Difference or disorder? Cultural issues in understanding neurodevelopmental disorders.

Animal personality

Autism spectrum disorder (ASD) and specific language impairment (SLI) are two neurodevelopmental disorders characterized by deficits in verbal and nonverbal communication skills. These skills are thought to develop largely through implicit—or automatic—learning mechanisms. The aim of the current paper was to investigate the role of implicit learning abilities in the atypical development of communication skills in ASD and SLI. In the current study, we investigated Response Times (RTs) and Event Related Potentials (ERPs) during implicit learning on a Serial Reaction Time (SRT) task in a group of typically developing (TD) children (n = 17), a group of autistic children (n = 16), and a group of children with SLI (n = 13). Findings suggest that learning in both ASD and SLI are similar to that in TD. However, electrophysiological findings suggest that autistic children seem to rely mainly on more automatic processes (as reflected by an N2b component), whereas the children with SLI seem to rely on more controlled processes (as reflected by a P3 component). The TD children appear to use a combination of both learning mechanisms. These findings suggest that clinical interventions should aim at compensating for an implicit learning deficit in children with SLI, but not in children with ASD. Future research should focus on developmental differences in implicit learning and related neural correlates in TD, ASD, and SLI. Autism Res2018, 11: 1050–1061. © 2018 The Authors Autism Research published by International Society for Autism Research and Wiley Periodicals, Inc.Lay SummaryAutism and Specific Language Impairment (SLI) are two disorders characterized by problems in social communication and language. Social communication and language are believed to be learned in an automatic way. This is called “implicit learning.” We have found that implicit learning is intact in autism. However, in SLI there seems different brain activity during implicit learning. Maybe children with SLI learn differently, and maybe this different learning makes it more difficult for them to learn language.

BackgroundThe diagnostic boundaries between autism spectrum disorder (ASD) and specific language impairment (SLI) are not clear‐cut. Evidence of the lack of distinct boundaries between these disorders comes from research identifying a group of children who have pragmatic language difficulties that can be distinguished from those in children with SLI and those with ASD. These findings have led to the inclusion of a new diagnostic category, social (pragmatic) communication disorder (SPCD), in the Diagnostic and Statistical Manual of Mental Disorders‐5th Edition DSM‐5. While this new diagnostic category appears to capture a subgroup of children who may not have been recognised in the DSM‐IV, SPCD has been criticised due to a lack of empirical evidence, showing that the disorder is distinct from ASD in terms of aetiology, intervention, and prognosis.ObjectiveThe purpose of this paper was to summarise the literature that has investigated overlaps in the phenotypes of SLI, ASD, and SPCD. A secondary objective was to present a framework for the assessment and diagnosis of these three conditions.Method and ResultsIn this paper, we review the research that has examined overlaps in the aetiologies and phenotypes of ASD, SPCD, and SLI. While the results highlighted overlaps in the language profiles and autistic symptomatology, these three conditions could also be distinguished based on the severity of the social communication deficits and the absence of rigid and repetitive behaviour in strictly defined cases of SPCD and SLI.ConclusionsStrictly defined cases of SPCD and SLI can be distinguished from ASD. However, there is a lack of assessment tools that can reliably distinguish these three conditions. We consider the clinical implications of the findings and present a model of assessment and diagnosis for ASD, SLI, and SPCD.

