Longitudinal development of thalamic and internal capsule microstructure in autism spectrum disorder

An Investigation of Age-related Neuropathophysiology in Autism Spectrum Disorder Using Fixel-based Analysis of Corpus Callosum White Matter Micro- and Macrostructure

Fixel-based analysis was used to probe age-related changes in white matter micro- and macrostructure of the corpus callosum between participants with (N = 54) and without (N = 50) autism spectrum disorder (ASD). Data were obtained from the Autism Brain Imaging Data Exchange-II (ABIDE-II). Compared to age-matched controls, young adolescents with ASD (11.19 ± 7.54 years) showed reduced macroscopic fiber cross-section (logFC) and combined fiber-density and cross-section (FDC). Reduced fiber-density (FD) and FDC was noted in a marginally older (13.87 ± 3.15 years) ASD cohort. Among the oldest ASD cohort (17.07 ± 3.56 years), a non-significant trend indicative of reduced FD was noted. White matter aberration appears greatest and most widespread among younger ASD cohorts. This supports the suggestion that some early neuropathophysiological indicators in ASD may dissipate with age.

Autistic-like behaviour and changes in thalamic cell numbers a rat model of valproic acid-induced autism; A behavioural and stereological study

The contribution of the thalamus to the development and behavioural changes in autism spectrum disorders (ASD), a neurodevelopmental syndrome, remains unclear. The aim of this study was to determine the changes in thalamic volume and cell number in the valproic acid (VPA)-induced ASD model using stereological methods and to clarify the relationship between thalamus and ASD-like behaviour. Ten pregnant rats were administered a single dose (600 mg/kg) of VPA intraperitoneally on G12.5 (VPA group), while five pregnant rats were injected with 5 ml saline (control group). Behavioural tests were performed to determine appropriate subjects and ASD-like behaviours. At P55, the brains of the subjects were removed. The sagittal sections were stained with cresyl violet and toluidine blue. The thalamic and hemispheric volumes with their ratios, the total number of thalamic cells, neurons and non-neuronal cells were calculated using stereological methods. Data were compared using a t-test and a Pearson correlation analysis was performed to examine the relationship between behaviour and stereological outcomes. VPA-treated rats had lower sociability and sociability indexes. There was no difference in social novelty preference and anxiety. The VPA group had larger hemispheric volume, lower thalamic volume, and fewer neurons. The highest percentage decrease was in non-neuronal cells. There was a moderate positive correlation between the number of non-neuronal cells and sociability, thalamic volume and the number of neurons as well as the time spent in the light box. The correlation between behaviour and stereological data suggests that the thalamus is associated with ASD-like behaviour.

Quantitative Relaxometry Assessment of Brain Microstructural Abnormality of Preschool Children With Autism Spectrum Disorder With Synthetic Magnetic Resonance Imaging

OBJECTIVE

This study aimed to perform an assessment of brain microstructure in children with autism aged 2 to 5 years using relaxation times acquired by synthetic magnetic resonance imaging.

MATERIALS AND METHODS

Thirty-four children with autism spectrum disorder (ASD) (ASD group) and 17 children with global developmental delay (GDD) (GDD group) were enrolled, and synthetic magnetic resonance imaging was performed to obtain T1 and T2 relaxation times. The differences in brain relaxation times between the 2 groups of children were compared, and the correlation between significantly changed T1/T2 and clinical neuropsychological scores in the ASD group was analyzed.

RESULTS

Compared with the GDD group, shortened T1 relaxation times in the ASD group were distributed in the genu of corpus callosum (GCC) ( P = 0.003), splenium of corpus callosum ( P = 0.002), and right thalamus (TH) ( P = 0.014), whereas shortened T2 relaxation times in the ASD group were distributed in GCC ( P = 0.011), left parietal white matter ( P = 0.035), and bilateral TH (right, P = 0.014; left, P = 0.016). In the ASD group, the T2 of the left parietal white matter is positively correlated with gross motor (developmental quotient [DQ] 2) and personal-social behavior (DQ5), respectively ( r = 0.377, P = 0.028; r = 0.392, P = 0.022); the T2 of the GCC was positively correlated with DQ5 ( r = 0.404, P = 0.018); and the T2 of the left TH is positively correlated with DQ2 and DQ5, respectively ( r = 0.433, P = 0.009; r = 0.377, P = 0.028). All significantly changed relaxation values were not significantly correlated with Childhood Autism Rating Scale scores.

