Therapeutic Alliance in Family-Based Treatment of Anorexia Nervosa: In-Person Versus Telehealth.

OBJECTIVE: The therapeutic alliance is broadly linked with positive outcomes. However, nearly all research in this area involves in-person therapy, whereas teletherapy has grown increasing common since the COVID-19 pandemic. There is now a pressing need to establish whether the nature and importance of the therapeutic alliance is impacted by teletherapy. This study examined therapeutic alliance in families of youth with anorexia nervosa who were participating in a randomized controlled trial that transitioned from in-person to telehealth visits during the COVID-19 pandemic. METHOD: We analysed data from 53 adolescents and their parents (20 began in-person, 33 began with telehealth). Both parents, youth and therapist completed the Working Alliance Inventory-Short Revised after 4 weeks of treatment. RESULTS: We found no significant differences across telehealth and in-person treatment for paternal or therapist reported data. However, both adolescents and mothers reported higher bond and goal-related alliance for in-person sessions compared to telehealth. CONCLUSIONS: Findings regarding alliance across telehealth and in-person sessions were mixed, with some preference among mothers and youth for in-person treatment. Future studies should determine whether possible adaptations can improve working alliance during family-based treatment for anorexia nervosa via telehealth.

White matter connectivity and social functioning in survivors of pediatric brain tumor.

OBJECTIVE: Survivors of pediatric brain tumors (SPBT) are at risk for social deficits, fewer friendships, and poor peer relations. SPBT also experience reduced brain connectivity via microstructural disruptions to white matter from neurological insults. Research with other populations implicates white matter connectivity as a key contributor to poor social functioning. This case-controlled diffusion-weighted imaging study evaluated structural connectivity in SPBT and typically developing controls (TDC) and associations between metrics of connectivity and social functioning. METHODS: Diffusion weighted-imaging results from 19 SPBT and 19 TDC were analyzed using probabilistic white matter tractography. Survivors were at least 5 years post-diagnosis and 2 years off treatment. Graph theory statistics measured group differences across several connectivity metrics, including average strength, global efficiency, assortativity, clustering coefficient, modularity, and betweenness centrality. Analyses also evaluated the effects of neurological risk on connectivity among SPBT. Correlational analyses evaluated associations between connectivity and indices of social behavior. RESULTS: SPBT demonstrated reduced global connectivity compared to TDC. Several medical factors (e.g., chemotherapy, recurrence, multimodal therapy) were related to decreased connectivity across metrics of integration (e.g., average strength, global efficiency) in SPBT. Connectivity metrics were related to peer relationship quality and social challenges in the SPBT group and to social challenges in the total sample. CONCLUSIONS: Microstructural white matter connectivity is diminished in SPBT and related to neurological risk and peer relationship quality. Additional neuroimaging research is needed to evaluate associations between brain connectivity metrics and social functioning in SPBT.

Comparison of Human Experts and AI in Predicting Autism from Facial Behavior.

Advances in computational behavior analysis via artificial intelligence (AI) promise to improve mental healthcare services by providing clinicians with tools to assist diagnosis or measurement of treatment outcomes. This potential has spurred an increasing number of studies in which automated pipelines predict diagnoses of mental health conditions. However, a fundamental question remains unanswered: How do the predictions of the AI algorithms correspond and compare with the predictions of humans? This is a critical question if AI technology is to be used as an assistive tool, because the utility of an AI algorithm would be negligible if it provides little information beyond what clinicians can readily infer. In this paper, we compare the performance of 19 human raters (8 autism experts and 11 non-experts) and that of an AI algorithm in terms of predicting autism diagnosis from short (3-minute) videos of N = 42 participants in a naturalistic conversation. Results show that the AI algorithm achieves an average accuracy of 80.5%, which is comparable to that of clinicians with expertise in autism (83.1%) and clinical research staff without specialized expertise (78.3%). Critically, diagnoses that were inaccurately predicted by most humans (experts and non-experts, alike) were typically correctly predicted by AI. Our results highlight the potential of AI as an assistive tool that can augment clinician diagnostic decision-making.

