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Non-speaking autistic individuals grapple with the profound impact of the 'double empathy problem' in their daily interactions with speaking others. This study rethinks the communication challenges faced by non-speaking autistic individuals, challenging traditional approaches that predominantly focus on speech and complex communication devices (AAC). By spotlighting the natural phenomenon of "interactive stimming," a powerful mode of communication among autistic individuals, this study advocates for a shift from a conventional emphasis on speech towards the foundational role of the body in autistic communication. Central to this exploration is the introduction of the Magical Musical Mat (MMM), an innovative interactive environment mapping interpersonal touch to musical sounds. Through a robust mixed-methods approach integrating video-based fieldwork and designbased research, this paper engages three non-speaking autistic children and their mothers in a 5-day empirical intervention. Results reveal significant transformations in parent-child interactions as both parents and children are acquainted with touch in a new environment. Children assert their autonomy, exploring at their own pace, and discovering sensory features of the environment. Notably, the introduction of sound prompts heightened awareness of the stims, leading to diversified and expressive stim movements. Foregrounding interpersonal touch eventually guides parents into their children's sensory activities where parents attune to the stims of their children by joining in and facilitating their expressiveness, co-creating extended, evolving patterns of repetitive cycles. The collaborative stim cycles can be likened to free improvisation, where dynamical coherence between individuals occurs through a blend of stability and active flexibility. By shifting the focus from speech to co-created sensory experiences, this paper sheds light on the value of transformative multisensory environments, envisioning a world where varied modes of communication are valued and embraced. [ABSTRACT FROM AUTHOR]

The paper reviews the entire spectrum of Artificial Intelligence (AI) in mental health and its positive role in mental health. AI has a huge number of promises to offer mental health care and this paper looks at multiple facets of the same. The paper first defines AI and its scope in the area of mental health. It then looks at various facets of AI like machine learning, supervised machine learning and unsupervised machine learning and other facets of AI. The role of AI in various psychiatric disorders like neurodegenerative disorders, intellectual disability and seizures are discussed along with the role of AI in awareness, diagnosis and intervention in mental health disorders. The role of AI in positive emotional regulation and its impact in schizophrenia, autism spectrum disorders and mood disorders is also highlighted. The article also discusses the limitations of AI based approaches and the need for AI based approaches in mental health to be culturally aware, with structured flexible algorithms and an awareness of biases that can arise in AI. The ethical issues that may arise with the use of AI in mental health are also visited. [ABSTRACT FROM AUTHOR]

This article is an editorial published in Frontiers in Psychiatry titled "Physical and medical conditions associated with autism." The editorial discusses the prevalence, causes, interventions, and long-term impacts of physical and medical conditions in autistic individuals. It highlights certain conditions such as sleep-wake disorders, epilepsy, and sensory impairments that are more common among autistic individuals. However, there are gaps in the literature regarding other conditions such as cardiovascular issues, immune dysregulation, genetic conditions, and constipation. The editorial also provides a summary of nine different papers included in the research topic, written by colleagues from various countries. These papers cover topics such as genetic and molecular mechanisms, immune dysregulation and inflammation, epidemiological and health profiles, treatment and strategies, and barriers to effective communication. The article emphasizes the importance of comprehensive medical assessments and individualized interventions for autistic individuals. [Extracted from the article]

Individuals with autism (ASD) often face difficulty in executing graphic tasks. This can be related to how one uses a graphic tool (e.g., pen) and plans ahead the graphic execution. Use of graphic tool can be captured using attributes, e.g., pen-tip pressure, number of pen lifts, etc. One's ability to plan a graphic execution can be quantified using the total duration of pen lifts (i.e., air time). Though pen-and-paper-based Trail Making Test-Part A (TMT-A) can estimate planning of graphic execution, yet it cannot capture other attributes, e.g., pentip pressure, pen lift, etc. This can be possible if TMT-A is administered on a pressure-sensitive tablet as seen from existing studies with typically developing (TD) individuals. However, quantification of such attributes using TMT-A administered on a pressure-sensitive tablet remains unexplored for individuals with ASD. In addition, such objective measures can help to understand variations in the use of graphic tool and ability to plan graphic execution even outside the TMT-A task, e.g., while drawing shapes which is important to the development of children's graphic skills. Here, we conducted a study with 12 pairs of TD children and those with ASD who executed TMT-A (in Phase-I) and shape drawing (in Phase-II) on a pressure-sensitive tablet. Results of our study show differences in the use of graphic tool and planning ahead the graphic execution between two participant groups in both the Phases. Such insights can offer clinical inputs that can be helpful in designing individualized intervention paradigms for children facing difficulties in graphic execution. [ABSTRACT FROM AUTHOR]

Early detection and diagnosis of Autism Spectrum Disorder (ASD) can significantly improve the quality of life for affected individuals. Identifying ASD based on brain functional connectivity (FC) poses a challenge due to the high heterogeneity of subjects’ fMRI data in different sites. Meanwhile, deep learning algorithms show efficacy in ASD identification but lack interpretability. In this paper, a novel approach for ASD recognition is proposed based on graph attention networks. Specifically, we treat the region of interest (ROI) of the subjects as node, conduct wavelet decomposition of the BOLD signal in each ROI, extract wavelet features, and utilize them along with the mean and variance of the BOLD signal as node features, and the optimized FC matrix as the adjacency matrix, respectively. We then employ the self-attention mechanism to capture long-range dependencies among features. To enhance interpretability, the node-selection pooling layers are designed to determine the importance of ROI for prediction. The proposed framework are applied to fMRI data of children (younger than 12  years old) from the Autism Brain Imaging Data Exchange datasets. Promising results demonstrate superior performance compared to recent similar studies. The obtained ROI detection results exhibit high correspondence with previous studies and offer good interpretability. [ABSTRACT FROM AUTHOR]

Background: Education should be inclusive, nurturing each individual's potential, talents, and creativity. However, criticisms have emerged regarding support for autistic learners, particularly in addressing disproportionately high absence levels within this group. The demand for accessible, person-centered, neuro-affirming approaches is evident. This paper provides a program description of a structured absence support framework, developed and implemented during and following the Covid-19 pandemic. We detail creation, content, and implementation. Methods: We collaborated with stakeholders, reviewed literature and drew on existing theoretical frameworks to understand absence in autistic learners, and produced draft guidance detailing practical approaches and strategies for supporting their return to school. The final resource was disseminated nationally and made freely available online with a supporting program of work around inclusive practices. Results: The resource is rooted in neuro-affirming perspectives, rejecting rewardbased systems and deficit models of autism. It includes key messages, case studies and a planning framework. It aims to cultivate inclusive practices with an autisminformed lens. The principles promoted include recognizing the child's 24-hour presentation, parental partnership, prioritizing environmental modifications, and providing predictable, desirable and meaningful experiences at school. Feedback to date has been positive in terms of feasibility, face validity, and utility. Conclusion: This novel, freely available resource provides a concise, practical framework for addressing absence in autistic learners by cultivating a more inclusive, equitable, and supportive educational system in which autistic individuals can thrive. [ABSTRACT FROM AUTHOR]