CONCLUSIONS

The shortened relaxometry times in the brain of children with ASD may be associated with the increased myelin content and decreased water content in the brain of children with ASD in comparison with GDD, contributing the understanding of the pathophysiology of ASD. Therefore, the T1 and T2 relaxometry may be used as promising imaging markers for ASD diagnosis.

Role of Artificial Intelligence for Autism Diagnosis Using DTI and fMRI: A Survey

Autism spectrum disorder (ASD) is a wide range of diseases characterized by difficulties with social skills, repetitive activities, speech, and nonverbal communication. The Centers for Disease Control (CDC) estimates that 1 in 44 American children currently suffer from ASD. The current gold standard for ASD diagnosis is based on behavior observational tests by clinicians, which suffer from being subjective and time-consuming and afford only late detection (a child must have a mental age of at least two to apply for an observation report). Alternatively, brain imaging-more specifically, magnetic resonance imaging (MRI)-has proven its ability to assist in fast, objective, and early ASD diagnosis and detection. With the recent advances in artificial intelligence (AI) and machine learning (ML) techniques, sufficient tools have been developed for both automated ASD diagnosis and early detection. More recently, the development of deep learning (DL), a young subfield of AI based on artificial neural networks (ANNs), has successfully enabled the processing of brain MRI data with improved ASD diagnostic abilities. This survey focuses on the role of AI in autism diagnostics and detection based on two basic MRI modalities: diffusion tensor imaging (DTI) and functional MRI (fMRI). In addition, the survey outlines the basic findings of DTI and fMRI in autism. Furthermore, recent techniques for ASD detection using DTI and fMRI are summarized and discussed. Finally, emerging tendencies are described. The results of this study show how useful AI is for early, subjective ASD detection and diagnosis. More AI solutions that have the potential to be used in healthcare settings will be introduced in the future.

Distinct and shared white matter abnormalities when ADHD is comorbid with ASD: A preliminary diffusion tensor imaging study

Attention deficit/hyperactivity disorder (ADHD), a common neurodevelopmental disorder, is the most frequent comorbid condition seen in children with autism spectrum disorder (ASD). This high comorbidity between ADHD and ASD worsens symptom manifestations and complicates disease treatment and prognosis. It remains unclear whether individuals suffering with both ADHD and ASD, compared to individuals with ADHD only, share overlapping neural correlates associated with ADHD neuropathology, or exhibit a distinct neuropathological profile. Answering this question is critical to the understanding of treatment outcomes for the challenging comorbid ADHD symptoms. To identify the shared and the differentiated neural correlates of the comorbidity mechanisms of ADHD with ASD, we use diffusion tensor imaging (DTI) to characterize white-matter microstructure integrity in youth diagnosed with ADHD+ASD and youth with ADHD-only (excluding both the diagnosis and symptoms of ASD) compared with a healthy control group. Results show that the ADHD-only cohort exhibits impaired microstructural integrity (lower fractional anisotropy, FA) in the callosal-cingulum (CC-CG) tracts compared to the control cohort. The ADHD+ASD comorbid cohort shows impaired FA in an overlapping region within the CC-CG tracts and, additionally, shows impaired FA in the frontolimbic tracts including the uncinate fasciculus and anterior thalamic radiation. Across all participants, FA in the CC-CG showed a significantly negative relationship with the degree of ADHD symptom severity. Findings of this study suggest a specific role of CC-CG underlying ADHD neuropathology and symptom manifestations, and when comorbid with ASD a shared ADHD profile with a shift toward an anterior-brain, frontal impact. Results of this study may facilitate future targeted therapeutics and assist in diagnostic precision for individuals suffering with differing levels of comorbid ADHD with ASD, and ultimately contribute to improve prognostication and outcomes for these two highly prevalent and comorbid neurodevelopmental disorders.

Technologies to support the diagnosis and/or treatment of neurodevelopmental disorders: A systematic review

In recent years, there has been a great interest in utilizing technology in mental health research. The rapid technological development has encouraged researchers to apply technology as a part of a diagnostic process or treatment of Neurodevelopmental Disorders (NDDs). With the large number of studies being published comes an urgent need to inform clinicians and researchers about the latest advances in this field. Here, we methodically explore and summarize findings from studies published between August 2019 and February 2022. A search strategy led to the identification of 4108 records from PubMed and APA PsycInfo databases. 221 quantitative studies were included, covering a wide range of technologies used for diagnosis and/or treatment of NDDs, with the biggest focus on Autism Spectrum Disorder (ASD). The most popular technologies included machine learning, functional magnetic resonance imaging, electroencephalogram, magnetic resonance imaging, and neurofeedback. The results of the review indicate that technology-based diagnosis and intervention for NDD population is promising. However, given a high risk of bias of many studies, more high-quality research is needed.

