Senior Seminar – Beyond the Two-Factor Model of the ASD Diagnostic Criteria

REVIEW

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

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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.

Summary

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.

Keywords

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

DOI:10.1097/WCO.0000000000000182

INTRODUCTION

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

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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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KEY POINTS

� 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.

EARLY SIGNS OF AUTISM SPETRUM DISORDER AND ASSOCIATED INTERVENTION TARGETS 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

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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 [17]).

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.

Attention

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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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- ing.

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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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 [2,54].

Communication

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

&&

,55 &

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

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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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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.

SUMMARY OF KEY INTERVENTION TARGETS

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.

PRACTICAL CONSIDERATIONS

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.

CONCLUSION

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.

Acknowledgements

None.

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.

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

& of special interest && of outstanding interest

1. &&

Jones EJ, Gliga T, Bedford R, et al. Developmental pathways to autism: a review of prospective studies of infants at risk. Neurosci Biobehav Rev 2014; 39:1 – 33.

This article provides a review of findings from longitudinal studies of high-risk infant siblings of children with ASD. 2. Rogers SJ, Vismara L, Wagner AL, et al. Autism treatment in the first year of

life: a pilot study of infant start, a parent-implemented intervention for sympto- matic infants. J Autism Dev Disord 2014; 44:2981 – 2995.

3. Siller M, Morgan L, Turner-Brown L, et al. Designing studies to evaluate parent-mediated interventions for toddlers with autism spectrum disorder. J Early Intervention 2014. [Epub ahead of print]

4. Wetherby AM, Guthrie W, Woods J, et al. Parent-implemented social inter- vention for toddlers with autism: an RCT. Pediatrics 2014; 134:1084 – 1093.

5. Baranek GT. Autism during infancy: a retrospective video analysis of sensory- motor and social behaviors at 9 – 12 months of age. J Aut Dev Disord 1999; 29:213 – 224.

6. Phagava H, Muratori F, Einspieler C, et al. General movements in infants with autism spectrum disorders. Georgian Med News 2008; 156:100 – 105.

7. Zwaigenbaum L, Bryson S, Rogers T, et al. Behavioral manifestations of autism in the first year of life. Int J Dev Neurosci 2005; 23:143 – 152.

8. Iverson JM, Wozniak RH. Variation in vocal-motor development in infant siblings of children with autism. J Autism Dev Disord 2007; 37:158 – 170.

9. Landa R, Garrett-Mayer E. Development in infants with autism spectrum disorders: a prospective study. J Child Psychol Psychiat 2006; 47:629 – 638.

10. Ozonoff S, Iosif AM, Baguio F, et al. A prospective study of the emergence of early behavioral signs of autism. J Am Acad Child Adolesc Psychiatry 2010; 49:256 – 266.

11. Brian J, Bryson SE, Garon N, et al. Clinical assessment of autism in high-risk 18-month-olds. Autism 2008; 12:433– 456.

12. Bryson SE, Zwaigenbaum L, Brian J, et al. A prospective case series of high- risk infants who developed autism. J Autism Dev Disord 2007; 37:12 – 24.

13. Elison JT, Wolff JJ, Reznick JS, et al. Infant Brain Imaging Study (IBIS) Network. Repetitive behavior in 12-month-olds later classified with autism spectrum disorder. J Am Acad Child Adolesc Psychiatry 2014; 53:1216 – 1224.

14. Loh A, Soman T, Brian J, et al. Stereotyped motor behaviors associated with autism in high-risk infants: a pilot videotape analysis of a sibling sample. J Autism Dev Disord 2007; 37:25 – 36.

15. Ozonoff S, Macari S, Young GS, et al. Atypical object exploration at 12 months of age is associated with autism in a prospective sample. Autism 2008; 12:457 – 472.

16. Sacrey LAR, Bryson SE, Zwaigenbaum L. Prospective examination of visual attention during play in infants at high-risk for autism spectrum disorder: A longitudinal study from 6 to 36 months of age. Behav Brain Res 2013; 256:441 – 450.

17. Flanagan JE, Landa R, Bhat A, Bauman M. Head lag in infants at risk for autism: a preliminary study. Am J Occup Ther 2012; 66:577 – 585.

18. Piaget J, Cook MT. The origins of intelligence in children. New York, NY: WW Norton; 1952.

19. Fischer KW. A theory of cognitive development: the control and construction of hierarchies of skills. Psychol Rev 1980; 87:477.

20. Rothbart MK, Ziaie H, O’Boyle CG. Self-regulation and emotion in infancy. In: Eisenberg N, Fabes RA, editors. New directions for child and adolescent development. San Francisco: Jossey-Bass publishers; 1992. pp. 7 – 23.

21. Colombo J, Cheatham CL. The emergence and basis of endogenous attention in infancy and early childhood. Adv Child Dev Behav 2006; 34:283 – 322.

22. Petersen SE, Posner MI. The attention system of the human brain: 20 years after. Annu Rev Neurosci 2012; 35:73.

23. Landry R, Bryson SE. Impaired disengagement of attention in young children with autism. J Child Psychol Psychiat 2004; 45:1115 – 1122.

24. &&

Keehn B, Müller RA, Townsend J. Atypical attentional networks and the emergence of autism. Neurosci Biobehav Rev 2013; 37:164 – 183.

