1,9]. Retro-
spective studies of infants at high risk for ASD or
with a confirmed diagnosis of ASD report the emer-
gence of motor impairments before the more salient
social-communicative impairment has been formally
diagnosed. It is well accepted that early emergence of
motor impairments has a downstream impact on key
aspects of social and communicative development, for
example, impairing a child’s ability to gesture, and
interact with other children in play [1,2,10].

Longitudinal studies reveal that the connection
between motor, language, and higher-level cogni-
tive impairment continues into childhood. In the
school-age period, when children may experience
higher developmental demands, studies have
shown a relationship between motor impairments
and disturbances in emotional and behavioral func-
tioning, as measured on the Developmental Behav-
ior Checklist. One explanation for this association is

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that children who experience greater motor prob-
lems may experience more adverse life events, for
example, being excluded from school yard games
and more trouble with academic tasks such as hand-
writing, thus leading to the higher levels of psycho-
pathology [11].

A recent study on high-risk infant siblings
(defined by having a sibling with ASD) examined
whether advances in sitting, and also prone loco-
motion, are related to communicative development


]. This longitudinal study included 37 high-risk
infants, with gross motor skills assessed at monthly
intervals from 5 to 14 months using the Alberta
Infant Motor Scale (AIMS), which is a standardized
observational measure of prone postures utilized in
sitting and locomotion [13]. The age of onset of
verbal and nonverbal communication was also
recorded. Motor delays were observed across all
observations, with the majority of participants
exhibiting delays by 5 and 6 months of age. Motor
development recorded monthly on the AIMS was
related to emergence of both verbal and nonverbal
communicative milestones. As the authors hypoth-
esized, the ability to sit unsupported relates to both
verbal (reduplicative babbling) and nonverbal com-
munication (show gesture onset), whereas prone
locomotion related to nonverbal communication
milestones (show and point gesture). The authors
state that acquiring independent sitting increases
the use of manual movements to engage with people
and also allows an infant to coordinate behaviors,
such as eye contact with multiple individuals [12


Therefore, in addition to the relationship of motor
skills with other domains (such as language and
communication), developments in gross motor
skills can serve as the building blocks for more
complex social and behavioral interactions. More-
over, there can be lifelong implications if motor
development is disrupted.

Another study that evaluated high-risk infant
siblings (defined as having a sibling with ASD)
examined the relationship between motor skills
and executive functioning, which is a set of
higher-level cognitive functions including atten-
tion, working memory, and planning. This study
compared the relationship of motor skills and exec-
utive functioning in high-risk infants (both those
who went on to receive an ASD diagnosis and those
who did not) and low-risk infants (defined as a child
without a sibling or family history of ASD) at 12 and
24 months of age. Motor function was assessed using
the Mullen Scales of Early Learning (MSEL) – a
standardized measure of cognitive development
for children from birth to 68 months [14]. Although
no group differences were seen at 12 months, at 24
months, all high-risk infants demonstrated worse

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rved. 135

Developmental disorders

working memory and response inhibition compared
to low-risk infants. In addition, in all groups, worse
gross motor skills were associated with worse
response inhibition [15


The mounting research evidence connecting

early motor impairment to poorer global develop-
mental outcomes for children at high risk for ASD
supports the importance of better understanding
motor impairments that might be specific to ASD
and when these impairments emerge. Given the
heterogeneity of ASD and the discovery of genetic
syndromes highly penetrant for ASD, quantitative
and neurodiagnostic measures of motor may shed
light on the individual variability of motor function
in these disorders.


Quantitative tools of motor function often use
kinetic and kinematic analysis to capture specific
spatiotemporal variables of motor function (e.g. gait
analysis, three-dimensional motion capture analy-
sis, digitized tablets). ‘Kinetics’ refers to the study of
forces that cause motion such as torque, gravity, and
friction. ‘Kinematics’ is the study of movement such
as displacement in time and velocity. These tools
have identified gross and fine motor impairments
that differentiate individuals with ASD from other
groups [16,17,18


Motor impairments in ASD are often present

beyond early childhood and can affect both gross
and fine motor domains such as balance and manual
dexterity [3]. These persistent deficits can affect
school-based activities, which can influence cogni-
tive and academic performance. For example, mea-
sures of handwriting ability can shed light on
multiple motor domains, such as grip strength
and manual dexterity, and they provide useful infor-
mation on a frequently employed school-based
activity. A recent study utilized an advanced quan-
titative digitized tablet to evaluate kinematic varia-
bles of handwriting (tortuosity, speed, size) and its
relationship to attention and ASD core symptomol-
ogy in school-aged children with ASD. The task was
designed to minimize additional cognitive and lin-
guistic processes, which can confound studies of
ASD [19


]. Participants were also evaluated using
the Movement Assessment Battery for Children-2
(MABC-2), a standardized measure of motor func-
tion examining three domains – manual dexterity,
balance, and aiming and catching [20]. Three main
findings were highlighted in the study: caregiver
report indicated greater handwriting difficulties in
children with ASD compared to typically developing

Copyright © 2018 Wolters Kluwer


age-matched peers; handwriting performance in the
ASD group was characterized by significantly poorer
writing quality and speed; and greater severity of
ASD, attention, and motor symptoms were corre-
lated with reduced handwriting performance and
greater difficulties in functional handwriting perfor-
mance [19


]. However, one of the most salient
points of the study was the value and feasibility of
a reliable, easy, and quantitative (rather than quali-
tative) assessment of handwriting performance.

