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.

Social impairment in survivors of pediatric brain tumors via reduced social attention and emotion-specific facial expression recognition.

BACKGROUND/OBJECTIVES: Survivors of pediatric brain tumors (SPBT) experience significant social challenges, including fewer friends and greater isolation than peers. Difficulties in face processing and visual social attention have been implicated in these outcomes. This study evaluated facial expression recognition (FER), social attention, and their associations with social impairments in SPBT. METHODS: SPBT (N = 54; ages 7-16) at least 2 years post treatment completed a measure of FER, while parents completed measures of social impairment. A subset (N = 30) completed a social attention assessment that recorded eye gaze patterns while watching videos depicting pairs of children engaged in joint play. Social Prioritization scores were calculated, with higher scores indicating more face looking. Correlations and regression analyses evaluated associations between variables, while a path analysis modeling tool (PROCESS) evaluated the indirect effects of Social Prioritization on social impairments through emotion-specific FER. RESULTS: Poorer recognition of angry and sad facial expressions was significantly correlated with greater social impairment. Social Prioritization was positively correlated with angry FER but no other emotions. Social Prioritization had significant indirect effects on social impairments through angry FER. CONCLUSION: Findings suggest interventions aimed at improving recognition of specific emotions may mitigate social impairments in SPBT. Further, reduced social attention (i.e., diminished face looking) could be a factor in reduced face processing ability, which may result in social impairments. Longitudinal research is needed to elucidate temporal associations between social attention, face processing, and social impairments.

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.

Creation of a versatile automated two-step purification system with increased throughput capacity for preclinical mAb material generation.

The ever-increasing speed of biotherapeutic drug discovery has driven the development of automated and high throughput purification capabilities. Typically, purification systems require complex flow paths or third-party components that are not found on a standard fast protein liquid chromatography instrument (FPLC) (e.g., Cytiva's ÄKTA) to enable higher throughput. In early mAb discovery there is often a trade-off between throughput and scale where a high-throughput process requires miniaturized workflows necessitating a sacrifice in the amount of material generated. At the interface of discovery and development, flexible automated systems are required that can perform purifications in a high-throughput manner, while also generating sufficient quantities of preclinical material for biophysical, developability, and preclinical animal studies. In this study we highlight the engineering efforts to generate a highly versatile purification system capable of balancing the purification requirements between throughput, chromatographic versatility, and overall product yields. We incorporated a 150 mL Superloop into an ÄKTA FPLC system to expand our existing purification capabilities. This allowed us to perform a range of automated two-step tandem purifications including primary affinity captures (protein A (ProA)/immobilized metal affinity chromatography (IMAC)/antibody fragment (Fab)) followed by secondary polishing with either size exclusion (SEC) or cation exchange (CEX) chromatography. We also integrated a 96 deep-well plate fraction collector into the ÄKTA FPLC system with purified protein fractions being analyzed by a plate based high performance liquid chromatography instrument (HPLC). This streamlined automated purification workflow allowed us to process up to 14 samples within 24 h, enabling purification of ∼1100 proteins, monoclonal antibodies (mAbs), and mAb related protein scaffolds during a 12-month period. We purified a broad range of cell culture supernatant volumes, between 0.1 and 2 L, with final purification yields up to 2 g. The implementation of this new automated, streamlined protein purification process greatly expanded our sample throughput and purification versatility while also enabling the accelerated production of greater quantities of biotherapeutic candidates for preclinical in vivo animal studies and developability assessment.

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.

Face Processing and Social Functioning in Pediatric Brain Tumor Survivors.

