As compared to the utility of early emerging social communicative risk markers for predicting a later diagnosis of autism spectrum disorder (ASD), less is known about the relevance of early patterns of restricted and repetitive behaviors. We examined patterns of stereotyped motor mannerisms and repetitive manipulation of objects in 12-month-olds at high and low risk for developing ASD, all of whom were assessed for ASD at 24 months.
Observational coding of repetitive object manipulation and stereotyped motor behaviors in digital recordings of the Communication and Symbolic Behavior Scales was conducted using the Repetitive and Stereotyped Movement Scales for three groups of 12-month-olds: 1) low-risk infants (LR, n = 53); 2) high-familial-risk infants who did not meet diagnostic criteria for ASD at 24-months (HR-negative, n = 75); and 3) high-familial-risk infants who met diagnostic criteria for ASD at 24 months (HR-ASD, n = 30).
The HR-ASD group showed significantly more stereotyped motor mannerisms than both the HR-negative group (p = .025) and the LR group (p = .001). The HR-ASD and HR-negative groups demonstrated statistically equivalent repetitive object manipulation scores (p = .431), and both groups showed significantly more repetitive object manipulation than the LR group (p’s < 0.040). Combining the motor and object stereotypy scores into an RSMS composite yielded a disorder-continuum effect such that each group was significantly different from one another (LR < HR-negative < HR-ASD).
These results suggest that targeted assessment of repetitive behavior during infancy may augment early identification efforts.
autism; repetitive behavior; motor stereotypies; infant siblings; development
While it is now recognized that autism spectrum disorder (ASD) is typically a life-long condition, there exist only a handful of systematic studies on middle-aged and older adults with this condition.
We first performed a structured examination of parkinsonian motor signs in a hypothesis-generating, pilot study (study I) of 19 adults with ASD over 49 years of age. Observing high rates of parkinsonism in those off atypical neuroleptics (2/12, 17 %) in comparison to published population rates for Parkinson’s disease and parkinsonism, we examined a second sample of 37 adults with ASD, over 39 years of age, using a structured neurological assessment for parkinsonism.
Twelve of the 37 subjects (32 %) met the diagnostic criteria for parkinsonism; however, of these, 29 subjects were on atypical neuroleptics, complicating interpretation of the findings. Two of eight (25 %) subjects not taking atypical neuroleptic medications met the criteria for parkinsonism. Combining subjects who were not currently taking atypical neuroleptic medications, across both studies, we conservatively classified 4/20 (20 %) with parkinsonism.
We find a high frequency of parkinsonism among ASD individuals older than 39 years. If high rates of parkinsonism and potentially Parkinson’s disease are confirmed in subsequent studies of ASD, this observation has important implications for understanding the neurobiology of autism and treatment of manifestations in older adults. Given the prevalence of autism in school-age children, the recognition of its life-long natural history, and the recognition of the aging of western societies, these findings also support the importance of further systematic study of other aspects of older adults with autism.
parkinsonism; autism; movement disorders; parkinson’s disease; adults
Recent evidence suggests that restricted and repetitive behaviors may
differentiate children who develop autism spectrum disorder (ASD) by late
infancy. How these core symptoms manifest early in life, particularly among
infants at high-risk for the disorder, is not well characterized.
Prospective, longitudinal parent-report data (Repetitive Behavior
Scales-Revised) were collected for 190 high-risk toddlers and 60 low-risk
controls from 12 to 24 months age. Forty-one high-risk children were
classified with ASD at age 2. Profiles of repetitive behavior were compared
between groups using generalized estimating equations.
Longitudinal profiles for children diagnosed with ASD differed
significantly from high- and low-risk children without the disorder on all
measures of repetitive behavior. High-risk toddlers without ASD were
intermediate to low-risk and ASD positive counterparts. Toddlers with ASD
showed significantly higher rates of repetitive behavior across subtypes at
the 12 month time point. Repetitive behaviors were significantly correlated
with adaptive behavior and socialization scores among children with ASD at
24 months-age but were largely unrelated to measures of general cognitive
These findings suggest that as early as 12 months age, a broad range
of repetitive behaviors are highly elevated in children who go on to develop
ASD. While some degree of repetitive behavior is elemental to typical early
development, the extent of these behaviors among children who develop ASD
appears highly atypical.
autism; repetitive behavior; high-risk siblings
To examine longitudinally the adaptive behavior patterns in fragile X syndrome.
