Stress in autism (STREAM): A study protocol on the role of circadian activity, sleep quality and sensory reactivity.

Mental health issues are markedly increased in individuals with autism, making it the number one research priority by stakeholders. There is a crucial need to use personalized approaches to understand the underpinnings of mental illness in autism and consequently, to address individual needs. Based on the risk factors identified in typical mental research, we propose the following themes central to mental health issues in autism: sleep difficulties and stress. Indeed, the prevalence of manifold circadian disruptions and sleep difficulties in autism, alongside stress related to sensory overload, forms an integral part of autistic symptomatology. This proof-of-concept study protocol outlines an innovative, individualised approach towards investigating the interrelationships between stress indices, sleep and circadian activation patterns, and sensory sensitivity in autism. Embracing an individualized methodology, we aim to collect 14 days of data per participant from 20 individuals with autism diagnoses and 20 without. Participants' sleep will be monitored using wearable EEG headbands and a sleep diary. Diurnal tracking of heart rate and electrodermal activity through wearables will serve as proxies of stress. Those objective data will be synchronized with subjective experience traces collected throughout the day using the Temporal Experience Tracing (TET) method. TET facilitates the quantification of relevant aspects of individual experience states, such as stress or sensory sensitivities, by providing a continuous multidimensional description of subjective experiences. Capturing the dynamics of subjective experiences phase-locked to neural and physiological proxies both between and within individuals, this approach has the potential to contribute to our understanding of critical issues in autism, including sleep problems, sensory reactivity and stress. The planned strives to provide a pathway towards developing a more nuanced and individualized approach to addressing mental health in autism.

Reduced stereotypicality and spared use of facial expression predictions for social evaluation in autism.

Background/Objective: Autism has been investigated through traditional emotion recognition paradigms, merely investigating accuracy, thereby constraining how potential differences across autistic and control individuals may be observed, identified, and described. Moreover, the use of emotional facial expression information for social functioning in autism is of relevance to provide a deeper understanding of the condition. Method: Adult autistic individuals (n = 34) and adult control individuals (n = 34) were assessed with a social perception behavioral paradigm exploring facial expression predictions and their impact on social evaluation. Results: Autistic individuals held less stereotypical predictions than controls. Importantly, despite such differences in predictions, the use of such predictions for social evaluation did not differ significantly between groups, as autistic individuals relied on their predictions to evaluate others to the same extent as controls. Conclusions: These results help to understand how autistic individuals perceive social stimuli and evaluate others, revealing a deviation from stereotypicality beyond which social evaluation strategies may be intact.

An evaluation of the German version of the Sensory Perception Quotient from an expert by experience perspective.

Sensory processing is often altered in individuals with autism; thus, it is essential to develop reliable measurement tools to assess sensory perception. The Sensory Perception Quotient (SPQ) quantifies basic sensory sensitivities in adults via self-report. Adopting an expert by experience perspective, this study aimed to evaluate a German translation of the SPQ for its use in clinical and research applications, especially for autistic adults. 108 adults (n = 54 autistic) completed the German SPQ in an online assessment. A 92-item and a 35-item version of the German SPQ were analyzed for group differences and internal consistency. Our results show that adults with autism reported greater sensory sensitivity compared to non-autistic adults. Results further suggest good to excellent internal consistency for the 95-item and 35-item SPQ translations. This finding was supported by the correlative relationship between sensory sensitivity and autistic traits. These findings confirm the reliability of our SPQ translation, making it a suitable German assessment tool for basic sensory sensitivity in autistic adults.

Classifying autism in a clinical population based on motion synchrony: a proof-of-concept study using real-life diagnostic interviews.