OBJECTIVE: Pediatric brain tumor survivors (PBTS) experience deficits in social functioning. Facial expression and identity recognition are key components of social information processing and are widely studied as an index of social difficulties in youth with autism spectrum disorder (ASD) and other neurodevelopmental conditions. This study evaluated facial expression and identity recognition among PBTS, youth with ASD, and typically developing (TD) youth, and the associations between these face processing skills and social impairments. METHODS: PBTS (N = 54; ages 7-16) who completed treatment at least 2 years prior were matched with TD (N = 43) youth and youth with ASD (N = 55) based on sex and IQ. Parents completed a measure of social impairments and youth completed a measure of facial expression and identity recognition. RESULTS: Groups significantly differed on social impairments (p < .001), with youth with ASD scoring highest followed by PBTS and lastly TD youth. Youth with ASD performed significantly worse on the two measures of facial processing, while TD youth and PBTS were not statistically different. The association of facial expression recognition and social impairments was moderated by group, such that PBTS with higher levels of social impairment performed worse on the expression task compared to TD and ASD groups (p < .01, η2 = 0.07). CONCLUSIONS: Variability in face processing may be uniquely important to the social challenges of PBTS compared to other neurodevelopmental populations. Future directions include prospectively examining associations between facial expression recognition and social difficulties in PBTS and face processing training as an intervention for PBTS.

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.

Heart rate increase predicts challenging behavior episodes in preschoolers with autism.

Identifying triggers for challenging behavior is difficult in some children with autism because of their limited communication abilities. Physiological indicators of stress may provide important insights. This study examined whether heart rate (HR) predicts challenging behavior in children with autism. While wearing an electrocardiograph monitor, 41 children with autism aged 2- to 4-years participated in tasks designed to induce low-level stress (e.g. waiting for a snack). Coders identified 106 time periods during which challenging behaviors occurred and also coded 106 randomly selected time samples that did not include challenging behaviors. Thirteen (32%) participants exhibited challenging behaviors and were included in the study. Baseline-corrected HR was computed for each behavior/time sample. On average, children with autism showed a 22 ± 16% HR increase from baseline 58 ± 22 seconds before the onset of a challenging behavior episode. Peak HR change had moderate predictive utility (area under the curve = .72, p < .001). The increase in HR before challenging behaviors was similar for children of different characteristics (age, autism severity, expressive language ability, overall developmental ability). Results highlight the promise of using physiological stress to predict challenging behavior in preschoolers with autism; although, they need to be replicated in larger samples. Given recent advances in wearable biosensing, it may be useful to incorporate HR monitoring in autism intervention. Lay summary In children with autism, changes in heart rate (HR) may help us predict when challenging behavior is about to occur - but this hypothesis has not been well studied. In this study, HR increase moderately predicted challenging behavior in preschoolers with autism. Given recent advances in wearable sensors, it may be useful to incorporate HR monitoring in autism intervention.

Translating Adult Electrophysiology Findings to Younger Patient Populations: Difficulty Measuring 40-Hz Auditory Steady-State Responses in Typically Developing Children and Children with Autism Spectrum Disorder.

