Assessment of Reward-Related Brain Function After a Single Dose of Oxytocin in Autism: A Randomized Controlled Trial.

Background: Autism spectrum disorder (ASD) is characterized by difficulties in social communication and interaction, which have been related to atypical neural processing of rewards, especially in the social domain. As intranasal oxytocin has been shown to modulate activation of the brain's reward circuit, oxytocin might ameliorate the processing of social rewards in ASD and thus improve social difficulties. Methods: In this randomized, double-blind, placebo-controlled, crossover functional magnetic resonance imaging study, we examined effects of a 24-IU dose of intranasal oxytocin on reward-related brain function in 37 men with ASD without intellectual impairment and 37 age- and IQ-matched control participants. Participants performed an incentive delay task that allows the investigation of neural activity associated with the anticipation and receipt of monetary and social rewards. Results: Nonsignificant tests suggested that oxytocin did not influence neural processes related to the anticipation of social or monetary rewards in either group. Complementary Bayesian analyses indicated moderate evidence for a null model, relative to an alternative model. Our results were inconclusive regarding possible oxytocin effects on amygdala responsiveness to social rewards during reward consumption. There were no significant differences in reward-related brain function between the two groups under placebo. Conclusions: Our results do not support the hypothesis that intranasal oxytocin generally enhances activation of reward-related neural circuits in men with and without ASD.

Phenotypic differences between female and male individuals with suspicion of autism spectrum disorder.

BACKGROUND: Although autism spectrum disorder (ASD) is a common developmental disorder, our knowledge about a behavioral and neurobiological female phenotype is still scarce. As the conceptualization and understanding of ASD are mainly based on the investigation of male individuals, females with ASD may not be adequately identified by routine clinical diagnostics. The present machine learning approach aimed to identify diagnostic information from the Autism Diagnostic Observation Schedule (ADOS) that discriminates best between ASD and non-ASD in females and males. METHODS: Random forests (RF) were used to discover patterns of symptoms in diagnostic data from the ADOS (modules 3 and 4) in 1057 participants with ASD (18.1% female) and 1230 participants with non-ASD (17.9% % female). Predictive performances of reduced feature models were explored and compared between females and males without intellectual disabilities. RESULTS: Reduced feature models relied on considerably fewer features from the ADOS in females compared to males, while still yielding similar classification performance (e.g., sensitivity, specificity). LIMITATIONS: As in previous studies, the current sample of females with ASD is smaller than the male sample and thus, females may still be underrepresented, limiting the statistical power to detect small to moderate effects. CONCLUSION: Our results do not suggest the need for new or altered diagnostic algorithms for females with ASD. Although we identified some phenotypic differences between females and males, the existing diagnostic tools seem to sufficiently capture the core autistic features in both groups.

How Do Adults with Autism Spectrum Disorder Participate in the Labor Market? A German Multi-center Survey.

International studies show disadvantages for adults with autism spectrum disorder (ASD) in the labor market. Data about their participation in the German labor market are scarce. The aim of this study was to examine the integration of adults with ASD in the German labor market in terms of education, employment and type of occupation by means of a cross-sectional-study, using a postal questionnaire. Findings show above average levels of education for adults with ASD compared to the general population of Germany and simultaneously, below average rates of employment and high rates of financial dependency. That indicates a poor integration of adults with ASD in the German labor market and emphasizes the need for vocational support policies for adults with ASD.

Health Services Use and Costs in Individuals with Autism Spectrum Disorder in Germany: Results from a Survey in ASD Outpatient Clinics.

Autism spectrum disorders (ASD) are associated with high services use, but European data on costs are scarce. Utilisation and annual costs of 385 individuals with ASD (aged 4-67 years; 18.2% females; 37.4% IQ < 85) from German outpatient clinics were assessed. Average annual costs per person were 3287 EUR, with psychiatric inpatient care (19.8%), pharmacotherapy (11.1%), and occupational therapy (11.1%) being the largest cost components. Females incurred higher costs than males (4864 EUR vs. 2936 EUR). In a regression model, female sex (Cost Ratio: 1.65), lower IQ (1.90), and Asperger syndrome (1.54) were associated with higher costs. In conclusion, ASD-related health costs are comparable to those of schizophrenia, thus underlining its public health relevance. Higher costs in females demand further research.

Is the Combination of ADOS and ADI-R Necessary to Classify ASD? Rethinking the "Gold Standard" in Diagnosing ASD.