Spatiotemporal Developmental Gradient of Thalamic Morphology, Microstructure, and Connectivity fromthe Third Trimester to Early Infancy

Thalamus is a critical component of the limbic system that is extensively involved in both basic and high-order brain functions. However, how the thalamic structure and function develops at macroscopic and microscopic scales during the perinatal period development is not yet well characterized. Here, we used multishell high-angular resolution diffusion MRI of 144 preterm-born and full-term infants in both sexes scanned at 32-44 postmenstrual weeks (PMWs) from the Developing Human Connectome Project database to investigate the thalamic development in morphology, microstructure, associated connectivity, and subnucleus division. We found evident anatomic expansion and linear increases of fiber integrity in the lateral side of thalamus compared with the medial part. The tractography results indicated that thalamic connection to the frontal cortex developed later than the other thalamocortical connections (parieto-occipital, motor, somatosensory, and temporal). Using a connectivity-based segmentation strategy, we revealed that functional partitions of thalamic subdivisions were formed at 32 PMWs or earlier, and the partition developed toward the adult pattern in a lateral-to-medial pattern. Collectively, these findings revealed faster development of the lateral thalamus than the central part as well as a posterior-to-anterior developmental gradient of thalamocortical connectivity from the third trimester to early infancy.SIGNIFICANCE STATEMENT This is the first study that characterizes the spatiotemporal developmental pattern of thalamus during the third trimester to early infancy. We found that thalamus develops in a lateral-to-medial pattern for both thalamic microstructures and subdivisions; and thalamocortical connectivity develops in a posterior-to-anterior gradient that thalamofrontal connectivity appears later than the other thalamocortical connections. These findings may enrich our understanding of the developmental principles of thalamus and provide references for the atypical brain growth in neurodevelopmental disorders.

Longitudinal Stability of Intellectual Functioning in Autism Spectrum Disorder: From Age 3 Through Mid-adulthood

Intelligence (IQ) scores are used in educational and vocational planning for individuals with autism spectrum disorder (ASD) yet little is known about the stability of IQ throughout development. We examined longitudinal age-related IQ stability in 119 individuals with ASD (3-36 years of age at first visit) and 128 typically developing controls. Intelligence measures were collected over a 20-year period. In ASD, Full Scale (FSIQ) and Verbal (VIQ) Intelligence started lower in childhood and increased at a greater rate with age relative to the control group. By early adulthood, VIQ and working memory stabilized, whereas nonverbal and perceptual scores continued to change. Our results suggest that in individuals with ASD, IQ estimates may be dynamic in childhood and young adulthood.

A recurrent SHANK1 mutation implicated in autism spectrum disorder causes autistic-like core behaviors in mice via downregulation of mGluR1-IP3R1-calcium signaling

The genetic etiology and underlying mechanism of autism spectrum disorder (ASD) remain elusive. SHANK family genes (SHANK1/2/3) are well known ASD-related genes. However, little is known about how SHANK missense mutations contribute to ASD. Here, we aimed to clarify the molecular mechanism of and the multilevel neuropathological features induced by Shank1 mutations in knock-in (KI) mice. In this study, by sequencing the SHANK1 gene in a cohort of 615 ASD patients and 503 controls, we identified an ASD-specific recurrent missense mutation, c.2621 G > A (p.R874H). This mutation demonstrated strong pathogenic potential in in vitro experiments, and we generated the corresponding Shank1 R882H-KI mice. Shank1 R882H-KI mice displayed core symptoms of ASD, namely, social disability and repetitive behaviors, without confounding comorbidities of abnormal motor function and heightened anxiety. Brain structural changes in the frontal cortex, hippocampus and cerebellar cortex were observed in Shank1 R882H-KI mice via structural magnetic resonance imaging. These key brain regions also showed severe and consistent downregulation of mGluR1-IP3R1-calcium signaling, which subsequently affected the release of intracellular calcium. Corresponding cellular structural and functional changes were present in Shank1 R882H-KI mice, including decreased spine size, reduced spine density, abnormal morphology of postsynaptic densities, and impaired hippocampal long-term potentiation and basal excitatory transmission. These findings demonstrate the causative role of SHANK1 in ASD and elucidate the underlying biological mechanism of core symptoms of ASD. We also provide a reliable model of ASD with core symptoms for future studies, such as biomarker identification and therapeutic intervention studies.