Review of the literature on attention in ASD with a focus on the alerting, orienting, and executive control networks. Includes discussion of neural substrates, and advances the proposition that deficits in attentional controls (particularly disen- gagement) underlie the emergence of ASD. 25. Sacrey LAR, Armstrong VL, Bryson SE, Zwaigenbaum L. Impairments to visual

disengagement in autism spectrum disorder: a review of experimental studies from infancy to adulthood. Neurosci Biobehav Rev 2014; 47:559 – 577.

26. &

Bryson SE. What do early signs tell us about the developmental roots of autism? In: Just MA, Pelphrey KA, editors. Development and brain systems in autism. New York, NY: Taylor & Francis; 2013. pp. 105 – 122.

This chapter provides an overview of findings from the Canadian high-risk infant sibling cohort, and theoretical discussion of mechanisms underlying early deficits in ASD and the broader autism phenotype. Discussion centers around emerging temperamental, attentional, and emotional regulation profiles in the first 2 years of life.

Copyright © 2015 Wolters Kluwer

122 www.co-neurology.com

27. Elsabbagh M, Fernandes J, Jane Webb S, et al. Disengagement of visual attention in infancy is associated with emerging autism in toddlerhood. Biol Psychiatry 2013; 74:189 – 194.

28. Garon N, Bryson SE, Zwaigenbaum L, et al. Temperament and its relationship to autistic symptoms in a high-risk infant sib cohort. J Abnorm Child Psychol 2009; 37:59 – 78.

29. Schietecatte I, Roeyers H, Warreyn P. Exploring the nature of joint attention impairments in young children with autism spectrum disorder: associated social and cognitive skills. J Autism Dev Disord 2012; 42:1 – 12.

30. Feldman R. The development of regulatory functions from birth to 5 years: Insights from premature infants. Child Dev 2009; 80:544– 561.

31. Wass S, Porayska-Pomsta K, Johnson MH. Training attentional control in infancy. Curr Biol 2011; 21:1543 – 1547.

32. Schreibman L. Intensive behavioral/psychoeducational treatments for autism: research needs and future directions. J Autism Dev Disord 2000; 30:373 – 378.

33. Berger M. A model of preverbal social development and its application to social dysfunctions in autism. J Child Psychol Psychiat 2006; 47:338– 371.

34. Farroni T, Csibra G, Simion F, Johnson MH. Eye contact detection in humans from birth. Proc Natl Acad Sci 2002; 99:9602 – 9605.

35. Messinger DS, Fogel A, Dickson KL. All smiles are positive, but some smiles are more positive than others. Dev Psychol 2001; 37:642.

36. Hobson RP, Meyer JA. Foundations for self and other: a study in autism. Dev Sci 2005; 8:481 – 491.

37. Gallese V. Intentional attunement: a neurophysiological perspective on social cognition and its disruption in autism. Brain Res 2006; 1079:15 – 24.

38. Mundy P, Gwaltney M, Henderson H. Self-referenced processing, neuro- development and joint attention in autism. Autism 2010; 14:408 – 429.

39. Czapinski P, Bryson SE. Reduced facial muscle movements in autism: Evidence for dysfunction in the neuromuscular pathway? Brain and Cog 2003; 51:177 – 179.

40. Snow ME, Herzig ME, Shapiro T. Expression of emotion in young autistic children. J Am Acad Child Adolesc Psychiatry 1987; 26:836– 838.

41. Filliter JH, Longard J, Lawrence MA, et al. Positive affect in infant siblings of children diagnosed with autism spectrum disorder. J Abnorm Child Psychol 2014. [Epub ahead of print]

42. Young GS, Merin N, Rogers SJ, Ozonoff S. Gaze behavior and affect at 6 months: predicting clinical outcomes and language development in typically developing infants and infants at risk for autism. Dev Sci 2009; 12:798 – 814.

43. Osterling J, Dawson G. Early recognition of children with autism: a study of first birthday home videotapes. J Autism Dev Disord 1994; 24:247 – 257.

44. Elsabbagh M, Gliga T, Pickles A, et al. The development of face orienting mechanisms in infants at-risk for autism. Behav Brain Res 2013; 251:147 – 154.

45. Chawarska K, Macari S, Shic F. Decreased spontaneous attention to social scenes in 6-month-old infants later diagnosed with autism spectrum disor- ders. Biol Psychiatry 2013; 74:195 – 203.

46. Elsabbagh M, Mercure E, Hudry K, et al. Infant neural sensitivity to dynamic eye gaze is associated with later emerging autism. Curr Biol 2012; 22:338 – 342.

47. Jones W, Klin A. Attention to eyes is present but in decline in 2 – 6-month-old infants later diagnosed with autism. Nature 2013; 504:427 – 431.

48. Kasari C, Siller M, Huynh LN, et al. Randomized controlled trial of parental responsiveness intervention for toddlers at high risk for autism. Infant Behav Dev 2014; 37:711 – 721.

49. Carter AS, Messinger DS, Stone WL, et al. A randomized controlled trial of Hanen’s ‘More Than Words’ in toddlers with early autism symptoms. J Child Psychol Psychiat 2011; 52:741 – 752.