Predicting Autism from Head Movement Patterns during Naturalistic Social Interactions.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized in part by difficulties in verbal and nonverbal social communication. Evidence indicates that autistic people, compared to neurotypical peers, exhibit differences in head movements, a key form of nonverbal communication. Despite the crucial role of head movements in social communication, research on this nonverbal cue is relatively scarce compared to other forms of nonverbal communication, such as facial expressions and gestures. There is a need for scalable, reliable, and accurate instruments for measuring head movements directly within the context of social interactions. In this study, we used computer vision and machine learning to examine the head movement patterns of neurotypical and autistic individuals during naturalistic, face-to-face conversations, at both the individual (monadic) and interpersonal (dyadic) levels. Our model predicts diagnostic status using dyadic head movement data with an accuracy of 80%, highlighting the value of head movement as a marker of social communication. The monadic data pipeline had lower accuracy (69.2%) compared to the dyadic approach, emphasizing the importance of studying back-and-forth social communication cues within a true social context. The proposed classifier is not intended for diagnostic purposes, and future research should replicate our findings in larger, more representative samples.

Head Movement Patterns during Face-to-Face Conversations Vary with Age.

Advances in computational behavior analysis have the potential to increase our understanding of behavioral patterns and developmental trajectories in neurotypical individuals, as well as in individuals with mental health conditions marked by motor, social, and emotional difficulties. This study focuses on investigating how head movement patterns during face-to-face conversations vary with age from childhood through adulthood. We rely on computer vision techniques due to their suitability for analysis of social behaviors in naturalistic settings, since video data capture can be unobtrusively embedded within conversations between two social partners. The methods in this work include unsupervised learning for movement pattern clustering, and supervised classification and regression as a function of age. The results demonstrate that 3-minute video recordings of head movements during conversations show patterns that distinguish between participants that are younger vs. older than 12 years with 78% accuracy. Additionally, we extract relevant patterns of head movement upon which the age distinction was determined by our models.

Reduced Fusiform Gyrus Activation During Face Processing in Pediatric Brain Tumor Survivors.

OBJECTIVE: The neural mechanisms contributing to the social problems of pediatric brain tumor survivors (PBTS) are unknown. Face processing is important to social communication, social behavior, and peer acceptance. Research with other populations with social difficulties, namely autism spectrum disorder, suggests atypical brain activation in areas important for face processing. This case-controlled functional magnetic resonance imaging (fMRI) study compared brain activation during face processing in PBTS and typically developing (TD) youth. METHODS: Participants included 36 age-, gender-, and IQ-matched youth (N = 18 per group). PBTS were at least 5 years from diagnosis and 2 years from the completion of tumor therapy. fMRI data were acquired during a face identity task and a control condition. Groups were compared on activation magnitude within the fusiform gyrus for the faces condition compared to the control condition. Correlational analyses evaluated associations between neuroimaging metrics and indices of social behavior for PBTS participants. RESULTS: Both groups demonstrated face-specific activation within the social brain for the faces condition compared to the control condition. PBTS showed significantly decreased activation for faces in the medial portions of the fusiform gyrus bilaterally compared to TD youth, ps ≤ .004. Higher peak activity in the left fusiform gyrus was associated with better socialization (r = .53, p < .05). CONCLUSIONS: This study offers initial evidence of atypical activation in a key face processing area in PBTS. Such atypical activation may underlie some of the social difficulties of PBTS. Social cognitive neuroscience methodologies may elucidate the neurobiological bases for PBTS social behavior.

Evaluating commercially available wireless cardiovascular monitors for measuring and transmitting real-time physiological responses in children with autism.