The Role of Diffusion Tensor MR Imaging (DTI) of the Brain in Diagnosing Autism Spectrum Disorder: Promising Results

Autism spectrum disorder (ASD) is a combination of developmental anomalies that causes social and behavioral impairments, affecting around 2% of US children. Common symptoms include difficulties in communications, interactions, and behavioral disabilities. The onset of symptoms can start in early childhood, yet repeated visits to a pediatric specialist are needed before reaching a diagnosis. Still, this diagnosis is usually subjective, and scores can vary from one specialist to another. Previous literature suggests differences in brain development, environmental, and/or genetic factors play a role in developing autism, yet scientists still do not know exactly the pathology of this disorder. Currently, the gold standard diagnosis of ASD is a set of diagnostic evaluations, such as the Autism Diagnostic Observation Schedule (ADOS) or Autism Diagnostic Interview-Revised (ADI-R) report. These gold standard diagnostic instruments are an intensive, lengthy, and subjective process that involves a set of behavioral and communications tests and clinical history information conducted by a team of qualified clinicians. Emerging advancements in neuroimaging and machine learning techniques can provide a fast and objective alternative to conventional repetitive observational assessments. This paper provides a thorough study of implementing feature engineering tools to find discriminant insights from brain imaging of white matter connectivity and using a machine learning framework for an accurate classification of autistic individuals. This work highlights important findings of impacted brain areas that contribute to an autism diagnosis and presents promising accuracy results. We verified our proposed framework on a large publicly available DTI dataset of 225 subjects from the Autism Brain Imaging Data Exchange-II (ABIDE-II) initiative, achieving a high global balanced accuracy over the 5 sites of up to 99% with 5-fold cross validation. The data used was slightly unbalanced, including 125 autistic subjects and 100 typically developed (TD) ones. The achieved balanced accuracy of the proposed technique is the highest in the literature, which elucidates the importance of feature engineering steps involved in extracting useful knowledge and the promising potentials of adopting neuroimaging for the diagnosis of autism.

Neural Mechanisms of Visual Motion Anomalies in Autism: A Two-Decade Update and Novel Aetiology

The 21st century has seen dramatic changes in our understanding of the visual physio-perceptual anomalies of autism and also in the structure and development of the primate visual system. This review covers the past 20 years of research into motion perceptual/dorsal stream anomalies in autism, as well as new understanding of the development of primate vision. The convergence of this literature allows a novel developmental hypothesis to explain the physiological and perceptual differences of the broad autistic spectrum. Central to these observations is the development of motion areas MT+, the seat of the dorsal cortical stream, central area of pre-attentional processing as well as being an anchor of binocular vision for 3D action. Such development normally occurs via a transfer of thalamic drive from the inferior pulvinar → MT to the anatomically stronger but later-developing LGN → V1 → MT connection. We propose that autistic variation arises from a slowing in the normal developmental attenuation of the pulvinar → MT pathway. We suggest that this is caused by a hyperactive amygdala → thalamic reticular nucleus circuit increasing activity in the PIm → MT via response gain modulation of the pulvinar and hence altering synaptic competition in area MT. We explore the probable timing of transfer in dominance of human MT from pulvinar to LGN/V1 driving circuitry and discuss the implications of the main hypothesis.

The influence of NRXN1 on systemizing and the brain structure in healthy adults

Certain behavioral characteristics of autism spectrum disorder can be found in otherwise healthy people. Individuals with difficulties in social adaptation may have subclinical autistic traits; however, effective biomarkers of these traits have not yet been established. There is a dire need for objective indices of these traits that combine behavior, brain images, and genetic information. In this study, we examined the association among a single nucleotide polymorphism of NRXN1 (rs858932; C/G), autistic traits, and brain structure in 311 healthy adults. We found that carriers of minor alleles (carriers of the G-allele) had significantly higher systemizing scores than major-allele (C-allele) homozygotes. Furthermore, the regional white matter volume in the right anterior limb of the internal capsule was significantly greater in carriers of the G-allele than in C-allele homozygotes. To the best of our knowledge, this is the first report of NRXN1 rs858932 being involved in systemizing and the brain structure of healthy adults. Our findings provide insight into the effects of genetics on autistic traits and their respective neural substrates.

