An investigation of the potential association between mercury and Autism Spectrum Disorder: an interdisciplinary approach

 Dr Shandley took a novel approach to investigate the mercury-autism hypothesis. Her studies unearthed conflicting results. Contrary to previous biological studies, autistic children did not demonstrate a pattern of mercury toxicity. However, in a world first study, Dr Shandley found that the rate of autism among children with a family history of mercury sensitivity was 6-7 times higher than the general population.

Autism spectrum disorder symptoms in children with ADHD: a community-based study

This study examined the prevalence of autism spectrum disorder (ASD) symptoms in a community-based sample of children with attention-deficit/hyperactivity disorder (ADHD) and non-ADHD controls. We also examined the relationship between ASD symptoms and ADHD subtype, ADHD symptom severity and child gender. Participants were 6-10-year-old children (164 ADHD; 198 non-ADHD control) attending 43 schools in Melbourne, Australia, who were participating in the Children's Attention Project. ADHD was assessed in two stages using the parent and teacher Conners' 3 ADHD index and the Diagnostic Interview Schedule for Children IV (DISC-IV). ASD symptoms were identified using the Social Communication Questionnaire (SCQ). Unadjusted and adjusted linear and logistic regression examined continuous and categorical outcomes, respectively. Children with ADHD had more ASD symptoms than non-ADHD controls (adjusted mean difference=4.0, 95% confidence interval (CI) 2.8; 5.3, p<0.001, effect size=0.7). Boys with ADHD had greater ASD symptom severity than girls with ADHD (adjusted mean difference=2.9, 95% CI 0.8; 5.2, p=0.01, effect size=0.4). Greater ADHD symptom severity was associated with greater ASD symptom severity (regression co-efficient=1.6, 95% CI 1.2; 2.0, p<0.001). No differences were observed by ADHD subtype. Greater hyperactive/impulsive symptoms were associated with greater ASD symptoms (regression coefficient=1.0; 95% CI 0.0; 2.0, p=0.04) however, this finding attenuated in adjusted analyses (p=0.45). ASD symptoms are common in children with ADHD. It is important for clinicians to assess for ASD symptoms to ensure appropriate intervention.

Attentional mechanisms in Autism, ADHD, and Autism-ADHD using a local-global paradigm

OBJECTIVE: Cognitive flexibility or attentional set-shifting capacity has long been considered a core area of executive dysfunction for individuals with autism. Whether these difficulties are due to higher-level attentional difficulties associated with comorbid ADHD remains unclear. METHOD: The current study compared the performance of 48 participants with autism, ADHD, autism-ADHD, and a comparison group (N = 12 per group) on a set-shifting task, which included a local-global paradigm. RESULTS: Results of this study revealed that participants with attentional difficulties (autism + ADHD and ADHD alone) exhibited a significant shifting cost (difference between maintaining and shifting attention). CONCLUSION: Attentional difficulties associated with ADHD may be associated with an enhanced attentional shifting cost. Implications of these results were discussed in relation to screening for ADHD symptoms in studies of individuals with autism which seek to determine the neuropsychological profile of this condition.

Mechanisms of anxiety related attentional biases in children with Autism Spectrum Disorder

Children with autism spectrum disorder (ASD) have high levels of anxiety. It is unclear whether they exhibit threat-related attentional biases commensurate with anxiety disorders as manifest in non-ASD populations, such as facilitated attention toward, and difficulties disengaging engaging from, threatening stimuli. Ninety children, 45 cognitively able with ASD and 45 age, perceptual-IQ, and gender matched typically developing children, aged 7–12 years, were administered a visual dot probe task using threatening facial pictures. Parent-reported anxiety symptoms were also collected. Children with ASD showed similarly high levels of anxiety compared with normative data from an anxiety disordered sample. Children with ASD had higher levels of parent-reported anxiety but did not show differences in disengaging from, or facilitated attention toward, threatening facial stimuli compared with typically developing children. In contrast to previously published studies of anxious children, in this study there were no differences in attentional biases in children with ASD meeting clinical cutoff for anxiety and those who did not. There were no correlations between attentional biases and anxiety symptoms and no gender differences. These findings indicate the cognitive mechanisms underlying anxiety in cognitively able children with ASD could differ from those commonly found in anxious children which may have implications for both understanding the aetiology of anxiety in ASD and for anxiety interventions

Motor functioning in autism spectrum disorders

Motor impairment is consistently reported in autism spectrum disorders (ASD) and may be an early risk factor for core ASD symptomatology. This chapter provides an overview of empirical motor studies in ASD and considers clinical, behavioral, neurophysiological, and neuroimaging studies of motor impairment in ASD. The association between motor impairment and core social communication disturbance is also explored, as well as the high comorbidity between ASD, motor impairment, and other neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD). Future research which aims to understand the specific motor pattern that may characterize ASD is suggested.