BACKGROUND: x03B3; (∼30-80 Hz) brain rhythms are thought to be abnormal in neurodevelopmental disorders such as schizophrenia and autism spectrum disorder (ASD). In adult populations, auditory 40-Hz click trains or 40-Hz amplitude-modulated tones are used to assess the integrity of superior temporal gyrus (STG) 40-Hz x03B3;-band circuits. As STG 40-Hz auditory steady-state responses (ASSRs) are not fully developed in children, tasks using these stimuli may not be optimal in younger patient populations. The present study examined this issue in typically developing (TD) children as well as in children with ASD, using source localization to directly assess activity in the principal generators of the 40-Hz ASSR in the left and right primary/secondary auditory cortices. METHODS: 40-Hz amplitude-modulated tones of 1 s duration were binaurally presented while magnetoencephalography data were obtained from 48 TD children (45 males; 7-14 years old) and 42 ASD children (38 males; 8-14 years old). T1-weighted structural MRI was obtained. Using single dipoles anatomically constrained to each participant's left and right Heschl's Gyrus, left and right 40-Hz ASSR total power (TP) and intertrial coherence (ITC) measures were obtained. Associations between 40-Hz ASSR TP, ITC and age as well as STG gray matter cortical thickness (CT) were assessed. Group STG function and structure differences were also examined. RESULTS: TD and ASD did not differ in 40-Hz ASSR TP or ITC. In TD and ASD, age was associated with left and right 40-Hz ASSR ITC (p < 0.01). The interaction term was not significant, indicating in both groups a ∼0.01/year increase in ITC. 40-Hz ASSR TP and ITC were greater in the right than left STG. Groups did not differ in STG CT, and no associations were observed between 40-Hz ASSR activity and STG CT. Finally, right STG transient x03B3; (50-100 ms and 30-50 Hz) was greater in TD versus ASD (significant for TP, trend for ITC). CONCLUSIONS: The 40-Hz ASSR develops, in part, via an age-related increase in neural synchrony. Greater right than left 40-Hz ASSRs (ITC and TP) suggested earlier maturation of right versus left STG neural network(s). Given a ∼0.01/year increase in ITC, 40-Hz ASSRs were weak or absent in many of the younger participants, suggesting that 40-Hz driving stimuli are not optimal for examining STG 40-Hz auditory neural circuits in younger populations. Given the caveat that 40-Hz auditory steady-state neural networks are poorly assessed in children, the present analyses did not point to atypical development of STG 40-Hz ASSRs in higher-functioning children with ASD. Although groups did not differ in 40-Hz auditory steady-state activity, replicating previous studies, there was evidence for greater right STG transient x03B3; activity in TD versus ASD.

Commentary: Cognitive and emotional empathy in transdiagnostic research - reflections on Klapwijk et al. (2016).

Evidence across multiple disorders indicates that empathy is a transdiagnostic dimension of psychopathology. Klapwijk et al.'s (2016) functional MRI study examines whether autism spectrum disorder (ASD) and conduct disorder (CD) can be distinguished by the constructs of 'cognitive' and 'emotional' empathy - with the former focusing on accurate emotion perception and the latter on shared affective experience. This commentary examines the implications of the cognitive/emotional empathy distinction, and how it fits with existing accounts of perceptual differences in ASD. Cognitive empathy overlaps substantially with the constructs of emotion perception and Theory of Mind - both well studied among individuals with ASD, but generally viewed as fairly distinct from empathy. CD, on the other hand, is typically not associated with frank perceptual deficits. Although the brain imaging data from this study do not provide strong support for the constructs of cognitive and emotional empathy, the general approach used in this study is precisely the kind needed to test the validity and utility of transdiagnostic mechanisms of psychopathology.

Design and methods of the NiCK study: neurocognitive assessment and magnetic resonance imaging analysis of children and young adults with chronic kidney disease.

BACKGROUND: Chronic kidney disease is strongly linked to neurocognitive deficits in adults and children, but the pathophysiologic processes leading to these deficits remain poorly understood. The NiCK study (Neurocognitive Assessment and Magnetic Resonance Imaging Analysis of Children and Young Adults with Chronic Kidney Disease) seeks to address critical gaps in our understanding of the biological basis for neurologic abnormalities in chronic kidney disease. In this report, we describe the objectives, design, and methods of the NiCK study. DESIGN/METHODS: The NiCK Study is a cross-sectional cohort study in which neurocognitive and neuroimaging phenotyping is performed in children and young adults, aged 8 to 25 years, with chronic kidney disease compared to healthy controls. Assessments include (1) comprehensive neurocognitive testing (using traditional and computerized methods); (2) detailed clinical phenotyping; and (3) multimodal magnetic resonance imaging (MRI) to assess brain structure (using T1-weighted MRI, T2-weighted MRI, and diffusion tensor imaging), functional connectivity (using functional MRI), and blood flow (using arterial spin labeled MRI). Primary analyses will examine group differences in neurocognitive testing and neuroimaging between subjects with chronic kidney disease and healthy controls. Mechanisms responsible for neurocognitive dysfunction resulting from kidney disease will be explored by examining associations between neurocognitive testing and regional changes in brain structure, functional connectivity, or blood flow. In addition, the neurologic impact of kidney disease comorbidities such as anemia and hypertension will be explored. We highlight aspects of our analytical approach that illustrate the challenges and opportunities posed by data of this scope. DISCUSSION: The NiCK study provides a unique opportunity to address key questions about the biological basis of neurocognitive deficits in chronic kidney disease. Understanding these mechanisms could have great public health impact by guiding screening strategies, delivery of health information, and targeted treatment strategies for chronic kidney disease and its related comorbidities.

