Elevated mean diffusivity in the left hemisphere superior longitudinal fasciculus in autism spectrum disorders increases with more profound language impairment

Cognitive and brain morphological deviations in middle-to-old aged autistic adults: A systematic review and meta-analysis

Cognitive challenges and brain structure variations are common in autism spectrum disorder (ASD) but are rarely explored in middle-to-old aged autistic adults. Cognitive deficits that overlap between young autistic individuals and elderlies with dementia raise an important question: does compromised cognitive ability and brain structure during early development drive autistic adults to be more vulnerable to pathological aging conditions, or does it protect them from further decline? To answer this question, we have synthesized current theoretical models of aging in ASD and conducted a systematic literature review (Jan 1, 1980 - Feb 29, 2024) and meta-analysis to summarize empirical studies on cognitive and brain deviations in middle-to-old aged autistic adults. We explored findings that support different aging theories in ASD and addressed study limitations and future directions. This review sheds light on the poorly understood consequences of aging question raised by the autism community to pave the way for future studies to identify sensitive and reliable measures that best predict the onset, progression, and prognosis of pathological aging in ASD.

White matter and cortical gray matter microstructural abnormalities in new daily persistent headache: a NODDI study

BACKGROUND

New daily persistent headache (NDPH) is a rare primary headache with unclear pathogenesis. Neuroimaging studies of NDPH are limited, and controversy still exists. Diffusion tensor imaging (DTI) is commonly used to study the white matter. However, lacking specificity, the potential pathological mechanisms of white matter microstructural changes remain poorly understood. In addition, the intricacy of gray matter structures impedes the application of the DTI model. Here, we applied an advanced diffusion model of neurite orientation dispersion and density imaging (NODDI) to study the white matter and cortical gray matter microstructure in patients with NDPH.

METHODS

This study assessed brain microstructure, including 27 patients with NDPH, and matched 28 healthy controls (HCs) by NODDI. The differences between the two groups were assessed by tract-based spatial statistics (TBSS) and surface-based analysis (SBA), focusing on the NODDI metrics (neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)). Furthermore, we performed Pearson's correlation analysis between the NODDI indicators and clinical characteristics.

RESULTS

Compared to HCs, patients with NDPH had a reduction of density and complexity in several fiber tracts. For robust results, the fiber tracts were defined as comprising more than 100 voxels, including bilateral inferior fronto-occipital fasciculus (IFOF), left superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF), as well as right corticospinal tract (CST). Moreover, the reduction of neurite density was uncovered in the left superior and middle frontal cortex, left precentral cortex, and right lateral orbitofrontal cortex and insula. There was no correlation between the NODDI metrics of these brain regions and clinical variables or scales of relevance after the Bonferroni correction.

CONCLUSIONS

Our research indicated that neurite loss was detected in both white matter and cortical gray matter of patients with NDPH.

Discourse- and lesion-based aphasia quotient estimation using machine learning

Discourse is a fundamentally important aspect of communication, and discourse production provides a wealth of information about linguistic ability. Aphasia commonly affects, in multiple ways, the ability to produce discourse. Comprehensive aphasia assessments such as the Western Aphasia Battery-Revised (WAB-R) are time- and resource-intensive. We examined whether discourse measures can be used to estimate WAB-R Aphasia Quotient (AQ), and whether this can serve as an ecologically valid, less resource-intensive measure. We used features extracted from discourse tasks using three AphasiaBank prompts involving expositional (picture description), story narrative, and procedural discourse. These features were used to train a machine learning model to predict the WAB-R AQ. We also compared and supplemented the model with lesion location information from structural neuroimaging. We found that discourse-based models could estimate AQ well, and that they outperformed models based on lesion features. Addition of lesion features to the discourse features did not improve the performance of the discourse model substantially. Inspection of the most informative discourse features revealed that different prompt types taxed different aspects of language. These findings suggest that discourse can be used to estimate aphasia severity, and provide insight into the linguistic content elicited by different types of discourse prompts.

A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.

Impaired white matter integrity in infants and young children with autism spectrum disorder: What evidence does diffusion tensor imaging provide?

BACKGROUND

Abnormal functional connections are associated with impaired white matter tract integrity in the brain. Diffusion tensor imaging (DTI) is a promising method for evaluating white matter integrity in infants and young children. This work aims to shed light on the location and nature of the decrease in white matter integrity.

METHODS

Here, the results of 19 studies have been presented that investigated white matter integrity in infants and young children (6 months to 12 years) with autism using diffusion tensor imaging.

RESULTS

In most of the reviewed studies, an increase in Fractional Anisotropy (FA) and a decrease in Radial Diffusivity (RD) were reported in Corpus Callosum (CC), Uncinate Fasciculus (UF), Cingulum (Cg), Inferior Longitudinal Fasciculus (ILF), and Superior Longitudinal Fasciculus (SLF), and in the Inferior Fronto-Occipital Fasciculus (IFOF) tract, a decrease in FA and an increase in RD were reported.

CONCLUSION

In the reviewed articles, except for one study, the diffusion indices were different compared to the control group.