Caregivers of 275 children and adolescents with fragile X syndrome and 225 typically developing children and adolescents (2–18 years) were interviewed with the Vineland Adaptive Behavior Scales every 2 to 4 years as part of a prospective longitudinal study.
Standard scores of adaptive behavior in people with fragile X syndrome are marked by a significant decline over time in all domains for males and in communication for females. Socialization skills are a relative strength as compared with the other domains for males with fragile X syndrome. Females with fragile X syndrome did not show a discernible pattern of developmental strengths and weaknesses.
This is the first large-scale longitudinal study to show that the acquisition of adaptive behavior slows as individuals with fragile X syndrome age. It is imperative to ensure that assessments of adaptive behavior skills are part of intervention programs focusing on childhood and adolescence in this condition.
fragile X syndrome; adaptive behavior; children; adolescents; Vineland
To delineate the early progression of autism spectrum disorder (ASD) symptoms, this study investigated developmental characteristics of infants at high familial risk for ASD (HR), and infants at low risk (LR).
Participants included 210 HR and 98 LR infants across 4 sites with comparable behavioral data at age 6, 12, and 24 months assessed in the domains of cognitive development (Mullen Scales of Early Learning), adaptive skills (Vineland Adaptive Behavioral Scales), and early behavioral features of ASD (Autism Observation Scale for Infants). Participants evaluated according to the DSM-IV-TR criteria at 24 months and categorized as ASD-positive or ASD-negative were further stratified by empirically derived cutoff scores using the Autism Diagnostic Observation Schedule yielding four groups: HR-ASD-High, HR-ASD-Moderate (HR-ASD-Mod), HR-ASD-Negative (HR-Neg), and LR-ASD-Negative (LR-Neg).
The four groups demonstrated different developmental trajectories that became increasingly distinct from 6 to 24 months across all domains. At 6 months, the HR-ASD-High group demonstrated less advanced Gross Motor and Visual Reception skills compared with the LR-Neg group. By 12 months, the HR-ASD-High group demonstrated increased behavioral features of ASD and decreased cognitive and adaptive functioning compared to the HR-Neg and LR-Neg groups. By 24 months, both the HR-ASD-High and HR-ASD-Moderate groups demonstrated differences from the LR- and HR-Neg groups in all domains.
These findings reveal atypical sensorimotor development at 6 months of age which is associated with ASD at 24 months in the most severely affected group of infants. Sensorimotor differences precede the unfolding of cognitive and adaptive deficits and behavioral features of autism across the 6- to 24-month interval. The less severely affected group demonstrates later symptom onset, in the second year of life, with initial differences in the social-communication domain.
Electronic supplementary material
The online version of this article (doi:10.1186/s11689-015-9117-6) contains supplementary material, which is available to authorized users.
To apply phenotypic and statistical methods designed to account for heterogeneity to linkage analyses of the autism Collaborative Linkage Study of Autism (CLSA) affected sibling pair families.
The CLSA contains two sets of 57 families each; Set 1 has been analyzed previously, whereas this study presents the first analyses of Set 2. The two sets were analyzed independently, and were further split based on the degree of phrase speech delay in the siblings. Linkage analysis was carried out using the posterior probability of linkage (PPL), a Bayesian statistic that provides a mathematically rigorous mechanism for combining linkage evidence across multiple samples.
Two-point PPLs from Set 1 led to the follow-up genotyping of 18 markers around linkage peaks on 1q, 13p, 13q, 16q, and 17q in both sets of families. Multipoint PPLs were then calculated for the entire CLSA sample. These analyses identified four regions with at least modest evidence in support of linkage: 1q at 173 cM, PPL = 0.12; 13p at 21 cM, PPL = 0.16; 16q at 63 cM, PPL= 0.36; Xq at 40 cM, PPL = 0.11.
We find strengthened evidence for linkage of autism to chromosomes 1q, 13p, 16q, and Xq, and diminished evidence for linkage to 7q and 13q. The verity of these findings will be tested by continuing to update our PPL analyses with data from additional autism datasets.
autism; genetics; heterogeneity; language delay; linkage; positional cloning
Autism is an etiologically heterogeneous neurodevelopmental disorder for which there is no known unifying etiology or pathogenesis. Many conditions of atypical development can lead to autism, including fragile X syndrome (FXS), which is presently the most common known single gene cause of autism.