Commercially available wearable biosensors have the potential to enhance psychophysiology research and digital health technologies for autism by enabling stress or arousal monitoring in naturalistic settings. However, such monitors may not be comfortable for children with autism due to sensory sensitivities. To determine the feasibility of wearable technology in children with autism age 8-12 years, we first selected six consumer-grade wireless cardiovascular monitors and tested them during rest and movement conditions in 23 typically developing adults. Subsequently, the best performing monitors (based on data quality robustness statistics), Polar and Mio Fuse, were evaluated in 32 children with autism and 23 typically developing children during a 2-h session, including rest and mild stress-inducing tasks. Cardiovascular data were recorded simultaneously across monitors using custom software. We administered the Comfort Rating Scales to children. Although the Polar monitor was less comfortable for children with autism than typically developing children, absolute scores demonstrated that, on average, all children found each monitor comfortable. For most children, data from the Mio Fuse (96%-100%) and Polar (83%-96%) passed quality thresholds of data robustness. Moreover, in the stress relative to rest condition, heart rate increased for the Polar, F(1,53) = 135.70, p < 0.001, ηp2  = 0.78, and Mio Fuse, F(1,53) = 71.98, p < 0.001, ηp2  = 0.61, respectively, and heart rate variability decreased for the Polar, F(1,53) = 13.41, p = 0.001, ηp2  = 0.26, and Mio Fuse, F(1,53) = 8.89, p = 0.005, ηp2  = 0.16, respectively. This feasibility study suggests that select consumer-grade wearable cardiovascular monitors can be used with children with autism and may be a promising means for tracking physiological stress or arousal responses in community settings. LAY SUMMARY: Commercially available heart rate trackers have the potential to advance stress research with individuals with autism. Due to sensory sensitivities common in autism, their comfort wearing such trackers is vital to gathering robust and valid data. After assessing six trackers with typically developing adults, we tested the best trackers (based on data quality) in typically developing children and children with autism and found that two of them met criteria for comfort, robustness, and validity.

Decreased Neural Connectivity in the Default Mode Network Among Youth and Young Adults With Chronic Kidney Disease.

An increasing amount of literature has indicated that chronic kidney disease (CKD) is associated with cognitive deficits that increase with worsening disease severity. Although abnormalities in brain structure have been widely documented, few studies to date have examined the functioning of brain areas associated with the specific cognitive domains affected by CKD (namely, attention and executive functions). Furthermore, few studies have examined functional connectivity among CKD youth who are relatively early in the course of the disease. The present study used functional magnetic resonance imaging to examine the resting state connectivity in 67 youth with CKD (mean age, 17 y) and 58 age-matched healthy controls. Using seed-based multiple regression, decreased connectivity was observed within the anterior cingulate portion of the default mode network. In addition, decreased connectivity within the dorsolateral prefrontal cortex, paracingulate gyrus, and frontal pole were correlated significantly with disease severity. These data indicate that connectivity deficits in circuits implementing attentional processes may represent an early marker for cognitive decline in CKD.

Dissociating regional gray matter density and gray matter volume in autism spectrum condition.

BACKGROUND: Despite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both. METHODS: Differences in MRI-based GM density and volume were examined in 6-25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47-154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67-155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods. RESULTS: No density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions. LIMITATIONS: The method for determining "density" is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences. CONCLUSIONS: These results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Discovering Synchronized Subsets of Sequences: A Large Scale Solution.

Finding the largest subset of sequences (i.e., time series) that are correlated above a certain threshold, within large datasets, is of significant interest for computer vision and pattern recognition problems across domains, including behavior analysis, computational biology, neuroscience, and finance. Maximal clique algorithms can be used to solve this problem, but they are not scalable. We present an approximate, but highly efficient and scalable, method that represents the search space as a union of sets called ϵ-expanded clusters, one of which is theoretically guaranteed to contain the largest subset of synchronized sequences. The method finds synchronized sets by fitting a Euclidean ball on ϵ-expanded clusters, using Jung's theorem. We validate the method on data from the three distinct domains of facial behavior analysis, finance, and neuroscience, where we respectively discover the synchrony among pixels of face videos, stock market item prices, and dynamic brain connectivity data. Experiments show that our method produces results comparable to, but up to 300 times faster than, maximal clique algorithms, with speed gains increasing exponentially with the number of input sequences.

Computer Vision Analysis of Reduced Interpersonal Affect Coordination in Youth With Autism Spectrum Disorder.