Fragile X syndrome (FXS) is a neurogenetic syndrome characterized by cognitive impairments and high rates of autism spectrum disorder (ASD). FXS is often highlighted as a model for exploring pathways of symptom expression in ASD due to the high prevalence of ASD symptoms in this population and the known single-gene cause of FXS. Early vocalization features-including volubility, complexity, duration, and pitch-have shown promise in detecting ASD in idiopathic ASD populations but have yet to be extensively studied in a population with a known genetic cause for ASD such as FXS. Investigating early trajectories of these features in FXS may inform our limited knowledge of potential mechanisms that predict later social communication outcomes. The present study addresses this need by presenting preliminary findings which (a) characterize early vocalization features in FXS relative to low-risk controls (LRC) and (b) test the specificity of associations between these features and language and ASD outcomes. We coded vocalization features during a standardized child-examiner interaction for 39 nine-month-olds (22 FXS, 17 LRC) whose clinical outcomes were assessed at 24 months. Our results provide preliminary evidence that within FXS, associations between vocalization features and 24-month language outcomes may diverge from those observed in LRC, and that vocalization features may be associated with later ASD symptoms. These findings provide a starting point for more research exploring these features as potential early markers of ASD in FXS, which in turn may lead to improved early identification methods, treatment approaches, and overall well-being of individuals with ASD. Autism Res2019. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Although vocal features of 9-month-olds with FXS did not differ from those of low-risk controls, several features were associated with later language and ASD outcomes at 24 months in FXS. These preliminary results suggest acoustic data may be related to clinical outcomes in FXS and potentially other high-risk populations. Further characterizing these associations may facilitate understanding of biological mechanisms and risk factors associated with social communication development and ASD.

While autism spectrum disorder (ASD) and specific language impairment (SLI) have traditionally been conceptualized as distinct disorders, recent findings indicate that the boundaries between these two conditions are not clear-cut. While considerable research has investigated overlap in the linguistic characteristics of ASD and SLI, relatively less research has explored possible overlap in the socio-cognitive domain, particularly in terms of the emotion recognition abilities of these two groups of children. To investigate facial and vocal emotion recognition in children with ASD, children with SLI and typically developing (TD) children. To do so, the ASD group was subdivided into those with 'normal' (ALN) and those with 'impaired' (ALI) language to explore the extent to which language ability influenced performance on the emotion recognition task. Twenty-nine children with ASD (17 ALN and 12 ALI), 18 children with SLI and 66 TD children completed visual and auditory versions of an emotion recognition task. For the visual version of the task, the participants saw photographs of people expressing one of six emotions (happy, sad, scared, angry, surprised, disgusted) on the whole face. For the auditory modality, the participants heard a neutral sentence that conveyed one of the six emotional expressions in the tone of the voice. In both conditions, the children were required to indicate how the person they could see/hear was feeling by selecting a cartoon face that was presented on the computer screen. The results showed that all clinical groups were less accurate than the TD children when identifying emotions on the face and in the voice. While the ALN children were less accurate than the TD children only when identifying expressions that require inferring another's mental state (surprise, disgust) emotional expressions, the ALI and the SLI children were less accurate than the TD children when identifying the basic (happy, sad, scared, angry) as well as the inferred emotions. The results indicate that children with ALI and children with SLI share emotion recognition deficits, which are likely to be driven by the poor language abilities of these two groups.

But they do! In ethology individual differences in behaviour have traditionally been ignored, treated as white noise (Ringler 1983) or, as Arak (1984) points out, considered to be maladaptive deviations from optimal strategies. Many classical ethology textbooks proceed with the implicit assumption that intraspecific differences in behaviour are less important and less interesting than differences between species. Fish behaviour, where most students begin by looking at the stereotyped response of the breeding male stickleback (Gasterosteus aculeatus) to things coloured red (Tinbergen 1951), is no exception. Closer inspection, however, reveals pronounced individual differences in the rate at which male sticklebacks attack red dummies (Rowland 1982).