Similar to the evaluation of handwriting skills,
there has been use of kinematic analysis for evaluate
of gait. Studies utilizing gait analysis have identified
differences in stride width, velocity, and stride
length in children with ASD compared to typically
developing children [21,22,23


]. These findings pro-
vide more clarity to previous qualitative descrip-
tions of gait in ASD such as ‘clumsy, rigid, and
wide-based’ [24,25]. A recent study using three-
dimensional motion capture to evaluate gait func-
tion in ASD has shown asymmetry of gait, which is
thought to be a marker of pathologic motor devel-
opment. Kinetic and kinematic gait data were
obtained from children 5–12 years of age with
ASD using a Vicon three-dimensional motion cap-
ture system. Unlike previous studies, the authors
used point-to-point analysis to evaluate data across
a gait cycle rather than in discrete time points. The
results showed significant asymmetry in joint posi-
tions (kinematic data) and nearing significance in
right and leg joint force (kinetic data). Additionally,
the analysis allowed evaluation at different points
during the gait cycle, which can indicate greater
dysfunction in positioning of the hips, knees, or
ankles. The authors noted that although asymmetry
might not always be detrimental, persistent asym-
metry in gait starting from childhood could be
problematic. When asymmetry is present, the con-
tralateral leg is required to compensate in position
and force, and this can place an individual at greater
risk for injury [26


]. Abnormalities in gait symmetry
can also lead to difficulties in social play-based
activities and sports, creating a barrier for children
with ASD to participate in such activities with their
peers. This work also provides clearer targets for
motor intervention.

These quantitative measures of motor function
have increased our knowledge of more specific
motor impairments in ASD and have even led
researchers to use these findings to hypothesize that
impairments in motor could be secondary to dis-
ruptions in cerebellar or fronto-striatal networks
[16,27]. The more recent utilization of neurodiag-
nostic measures, such as electroencephalography
(EEG), MRI, and transcranial magnetic stimulation
(TMS), has provided early insights into more specific

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Volume 31 � Number 2 � April 2018

Autism spectrum disorders Wilson et al.

abnormal neural networks leading to motor impair-
ments in ASD [28







Studies of neural mechanisms used in conjunction
with standardized and quantitative motor measures
are essential to parse out the heterogeneity of ASD
and identify targets for behavioral and pharmaco-
logic interventions for motor impairments.

Electroencephalography offers an economical
and noninvasive method for investigating motor-
related neural activity, including neural connectiv-
ity [32]. Oscillatory electrical activity, as captured by
EEG, reflects aspects of neural excitation and inhi-
bition, with the latter primarily modulated by
GABAergic processes. Altered brain oscillatory activ-
ity has been implicated in ASD (for review, see [33]).
In motor output areas, the modulation (suppres-
sion) of beta band oscillations (typically defined
as 13–30 Hz) has emerged as a prominent signal,
particularly elicited during motor specific actions.
Beta oscillations might indicate ongoing sensorimo-
tor integration, coordination, and motor prepara-
tion, as attenuation of beta oscillations are linked to
faster onset of movement [34]. Quantifying modu-
lations of beta oscillations during task-dependent
motor activities in individuals with ASD can provide
valuable information regarding potential aberrant
cortical networks that might be contributing to the
motor dysfunction.

In a recent study, EEG was used to evaluate the
role of oscillatory changes during a praxis motor
control task in children with ASD from 8 to 13 years
of age [31


]. The study chose to evaluate praxis,
because this motor domain represents the perfor-
mance of complex, skilled gestures that are used in
functional skills and communication. EEG was
recorded while the patients performed a praxis par-
adigm made up of pantomiming 10 common tools.
Individuals with ASD displayed reduced task-related
EEG power modulation during performance on the
praxis task, which suggests that dyspraxia in ASD
might be associated with decreased activity in the
frontal-parietal praxis network. The authors also
found a correlation between decreased left central
beta band desynchronization and autism severity
(defined from Autism Diagnostic Observation Scale
severity scores). These findings indicate aberrant
neural physiology associated with motor impair-
ments in ASD, and offers a potential brain-based
marker that can be measured with introduction of
interventions [31


Imaging studies using MRI, functional MRI

(fcMRI), and diffusion-tensor imaging (DTI)/

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diffusion tractography/diffusion-weighted images
have identified atypical patterns of structural brain
growth in ASD [35]. The use of imaging studies in
conjunction with behavioral measures of motor
function can allow evaluation of the neurobiology
underlying motor development.

As noted earlier in this review, studies of infants
at risk for ASD have primarily utilized behavioral
measures to identify differences in motor develop-
ment. A recent study used resting state fcMRI to
identify functional brain networks associated with
walking and gross motor skills in infants at low and
high risk for ASD. In all, 187 infants at 12 and
24 months of age underwent gross motor assess-
ments through the Mullen Scales of Early Learning
(MSEL) and brain MRI. Scores for walking and gross
motor function were analyzed in relation to network
level functional connectivity based on fcMRI data
acquired from infants and toddlers during natural
sleep. The authors adapted a statistical method
termed enrichment analysis to use a brain-wide
approach to identify networks with a significantly
increased density of connections strongly related to
the studies of walking and gross motor behaviors.
The findings indicated that subsets of infant/toddler
brain networks show strong relationships of func-
tional connectivity to walking and gross motor
function, and the profile of these brain networks
differs at 12 and 24 months. Additionally, these
network profiles involve both positive and negative
brain–behavior relationships, which implies that
increases and decreases in network level connectiv-
ity may underlie the developmental progression of
walking and gross motor function during this age
range. The description of these brain networks of
early gross motor development can aid in informing
neural systems contributing to typical and atypical
motor outcomes and also potentially aid in differ-
entiating neurodevelopmental disorders associated
with motor abnormalities [36


Studies of neuroimaging to better identify neu-

ral mechanisms of motor dysfunction in adults with
ASD has been more frequently utilized compared to
younger populations. A recent study of adults with
high functioning ASD combined the use of diffusion
tractography and a behavioral measure of fine
motor skill performance [37