Atypical social-emotional reciprocity is a core feature of autism spectrum disorder (ASD) but can be difficult to operationalize. One measurable manifestation of reciprocity may be interpersonal coordination, the tendency to align the form and timing of one's behaviors (including facial affect) with others. Interpersonal affect coordination facilitates sharing and understanding of emotional cues, and there is evidence that it is reduced in ASD. However, most research has not measured this process in true social contexts, due in part to a lack of tools for measuring dynamic facial expressions over the course of an interaction. Automated facial analysis via computer vision provides an efficient, granular, objective method for measuring naturally occurring facial affect and coordination. Youth with ASD and matched typically developing youth participated in cooperative conversations with their mothers and unfamiliar adults. Time-synchronized videos were analyzed with an open-source computer vision toolkit for automated facial analysis, for the presence and intensity of facial movements associated with positive affect. Both youth and adult conversation partners exhibited less positive affect during conversations when the youth partner had ASD. Youth with ASD also engaged in less affect coordination over the course of conversations. When considered dimensionally across youth with and without ASD, affect coordination significantly predicted scores on rating scales of autism-related social atypicality, adaptive social skills, and empathy. Findings suggest that affect coordination is an important interpersonal process with implications for broader social-emotional functioning. This preliminary study introduces a promising novel method for quantifying moment-to-moment facial expression and emotional reciprocity during natural interactions. LAY SUMMARY: This study introduces a novel, automated method for measuring social-emotional reciprocity during natural conversations, which may improve assessment of this core autism diagnostic behavior. We used computerized methods to measure facial affect and the degree of affect coordination between conversation partners. Youth with autism displayed reduced affect coordination, and reduced affect coordination predicted lower scores on measures of broader social-emotional skills.

Reliability and validity of the Pediatric Anxiety Rating Scale modified for autism spectrum disorder.

LAY ABSTRACT: Many youth with autism spectrum disorder have anxiety, but it can be difficult to assess anxiety with existing measures. We modified the Pediatric Anxiety Rating Scale for youth with autism spectrum disorder and tested the new measure in a group of 116 youth (age: 5-17 years) with autism spectrum disorder. The Pediatric Anxiety Rating Scale for youth with autism spectrum disorder is an interview that a clinician usually completes with the child and parent together. We modified the interview questions and scoring instructions based on feedback from parents of children with autism spectrum disorder and from a panel of experts in autism spectrum disorder and anxiety. Unlike many other anxiety measures, the Pediatric Anxiety Rating Scale for youth with autism spectrum disorder relies less on a child's verbal expression of anxiety and more on signs that a parent can easily observe. Training clinicians to administer and score the Pediatric Anxiety Rating Scale for youth with autism spectrum disorder was uncomplicated, and raters showed excellent agreement on video-recorded interviews. Youth who were not currently in treatment for anxiety had stable Pediatric Anxiety Rating Scale for youth with autism spectrum disorder scores with repeat measurement over a 1-month period. The Pediatric Anxiety Rating Scale for youth with autism spectrum disorder is a useful clinician-rated measure of anxiety in youth with autism spectrum disorder and fills a gap for assessing anxiety in this population.

Evidence against the "normalization" prediction of the early brain overgrowth hypothesis of autism.