50. Green J, Charman T, McConachie H, et al. Parent-mediated communication- focused treatment in children with autism (PACT): A randomised controlled trial. Lancet 2010; 375:2152 – 2160.

51. Landa RJ, Holman KC, O’Neill AH, Stuart EA. Intervention targeting devel- opment of socially synchronous engagement in toddlers with autism spectrum disorder: a randomized controlled trial. J Child Psychol Psychiat 2011; 52:13 – 21.

52. Hohenberger A. The role of affect and emotion in language development. In: Gokcay D, Yildirim G (Eds.) Affective computing and interaction: psycholo- gical, cognitive and neuroscientific perspectives 2011. Hershey, PA: IGI Global. pp. 208 – 243.

53. Kasari C, Sigman M, Mundy P, Yirmiya N. Affective sharing in the context of joint attention interactions. J Autism Dev Disord 1990; 20:87 – 100.

54. Schreibman L, Kaneko WM, Koegel RL. Positive affect of parents of autistic children: a comparison across two teaching techniques. Behav Ther 1991; 22:479 – 490.

55. &

Zwaigenbaum L, Bryson S, Garon N. Early identification of autism spectrum disorders. Behav Brain Res 2013; 251:133 – 146.

Review of early signs of ASD in the first 2 years of life, from prospective and retrospective designs. Early signs include deficits in social-communication and repetitive behavior as well as sensory-motor, emotional regulation, and attention. 56. Charman T. Why is joint attention a pivotal skill in autism? Philos Trans R Soc

Lond B Biol Sci 2003; 358:315 – 324.

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Autism spectrum disorder in infancy Brian et al.

57. Siller M, Sigman M. Modeling longitudinal change in the language abilities of children with autism: parent behaviors and child characteristics as predictors of change. Dev Psychol 2008; 44:1691.

58. Bono MA, Daley T, Sigman M. Relations among joint attention, amount of intervention and language gain in autism. J Autism Dev Disord 2004; 34:495 – 505.

59. Kasari C, Freeman S, Paparella T. Joint attention and symbolic play in young children with autism: a randomized controlled intervention study. J Child Psychol Psychiat 2006; 47:611 – 620.

60. Kasari C, Paparella T, Freeman S, Jahromi LB. Language outcome in autism: randomized comparison of joint attention and play interventions. J Consult Clin Psychol 2008; 76:125.

61. Mundy P, Crowson M. Joint attention and early social communication: implications for research on intervention with autism. J Autism Dev Disord 1997; 27:653 – 676.

62. Dawson G, Rogers S, Munson J, et al. Randomized, controlled trial of an intervention for toddlers with autism: the Early Start Denver Model. Pediatrics 2010; 125:e17 – e23.

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63. Mawhood L, Howlin P, Rutter M. Autism and developmental receptive language disorder: a comparative follow-up in early adult life. J Child Psychol Psychiat 2003; 41:547 – 559.

64. Huttenlocher PR. Cambridge, MA: Harvard University Press: Neural plasti- city; 2009.

65. Dawson G. Early behavioral intervention, brain plasticity, and the prevention of autism spectrum disorder. Dev Psychopathol 2008; 20:775 – 803.

66. Centers for Disease Control and Prevention. (2014). Prevalence of autism spectrum disorder among children aged 8 years – Autism and Developmental Disabilities Monitoring Network, 11 sites, United States, 2010. Morbidity and Mortality Weekly Report, Surveillance Summary, 63: 1-20.

67. Reichow B. Overview of meta-analyses on early intensive behavioral inter- vention for young children with autism spectrum disorders. J Autism Dev Disord 2012; 42:512 – 520.

68. Dawson G, Toth K, Abbott R, et al. Early social attention impairments in autism: social orienting, joint attention, and attention to distress. Dev Psychol 2004; 40:271.

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REVIEW

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

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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.

Summary

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.

Keywords

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, Australia

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

DOI:10.1097/WCO.0000000000000541

INTRODUCTION

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

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[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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KEY POINTS

� 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 functioning.

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.

RELATIONSHIP OF MOTOR FUNCTION TO OTHER DEVELOPMENTAL DOMAINS

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 [12

&&

]. 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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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 MEASURES OF MOTOR FUNCTION IN AUTISM SPECTRUM DISORDER

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

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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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Autism spectrum disorders Wilson et al.

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

&

,29 &

,30 &&

,31 &&

].

NEURODIAGNOSTIC MEASURES OF MOTOR FUNCTION

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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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

&&

]

FUTURE DIRECTIONS AND CONCLUSION

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 impairments.

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

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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.

Acknowledgements

None.

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.

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

& of special interest && of outstanding interest

1. Iverson JM. Developing language in a developing body: the relationship between motor development and language development. J Child Lang 2010; 37:1 – 25.

Health, Inc. All rights reserved.

Volume 31 � Number 2 � April 2018

Autism spectrum disorders Wilson et al.

2. Esposito G, Venuti P, Maestro S, Muratori F. An exploration of symmetry in early autism spectrum disorders: analysis of lying. Brain Dev 2009; 31: 131 – 138.

3. Fournier KA, Hass CJ, Naik SK, et al. Motor coordination in autism spectrum disorders: a synthesis and meta-analysis. J Autism Dev Disord 2010; 40:1227 – 1240.