A narrative review of the anatomy and function of the white matter tracts in language production and comprehension

Much is known about the role of cortical areas in language processing. The shift towards network approaches in recent years has highlighted the importance of uncovering the role of white matter in connecting these areas. However, despite a large body of research, many of these tracts' functions are not well-understood. We present a comprehensive review of the empirical evidence on the role of eight major tracts that are hypothesized to be involved in language processing (inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, extreme capsule, middle longitudinal fasciculus, superior longitudinal fasciculus, arcuate fasciculus, and frontal aslant tract). For each tract, we hypothesize its role based on the function of the cortical regions it connects. We then evaluate these hypotheses with data from three sources: studies in neurotypical individuals, neuropsychological data, and intraoperative stimulation studies. Finally, we summarize the conclusions supported by the data and highlight the areas needing further investigation.

Application of TBSS-based machine learning models in the diagnosis of pediatric autism

Objective

To explore the microstructural changes of white matter in children with pediatric autism by using diffusion kurtosis imaging (DKI), and evaluate whether the combination of tract-based spatial statistics (TBSS) and back-propagation neural network (BPNN)/support vector machine (SVM)/logistic regression (LR) was feasible for the classification of pediatric autism.

Methods

DKI data were retrospectively collected from 32 children with autism and 27 healthy controls (HCs). Kurtosis fractional anisotropy (FAK), mean kurtosis (MK), axial kurtosis (KA), radial kurtosis (RK), fractional anisotropy (FA), axial diffusivity (DA), mean diffusivity (MD) and Radial diffusivity (DR) were generated by iQuant workstation. TBSS was used to detect the regions of parameters values abnormalities and for the comparison between these two groups. In addition, we also introduced the lateralization indices (LI) to study brain lateralization in children with pediatric autism, using TBSS for additional analysis. The parameters values of the differentiated regions from TBSS were then calculated for each participant and used as the features in SVM/BPNN/LR. All models were trained and tested with leave-one-out cross validation (LOOCV).

Results

Compared to the HCs group, the FAK, DA, and KA values of multi-fibers [such as the bilateral superior longitudinal fasciculus (SLF), corticospinal tract (CST) and anterior thalamic radiation (ATR)] were lower in pediatric autism group (p < 0.05, TFCE corrected). And we also found DA lateralization abnormality in Superior longitudinal fasciculus (SLF) (the LI in HCs group was higher than that in pediatric autism group). However, there were no significant differences in FA, MD, MK, DR, and KR values between HCs and pediatric autism group (P > 0.05, TFCE corrected). After performing LOOCV to train and test three model (SVM/BPNN/LR), we found the accuracy of BPNN (accuracy = 86.44%) was higher than that of LR (accuracy = 76.27%), but no different from SVM (RBF, accuracy = 81.36%; linear, accuracy = 84.75%).

Conclusion

Our proposed method combining TBSS findings with machine learning (LR/SVM/BPNN), was applicable in the classification of pediatric autism with high accuracy. Furthermore, the FAK, DA, and KA values and Lateralization index (LI) value could be used as neuroimaging biomarkers to discriminate the children with pediatric autism or not.

Topological analysis of brain dynamics in autism based on graph and persistent homology

Autism spectrum disorder (ASD) is a heterogeneous disorder with a rapidly growing prevalence. In recent years, the dynamic functional connectivity (DFC) technique has been used to reveal the transient connectivity behavior of ASDs' brains by clustering connectivity matrices in different states. However, the states of DFC have not been yet studied from a topological point of view. In this paper, this study was performed using global metrics of the graph and persistent homology (PH) and resting-state functional magnetic resonance imaging (fMRI) data. The PH has been recently developed in topological data analysis and deals with persistent structures of data. The structural connectivity (SC) and static FC (SFC) were also studied to know which one of the SC, SFC, and DFC could provide more discriminative topological features when comparing ASDs with typical controls (TCs). Significant discriminative features were only found in states of DFC. Moreover, the best classification performance was offered by persistent homology-based metrics and in two out of four states. In these two states, some networks of ASDs compared to TCs were more segregated and isolated (showing the disruption of network integration in ASDs). The results of this study demonstrated that topological analysis of DFC states could offer discriminative features which were not discriminative in SFC and SC. Also, PH metrics can provide a promising perspective for studying ASD and finding candidate biomarkers.

Atypical structural connectivity of language networks in autism spectrum disorder: A meta-analysis of diffusion tensor imaging studies

Patients with autism spectrum disorder (ASD) often show pervasive and complex language impairments that are closely associated with aberrant structural connectivity of language networks. However, the characteristics of white matter connectivity in ASD have remained inconclusive in previous diffusion tensor imaging (DTI) studies. The current meta‐analysis aimed to comprehensively elucidate the abnormality in language‐related white matter connectivity in individuals with ASD. We searched PubMed, Web of Science, Scopus, and Medline databases to identify relevant studies. The standardized mean difference was calculated to measure the pooled difference in DTI metrics in each tract between the ASD and typically developing (TD) groups. The moderating effects of age, sex, language ability, and symptom severity were investigated using subgroup and meta‐regression analysis. Thirty‐three DTI studies involving 831 individuals with ASD and 836 TD controls were included in the meta‐analysis. ASD subjects showed significantly lower fractional anisotropy or higher mean diffusivity across language‐associated tracts than TD controls. These abnormalities tended to be more prominent in the left language networks than in the right. In addition, children with ASD exhibit more pronounced and pervasive disturbances in white matter connectivity than adults. These results support the under‐connectivity hypothesis and demonstrate the widespread abnormal microstructure of language‐related tracts in patients with ASD. Otherwise, white matter abnormalities in the autistic brain could vary depending on the developmental stage and hemisphere.