Parr et al. report on a study of autism and autistic-like behaviour in children with optic nerve hypoplasia and/or septo-optic dysplasia.1 The paper mainly addresses two important, and still controversial topics: (1) autism in visually impaired children; and (2) methods for assessing development and autism in visually impaired children. The most commonly reported developmental disorder in blind children is autism. The possible factors accounting for this have been discussed over the years, ever since blindness and autism was first described by Keeler in 1958. Cass discussed the strong evidence that neurological disorders play a major part in deviant development and autism and stated: ‘A phenomenon with such a remarkably high prevalence among the visually impaired population might be expected to arouse a considerable concern among parents, educators, therapists and doctors, and yet it has received relatively little attention in the literature’ (p 118).2 Optic nerve hypoplasia is now a leading cause of vision loss in young children, a six-fold increase has been reported since 1977 and is now estimated at 10.9 per 100 000.3 Several authors have reported high frequencies of autism and developmental disorders in children with optic nerve hypoplasia. Tornqvist et al.4 reported additional impairments in 63% of a Swedish population. Our group5 reported six children with autism and three with an autistic-like condition, with high frequencies of hormonal deficiencies and midline malformations (shown on computed tomography or magnetic resonance imaging), in a group of 13 blind children. In a prospective study focusing on neuroradiographic, endocrinological, and ophthalmic correlates of adverse developmental outcome, developmental delay was found in 71% of a population of 73 children.3 Hypoplasia of the corpus callosum was highly correlated with deficiencies in the areas of personal, adaptive, communication, and cognitive functioning as well as with the overall development of the children. In cases of hypothyroidism, 93% had overall delay at the age of 5.3 The study by Parr et al. describes a large population (n=83) with severe or profound visual impairment. This is very unusual in studies of a specific ophthalmologic group like this; normally we have to be satisfied with much smaller groups. The main weakness, however, is the retrospective design of the study. Over the study period (1977–2009) our knowledge of developmental disorders in visually impaired children and the methods for assessing it have changed. The retrospective study of case notes, estimating behaviour disorders and cognitive performance during one clinic visit, is questionable. These methods most certainly underestimate the true rate of autism spectrum disorders. Furthermore, it is not stated how many children in the study were blind (no light perception). Blindness in combination with brain disorder poses a definite risk of autism. Intelligence testing in blind children is difficult and the problem has received extensive study. Few modern, well-standardized tests for visually impaired children are available. As the panorama of visual impairment has changed over the years, with more children now being diagnosed as visually impaired owing to causes affecting the posterior visual pathways and the brain, these norms are not accurate. Instead, we need in-depth clinical assessments using a variety of methods. The test performance by itself should be only one measure of intellectual ability. Observations of behaviour as well as teachers’ and parents’ reports and interviews are equally important. The assessment of autism in blind children is a delicate process. The most common methods for scoring autistic behaviour include several items dependant on vision. Furthermore, no agreement has been reached as to distinguishing blindisms (stereotype, repetitive behaviour commonly found in blind children) from autism. The Autism Diagnostic Interview6 is a comprehensive interview with parents that is useful also in blind children. Hypothyroidism and hypoplasia of the corpus callosum are reported to be associated with developmental delay and autism. We look forward to the next paper by Parr et al. reporting their findings on imaging and hormonal data in this study group.

