Children with autism spectrum disorder (ASD) exhibit diminished visual engagement to environmental stimuli. Aberrant attentional function provides an explanation by reduced phasic alerting and ...orienting to exogenous stimuli. We review aberrant attentional function (alerting, orienting and attentional control) in children with ASD as studied by neurocognitive and neurophysiological tasks as well as magnetic resonance imaging studies. The locus coeruleus–norepinephrine (LC–NE) system is outlined as a pacemaker of attentional function. The LC–NE system regulates adaptive gain in synaptic signal transmission, which moderates phasic alerting (‘promoting’) and the activation of the ventral frontoparietal attention network within orienting (‘permitting’). In children with ASD, atypical LC–NE activity is proposed as underlying mechanism of aberrant attentional function. It may manifest as (i) increased tonic activity with reduced phasic reactivity to exogenous stimuli, (ii) attenuated bottom‐up signalling mitigating salience and predictive reward attribution during phasic alerting, and (iii) reduced activation of the ventral frontoparietal attention system attenuating orienting to exogenous stimuli. Increased tonic pupil dilation and aberrant pupil reactivity are discussed as indicators of atypical LC–NE activity. Pupillometry is outlined as feasible method to assess alerting, orienting and attentional control that can be dissected from the pupil dilation time course. In children with ASD, aberrant attentional function through atypical LC–NE activity is proposed as developmental mechanism leading to reduced social attention as well as social interaction and communication impairments.
In children with autism spectrum disorder, aberrant locus coeruleus–norepinephrine (LC–NE) functioning is reviewed as developmental mechanism of aberrant attentional function. Increased tonic activity and aberrant phasic reactivity relate to autism symptoms and aberrations in functional networks. Pupil dilation time course is proposed as feasible assessment method of LC–NE functioning in human clinical studies.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
The past decade has evinced a boom of computer-based approaches to aid movement assessment in early infancy. Increasing interests have been dedicated to develop AI driven approaches to complement the ...classic Prechtl general movements assessment (GMA). This study proposes a novel machine learning algorithm to detect an age-specific movement pattern, the fidgety movements (FMs), in a prospectively collected sample of typically developing infants. Participants were recorded using a passive, single camera RGB video stream. The dataset of 2800 five-second snippets was annotated by two well-trained and experienced GMA assessors, with excellent inter- and intra-rater reliabilities. Using OpenPose, the infant full pose was recovered from the video stream in the form of a 25-points skeleton. This skeleton was used as input vector for a shallow multilayer neural network (SMNN). An ablation study was performed to justify the network's architecture and hyperparameters. We show for the first time that the SMNN is sufficient to discriminate fidgety from non-fidgety movements in a sample of age-specific typical movements with a classification accuracy of 88%. The computer-based solutions will complement original GMA to consistently perform accurate and efficient screening and diagnosis that may become universally accessible in daily clinical practice in the future.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Chronic peer victimization has long-term impacts on mental health; however, the biological mediators of this adverse relationship are unknown. We sought to determine whether adolescent brain ...development is involved in mediating the effect of peer victimization on psychopathology. We included participants (n = 682) from the longitudinal IMAGEN study with both peer victimization and neuroimaging data. Latent profile analysis identified groups of adolescents with different experiential patterns of victimization. We then associated the victimization trajectories and brain volume changes with depression, generalized anxiety, and hyperactivity symptoms at age 19. Repeated measures ANOVA revealed time-by-victimization interactions on left putamen volume (F = 4.38, p = 0.037). Changes in left putamen volume were negatively associated with generalized anxiety (t = -2.32, p = 0.020). Notably, peer victimization was indirectly associated with generalized anxiety via decreases in putamen volume (95% CI = 0.004-0.109). This was also true for the left caudate (95% CI = 0.002-0.099). These data suggest that the experience of chronic peer victimization during adolescence might induce psychopathology-relevant deviations from normative brain development. Early peer victimization interventions could prevent such pathological changes.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Autism spectrum disorder shares many symptoms with other mental health disorders, and comorbid disorders such as mood and anxiety disorders are common, making the diagnostic process challenging. We ...aimed to explore the diagnostic accuracy of two standard autism spectrum disorder diagnostic instruments and to identify those behavioral items that best differentiate between autism spectrum disorder and mood and anxiety disorder in a naturalistic sample of patients utilizing autism spectrum disorder specialist services. The study included data of 847 participants (5–65 years of age, n = 586 with autism spectrum disorder, n = 261 with mood and anxiety disorder) all evaluated with the Autism Diagnostic Observation Schedule in the context of the diagnostic process. Data of the Autism Diagnostic Interview–Revised were available for 428 participants (5–51 years of age, n = 367 with autism spectrum disorder, n = 61 with mood and anxiety disorder). By means of binominal logistic regressions and an ensemble feature selection, we identified a subset of items that best differentiated between autism spectrum disorder and mood and anxiety disorder. Overall, the results indicate that a combination of communicational deficits and unusual and/or inappropriate social overtures differentiates autism spectrum disorder and mood and anxiety disorder. Aspects of social cognition are also relevant. Limitations of the current study and implications for research and practice are discussed.