The neurodiversity movement has introduced a new era for autism research. Yet, the neurodiversity paradigm and the autism clinic remain largely unconnected. With the present work, we aim to contribute to filling this lacuna by putting forward phenomenology as a foundation for developing neurodiversity-affirming clinical interventions for autism. In the first part of this paper, we highlight that autistic people face a severe mental health crisis. We argue that approaches focused on reducing autistic 'symptoms' are unlikely to solve the problem, as autistic mental health is positively correlated with autism acceptance and perceived quality of support provided, not necessarily with lack of 'symptomatologic severity'. Therefore, the development and dissemination of neurodiversity-affirming clinical interventions is key for addressing the autism mental health crisis. However, therapists and researchers exploring such neurodiversity-affirming practices are faced with two significant challenges. First, they lack concrete methodological principles regarding the incorporation of neurodiversity into clinical work. Second, they need to find ways to acknowledge rightful calls to respect the 'autistic self' within the clinic, while also challenging certain beliefs and behaviors of autistic clients in a manner that is sine qua non for therapy, irrespective of neurotype. In the second part of the paper, we introduce phenomenological psychology as a potential resource for engaging with these challenges in neurodiversity-affirming approaches to psychotherapy. In this vein, we put forward specific directions for adapting cognitive behavioral and interpersonal psychotherapy for autism. [ABSTRACT FROM AUTHOR]

Differences between autistic and nonautistic people are often framed as deficits. This research considers whether some of these differences might actually be strengths. In particular, autistic people tend to be less sensitive to their social environment than nonautistic people who are easily influenced by the judgments, opinions, beliefs and actions of others. Because autistic people are less susceptible to social influence, as employees they are more likely to take action when they witness an operational inefficiency or an ethical problem in the organization. By reporting problems, autistic employees may contribute to the introduction of innovations and improvements in organizational processes and effectiveness that result in superior performance. This paper considers whether and the extent to which these differences between autistic and nonautistic employees are moderated by “moral disengagement,” a set of interrelated cognitive mechanisms that allow people to make unethical decisions by deactivating moral self-regulatory processes. While previous research has shown that moral disengagement is related to unethical decisions, there is no research on whether and the extent to which autistic people are vulnerable to moral disengagement. Thirty-three autistic employees and 34 nonautistic employees completed an on-line survey to determine whether differences between autistic and nonautistic employees with regards to (1) likelihood they would voice concerns about organizational dysfunctions, and (2) degree to which they were influenced by the presence of others when deciding to intervene, are moderated by individual differences in moral disengagement. As predicted, autistic participants scored lower on moral disengagement than nonautistic participants. In terms of the moderating effects of moral disengagement, the results are mixed. Although moral disengagement reduced intervention likelihood, there was not a difference between autistic and nonautistic employees in the degree to which intervention likelihood was changed by an individual’s level of moral disengagement. However, there was a difference between autistic and nonautistic employees in the extent to which acknowledging the influence of others was affected by moral disengagement. These findings suggest that autistic adults are not just more likely to intervene when they witness dysfunction or misconduct in an organizational context; they are also less likely to engage in unethical behavior in general due to lower levels of moral disengagement. The reduced susceptibility to the bystander effect evidenced by autistic adults in the workplace may be accounted for, in part, by their lower levels of moral disengagement compared with nonautistic adults. [ABSTRACT FROM AUTHOR]

Introduction: Autism is a global health priority with an urgent need for evidence-based, resource-efficient, scalable supports that are feasible for implementation in low- and middle-income countries (LMICs). Initiating supports in the toddler years has potential to significantly impact child and family outcomes. The current paper describes the feasibility and outcomes associated with a Canadian-developed caregiver-mediated intervention for toddlers (the Social ABCs), delivered through a clinical service in Goa, India. Methods: Clinical staff at the Sethu Centre for Child Development and Family Guidance in Goa, India, were trained by the Canadian program development team and delivered the program to families seen through their clinic. Using a retrospective chart review, we gathered information about participating families and used a pre-post design to examine change over time. Results: Sixty-four families were enrolled (toddler mean age = 28.5 months; range: 19-35), of whom 55 (85.94%) completed the program. Video-coded data revealed that parents learned the strategies (implementation fidelity increased from M= 45.42% to 76.77%, p < .001, with over 90% of caregivers attaining at least 70% fidelity). Toddler responsivity to their caregivers (M = 7.00% vs. 46.58%) and initiations per minute (M= 1.16 vs. 3.49) increased significantly, p's < .001. Parents also reported significant improvements in child behaviour/skills (p < .001), and a non-significant trend toward reduced parenting stress (p = .056). Discussion: Findings corroborate the emerging evidence supporting the use of caregiver-mediated models in LMICs, adding evidence that such supports can be provided in the very early years (i.e., under three years of age) when learning may be optimized. [ABSTRACT FROM AUTHOR]

Keywords: autism; schizophenia; psychosis; social cognition; neurocognition; neurobiology EN autism schizophenia psychosis social cognition neurocognition neurobiology N.PAG N.PAG 3 02/12/21 20210210 NES 210210 Although Autism Spectrum Conditions (ASC) and Schizophrenia Spectrum Conditions (SSC) are recognized as distinct diagnostic categories with independent features, they share a history of clinical entanglement stemming from overlapping symptomatology, particularly in the area of social behavior ([1]). Meanwhile, the papers by Maat et al. and Abu-Akel et al. demonstrate that the presence of cross-diagnostic symptoms along the autism-psychosis spectrum may produce novel cognitive effects in autistic people not seen in autism alone. The cognitive differences characterizing the autism-psychosis spectrum are supported by an underlying neurobiology that five papers in this collection seek to better understand. [Extracted from the article]

Empathy, broadly defined as the ability to understand the other and to share others' emotions, motivates prosocial behavior and underlies successful interpersonal relations. Dysfunctions in this ability may cause fundamental difficulties in social communication. Empathy has been measured in various ways, from self-report questionnaires to laboratory objective performance tests. Empathic accuracy (EA), i.e., the ability to accurately empathize, is measured using more complex and ecological paradigms, such as asking participants to infer filmed interactions, or having people narrate personal emotional stories then assessing the correspondence between the perceiver and the target of empathy as the criteria for empathic ability. This measure is particularly useful in the study of clinical populations, where deconstructing the multifaceted concept of empathy may contribute to a more complete understanding of specific clinical profiles. This paper presents a scoping review of the literature on EA in clinical populations, and on EA and clinical traits and states in nonclinical or high-risk populations. Following an exhaustive literature search, 34 studies were found eligible to be included in this review. The largest category was studies focused on EA in people with schizophrenia (31%; 11 papers), followed by studies focused on EA in autism spectrum disorders (ASD) and autistic traits in a nonclinical population (22%; 8 papers). Studies were also found on EA and depression tendencies, psychopathy, social anxiety, behavior disorders, and personality disorders, and a few other clinical conditions. The included studies varied on research aims, designs, sample sizes, and male:female ratios. The overall synthesized results suggest that EA is reduced in schizophrenia and ASD. In other clinical populations, the number of studies was very limited. We urge researchers to further examine EA in these less-studied populations. The review reveals a general underrepresentation of female participants in studies on EA in clinical populations. We suggest that future research address understudied clinical populations, such as those diagnosed with psychopathy. Subject, target, and situational variables should also be considered, with special attention to gender differences (and similarities), the association between EA abilities and adaptive functioning, and the study of individuals with clinical conditions as targets, not just observers, in EA tasks. [ABSTRACT FROM AUTHOR]