Neonatal brain injury influences structural connectivity and childhood functional outcomes

Neonatal brain injury may impact brain development and lead to lifelong functional impairments. Hypoxic-ischemic encephalopathy (HIE) and congenital heart disease (CHD) are two common causes of neonatal brain injury differing in timing and mechanism. Maturation of whole-brain neural networks can be quantified during development using diffusion magnetic resonance imaging (dMRI) in combination with graph theory metrics. DMRI of 35 subjects with CHD and 62 subjects with HIE were compared to understand differences in the effects of HIE and CHD on the development of network topological parameters and functional outcomes. CHD newborns had worse 12–18 month language (P<0.01) and 30 month cognitive (P<0.01), language (P = 0.05), motor outcomes (P = 0.01). Global efficiency, a metric of brain integration, was lower in CHD (P = 0.03) than in HIE, but transitivity, modularity and small-worldness were similar. After controlling for clinical factors known to affect neurodevelopmental outcomes, we observed that global efficiency was highly associated with 30 month motor outcomes (P = 0.02) in both groups. To explore neural correlates of adverse language outcomes in CHD, we used hypothesis-based and data-driven approaches to identify pathways with altered structural connectivity. We found that connectivity strength in the superior longitudinal fasciculus (SLF) tract 2 was inversely associated with expressive language. After false discovery rate correction, a whole connectome edge analysis identified 18 pathways that were hypoconnected in the CHD cohort as compared to HIE. In sum, our study shows that neonatal structural connectivity predicts early motor development after HIE or in subjects with CHD, and regional SLF connectivity is associated with language outcomes. Further research is needed to determine if and how brain networks change over time and whether those changes represent recovery or ongoing dysfunction. This knowledge will directly inform strategies to optimize neurologic functional outcomes after neonatal brain injury.

What's your name again? A review of the superior longitudinal and arcuate fasciculus evolving nomenclature

Studies of the superior longitudinal fasciculus (SLF) have multiplied in recent decades owing to methodological advances, but the absence of a convention for nomenclature remains a source of confusion. Here, we have reviewed existing nomenclatures in the context of the research studies that generated them and we have identified their agreements and disagreements. A literature search was conducted using PubMed/MEDLINE, Web-of-Science, Embase, and a review of seminal publications, without restrictions regarding publication date. Our search revealed that diffusion imaging, autoradiography, and fiber dissection have been the main methods contributing to tract designation. The first two have been particularly influential in systematizing the horizontal elements distant from the lateral sulcus. Twelve approaches to naming were identified, eight of them differing considerably from each other. The terms SLF and arcuate fasciculus (AF) were often used as synonyms until the second half of the 20th century. During the last 15 years, this has ceased to be the case in a growing number of publications. The term AF has been used to refer to the assembly of three different segments, or exclusively to long frontotemporal fibers. Similarly, the term SLF has been employed to denote the whole superior longitudinal associative system, or only the horizontal frontoparietal parts. As only partial correspondence can be identified among the available nomenclatures, and in the absence of an official designation of all anatomical structures that can be encountered in clinical practice, a high level of vigilance regarding the effectiveness of every oral or written act of communication is mandatory.

Brain and Language Associations in Autism Spectrum Disorder: A Scoping Review

Examining brain and behaviour associations for language in autism spectrum disorder (ASD) may bring us closer to identifying neural profiles that are unique to a subgroup of individuals with ASD identified as language impaired (e.g. ASD LI+). We conducted a scoping review to examine brain regions that are associated with language performance in ASD. Further, we examined methodological differences across studies in how language ability was characterized and what neuroimaging methods were used to explore brain regions. Seventeen studies met inclusion criteria. Brain regions specific to ASD LI+ groups were found, however inconsistencies in brain and language associations were evident across study findings. Participant age, age-appropriate language scores, and neuroimaging methods likely contributed to differences in associations found.

White Matter Correlates of Theory of Mind in Patients With First-Episode Psychosis

Deficits in theory of mind (ToM) are considered as a distinctive feature of schizophrenia. Functional magnetic resonance imaging (fMRI) studies have suggested that aberrant activity among the regions comprising the mentalizing network is related to observed ToM deficits. However, the white matter structures underlying the ToM functional network in schizophrenia remain unclear. To investigate the relationship between white matter integrity and ToM impairment, 35 patients with first-episode psychosis (FEP) and 29 matched healthy controls (HCs) underwent diffusion tensor imaging (DTI). Using tract-based spatial statistics (TBSS), fractional anisotropy (FA) values of the two regions of interest (ROI)-the cingulum and superior longitudinal fasciculus (SLF)-were acquired, and correlational analysis with ToM task scores was performed. Among the patients with FEP, ToM strange story scores were positively correlated with the FA values of the left cingulum and left SLF. There was no significant correlation between FA and ToM task scores in HCs. These results suggest that the left cingulum and SLF constitute a possible neural basis for ToM deficits in schizophrenia. Our study is the first to demonstrate the white matter connectivity underlying the mentalizing network, as well as its relation to ToM ability in patients with FEP.