Predictive modeling strategies are increasingly studied as a means to overcome clinical bottlenecks in the diagnostic classification of autism spectrum disorder. However, while some findings are promising in the light of diagnostic marker research, many of these approaches lack the scalability for adequate and effective translation to everyday clinical practice. In this study, our aim was to explore the use of objective computer vision video analysis of real-world autism diagnostic interviews in a clinical sample of children and young individuals in the transition to adulthood to predict diagnosis. Specifically, we trained a support vector machine learning model on interpersonal synchrony data recorded in Autism Diagnostic Observation Schedule (ADOS-2) interviews of patient-clinician dyads. Our model was able to classify dyads involving an autistic patient (n = 56) with a balanced accuracy of 63.4% against dyads including a patient with other psychiatric diagnoses (n = 38). Further analyses revealed no significant associations between our classification metrics with clinical ratings. We argue that, given the above-chance performance of our classifier in a highly heterogeneous sample both in age and diagnosis, with few adjustments this highly scalable approach presents a viable route for future diagnostic marker research in autism.

Machine learning classification of autism spectrum disorder based on reciprocity in naturalistic social interactions.

Autism spectrum disorder is characterized by impaired social communication and interaction. As a neurodevelopmental disorder typically diagnosed during childhood, diagnosis in adulthood is preceded by a resource-heavy clinical assessment period. The ongoing developments in digital phenotyping give rise to novel opportunities within the screening and diagnostic process. Our aim was to quantify multiple non-verbal social interaction characteristics in autism and build diagnostic classification models independent of clinical ratings. We analyzed videos of naturalistic social interactions in a sample including 28 autistic and 60 non-autistic adults paired in dyads and engaging in two conversational tasks. We used existing open-source computer vision algorithms for objective annotation to extract information based on the synchrony of movement and facial expression. These were subsequently used as features in a support vector machine learning model to predict whether an individual was part of an autistic or non-autistic interaction dyad. The two prediction models based on reciprocal adaptation in facial movements, as well as individual amounts of head and body motion and facial expressiveness showed the highest precision (balanced accuracies: 79.5% and 68.8%, respectively), followed by models based on reciprocal coordination of head (balanced accuracy: 62.1%) and body (balanced accuracy: 56.7%) motion, as well as intrapersonal coordination processes (balanced accuracy: 44.2%). Combinations of these models did not increase overall predictive performance. Our work highlights the distinctive nature of non-verbal behavior in autism and its utility for digital phenotyping-based classification. Future research needs to both explore the performance of different prediction algorithms to reveal underlying mechanisms and interactions, as well as investigate the prospective generalizability and robustness of these algorithms in routine clinical care.

Interacting with autistic virtual characters: intrapersonal synchrony of nonverbal behavior affects participants' perception.

Temporal coordination of communicative behavior is not only located between but also within interaction partners (e.g., gaze and gestures). This intrapersonal synchrony (IaPS) is assumed to constitute interpersonal alignment. Studies show systematic variations in IaPS in individuals with autism, which may affect the degree of interpersonal temporal coordination. In the current study, we reversed the approach and mapped the measured nonverbal behavior of interactants with and without ASD from a previous study onto virtual characters to study the effects of the differential IaPS on observers (N = 68), both with and without ASD (crossed design). During a communication task with both characters, who indicated targets with gaze and delayed pointing gestures, we measured response times, gaze behavior, and post hoc impression formation. Results show that character behavior indicative of ASD resulted in overall enlarged decoding times in observers and this effect was even pronounced in observers with ASD. A classification of observer's gaze types indicated differentiated decoding strategies. Whereas non-autistic observers presented with a rather consistent eyes-focused strategy associated with efficient and fast responses, observers with ASD presented with highly variable decoding strategies. In contrast to communication efficiency, impression formation was not influenced by IaPS. The results underline the importance of timing differences in both production and perception processes during multimodal nonverbal communication in interactants with and without ASD. In essence, the current findings locate the manifestation of reduced reciprocity in autism not merely in the person, but in the interactional dynamics of dyads.

[Autism spectrum disorder in adulthood]. / Autismus-Spektrum-Störung im Erwachsenenalter.