This article presents a novel theoretical perspective on the role of cognitive biases within the autism and schizophrenia spectrum by integrating the evolutionary and computational approaches. Against the background of neurodiversity, cognitive biases are presented as primary adaptive strategies, while the compensation of their shortcomings is a potential cognitive advantage. The article delineates how certain subtypes of autism represent a unique cognitive strategy to manage cognitive biases at the expense of rapid and frugal heuristics. In contrast, certain subtypes of schizophrenia emerge as distinctive cognitive strategies devised to navigate social interactions, albeit with a propensity for overdetecting intentional behaviors. In conclusion, the paper emphasizes that while extreme manifestations might appear non-functional, they are merely endpoints of a broader, primarily functional spectrum of cognitive strategies. The central argument hinges on the premise that cognitive biases in both autism and schizophrenia spectrums serve as compensatory mechanisms tailored for specific ecological niches. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is diagnosed based on socio-communicative difficulties, which are believed to result from deficits in mentalizing, mainly evidenced by alterations in recognizing and responding to the mental states of others. In recent years, efforts have been made to develop mentalization-based treatment (MBT) models for this population. These models focus on enhancing individuals’ ability to understand and reflect on their own mental states, as well as those of others. However, MBT approaches for people with ASD are limited by their existing theoretical background, which lacks a strong foundation grounded in neuroscience-based evidence properly integrated with attachment, and mentalizing. These are crucial aspects for understanding psychological processes in autism, and as such, they play a pivotal role in shaping the development of tailored and effective therapeutic strategies for this specific population. In this paper we review evidence related to the neurobiological, interpersonal, and psychological dimensions of autism and their implications for mentalizing processes. We also review previous mentalization-based frameworks on the psychosis continuum to provide a comprehensive understanding of attachment, neurobiology, and mentalization domains in therapeutic approaches for autism. After presenting a synthesis of the literature, we offer a set of clinical strategies for the work with children with autism. Finally, we provide recommendations to advance the field towards more robust models that can serve as a basis for evidence-based therapeutic strategies. [ABSTRACT FROM AUTHOR]

Introduction: Autistic students have limited access to inclusive classes and activities in their schools. Principals and special education teachers who directly teach and administer programs for autistic elementary students can offer critical insight into factors, such as educators' attitudes, that may impact inclusive opportunities in schools. These attitudes may serve as barriers to or facilitators of promoting an inclusive school setting. Methods: Semi-structured interviews with 26 elementary school principals and 26 special education teachers explored their experiences implementing evidence-based practices for autistic students (pivotal response training, discrete trial training, and visual schedules) in 26 self-contained classrooms in the United States. Autism-specific culture and inclusion emerged as a theme, which was analyzed for this paper. Results: An inductive approach to thematic analysis revealed principals' and special education teachers' perspectives regarding the "autism-specific culture" in the school, including attitudes towards and inclusion of autistic students in self-contained classrooms in the broader school environment. Analysis of text related to "autism-specific culture" detailed aspects of inclusion, factors (i.e., barriers and facilitators) affecting inclusion, principals' and special education teachers' attitudes towards autistic students placed in self-contained classrooms, attitudes of other school staff towards teachers in self-contained classrooms, and recommendations to support an inclusive school environment for autistic students. Discussion: Results suggest that valuing "equal" access to classes and activities for autistic students in self-contained classrooms may not be sufficient for promoting an inclusive school environment, Educators may benefit from targeted strategies to facilitate inclusion. Strategies range from supporting educators' attitudes and knowledge of autism to shifting physical aspects of the school environment (e.g., location of classrooms). Additional implications for supporting the true inclusion (i.e., inclusion that goes beyond physical inclusion) involves of autistic students in self-contained classrooms schools are discussed. [ABSTRACT FROM AUTHOR]

Many researchers now believe that autism heterogeneity is likely to include many disorders, but most research is based on samples defined by the DSM-5 Autism Spectrum Disorder (ASD) criteria. However, individuals diagnosed with autism have complex and varied biological causes for their symptoms. Therefore, autism is not a unitary biological entity. And although autism is significantly different from typical development, autism is not a unitary clinical disorder because diagnosed individuals vary in symptom patterns, comorbidities, biomarkers, and gene variants. The DSM-5 ASD criteria were designed to reduce heterogeneity, and there have been many other efforts to reduce autism heterogeneity including using more stringent clinical criteria, dividing autism into low and high functioning groups, creating subgroups, and by studying larger samples. However, to date these efforts have not been successful. Heterogeneity is extensive and remains unexplained, and no autismpathophysiology has been discovered. Most importantly, heterogeneity has hindered the explanatory power of the autism diagnosis to discover drug regimens and effective behavioral treatments. The paper proposes that possible transdiagnostic endophenotypes may reduce autism heterogeneity. Searching for transdiagnostic endophenotypes requires exploring autism symptoms outside of the framework of the DSM-5 autism diagnosis. This paper proposes that researchers relax diagnostic criteria to increase the range of phenotypes to support the search for transdiagnostic endophenotypes. The paper proposes possible candidates for transdiagnostic endophenotypes. These candidates are taken from DSM-5 ASD criteria, from concepts that have resulted from researched theories, and from symptoms that are the result of subtyping. The paper then sketches a possible basis for a future transdiagnostic endophenotypes screening tool that includes symptoms of autism and other neurodevelopmental disorders. [ABSTRACT FROM AUTHOR]

As a neurodevelopmental disorder, autism spectrum disorder (ASD) severely affects the living conditions of patients and their families. Early diagnosis of ASD can enable the disease to be effectively intervened in the early stage of development. In this paper, we present an ASD classification network defined as CNNG by combining of convolutional neural network (CNN) and gate recurrent unit (GRU). First, CNNG extracts the 3D spatial features of functional magnetic resonance imaging (fMRI) data by using the convolutional layer of the 3D CNN. Second, CNNG extracts the temporal features by using the GRU and finally classifies them by using the Sigmoid function. The performance of CNNG was validated on the international public data--autism brain imaging data exchange (ABIDE) dataset. According to the experiments, CNNG can be highly effective in extracting the spatio-temporal features of fMRI and achieving a classification accuracy of 72.46%. [ABSTRACT FROM AUTHOR]