4. Jeste SS, Geschwind DH. Clinical trials for neurodevelopmental disorders: at a therapeutic frontier. Sci Transl Med 2016; 8:1 – 4.

5. &&

Bishop SL, Farmer C, Bal V, et al. Identification of developmental and behavioral markers associated with genetic abnormalities in autism spectrum disorder. Am J Psychiatry 2017; 174:576 – 585.

This study highlights the prevalence of motor function in genetic disorders associated with ASD and relationship of gait dysfunction to the yield of genetic testing. 6. Distefano C, Gulsrud A, Huberty S, et al. Identification of a distinct develop-

mental and behavioral profile in children with Dup15q syndrome. J Neurodev Disord 2016; 8:19.

7. Staples KL, Reid G. Fundamental movement skills and autism spectrum disorders. J Autism Dev Disord 2010; 40:209– 217.

8. Allen KA, Bredero B, Van Damme T, et al. Test of gross motor development-3 (TGMD-3) with the use of visual supports for children with autism spectrum disorder: validity and reliability. J Autism Dev Disord 2017; 47:813 – 833.

9. Karasik LB, Tamis-lemonda CS, Adolph KE. Transition from crawling to walking and infants’ actions with objects and people. Child Dev 2011; 82:1199 – 1209.

10. Bhat AN, Landa RJ, Galloway JC, et al. Current perspectives on motor functioning in infants, children, and adults with autism spectrum disorders. Phys Ther 2011; 91:1116 – 1129.

11. Papadopoulos N, Mcginley J, Tonge B, et al. Motor proficiency and emotional / behavioural disturbance in autism and Asperger ’ s disorder: another piece of the neurological puzzle? 2011. Autism 2012; 16:627 – 640.

12. &&

Lebarton ES, Iverson JM. Infant behavior and development full length article associations between gross motor and communicative development in at-risk infants. Infant Behav Dev 2016; 44:59 – 67.

This study highlights the relationship of motor development to social communication 13. Piper M, Darrah J. Motor Assessment of the Developing Infant. Philadelphia,

PA: Saunders Publishing; 1994. 14. Mullen EM. Mullen Scales of Early Learning. Circle Pines, MN: American

Guidance Service; 1995. 15. &&

John TS, Estes AM, Dager SR, et al. Emerging executive functioning and motor development in infants at high and low risk for autism spectrum disorder. Front Psychol 2016; 7:1016.

This study highlights the relationship of motor impairments and more complex cognitive development. 16. Rinehart NJ, Tonge BJ, Iansek R, et al. Gait function in newly diagnosed

children with autism: cerebellar and basal ganglia related motor disorder. Dev Med Child Neurol 2006; 48:819 – 824.

17. Cook JL, Blakemore SJ, Press C. Atypical basic movement kinematics in autism spectrum conditions. Brain 2013; 136:2816 – 2824.

18. &

Anzulewicz A, Sobota K, Delafield-butt JT. Toward the autism motor signature: gesture patterns during smart tablet gameplay identify children with autism. Sci Rep 2016; 6:31107.

This study demonstrates the ability to use a quantitative tablet to evaluate fine motor function in young children with ASD. 19. &&

Grace N, Gregory P, Beth E, et al. Do handwriting difficulties correlate with core symptomology, motor proficiency and attentional behaviours? J Autism Dev Disord 2017; 47:1006 – 1017.

This study utilizes a quantitative measure of handwriting to identify my subtle and specific impairments in handwriting in children with ASD compared to typically developing children. 20. Henderson SE, Sugden DA, Barnett AL. Movement assessment battery for

children (2nd ed.). London: Harcourt Assessment; 2007. 21. Kindregan D, Gallagher L, Gormley J. Gait deviations in children with autism

spectrum disorders: a review. Autism Res Treat 2015; 2015:741480. 22. Lim BO, O’Sullivan D, Choi B-G, Kim M-Y. Comparative gait analysis between

children with autism and age-matched controls: analysis with temporal-spatial and foot pressure variables. J Phys Ther Sci 2016; 28:286 – 292.

23. &

Dufek JS, Eggleston JD, Harry JR, Hickman RA. A comparative evaluation of gait between children with autism and typically developing matched controls. Med Sci (Basel) 2017; 5:. doi: 10.3390/medsci5010001.

This study utilizes three-dimensional motion capture to evaluate multiple gait trials of children with ASD compared to age matched typically developing children.

Copyright © 2018 Wolters Kluwe

1350-7540 Copyright � 2018 Wolters Kluwer Health, Inc. All rights rese

24. Kanner L. Autistic disturbances of affective contact. Nerv Child 1943; 2:217 – 250.

25. Wing L. Asperger’s syndrome: a clinical account. Psychol Med 1981; 11:115 – 129.

26. &

Eggleston D, Harry JR, Hickman RA, Dufek JS. Analysis of gait symmetry during over-ground walking in children with autism spectrum disorder. Gait Posture 2017; 55:162 – 166.

This study utilizes three dimensional motion capture to evaluate the entire gait cycle in children with ASD. 27. Mostofsky SH, Dubey P, Jerath VK, et al. Developmental dyspraxia is not

limited to imitation in children with autism spectrum disorders. J Int Neurop- sychol Soc 2006; 12:314 – 326.