]. It was found that
participants with ASD had slower performance on
the Purdue Pegboard test compared to typically
developing adults. Additionally, diffusion tractog-
raphy investigating primary motor cortex (M1) and
somatosensory cortex (S1) connections showed
decreased fractional anisotropy and increased per-
pendicular diffusivity, which has been seen in asso-
ciation with abnormalities of white matter tract
structure, reduced tract coherence and organization,

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rved. 137

Developmental disorders

and reduced myelination. It is thought that these
white matter abnormalities might underpin slower
and worse performance on the Purdue Pegboard
test. This study provides direct support of the
role of the connections between S1, M1, and fine
motor skill performance, and supports the potential
development of therapeutic approaches due to the
relationship of S1 input to M1 in long term potenti-
ation [37




As we move forward in the assessment of motor
function in ASD it is imperative the field continue
to employ these quantitative (both behavioral
and neurodiagnostic) measures. This study has
highlighted the advances in assessment of motor
function in ASD and the contribution these assess-
ments have made in better understanding more
specific and subtle motor impairments in ASD and
the underlying pathophysiology leading to these

Despite evidence for definitive motor dysfunc-
tion in ASD, studies of motor function in ASD, how-
ever, face some significant limitations, which include
lack of large samples of children with ASD and varying
levels of behavioral and cognitive functioning; few
studies evaluating children with ASD across develop-
ment to examine emergence of motor impairment
and changes over time; few studies that evaluate the
impact of genetic cause, ASD severity, and prevalent
behavioral comorbidities (attention deficit hyperac-
tivity disorder, intellectual disability, irritability) on
the manifestation of motor impairments. Quantita-
tive measures of motor function can alleviate the
cognitive and behavioral requirements of most stan-
dardized motor assessments and assess individuals
with ASD across a lifespan. These qualities allow
the study of a more heterogeneous sample of individ-
uals with ASD. Additionally, future studies should
utilize these measures to compare motor impairments
in other NDDs to ASD, to establish the degree of
specificity of certain motor impairments in ASD.

Recently, the literature has recognized how
motor impairments in ASD not only affect other
developmental domains but can also lead to reduced
participation in physical activity and subsequent
predisposition to poorer health outcomes [38


]. Evi-
dence-based early intervention programs that target
social and behavioral difficulties in children with
ASD have shown to facilitate long-term improve-
ments in these areas [39]. A recent systematic review
highlighted the benefits of various physical activity
interventions for children with ASD below 16 years
of age. The study found that jogging, horseback
riding, martial arts, swimming, and yoga/dance can

Copyright © 2018 Wolters Kluwer


result in improvements to numerous behavioral out-
comes. These outcomes include stereotyped behav-
iors, social–emotional functioning, cognition, and
attention [40]. Another study evaluated the benefits
of an Australian Football League program adapted for
children with ASD. Children enrolled in the program
for 1.5 h a week over a total of 11 weeks. Although
there was not significant change on the objective
motor assessment, standardized parent question-
naire indicated significant improvement in child
object control skills. Parents also noted improve-
ments in coordination and social skills [41]. The
positive results of these studies highlight the critical
need to develop evidence-based motor and physical
activity interventions for individuals with ASD.

As we begin to identify specific motor impair-
ments in ASD and the timing of emergence of these
impairments, we can begin to develop timely, indi-
vidualized interventions and community-based ser-
vices that support these individuals and improve
overall neurodevelopmental outcomes and long-
term functioning.



Financial support and sponsorship

Dr Wilson is funded by the National Institutes of Health.
Professor Enticott is funded by a Future Fellowship

from the Australian Research Council (FT160100077).
He also receives funding from the Brain and Behavior
Research Foundation and Fererro.

The work was supported by the Department of Psy-
chiatry at UCLA and the Centre for Social and Early
Emotional Development (SEED), Deakin University.

Conflicts of interest

Dr Wilson has no conflicts of interest to disclose.
Prof. Enticott and Professor Rinehart receive funding
from the Ferrero Group, Australia as part of its Kinder
þ Sport pillar of Corporate Social Responsibility initia-
tives to promote active lifestyles among young people.
Ferrero Group Australia had no role in this research
including the collection, analysis, and interpretation of
data; in writing of the manuscript; and in the decision to
submit the article for publication.

Papers of particular interest, published within the annual period of review, have
been highlighted as:

& of special interest
&& of outstanding interest

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Brief Report: DSM-5 Sensory Behaviours in Children With
and Without an Autism Spectrum Disorder

Dido Green1 • Susie Chandler2 • Tony Charman3 • Emily Simonoff2,5 •

Gillian Baird4

Published online: 30 July 2016

� Springer Science+Business Media New York 2016

Abstract Atypical responses to sensory stimuli are a new

criterion in DSM-5 for the diagnosis of an autism spectrum

disorder (ASD) but are also reported in other develop-

mental disorders. Using the Short Sensory profile (SSP)

and Autism Diagnostic Interview-Revised we compared

atypical sensory behaviour (hyper- or hypo-reactivity to

sensory input or unusual sensory interests) in children aged

10–14 years with (N = 116) or without an ASD but with

special educational needs (SEN; N = 72). Atypical sensory

behaviour was reported in 92 % of ASD and 67 % of SEN

children. Greater sensory dysfunction was associated with

increased autism severity (specifically restricted and

repetitive behaviours) and behaviour problems (specifically

emotional subscore) on teacher and parent Strengths and

Difficulties Questionnaires but not with IQ.