Many techniques have attempted to provide physical support to ease the execution of a typing task by individuals with developmental disabilities (DD). These techniques have been controversial due to concerns that the support provider's touch can influence the typed content. The most common interpretation of assisted typing as an ideomotor phenomenon has been qualified recently by studies showing that users with DD make identifiable contributions to the process. This paper suggests a neurophysiological pathway by which touch could lower the cognitive load of seated typing by people with DD. The required sensorimotor processes (stabilizing posture and planning and executing manual reaching movements) and cognitive operations (generating and transcribing linguistic material) place concurrent demands on cognitive resources, particularly executive function (EF). A range of developmental disabilities are characterized by deficits in sensorimotor and EF capacity. As light touch has been shown to facilitate postural coordination, it is proposed that a facilitator's touch could assist the seated typist with sensorimotor and EF deficits by reducing their sensorimotor workload and thereby freeing up shared cognitive resources for the linguistic elements of the task. This is the first theoretical framework for understanding how a facilitator's touch may assist individuals with DD to contribute linguistic content during touch-assisted typing. [ABSTRACT FROM AUTHOR]

The dominant discourse surrounding neurodevelopmental conditions such as autism and ADHD emphasizes biological explanations. Neurodevelopmental conditions are conceived as different types of brains, the result of different types of genes. This way of thinking is present both in medical research and in clinical practice. Indeed, it is widely acknowledged that the idea of having a biological diagnosis helps people see beyond blame and guilt. It aids acceptance. However, simplistic approaches to biology risks neglecting the experiences and stories of autistic people in favor of finding etiological causes. At the same time, there is growing awareness that risks, functioning, and resilience are not solely defined by genes and brains but have a cultural and experiential component as well. Furthermore, atypical cognitive trajectories are not straightforwardly associated with poor outcomes. In this paper we describe the concept of developmental diversity as an alternative to more categorical approaches to neurodevelopmental conditions. We explore how dynamic models of life offer possibilities to look at neurodevelopmental conditions differently: rather than seeing autistic people as people with fundamental flaws in their genes or software faults in their brains that have to be explained, autism appears as a phenomenon that exists in interaction with the context, as a meaningful reaction to the environment. We explore what it would mean for research to go from a diagnosis-based approach to a developmental diversity approach that will define wellbeing and functioning in a more granular way across developmental trajectories. We argue that this wouldmean incorporating lived experiences into biological research and going beyond genes-environment dichotomies. Next to yielding a more complete picture on the phenomenon of autism, we describe how an approach that takes developmental diversity as a starting point offers a new way to look at existing challenges of autism research, such as how to deal with the significant overlap between diagnosis. Our hypothesis is that thinking with developmental diversity rather than categorical difference both represents an opportunity for a more inclusive society, and fundamentally can alter the way we perform research. As such, it is in line with requests of neurodiversity and disability movements. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a deep learning model to classify children as either healthy or potentially having autism with 94.6% accuracy using Deep Learning. Patients with autism struggle with social skills, repetitive behaviors, and communication, both verbal and non-verbal. Although the disease is considered to be genetic, the highest rates of accurate diagnosis occur when the child is tested on behavioral characteristics and facial features. Patients have a common pattern of distinct facial deformities, allowing researchers to analyze only an image of the child to determine if the child has the disease. While there are other techniques and models used for facial analysis and autism classification on their own, our proposal bridges these two ideas allowing classification in a cheaper, more efficient method. Our deep learning model uses MobileNet and two dense layers to perform feature extraction and image classification. The model is trained and tested using 3,014 images, evenly split between children with autism and children without it; 90% of the data is used for training and 10% is used for testing. Based on our accuracy, we propose that the diagnosis of autism can be done effectively using only a picture. Additionally, there may be other diseases that are similarly diagnosable. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between time and motion perception in virtual environments. Previous work has shown that the perception of motion can affect the perception of time. We developed a virtual environment that simulates motion in a tunnel and measured its effects on the estimation of the duration of time, the speed at which perceived time passes, and the illusion of self-motion, also known as vection. When large areas of the visual field move in the same direction, vection can occur; observers often perceive this as self-motion rather than motion of the environment. To generate different levels of vection and investigate its effects on time perception, we developed an abstract procedural tunnel generator. The generator can simulate different speeds and densities of tunnel sections (visibly distinguishable sections that form the virtual tunnel), as well as the degree of embodiment of the user avatar (with or without virtual hands). We exposed participants to various tunnel simulations with different durations, speeds, and densities in a remote desktop and a virtual reality (VR) laboratory study. Time passed subjectively faster under high-speed and high-density conditions in both studies. The experience of self-motion was also stronger under high-speed and high-density conditions. Both studies revealed a significant correlation between the perceived passage of time and perceived self-motion. Subjects in the virtual reality study reported a stronger self-motion experience, a faster perceived passage of time, and shorter time estimates than subjects in the desktop study. Our results suggest that a virtual tunnel simulation can manipulate time perception in virtual reality. We will explore these results for the development of virtual reality applications for therapeutic approaches in our future work. This could be particularly useful in treating disorders like depression, autism, and schizophrenia, which are known to be associated with distortions in time perception. For example, the tunnel could be therapeutically applied by resetting patients’ time perceptions by exposing them to the tunnel under different conditions, such as increasing or decreasing perceived time. [ABSTRACT FROM AUTHOR]

Aims: Autism is a multifaceted developmental disorder of the nervous system, that necessitates novel therapeutic approaches beyond traditional medications and psychosomatic therapy, such as appropriate sensory integration training. This systematic mapping review aims to synthesize existing knowledge on enriching environmental interventions as an alternative avenue for improving autism, guiding future research and practice. Method: A comprehensive search using the terms ASD and Enriched Environment was conducted across PubMed, EMBASE, ISI, Cochrane, and OVID databases. Most of the literature included in this review was derived from animal model experiments, with a particular focus on assessing the effect of EE on autism-like behavior, along with related pathways and molecular mechanisms. Following extensive group discussion and screening, a total of 19 studies were included for analysis. Results: Enriched environmental interventions exhibited the potential to induce both behavioral and biochemical changes, ameliorating autism-like behaviors in animal models. These improvements were attributed to the targeting of BDNFrelated pathways, enhanced neurogenesis, and the regulation of glial inflammation. Conclusion: This paper underscores the positive impact of enriched environmental interventions on autism through a review of existing literature. The findings contribute to a deeper understanding of the underlying brain mechanisms associated with this intervention. [ABSTRACT FROM AUTHOR]

Introduction: Social differences characteristic of autism spectrum disorder (ASD) and other developmental disabilities are evident in early childhood and are associated with later difficulties. Unfortunately, there is a paucity of evidence-based interventions explicitly targeting social skills development for young children, few actively integrate parents and caregivers, and even fewer have remote models. The importance of providing accessible, tailored services for families in the wake of the COVID-19 pandemic, prompted the creation of a parent-mediated telehealth version of Program for the Education and Enrichment of Relational Skills (PEERS®) for Preschoolers (P4P), a pre-existing, evidence-based social skills intervention for children 4-6 years focused on making and keeping friends. Method: This methodological paper documents the implementation, feasibility, and satisfaction of a novel telehealth group-based delivery of P4P. Results: Qualitative results indicate acceptable feasibility and satisfaction. Additionally, following completion there was an increase in parental confidence in social coaching and increased use of child social skills. Discussion: Future work will evaluate quantitative outcomes and comparisons between delivery methods (e.g., telehealth vs. in-person). [ABSTRACT FROM AUTHOR]