Sex/gender differences in the human autistic brains: A systematic review of 20 years of neuroimaging research

Our current understanding of autism is largely based on clinical experiences and research involving male individuals given the male-predominance in prevalence and the under-inclusion of female individuals due to small samples, co-occurring conditions, or simply being missed for diagnosis. There is a significantly biased 'male lens' in this field with autistic females insufficiently understood. We therefore conducted a systematic review to examine how sex and gender modulate brain structure and function in autistic individuals. Findings from the past 20 years are yet to converge on specific brain regions/networks with consistent sex/gender-modulating effects. Despite at least three well-powered studies identifying specific patterns of significant sex/gender-modulation of autism-control differences, many other studies are likely underpowered, suggesting a critical need for future investigation into sex/gender-based heterogeneity with better-powered designs. Future research should also formally investigate the effects of gender, beyond biological sex, which is mostly absent in the current literature. Understanding the roles of sex and gender in the development of autism is an imperative step to extend beyond the 'male lens' in this field.

Diagnostic Value of Diffusion Tensor Imaging for Infants' Brain Development Retardation Caused by Pre-Eclampsia

Objective

Pre-eclampsia (PE) can cause brain development delay in infants. This work aims to characterize the pattern differences of brain white matter development in premature infants under PE conditions and those without.

Methods

Eighty preterm infants delivered by women with PE were selected as the PE group, and ninety-six preterm infants of the same period born to women without high-risk perinatal factors were used as control. All infants underwent diffusion tensor imaging (DTI) examination. The fractional anisotropy (FA) was measured in five regions of interests (ROIs), including posterior limbs of internal capsule (PLIC), splenium of the corpus callosum (SCC), superior frontal gyrus (SFG), superior parietal lobule (SPL), and superior occipital gyrus (SOG). The relationship between the FA values and postmenstrual age (PMA) was analyzed.

Results

After adjusting for the birth weight and gestational ages, in the SCC and PLIC, the PMA and FA values showed a low-to-medium intensity positive correlation in the control group (r = 0.30, p=0.003; r = 0.53, p < 0.0001), while no positive relevance was detected in the PE group (r = 0.08, p=0.47; r = 0.19, p < 0.08). In the PE and control groups, in the SPL and SOG, the PMA and FA values showed a near-consistent positive correlation (r = 0.57, r = 0.55 vs. r = 0.31, r = 0.55; all p < 0.05). In the control group, in SFG, the PMA and FA values had a medium intensity positive correlation (r = 0.47, p < 0.0001), but there was no statistical difference in correlation in PE (r = 0.10, p=0.39).

Conclusion

PE may cause lagging brain development in the SCC, PLIC, and SFG during infancy. DTI may be an effective and sensitive detection tool.

Supplementary and Premotor Aspects of the Corticospinal Tract Show Links with Restricted and Repetitive Behaviors in Middle-Aged Adults with Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) show motor impairment into adulthood and risk decline during aging, but little is known about brain changes in aging adults with ASD. Few studies of ASD have directly examined the corticospinal tract (CST)-the major descending pathway in the brain responsible for voluntary motor behavior-outside its primary motor (M1) connections. In 26 middle-aged adults with ASD and 26 age-matched typical comparison participants, we used diffusion imaging to examine the microstructure and volume of CST projections from M1, dorsal premotor (PMd), supplementary motor area (SMA), and primary somatosensory (S1) cortices with respect to age. We also examined relationships between each CST sub-tract (-cst), motor skills, and autism symptoms. We detected no significant group or age-related differences in tracts extending from M1 or other areas. However, sub-tracts of the CST extending from secondary (but not primary) motor areas were associated with core autism traits. Increased microstructural integrity of left PMd-cst and SMA-cst were associated with less-severe restricted and repetitive behaviors (RRB) in the ASD group. These findings suggest that secondary motor cortical areas, known to be involved in selecting motor programs, may be implicated in cognitive motor processes underlying RRB in ASD.