Is Migraine Associated to Brain Anatomical Alterations? New Data and Coordinate-Based Meta-analysis

A growing number of studies investigate brain anatomy in migraine using voxel- (VBM) and surface-based morphometry (SBM), as well as diffusion tensor imaging (DTI). The purpose of this article is to identify consistent patterns of anatomical alterations associated with migraine. First, 19 migraineurs without aura and 19 healthy participants were included in a brain imaging study. T1-weighted MRIs and DTI sequences were acquired and analyzed using VBM, SBM and tract-based spatial statistics. No significant alterations of gray matter (GM) volume, cortical thickness, cortical gyrification, sulcus depth and white-matter tract integrity could be observed. However, migraineurs displayed decreased white matter (WM) volume in the left superior longitudinal fasciculus. Second, a systematic review of the literature employing VBM, SBM and DTI was conducted to investigate brain anatomy in migraine. Meta-analysis was performed using Seed-based d Mapping via permutation of subject images (SDM-PSI) on GM volume, WM volume and cortical thickness data. Alterations of GM volume, WM volume, cortical thickness or white-matter tract integrity were reported in 72%, 50%, 56% and 33% of published studies respectively. Spatial distribution and direction of the disclosed effects were highly inconsistent across studies. The SDM-PSI analysis revealed neither significant decrease nor significant increase of GM volume, WM volume or cortical thickness in migraine. Overall there is to this day no strong evidence of specific brain anatomical alterations reliably associated to migraine. Possible explanations of this conflicting literature are discussed. Trial registration number: NCT02791997, registrated February 6th, 2015.

Preeclampsia and Neurodevelopmental Outcomes: Potential Pathogenic Roles for Inflammation and Oxidative Stress?

Preeclampsia (PE) is a common and serious hypertensive disorder of pregnancy that occurs in approximately 3-5% of first-time pregnancies and is a well-known leading cause of maternal and neonatal mortality and morbidity. In recent years, there has been accumulating evidence that in utero exposure to PE acts as an environmental risk factor for various neurodevelopmental disorders, particularly autism spectrum disorder and ADHD. At present, the mechanism(s) mediating this relationship are uncertain. In this review, we outline the most recent evidence implicating a causal role for PE exposure in the aetiology of various neurodevelopmental disorders and provide a novel interpretation of neuroanatomical alterations in PE-exposed offspring and how these relate to their sub-optimal neurodevelopmental trajectory. We then postulate that inflammation and oxidative stress, two prominent features of the pathophysiology of PE, are likely to play a major role in mediating this association. The increased inflammation in the maternal circulation, placenta and fetal circulation in PE expose the offspring to both prenatal maternal immune activation-a risk factor for neurodevelopmental disorders, which has been well-characterised in animal models-and directly higher concentrations of pro-inflammatory cytokines, which adversely affect neuronal development. Similarly, the exaggerated oxidative stress in the mother, placenta and foetus induces the placenta to secrete factors deleterious to neurons, and exposes the fetal brain to directly elevated oxidative stress and thus adversely affects neurodevelopmental processes. Finally, we describe the interplay between inflammation and oxidative stress in PE, and how both systems interact to potentially alter neurodevelopmental trajectory in exposed offspring.

Differences in attentional control and white matter microstructure in adolescents with attentional, affective, and behavioral disorders

Adolescence is a critical time of physiological, cognitive, and social development. It is also a time of increased risk-taking and vulnerability for psychopathology. White matter (WM) changes during adolescence have been better elucidated in the last decade, but how WM is impacted by psychopathology during this time remains unclear. Here, we examined the link between WM microstructure and psychopathology during adolescence. Twenty youth diagnosed with affective, attentional, and behavioral disorders (clinical sample), and 20 age-matched controls were recruited to examine group differences in WM microstructure, attentional control, and the link between them. The main results showed that clinical sample had relatively lower attentional control and fractional anisotropy (FA) in WM throughout the brain: two association tracts were identified, and many differences were found in areas rich in callosal and projection fibers. Moreover, increased FA was positively associated with attention performance in the clinical sample in structures supporting ventral WM pathways, whereas a similar link was identified in controls in dorsal WM association fibers. Overall, these results support a model of general impairment in WM microstructure combined with reliance on altered, perhaps less efficient, pathways for attentional control in youth with affective, attentional, and behavioral disorders.

Phonetic discrimination mediates the relationship between auditory brainstem response stability and syntactic performance

Syntactic, lexical, and phonological/phonetic knowledge are vital aspects of macro level language ability. Prior research has predominantly focused on environmental or cortical sources of individual differences in these areas; however, a growing literature suggests an auditory brainstem contribution to language performance in both typically developing (TD) populations and children with autism spectrum disorder (ASD). This study investigates whether one aspect of auditory brainstem responses (ABRs), neural response stability, which is a metric reflecting trial-by-trial consistency in the neural encoding of sound, can predict syntactic, lexical, and phonetic performance in TD and ASD school-aged children. Pooling across children with ASD and TD, results showed that higher neural stability in response to the syllable /da/ was associated with better phonetic discrimination, and with better syntactic performance on a standardized measure. Furthermore, phonetic discrimination was a successful mediator of the relationship between neural stability and syntactic performance. This study supports the growing body of literature that stable subcortical neural encoding of sound is important for successful language performance.