Keywords Autism spectrum disorder � Sensory reactivity �
Sensory interests � DSM-5 � Diagnostic criteria � Behaviour


Kanner’s (1943) original description of autism referred to

negative reactions to sensory stimuli, ‘‘loud noises or

moving objects, which are therefore reacted to with horror

or panic’’ (p. 245) while noting that the child ‘‘can happily

make as great a noise as any that he dreads and move

objects to his heart’s desire’’ (p. 245). Asperger (1944) also

described children as demonstrating hypersensitivity in

some circumstances but in other situations either ignoring

(appearing hyposensitive) or seeking out particular stimuli.

The Third Diagnostic and Statistical Manual of Mental

Disorders (DSM-III) (American Psychiatric Association

(APA) 1980) included atypical sensory responsiveness as

an associated feature of infantile autism under diagnostic

criterion E: ‘‘Bizarre responses to various aspects of the

environment’’ (APA 1980, p. 90). However, the subsequent

two editions of the DSM did not include specific reference

to sensory responsiveness in the diagnostic criteria (DSM-

IV, APA 1994; DSM-IV-TR, APA 1987). Since then,

atypical responses to sensory stimuli have been reported as

occurring in 65–95 % of individuals with ASD (Lane et al.

2014; Leekam et al. 2007; Tomchek and Dunn 2007;

Zachor and Ben-Itzchak 2014). Different types of response

to the sensory environment in ASD have been described;

hyper-responsivity, hypo-responsivity and over focussed

sensory interests (described in the literature as sensory

seeking) (Ausderau et al. 2014). Single or mixed sensory

modality responsivity and association with core features of

ASD and comorbidities have also been explored. A meta-

analysis of sensory behaviours in individuals with ASD

showed significant variation between studies with three

important moderators identified; chronological age, sever-

ity of autism and type of control group (whether compar-

ison groups were matched for chronological or mental age

& Dido Green
[email protected]

Centre for Rehabilitation, Oxford Brookes University,

Marston Road Campus, Jack Straw’s Lane, Oxford OX3 3FL,


Department of Child and Adolescent Psychiatry, Institute of

Psychiatry, Psychology and Neuroscience, King’s College

London, London, UK

Department of Psychology, Institute of Psychiatry,

Psychology and Neuroscience, King’s College London,

London, UK

Guy’s and St Thomas’ NHS Foundation Trust, King’s Health

Partners, London, UK

NIHR Biomedical Research Centre for Mental Health,

Institute of Psychiatry, Psychology and Neuroscience, King’s

College London, London, UK


J Autism Dev Disord (2016) 46:3597–3606

DOI 10.1007/s10803-016-2881-7

or other developmental disorder) (Ben-Sasson et al. 2009).

Altered sensory responsivity is reported as being associated

with restricted repetitive behaviours (Chen et al. 2009;

Foss-Feig et al. 2012) and need for sameness (Wigham

et al. 2015). Foss-Feig et al. (2012) considered sensory

subtypes in a study of 5–8 year olds with ASD (without a

comparison group) using both parent questionnaire and

direct observation of sensory behaviour. They found that

tactile hypo-responsiveness and sensory seeking correlated

strongly with increased social and communication impair-

ment on the Autism Diagnostic Interview-Revised (ADI-R)

(LeCouteur et al. 2003) and Autism Diagnostic Observa-

tion Schedule-Generic (ADOS-G) (Lord et al. 2000), and to

a lesser degree, repetitive behaviours. Tactile hyper-re-

sponsiveness did not significantly correlate with any of the

core features of ASD (Foss-Feig et al. 2012). Lane et al.

(2010; 2014) described four distinct sensory subtypes

showing different associations with age and IQ (e.g., taste/

smell versus postural inattentiveness) but noted that the

sensory phenotypes were not explained by gender or autism

severity (Lane et al. 2014). Altered sensory responsiveness

has been linked to anxiety (e.g., Lane et al. 2012; Ben-

Sasson et al. 2008; Wigham et al. 2015) and depression

(Bitsika et al. 2016) and may also have a significant impact

on adaptive function (e.g. Ben-Sasson et al. 2009; Lane

et al. 2010; Tomchek and Dunn 2007; Zachor and Ben-

Itzchak 2014).

The latest version of the DSM has again included

atypical sensory responsiveness (hyper- or hypo- reactivity

to sensory input) or unusual interest in sensory aspects of

the environment as one of four possible elements of which

two must be met in Criterion B: Restricted, repetitive

patterns of behaviour, interests, or activities. Combined

with persistent deficits in social communication and social

interaction across multiple contexts, these two domains

define autism spectrum disorder (DSM-5; APA 2013).

However, atypical responses to sensory stimuli are also

reported in people with intellectual disability and other

neurodevelopmental disorders (Watling et al. 2001; Green

et al. 2003; Tomchek and Dunn 2007; Lane et al. 2012),

leading to the suggestion that sensory symptoms are a non-

specific indicator, along with abnormalities in motor skills

or self-regulation, of brain network vulnerability in

developmental psychopathology (Levit-Binnun et al.

2013). While sensory behaviours are reported as occurring

more frequently in ASD than in comparator groups

(Watling et al. 2001; Tomchek and Dunn 2007), it is not

clear what proportion of individuals with conditions other

than ASD have hyper- or hypo-reactivity or sensory

interests and whether these involve the same sensory

modalities, single or multiple. We therefore contrasted the

proportion of individuals with hyper-or hypo-reactivity or

sensory interest to environmental sensory input, consistent

with DSM-5 criteria, in two groups of children from the

Special Needs and Autism Project (SNAP; Baird et al.

2006). Children with ASD and children with other forms of

special educational needs (SEN) without ASD were com-

pared using relevant items from the ADI-R (Lord et al.

1994) and the Short Sensory Profile (SSP) (Dunn 1999).

