Correlation between autistic traits and brain functional connectivity in preschoolers with autism spectrum disorder: a resting state MEG study.

BACKGROUND: Neurophysiological studies recognized that Autism Spectrum Disorder (ASD) is associated with altered patterns of over- and under-connectivity. However, little is known about network organization in children with ASD in the early phases of development and its correlation with the severity of core autistic features. METHODS: The present study aimed at investigating the association between brain connectivity derived from MEG signals and severity of ASD traits measured with different diagnostic clinical scales, in a sample of 16 children with ASD aged 2 to 6 years. RESULTS: A significant correlation emerged between connectivity strength in cortical brain areas implicated in several resting state networks (Default mode, Central executive, Salience, Visual and Sensorimotor) and the severity of communication anomalies, social interaction problems, social affect problems, and repetitive behaviors. Seed analysis revealed that this pattern of correlation was mainly caused by global rather than local effects. CONCLUSIONS: The present evidence suggests that altered connectivity strength in several resting state networks is related to clinical features and may contribute to neurofunctional correlates of ASD. Future studies implementing the same method on a wider and stratified sample may further support functional connectivity as a possible biomarker of the condition.

CGH Findings in Children with Complex and Essential Autistic Spectrum Disorder.

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition with a strong genetic basis. We accurately assessed 209 ASD subjects, categorized in complex (47) and essential (162), and performed array comparative genomic hybridization to identify pathogenic and recurrent Copy Number Variants (CNVs). We found 117 CNVs in 75 patients, 11 classified as pathogenic. The complex ASD subjects have higher frequency of pathogenic CNVs with a diagnostic yield of 12.8%. Familiality, cognitive and verbal abilities, severity of autistic symptoms, neuroimaging and neurophysiological findings are not related to genetic data. This study identifies loci of interest for ASD and highlights the importance of a careful phenotypic characterization, as complex ASD is related to higher rate of pathogenic CNVs.

Development of an Interactive Total Body Robot Enhanced Imitation Therapy for ASD children.

Autism is a neurodevelopmental disorder in which the available therapies target the improvement of social skills, in order to ensure a high quality of life for the child. The use of Social Assistive Robots offers new therapeutic possibilities in which robots can act as therapy enhancers. IOGIOCO project emerges in this framework: it aims at the development of a Robot- Assisted Therapy protocol for the treatment of Autism Spectrum Disorder, through gesture training. The definition of these gestures and their recognition by the robot are parameters that directly affect the engagement of the children. However, the design of a protocol becomes harder in a highly unconstrained environment. Therefore, the current work aims at expanding the gesture set and improving the gesture recognition algorithm available in the IOGIOCO platform. More specifically, total body gestures have been added to the available upper limbs movements, and a custom Activity Detection method has been developed, which allows the identification of the time window in which a gesture is performed. The insertion of this method on a recognition algorithm based on a ResNet, a particular kind of Convolutional Neural Network, improved its F1-score from 57% obtained with the previously-available version, in a dataset of ASD children, to 76%, demonstrating the effectiveness of the Activity Detection method. Furthermore, the expansion of the interaction possibilities to total body movements was positively evaluated by the clinical staff, increasing the engagement of patients and the set of possible trained skills. Therefore, the results of the current work are encouraging. To reinforce the conclusions drawn, the proposed algorithm should be tested in real time on several autistic children within a complete Randomized Clinical Trial, also to study the effectiveness of this type of treatment. From the technical point of view, further improvements of the developed methodology should tackle the remained issues, such as further increasing the recognition capability, especially in the transitions from sitting to standing, that proved to be a hard task for the developed method.

Sharing Worlds: Design of a Real-Time Attention Classifier for Robotic Therapy of ASD Children.

Joint attention is the capacity of sharing attention between two agents and an aspect of the environment, through the use of different cues, namely gaze. This capacity is of paramount importance for social skills. People with Autism Spectrum Disorder (ASD) present certain deficits in joint attention. Therefore, there is an increasing interest in finding therapies to improve this skill. Some of these therapies include robots since they are known to be attractive to people with autism due to their motivation ability and predictability when compared with humans. In this line, we have designed a real-time attention classifier for a triadic robotic therapy, using Gaze360 and geometrical considerations of the scene. We were able to classify the gaze of the therapist and the one of the child during the whole session, even in a highly unconstrained scenario with a single camera, achieving a mean accuracy of 59%. This classifier can be used for the measurement of joint attention, an important metric for the development of adaptive robotic therapies, where increasing levels of difficulty and engagement are provided dependent on the ASD children, who are characterised by high heterogeneity. Future work will pass by the calculation of this metric and integration on a robotic platform for ASD therapy to understand the impact of these robotic therapies in improving ASD symptoms, specifically on how ASD children share their attention with other people present in the rehabilitation scenarios.

Small 6q16.1 Deletions Encompassing POU3F2 Cause Susceptibility to Obesity and Variable Developmental Delay with Intellectual Disability.