Breastfeeding Duration Is Associated with Regional, but Not Global, Differences in White Matter Tracts

Extended breastfeeding through infancy confers benefits on neurocognitive performance and intelligence tests, though few have examined the biological basis of these effects. To investigate correlations with breastfeeding, we examined the major white matter tracts in 4–8 year-old children using diffusion tensor imaging and volumetric measurements of the corpus callosum. We found a significant correlation between the duration of infant breastfeeding and fractional anisotropy scores in left-lateralized white matter tracts, including the left superior longitudinal fasciculus and left angular bundle, which is indicative of greater intrahemispheric connectivity. However, in contrast to expectations from earlier studies, no correlations were observed with corpus callosum size, and thus no correlations were observed when using such measures of global interhemispheric white matter connectivity development. These findings suggest a complex but significant positive association between breastfeeding duration and white matter connectivity, including in pathways known to be functionally relevant for reading and language development.

Widespread Disrupted White Matter Microstructure in Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) are characterised by impaired social communication and restricted repetitive behaviours. Researchers posit that these core features may be underpinned by disrupted structural connectivity. A tract based spatial statistical analysis of diffusion MRI data was performed to investigate white matter organisation (an indication of structural connectivity) in a well-defined cohort of 45 ASD and 45 age and IQ matched control participants. Aberrant structural connectivity characterised by reduced fractional anisotropy was observed in several fiber pathways in ASD relative to controls. Disrupted white matter organisation was associated with social deficits and restricted repetitive behaviours in ASD. Abnormal structural connectivity is apparent in ASD and may be linked to the core behavioural features of the disorder.

Altered structural brain connectivity involving the dorsal and ventral language pathways in 16p11.2 deletion syndrome

Copy number variants at the chromosomal locus 16p11.2 contribute to neurodevelopmental disorders such as autism spectrum disorders, epilepsy, schizophrenia, and language and articulation disorders. Here, we provide detailed findings on the disrupted structural brain connectivity in 16p11.2 deletion syndrome (patients: N = 21, age range: 8-16 years; typically developing (TD) controls: 18, 9-16 years) using structural and diffusion MRI. We performed global short-, middle-, long-range, and interhemispheric connectivity analysis in the whole brain using gyral topology-based cortical parcellation. Using region of interest analysis, we studied bilateral dorsal (3 segments of arcuate fasciculus (AF)) and ventral (inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF)) language pathways. Our results showed significantly increased axial (AD) and radial (RD) diffusivities in bilateral anterior AF, decreased volume for left long AF, increased mean diffusivity (MD) and RD for right long AF, and increased AD for bilateral UF in the 16p11.2 deletion group in the absence of significant abnormalities in the whole-brain gyral and interhemispheric connectivity. The selective involvement of the language networks may aid in understanding effects of altered white matter connectivity on neurodevelopmental outcomes in 16p11.2 deletion.

Altered Neural Connectivity in Females, But Not Males with Autism: Preliminary Evidence for the Female Protective Effect from a Quality-Controlled Diffusion Tensor Imaging Study

Previous studies using diffusion tensor imaging (DTI) to investigate white matter (WM) structural connectivity have suggested widespread, although inconsistent WM alterations in autism spectrum disorder (ASD), such as greater reductions in fractional anisotropy (FA). However, findings may lack generalizability because: (a) most have focused solely on the ASD male brain phenotype, and not sex‐differences in WM integrity; (b) many lack stringent and transparent data quality control such as controlling for head motion in analysis. This study addressed both issues by using Tract‐Based Spatial Statistics (TBSS) to separately compare WM differences in 81 ASD (56 male, 25 female; 4–21 years old) and 39 typically developing (TD; 23 males, 16 females; 5–18 years old) children and young people, carefully group‐matched on sex, age, cognitive abilities, and head motion. ASD males and females were also matched on autism symptom severity. Two independent‐raters completed a multistep scan quality assurance to remove images that were significantly distorted by motion artifacts before analysis. ASD females exhibited significant widespread reductions in FA compared to TD females, suggesting altered WM integrity. In contrast, no significant localized or widespread WM differences were found between ASD and TD males. This study highlights the importance of data quality control in DTI, and outlines important sex‐differences in WM alterations in ASD females. Future studies can explore the extent to which neural structural differences might underlie sex‐differences in ASD behavioral phenotype, and guide clinical interventions to be tailored toward the unique needs of ASD females and males. Autism Res 2019, 12: 1472–1483. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc.

Lay Summary

Previous Diffusion Tensor Imaging (DTI) studies have found atypical brain structural connectivity in males with autism, although findings are inconclusive in females with autism. To investigate potential sex‐differences, we studied males and females with and without autism who showed a similar level of head movement during their brain scan. We found that females with autism had widespread atypical neural connectivity than females without autism, although not in males, highlighting sex‐differences.