We also explored whether atypical sensory behaviours in

ASD were associated with autism symptom severity, IQ or

co-occurring emotional and behavioural problems. We

hypothesised that children with ASD would show a high

frequency of atypical responses to the sensory environ-

ment. These atypical responses would be more frequent

and more severe than in children with other neurodevel-

opmental problems and associated with autism severity and

behaviour problems.


The study was approved by the South East Multicentre

Research Ethics Committee (REC) (00/01/50). Parents

gave informed consent for participation.


The sampling methodology of the SNAP study has been

described previously (Baird et al. 2006) and is illustrated in

Fig. 1. In brief, this was a study of the prevalence of ASD

within a total population cohort of 56,946 children born

between July 1st 1990 and December 31st 1991 who were

assessed when aged 9–14 years. All those with a current

clinical diagnosis of ASD (N = 255) or considered ‘at risk’

of ASD by virtue of having a Statement of SEN

(N = 1515) were screened using the Social Communica-

tion Questionnaire (SCQ) (Rutter et al. 2003). Based on

SCQ score, a subsample stratified by four levels of SCQ


representing low (8), moderately low (8–14),
moderately high (15–21) and high ([21) scores (by coin-
cidence also N = 255), received a face to face compre-

hensive diagnostic assessment by trained researchers which

included the ADOS-G (Lord et al. 2000) and the ADI-R

(Lord et al. 1994), and measures of intellectual ability

(IQ).and behaviour. All information was used by the senior

authors to derive a clinical consensus diagnosis of ASD

(childhood autism and other ASDs; Baird et al. 2006) based

on ICD-10 (World Health Organization (WHO) 1993)

A Statement of Special Educational Needs is a legal document

issued by the local educational authority when children require

significant additional support in school due to any learning and/or

behavioural problems.
The cut-offs of 15 and 22 are recommended by Rutter et al. (2003),

and an additional cut-point of 8 was applied, based on the
distribution of SCQ scores within the sample.

3598 J Autism Dev Disord (2016) 46:3597–3606


research criteria. The total number of ICD-10 autism

symptoms was recorded. A panel of international experts

reviewed a proportion of cases and agreement on diagnosis

was high (see Baird et al. 2006 for details). Cases not

meeting criteria for a diagnosis of ASD were categorized as

SEN. These children had educational needs and a variety of

other developmental/medical diagnoses.


ADI-R the ADI-R has three items relevant to sensory

responsivity; ‘unusual sensory interests’, ‘undue sensitivity

to noise’, and ‘abnormal idiosyncratic response to specific

sensory stimuli’. Scored as current or having ever been

present; 0 (nil), 1 (present but with little or no impact, 2

(definite with impact), and 3 (for two items indicating

severe impact).

The Sensory Profile (SPr) (Dunn 1999). Parents com-

pleted the SSP (Dunn 1999), a commonly used question-

naire measure of abnormal responses to sensory stimuli,

reported to have good discriminate validity for children

(McIntosh et al. 1999a). The parent or carer rates the

child’s typical responses to sensory stimuli across 38 items

on a five point scale from ‘never = 5’ responds in this

ASD Autism Spectrum Disorder; SCQ Social Communication
Questionnaire; SEN Special Educational Needs; SSP Short Sensory Profile

56, 946 births in total population
(July 1, 1990 to Dec 31 1991)

1515 with SEN but no local ASD diagnosis
37 with local ASD diagnosis but no SEN
218 with local ASD diagnosis and SEN

1770 screened with the SCQ

1035 completed SCQ and opted in for further assessment

363 selected for in-depth assessment
Local diagnosis SCQ<8 SCQ 8-14 SCQ 15-21 SCQ>21 Total
No Selected 94 36 31 61 222

Participated 62 16 19 46 143
Yes Selected 9 14 29 89 141

Participated 3 9 26 74 112

255 seen for assessment
(Consensus diagnosis: 97 no ASD (SEN), 158 ASD)

66 opt-outs
30 uncontactable
12 did not attend

173 SSPs fully completed
15 SSPs pro-rated

188 SSPs for analysis

72 SEN 116 ASD

Fig. 1 SNAP sampling methodology

J Autism Dev Disord (2016) 46:3597–3606 3599


manner to ‘always = 1’. The time period is not specified

but the present tense phrasing implies current behaviour.

The total score indicates overall sensory dysfunction

(lower scores reflecting greater sensory dysfunction), and

seven subscales reflect dysfunction in the following

domains; tactile sensitivity, taste/smell sensitivity, move-

ment sensitivity, under-responsive/seeks sensation, audi-

tory filtering, low energy/weak, and visual/auditory

sensitivity. Missing values were prorated as an average for

the subscale if 10 % of items were missing for that
subscale and no more than 10 % of items missing across all

subscales. Cut-off scores for typical performance, probable

difference and definite difference can be calculated for the

total as well as each subscale. Construct validity and cut-

off scores have been derived from a North American

sample exploring the relationship of the SSP to physio-

logical responses in skin conductance in typical children

and a clinical sample of children identified with sensory

modulation difficulties (McIntosh et al. 1999a, b).

To conform to DSM-5 criteria, hyper-reactivity was

defined as scoring within the definite difference range on

SSP domains (tactile sensitivity, taste/smell sensitivity,

movement sensitivity or visual/auditory sensitivity) or a

score of 2 or 3 on the ADI-R items describing undue

sensitivity to noise or idiosyncratic negative responses to

sensory stimuli (using current codes). Hypo-reactivity was

defined as definite difference in the auditory filtering

domain of the SSP and an ‘always’ or ‘frequently’ response

to ‘Doesn’t seem to notice when face or hands are messy’,

or ‘Leaves clothing twisted on body’ items (both from the

under-responsive/seeks sensation domain) of the SSP.