Non-speaking autistic individuals grapple with the profound impact of the ‘double empathy problem’ in their daily interactions with speaking others. This study rethinks the communication challenges faced by non-speaking autistic individuals, challenging traditional approaches that predominantly focus on speech and complex communication devices (AAC). By spotlighting the natural phenomenon of “interactive stimming,” a powerful mode of communication among autistic individuals, this study advocates for a shift from a conventional emphasis on speech towards the foundational role of the body in autistic communication. Central to this exploration is the introduction of the Magical Musical Mat (MMM), an innovative interactive environment mapping interpersonal touch to musical sounds. Through a robust mixed-methods approach integrating video-based fieldwork and design-based research, this paper engages three non-speaking autistic children and their mothers in a 5-day empirical intervention. Results reveal significant transformations in parent–child interactions as both parents and children are acquainted with touch in a new environment. Children assert their autonomy, exploring at their own pace, and discovering sensory features of the environment. Notably, the introduction of sound prompts heightened awareness of the stims, leading to diversified and expressive stim movements. Foregrounding interpersonal touch eventually guides parents into their children’s sensory activities where parents attune to the stims of their children by joining in and facilitating their expressiveness, co-creating extended, evolving patterns of repetitive cycles. The collaborative stim cycles can be likened to free improvisation, where dynamical coherence between individuals occurs through a blend of stability and active flexibility. By shifting the focus from speech to co-created sensory experiences, this paper sheds light on the value of transformative multisensory environments, envisioning a world where varied modes of communication are valued and embraced.

Schizophrenia Spectrum Disorders (SSD) and Autism Spectrum Disorders (ASD) are considered separate entities, but the two spectra share important similarities, and the study of these areas of overlap represents a field of growing scientific interest. The PANSS Autism Score (PAUSS) was recently developed specifically to assess autistic symptoms in people living with SSD reliably and quickly. The aims of the present systematic review were to provide a comprehensive assessment of the use of the PAUSS scale in available literature and to systematically analyze cognitive, functional and neurobiological correlates of autistic symptoms measured with this instrument in SSD. The systematic literature search included three electronic databases (PubMed, Scopus and PsycINFO) as well as a manual search in Google Scholar and in reference lists of included papers. Screening and extraction were conducted by at least two independent reviewers. Out of 213 identified records, 22 articles referring to 15 original studies were included in the systematic review. Studies were conducted in several different countries by independent groups, showing consistent scientific interest in the use of the scale; most works focused on cognitive and functional correlates of ASD symptoms, but some also considered neurobiological features. Results of included studies showed that autistic symptoms in people with SSD are consistently associated with worse cognitive performance, especially in the social cognition domain, and with worse psychosocial functioning. However, the presence of autistic symptoms appears to also have a protective role, particularly on functioning, in subjects with more severe psychotic symptoms. Further exploring the impact of autistic symptoms could be of significant scientific and clinical interest, allowing the development of tailored interventions to improve treatment for people living with SSDs. [ABSTRACT FROM AUTHOR]

Background: As countries like India improve access to maternal and infant care, the health systems need to develop services that enable all children to thrive. A key demographic which needs to be supported are children with disabilities, such as autism. With an estimated prevalence of one percent, there are over five million young children who need services to support their needs. However, the paucity of specialist care makes access to interventions diffcult. In this context a public health research not-for-profit is evaluating the effectiveness of the task-sharing approach to support the delivery of an evidenced social communication intervention for young children with autism. This paper describes the process of engaging and training the non-specialist frontline Accredited Social Health Activists (ASHAs), who are embedded within the Ministry of Health and Family Welfare under the Delhi State Health Mission, to deliver a complex intervention for autism to inform the future scalability of services for neurodevelopmental disorders. Methods: The present study describes the process which included (i) engagement meetings, (ii) recruitment, (iii) training, (iv) internship, and (v) competency evaluation. The shortlisted ASHAs received a 7-day classroom training followed by an internship period with practice cases. Finally, competency assessments, comprising of a test of knowledge and skills through role-plays, was administered. Results: Twenty three Primary Urban Health Centers across seven districts of Delhi were approached and 408 ASHAs were engaged in initial meetings. Telephonic screening with 127 ASHAs resulted in 72 ASHAs being selected for in-person interviews. Of the 45 ASHAs who attended, 33 were shortlisted for training and 18 completed it. Fifteen ASHAs entered the internship of which 7 ASHAs achieved competency. Discussion and conclusion: There was significant attrition along the pathway to having a competent non-specialist worker deliver a complex autism intervention. The lessons learnt from this process can inform the possibility of developing a cadre of disability specific frontline health workers who can deliver evidence-based interventions for neurodevelopmental disorders under supervision. [ABSTRACT FROM AUTHOR]

There is overwhelming evidence that autism spectrum disorder (ASD) is related to altered brain connectivity. While these alterations are starting to be well characterized in subjects where the clinical picture is fully expressed, less is known on their earlier developmental course. In the present study we systematically reviewed current knowledge on structural connectivity in ASD infants and toddlers. We searched PubMed and Medline databases for all English language papers, published from year 2000, exploring structural connectivity in populations of infants and toddlers whose mean age was below 30 months. Of the 264 papers extracted, four were found to be eligible and were reviewed. Three of the four selected studies reported higher fractional anisotropy values in subjects with ASD compared to controls within commissural fibers, projections fibers, and association fibers, suggesting brain hyper-connectivity in the earliest phases of the disorder. Similar conclusions emerged from the other diffusion parameters assessed. These findings are reversed to what is generally found in studies exploring older patient groups and suggest a developmental course characterized by a shift toward hypo-connectivity starting at a time between two and four years of age. [ABSTRACT FROM AUTHOR]

This paper describes an eating disorder service development pilot project helping clinicians implement evidence-based research for patients with anorexia nervosa and autism spectrum condition comorbidity. Currently, there are no clear guidelines or recommendations for people who have the developmental condition of autism spectrum condition and a comorbid eating disorder. The Maudsley eating disorder team is pioneering a tailored approach of adaptations for this autism and eating disorder comorbidity to improve and adapt evidenced-based treatments and improve the experience for patients, families, and clinicians involved in their care. This paper aims to support the clinical and research community to implement some of the learning and new strategies developed through the PEACE pathway. The authors aim is to collaborate with teams nationally and internationally to scale up the project to benefit patients with this comorbidity. [ABSTRACT FROM AUTHOR]