To examine whole-brain morphometric patterns that discriminate young boys with FXS from those with idiopathic autism (iAUT), as well as control participants.
Cross sectional, in-vivo neuroimaging study.
Academic medical centers.
Young boys (n=165, 1.57-4.15 years) diagnosed as FXS or iAUT as well as typically developing (TD) and idiopathic developmentally delayed (DD) controls.
Main Outcome measures
Univariate voxel-based morphometric (VBM) analyses, VBM multivariate pattern classification (linear support vector machine) and clustering analyses (self organizing map).
We found that frontal and temporal grey and white matter regions often implicated in social cognition, including the medial prefrontal cortex, orbitofrontal cortex, superior temporal region, temporal pole, amygdala, insula, and dorsal cingulum, were aberrant in FXS and iAUT as compared to controls. However, these differences were in opposite directions for FXS and iAUT relative to controls; in general, greater volume was seen in iAUT compared to controls, who in turn had greater volume than FXS. Multivariate analysis showed that the overall pattern of brain structure in iAUT generally resembled that of the controls more than FXS, both with and without AUT (FXS+A, FXS-A, respectively).
Our findings demonstrate that FXS and iAUT are associated with distinct neuroanatomical patterns, and further underscores the neurobiological heterogeneity of iAUT.
We thank all of our reviewers who have contributed to the journal in volume 6 (2014). High quality and timely reviews are critical to the overall quality of the journal. We are committed to providing a unique and important outlet for scholarship regarding neurodevelopmental disorders and are indebted to the outstanding reviewers who have contributed their time over the last year in helping us to reach this goal.
In this paper, we propose a new method for longitudinal shape analysis that fits a linear mixed-effects model, while simultaneously optimizing correspondences on a set of anatomical shapes. Shape changes are modeled in a hierarchical fashion, with the global population trend as a fixed effect and individual trends as random effects. The statistical significance of the estimated trends are evaluated using specifically designed permutation tests. We also develop a permutation test based on the Hotelling T2 statistic to compare the average shapes trends between two populations. We demonstrate the benefits of our method on a synthetic example of longitudinal tori and data from a developmental neuroimaging study.
Diffusion-weighted imaging (DWI) is known to be prone to artifacts related to motion originating from subject movement, cardiac pulsation, and breathing, but also to mechanical issues such as table vibrations. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which involves simple qualitative viewing of the set of DWI data, or the selection of transformation parameter thresholds for detection of motion outliers. The scientific community offers strong theoretical and experimental work on noise reduction and orientation distribution function (ODF) reconstruction techniques for HARDI data, where post-acquisition motion correction is widely performed, e.g., using the open-source DTIprep software (1), FSL (the FMRIB Software Library) (2), or TORTOISE (3). Nonetheless, effects and consequences of the selection of motion correction schemes on the final analysis, and the eventual risk of introducing confounding factors when comparing populations, are much less known and far beyond simple intuitive guessing. Hence, standard users lack clear guidelines and recommendations in practical settings. This paper reports a comprehensive evaluation framework to systematically assess the outcome of different motion correction choices commonly used by the scientific community on different DWI-derived measures. We make use of human brain HARDI data from a well-controlled motion experiment to simulate various degrees of motion corruption and noise contamination. Choices for correction include exclusion/scrubbing or registration of motion corrupted directions with different choices of interpolation, as well as the option of interpolation of all directions. The comparative evaluation is based on a study of the impact of motion correction using four metrics that quantify (1) similarity of fiber orientation distribution functions (fODFs), (2) deviation of local fiber orientations, (3) global brain connectivity via graph diffusion distance (GDD), and (4) the reproducibility of prominent and anatomically defined fiber tracts. Effects of various motion correction choices are systematically explored and illustrated, leading to a general conclusion of discouraging users from setting ad hoc thresholds on the estimated motion parameters beyond which volumes are claimed to be corrupted.