BACKGROUND: The frequently cited Early Overgrowth Hypothesis of autism spectrum disorder (ASD) postulates that there is overgrowth of the brain in the first 2 years of life, which is followed by a period of arrested growth leading to normalized brain volume in late childhood and beyond. While there is consistent evidence for early brain overgrowth, there is mixed evidence for normalization of brain volume by middle childhood. The outcome of this debate is important to understanding the etiology and neurodevelopmental trajectories of ASD. METHODS: Brain volume was examined in two very large single-site samples of children, adolescents, and adults. The primary sample comprised 456 6-25-year-olds (ASD n = 240, typically developing controls (TDC) n = 216), including a large number of females (n = 102) and spanning a wide IQ range (47-158). The replication sample included 175 males. High-resolution T1-weighted anatomical MRI images were examined for group differences in total brain, cerebellar, ventricular, gray, and white matter volumes. RESULTS: The ASD group had significantly larger total brain, cerebellar, gray matter, white matter, and lateral ventricular volumes in both samples, indicating that brain volume remains enlarged through young adulthood, rather than normalizing. There were no significant age or sex interactions with diagnosis in these measures. However, a significant diagnosis-by-IQ interaction was detected in the larger sample, such that increased brain volume was related to higher IQ in the TDCs, but not in the ASD group. Regions-of-significance analysis indicated that total brain volume was larger in ASD than TDC for individuals with IQ less than 115, providing a potential explanation for prior inconsistent brain size results. No relationships were found between brain volume and measures of autism symptom severity within the ASD group. LIMITATIONS: Our cross-sectional sample may not reflect individual changes over time in brain volume and cannot quantify potential changes in volume prior to age 6. CONCLUSIONS: These findings challenge the "normalization" prediction of the brain overgrowth hypothesis by demonstrating that brain enlargement persists across childhood into early adulthood. The findings raise questions about the clinical implications of brain enlargement, since we find that it neither confers cognitive benefits nor predicts increased symptom severity in ASD.

A Pilot Study of Cardiovascular Reactivity in Children With Autism Spectrum Disorder.

In preparation for a larger case-control study of children with autism spectrum disorder (ASD) and anxiety, we conducted a pilot study using a noninvasive electrocardiographic device to measure cardiovascular reactivity in 10 children (age range 9-14) with ASD. The 45-minute procedure included 6 conditions: baseline rest, an interview about school, interim rest, an unfair computerized ball-toss game followed by a fair version of the game, and a final rest. Data were successfully collected for 95% of all conditions. Omnibus Skillings-Mack tests suggested that heart rate variability variables including mean heart rate, mean RR interval, and root mean square of successive differences showed statistically significant variation across conditions. The procedure appears feasible and may be an informative biomarker of anxiety in ASD.

Diminished social attention in pediatric brain tumor survivors: Using eye tracking technology during naturalistic social perception.

OBJECTIVE: The etiology of pediatric brain tumor survivor (PBTSs) social difficulties is not well understood. A model of social competence for youth with brain disorder and evidence from youth with autism spectrum disorder (ASD) suggests that diminished social attention may underlie social deficits in PBTSs. This study used eye tracking technology to compare visual social attention in PBTSs, youth with ASD, and typically developing (TD) youth. METHODS: Participants included 90 age-, gender-, and IQ-matched youth (N = 30 per group). PBTSs were at least 5 years from diagnosis and 2 years from the completion of tumor-directed therapy. Participants' eye gaze patterns were recorded while watching an established social play paradigm that presented videos of children engaging in either interactive or parallel play. Group differences in proportional gaze duration toward social versus nonsocial areas of interest were compared. Medical correlates of social attention in PBTSs were evaluated. RESULTS: Groups significantly differed in gaze preference across conditions, with PBTSs looking less at social areas of interest than TD youth and in a manner comparable to youth with ASD. Among PBTSs, multimodal tumor-directed therapy was associated with reduced gaze preference for faces. CONCLUSIONS: This study provides the first evidence of disrupted social attention in PBTSs, with parallels to the social attention deficits observed in ASD. Findings offer a new way to conceptualize the social difficulties of PBTSs and could guide interventions aimed at improving PBTS social adjustment by increasing visual attention to socially relevant information during social interactions. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Bayesian regression-based developmental norms for the Benton Facial Recognition Test in males and females.

Face identity recognition is important for social interaction and is impaired in a range of clinical disorders, including several neurodevelopmental disorders. The Benton Facial Recognition Test (BFRT; Benton & Van Allen, 1968), a widely used assessment of identity recognition, is the only standardized test of face identity perception, as opposed to face memory, that has been normed on children and adolescents. However, the existing norms for the BFRT are suboptimal, with several ages not represented and no established time limit (which can lead to inflated scores by allowing individuals with prosopagnosia to use feature matching). Here we address these issues with a large normative dataset of children and adolescents (ages 5-17, N = 398) and adults (ages 18-55; N = 120) who completed a time-limited version of the BFRT. Using Bayesian regression, we demonstrate that face identity perception increases asymptotically from childhood through adulthood, and provide continuous norms based on age and sex that can be used to calculate standard scores. We show that our time limit of 16 seconds per item yields scores comparable to the existing norms without time limits from the non-prosopagnostic samples. We also find that females (N = 156) score significantly higher than males (N = 362), supporting the existence of a female superiority effect for face identification. Overall, these results provide more robust norms for the BFRT and promote future research on face identity perception in developmental populations.