Alongside the core diagnostic features of autism, research has highlighted the significant and pervasive impact of motor dysfunction in autism spectrum disorders (ASD) (Fournier et al., J Autism Dev Disord 40(10):1227–40, 2010). Motor difficulties are commonly associated with ASD and potentially may be considered a “cardinal feature” (Fournier et al., J Autism Dev Disord 40(10):1227–40, 2010) of the disorder. Indeed, there has been an increase in the trajectory of motor research over the past decade, with greater understanding of the underlying neurobiological disruption that characterizes the disorder (Mostofsky et al., Brain 132:2413–25, 2009). This chapter will illustrate the importance of neuromotor assessment as a routine part of the diagnostic process and provide an overview of empirical research in the field.

Autism spectrum disorder, essential fatty acids and infant feeding

 Dr Brown’s research identified the importance of breastfeeding duration and essential fatty acids in children. Her research found that children who were breastfed for a longer duration in infancy were significantly less likely to have a diagnosis of autism or show signs of a fatty acid deficiency.

Transcranial magnetic stimulation in autism spectrum disorder: challenges, promise, and roadmap for future research

Autism Spectrum Disorder (ASD) is a behaviorally defined complex neurodevelopmental syndrome characterized by impairments in social communication, by the presence of restricted and repetitive behaviors, interests and activities, and by abnormalities in sensory reactivity. Transcranial magnetic stimulation (TMS) is a promising, emerging tool for the study and potential treatment of ASD. Recent studies suggest that TMS measures provide rapid and noninvasive pathophysiological ASD biomarkers. Furthermore, repetitive TMS (rTMS) may represent a novel treatment strategy for reducing some of the core and associated ASD symptoms. However, the available literature on the TMS use in ASD is preliminary, composed of studies with methodological limitations. Thus, off-label clinical rTMS use for therapeutic interventions in ASD without an investigational device exemption and outside of an IRB approved research trial is premature pending further, adequately powered and controlled trials. Leaders in this field have gathered annually for a two-day conference (prior to the 2014 and 2015 International Meeting for Autism Research, IMFAR) to share recent progress, promote collaboration across laboratories, and establish consensus on protocols. Here we review the literature in the use of TMS in ASD in the context of the unique challenges required for the study and exploration of treatment strategies in this population. We also suggest future directions for this field of investigations. While its true potential in ASD has yet to be delineated, TMS represents an innovative research tool and a novel, possibly transformative approach to the treatment of neurodevelopmental disorders. Autism Res 2015. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Atypical neural activity in males but not females with autism spectrum disorder

The medial prefrontal cortex (mPFC) and the right temporo-parietal junction (rTPj) are highly involved in social understanding, a core area of impairment in autism spectrum disorder (ASD). We used fMRI to investigate sex differences in the neural correlates of social understanding in 27 high-functioning adults with ASD and 23 matched controls. There were no differences in neural activity in the mPFC or rTPj between groups during social processing. Whole brain analysis revealed decreased activity in the posterior superior temporal sulcus in males with ASD compared to control males while processing social information. This pattern was not observed in the female sub-sample. The current study indicates that sex mediates the neurobiology of ASD, particularly with respect to processing social information.

Exploring behavioral sleep problems in children with ADHD and comorbid Autism Spectrum Disorder

OBJECTIVE: This study (a) compared behavioral sleep problems in children with comorbid ADHD and autism spectrum disorder (ASD) with those with ADHD and (b) examined child/family factors associated with sleep problems. METHOD: Cross-sectional study comparison of 392 children with a confirmed ADHD diagnosis (ADHD+ASD, n=93, ADHD, n=299) recruited from 21 peadiatric practises in Victoria, Australia. Data were collected from parents. Key measures included the Child Sleep Habits Questionnaire (CSHQ). RESULTS: Children with ADHD + ASD experienced similar levels and types of behavioral sleep problems compared with those with ADHD. In both groups, the presence of co-occurring internalizing and externalizing comorbidities was associated with sleep problems. Sleep problems were also associated with parent age in the ADHD + ASD group and poorer parent mental health in the ADHD group. CONCLUSION: Findings suggest comorbid ASD is not associated with increased behavioral sleep problems in children with ADHD and that co-occurring internalizing and externalizing comorbidities may flag children in these groups with sleep problems.