Autism is a neurodevelopmental disorder that starts in early childhood and persists over the lifespan. A combination of genetic factors and environmental factors around birth contribute to its etiology. Autistic individuals show differences and difficulties in social interaction and communication as well as repetitive, stereotypical behavior and interests. The diagnostic procedure is complex and should be carried out in a specialized assessment unit. Diagnostic assessment is based on behavioral observation and a careful evaluation of developmental history. A wide range of potential differential diagnoses should be considered. Autistic adults have a higher risk of developing psychiatric disorders such as anxiety and depression. Psychotherapeutic treatment that is adapted to autism-related difficulties can be helpful. Co-occurring conditions should be treated in accordance with disorder-specific guidelines. Psychopharmacological treatment of co-occurring conditions is, in most cases, only recommended as an addition to behavioral interventions. Autistic people often experience difficulties in social participation, which can be targeted with sociotherapeutic interventions.

Differentiated, rather than shared, strategies for time-coordinated action in social and non-social domains in autistic individuals.

Autism spectrum disorder (ASD) is a neurodevelopmental condition with a highly heterogeneous adult phenotype that includes social and non-social behavioral characteristics. The link between the characteristics assignable to the different domains remains unresolved. One possibility is that social and non-social behaviors in autism are modulated by a common underlying deficit. However, here we report evidence supporting an alternative concept that is individual-centered rather than deficit-centered. Individuals are assumed to have a distinctive style in the strategies they adopt to perform social and non-social tasks with these styles presumably being structured differently between autistic individuals and typically-developed (TD) individuals. We tested this hypothesis for the execution of time-coordinated (synchronized) actions. Participants performed (i) a social task that required synchronized gaze and pointing actions to interact with another person, and (ii) a non-social task that required finger-tapping actions synchronized to periodic stimuli at different time-scales and sensory modalities. In both tasks, synchronization behavior differed between ASD and TD groups. However, a principal component analysis of individual behaviors across tasks revealed associations between social and non-social features for the TD persons but such cross-domain associations were strikingly absent for autistic individuals. The highly differentiated strategies between domains in ASD are inconsistent with a general synchronization deficit and instead highlight the individualized developmental heterogeneity in the acquisition of domain-specific behaviors. We propose a cognitive model to help disentangle individual-centered from deficit-centered effects in other domains. Our findings reinforce the importance to identify individually differentiated phenotypes to personalize autism therapies.

Synchrony in psychotherapy: High physiological positive concordance predicts symptom reduction and negative concordance predicts symptom aggravation.

OBJECTIVE: Therapeutic alliance is often considered as a predictor for therapeutic success. This study explored dyadic synchrony of skin conductance response (SCR) during naturalistic therapeutic interactions and investigated its potential as an objective biomarker for predicting therapy effectiveness. METHODS: In this proof-of-concept study, skin conductance from both dyad members was continuously measured via wristbands during psychotherapy. Patients and therapists completed post-session reports capturing their subjective appraisal of therapeutic alliance. Additionally, patients completed symptom questionnaires. Each therapeutic dyad was recorded twice in a follow-up design. The first session of the follow-up group was assessed for physiological synchrony (Single Session Index (SSI)). Therapy outcome was captured by the difference between symptom severity scores over time. RESULTS: SCR synchrony significantly predicted the outcome variable of change in patients' global severity index (GSI). High positive SCR concordance was linked to a reduction in patients' GSI, while negative or small positive SSI values were linked to an increase in patients' GSI. CONCLUSION: The results demonstrate the presence of SCR synchrony in clinical interactions. Skin conductance response synchrony was a significant predictor for change in patients' symptom severity index, emphasizing its potential as an objective biomarker in the context of evidence-based psychotherapy.

What is specific about employment status, workplace experiences and requirements in individuals with autism in Germany?

The challenge of sustainably integrating highly educated individuals with ASD without intellectual disabilities in the first labor market is repeatedly described in literature. In a retrospective study, a group of 197 clinically late-diagnosed adults with ASD without intellectual disabilities was compared to a closely matched group of 501 individuals who did not meet the criteria for the diagnosis of ASD within a utilization population of the Cologne Autism Outpatient Clinic. Results indicated that the pronounced demand for reduction of social and interpersonal requirements at the workplace (including planned or limited contact with colleagues and customers) as well as the experience of difficulties following unexpected changes in the daily routine were specific for ASD. In addition, individuals with ASD reported greater difficulties in finding a suitable job and being able to live on their wages, taking age and educational qualification into account. Supported employment measures were provided significantly more frequently to individuals in the ASD group. In conclusion, impairments in social skills emerged as one of the main obstacles of workplace performance for individuals with ASD emphasizing the necessity to develop and apply ASD-specific support services.