28. &

Jarczok TA, Fritsch M, Kroger A, et al. Maturation of interhemispheric signal propagation in autism spectrum disorder and typically developing controls: a TMS-EEG study. J Neural Transm (Vienna) 2016; 123:925 – 935.

This study utilizes two neurodiagnostic measures to evaluate interhemispheric connections and better understand development and maturation of the corpus callosum in adolescents with ASD. 29. &

Kirkovski M, Rogasch NC, Saeki T, et al. Single pulse transcranial magnetic stimulation: electroencephalogram reveals no electrophysiological abnorm- ality in adults with high-functioning. J Child Adolesc Psychopharmacol 2016; 26:606 – 616.

This study utilizes two neurodiagnostic measures to evaluate cortical function and connectivity in adults with ASD. 30. &&

Floris DL, Barber AD, Nebel MB, et al. Atypical lateralization of motor circuit functional connectivity in children with autism is associated with motor deficits. Mol Autism 2016; 7:35.

This study utilized functional MRI to study whether the functional motor execution network shows an atypical pattern of hemispheric specialization in ASD. 31. &&

Ewen JB, Lakshmanan BM, Pillai AS, et al. Decreased modulation of EEG oscillations in high-functioning autism during a motor control task. Front Hum Neurosci 2016; 10:198.

This study utilizes EEG to evaluate if there is abnormal oscillatory modulation during a praxis task, which is a motor domain that has been frequently implicated in the ASD phenotype. 32. Jeste SS, Frohlich J, Loo SK. Electrophysiological biomarkers of diagnosis

and outcome in neurodevelopmental disorders. Curr Opin Neurol 2015; 28:110 – 116.

33. Mohammad-Rezazadeh I, Frohlich J, Loo SK, Jeste SS. Brain connectivity in autism spectrum disorder. Curr Opin Neurol 2016; 29:137 – 147.

34. Khanna P, Carmena JM. Beta band oscillations in motor cortex reflect neural population signals that delay movement onset. Elife 2017; 6:1 – 31.

35. Mahajan R, Mostofsky SH. Neuroimaging endophenotypes in autism spec- trum disorder. CNS Spectr 2015; 20:412– 426.

36. &&

Marrus N, Eggebrecht AT, Todorov A, et al. Walking, gross motor develop- ment, and brain functional connectivity in infants and toddlers. Cereb Cortex 2018; 28(2):750 – 763.

This study utlizes functional MRI to evaluate the relationship between functional connectivity and the emergence of gross motor function 37. &&

Thompson A, Murphy D, Acqua FD, et al. Archival report impaired commu- nication between the motor and somatosensory homunculus is associated with poor manual dexterity in autism spectrum disorder. Biol Psychiatry 2017; 81:211 – 219.

This study utilizes diffusion tensor imaging to evaluate sensory input to the primary motor cortex from the somatosensory cortex and the possibility of alternations in this network leading to fine motor impairments in adults with ASD. 38. &

Jones R, Downing K, Rinehart N. A systematic review of physical activity and sedentary behavior in children with Autism. PLoS One 2017; 12:e0172482.

This review highlights the prevalence of decreased physical activity in individuals with ASD and how this can lead to sedentary behaviors and contribute to harmful health outcomes. 39. Makrygianni MK, Reed P. A meta-analytic review of the effectiveness of

behavioural early intervention programs for children with Autistic Spectrum Disorders. Res Autism Spectr Disord 2010; 4:577 – 593.

40. Bremer E, Crozier M, Lloyd M. A systematic review of the behavioural out- comes following exercise interventions for children and youth with autism spectrum disorder. Autism 2016; 20:899– 915.

41. Tamara May. Lisa Barnett. Trina Hinkley, et al. We’re doing afl auskick as well’: experiences of an adapted football program for children with autism. J Mot Learn Dev 2016; 1 – 29; https://journals.humankinetics.com/doi/abs/ 10.1123/jmld.2016-0055.

r Health, Inc. All rights reserved.

rved. www.co-neurology.com 139

BRIEF REPORT

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

Introduction

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]

1 Centre for Rehabilitation, Oxford Brookes University,

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

UK

2 Department of Child and Adolescent Psychiatry, Institute of

Psychiatry, Psychology and Neuroscience, King’s College

London, London, UK

3 Department of Psychology, Institute of Psychiatry,

Psychology and Neuroscience, King’s College London,

London, UK

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

Partners, London, UK

5 NIHR Biomedical Research Centre for Mental Health,

Institute of Psychiatry, Psychology and Neuroscience, King’s

College London, London, UK

123

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.

Methods

The study was approved by the South East Multicentre

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

gave informed consent for participation.

Participants

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 1

(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

score 2

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)

1 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. 2 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

123

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.

Measures

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

123

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

used).

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

disability. 3

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).

Results

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].

3 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

papers.

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

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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

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Discussion

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

SEN

(N = 72)

ASD

(N = 116)

Chi-Sqaure/

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

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

SEN

(N = 72)

ASD

(N = 116)

Chi-sqaure/Fisher’s

exact

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

cold

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

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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 severity (as measured by the ADOS

whereas we included history from the ADI-R and ADOS).