BackgroundWidespread use of microarray technology has led to increasing identification of 22q11.2 duplication syndrome (22q11.2DupS), the reciprocal syndrome of the well-characterized 22q11.2 deletion syndrome (22q11.2DS). Individuals with 22q11.2DS have elevated rates of community diagnoses of autism spectrum disorder (ASD), schizophrenia, and a range of medical problems and birth defects that necessitate extensive medical screening. Case reports of 22q11.2DupS include patients with ASD, fewer medical problems, and no schizophrenia; however, no prospective cohort study has been reported. The goals of the study were to (1) characterize the neuropsychiatric functioning of a cohort of individuals with 22q11.2DupS in comparison to large samples of typically developing controls (TDCs), ASD and 22q11.2DS; (2) estimate the prevalence of ASD in 22q11.2DupS; (3) determine whether the indications that prompted the genetic testing in 22q11.2DupS differ from 22q11.2DS and (4) determine whether comprehensive medical screening should be recommended for those diagnosed with 22q11.2DupS.MethodsMedical characterization was done by parental questionnaire and medical chart review of individuals with 22q11.2DupS (n = 37) and 22q11.2DS (n = 101). Neuropsychiatric characterization of children with 22.11.2DupS, 22q11.2DS, TDCs, and ASD was done by parent-report questionnaires; in addition, the ASD and 22q11.2DupS groups received the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule.ResultsIndividuals with 22q11.2DupS, 22q11.2DS, and ASD had significantly impaired social interaction and adaptive behavior skills compared to TDCs. Overall, 38 % of children aged 2–18 with 22q11.2DupS had community diagnoses of ASD, but fewer (14–25 %) met on the basis of best clinical judgment that included ADI-R and ADOS data. Indications for genetic testing were significantly different for 22q11.2DupS and 22q11.2DS, with the deletions more commonly tested because of birth defects or medical problems, and the duplications because of developmental delay. However, when the screening protocol for 22q11.2DS was applied to the 22q11.2DupS sample, several medical problems were identified that would pose significant risk if left undetected.Conclusions22q11.2DupS has a high rate of ASD at 14–25 %, among the highest of any genetic disorder. Prospective medical screening should be done for all patients with 22q11.2DupS, including those diagnosed due to developmental delays and ASD alone.Electronic supplementary materialThe online version of this article (doi:10.1186/s13229-016-0090-z) contains supplementary material, which is available to authorized users.

BackgroundThe incidence rate of autism spectrum disorders (ASDs) has been rising; this study aimed to explore the relationship between nutritional intake and neurodevelopment in children with ASDs.MethodsThis study is a case–control cross-sectional comparison including 50 children with ASDs and 50 typically developing controls. A total of 500 children with neurodevelopmental disorders and 500 typically developing (TD) children were recruited based on clinical diagnosis to compare levels of inflammation. Among them, 50 children were diagnosed with ASDs based on DSM-5 criteria by experienced developmental behavioral pediatricians. A total of 50 typically developing children were matched with the 50 children with ASDs. Dietary surveys, Autism Diagnostic Observation Schedule (ADOS), and physical development evaluations were conducted on these 100 children.ResultsThe children’s dietary inflammatory index (C-DII), systemic immune inflammatory index (SII), and systemic inflammatory response index (SIRI) in the ASD group were significantly higher compared to the TD group (p<0.05). A positive correlation was observed between C-DII and SII (r = 0.323, p = 0.022), as well as SIRI (r = 0.283, p = 0.046). The dietary diversity in the ASD group was lower than that of the TD group, with a higher prevalence of picky eating behaviors in the ASD group. After adjusting for demographic characteristics, the C-DII may be correlated with ASD [odds ratio (OR) = 1.842, 95% confidence interval (CI) = 1.114 ~ 3.046, p = 0.017].ConclusionChildren with autism spectrum disorders (ASD) displayed higher C-DII scores. The results of this study suggest that there may be a correlation between C-DII and the neurodevelopment of children with ASD, not causality. Inflammatory dietary patterns may represent a modifiable factor linked to neurodevelopmental outcomes.

We hypothesize that Duchenne muscular dystrophy and autism spectrum disorder/pervasive developmental disorder co-occur with a greater than random frequency. In this study, we set out to reject the hypothesis that Duchenne muscular dystrophy and autism spectrum disorder/pervasive developmental disorder co-occur no more often than expected by chance. Two index cases and six additional boys with concomitant Duchenne muscular dystrophy and autism spectrum disorder were identified in a muscular dystrophy clinic that approximates the total number of Duchenne muscular dystrophy boys (158) in the state of Massachusetts. The rate of prevalence (6 of 158) was compared with the prevalence rate of autism spectrum disorder in boys in the general population (1.6 in 1,000). We rejected the hypothesis that Duchenne muscular dystrophy and autism spectrum disorder co-occurrence was likely to be explained by chance (P = .006). We identify a previously unrecognized association of Duchenne muscular dystrophy with autism spectrum disorder. Further work might elucidate the level of association between these two conditions, either at the genetic or at the protein level, and might clarify, at least partially, the neurobiologic mechanisms associated with autism spectrum disorder.