HARDI; subject motion; motion correction; fiber orientations; orientation distribution functions; tractography comparison; impact quantification
Diffusion MR imaging has received increasing attention in the neuroimaging community, as it yields new insights into the microstructural organization of white matter that are not available with conventional MRI techniques. While the technology has enormous potential, diffusion MRI suffers from a unique and complex set of image quality problems, limiting the sensitivity of studies and reducing the accuracy of findings. Furthermore, the acquisition time for diffusion MRI is longer than conventional MRI due to the need for multiple acquisitions to obtain directionally encoded Diffusion Weighted Images (DWI). This leads to increased motion artifacts, reduced signal-to-noise ratio (SNR), and increased proneness to a wide variety of artifacts, including eddy-current and motion artifacts, “venetian blind” artifacts, as well as slice-wise and gradient-wise inconsistencies. Such artifacts mandate stringent Quality Control (QC) schemes in the processing of diffusion MRI data. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts, often only visible when investigating groups of DWI's or a derived diffusion model, such as the most-employed diffusion tensor imaging (DTI). Here, we propose a novel regional QC measure in the DTI domain that employs the entropy of the regional distribution of the principal directions (PD). The PD entropy quantifies the scattering and spread of the principal diffusion directions and is invariant to the patient's position in the scanner. High entropy value indicates that the PDs are distributed relatively uniformly, while low entropy value indicates the presence of clusters in the PD distribution. The novel QC measure is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Such residual artifacts cause directional bias in the measured PD and here called dominant direction artifacts. Experiments show that our automatic method can reliably detect and potentially correct such artifacts, especially the ones caused by the vibrations of the scanner table during the scan. The results further indicate the usefulness of this method for general quality assessment in DTI studies.
Diffusion magnetic resonance imaging; Diffusion tensor imaging; Quality assessment; Entropy
Medical imaging studies increasingly use longitudinal images of individual subjects in order to follow-up changes due to development, degeneration, disease progression or efficacy of therapeutic intervention. Repeated image data of individuals are highly correlated, and the strong causality of information over time lead to the development of procedures for joint segmentation of the series of scans, called 4D segmentation. A main aim was improved consistency of quantitative analysis, most often solved via patient-specific atlases. Challenging open problems are contrast changes and occurance of subclasses within tissue as observed in multimodal MRI of infant development, neurodegeneration and disease. This paper proposes a new 4D segmentation framework that enforces continuous dynamic changes of tissue contrast patterns over time as observed in such data. Moreover, our model includes the capability to segment different contrast patterns within a specific tissue class, for example as seen in myelinated and unmyelinated white matter regions in early brain development. Proof of concept is shown with validation on synthetic image data and with 4D segmentation of longitudinal, multimodal pediatric MRI taken at 6, 12 and 24 months of age, but the methodology is generic w.r.t. different application domains using serial imaging.
Post-acquisition motion correction is widely performed in diffusion-weighted imaging (DWI) to guarantee voxel-wise correspondence between DWIs. Whereas this is primarily motivated to save as many scans as possible if corrupted by motion, users do not fully understand the consequences of different types of interpolation schemes on the final analysis. Nonetheless, interpolation might increase the partial volume effect while not preserving the volume of the diffusion profile, whereas excluding poor DWIs may affect the ability to resolve crossing fibers especially with small separation angles. In this paper, we investigate the effect of interpolating diffusion measurements as well as the elimination of bad directions on the reconstructed fiber orientation diffusion functions and on the estimated fiber orientations. We demonstrate such an effect on synthetic and real HARDI datasets. Our experiments demonstrate that the effect of interpolation is more significant with small fibers separation angles where the exclusion of motion-corrupted directions decreases the ability to resolve such crossing fibers.
Diffusion MRI; HARDI; motion correction; interpolation
Understanding the growth patterns of the early brain is crucial to the study of neuro-development. In the early stages of brain growth, a rapid sequence of biophysical and chemical processes take place. A crucial component of these processes, known as myelination, consists of the formation of a myelin sheath around a nerve fiber, enabling the effective transmission of neural impulses. As the brain undergoes myelination, there is a subsequent change in the contrast between gray matter and white matter as observed in MR scans. In this work, gray-white matter contrast is proposed as an effective measure of appearance which is relatively invariant to location, scanner type, and scanning conditions. To validate this, contrast is computed over various cortical regions for an adult human phantom. MR (Magnetic Resonance) images of the phantom were repeatedly generated using different scanners, and at different locations. Contrast displays less variability over changing conditions of scan compared to intensity-based measures, demonstrating that it is less dependent than intensity on external factors. Additionally, contrast is used to analyze longitudinal MR scans of the early brain, belonging to healthy controls and Down’s Syndrome (DS) patients. Kernel regression is used to model subject-specific trajectories of contrast changing with time. Trajectories of contrast changing with time, as well as time-based biomarkers extracted from contrast modeling, show large differences between groups. The preliminary applications of contrast based analysis indicate its future potential to reveal new information not covered by conventional volumetric or deformation-based analysis, particularly for distinguishing between normal and abnormal growth patterns.
