Grammatical comprehension in italian children with autism spectrum disorder

Language deficits represent one of the most relevant factors that determine the clinical phenotype of children with autism spectrum disorder (ASD). The main aim of the research was to study the grammatical comprehension of children with ASD. A sample of 70 well-diagnosed children (60 boys and 10 girls; aged 4.9–8 years) were prospectively recruited. The results showed that language comprehension is the most impaired language domain in ASD. These findings have important clinical implications, since the persistence of grammatical receptive deficits may have a negative impact on social, adaptive and learning achievements. As for the grammatical profiles, persistent difficulties were found during the school-age years in morphological and syntactic decoding in children with relatively preserved cognitive and expressive language skills. These data and the lack of a statistically significant correlation between the severity of ASD symptoms and language skills are in line with the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) perspective that considers the socio-communication disorder as a nuclear feature of ASD and the language disorder as a specifier of the diagnosis and not as a secondary symptom anymore. The presence of receptive difficulties in school-age ASD children with relatively preserved non-verbal cognitive abilities provides important hints to establish rehabilitative treatments

Disentangling the initiation from the response in joint attention: an eye-tracking study in toddlers with autism spectrum disorders

Joint attention (JA), whose deficit is an early risk marker for autism spectrum disorder (ASD), has two dimensions: (1) responding to JA and (2) initiating JA. Eye-tracking technology has largely been used to investigate responding JA, but rarely to study initiating JA especially in young children with ASD. The aim of this study was to describe the differences in the visual patterns of toddlers with ASD and those with typical development (TD) during both responding JA and initiating JA tasks. Eye-tracking technology was used to monitor the gaze of 17 children with ASD and 15 age-matched children with TD during the presentation of short video sequences involving one responding JA and two initiating JA tasks (initiating JA-1 and initiating JA-2). Gaze accuracy, transitions and fixations were analyzed. No differences were found in the responding JA task between children with ASD and those with TD, whereas, in the initiating JA tasks, different patterns of fixation and transitions were shown between the groups. These results suggest that children with ASD and those with TD show different visual patterns when they are expected to initiate joint attention but not when they respond to joint attention. We hypothesized that differences in transitions and fixations are linked to ASD impairments in visual disengagement from face, in global scanning of the scene and in the ability to anticipate object's action

Feature-by-Feature – Evaluating De Novo Sequence Assembly

The whole-genome sequence assembly (WGSA) problem is among one of the most studied problems in computational biology. Despite the availability of a plethora of tools (i.e., assemblers), all claiming to have solved the WGSA problem, little has been done to systematically compare their accuracy and power. Traditional methods rely on standard metrics and read simulation: while on the one hand, metrics like N50 and number of contigs focus only on size without proportionately emphasizing the information about the correctness of the assembly, comparisons performed on simulated dataset, on the other hand, can be highly biased by the non-realistic assumptions in the underlying read generator. Recently the Feature Response Curve (FRC) method was proposed to assess the overall assembly quality and correctness: FRC transparently captures the trade-offs between contigs' quality against their sizes. Nevertheless, the relationship among the different features and their relative importance remains unknown. In particular, FRC cannot account for the correlation among the different features. We analyzed the correlation among different features in order to better describe their relationships and their importance in gauging assembly quality and correctness. In particular, using multivariate techniques like principal and independent component analysis we were able to estimate the “excess-dimensionality” of the feature space. Moreover, principal component analysis allowed us to show how poorly the acclaimed N50 metric describes the assembly quality. Applying independent component analysis we identified a subset of features that better describe the assemblers performances. We demonstrated that by focusing on a reduced set of highly informative features we can use the FRC curve to better describe and compare the performances of different assemblers. Moreover, as a by-product of our analysis, we discovered how often evaluation based on simulated data, obtained with state of the art simulators, lead to not-so-realistic results