The present research aims to investigate the kinetic profile of Greek school children (6-12 years old) with Dyslexia & Specific Language Impairment (SLI) using the Movement Assessment Battery for Children, MABC-2, and tool as compared with children in formal education and assess any differences in kinetic profile among subgroups of such children. Participants were two groups of children of which 36 comprised the first group and were diagnosed, either by a Center for Differential Diagnosis, Diagnosis and Support (KE.D.D.Y.) or Psychodiagnostic Centers for Special Educational Needs, as children with Dyslexia & Specific Language Impairment (SLI) (average age: 112.05 months). The second group comprised 51 children of the same sex and age without any developmental disorder (average age: 114.55 months). The research was conducted individually at the Center for Differential Diagnosis, Diagnosis and Support (KE.D.D.Y.) Thessaloniki II, as well as in Primary and Secondary Schools in the Prefecture of Serres. Statistical analysis was performed by means of two-way analysis of variance (ANOVA) and the results established statistically significant differences in the general motor score of Movement Assessment Battery for Children (MABC-2) between the group of children with Dyslexia & Specific Language Impairment (SLI) and the group of children in formal education. In addition, ANOVA established significant differences in hand dexterity, ball skills and balance between the two groups of children with dyslexia & Specific Language Impairment (SLI) and the group of children in formal education. Further analysis established that no significant differences in the general motor score of the test were exhibited among children with Dyslexia & Specific Language Impairment (SLI). Specifically, the group of children with Dyslexia & SLI in our research exhibits Developmental coordination disorder (DCD) at a rate (44%) as opposed to children of typical development who exhibit a much lower percentage (12%). Even within the group of Dyslexia & SLI exhibits a DCD, a percentage of children exhibit a DCD risk (22%) while the remainder (33%) does not exhibit any difficulties. On the contrary, children of atypical development exhibit much lower rates, i.e. there is a DCD risk percentage (12%) and another (78%) exhibiting no DCD at all. Within this research framework, the view supported by the contemporary international literature that movement disorders often coexist with Specific Learning Difficulties is established.

Although the prevalence rate of Autism Spectrum Disorders (ASD) varies, recent figures suggest that close to 1% of children (Autism Society Canada, 2009; CDC, 2006) are identified with ASD. With inclusive philosophies paving the way for education in mainstream classrooms, attention must be given to equitable opportunities and practices for this growing population in our school systems (Killoran & Adams, 2006; Sapon-Shevin, 2003; United Nations, 2006). The research on inclusion and children with ASD is fairly limited; however, it has shown that in some regions at least, these students are excluded from school at a “significantly higher rate than students with other [special education needs]” (Humphrey & Lewis, 2008, p. 132). Children with ASD are “considered more difficult to include effectively than those with other SEN” (Humphrey & Lewis, 2008, p. 133). While there is much diversity with respect to strengths, abilities, functional levels and challenges among children with ASD, a core set of universal concerns exist. Some of these include sensory responsiveness, communication, and socialization. This chapter will focus on creating a sensory responsive environment, developing effective verbal and/or non-verbal communication, and fostering genuine relationships. Using the three main principles of Universal Design for Learning (UDL) as an overarching assumption, this chapter will explore how educators can provide effective opportunities for multiple means of representation, expression, and engagement to address common areas of need (CAST, 2011; Hehir, 2009). By following these principles, an educator is able to create a community that welcomes all while addressing students’ specific needs. Many educators have been overwhelmed with the past practice of individualization in isolation, a task that left many students alone and disconnected from their peers. The current practices of differentiation and universal design for learning enable educators to plan for their students in such a way that all are integral, contributing, valued members of the learning community. This chapter provides a synthesis of current research on evidence-based classroom interventions and accommodations for learners with ASD in inclusive settings, at all age levels, with respect to sensory environments, assisted communication, and facilitation of social relationships. Emphasis is placed on accommodations that meet UDL requirements. A comprehensive search of the Education Resources Information Center (ERIC) database was conducted using keywords for, and related to, autism, universal design for learning and