Neurobiological and behavioural outcomes of biofeedback-based training in autism: a randomized controlled trial

The human brain has demonstrated the power to structurally change as a result of movement-based interventions. However, it is unclear whether these structural brain changes differ in autistic individuals compared to non-autistic individuals. The purpose of the present study was to pilot a randomized controlled trial to investigate brain, balance, autism symptom severity and daily living skill changes that result from a biofeedback-based balance intervention in autistic adolescents (13-17 years old). Thirty-four autistic participants and 28 age-matched non-autistic participants underwent diagnostic testing and pre-training assessment (neuroimaging, cognitive, autism symptom severity and motor assessments) and were then randomly assigned to 6 weeks of a balance-training intervention or a sedentary-control condition. After the 6 weeks, neuroimaging, symptom severity and motor assessments were repeated. Results found that both the autistic and non-autistic participants demonstrated similar and significant increases in balance times with training. Furthermore, individuals in the balance-training condition showed significantly greater improvements in postural sway and reductions in autism symptom severity compared to individuals in the control condition. Daily living scores did not change with training, nor did we observe hypothesized changes to the microstructural properties of the corticospinal tract. However, follow-up voxel-based analyses found a wide range of balance-related structures that showed changes across the brain. Many of these brain changes were specific to the autistic participants compared to the non-autistic participants, suggesting distinct structural neuroplasticity in response to balance training in autistic participants. Altogether, these findings suggest that biofeedback-based balance training may target postural stability challenges, reduce core autism symptoms and influence neurobiological change. Future research is encouraged to examine the superior cerebellar peduncle in response to balance training and symptom severity changes in autistic individuals, as the current study produced overlapping findings in this brain region.

White Matter Structural and Network Topological Changes Underlying the Behavioral Phenotype of MECP2 Mutant Monkeys

To explore the brain structural basis underlying the behavioral abnormalities associated with Rett syndrome (RTT), we carried out detailed longitudinal noninvasive magnetic resonance imaging analyses of RTT monkey models created by gene-editing, from weaning, through adolescence, till sexual maturation. Here, we report abnormal developmental dynamics of brain white matter (WM) microstructures and network topological organizations via diffusion tensor imaging. Specifically, disrupted WM microstructural integrity was observed at 9 months, but recovered thereafter, whereas WM network topological properties showed persistent abnormal dynamics from 9 to 37 months. Changes in the WM microstructure and WM network topology were correlated well with RTT-associated behavioral abnormalities including sleep latency, environmental exploration, and conflict encounters. Deleterious and protracted early WM myelination process likely lead to abnormal synaptic pruning, resulting in poor functional segregations. Together, this study provides initial evidence for changes in WM microstructure and network topological organization, which may underlie the neuro-patho-etilogy of RTT.

A Longitudinal Study of White Matter Development in Relation to Changes in Autism Severity Across Early Childhood

BACKGROUND

Cross-sectional diffusion-weighted magnetic resonance imaging studies suggest that young autistic children have alterations in white matter structure that differ from older autistic individuals. However, it is unclear whether these differences result from atypical neurodevelopment or sampling differences between young and older cohorts. Furthermore, the relationship between altered white matter development and longitudinal changes in autism symptoms is unknown.

METHODS

Using longitudinal diffusion-weighted magnetic resonance imaging acquired over 2 to 3 time points between the ages of approximately 2.5 to 7.0 years in 125 autistic children and 69 typically developing control participants, we directly tested the hypothesis that autistic individuals have atypical white matter development across childhood. Additionally, we sought to determine whether changes in white matter diffusion parameters were associated with longitudinal changes in autism severity.

RESULTS

Autistic children were found to have slower development of fractional anisotropy in the cingulum bundle, superior longitudinal fasciculus, internal capsule, and splenium of the corpus callosum. Furthermore, in the sagittal stratum, autistic individuals who increased in autism severity over time had a slower developmental trajectory of fractional anisotropy compared with individuals whose autism decreased in severity. In the uncinate fasciculus, autistic individuals who decreased in autism symptom severity also had greater increases in fractional anisotropy with age.

CONCLUSIONS

These longitudinal findings indicate that previously reported differences in diffusion-weighted magnetic resonance imaging measures between younger and older autism cohorts are attributable to an atypical developmental trajectory of white matter. Differences in white matter development between individuals whose autism severity increased, remained stable, or decreased suggest that these functional differences are associated with fiber development in the autistic brain.

Age-related differences in white matter diffusion measures in autism spectrum condition

BACKGROUND

Autism spectrum condition (ASC) is accompanied by developmental differences in brain anatomy and connectivity. White matter differences in ASC have been widely studied with diffusion imaging but results are heterogeneous and vary across the age range of study participants and varying methodological approaches. To characterize the neurodevelopmental trajectory of white matter maturation, it is necessary to examine a broad age range of individuals on the autism spectrum and typically developing controls, and investigate age × group interactions.