Diagnosing autism spectrum disorder (ASD) requires extensive clinical expertise and training as well as a focus on differential diagnoses. The diagnostic process is particularly complex given symptom overlap with other mental disorders and high rates of co-occurring physical and mental health concerns. The aim of this study was to conduct a data-driven selection of the most relevant diagnostic information collected from a behavior observation and an anamnestic interview in two clinical samples of children/younger adolescents and adolescents/adults with suspected ASD. Via random forests, the present study discovered patterns of symptoms in the diagnostic data of 2310 participants (46% ASD, 54% non-ASD, age range 4-72 years) using data from the combined Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview-Revised (ADI-R) and ADOS data alone. Classifiers built on reduced subsets of diagnostic features yield satisfactory sensitivity and specificity values. For adolescents/adults specificity values were lower compared to those for children/younger adolescents. The models including ADOS and ADI-R data were mainly built on ADOS items and in the adolescent/adult sample the classifier including only ADOS items performed even better than the classifier including information from both instruments. Results suggest that reduced subsets of ADOS and ADI-R items may suffice to effectively differentiate ASD from other mental disorders. The imbalance of ADOS and ADI-R items included in the models leads to the assumption that, particularly in adolescents and adults, the ADI-R may play a lesser role than current behavior observations.

Identification of the most indicative and discriminative features from diagnostic instruments for children with autism.

Background: Diagnosing autism spectrum disorder (ASD) is complex and time-consuming. The present work systematically examines the importance of items from the Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) in discerning children with and without ASD. Knowledge of the most discriminative features and their underlying concepts may prove valuable for the future training tools that assist clinicians to substantiate or extenuate a suspicion of ASD in nonverbal and minimally verbal children. Methods: In two samples of nonverbal (N = 466) and minimally verbal (N = 566) children with ASD (N = 509) and other mental disorders or developmental delays (N = 523), we applied random forests (RFs) to (i) the combination of ADI-R and ADOS data versus (ii) ADOS data alone. We compared the predictive performance of reduced feature models against outcomes provided by models containing all features. Results: For nonverbal children, the RF classifier indicated social orientation to be most powerful in differentiating ASD from non-ASD cases. In minimally verbal children, we find language/speech peculiarities in combination with facial/nonverbal expressions and reciprocity to be most distinctive. Conclusion: Based on machine learning strategies, we carve out those symptoms of ASD that prove to be central for the differentiation of ASD cases from those with other developmental or mental disorders (high specificity in minimally verbal children). These core concepts ought to be considered in the future training tools for clinicians.

Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning.

Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). Previous work using machine learning techniques suggested that ASD detection in children can be achieved with substantially fewer items than the original ADOS. Here, we expand on this work with a specific focus on adolescents and adults as assessed with the ADOS Module 4. We used a machine learning algorithm (support vector machine) to examine whether ASD detection can be improved by identifying a subset of behavioral features from the ADOS Module 4 in a routine clinical sample of N = 673 high-functioning adolescents and adults with ASD (n = 385) and individuals with suspected ASD but other best-estimate or no psychiatric diagnoses (n = 288). We identified reduced subsets of 5 behavioral features for the whole sample as well as age subgroups (adolescents vs. adults) that showed good specificity and sensitivity and reached performance close to that of the existing ADOS algorithm and the full ADOS, with no significant differences in overall performance. These results may help to improve the complicated diagnostic process of ASD by encouraging future efforts to develop novel diagnostic instruments for ASD detection based on the identified constructs as well as aiding clinicians in the difficult question of differential diagnosis.

Internalised stigma in adults with autism: A German multi-center survey.

The aim of this study was to evaluate the extent of internalised stigma and possible predictors in adults with a diagnosis of autism spectrum disorder (ASD). We measured internalised stigma in a sample of 149 adults with ASD and an IQ ≥70 (79.2% male, mean age 31.8 years), using the Brief Version of the Internalized Stigma of Mental Illness Scale (ISMI-10). The mean ISMI-10 score was 1.93 (SD=0.57), with 15.4% of participants reporting moderate or severe internalised stigma. Moderate or severe stigma was more frequent in persons aged ≥35 years (OR: 4.36), and in individuals with low educational level (OR: 6.00). IQ, sex and ASD diagnostic subtype (ICD-10) did not influence stigma severity. Compared to other mental disorders, the level of internalised stigma in adults with ASD without intellectual disability appears to be lower.