We did not explore sensory subtypes but other studies have

found individual sensory subtypes e.g. tactile responsive-

ness patterns in ASD, to be only weakly (or not at all)

correlated with repetitive behaviours and extent of social

impairment (Foss-Feig et al. 2012). Some aspects of

atypical sensory behaviours, e.g. sensory interests, in ASD

may be an expression of positive absorption in a detail of

the environment similar to other restricted and repetitive

behaviours.

Our finding of an association between atypical sensory

behaviours and increased emotional symptoms in ASD is

consistent with the literature showing a potential link

between sensory symptoms and anxiety (Lane et al. 2012)

and depression (Bitsika et al. 2016) although the direction

of effect is not known. Further research is required for a

better understanding of the inter-relationship between aut-

ism, comorbidities and sensory symptoms and, how these

may change over time (Chen et al. 2009; McCormick et al.

2015). Anecdotally, many sensory symptoms persist into

adult life and continue to have a significant impact on

individuals.

Assessing sensory behaviours is limited by the current

methods available, usually through questionnaires com-

pleted by parent or carers or individuals themselves rather

than objective measures (Tavassoli et al. 2016). The SSP

has been widely used clinically and in research studies but

for some items the face validity as a ‘sensory’ behaviour is

unclear e.g. ‘Has a weak grasp’. Some clinically important

items are not recorded in the SSP, for example lack of

response to pain and lack of awareness of temperature,

which are hypo-responsivities frequently commented on by

parents. Thus, for this study we used complete SSP

domains for hypersensitivity but for hyposensitivity, one

domain and two items met face validity as representing

Table 4 Multiple regression results for Short Sensory Profile

Total Scores and features of

Autism and behavioural factors

as report on the parent SDQ

Coefficient t 95 % CI p

Full scales

F(6108) = 6.50, p .001, R2 = .224 IQ .150 1.58 -.038, .337 .117

ADOS age years -.235 -0.10 -4.92, 4.45 .921

ICD 10 total -.066 -0.06 -2.34, 2.20 .954

ADI-R total -.709 -3.42 -1.12, -.298 .001

ADOS G total .370 0.90 -.448, 1.19 .372

SDQ total -1.58 -3.79 -2.40, -.752 .001 Subscales

F(10,101) = 3.41, p .001, R2 = .253 ICD 10_social 2.20 0.91 -2.57, 6.96 .362

ICD 10 communication -1.87 -0.74 -6.83, 3.10 .458

ICD 10 repetitive -5.50 -2.18 -10.5, -.510 .031

SDQ emotional -2.54 -2.96 -4.24, -.834 .004

SDQ conduct -1.18 -1.21 -3/12, .750 .228

SDQ peer relations -1.70 -1.45 -4.03, .621 .149

SDQ hyperactivity -.038 -0.04 -2.09, 2.01 .971

SDQ pro-social -.043 -0.05 -1.87, 1.79 .963

CI confidence interval; Rfsiq Raven’s full scale IQ; ADOS Autistic Diagnostic Observation Scale-Generic;

ICD International Classification of Diseases; SDQ Strengths and Difficulties Questionnaire

3604 J Autism Dev Disord (2016) 46:3597–3606

123

under-responsiveness to sensory stimuli. This aspect of

behaviour may therefore have been underestimated.

Strengths of the study are a well characterised sample, the

use of a recognised sensory questionnaire and a comparison

group who have special educational needs and are a group

in which ASD is often considered as a differential

diagnosis.

In summary, the inclusion of hyper-or hypo respon-

sivity or sensory interests within the ASD diagnostic cri-

teria of DSM-5 is supported. However, comparison of

children with ASD to those with SEN affirms the finding

that young people with other developmental disorders may

also demonstrate altered sensory responsivity. In ASD

altered sensory function was associated with emotional

problems and restricted repetitive behaviours. It remains to

be seen if the profile of sensory responsivities differs

between neurodevelopmental disorders, how these may

differentially impact on function and participation and how

these may change over time.

Acknowledgments We are grateful to the children and families and the clinical teams in South Thames, whose participation and collab-

oration made the study possible.

Funding This study was funded by the Wellcome Trust and the Department of Health (Grant Number 039/0026).

Author Contributions All of the individuals listed as authors on this manuscript contributed to the study design, data collection and or data

analysis along with manuscript preparation. All authors have read the

manuscript and agreed to its submission for publication. All authors

meet the appropriate authorship criteria, nobody who qualifies for

authorship has been omitted, all contributors and funding sources

have been properly acknowledged, and authors and contributors have

approved the acknowledgement of their contributions.

Compliance with Ethical Standards

Conflict of interest Dr Green declares that she has no conflict of interest. Dr Chandler declares that she has no conflict of interest. Prof

Charman declares that he has no conflict of interest. Prof Simonoff

declares that she has no conflict of interest. Prof Baird declares that

she has no conflict of interest.

Ethical Approval All procedures performed in studies involving human participants were in accordance with the ethical standards of

the institutional and/or national research committee and with the 1964

Helsinki declaration and its later amendments or comparable ethical

standards.

Informed Consent Informed consent was obtained from all parents for their and their child’s participation in the study.