Safe and complete contig assembly via omnitigs

Contig assembly is the first stage that most assemblers solve when reconstructing a genome from a set of reads. Its output consists of contigs -- a set of strings that are promised to appear in any genome that could have generated the reads. From the introduction of contigs 20 years ago, assemblers have tried to obtain longer and longer contigs, but the following question was never solved: given a genome graph $G$ (e.g. a de Bruijn, or a string graph), what are all the strings that can be safely reported from $G$ as contigs? In this paper we finally answer this question, and also give a polynomial time algorithm to find them. Our experiments show that these strings, which we call omnitigs, are 66% to 82% longer on average than the popular unitigs, and 29% of dbSNP locations have more neighbors in omnitigs than in unitigs.Comment: Full version of the paper in the proceedings of RECOMB 201

Multimodal functional and structural brain connectivity analysis in autism: A preliminary integrated approach with EEG, fMRI and DTI

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.This paper proposes a novel approach of integrating different neuroimaging techniques to characterize an autistic brain. Different techniques like EEG, fMRI and DTI have traditionally been used to find biomarkers for autism, but there have been very few attempts for a combined or multimodal approach of EEG, fMRI and DTI to understand the neurobiological basis of autism spectrum disorder (ASD). Here, we explore how the structural brain network correlate with the functional brain network, such that the information encompassed by these two could be uncovered only by using the latter. In this paper, source localization from EEG using independent component analysis (ICA) and dipole fitting has been applied first, followed by selecting those dipoles that are closest to the active regions identified with fMRI. This allows translating the high temporal resolution of EEG to estimate time varying connectivity at the spatial source level. Our analysis shows that the estimated functional connectivity between two active regions can be correlated with the physical properties of the structure obtained from DTI analysis. This constitutes a first step towards opening the possibility of using pervasive EEG to monitor the long-term impact of ASD treatment without the need for frequent expensive fMRI or DTI investigations

Disentangling the initiation from the response in joint attention: An eye-tracking study in toddlers with autism spectrum disorders

Joint attention (JA), whose deficit is an early risk marker for autism spectrum disorder (ASD), has two dimensions: (1) responding to JA and (2) initiating JA. Eye-tracking technology has largely been used to investigate responding JA, but rarely to study initiating JA especially in young children with ASD. The aim of this study was to describe the differences in the visual patterns of toddlers with ASD and those with typical development (TD) during both responding JA and initiating JA tasks. Eye-tracking technology was used to monitor the gaze of 17 children with ASD and 15 age-matched children with TD during the presentation of short video sequences involving one responding JA and two initiating JA tasks (initiating JA-1 and initiating JA-2). Gaze accuracy, transitions and fixations were analyzed. No differences were found in the responding JA task between children with ASD and those with TD, whereas, in the initiating JA tasks, different patterns of fixation and transitions were shown between the groups. These results suggest that children with ASD and those with TD show different visual patterns when they are expected to initiate joint attention but not when they respond to joint attention. We hypothesized that differences in transitions and fixations are linked to ASD impairments in visual disengagement from face, in global scanning of the scene and in the ability to anticipate object's action

A genetically informed cross-lagged analysis of autistic-like traits and affective problems in early childhood

A genetically informed cross-lagged model was applied to twin data to explore etiological links between autistic-like traits and affective problems in early childhood. The sample comprised 310 same-sex twin pairs (143 monozygotic and 167 dizygotic; 53% male). Autistic-like traits and affective problems were assessed at ages 2 and 3 using parent ratings. Both constructs were related within and across age (r = .30-.53) and showed moderate stability (r = .45-.54). Autistic-like traits and affective problems showed genetic and environmental influences at both ages. Whereas at age 2, the covariance between autistic-like traits and affective problems was entirely due to environmental influences (shared and nonshared), at age 3, genetic factors also contributed to the covariance between constructs. The stability paths, but not the cross-lagged paths, were significant, indicating that there is stability in both autistic-like traits and affective problems but they do not mutually influence each other across age. Stability effects were due to genetic, shared, and nonshared environmental influences. Substantial novel genetic and nonshared environmental influences emerge at age 3 and suggest change in the etiology of these constructs over time. During early childhood, autistic-like traits tend to occur alongside affective problems and partly overlapping genetic and environmental influences explain this association