Resting metabolic rate (RMR) is highly variable between individuals within a single species and the relationship between body mass and RMR does not wholly explain this variability. One factor that could account for a portion of the residual variation is animal personality or consistent individual differences (CIDs) in behaviour, but no study has examined this relationship in a free-living population of mammals. In this paper, we test for a relationship between RMR and CIDs in activity in live-trapped meadow voles Microtus pennsylvanicus after controlling for the effect of body mass. We quantified the activity levels of voles both in an unfamiliar environment and for the first 2 min in the metabolic apparatus, and then measured RMR using open-flow respirometry. As expected, there was a linear relationship between RMR and body mass, and we found strong evidence for repeatable differences in activity levels between individuals. However, contrary to the hypothesis, we did not identify a significant correlation between CIDs in behaviour and RMR after controlling for body mass. Our results suggest that, at least within species, higher activity levels may not require a greater investment in energetically demanding tissues or increased capacity for processing of energy. Alternatively, if a relationship exists, our inability to detect it may reflect a weak behavioural signal in noisy RMR data that are influenced by many factors. Our results could also reflect an artefact of individual responses to stress or a sampling bias towards more exploratory individuals in animals captured by live-trapping.

Consistent individual differences in parenting are widespread; however, we know little about why there is variation in parenting behavior among individuals within species. One possible explanation for consistent individual differences in parenting is that individuals invest in different aspects of parental care, such as provisioning or defense. In this field study we measured consistent individual differences in parenting behavior and evaluated correlations between parenting and other behaviors in threespine stickleback (Gasterosteus aculeatus). We repeatedly measured male parenting behavior and male behavior in the presence of three different types of live intruders: a female, a conspecific male, and a predator, meant to provoke courtship, aggressive and antipredator behavior, respectively. While males plastically adjusted their reactions to different types of intruders, we found consistent individual differences in behavior (behavioral types) both within and across contexts, even after accounting for variation in body size and nest characteristics. Males that performed more parenting behavior responded faster to all types of intruders. These results suggest that in nature, individual male stickleback exhibit robust parental behavioral types, and highly parental males are more attentive to their surroundings. Future studies are needed to examine the potential causes of individual variation in parental behavior in the field.

Fish play an important role in the culture of Japan, supplying the primary source of food protein. Research on fish ecology in Japan began developing about 1955, and paralleled that in North America and Europe, but has a number of unique differences. Two main research foci, stream fish ecology and ecology of Lake Biwa, were founded by H. Kawanabe and his colleagues while graduate students in D. Miyadi’s laboratory at Kyoto University in the 1950s. The focus on studies of individual differences in ecology, life history, and behavior by direct observation that were developed in this laboratory had a pervasive influence on research that has continued to the present. In the 1980s, Kawanabe, who had succeeded Miyadi as laboratory head, also co-organized a major research project on the complex communities of cichlid fishes in Lake Tanganyika, which has involved nearly every major Japanese investigator in fish ecology since. A review of research conducted by Japanese investigators in stream fish ecology, ecology of fishes in lakes Biwa and Tanganyika, and marine reef fish ecology revealed a wealth of literature of which most English-speaking fish ecologists are unaware. The most striking difference between Western and Japanese research is the focus on detailed observations and experiments in natural habitats of individual differences in behavior, life history, and ecology, and how these ultimately affect processes at the population and community level, as amply demonstrated by Kawanabe’s early work on ayu, Plecoglossus altivelis. This approach predated by 20–30 years the current interest in individual differences and individual-based models in North America and Europe.