The language network in autism: Atypical functional connectivity with default mode and visual regions

Autism spectrum disorders (ASDs) are neurodevelopmental disorders associated with atypical brain connectivity. Although language abilities vary widely, they are impaired or atypical in most children with ASDs. Underlying brain mechanisms, however, are not fully understood. The present study examined intrinsic functional connectivity (iFC) of the extended language network in a cohort of 52 children and adolescents with ASDs (ages 8-18 years), using resting-state functional magnetic resonance imaging. We found that, in comparison to typically developing peers (n = 50), children with ASDs showed increased connectivity between some language regions. In addition, seed-to-whole brain analyses revealed increased connectivity of language regions with posterior cingulate cortex (PCC) and visual regions in the ASD group. Post hoc effective connectivity analyses revealed a mediation effect of PCC on the iFC between bilateral inferior frontal and visual regions in an ASD subgroup. This finding qualifies and expands on previous reports of recruitment of visual areas in language processing in ASDs. In addition, increased iFC between PCC and visual regions was linked to lower language scores in this ASD subgroup, suggesting that increased connectivity with visual cortices, mediated by default mode regions, may be detrimental to language abilities. Autism Res 2019, 12: 1344-1355. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: We examined the functional connectivity between regions of the language network in children with autism spectrum disorders (ASDs) compared to typically developing peers. We found connectivity to be intact between core language in the ASD group, but also showed abnormally increased connectivity between regions of an extended language network. Additionally, connectivity was increased with regions associated with brain networks responsible for self-reflection and visual processing.

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.

Hippocampal subfield-specific connectivity findings in major depressive disorder: A 7 Tesla diffusion MRI study

OBJECTIVE

Diffusion magnetic resonance imaging (dMRI) enables non-invasive characterization of white matter (WM) structures in vivo. Prior studies suggest that certain WM tracts may be affected in major depressive disorder (MDD), however, hippocampal subfield-specific dMRI measures have not yet been explored in MDD. We use 7 Tesla dMRI to investigate differences in hippocampal subfield connectivity of MDD patients.

METHODS

Eighteen MDD patients and eighteen matched healthy volunteers underwent 7 Tesla MRI. The hippocampal formations were segmented by subfields and tractography was performed to determine streamline count (SC), fractional anisotropy (FA), and mean diffusivity (MD) in patients and controls. Significant subfield connectivity measures were also correlated with age at depression onset.

RESULTS

Compared with controls, MDD patients exhibited reduced SC in the molecular layer of the left dentate gyrus (p < 0.001). SC count in the left dentate gyrus was shown to positively correlate with age at disease onset (p < 0.05). Increased MD was observed in streamlines emanating from both the left (p = 0.0001) and right (p < 0.001) fimbriae in MDD patients.

CONCLUSIONS

Increased MD of tracts in the fimbriae suggests compromised neuronal membranes in the major hippocampal output gate. Reduced SC of the dentate gyri indexes a disruption of normal cellular processes such as neurogenesis. These findings may have significant implications for identifying biomarkers of MDD and elucidating the neurobiological underpinnings of depression.

White Matter Connectome Correlates of Auditory Over-Responsivity: Edge Density Imaging and Machine-Learning Classifiers

Sensory over-responsivity (SOR) commonly involves auditory and/or tactile domains, and can affect children with or without additional neurodevelopmental challenges. In this study, we examined white matter microstructural and connectome correlates of auditory over-responsivity (AOR), analyzing prospectively collected data from 39 boys, aged 8–12 years. In addition to conventional diffusion tensor imaging (DTI) maps – including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD); we used DTI and high-resolution T1 scans to develop connectome Edge Density (ED) maps. The tract-based spatial statistics was used for voxel-wise comparison of diffusion and ED maps. Then, stepwise penalized logistic regression was applied to identify independent variable (s) predicting AOR, as potential imaging biomarker (s) for AOR. Finally, we compared different combinations of machine learning algorithms (i.e., naïve Bayes, random forest, and support vector machine (SVM) and tract-based DTI/connectome metrics for classification of children with AOR. In direct sensory phenotype assessment, 15 (out of 39) boys exhibited AOR (with or without neurodevelopmental concerns). Voxel-wise analysis demonstrates extensive impairment of white matter microstructural integrity in children with AOR on DTI maps – evidenced by lower FA and higher MD and RD; moreover, there was lower connectome ED in anterior-superior corona radiata, genu and body of corpus callosum. In stepwise logistic regression, the average FA of left superior longitudinal fasciculus (SLF) was the single independent variable distinguishing children with AOR (p = 0.007). Subsequently, the left SLF average FA yielded an area under the curve of 0.756 in receiver operating characteristic analysis for prediction of AOR (p = 0.008) as a region-of-interest (ROI)-based imaging biomarker. In comparative study of different combinations of machine-learning models and DTI/ED metrics, random forest algorithms using ED had higher accuracy for AOR classification. Our results demonstrate extensive white matter microstructural impairment in children with AOR, with specifically lower connectomic ED in anterior-superior tracts and associated commissural pathways. Also, average FA of left SLF can be applied as ROI-based imaging biomarker for prediction of SOR. Finally, machine-learning models can provide accurate and objective image-based classifiers for identification of children with AOR based on white matter tracts connectome ED.