Autism blogs: expressed emotion, language styles and concerns in personal and community settings

The Internet has provided an ever increasingly popular platform for individuals to voice their thoughts, and like-minded people to share stories. This unintentionally leaves characteristics of individuals and communities, which are often difficult to be collected in traditional studies. Individuals with autism are such a case, in which the Internet could facilitate even more communication given its social-spatial distance being a characteristic preference for individuals with autism. Previous studies examined the traces left in the posts of online autism communities (Autism) in comparison with other online communities (Control). This work further investigates these online populations through the contents of not only their posts but also their comments. We first compare the Autism and Control blogs based on three features: topics, language styles and affective information. The autism groups are then further examined, based on the same three features, by looking at their personal (Personal) and community (Community) blogs separately. Machine learning and statistical methods are used to discriminate blog contents in both cases. All three features are found to be significantly different between Autism and Control, and between autism Personal and Community. These features also show good indicative power in prediction of autism blogs in both personal and community settings.

Hierarchical dirichlet process for tracking complex topical structure evolution and its application to autism research literature

In this paper we describe a novel framework for the discovery of the topical content of a data corpus, and the tracking of its complex structural changes across the temporal dimension. In contrast to previous work our model does not impose a prior on the rate at which documents are added to the corpus nor does it adopt the Markovian assumption which overly restricts the type of changes that the model can capture. Our key technical contribution is a framework based on (i) discretization of time into epochs, (ii) epoch-wise topic discovery using a hierarchical Dirichlet process-based model, and (iii) a temporal similarity graph which allows for the modelling of complex topic changes: emergence and disappearance, evolution, splitting and merging. The power of the proposed framework is demonstrated on the medical literature corpus concerned with the autism spectrum disorder (ASD) - an increasingly important research subject of significant social and healthcare importance. In addition to the collected ASD literature corpus which we made freely available, our contributions also include two free online tools we built as aids to ASD researchers. These can be used for semantically meaningful navigation and searching, as well as knowledge discovery from this large and rapidly growing corpus of literature.

Learning entry profiles of children with autism from multivariate treatment information using restricted boltzmann machines

Entry profiles can be generated before children with Autism Spectrum Disorders (ASD) begin to traverse an intervention program. They can help evaluate the progress of each child on the dedicated syllabus in addition to enabling narrowing down the best intervention course over time. However, the traits of ASD are expressed in different ways in every individual affected. The resulting spectrum nature of the disorder makes it challenging to discover profiles of children with ASD. Using data from 491 children, traversing the syllabus of a comprehensive intervention program on iPad called TOBY Playpad, we learn the entry profiles of the children based on their age, sex and performance on their first skills of the syllabus. Mixed-variate restricted Boltzmann machines allow us to integrate the heterogeneous data into one model making it a suitable technique. The data based discovery of entry profiles may assist in developing systems that can automatically suggest best suitable paths through the syllabus by clustering the children based on the characteristics they present at the beginning of the program. This may open the pathway for personalised intervention.

Using Twitter to learn about the autism community

Considering the raising socio-economic burden of autism spectrum disorder (ASD), timely and evidence-driven public policy decision-making and communication of the latest guidelines pertaining to the treatment and management of the disorder is crucial. Yet evidence suggests that policy makers and medical practitioners do not always have a good understanding of the practices and relevant beliefs of ASD-afflicted individuals’ carers who often follow questionable recommendations and adopt advice poorly supported by scientific data. The key goal of the present work is to explore the idea that Twitter, as a highly popular platform for information exchange, could be used as a data-mining source to learn about the population affected by ASD—their behaviour, concerns, needs, etc. To this end, using a large data set of over 11 million harvested tweets as the basis for our investigation, we describe a series of experiments which examine a range of linguistic and semantic aspects of messages posted by individuals interested in ASD. Our findings, the first of their nature in the published scientific literature, strongly motivate additional research on this topic and present a methodological basis for further work.

Adult Autism Spectrum Disorder and intimate relationships

 This thesis investigated the link between ASD traits and relationship development and experience in both adults with ASD and their TD partners, through a series of online questionnaires. Firstly, for a large sample of female and male adults with ASD, we found that poor relationship development outcome was predicted by higher severity of social skills impairment. When males and females were considered separately, we found that higher severity of communication deficits predicted poor relationship development outcome for males only, and higher severity of social skills deficits predicted poor relationship development outcome for females only. We also found that higher severity of circumscribed interests predicted better relationship development outcomes for the whole sample. Next, in a comparison of relationship functioning across three partner groups (TD partners within a TD/TD dyad, ASD partners within an ASD/TD dyad and TD partners within an ASD/TD dyad), findings indicated that TD partners within an ASD/TD dyad had the poorest relationship outcome. Lastly, we investigated actor and partner effects of ASD traits on relationship outcome for a sample of ASD/TD dyads using an APIM. We found minimal evidence to suggest that ASD traits negatively impact relationship outcome of ASD/TD dyads. However, we consistently found that TD partner’s ASD trait severity positively influenced both ASD and TD partner’s relationship outcome, suggesting that mutual understanding between partners is protective against the challenges faced within ASD/TD relationships.

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.