Services for the assessment and diagnosis of autism in adults have been widely criticized and there is an identified need for further research in this field. There is a call for diagnostic services to become more accessible, person-centered, neurodiversity affirming, and respectful. There is a need for workforce development which will increase capacity for diagnostic assessment and support for adults. ADOS-2 is a gold-standard diagnostic assessment tool for autism recommended in clinical guidelines. However, diagnostic procedures such as the ADOS-2 are rooted in the medical model and do not always sit comfortably alongside the neurodiversity paradigm or preferences of the autistic community. Training and educational materials need to account for the differences between these approaches and support clinicians to provide services which meet the needs of the adults they serve. The National Autism Implementation Team worked alongside ADOS-2 training providers to support clinicians in Scotland, to provide effective and respectful diagnostic assessment. The team engaged with clinicians who had attended ADOS training to identify areas of uncertainty or concern. Training materials were developed to support ADOS assessors to incorporate key principles including "nothing about us without us"; "difference not deficit"; "environment first"; "diagnosis matters," "language and mindsets matter"; and "a neurodevelopmental lens," to support the provision of neurodiversity affirming assessment practice. The National Autism Implementation Team also provided examples of actions which can be undertaken by clinicians to improve the assessment experience for those seeking a diagnosis. Training materials are based on research evidence, clinical experience, and the needs and wishes of autistic people. [ABSTRACT FROM AUTHOR]

The origin of moral agency is a much-debated issue. While rationalists or Kantians have argued that moral agency is rooted in reason, sentimentalists or Humeans have ascribed its origin to empathic feelings. This debate between rationalists and sentimentalists still stands with respect to persons with mental disorders, such as individuals diagnosed with mild forms of Autism Spectrum Disorder (ASD), without intellectual impairment. Individuals with ASD are typically regarded as moral agents, however their ability for empathy remains debated. The goal of this paper is to investigate the mechanisms of moral actions in people with ASD, by finding arguments for the origin of their moral actions, supporting either the sentimentalist or the rationalist view of the dispute. We propose to revisit the debate using Interpretative Phenomenological Analysis to study the autobiographies of individuals with High-Functioning Autism (HFA) and Asperger Syndrome (AS). While conducting the systematic analysis of 10 autobiographies, we re-examined both the rationalist and the sentimentalist positions, considering the links between empathic feelings and moral agency. The investigation of the temporal dimensions of emotional experiences, an aspect overlooked by previous research, indicated that individuals with ASD empathize with others, but in different ways as compared to neurotypicals. A relationship between emotional experience and the type of moral agency exhibited by individuals with forms of ASD was established. As a consequence, our analyses support the sentimentalist stance on moral action. [ABSTRACT FROM AUTHOR]

Pain sensation in autism spectrum disorder (ASD) has been a growing research field in the last two decades. Existing pain research has focused on pain sensitivity, suggesting either hyposensitivity or hypersensitivity to pain in individuals with ASD. However, research about other aspects of pain experience is scarce. Moreover, most pain-related research in ASD focused on quantitative measures, such as neuroimaging or parental reports. Instead, this paper aimed to illuminate the various aspects of pain experience as perceived by adults with ASD. Its descriptive qualitative research design incorporated semi-structured interviews and deductive thematic analysis. This phenomenological approach captured the subjective pain experience through the lens of people with ASD. Four primary themes emerged from the data: (a) physical pain experience, including the sequence of pain sensitivity, pain awareness, pain-related emotional aspects, and pain communication; (b) direct and indirect coping strategies; (c) function and participation outcomes; and (d) suggestions for Healthcare Providers. The findings echo the crucial role of pain awareness and communication in the pain experience of people with ASD. These two factors have been reported as profoundly influencing coping strategies, function, and participation. The results emphasize the need to expand the exploration of pain in this population, calling for greater understanding, and listening to this population's unique pain profiles and experiences to promote better-suited evaluation, diagnosis, and intervention in pain conditions. [ABSTRACT FROM AUTHOR]

Social dysfunction is a key characteristic of autism. Determining and treating autism-related social deficits have been challenging. The medical model views interpersonal difficulties in autism as a localized set of deficits to be managed, whereas the neurodiversity movement calls for the accommodation of differences by the larger community. One common assumption underlying these perspectives is a misalignment in social behaviors between autistic individuals and neurotypicals. This paper reviews and interrogates current perspectives on social functioning in autism to uncover the intricacies of such a notion. Even though extant literature has alluded to a misalignment in social behaviors between autistic and neurotypical individuals, it is uncertain where this disparity lies. Implications for future research and practice are discussed. [ABSTRACT FROM AUTHOR]

Self-other distinction refers to the ability to distinguish between our own and other people's physical and mental states (actions, perceptions, emotions etc.). Both the right temporo-parietal junction and brain areas associated with the human mirror neuron system are likely to critically influence self-other distinction, given their respective contributions to theory of mind and embodied empathy. The degree of appropriate self-other distinction will vary according to the exact social situation, and how helpful it is to feel into, or remain detached from, another person's mental state. Indeed, the emotional resonance that we can share with others affords the gift of empathy, but over-sharing may pose a downside, leading to a range of difficulties from personal distress to paranoia, and perhaps even motor tics and compulsions. The aim of this perspective paper is to consider how evidence from behavioral and neurophysiological studies supports a role for problems with self-other distinction in a range of psychiatric symptoms spanning the emotional, cognitive and motor domains. The various signs and symptoms associated with problematic self-other distinction comprise both maladaptive and adaptive (compensatory) responses to dysfunction within a common underlying neuropsychological mechanism, compelling the adoption of more holistic transdiagnostic therapeutic approaches within Psychiatry. [ABSTRACT FROM AUTHOR]

Recent advances in longitudinal methodologies for observational studies have contributed to a better understanding of Autism as a neurodevelopmental condition characterized by within-person and between-person variability over time across behavioral domains. However, this finer-grained approach to the study of developmental variability has yet to be applied to Autism intervention science. The widely adopted experimental designs in the field—randomized control trials and quasi-experimental designs—hold value for inferring treatment effects; at the same time, they are limited in elucidating what works for whom, why , and when , given the idiosyncrasies of neurodevelopmental disorders where predictors and outcomes are often dynamic in nature. This perspective paper aims to serve as a primer for Autism intervention scientists to rethink the way we approach predictors of treatment response and treatment-related change using a dynamic lens. We discuss several empirical gaps, and potential methodological challenges and opportunities pertaining to: (1) capturing finer-grained treatment effects in specific behavioral domains as indexed by micro-level within-person changes during and beyond intervention; and (2) examining and modeling dynamic prediction of treatment response. Addressing these issues can contribute to enhanced study designs and methodologies that generate evidence to inform the development of more personalized interventions and stepped care approaches for individuals on the heterogeneous spectrum of Autism with changing needs across development. [ABSTRACT FROM AUTHOR]