Multimodal imaging in autism: an early review of comprehensive neural circuit characterization.

There is accumulating evidence that the neurobiology of autism spectrum disorders (ASD) is linked to atypical neural communication and connectivity. This body of work emphasizes the need to characterize the function of multiple regions that comprise neural circuits rather than focusing on singular regions as contributing to deficits in ASD. Multimodal neuroimaging - the formal combination of multiple functional and structural measures of the brain - is extremely promising as an approach to understanding neural deficits in ASD. This review provides an overview of the multimodal imaging approach, and then provides a snapshot of how multimodal imaging has been applied in the study of ASD to date. This body of work is separated into two categories: one concerning whole brain connectomics and the other focused on characterizing neural circuits implicated as altered in ASD. We end this review by highlighting emerging themes from the existing body of literature, and new resources that will likely influence future multimodal imaging studies.

Ethical considerations for integrating multimodal computer perception and neurotechnology.

Background: Artificial intelligence (AI)-based computer perception technologies (e.g., digital phenotyping and affective computing) promise to transform clinical approaches to personalized care in psychiatry and beyond by offering more objective measures of emotional states and behavior, enabling precision treatment, diagnosis, and symptom monitoring. At the same time, passive and continuous nature by which they often collect data from patients in non-clinical settings raises ethical issues related to privacy and self-determination. Little is known about how such concerns may be exacerbated by the integration of neural data, as parallel advances in computer perception, AI, and neurotechnology enable new insights into subjective states. Here, we present findings from a multi-site NCATS-funded study of ethical considerations for translating computer perception into clinical care and contextualize them within the neuroethics and neurorights literatures. Methods: We conducted qualitative interviews with patients (n = 20), caregivers (n = 20), clinicians (n = 12), developers (n = 12), and clinician developers (n = 2) regarding their perspective toward using PC in clinical care. Transcripts were analyzed in MAXQDA using Thematic Content Analysis. Results: Stakeholder groups voiced concerns related to (1) perceived invasiveness of passive and continuous data collection in private settings; (2) data protection and security and the potential for negative downstream/future impacts on patients of unintended disclosure; and (3) ethical issues related to patients' limited versus hyper awareness of passive and continuous data collection and monitoring. Clinicians and developers highlighted that these concerns may be exacerbated by the integration of neural data with other computer perception data. Discussion: Our findings suggest that the integration of neurotechnologies with existing computer perception technologies raises novel concerns around dignity-related and other harms (e.g., stigma, discrimination) that stem from data security threats and the growing potential for reidentification of sensitive data. Further, our findings suggest that patients' awareness and preoccupation with feeling monitored via computer sensors ranges from hypo- to hyper-awareness, with either extreme accompanied by ethical concerns (consent vs. anxiety and preoccupation). These results highlight the need for systematic research into how best to implement these technologies into clinical care in ways that reduce disruption, maximize patient benefits, and mitigate long-term risks associated with the passive collection of sensitive emotional, behavioral and neural data.

Physiological and communicative emotional disconcordance in children on the autism spectrum.