References

American Psychiatric Association (APA). (1980). Diagnostic and

statistical manual of mental disorders DSM-III (3rd ed.).

Washington, DC: American Psychiatric Association.

American Psychiatric Association (APA). (1987). Diagnostic and

statistical manual of mental disorders III-R. Washington, DC:

American Psychiatric Association.

American Psychiatric Association (APA). (1994). Diagnostic and

statistical manual of mental disorders (DSM-IV) (4th ed.).

Washington, DC: American Psychiatric Association.

American Psychiatric Association (APA). (2013). Diagnostic and

statistical manual of mental disorders (DSM-V) (5th ed.).

Washington, DC: American Psychiatric Association.

Asperger, H. (1944). Autistic Psychopathy in Children. Autism and

Asperger syndrome (U. Frith, Trans.). Cambridge: Cambridge

University Press. (1991).

Ausderau, K., Sideris, J., Furlong, M., Little, L. M., Buluck, J., &

Baranek, G. T. (2014). National survey of sensory features in

children with ASD: Factor structure of the sensory experience

questionnaire (3.0). Journal of Autism and Developmental

Disorders, 44, 915–925. doi:10.1007/s10803-013-1945-1.

Baird, G., Simonoff, E., Pickles, A., Chandler, S., Loucas, T.,

Meldrum, D., et al. (2006). Prevalence of disorders of the autism

spectrum in a population cohort of children in South Thames: the

Special Needs and Autism Project (SNAP). The Lancet,

368(9531), 210–215. doi:10.1016/S0140-6736(06)69041-7.

Ben-Sasson, A., Cermak, S. A., Orsmond, G. I., Carter, A. S., & Fogg,

L. (2008). Can we differentiate sensory over-responsivity from

anxiety symptoms in toddlers? Perspectives of occupational

therapists and psychologists. Infant Mental Health Journal, 28,

536–558. doi:10.1002/imhj.20152.

Ben-Sasson, A., Hen, L., Fluss, R., Cermak, S. A., Engel-Yeger, B., &

Gal, E. (2009). A meta-analysis of sensory modulation symp-

toms in individuals with autism spectrum disorders. Journal of

Autism and Developmental Disorders, 39(1), 1–11. doi:10.1007/

s10803-008-0593-3.

Bitsika, V., Sharpley, C. F., & Mills, R. (2016). Are sensory

processing features associated with depressive symptoms in boys

with an ASD? Journal of Autism and Developmental Disorders,

46, 242–252. doi:10.1007/s10803-015-2569-4.

Boyd, B. A., Baranek, G. T., Sideris, J., Poe, M. D., Watson, L. R.,

Patten, E., et al. (2010). Sensory features and repetitive

behaviors in children with autism and developmental delays.

Autism Research, 3(2), 78–87. doi:10.1002/aur.124.

Chen, Y. H., Rodgers, J., & McConachie, H. (2009). Restricted and

repetitive behaviours, sensory processing and cognitive style in

children with autism spectrum disorders. Journal of Autism and

Developmental Disorders, 39, 635–642. doi:10.1007/s10803-

008-0663-6.

Dar, R., Kahn, D. T., & Carmeli, R. (2012). The relationship between

sensory processing, childhood rituals and obsessive–compulsive

symptoms. Journal of Behavior Therapy and Experimental

Psychiatry, 43(1), 679–684. doi:10.1016/j.jbtep.2011.09.008.

Dunn, W. (1999). The sensory profile manual. San Antonio, TX:

Psychological Corporation.

Foss-Feig, J. H., Heacock, J. L., & Cascio, C. J. (2012). Tactile

responsiveness patterns and their association with core features

in autism spectrum disorders. Research in Autism Spectrum

Disorders, 6(1), 337–344. doi:10.1016/j.rasd.2011.06.007.

Goodman, R. (1997). The Strengths and Difficulties Questionnaire: a research note. Journal of Child Psychology and Psychiatry,

38(5), 581–586.

Goodman, R., Ford, T., Simmons, H., Gatward, R., & Meltzer, H.

(2000). Using the Strengths and Difficulties Questionnaire to

screen for child psychiatric disorders in a community sample.

British Journal of Psychiatry, 177, 534–539. doi:10.1080/

0954026021000046128.

Green, D., Beaton, L., Moore, D., Warren, L., Wick, V., & Sanford,

E. (2003). Efficacy of sensory integrative therapy for adults with

J Autism Dev Disord (2016) 46:3597–3606 3605

123

learning disabilities: Two single subject studies. British Journal

of Occupational Therapy, 66, 454–463.

Kanner, L. (1943). Autistic disturbances of affective contact. The

Nervous Child, 2, 217–250.

Lane, A. E., Molloy, C. A., & Bishop, S. L. (2014). Classification of

children with autism spectrum disorder by sensory subtype: A

case for sensory-based phenotypes. Autism Research, 7(3),

322–333. doi:10.1002/aur.1368.

Lane, S. H., Reynolds, S., & Dumenci, L. (2012). Sensory overre-

sponsivity and anxiety in typically developing children and

children with autism and attention deficit hyperactivity disorder:

cause or coexistence? American Journal of Occupational

Therapy, 66, 595–603. doi:10.5014/ajot.2012.004523.

Lane, A. E., Young, R. L., Baker, A. E., & Angley, M. T. (2010).