Contrast; Early brain development; Structural MRI; Reliability; Contrast Change Trajectories; Time-based biomarkers
The Broad Autism Phenotype Questionnaire (BAPQ; Hurley et al, 2007) was administered to a large community-based sample of biological parents of children with autism (PCAs) and comparison parents (CPs) (n = 1692). Exploratory factor analysis and internal consistency parameters confirmed a robust three factor structure of the BAPQ, corresponding to the proposed aloof, pragmatic language and rigidity subscales. Based upon the distribution of BAP features in the general population, new normative cutoff values for BAPQ subscales were established that provide increased specificity relative to those previously reported (Hurley et al, 2007), and thus enhance the utility of the BAPQ for diagnostically classifying the BAP. These cutoffs were also used to estimate prevalence of the BAP and its three components, with rates ranging between 14 – 23% for PCAs and between 5 – 9% for CPs. Analysis of patterns of BAP characteristics within family members revealed that BAP features were more likely to co-occur in PCAs relative to CPs. Collectively, these findings extend the utility of the BAPQ and provide additional evidence that it is an efficient and reliable tool for disaggregating the heterogeneity of autism through the identification of meaningful subgroups of parents.
Autism; Broad Autism Phenotype; Assessment; Prevalence; Genetics
Elucidating the neural basis of joint attention in infancy promises to yield important insights into the development of language and social cognition, and directly informs developmental models of autism. We describe a new method for evaluating responding to joint attention performance in infancy that highlights the 9 to 10 month period as a time interval of maximal individual differences. We then demonstrate that fractional anisotropy in the right uncinate fasciculus, a white matter fiber bundle connecting the amygdala to the ventral-medial prefrontal cortex and anterior temporal pole, measured in 6 month-olds predicts individual differences in responding to joint attention at 9 months of age. The white matter microstructure of the right uncinate was not related to receptive language ability at 9 months. These findings suggest that the development of core nonverbal social communication skills in infancy is largely supported by preceding developments within right lateralized frontotemporal brain systems.
joint attention; DTI; amygdala; uncinate fasciculus; infancy; development
The degree of white matter (WM) myelination is rather inhomogeneous across the brain. White matter appears differently across the cortical lobes in MR images acquired during early postnatal development. Specifically at 1-year of age, the gray/white matter contrast of MR T1 and T2 weighted images in prefrontal and temporal lobes is reduced as compared to the rest of the brain, and thus, tissue segmentation results commonly show lower accuracy in these lobes. In this novel work, we propose the use of spatial intensity growth maps (IGM) for T1 and T2 weighted images to compensate for local appearance inhomogeneity. The IGM captures expected intensity changes from 1 to 2 years of age, as appearance homogeneity is greatly improved by the age of 24 months. The IGM was computed as the coefficient of a voxel-wise linear regression model between corresponding intensities at 1 and 2 years. The proposed IGM method revealed low regression values of 1–10% in GM and CSF regions, as well as in WM regions at maturation stage of myelination at 1 year. However, in the prefrontal and temporal lobes we observed regression values of 20–25%, indicating that the IGM appropriately captures the expected large intensity change in these lobes mainly due to myelination. The IGM is applied to cross-sectional MRI datasets of 1-year-old subjects via registration, correction and tissue segmentation of the IGM-corrected dataset. We validated our approach in a small leave-one-out study of images with known, manual ‘ground truth’ segmentations.