Digitally assisted diagnostics of autism spectrum disorder.

Digital technologies have the potential to support psychiatric diagnostics and, in particular, differential diagnostics of autism spectrum disorder in the near future, making clinical decisions more objective, reliable and evidence-based while reducing clinical resources. Multimodal automatized measurement of symptoms at cognitive, behavioral, and neuronal levels combined with artificial intelligence applications offer promising strides toward personalized prognostics and treatment strategies. In addition, these new technologies could enable systematic and continuous assessment of longitudinal symptom development, beyond the usual scope of clinical practice. Early recognition of exacerbation and simplified, as well as detailed, progression control would become possible. Ultimately, digitally assisted diagnostics will advance early recognition. Nonetheless, digital technologies cannot and should not substitute clinical decision making that takes the comprehensive complexity of individual longitudinal and cross-section presentation of autism spectrum disorder into account. Yet, they might aid the clinician by objectifying decision processes and provide a welcome relief to resources in the clinical setting.

Alarmingly large unemployment gap despite of above-average education in adults with ASD without intellectual disability in Germany: a cross-sectional study.

For individuals with autism spectrum disorder (ASD), both getting access to as well as staying in the labor market are very challenging. However, the detailed educational, vocational, and employment characteristics of persons with ASD without intellectual disabilities are not yet studied. We conducted a retrospective study on a sample of 232 clinically late-diagnosed adults with ASD without intellectual disabilities. Data were compared to the general German population obtained from the public database of the German Federal Employment Agency. Results showed that the majority of persons with ASD graduated from high school and obtained a university entrance qualification (ASD: 50.4%; general population: 32.5%). Also, lower rates of basic secondary education were found in the ASD sample (ASD: 16.5%, general population: 29.6%). Significantly less individuals with ASD completed vocational training (40.1%) in comparison to the German population (56.3%). Despite the above-average level of education, the unemployment rate of the sample substantially exceeds that of the general population by the factor 5 (ASD: 25.2%; general population: 5.2%). Periods of unwanted unemployment of persons with ASD lasted on average 23 months with interpersonal problems being the main reason for contract termination. A higher level of educational qualification does not protect against a higher risk of unemployment for individuals with ASD presumably due to autism-specific interpersonal difficulties. Data emphasize the necessity to develop and spread both specific employment support activities for individuals with ASD as well as adequate awareness raising strategies. Funded by a public grant of the "Landschaftsverband Rheinland (LVR)".

Perceptual Grouping in Autism Spectrum Disorder: An Exploratory Magnetoencephalography Study.

Visual information is organised according to visual grouping principles. In visual grouping tasks individuals with ASD have shown equivocal performance. We explored neural correlates of Gestalt grouping in individuals with and without ASD. Neuromagnetic activity of individuals with (15) and without (18) ASD was compared during a visual grouping task testing grouping by proximity versus similarity. Individuals without ASD showed stronger evoked responses with earlier peaks in response to both grouping types indicating an earlier neuronal differentiation between grouping principles in individuals without ASD. In contrast, individuals with ASD showed particularly prolonged processing of grouping by similarity suggesting a high demand of neural resources. The neuronal processing differences found could explain less efficient grouping performance observed behaviourally in ASD.

Intrapersonal synchrony analysis reveals a weaker temporal coherence between gaze and gestures in adults with autism spectrum disorder.

The temporal encoding of nonverbal signals within individuals, referred to as intrapersonal synchrony (IaPS), is an implicit process and essential feature of human communication. Based on existing evidence, IaPS is thought to be a marker of nonverbal behavior characteristics in autism spectrum disorders (ASD), but there is a lack of empirical evidence. The aim of this study was to quantify IaPS in adults during an experimentally controlled real-life interaction task. A sample of adults with a confirmed ASD diagnosis and a matched sample of typically-developed adults were tested (N = 48). Participants were required to indicate the appearance of a target invisible to their interaction partner nonverbally through gaze and pointing gestures. Special eye-tracking software allowed automated extraction of temporal delays between nonverbal signals and their intrapersonal variability with millisecond temporal resolution as indices for IaPS. Likelihood ratio tests of multilevel models showed enlarged delays between nonverbal signals in ASD. Larger delays were associated with greater intrapersonal variability in delays. The results provide a quantitative constraint on nonverbal temporality in typically-developed adults and suggest weaker temporal coherence between nonverbal signals in adults with ASD. The results provide a potential diagnostic marker and inspire predictive coding theories about the role of IaPS in interpersonal synchronization processes.