Sensory processing subtypes in autism: association with adaptive

behavior. Journal of Autism and Developmental Disorders, 40,

112–122. doi:10.1007/s10803-009-0840-2.

LeCouteur, A., Lord, C., & Rutter, M. (2003). The Autism Diagnostic

Interview-Revised (ADI-R). Los Angeles: Western Psychological

Corporation.

Leekam, S. R., Nieto, C., Libby, S. J., Wing, L., & Gould, J. (2007).

Describing the sensory abnormalities of children and adults with

autism. Journal of Autism and Developmental Disorders, 37(5),

894–910. doi:10.1007/s10803-006-0218-7.

Levit-Binnun, N., Davidovitch, M., & Golland, Y. (2013). Sensory

and motor secondary symptoms as indicators of brain vulnera-

bility. Journal of Neurodevelopmental Disorders, 5(1), 1. doi:10.

1186/1866-1955-5-26.

Lord, C., Risi, S., Lambrecht, L., Cook, E. H, Jr., Leventhal, B. L.,

DiLavore, P. C., et al. (2000). The Autism Diagnostic Obser-

vation Schedule—Generic: A standard measure of social and

communication deficits associated with the spectrum of autism.

Journal of Autism and Developmental Disorders, 30(3),

205–223. doi:10.1023/A:1005592401947.

Lord, C., Rutter, M., & Le Couteur, A. (1994). Autism Diagnostic

Interview-Revised: a revised version of a diagnostic interview

for caregivers of individuals with possible pervasive develop-

mental disorders. Journal of Autism and Developmental Disor-

ders, 24(5), 659–685.

Mandy, W. P., Charman, T., & Skuse, D. H. (2012). Testing the

construct validity of proposed criteria for DSM-5 autism

spectrum disorder. Journal of the American Academy of Child

and Adolescent Psychiatry, 51(1), 41–50. doi:10.1016/j.jaac.

2011.10.013.

McCormick, C., Hepburn, S., Young, G. S., & Rogers, S. J. (2015).

Sensory symptoms in children with autism spectrum disorder,

other developmental disorders and typical development: A

longitudinal study. Autism. doi:10.1177/1362361315599755.

McIntosh, D. N., Miller, L. J., Shyu, V., & Dunn, W. (1999b).

Development and validation of the short sensory profile. In W.

Dunn (Ed.), Sensory profile manual (pp. 59–73). San Antonio,

TX: Psychological Corporation.

McIntosh, D. N., Miller, L. J., Shyu, V., & Hagerman, R. J. (1999a).

Sensory-modulation disruption, electrodermal responses, and

functional behaviors. Developmental Medicine and Child Neu-

rology, 41(9), 608–615.

Raven, J. C., Court, J. H., & Raven, J. (1990a). Coloured progressive

matrices. Oxford, UK: Oxford University Press.

Raven, J. C., Court, J. H., & Raven, J. (1990b). Standard progressive

matrices. Oxford, UK: Oxford University Press.

Rutter, M., Bailey, A., & Lord, C. (2003). The social communication

questionnaire: Manual. Los Angeles: Western Psychological

Corporation.

Sparrow, S. S., Balla, D. A., & Cicchetti, D. V. (1984). Vineland

adaptive behavior scales. Circle Pines, MN: American Guidance

Service.

StataCorp, L. (2009). Stata version 11.0. College Station, TX:

StataCorp LP.

Tavassoli, T., Bellesheim, K., Siper, P. M., Wang, A. T., Halpern, D.,

Gorenstein, M., et al. (2016). Measuring sensory reactivity in

autism spectrum disorder: Application and simplification of a

clinician-administered sensory observation scale. Journal of

Autism and Developmental Disorders, 46(1), 287–293. doi:10.

1007/s10803-015-2578-3.

Tomchek, S. D., & Dunn, W. (2007). Sensory processing in children

with and without autism: A comparative study using the short

sensory profile. American Journal of Occupational Therapy,

61(2), 190–200. doi:10.5014/ajot.61.2.190.

Watling, R. L., Deitz, J., & White, O. (2001). Comparison of sensory

profile scores of young children with and without autism

spectrum disorders. American Journal of Occupational Therapy,

55(4), 416–423. doi:10.5014/ajot.55.4.416.

Wechsler, D. (1991). WISC-III: Wechsler intelligence scale for

children: Manual. London: Psychological Corporation.

Wigham, S., Rodgers, J., South, M., McConachie, H., & Freeston, M.

(2015). The interplay between sensory processing abnormalities,

intolerance of uncertainty, anxiety and restricted and repetitive

behaviours in autism spectrum disorder. Journal of Autism and

Developmental Disorders, 45(4), 943–952. doi:10.1007/s10803-

014-2248-x.

World Health Organization. (1993). The ICD-10 classification of

mental and behavioural disorders: Diagnosis criteria for

research (DCR-10). Geneva: World Health Organization.

Zachor, D. A., & Ben-Itzchak, E. (2014). The relationship between

clinical presentation and unusual sensory interests in autism

spectrum disorders: A preliminary investigation. Journal of

Autism and Developmental Disorders, 44(1), 229–235. doi:10.

1007/s10803-013-1867-y.

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

123

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