Myelination; Expectation Maximization algorithm; Tissue segmentation; Intensity growth map; and Partial volume estimation
Longitudinal MR imaging during early brain development provides important information about growth patterns and the development of neurological disorders. We propose a new framework for studying brain growth patterns within and across populations based on MRI contrast changes, measured at each time point of interest and at each voxel. Our method uses regression in the LogOdds space and an information-theoretic measure of distance between distributions to capture contrast in a manner that is robust to imaging parameters and without requiring intensity normalization. We apply our method to a clinical neuroimaging study on early brain development in autism, where we obtain a 4D spatiotemporal model of contrast changes in multimodal structural MRI.
Contrast; longitudinal MRI; regression; Kullback-Leibler
Nonverbal motion cues (a clenched fist) convey essential information about the intentions of the actor. Individuals with anorexia nervosa (AN) have demonstrated impairment in deciphering intention from facial affective cues but it is unknown whether such deficits extend to deciphering affect from body motion cues.
We examined the capacities of adults with AN (AN; n=21) or those weight restored for >= 12 months (WR; n=20) to perceive affect in biological motion cues relative to healthy controls (HC; n=23).
Overall, individuals with AN evidenced greater deficit in discriminating affect from biological motion cues than WR or HC. Follow-up analyses showed that individuals with AN differed especially across two of the five conditions—deviating most from normative data when discriminating sadness and more consistently discriminating anger relative to WR or HC.
Implications of these findings are discussed in relation to some puzzling interpersonal features of AN.
anorexia nervosa; eating disorders; social cognition; social perception; motion perception
We thank all of our reviewers who have contributed to the journal in volume 5 (2013). High quality and timely reviews are critical to the overall quality of the journal. We are committed to providing a unique and important outlet for scholarship regarding neurodevelopmental disorders and are indebted to the outstanding reviewers who have contributed their time over the last year in helping us to reach this goal.
Autism and the fragile X syndrome (FXS) are related to each other genetically and symptomatically. A cardinal biological feature of both disorders is abnormalities of cerebral cortical brain volumes. We have previously shown that the monoamine oxidase A (MAOA) promoter polymorphism is associated with cerebral cortical volumes in children with autism, and we now sought to determine whether the association was also present in children with FXS.
Participants included 47 2-year-old Caucasian boys with FXS, some of whom also had autism, as well as 34 2-year-old boys with idiopathic autism analyzed in a previous study. The MAOA promoter polymorphism was genotyped and tested for relationships with gray and white matter volumes of the cerebral cortical lobes and cerebro-spinal fluid volume of the lateral ventricles.
MAOA genotype effects in FXS children were the same as those previously observed in idiopathic autism: the low activity MAOA promoter polymorphism allele was associated with increased gray and white matter volumes in all cerebral lobes. The effect was most pronounced in frontal lobe gray matter and all three white matter regions: frontal gray, F = 4.39, P = 0.04; frontal white, F = 5.71, P = 0.02; temporal white, F = 4.73, P = 0.04; parieto-occipital white, F = 5.00, P = 0.03. Analysis of combined FXS and idiopathic autism samples produced P values for these regions <0.01 and effect sizes of approximately 0.10.
The MAOA promoter polymorphism is similarly associated with brain structure volumes in both idiopathic autism and FXS. These data illuminate a number of important aspects of autism and FXS heritability: a genetic effect on a core biological trait of illness, the specificity/generalizability of the genetic effect, and the utility of examining individual genetic effects on the background of a single gene disorder such as FXS.
Autism; Fragile X syndrome; Brain structure; Monoamine oxidase A; Polymorphism
Traditional longitudinal analysis begins by extracting desired clinical measurements, such as volume or head circumference, from discrete imaging data. Typically, the continuous evolution of a scalar measurement is estimated by choosing a 1D regression model, such as kernel regression or fitting a polynomial of fixed degree. This type of analysis not only leads to separate models for each measurement, but there is no clear anatomical or biological interpretation to aid in the selection of the appropriate paradigm. In this paper, we propose a consistent framework for the analysis of longitudinal data by estimating the continuous evolution of shape over time as twice differentiable flows of deformations. In contrast to 1D regression models, one model is chosen to realistically capture the growth of anatomical structures. From the continuous evolution of shape, we can simply extract any clinical measurements of interest. We demonstrate on real anatomical surfaces that volume extracted from a continuous shape evolution is consistent with a 1D regression performed on the discrete measurements. We further show how the visualization of shape progression can aid in the search for significant measurements. Finally, we present an example on a shape complex of the brain (left hemisphere, right hemisphere, cerebellum) that demonstrates a potential clinical application for our framework.