Biobanking in everyday clinical practice in psychiatry-The Munich Mental Health Biobank.

Translational research on complex, multifactorial mental health disorders, such as bipolar disorder, major depressive disorder, schizophrenia, and substance use disorders requires databases with large-scale, harmonized, and integrated real-world and research data. The Munich Mental Health Biobank (MMHB) is a mental health-specific biobank that was established in 2019 to collect, store, connect, and supply such high-quality phenotypic data and biosamples from patients and study participants, including healthy controls, recruited at the Department of Psychiatry and Psychotherapy (DPP) and the Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital of the Ludwig-Maximilians-University (LMU), Munich, Germany. Participants are asked to complete a questionnaire that assesses sociodemographic and cross-diagnostic clinical information, provide blood samples, and grant access to their existing medical records. The generated data and biosamples are available to both academic and industry researchers. In this manuscript, we outline the workflow and infrastructure of the MMHB, describe the clinical characteristics and representativeness of the sample collected so far, and reveal future plans for expansion and application. As of 31 October 2021, the MMHB contains a continuously growing set of data from 578 patients and 104 healthy controls (46.37% women; median age, 38.31 years). The five most common mental health diagnoses in the MMHB are recurrent depressive disorder (38.78%; ICD-10: F33), alcohol-related disorders (19.88%; ICD-10: F10), schizophrenia (19.69%; ICD-10: F20), depressive episode (15.94%; ICD-10: F32), and personality disorders (13.78%; ICD-10: F60). Compared with the average patient treated at the recruiting hospitals, MMHB participants have significantly more mental health-related contacts, less severe symptoms, and a higher level of functioning. The distribution of diagnoses is also markedly different in MMHB participants compared with individuals who did not participate in the biobank. After establishing the necessary infrastructure and initiating recruitment, the major tasks for the next phase of the MMHB project are to improve the pace of participant enrollment, diversify the sociodemographic and diagnostic characteristics of the sample, and improve the utilization of real-world data generated in routine clinical practice.

Figure-Disembedding Is Inferior in Non-autistic Compared to Autistic Individuals but Can Be Improved by Training.

Background: Figure-disembedding is one of the most discussed visuo-cognitive functions, in which individuals with Autism Spectrum Disorder (ASD) have been reported to outperform non-autistic individuals. A local processing bias has been assumed to underlie such superior performance patterns. The aim of the current study is to investigate whether processing preferences can be modified by procedural priming. Method: The current study used a procedural priming task (Navon figures) to induce more local or global processing in 25 autistic and 21 typically developing (TD) control participants, using hierarchical figures preceding the figure-disembedding task. Results: Participants with ASD outperformed non-autistic individuals in the unprimed baseline task version. The performance was not modulated by priming in either direction (toward a local or global processing style) in both groups. However, the performance of TD control participants was improved by training to the same level as that observed in the ASD group. Conclusion: Figure-disembedding performance in ASD is superior to that in TD control participants and robust against procedural priming or training. In contrast, performance in the TD control group can be improved up to the level of the ASD group. Any studies reporting superiority in individuals with ASD in figure-disembedding should consider training effects when evaluating group differences.

Are Executive Dysfunctions Relevant for the Autism-Specific Cognitive Profile?