Caregiver Report of Executive Functioning in Adolescent Females With Anorexia Nervosa or Autism Spectrum Disorder.

Current literature suggesting a shared endophenotype between individuals with anorexia nervosa (AN) and autism spectrum disorder (ASD) related to executive functioning (EF) has several limitations: performance-based instead of ecologically valid measures of set-shifting are used, lack of comparisons between same-sex groups, and reliance on adult samples only. This was the first study directly comparing female youth with ASD to female youth with AN using an ecologically valid measure of EF. A secondary data analysis combined caregiver-reported EF on the Behavior Rating Inventory of Executive Functioning (BRIEF) for 22 female adolescent youth with AN and 29 female adolescent youth with ASD. EF in each group was compared to population norms, and EF was compared between groups. Compared to population norms, adolescents with AN had elevated scores on shift, initiate, and emotional control scales, and adolescents with ASD had elevated scores on all scales of the BRIEF and were more likely to have scores in the clinical range. There were significant differences between groups on all but three scales. The cognitive profiles and clinical scores of AN females were not comparable to those of ASD females. The findings reveal a clear clinical impairment in females with ASD but not in females with AN. The results do not support the hypothesis of similar real-world EF profiles between these groups. The results encourage further exploration into the similarities and distinctions between these two disorders.

Functional Connectivity of Frontoparietal and Salience/Ventral Attention Networks Have Independent Associations With Co-occurring Attention-Deficit/Hyperactivity Disorder Symptoms in Children With Autism.

BACKGROUND: Children with autism spectrum disorder (ASD) and co-occurring attention-deficit/hyperactivity disorder (ADHD) symptoms have worse functional outcomes and treatment response than those without ADHD symptoms. There is limited knowledge of the neurobiology of ADHD symptoms in ASD. Here, we test the hypothesis that aberrant functional connectivity of two large-scale executive brain networks implicated in ADHD-the frontoparietal and salience/ventral attention networks-also play a role in ADHD symptoms in ASD. METHODS: We compared resting-state functional connectivity of the two executive brain networks in children with ASD (n = 77) and typically developing control children (n = 82). These two executive brain networks comprise five subnetworks (three frontoparietal, two salience/ventral attention). After identifying aberrant functional connections among subnetworks, we examined dimensional associations with parent-reported ADHD symptoms. RESULTS: Weaker functional connectivity in ASD was present within and between the frontoparietal and salience/ventral attention subnetworks. Decreased functional connectivity within a single salience/ventral attention subnetwork, as well as between two frontoparietal subnetworks, significantly correlated with ADHD symptoms. Furthermore, follow-up linear regressions demonstrated that the salience/ventral attention and frontoparietal subnetworks explain unique variance in ADHD symptoms. These executive brain network-ADHD symptom relationships remained significant after controlling for ASD symptoms. Finally, specificity was also demonstrated through the use of a control brain network (visual) and a control co-occurring symptom domain (anxiety). CONCLUSIONS: The present findings provide novel evidence that both frontoparietal and salience/ventral attention networks' weaker connectivities are linked to ADHD symptoms in ASD. Moreover, co-occurring ADHD in the context of ASD is a source of meaningful neural heterogeneity in ASD.

Arterial spin labeling provides a reliable neurobiological marker of autism spectrum disorder.