BACKGROUND: Individuals on the autism spectrum commonly have differences from non-autistic people in expressing their emotions using communicative behaviors, such as facial expressions. However, it is not yet clear if this reduced expressivity stems from reduced physiological reactivity in emotional contexts or if individuals react internally, but do not show these reactions externally to others. We hypothesized that autism is characterized by a discordance between in-the-moment internal psychophysiological arousal and external communicative expressions of emotion. METHODS: Forty-one children on the autism spectrum and 39 non-autistic, typically developing (TD) children of two age groups (2-4 and 8-12 years) participated in a low-level stress task whilst wearing a wireless electrocardiogram. Children's negative emotional expressions (facial, vocal, bodily) were coded following standardized protocols. Alexithymia traits were assessed using the Children's Alexithymia Measure with school-aged children only. Data analyses involved ANOVAs, correlations, and sensitivity analyses. RESULTS: There were no group differences in physiological arousal (heart rate) or in communicative expressions of stress to the stress task. For TD preschoolers, physiological arousal during the stress task was associated with vocal expressions and for TD school-aged children, they were associated with facial and bodily expressions. By contrast, for children on the autism spectrum, physiological arousal during the stress tasks was not associated with communicative expressions across age groups. CONCLUSIONS: Our findings suggest that children on the autism spectrum might experience emotional disconcordance, in that their physiological arousal does not align with their communicative expressions. Therefore, the internally experienced stress of children on the autism spectrum may be inadvertently missed by teachers and caregivers and, consequently, learning opportunities for teaching emotional communication and regulation may be also missed. Our results support the use of wearable biosensors to facilitate such interventions in children on the autism spectrum.

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.

Sleep problems in autism: Sex differences in the school-age population.

Clinically significant sleep problems affect up to 86% of the autistic population in school-age. Sleep problems can have negative impacts on child cognition, behavior, and health. However, sex differences in the prevalence and types of sleep problems are not well understood in autism. To evaluate sex differences in sleep problems in the school-age autistic population, we obtained parent-report of sleep problems on the Children's Sleep Habits Questionnaire and conducted direct assessments to establish diagnosis and intellectual ability in 6-12-year-old children (autism n = 250; typical development [TD] n = 114). Almost 85% of autistic females demonstrated sleep problems compared to 65.8% of autistic males, 44.8% of TD females, and 42.4% of TD males; a statistically significant increase for autistic females. Autistic females demonstrated increased bedtime resistance, sleep anxiety, and sleepiness, and decreased sleep duration, but did not differ in sleep onset delay, night wakings, parasomnias, or disordered breathing compared with autistic males. Intellectual ability was not related to increased sleep problems. Higher anxiety scores were associated with more sleep problems for males but not females. In one of the first studies to evaluate sex differences in sleep in the school-age, autistic population, autistic females demonstrated increased sleep problems compared to autistic males, TD females, and TD males. Current autism assessment and intervention practices may benefit from increased attention to sleep problems in autistic school-age females and to anxiety in autistic males to enhance well-being and behavioral and health outcomes.

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.

The responsiveness of biological motion processing areas to selective attention towards goals.

A growing literature indicates that visual cortex areas viewed as primarily responsive to exogenous stimuli are susceptible to top-down modulation by selective attention. The present study examines whether brain areas involved in biological motion perception are among these areas-particularly with respect to selective attention towards human movement goals. Fifteen participants completed a point-light biological motion study following a two-by-two factorial design, with one factor representing an exogenous manipulation of human movement goals (goal-directed versus random movement), and the other an endogenous manipulation (a goal identification task versus an ancillary color-change task). Both manipulations yielded increased activation in the human homologue of motion-sensitive area MT+ (hMT+) as well as the extrastriate body area (EBA). The endogenous manipulation was associated with increased right posterior superior temporal sulcus (STS) activation, whereas the exogenous manipulation was associated with increased activation in left posterior STS. Selective attention towards goals activated a portion of left hMT+/EBA only during the perception of purposeful movement-consistent with emerging theories associating this area with the matching of visual motion input to known goal-directed actions. The overall pattern of results indicates that attention towards the goals of human movement activates biological motion areas. Ultimately, selective attention may explain why some studies examining biological motion show activation in hMT+ and EBA, even when using control stimuli with comparable motion properties.

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.