Complementary and alternative medicine use in adults with autism spectrum disorder in Germany: results from a multi-center survey.

BACKGROUND: Complementary and Alternative Medicine (CAM) is widely used both in the general population and for the treatment of somatic and psychiatric disorders. Studies on CAM use among patients with autism spectrum disorder (ASD) have so far only focused on children and adolescents. The aim of this study was to investigate patterns of CAM use among adults with ASD. METHODS: A questionnaire survey concerning current and lifetime use of CAM was distributed to adults with ASD between November 2015 and June 2016. Participants diagnosed by experienced clinicians using the current diagnostic gold standard were recruited from four ASD outpatient clinics in Germany. Questionnaire data was then linked to supplementary clinical data. RESULTS: The final sample consisted of 192 adults (response: 26.8%) with a mean age of 31.5 years (80% male; diagnoses: Asperger's syndrome (58%), childhood autism (27%), atypical autism (12%)). 45% of the respondents stated that they were currently using or had used at least one CAM modality in their life. Among the participants with lifetime CAM use, almost half had used two or more different types of CAM. Alternative medical systems (e.g. homeopathy, acupuncture) were most frequently used, followed by mind-body interventions (e.g. yoga, biofeedback, animal assisted therapy). Overall, 20% of respondents stated that they would like to try at least one listed CAM modality in the future. CONCLUSIONS: This is the first study on CAM use in adults with ASD, demonstrating considerable CAM use in this population. Given the popularity of CAM, patients should be informed about the effectiveness and potentially dangerous side effects of CAM treatments, as evidence for the majority of CAM methods in ASD is still limited.

Failing to forget: inhibitory-control deficits compromise memory suppression in posttraumatic stress disorder.

Most people have experienced distressing events that they would rather forget. Although memories of such events become less intrusive with time for the majority of people, those with posttraumatic stress disorder (PTSD) are afflicted by vivid, recurrent memories of their trauma. Often triggered by reminders in the daily environment, these memories can cause severe distress and impairment. We propose that difficulties with intrusive memories in PTSD arise in part from a deficit in engaging inhibitory control to suppress episodic retrieval. We tested this hypothesis by adapting the think/no-think paradigm to investigate voluntary memory suppression of aversive scenes cued by naturalistic reminders. Retrieval suppression was compromised significantly in PTSD patients, compared with trauma-exposed control participants. Furthermore, patients with the largest deficits in suppression-induced forgetting were also those with the most severe PTSD symptoms. These results raise the possibility that prefrontal mechanisms supporting inhibitory control over memory are impaired in PTSD.

Direct suppression as a mechanism for controlling unpleasant memories in daily life.

Suppressing unwanted memories can impair their later recall. Recent work shows that this forgetting is achieved by at least two mechanisms supported by distinct neural systems: thought substitution and direct suppression (Benoit & Anderson, 2012). Here, we examined whether direct suppression, thought to be achieved by down-regulation of hippocampal activity, can disrupt memory of aversive scenes, and, if so, whether this disruption is linked to people's perception of their ability to control intrusive thoughts. We presented participants with strong naturalistic reminders to aversive scenes and asked them to either covertly retrieve or directly suppress the associated scenes. Later, participants were cued with the reminders and asked to recall the scenes in detail. Direct suppression reduced recall probability of the scenes and also reduced the number of details recalled, even when scenes were remembered. Deficits in recall arose for minor details but also for details central to each scene's gist. Participants with higher self-perceived control abilities over intrusive thoughts showed greater forgetting than did those reporting lower levels of control. These findings suggest that inhibitory processes underlying direct suppression can disrupt retention of aversive visual memories and link those processes to individual differences in control over intrusive thoughts in everyday life. These findings reinforce the possibility that inhibition may be less efficient in people likely to acquire posttraumatic stress disorder in the wake of a traumatic experience.

Processing social participation: an event-related brain potential study.

We examined the electrophysiological correlates of the processing of social exclusion and inclusion by using a modified version of the Cyberball paradigm. Exclusion was found to be associated with a significant increase in the P3 complex. The frontal-central P3a was primarily related to the affective processing of rejection, whereas the late parietal P3b was associated with its perceived intensity. The expression of P3a and negative mood did also depend on the earlier experience; earlier inclusion affected the processing of exclusion, and vice versa. In conclusion, our data indicate that the complex process of social rejection can be tracked by using event-related brain potentials.