Diffusion-weighted imaging evidence of altered white matter development from late childhood to early adulthood in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is thought to reflect disrupted development of brain connectivity characterized by white matter abnormalities and dyscoordination of activity across brain regions that give rise to core features. But there is little consensus about the nature, timing and location of white matter abnormalities as quantified with diffusion-weighted MRI. Inconsistent findings likely reflect small sample sizes, motion confounds and sample heterogeneity, particularly different age ranges across studies. We examined the microstructural integrity of major white matter tracts in relation to age in 38 high functioning ASD and 35 typically developing (TD) participants, aged 8-25, whose diffusion-weighted scans met strict data-quality criteria and survived group matching for motion. While there were no overall group differences in diffusion measures, the groups showed different relations with age. Only the TD group showed the expected positive correlations of fractional anisotropy with age. In parallel, axial diffusivity was unrelated to age in TD, but showed inverse correlations with age in ASD. Younger participants with ASD tended to have higher fractional anisotropy and axial diffusivity than their TD peers, while the opposite was true for older participants. Most of the affected tracts - cingulum bundle, inferior and superior longitudinal fasciculi - are association bundles related to cognitive, social and emotional functions that are abnormal in ASD. The manifestations of abnormal white matter development in ASD as measured by diffusion-weighted MRI depend on age and this may contribute to inconsistent findings across studies. We conclude that ASD is characterized by altered white matter development from childhood to early adulthood that may underlie abnormal brain function and contribute to core features.

Arcuate Fasciculus in Autism Spectrum Disorder Toddlers with Language Regression

Language regression is observed in a subset of toddlers with autism spectrum disorder (ASD) as initial symptom. However, such a phenomenon has not been fully explored, partly due to the lack of definite diagnostic evaluation methods and criteria. Materials and Methods: Fifteen toddlers with ASD exhibiting language regression and fourteen age-matched typically developing (TD) controls underwent diffusion tensor imaging (DTI). DTI parameters including fractional anisotropy (FA), average fiber length (AFL), tract volume (TV) and number of voxels (NV) were analyzed by Neuro 3D in Siemens syngo workstation. Subsequently, the data were analyzed by using IBM SPSS Statistics 22. Results: Compared with TD children, a significant reduction of FA along with an increase in TV and NV was observed in ASD children with language regression. Note that there were no significant differences between ASD and TD children in AFL of the arcuate fasciculus (AF). Conclusions: These DTI changes in the AF suggest that microstructural anomalies of the AF white matter may be associated with language deficits in ASD children exhibiting language regression starting from an early age.

Effects of bilingualism on white matter integrity in older adults

Bilingualism can delay the onset of dementia symptoms and has thus been characterized as a mechanism for cognitive or brain reserve, although the origin of this reserve is unknown. Studies with young adults generally show that bilingualism is associated with a strengthening of white matter, but there is conflicting evidence for how bilingualism affects white matter in older age. Given that bilingualism has been shown to help stave off the symptoms of dementia by up to four years, it is crucial that we clarify the mechanism underlying this reserve. The current study uses diffusion tensor imaging (DTI) to compare monolinguals and bilinguals while carefully controlling for potential confounds (e.g., I.Q., MMSE, and demographic variables). We show that group differences in Fractional Anisotropy (FA) and Radial Diffusivity (RD) arise from multivariable interactions not adequately controlled for by sequential bivariate testing. After matching and statistically controlling for confounds, bilinguals still had greater axial diffusivity (AD) in the left superior longitudinal fasciculus than monolingual peers, supporting a neural reserve account for healthy older bilinguals.

Differential effect of disease-associated ST8SIA2 haplotype on cerebral white matter diffusion properties in schizophrenia and healthy controls

Brain white matter abnormalities are evident in individuals with schizophrenia, and also their first-degree relatives, suggesting that some alterations may relate to underlying genetic risk. The ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 2 (ST8SIA2) gene, which encodes the alpha-2,8-sialyltransferase 8B enzyme that aids neuronal migration and synaptic plasticity, was previously implicated as a schizophrenia susceptibility gene. This study examined the extent to which specific haplotypes in ST8SIA2 influence white matter microstructure using diffusion-weighted imaging of individuals with schizophrenia (n = 281) and healthy controls (n = 172), recruited across five Australian sites. Interactions between diagnostic status and the number of haplotype copies (0 or ≥1) were tested across all white matter voxels with cluster-based statistics. Fractional anisotropy (FA) in the right parietal lobe was found to show a significant interaction between diagnosis and ST8SIA2 protective haplotype (p < 0.05, family-wise error rate (FWER) cluster-corrected). The protective haplotype was associated with increased FA in controls, but this effect was reversed in people with schizophrenia. White matter fiber tracking revealed that the region-of-interest was traversed by portions of the superior longitudinal fasciculus, corona radiata, and posterior limb of internal capsule. Post hoc analysis revealed that reduced FA in this regional juncture correlated with reduced IQ in people with schizophrenia. The ST8SIA2 risk haplotype copy number did not show any differential effects on white matter. This study provides a link between a common disease-associated haplotype and specific changes in white matter microstructure, which may relate to resilience or risk for mental illness, providing further compelling evidence for involvement of ST8SIA2 in the pathophysiology of schizophrenia.