Sensory interests were defined as a score of 1 or 2 on the

ADI-R item ‘unusual sensory interests’ (current code


IQ was measured using the Wechsler Intelligence Scale

for Children (WISC-III, Wechsler 1991; the current version

at the time of the study) or Raven’s Standard (SPM) or

Coloured Progressive Matrices (CPM) (Raven et al.

1990a, b) depending on the child’s ability. Where WISC

full scale IQs were not available, imputed full-scale IQs

were obtained using the regression relationship of full scale

IQ to SPM/CPM IQ (N = 12). For the five cases where no

direct cognitive testing was possible, all had Vineland

Adaptive Behaviour composite scores (Sparrow et al.

1984) below 20 and these cases were assigned an IQ score

of 19 to reflect their profound level of intellectual


Severity of ASD was measured by ADI-R (4–5 and

current) and ADOS total scores, as well as an overall ICD-

10 symptom count based on all available information (with

symptom counts ranging 0–12). For each of these mea-

sures, total scores as well as domain scores for social

impairment, communication impairment, and restrictive,

repetitive and stereotyped behaviours (RRSB) were cal-

culated. Behaviour problems were measured by the parent

and teacher versions of the Strengths and Difficulties

Questionnaire (SDQ) (Goodman 1997), which asks par-

ents/teachers to rate 25 behaviours as not true (0), some-

what true (1) or certainly true (2). These ratings can be

used to generate a total difficulties score, as well as sub-

scales for emotional symptoms, conduct problem, hyper-

activity, peer problems, and prosocial behaviours. The

SDQ is widely used as a brief screening instrument for

psychiatric problems and its psychometric properties have

been established in several samples, including the UK (e.g.

Goodman et al. 2000).

Data Analysis

Chi squared analyses and Fisher’s exact tests were used to

compare the proportions of children, with and without

ASD, with a hypersensitivity or a hyposensitivity or a

sensory interest consistent with DSM-5 criteria. Within the

ASD group, linear regression was used to examine the

relationship between sensory dysfunction (indicated by

lower SSP total scores) and other child characteristics, IQ,

age, autism symptoms (domain scores from the ICD-10

symptom count, ADOS and ADI-R), and behaviour and

emotions (SDQ subscale scores). Analyses were carried out

using Stata 11 (StataCorp 2009).


From a sample of 255 children, a total of 210 SSPs were

returned. Of these, 173 were fully completed and prorated

scores were calculated for a further 15 resulting in a total of

188 SSPs available for analysis (see Fig. 1). Of the 188,

116 children received a consensus diagnosis of ASD. The

diagnoses of the remaining 72 children (categorised as

SEN) included: 39 intellectual disability, 11 hyperkinetic

or conduct disorder, 10 language impairment, 4 hearing

impairment, 5 physical disability or medical condition, 2

chromosome disorders and 1 with no current clinical

diagnosis. Sample characteristics, mean SSP total and

domain scores are presented in Table 1. The SEN group

was slightly older than the ASD group [t (186) = 8.85,

p .001] but the groups did not differ in terms of IQ
[t (186) = 0.92, p = 0.36].

As these children scored at floor (composite standard score 20)

on the Vineland Adaptive Behaviour Scale, these cases were assigned

a proxy IQ score of one point below this, consistent with previous


3600 J Autism Dev Disord (2016) 46:3597–3606


The proportions of SEN and ASD children reported to

have sensory behaviours on the ADI-R, and those scoring

within the definite difference range for each of the SSP

domains are shown in Table 2. Ninety-two percent (107) of

the ASD group compared with 67 % (48) of the SEN group

had either a hypersensitivity, hyposensitivity or a sensory

interest [v2 (1, N = 188) = 20.1, p .001].
Compared to the SEN group more children with ASD

scored within the definite difference range on at least one

hyper-reactive domain on the SSP [v2 (1, N = 188) =
29.7, p .001] and also for two hyper-reactive domains
[v2 (1, N = 188) = 27.1, p .001]. Hyper-reactivity to
the sensory environment was more common among the

ASD group compared to the SEN group for tactile, taste/

smell and visual/auditory sensitivity (all p .05); for
movement sensitivity, the difference in rates did not quite

reach significance [v2 (1, N = 188) = 3.84, p = .05].
Definite/marked oversensitivity to noise (ADI item, current

coding of 2 or 3) was also more common in the ASD group,

compared to the SEN group (Fisher’s exact: N = 188,

p .001). However rates of idiosyncratic negative
responses to specific sensory stimuli causing intrusion

(ADI item coding of 2 or 3) did not differ significantly

(Fisher’s exact: N = 188, p = .295).

Regarding hyposensitivity, a greater proportion of the

ASD group compared to the SEN group, scored within the

definite difference on the SSP auditory filtering subscale

[70 vs 49 %, v2 (1, N = 188) = 8.46, p .05]. The SEN

and ASD groups showed similar proportions of children

who always/frequently ‘[doesn’t] seem to notice when face

or hands are messy’ [v2 (1, N = 188) = .92, p = .34, see
Table 3]. However, the proportion of children who always/

frequently ‘leaves clothing twisted on body’ was signifi-

cantly higher in the ASD group [v2 (1, N = 188) = 13.3,
p .001].

More children in the ASD than SEN group were

reported to have unusual sensory interests both by current

[v2 (1, N = 188) = 23.2, p .001] and historical [v2 (1,
N = 188) = 36.4, p .001] ADI-R score (coding 1 or 2).