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Symptoms of mood and anxiety disorders overlap with symptoms of autism spectrum disorder, making the diagnostic process challenging. This study found that a combination of communicational deficits and unusual and/or inappropriate social overtures facilitates differentiation between autism spectrum disorder and mood and anxiety disorders. Furthermore, the results confirm the essential need of a behavioral observation with the Autism Diagnostic Observation Schedule in combination with a full Autism Diagnostic Interview–Revised to support diagnostic decisions.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
Objective:The authors examined whether alterations in the brain’s reward network operate as a mechanism across the spectrum of risk for depression. They then tested whether these alterations are ...specific to anhedonia as compared with low mood and whether they are predictive of depressive outcomes.Method:Functional MRI was used to collect blood-oxygen-level-dependent (BOLD) responses to anticipation of reward in the monetary incentive task in 1,576 adolescents in a community-based sample. Adolescents with current subthreshold depression and clinical depression were compared with matched healthy subjects. In addition, BOLD responses were compared across adolescents with anhedonia, low mood, or both symptoms, cross-sectionally and longitudinally.Results:Activity in the ventral striatum was reduced in participants with subthreshold and clinical depression relative to healthy comparison subjects. Low ventral striatum activation predicted transition to subthreshold or clinical depression in previously healthy adolescents at 2-year follow-up. Brain responses during reward anticipation decreased in a graded manner between healthy adolescents, adolescents with current or future subthreshold depression, and adolescents with current or future clinical depression. Low ventral striatum activity was associated with anhedonia but not low mood; however, the combined presence of both symptoms showed the strongest reductions in the ventral striatum in all analyses.Conclusions:The findings suggest that reduced striatal activation operates as a mechanism across the risk spectrum for depression. It is associated with anhedonia in healthy adolescents and is a behavioral indicator of positive valence systems, consistent with predictions based on the Research Domain Criteria.
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.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, ODKLJ, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
IMPORTANCE: Cannabis use during adolescence is known to increase the risk for schizophrenia in men. Sex differences in the dynamics of brain maturation during adolescence may be of particular ...importance with regard to vulnerability of the male brain to cannabis exposure. OBJECTIVE: To evaluate whether the association between cannabis use and cortical maturation in adolescents is moderated by a polygenic risk score for schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Observation of 3 population-based samples included initial analysis in 1024 adolescents of both sexes from the Canadian Saguenay Youth Study (SYS) and follow-up in 426 adolescents of both sexes from the IMAGEN Study from 8 European cities and 504 male youth from the Avon Longitudinal Study of Parents and Children (ALSPAC) based in England. A total of 1577 participants (aged 12-21 years; 899 57.0% male) had (1) information about cannabis use; (2) imaging studies of the brain; and (3) a polygenic risk score for schizophrenia across 108 genetic loci identified by the Psychiatric Genomics Consortium. Data analysis was performed from March 1 through December 31, 2014. MAIN OUTCOMES AND MEASURES: Cortical thickness derived from T1-weighted magnetic resonance images. Linear regression tests were used to assess the relationships between cannabis use, cortical thickness, and risk score. RESULTS: Across the 3 samples of 1574 participants, a negative association was observed between cannabis use in early adolescence and cortical thickness in male participants with a high polygenic risk score. This observation was not the case for low-risk male participants or for the low- or high-risk female participants. Thus, in SYS male participants, cannabis use interacted with risk score vis-à-vis cortical thickness (P = .009); higher scores were associated with lower thickness only in males who used cannabis. Similarly, in the IMAGEN male participants, cannabis use interacted with increased risk score vis-à-vis a change in decreasing cortical thickness from 14.5 to 18.5 years of age (t137 = −2.36; P = .02). Finally, in the ALSPAC high-risk group of male participants, those who used cannabis most frequently (≥61 occasions) had lower cortical thickness than those who never used cannabis (difference in cortical thickness, 0.07 95% CI, 0.01-0.12; P = .02) and those with light use (<5 occasions) (difference in cortical thickness, 0.11 95% CI, 0.03-0.18; P = .004). CONCLUSIONS AND RELEVANCE: Cannabis use in early adolescence moderates the association between the genetic risk for schizophrenia and cortical maturation among male individuals. This finding implicates processes underlying cortical maturation in mediating the link between cannabis use and liability to schizophrenia.
Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical ...studies, it is of utmost importance to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well documented, the empirical assessment of the interplay between sample size and replicability of results for task-based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly, we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability. We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation between experimental paradigms or contrasts of parameter estimates within these.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
There is an extensive body of literature linking ADHD to overweight and obesity. Research indicates that impulsivity features of ADHD account for a degree of this overlap. The neural and polygenic ...correlates of this association have not been thoroughly examined. In participants of the IMAGEN study, we found that impulsivity symptoms and body mass index (BMI) were associated (r = 0.10, n = 874, p = 0.014 FWE corrected), as were their respective polygenic risk scores (PRS) (r = 0.17, n = 874, p = 6.5 × 10
FWE corrected). We then examined whether the phenotypes of impulsivity and BMI, and the PRS scores of ADHD and BMI, shared common associations with whole-brain grey matter and the Monetary Incentive Delay fMRI task, which associates with reward-related impulsivity. A sparse partial least squared analysis (sPLS) revealed a shared neural substrate that associated with both the phenotypes and PRS scores. In a last step, we conducted a bias corrected bootstrapped mediation analysis with the neural substrate score from the sPLS as the mediator. The ADHD PRS associated with impulsivity symptoms (b = 0.006, 90% CIs = 0.001, 0.019) and BMI (b = 0.009, 90% CIs = 0.001, 0.025) via the neuroimaging substrate. The BMI PRS associated with BMI (b = 0.014, 95% CIs = 0.003, 0.033) and impulsivity symptoms (b = 0.009, 90% CIs = 0.001, 0.025) via the neuroimaging substrate. A common neural substrate may (in part) underpin shared genetic liability for ADHD and BMI and the manifestation of their (observable) phenotypic association.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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