Synaptic gene conditions, i.e., "synaptopathies," involve disruption to genes expressed at the synapse and account for between 0.5 and 2% of autism cases. They provide a unique entry point to understanding the molecular and biological mechanisms underpinning autism-related phenotypes. Phelan-McDermid Syndrome (PMS, also known as 22q13 deletion syndrome) and NRXN1 deletions (NRXN1ds) are two synaptopathies associated with autism and related neurodevelopmental disorders (NDDs). PMS often incorporates disruption to the SHANK3 gene, implicated in excitatory postsynaptic scaffolding, whereas the NRXN1 gene encodes neurexin-1, a presynaptic cell adhesion protein; both are implicated in trans -synaptic signaling in the brain. Around 70% of individuals with PMS and 43–70% of those with NRXN1ds receive a diagnosis of autism, suggesting that alterations in synaptic development may play a crucial role in explaining the aetiology of autism. However, a substantial amount of heterogeneity exists between conditions. Most individuals with PMS have moderate to profound intellectual disability (ID), while those with NRXN1ds have no ID to severe ID. Speech abnormalities are common to both, although appear more severe in PMS. Very little is currently known about the neurocognitive underpinnings of phenotypic presentations in PMS and NRXN1ds. The Synaptic Gene (SynaG) study adopts a gene-first approach and comprehensively assesses these two syndromic forms of autism. The study compliments preclinical efforts within AIMS-2-TRIALS focused on SHANK3 and NRXN1. The aims of the study are to (1) establish the frequency of autism diagnosis and features in individuals with PMS and NRXN1ds, (2) to compare the clinical profile of PMS, NRXN1ds, and individuals with 'idiopathic' autism (iASD), (3) to identify mechanistic biomarkers that may account for autistic features and/or heterogeneity in clinical profiles, and (4) investigate the impact of second or multiple genetic hits on heterogeneity in clinical profiles. In the current paper we describe our methodology for phenotyping the sample and our planned comparisons, with information on the necessary adaptations made during the global COVID-19 pandemic. We also describe the demographics of the data collected thus far, including 25 PMS, 36 NRXN1ds, 33 iASD, and 52 NTD participants, and present an interim analysis of autistic features and adaptive functioning. [ABSTRACT FROM AUTHOR]

It is well-documented that autism can be reliably diagnosed by age two and that early signs emerge most often between 18 and 24 months. However, despite the increased awareness and focus on early diagnosis, the average age of diagnosis is over 4 years old; even later for Black children and those who are Medicaid-eligible. In this paper, we will propose a framework for accurate and accelerated autism diagnosis for children before age three. The proposed framework emphasizes a collaborative diagnostic process, which relies heavily on Birth to Three provider knowledge and expertise. Considerations for next steps are presented. This approach could increase access to diagnosis of young children soon after first signs of autism emerge. [ABSTRACT FROM AUTHOR]

Autism spectrum disorders (ASD) are a group of disorders characterized by impairment in social communication and repetitive and stereotyped behaviors. ASD etiology is very complex, including the effect of both genetic and environmental factors. So far, no specific treatment for the core symptoms of ASD has been developed, although attempts have been made for the treatment of repetitive behavior. The pharmacological treatment is aimed at treating non-specific symptoms such as irritability and aggression. Recent studies pointed out to the possible role of altered dopamine signaling in mesocorticolimbic and nigrostriatal circuits in ASD. In addition, several research pointed out to the association of dopamine receptors polymorphism and ASD, specifically repetitive and stereotyped behavior. In this paper, we will provide a review of the studies regarding dopamine signaling in ASD, existing data on the effects of D2/D3 partial agonists in ASD, possible implications regarding their individual receptor profiles, and future perspectives of their possible use in ASD treatment. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a deep learning model to classify children as either healthy or potentially having autism with 94.6% accuracy using Deep Learning. Patients with autism struggle with social skills, repetitive behaviors, and communication, both verbal and non-verbal. Although the disease is considered to be genetic, the highest rates of accurate diagnosis occur when the child is tested on behavioral characteristics and facial features. Patients have a common pattern of distinct facial deformities, allowing researchers to analyze only an image of the child to determine if the child has the disease. While there are other techniques and models used for facial analysis and autism classification on their own, our proposal bridges these two ideas allowing classification in a cheaper, more efficient method. Our deep learning model uses MobileNet and two dense layers to perform feature extraction and image classification. The model is trained and tested using 3,014 images, evenly split between children with autism and children without it; 90% of the data is used for training and 10% is used for testing. Based on our accuracy, we propose that the diagnosis of autism can be done effectively using only a picture. Additionally, there may be other diseases that are similarly diagnosable. [ABSTRACT FROM AUTHOR]

Resting-state functional MRI (rs-fMRI) has been widely used for the early diagnosis of autism spectrum disorder (ASD). With rs-fMRI, the functional connectivity networks (FCNs) are usually constructed for representing each subject, with each element representing the pairwise relationship between brain region-of-interests (ROIs). Previous studies often first extract handcrafted network features (such as node degree and clustering coefficient) from FCNs and then construct a prediction model for ASD diagnosis, which largely requires expert knowledge. Graph convolutional networks (GCNs) have recently been employed to jointly perform FCNs feature extraction and ASD identification in a data-driven manner. However, existing studies tend to focus on the single-scale topology of FCNs by using one single atlas for ROI partition, thus ignoring potential complementary topology information of FCNs at different spatial scales. In this paper, we develop a multi-scale graph representation learning (MGRL) framework for rs-fMRI based ASD diagnosis. The MGRL consists of three major components: (1) multi-scale FCNs construction using multiple brain atlases for ROI partition, (2) FCNs representation learning via multi-scale GCNs, and (3) multi-scale feature fusion and classification for ASD diagnosis. The proposed MGRL is evaluated on 184 subjects from the public Autism Brain Imaging Data Exchange (ABIDE) database with rs-fMRI scans. Experimental results suggest the efficacy of our MGRL in FCN feature extraction and ASD identification, compared with several state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper provides a brief review of the history, proposed pharmacological mechanisms, safety issues, and clinical applications of the medicine 3,4-methylenedioxymethamphetamine (MDMA). Most clinical MDMA research in patients to date has focused on MDMA-assisted psychotherapy to treat posttraumatic stress disorder (PTSD). In this review paper other potential therapeutic applications for MDMA therapy are described, including contemporary studies treating anxiety associated with autism and the authors' ongoing study exploring the potential role for MDMA-assisted psychotherapy to treat alcohol use disorder. MDMA therapy for PTSD is now entering the final Phase 3 stage of drug development, with a target set for licensing by the FDA and EMA in 2021. This means that if clinical efficacy criteria are achieved, MDMA would become a medicine. [ABSTRACT FROM AUTHOR]

Empirical evidence suggests that children with autism spectrum disorder (ASD) show abnormal behavior during delay eyeblink conditioning. They show a higher conditioned response learning rate and earlier peak latency of the conditioned response signal. The neuronal mechanisms underlying this autistic behavioral phenotype are still unclear. Here, we use a physiologically constrained spiking neuron model of the cerebellar-cortical system to investigate which features are critical to explaining atypical learning in ASD. Significantly, the computer simulations run with the model suggest that the higher conditioned responses learning rate mainly depends on the reduced number of Purkinje cells. In contrast, the earlier peak latency mainly depends on the hyper-connections of the cerebellum with sensory and motor cortex. Notably, the model has been validated by reproducing the behavioral data collected from studies with real children. Overall, this article is a starting point to understanding the link between the behavioral and neurobiological basis in ASD learning. At the end of the paper, we discuss how this knowledge could be critical for devising new treatments. [ABSTRACT FROM AUTHOR]