METHODS

Here, we employed a spatially unbiased tract-based spatial statistics (TBSS) approach to examine age-related differences in white matter connectivity in a sample of 41 individuals with ASC, and 41 matched controls between 7-17 years of age.

RESULTS

We found significant age-related differences between the ASC and control group in widespread brain regions. This included age-related differences in the uncinate fasciculus, corticospinal tract, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, anterior thalamic radiation, superior longitudinal fasciculus and forceps major. Measures of fractional anisotropy (FA) were significantly positively associated with age in both groups. However, this relationship was significantly stronger in the ASC group relative to controls. Measures of radial diffusivity (RD) were significantly negatively associated with age in both groups, but this relationship was significantly stronger in the ASC group relative to controls.

LIMITATIONS

The generalisability of our findings is limited by the restriction of the sample to right-handed males with an IQ > 70. Furthermore, a longitudinal design would be required to fully investigate maturational processes across this age group.

CONCLUSIONS

Taken together, our findings suggest that autistic males have an altered trajectory of white matter maturation relative to controls. Future longitudinal analyses are required to further characterize the extent and time course of these differences.

Mindfulness-Based Stress Reduction-related changes in posterior cingulate resting brain connectivity

Mindfulness meditation training has been shown to increase resting-state functional connectivity between nodes of the frontoparietal executive control network (dorsolateral prefrontal cortex [DLPFC]) and the default mode network (posterior cingulate cortex [PCC]). We investigated whether these effects generalized to a Mindfulness-Based Stress Reduction (MBSR) course and tested for structural and behaviorally relevant consequences of change in connectivity. Healthy, meditation-naïve adults were randomized to either MBSR (N = 48), an active (N = 47) or waitlist (N = 45) control group. Participants completed behavioral testing, resting-state fMRI scans and diffusion tensor scans at pre-randomization (T1), post-intervention (T2) and ~5.5 months later (T3). We found increased T2–T1 PCC–DLPFC resting connectivity for MBSR relative to control groups. Although these effects did not persist through long-term follow-up (T3–T1), MBSR participants showed a significantly stronger relationship between days of practice (T1 to T3) and increased PCC–DLPFC resting connectivity than participants in the active control group. Increased PCC–DLPFC resting connectivity in MBSR participants was associated with increased microstructural connectivity of a white matter tract connecting these regions and increased self-reported attention. These data show that MBSR increases PCC–DLPFC resting connectivity, which is related to increased practice time, attention and structural connectivity.

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder

Background

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition. The degree to which the brain development in ASD deviates from typical brain development, and how this deviation relates to observed behavioral outcomes at the individual level are not well-studied. We hypothesize that the degree of deviation from typical brain development of an individual with ASD would relate to observed symptom severity.

Methods

The developmental changes in anatomical (cortical thickness, surface area, and volume) and diffusion metrics (fractional anisotropy and apparent diffusion coefficient) were compared between a sample of ASD (n = 247) and typically developing children (TDC) (n = 220) aged 6-25. Machine learning was used to predict age (brain age) from these metrics in the TDC sample, to define a normative model of brain development. This model was then used to compute brain age in the ASD sample. The difference between chronological age and brain age was considered a developmental deviation index (DDI), which was then correlated with ASD symptom severity.

Results

Machine learning model trained on all five metrics accurately predicted age in the TDC (r = 0.88) and the ASD (r = 0.85) samples, with dominant contributions to the model from the diffusion metrics. Within the ASD group, the DDI derived from fractional anisotropy was correlated with ASD symptom severity (r = - 0.2), such that individuals with the most advanced brain age showing the lowest severity, and individuals with the most delayed brain age showing the highest severity.

Limitations

This work investigated only linear relationships between five specific brain metrics and only one measure of ASD symptom severity in a limited age range. Reported effect sizes are moderate. Further work is needed to investigate developmental differences in other age ranges, other aspects of behavior, other neurobiological measures, and in an independent sample before results can be clinically applicable.

Conclusions

Findings demonstrate that the degree of deviation from typical brain development relates to ASD symptom severity, partially accounting for the observed heterogeneity in ASD. Our approach enables characterization of each individual with reference to normative brain development and identification of distinct developmental subtypes, facilitating a better understanding of developmental heterogeneity in ASD.