The authors sought to determine whether specific patterns of oculomotor functioning and visual orienting characterize 7-month-old infants who later meet criteria for an autism spectrum disorder (ASD) and to identify the neural correlates of these behaviors.
Data were collected from 97 infants, of whom 16 were high-familial-risk infants later classified as having an ASD, 40 were high-familial-risk infants who did not later meet ASD criteria (high-risk negative), and 41 were low-risk infants. All infants underwent an eye-tracking task at a mean age of 7 months and a clinical assessment at a mean age of 25 months. Diffusion-weighted imaging data were acquired for 84 of the infants at 7 months. Primary outcome measures included average saccadic reaction time in a visually guided saccade procedure and radial diffusivity (an index of white matter organization) in fiber tracts that included corticospinal pathways and the splenium and genu of the corpus callosum.
Visual orienting latencies were longer in 7-month-old infants who expressed ASD symptoms at 25 months compared with both high-risk negative infants and low-risk infants. Visual orienting latencies were uniquely associated with the microstructural organization of the splenium of the corpus callosum in low-risk infants, but this association was not apparent in infants later classified as having an ASD.
Flexibly and efficiently orienting to salient information in the environment is critical for subsequent cognitive and social-cognitive development. Atypical visual orienting may represent an early prodromal feature of an ASD, and abnormal functional specialization of posterior cortical circuits directly informs a novel model of ASD pathogenesis.
How does the behavioral expression of autism in fragile X syndrome (FXS+Aut) compare to idiopathic autism (iAut)? While social impairments and restricted, repetitive behaviors (RRBs) are common to both variants of autism, closer examination of these symptom domains may reveal meaningful similarities and differences. To this end, we profiled the specific behaviors comprising the social and repetitive behavioral domains in young children with FXS+Aut and iAut.
Twenty-three males ages 3–5 years with FXS + Aut were age-matched with a group of 38 boys with iAut. Repetitive behavior was assessed using the RBS-R. Social behavior was evaluated using Autism Diagnostic Observation Schedule (ADOS) social item severity scores.
Rates of stereotypy, self-injury, and sameness behaviors did not differ between groups, whereas compulsive and ritual behavior scores were significantly lower for individuals with FXS + Aut compared to iAut. Those with FXS + Aut scored significantly lower (less severe) than the iAut group on five ADOS measures of social behavior: Gaze Integration, Quality of Social Overtures, Social Smile, Facial Expressions, and Response to Joint Attention.
The behavioral phenotype of FXS + Aut and iAut are most similar with respect to lower-order (motoric) RRBs and social approach, but differ in more complex forms of RRB and some social response behaviors. These findings highlight the phenotypic heterogeneity of autism overall and its unique presentation in an etiologically distinct condition.
fragile X syndrome; autism; repetitive behavior; behavioral phenotype
To examine patterns of early brain growth in young children with fragile X syndrome (FXS) compared to a comparison group (controls) and a group with idiopathic autism.
The study included 53 boys between 18–42 months of age with FXS, 68 boys with idiopathic autism (ASD), and a comparison group of 50 typically-developing and developmentally-delayed controls. We examined structural brain volumes using magnetic resonance imaging (MRI) across two timepoints between ages 2–3 and 4–5 years and examined total brain volumes and regional (lobar) tissue volumes. Additionally, we studied a selected group of subcortical structures implicated in the behavioral features of FXS (e.g., basal ganglia, hippocampus, amygdala).
Children with FXS had greater global brain volumes compared to controls, but were not different than children with idiopathic autism, and the rate of brain growth between ages 2 and 5 paralleled that seen in controls. In contrast to the children with idiopathic autism who had generalized cortical lobe enlargement, the children with FXS showed a specific enlargement in temporal lobe white matter, cerebellar gray matter, and caudate nucleus, but significantly smaller amygdala.
This structural longitudinal MRI study of preschoolers with FXS observed generalized brain overgrowth in FXS compared to controls, evident at age 2 and maintained across ages 4–5. We also find different patterns of brain growth that distinguishes boys with FXS from children with idiopathic autism.
fragile X syndrome; autism; children; brain MRI; brain volume