Purpose: Narratives of personal experiences emerge early in language acquisition and are particularly commonly experienced in children's daily lives. To produce these stories, children need to develop narrative, linguistic, and social-cognitive skills. Research has shown that these skills are impaired in children with developmental language disorder (DLD) and high functioning autism (HFA). Aim: This study aimed to determine whether narrative skills are still impaired in adolescence and to highlight the language similarities and differences between teenagers with DLD and HFA in the production of a narrative of a personal experience. Method: Ten teenagers with DLD, 10 teenagers with HFA and 10 typically developing (TD) teenagers, matched on chronological age, told a narrative of a personal experience. These stories were analyzed to evaluate narrative skills through coherence (respect of the narrative schema) and cohesion (anaphora and connectors) and social-cognitive skills (affective and cognitive mental states of the characters, and arbitrary vocalizations such as voice noises). Results: Teenagers with DLD were less compliant with the complication step in the narrative schema than teenagers with HFA or TD. No difference was observed between the three groups of teenagers in terms of cohesion or regarding the positive and negative social-cognitive skills used in narratives. Conclusion: When producing a narrative of a personal experience, HFA teens do not have difficulties neither with narrative skills and with social-cognitive skills assessed in this paper. In DLD the profile of the teens is not the same: They do not have difficulties with social-cognitive skills and with a part of narrative skills (cohesion), and they have difficulties with the narrative schema. [ABSTRACT FROM AUTHOR]

Fragile X syndrome (FXS) is the most common single-gene cause of intellectual disability and autism spectrum disorder. Individuals with FXS present with a wide range of severity in multiple phenotypes including cognitive delay, behavioral challenges, sleep issues, epilepsy, and anxiety. These symptoms are also shared by many individuals with other neurodevelopmental disorders (NDDs). Since the discovery of the FXS gene, FMR1, FXS has been the focus of intense preclinical investigation and is placed at the forefront of clinical trials in the field of NDDs. So far, most studies have aimed to translate the rescue of specific phenotypes in animal models, for example, learning, or improving general cognitive or behavioral functioning in individuals with FXS. Trial design, selection of outcome measures, and interpretation of results of recent trials have shown limitations in this type of approach. We propose a new paradigm in which all phenotypes involved in individuals with FXS would be considered and, more importantly, the possible interactions between these phenotypes. This approach would be implemented both at the baseline, meaning when entering a trial or when studying a patient population, and also after the intervention when the study subjects have been exposed to the investigational product. This approach would allow us to further understand potential trade-offs underlying the varying effects of the treatment on different individuals in clinical trials, and to connect the results to individual genetic differences. To better understand the interplay between different phenotypes, we emphasize the need for preclinical studies to investigate various interrelated biological and behavioral outcomes when assessing a specific treatment. In this paper, we present how such a conceptual shift in preclinical design could shed new light on clinical trial results. Future clinical studies should take into account the rich neurodiversity of individuals with FXS specifically and NDDs in general, and incorporate the idea of trade-offs in their designs. [ABSTRACT FROM AUTHOR]

The infant brain undergoes a remarkable period of neural development that is crucial for the development of cognitive and behavioral capacities (Hasegawa et al., 2018). Longitudinal magnetic resonance imaging (MRI) is able to characterize the developmental trajectories and is critical in neuroimaging studies of early brain development. However, missing data at different time points is an unavoidable occurrence in longitudinal studies owing to participant attrition and scan failure. Compared to dropping incomplete data, data imputation is considered a better solution to address such missing data in order to preserve all available samples. In this paper, we adapt generative adversarial networks (GAN) to a new application: longitudinal image prediction of structural MRI in the first year of life. In contrast to existing medical image-to-image translation applications of GANs, where inputs and outputs share a very close anatomical structure, our task is more challenging as brain size, shape and tissue contrast vary significantly between the input data and the predicted data. Several improvements over existing GAN approaches are proposed to address these challenges in our task. To enhance the realism, crispness, and accuracy of the predicted images, we incorporate both a traditional voxel-wise reconstruction loss as well as a perceptual loss term into the adversarial learning scheme. As the differing contrast changes in T1w and T2w MR images in the first year of life, we incorporate multi-contrast images leading to our proposed 3D multi-contrast perceptual adversarial network (MPGAN). Extensive evaluations are performed to assess the qualityand fidelity of the predicted images, including qualitative and quantitative assessments of the image appearance, as well as quantitative assessment on two segmentation tasks. Our experimental results show that our MPGAN is an effective solution for longitudinal MR image data imputation in the infant brain. We further apply our predicted/imputed images to two practical tasks, a regression task and a classification task, in order to highlight the enhanced task-related performance following image imputation. The results show that the model performance in both tasks is improved by including the additional imputed data, demonstrating the usability of the predicted images generated from our approach. [ABSTRACT FROM AUTHOR]

The presence of prosodic anomalies in autistic is recognized by experienced clinicians but their quantitative analysis is a cumbersome task beyond the scope of typical pen and pencil assessment. This paper proposes an automatic approach allowing to tease apart various aspects of prosodic abnormalities and to translate them into fine-grained, automated, and quantifiable measurements. Using a harmonic model (HM) of voiced signal, we isolated the harmonic content of speech and computed a set of quantities related to harmonic content. Employing these measures, along with standard speech measures such as loudness, we successfully trained machine learning models for distinguishing individuals with autism from those with typical development (TD). We evaluated our models empirically on a task of detecting autism on a sample of 118 youth (90 diagnosed with autism and 28 controls; mean age: 10.9 years) and demonstrated that these models perform significantly better than a chance model. Voice and speech analyses could be incorporated as novel outcome measures for treatment research and used for early detection of autism in preverbal infants or toddlers at risk of autism. [ABSTRACT FROM AUTHOR]

The article discusses various papers published in this issue including one by Schore on an interpersonal neurobiological theoretical model of early socio-emotional development in children, one by De Falco et al. on motion-child interaction, and one by Pace on friend and family.

An introduction to the research topic on autism which will be published in "Frontiers in Integrative Neuroscience" is presented.

The 1998 Lancet paper by Wakefield et al., despite subsequent retraction and evidence indicating no causal link between vaccinations and autism, triggered significant parental concern. The aim of this study was to analyze the online information available on this topic. Using localized versions of Google, we searched "autism vaccine" in English, French, Italian, Portuguese, Mandarin, and Arabic and analyzed 200 websites for each search engine result page (SERP). A common feature was the newsworthiness of the topic, with news outlets representing 25-50% of the SERP, followed by unaffiliated websites (blogs, social media) that represented 27-41% and included most of the vaccine-negative websites. Between 12 and 24% of websites had a negative stance on vaccines, while most websites were pro-vaccine (43-70%). However, their ranking by Google varied. While in Google.com, the first vaccine-negative website was the 43rd in the SERP, there was one vaccine-negative webpage in the top 10 websites in both the British and Australian localized versions and in French and two in Italian, Portuguese, and Mandarin, suggesting that the information quality algorithm used by Google may work better in English. Many webpages mentioned celebrities in the context of the link between vaccines and autism, with Donald Trump most frequently. Few websites (1-5%) promoted complementary and alternative medicine (CAM) but 50-100% of these were also vaccine-negative suggesting that CAM users are more exposed to vaccine-negative information. This analysis highlights the need for monitoring the web for information impacting on vaccine uptake. [ABSTRACT FROM AUTHOR]