Within the ASD group, a lower SSP total (indicating

greater sensory dysfunction) was associated with higher

SDQ total score, accounted for by the emotional subscale

on parent report [b = -2.54, t (101) = -2.96, p = .004]
and with repetitive, restricted and stereotyped behaviour as

recorded on the ICD-10 symptom count [b = -5.49,
t (101) = -2.18, p = .03];but not with ICD-10 social or

communication impairment scores (p = .36 and p = .46,

respectively) (See Table 4). Sensory dysfunction was not

associated with IQ, age, or the remaining SDQ subscales

(all p [ .12). Repeated regressions using the different
measures of autism severity, ADI-R and ADOS scores,

yielded the same results, i.e. autism severity and SDQ total

were associated with sensory behaviours, while IQ was not.

A similar pattern was found when the regression analysis

was repeated using teacher SDQ totals in place of parent

SDQ totals.

Table 1 Sample characteristics and mean SSP scores

SEN (N = 72) ASD (N = 116) T test/Chi square/Fisher’s exact

Sample characteristics

Age in years (SD, range) 12.7 (0.87, 10.1–14) 11.6 (0.87, 10–13.8) p .001
IQ (SD, range) 77.0 (20.5, 31–131) 73.9 (23.0, 19–136) p = .359

Ethnicity 94 % white 95 % white p = .909

Parental education 39 % with A-levels 47 % with A-levels p = .287

Gender 82 % male 87 % male p = .337

ADI-R 4–5 total (SD) 12.0 (8.87) 43.2 (11.0) p .001
ADOS-G total (SD) 3.99 (2.92) 12.5 (6.39) p .001
ICD-10 symptom count (SD) 1.38 (1.17) 7.97 (2.47) p .001

SSP scores

SSP total [mean (SD)] 153.7 (24.1) 131.0 (24.3) p .001
SSP domain scores [mean (SD)]: tactile sensitivity 30.4 (4.45) 26.4 (5.68) p .001
Taste sensitivity 16.8 (4.58) 13.5 (5.51) p .001
Movement sensitivity 13.0 (2.64) 11.89 (3.30) p .014
Underresponsive/seeks sensation 26.2 (7.54) 21.4 (6.20) p .001
Auditory filtering 20.2 (5.25) 16.8 (4.85) p .001
Low energy/weak 25.6 (5.98) 23.4 (7.12) p = .029

Visual/auditory 21.4 (3.71) 17.6 (5.22) p .001

A-Levels Advanced Level General Certificate of Education equivalent to Secondary or High School leaving qualification, ADI-R Autism

Diagnostic Interview-Revised, ADOS-G Autism Diagnostic Observation Scale-Generic, SSP Short Sensory Profile

J Autism Dev Disord (2016) 46:3597–3606 3601



In this well characterised cohort, sensory interests or hyper

or hypo reactivity to sensory input were reported in the

majority (92 %) of children with ASD but were also

reported in 67 % with SEN but without ASD. A definite

difference in total SSP score was found in 66 % of the

ASD group and 32 % of the SEN group. Both

groups showed a higher frequency than in a group of

typically developing children without functional/clinical

Table 2 Frequency and percentage of definite sensory symptoms among the SEN and ASD groups


(N = 72)


(N = 116)


Fisher’s exact

ADI-R items

Sensory interests (current) 1 or 2 shown regularly—score

1 [n (%)]

11 (15 %) 49 (42 %) p .001

Marked with impact—score 2

[n (%)]

2 (3 %) 13 (11 %) p = .051

Any-score 1 or 2 [n (%)] 13 (18 %) 62 (53 %) p .001
Sensory interests (ever): 1 or 2 shown regularly score 1

[n (%)]

11 (15 %) 49 (42 %) p .001

Marked with impact—score 2

[n (%)]

3 (4 %) 26 (23 %) p = .001

Any—score 1 or 2 [n (%)] 14 (20 %) 75 (65 %) p .001
Sensitivity to noise (current): Slight—score 1 [n (%)] 9 (13 %) 31 (27 %) p = .027

Definite—score 2 [n (%)] 2 (3 %) 28 (24 %) p .001
Marked with impact—score 3

[n (%)]

1 (1 %) 6 (5 %) p = .254

Any—score 1–3 [n (%)] 12 (17 %) 65 (56 %) P .001
Sensitivity to noise (ever): Slight—score 1 [n (%)] 8 (11 %) 32 (28 %) p = .008

Definite—score 2 [n (%)] 7 (10 %) 40 (34 %) p .001
Marked with impact—score 3

[n (%)]

1 (1 %) 12 (10 %) p = .020

Any—score 1–3 [n (%)] 16 (23 %) 84 (72 %) p .001
Abnormal idiosyncratic negative response to specific

sensory stimuli (current):

Mild reaction—score 1 [n (%)] 5 (7 %) 23 (20 %) p = .020

Causes some intrusion—score

2 [n (%)]

4 (6 %) 11 (9 %) p = .415

Substantial intrusion—score 3

[n (%)]

0 (-) 2 (2 %) p = .525

Any—score 1–3 [n (%)] 9 (13 %) 36 (31 %) p = .005

Abnormal idiosyncratic negative response to specific

sensory stimuli (ever):

Mild reaction—Score 1 [n


7 (10 %) 26 (22 %) p = .030

Causes some intrusion—score

2 [n (%)]

4 (6 %) 14 (12 %) p = .202

Substantial intrusion—score 3

[n (%)]

0 (-) 3 (3 %) p = .287

Any—score 1–3 [n (%)] 11 (15 %) 43 (37 %) p = .001

SSP domains

SSP total Definite difference [n (%)] 23 (32 %) 76 (66 %) p .001
Taste/smell sensitivity Definite difference [n (%)] 9 (13 %) 41 (35 %) p = .001