Executive functions (EF) have been shown to be important for the understanding of Autism Spectrum Disorder (ASD), but dysfunctions of EF are not autism-specific. The specific role of EF in ASD, its relationship to core autism characteristics, such as mentalizing, needs to be explored. Medline- and PsychINFO databases were searched for studies published between 1990 and 2020 that included measures of EF in ASD and typically developing control persons (TD) in combination with either Theory of Mind (ToM) or Weak Central Coherence (WCC) tasks. A pre-registered meta-analysis and cross-study regression was performed including a total of 42 studies (ASD n = 1,546, TD n = 1,206). Results were reported according to PRISMA guidelines. In all cognitive domains, the ASD group showed significantly reduced performance. Importantly, EF subdomains and ToM were not significantly correlated. This finding rules out a significant association between EF subdomains and ToM and questions the relevance of EF dysfunctions for the autism-specific feature of reduced mentalizing.

Autism traits outweigh alexithymia traits in the explanation of mentalising performance in adults with autism but not in adults with rejected autism diagnosis.

BACKGROUND: Pronounced alexithymia traits have been found in autism spectrum disorder (ASD) and recent research has been carving out the impact alexithymia traits might have on mentalising deficits associated with ASD. METHOD: In this cross-sectional study, a large representative referral population for diagnostic examination for possible ASD (n = 400) was screened for clinical alexithymia with a German version of the Reading the Mind in the Eyes test (RME). In contrast to previous attempts to carve out the impact of alexithymia traits on mentalising deficits though, we employed dominance analysis to account for the correlation between predictors. The relative relationship between alexithymia traits and autism traits with RME performance was investigated in the group of individuals with confirmed ASD diagnosis (N = 281) and compared to the clinical referral sample in which ASD was ruled out (N = 119). RESULTS: Dominance analysis revealed autism traits to be the strongest predictor for reduced mentalising skills in the ASD sample, whereas alexithymia contributed significantly less. In the sample of individuals with ruled out diagnosis, autism traits were the strongest predictor, but alexithymia traits were in sum equally associated to mentalising, with the External-Oriented Thinking subscale as an important predictor of this association. LIMITATIONS: It needs to be considered that the cross-sectional study design does not allow for causal inference. Furthermore, mentalising is a highly facetted capacity and measurements need to reduce this complexity into simple quantities which limits the generalizability of results. DISCUSSION: While alexithymia traits should be considered for their mental health importance, they do not dominate the explanation of reduced mentalising skills in individuals with ASD, but they might do to a larger degree in individuals with ruled out ASD.

A Virtual Reality Based System for the Screening and Classification of Autism.

Autism - also known as Autism Spectrum Disorders or Autism Spectrum Conditions - is a neurodevelopmental condition characterized by repetitive behaviours and differences in communication and social interaction. As a consequence, many autistic individuals may struggle in everyday life, which sometimes manifests in depression, unemployment, or addiction. One crucial problem in patient support and treatment is the long waiting time to diagnosis, which was approximated to thirteen months on average. Yet, the earlier an intervention can take place the better the patient can be supported, which was identified as a crucial factor. We propose a system to support the screening of Autism Spectrum Disorders based on a virtual reality social interaction, namely a shopping experience, with an embodied agent. During this everyday interaction, behavioral responses are tracked and recorded. We analyze this behavior with machine learning approaches to classify participants from an autistic participant sample in comparison to a typically developed individuals control sample with high accuracy, demonstrating the feasibility of the approach. We believe that such tools can strongly impact the way mental disorders are assessed and may help to further find objective criteria and categorization.

Brief Report: Specificity of Interpersonal Synchrony Deficits to Autism Spectrum Disorder and Its Potential for Digitally Assisted Diagnostics.

Reliably diagnosing autism spectrum disorders (ASD) in adulthood poses a challenge to clinicians due to the absence of specific diagnostic markers. This study investigated the potential of interpersonal synchrony (IPS), which has been found to be reduced in ASD, to augment the diagnostic process. IPS was objectively assessed in videos of diagnostic interviews in a representative referral population from two specialized autism outpatient clinics. In contrast to the current screening tools that could not reliably differentiate, we found a significant reduction of IPS in interactions with individuals later diagnosed with ASD (n = 16) as opposed to those not receiving a diagnosis (n = 23). While these findings need to be validated in larger samples, they nevertheless underline the potential of digitally-enhanced diagnostic processes for ASD.