BACKGROUND: Research on neurobiological markers of autism spectrum disorder (ASD) has been elusive. However, radionuclide studies of cerebral blood flow (CBF) have shown decreased blood flow (hypoperfusion) in the temporal lobes of individuals with ASD across ages and intelligence. This observation fits with current neuroscientific models that implicate temporal regions in social perception and social cognition. Arterial spin labeled perfusion MRI allows noninvasive quantification of regional CBF as part of a multimodal MRI protocol. This method is almost entirely absent from ASD research to date. Our a priori hypothesis was that children with ASD would present with hypoperfusion in the temporal lobes-most notably the fusiform gyrus (given its prominent role in ASD social perception deficits). We also sought to examine the reproducibility of CBF measures, and their relationship to individual differences in facial recognition and ASD symptoms. METHODS: A total of 58 males (33 with ASD) between the ages of 12 and 17 years participated in the study. All children completed two arterial spin labeling and structural (T1) scans using a 3 T Siemens Verio scanner approximately 8 weeks apart, as well as behavioral testing at time 1 that included diagnostic measures and the Benton Facial Recognition Test. CBF was the key dependent variable, as was facial recognition performance, and ASD symptoms. The two scans were used for reliability analyses. RESULTS: The ASD group showed hypoperfusion in the bilateral fusiform gyrus and in right inferior temporal gyrus. Intra-class correlations showed moderate to good reliability across time within both groups, and no diagnostic group × time interactions. CBF in the left fusiform gyrus was significantly positively correlated with facial recognition. No significant correlations were observed with core ASD symptoms. CONCLUSIONS: Arterial spin labeling revealed hypoperfusion in children with ASD in regions critical to social perception and cognition. The left fusiform gyrus plays an important role in facial recognition, and greater CBF in this region was correlated with more normative facial recognition performance in children with ASD. This study takes an important first step in establishing CBF of the temporal lobes as a reliable marker of ASD.

Evaluation of the Social Motivation Hypothesis of Autism: A Systematic Review and Meta-analysis.

Importance: The social motivation hypothesis posits that individuals with autism spectrum disorder (ASD) find social stimuli less rewarding than do people with neurotypical activity. However, functional magnetic resonance imaging (fMRI) studies of reward processing have yielded mixed results. Objectives: To examine whether individuals with ASD process rewarding stimuli differently than typically developing individuals (controls), whether differences are limited to social rewards, and whether contradictory findings in the literature might be due to sample characteristics. Data Sources: Articles were identified in PubMed, Embase, and PsycINFO from database inception until June 1, 2017. Functional MRI data from these articles were provided by most authors. Study Selection: Publications were included that provided brain activation contrasts between a sample with ASD and controls on a reward task, determined by multiple reviewer consensus. Data Extraction and Synthesis: When fMRI data were not provided by authors, multiple reviewers extracted peak coordinates and effect sizes from articles to recreate statistical maps using seed-based d mapping software. Random-effects meta-analyses of responses to social, nonsocial, and restricted interest stimuli, as well as all of these domains together, were performed. Secondary analyses included meta-analyses of wanting and liking, meta-regression with age, and correlations with ASD severity. All procedures were conducted in accordance with Meta-analysis of Observational Studies in Epidemiology guidelines. Main Outcomes and Measures: Brain activation differences between groups with ASD and typically developing controls while processing rewards. All analyses except the domain-general meta-analysis were planned before data collection. Results: The meta-analysis included 13 studies (30 total fMRI contrasts) from 259 individuals with ASD and 246 controls. Autism spectrum disorder was associated with aberrant processing of both social and nonsocial rewards in striatal regions and increased activation in response to restricted interests (social reward, caudate cluster: d = -0.25 [95% CI, -0.41 to -0.08]; nonsocial reward, caudate and anterior cingulate cluster: d = -0.22 [95% CI, -0.42 to -0.02]; restricted interests, caudate and nucleus accumbens cluster: d = 0.42 [95% CI, 0.07 to 0.78]). Conclusions and Relevance: Individuals with ASD show atypical processing of social and nonsocial rewards. Findings support a broader interpretation of the social motivation hypothesis of ASD whereby general atypical reward processing encompasses social reward, nonsocial reward, and perhaps restricted interests. This meta-analysis also suggests that prior mixed results could be driven by sample age differences, warranting further study of the developmental trajectory for reward processing in ASD.