Genetic studies of intellectual disability and identification of monogenic causes of obesity in humans have made immense contribution toward the understanding of the brain and control of body mass. The leptin > melanocortin > SIM1 pathway is dysregulated in multiple monogenic human obesity syndromes but its downstream targets are still unknown. In ten individuals from six families, with overlapping 6q16.1 deletions, we describe a disorder of variable developmental delay, intellectual disability, and susceptibility to obesity and hyperphagia. The 6q16.1 deletions segregated with the phenotype in multiplex families and were shown to be de novo in four families, and there was dramatic phenotypic overlap among affected individuals who were independently ascertained without bias from clinical features. Analysis of the deletions revealed a ∼350 kb critical region on chromosome 6q16.1 that encompasses a gene for proneuronal transcription factor POU3F2, which is important for hypothalamic development and function. Using morpholino and mutant zebrafish models, we show that POU3F2 lies downstream of SIM1 and controls oxytocin expression in the hypothalamic neuroendocrine preoptic area. We show that this finding is consistent with the expression patterns of POU3F2 and related genes in the human brain. Our work helps to further delineate the neuro-endocrine control of energy balance/body mass and demonstrates that this molecular pathway is conserved across multiple species.

Low-Functioning Autism and Nonsyndromic Intellectual Disability: Magnetic Resonance Imaging (MRI) Findings.

Previous neuroradiologic studies reported a high incidence of abnormalities in low-functioning autistic children. In this population, it is difficult to know which abnormality depends on autism itself and which is related to intellectual disability associated with autism. The aim of this study was to evaluate the frequency of neuroradiologic abnormalities in low-functioning autistic children compared to Intellectual Quotient and age-matched nonsyndromic children, using the same set of magnetic resonance imaging (MRI) sequences. MRI was rated as abnormal in 44% of autistic and 54% of children with intellectual disability. The main results were mega cisterna magna in autism and hypoplastic corpus callosum in intellectual disability. These abnormalities are morphologically visible signs of altered brain development. These findings, more frequent than expected, are not specific to the 2 conditions. Although MRI cannot be considered mandatory, it allows an in-depth clinical assessment in nonsyndromic intellectual-disabled and autistic children.

Constrained spherical deconvolution-based tractography to depict and characterize a case of "hyperplastic fornix dorsalis".

The authors report the relevance of Constrained Spherical Deconvolution (CSD)-based tractography in demonstrating and quantitatively assessing a complex midline structure malformation in a 9-year-old girl with moderate intellectual disability and thickening of corpus callosum (CC) body discovered through conventional MRI (cMRI). Color-encoded fractional anisotropy (FA) maps clearly demonstrated what the cMRI showed as a thicknening of CC: a green, longitudinal bundle running dorsally to the body of CC. A more complex midline maldevelopmental disorder was suspected. CSD-based tractography was performed to virtually dissect the anomalous supracallosal longitudinal bundle (SLB), CC, fornix, anterior commissure (AC) and cingula. In addition, DTI-derived metrics were calculated for each virtually dissected fiber tract. The tractography study evidenced projections of the anomalous SLB in left forceps minor and to parietal regions, and projections of the fornix in right forceps minor. CC virtual dissection showed no gross abnormality, and cingula appeared slightly less extended than normal. The considerable thinning of AC hampered its virtual dissection. DTI-derived metrics suggested alterations in fornix microstructure, attributable to higher fiber density. In investigating white matter, cMRI may not be sufficient in addressing and assessing possible anomalies, while advanced CSD-based tractography and DTI-derived metrics may prove helpful in depicting and characterizing white matter anomalies in developmental disorders.

Gray matter reduction in the vermis and CRUS-II is associated with social and interaction deficits in low-functioning children with autistic spectrum disorders: a VBM-DARTEL Study.

Voxel-based morphometry (VBM) studies have reported abnormalities in brain regions involved in functions that are commonly impaired in autism spectrum disorders (ASD). However, little is known about brain structure anomalies in low-functioning (LF) young children with ASD. A VBM analysis was carried out to assess brain regions involved in ASD LF children, and a multiple regression analysis was used to examine the relationship between regional volume changes and autism symptom measures. Twenty-six LF ASD children (2-10 years) were compared with 21 controls. A VBM-Diffeomorphic Anatomical Registration analysis using Exponentiated Lie algebra (DARTEL) was used to evaluate gray matter (GM) and white matter alterations, covaried with Intelligence Quotient, age, and total brain volume. The resulting altered regions were correlated with Autism Diagnostic Interview (ADI)-Revised and Autism Diagnostic Observation Schedule (ADOS)-Generic scores. GM bilateral reduction was noted in the cerebellum (Crus II and vermis) and in the hippocampi in ASD group. GM reduction was also detected in the inferior and superior frontal gyri, in the occipital medial and superior gyri, and in the inferior temporal gyrus of the left cerebral hemisphere. In the right hemisphere, GM reduction was found in the post-central cortex and in the occipital inferior gyrus. Multiple regression analysis showed a correlation between alterations in GM volume in the cerebellum (Crus II and vermis) and ADI-communication and ADOS-total (communication and interaction) scores. These findings seem to confirm that the cerebellum is involved in integrating and regulating emotional and cognitive functions which are impaired in ASD.