Children with Autism Spectrum Disorder Demonstrate Regionally Specific Altered Resting-State Phase-Amplitude Coupling

Studies suggest that individuals with autism spectrum disorder (ASD) exhibit altered electrophysiological alpha to gamma phase-amplitude coupling (PAC). Preliminary reports with small samples report conflicting findings regarding the directionality of the alpha to gamma PAC alterations in ASD. The present study examined resting-state activity throughout the brain in a relatively large sample of 119 children with ASD and 47 typically developing children. Children with ASD demonstrated regionally specific abnormalities in alpha to low-gamma PAC, with increased alpha to low-gamma PAC for a central midline source and decreased PAC at lateral sources. Group differences in local gamma-band power did not account for the regional group differences in alpha to low-gamma PAC. Moreover, local alpha power did not significantly modulate alpha to low-gamma PAC estimates. Finally, PAC estimates were correlated with Social Responsiveness Scale (SRS) indicating clinical relevance of the PAC metric. In conclusion, alpha to low-gamma PAC alterations in ASD demonstrate a heterogeneous spatial profile consistent with previous studies and were related to symptom severity.

Reciprocal White Matter Changes Associated With Copy Number Variation at 15q11.2 BP1-BP2: A Diffusion Tensor Imaging Study

BACKGROUND

The 15q11.2 BP1-BP2 cytogenetic region has been associated with learning and motor delays, autism, and schizophrenia. This region includes a gene that codes for the cytoplasmic FMR1 interacting protein 1 (CYFIP1). The CYFIP1 protein is involved in actin cytoskeletal dynamics and interacts with the fragile X mental retardation protein. Absence of fragile X mental retardation protein causes fragile X syndrome. Because abnormal white matter microstructure has been reported in both fragile X syndrome and psychiatric disorders, we looked at the impact of 15q11.2 BP1-BP2 dosage on white matter microstructure.

METHODS

Combining a brain-wide voxel-based approach and a regional-based analysis, we analyzed diffusion tensor imaging data from healthy individuals with the deletion (n = 30), healthy individuals with the reciprocal duplication (n = 27), and IQ-matched control subjects with no large copy number variants (n = 19), recruited from a large genotyped population sample.

RESULTS

We found global mirror effects (deletion > control > duplication) on fractional anisotropy. The deletion group showed widespread increased fractional anisotropy when compared with duplication. Regional analyses revealed a greater effect size in the posterior limb of the internal capsule and a tendency for decreased fractional anisotropy in duplication.

CONCLUSIONS

These results show a reciprocal effect of 15q11.2 BP1-BP2 on white matter microstructure, suggesting that reciprocal chromosomal imbalances may lead to opposite changes in brain structure. Findings in the deletion overlap with previous white matter differences reported in fragile X syndrome patients, suggesting common pathogenic mechanisms derived from disruptions of cytoplasmic CYFIP1-fragile X mental retardation protein complexes. Our data begin to identify specific components of the 15q11.2 BP1-BP2 phenotype and neurobiological mechanisms of potential relevance to the increased risk for disorder.

Evidence for Brainstem Contributions to Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects one in 59 children in the United States. Although there is a mounting body of knowledge of cortical and cerebellar contributions to ASD, our knowledge about the early developing brainstem in ASD is only beginning to accumulate. Understanding how brainstem neurotransmission is implicated in ASD is important because many of this condition’s sensory and motor symptoms are consistent with brainstem pathology. Therefore, the purpose of this review was to integrate epidemiological, behavioral, histological, neuroimaging, and animal evidence of brainstem contributions to ASD. Because ASD is a neurodevelopmental condition, we examined the available data through a lens of hierarchical brain development. The review of the literature suggests that developmental alterations of the brainstem could have potential cascading effects on cortical and cerebellar formation, ultimately leading to ASD symptoms. This view is supported by human epidemiology findings and data from animal models of ASD, showing that perturbed development of the brainstem substructures, particularly during the peak formation of the brainstem’s monoaminergic centers, may relate to ASD or ASD-like behaviors. Furthermore, we review evidence from human histology, psychophysiology, and neuroimaging suggesting that brainstem development and maturation may be atypical in ASD and may be related to key ASD symptoms, such as atypical sensorimotor features and social responsiveness. From this review there emerges the need of future research to validate early detection of the brainstem-based somatosensory and psychophysiological behaviors that emerge in infancy, and to examine the brainstem across the life span, while accounting for age. In all, there is preliminary evidence for brainstem involvement in ASD, but a better understanding of the brainstem’s role would likely pave the way for earlier diagnosis and treatment of ASD.