Movement sensitivity Definite difference [n (%)] 12 (17 %) 34 (29 %) p = .050

Under-responsive/seeks sensation Definite difference [n (%)] 23 (32 %) 72 (76 %) p .001
Auditory filtering Definite difference [n (%)] 35 (49 %) 81 (70 %) p = .004

Low energy/weak Definite difference [n (%)] 20 (28 %) 42 (36 %) p = .232

Visual/auditory sensitivity Definite difference [n (%)] 3 (4 %) 37 (32 %) p .001

3602 J Autism Dev Disord (2016) 46:3597–3606


Table 3 Frequency and percentage of children who always or frequently displayed behaviours on the Short Sensory Profile


(N = 72)


(N = 116)



Tactile sensitivity

1. Expresses distress during grooming 5 (7 %) 39 (34 %) p .001
2. Prefers long-sleeved clothing even when it is warm or short sleeves when it is


8 (11 %) 20 (17 %) p = .296

3. Avoids going barefoot, especially in grass or sand 4 (6 %) 18 (16 %) p = .060

4. Reacts emotionally or aggressively to touch 5 (7 %) 15 (13 %) p = .231

5. Withdraws from splashing water 4 (6 %) 18 (16 %) p = .060

6. Has difficulty standing in line or close to other people 7 (10 %) 41 (35 %) p .001
7. Rubs or scratches out a spot that has been touched 5 (7 %) 12 (10 %) p = .602

Taste/smell sensitivity

8. Avoids certain tastes or food smells that are typically part of children’s diets 7 (10 %) 40 (34 %) p .001
9. Will only eat certain tastes 9 (13 %) 37 (32 %) p = .003

10. Limits self to particular food textures/temperatures 7 (10 %) 34 (29 %) p = .002

11. Picky eater, especially regarding food textures 14 (19 %) 41 (35 %) p = .020

Movement sensitivity

12. Becomes anxious or distressed when feet leave the ground 1 (1 %) 9 (8 %) p = .092

13. Fears falling or heights 4 (6 %) 22 (19 %) p = .009

14. Dislikes activities where head is upside down 12 (17 %) 24 (21 %) p = .496

Underresponsive/seeks sensation

15. Enjoys strange noises/seeks to make noise for noise’s sake 11 (15 %) 45 (39 %) p = .001

16. Seeks all kinds of movement and this interferes with daily routines 24 (33 %) 58 (50 %) p = .025

17. Becomes overly excitable during movement activity 13 (18 %) 39 (34 %) p = .020

18. Touches people and objects 15 (21 %) 46 (40 %) p = .007

19. Doesn’t seem to notice when face or hands are messy 20 (28 %) 40 (34 %) p = .338

20. Jumps from one activity to another so that it interferes with play 15 (21 %) 39 (34 %) p = .060

21. Leaves clothing twisted on body 10 (14 %) 46 (40 %) p .001
Auditory filtering

22. Is distracted or has trouble functioning if there is a lot of noise around 32 (44 %) 75 (67 %) p = .007

23. Appears to not hear what you say 21 (29 %) 63 (54 %) p = .001

24. Can’t work with background noise 6 (8 %) 25 (22 %) p = .025

25. Has trouble completing tasks when the radio is on 12 (17 %) 33 (28 %) p = .066

26. Doesn’t respond when name is called but you know the child’s hearing is ok 10 (14 %) 39 (34 %) p = .003

27. Has difficulty paying attention 30 (42 %) 70 (60 %) p = .013

Low energy/weak

28. Seems to have weak muscles 7 (10 %) 25 (22 %) p = .045

29. Tires easily, especially when standing or holding particular body position 12 (17 %) 25 (22 %) p = .413

30. Has weak grip 7 (10 %) 17 (15 %) p = .375

31. Can’t lift heavy objects 8 (11 %) 25 (22 %) p = .078

32. Props to support self 8 (11 %) 16 (14 %) p = .592

33. Poor endurance/tires easily 10 (14 %) 27 (24 %) p = .089

Visual auditory sensitivity

34. Responds negatively to unexpected or loud noises 3 (4 %) 43 (37 %) p .001
35. Holds hands over ears to protect ears from sound 7 (10 %) 47 (41 %) p .001
36. Is bothered by bright lights after others have adapted to the light 2 (3 %) 19 (16 %) p = .004

37. Watches everyone when they move around the room 16 (22 %) 24 (21 %) p = .803

38. Covers eyes or squints to protect eyes from light 3 (4 %) 21 (18 %) p = .006

J Autism Dev Disord (2016) 46:3597–3606 3603


impairments (albeit aged 3–6 years) who were reported as

having a probable (13 %) or definite (3 %) difference in

total SSP scores (Tomchek and Dunn 2007). Multiple

hyper-sensitivities (i.e. tactile, taste/smell, and noise) were

much more common in ASD than in the SEN group, as was

severity of hypersensitivity and impact particularly from

noise as shown on ADI score. Sensory interests were more

common in the ASD than SEN group.

Our findings support the inclusion of atypical sensory

responsivity to the environment in the DSM-5 diagnostic

criteria but emphasise that such behaviours are not unique

to ASD; one feature does not make a diagnosis, other

features remain essential. The findings are also supportive

of the hypothesis that sensory symptoms are a non-specific

indicator of brain functional network difference in devel-

opmental psychopathology (Levit-Binnun et al. 2013).

The association of atypical sensory behaviours with

restricted, repetitive and stereotyped behaviours, but not

IQ, are consistent with those of Boyd et al. (2010), Mandy

et al. (2012), Dar et al. (2012) and Wigham et al. (2015)

but inconsistent with Lane et al. (2014) who found hyper-

sensitivity and generalised reactivity to differ by age and

IQ but not ASD …

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