Atypical age-dependency of executive function and white matter microstructure in children and adolescents with autism spectrum disorders

Executive function (EF) performance is associated with measurements of white matter microstructure (WMS) in typical individuals. Impaired EF is a hallmark symptom of autism spectrum disorders (ASD) but it is unclear how impaired EF relates to variability in WMS. Twenty-one male youth (8-18 years) with ASD and without intellectual disability and twenty-one typical male participants (TP) matched for age, intelligence quotient, handedness, race and parental socioeconomic status were recruited. Five EF domains were assessed and several DTI-based measurements of WMS [fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD)] were estimated for eighteen white matter tracts. The ASD group had lower scores for attention (F = 8.37, p = 0.006) and response inhibition (F = 13.09, p = 0.001). Age-dependent changes of EF performance and WMS measurements were present in TP but attenuated in the ASD group. The strongest diagnosis-by-age effect was found for forceps minor, left anterior thalamic radiation and left cingulum angular bundle (all p's ≤ 0.002). In these tracts subjects with ASD tended to have equal or increased FA and/or reduced MD and/or RD at younger ages while controls had increased FA and/or reduced MD and/or RD thereafter. Only for TP individuals, increased FA in the left anterior thalamic radiation was associated with better response inhibition, while reduced RD in forceps minor and left cingulum angular bundle was related to better problem solving and working memory performance respectively. These findings provide novel insight into the age-dependency of EF performance and WMS in ASD, which can be instructive to cognitive training programs.

Whole brain white matter connectivity analysis using machine learning: An application to autism

In this paper, we propose an automated white matter connectivity analysis method for machine learning classification and characterization of white matter abnormality via identification of discriminative fiber tracts. The proposed method uses diffusion MRI tractography and a data-driven approach to find fiber clusters corresponding to subdivisions of the white matter anatomy. Features extracted from each fiber cluster describe its diffusion properties and are used for machine learning. The method is demonstrated by application to a pediatric neuroimaging dataset from 149 individuals, including 70 children with autism spectrum disorder (ASD) and 79 typically developing controls (TDC). A classification accuracy of 78.33% is achieved in this cross-validation study. We investigate the discriminative diffusion features based on a two-tensor fiber tracking model. We observe that the mean fractional anisotropy from the second tensor (associated with crossing fibers) is most affected in ASD. We also find that local along-tract (central cores and endpoint regions) differences between ASD and TDC are helpful in differentiating the two groups. These altered diffusion properties in ASD are associated with multiple robustly discriminative fiber clusters, which belong to several major white matter tracts including the corpus callosum, arcuate fasciculus, uncinate fasciculus and aslant tract; and the white matter structures related to the cerebellum, brain stem, and ventral diencephalon. These discriminative fiber clusters, a small part of the whole brain tractography, represent the white matter connections that could be most affected in ASD. Our results indicate the potential of a machine learning pipeline based on white matter fiber clustering.

Neural correlates of language variability in preschool-aged boys with autism spectrum disorder

Children with autism vary widely in their language abilities, yet the neural correlates of this language variability remain unclear, especially early in development. Diffusion tensor imaging (DTI) was used to examine diffusivity measures along the length of 18 major fiber tracts in 104 preschool-aged boys with autism spectrum disorder (ASD). The boys were assigned to subgroups according to their level of language development (Low: no/low language, Middle: small vocabulary, High: large vocabulary and grammar), based on their raw scores on the expressive language (EL) and receptive language (RL) sections of the Mullen Scales of Early Learning (MSEL). Results indicate that the subgroups differed in fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) along the inferior longitudinal fasciculus (ILF) in both hemispheres. Moreover, FA correlated significantly with Mullen EL and RL raw scores, but not ADOS severity score, along the left and right ILF. Subgroups also differed in MD (but not FA) along the left superior longitudinal fasiculus and left corticospinal tract, but these differences were not correlated with language scores. These findings suggest that white matter microstructure in the left and right ILF varies in relation to lexical development in young males with ASD. The findings also support the use of raw scores on language-relevant standardized tests for assessing early language-brain relationships. Autism Res 2017. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 1107-1119. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies

Searching for effective biomarkers is one of the most challenging tasks in the research field of Autism Spectrum Disorder (ASD). Magnetic resonance imaging (MRI) provides a non-invasive and powerful tool for investigating changes in the structure, function, maturation, connectivity, and metabolism of the brain of children with ASD. Here, we review the more recent MRI studies in young children with ASD, aiming to provide candidate biomarkers for the diagnosis of childhood ASD. The review covers structural imaging methods, diffusion tensor imaging, resting-state functional MRI, and magnetic resonance spectroscopy. Future advances in neuroimaging techniques, as well as cross-disciplinary studies and large-scale collaborations will be needed for an integrated approach linking neuroimaging, genetics, and phenotypic data to allow the discovery of new, effective biomarkers.

White Matter Diffusion of Major Fiber Tracts Implicated in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder found to have widespread alterations in the function and synchrony of brain regions. These differences may underlie alterations in microstructural organization, such as in white matter pathways. To investigate the diffusion of major white matter tracts, the current study examined multiple indices of white matter diffusion in 42 children and adults with ASD and 44 typically developing (TD) age- and IQ-matched peers using diffusion tensor imaging. Diffusivity measures were compared between groups for the following tracts: bilateral cingulum bundle, corpus callosum, inferior longitudinal fasciculus, superior longitudinal fasciculus, and uncinate fasciculus. Results indicate a significant reduction in fractional anisotropy (FA) for the left superior longitudinal fasciculus (LSLF) in ASD children and adults compared with TD peers. A significant increase in radial diffusivity for ASD participants was also found in the same cluster along the LSLF. In addition, a significant positive correlation emerged for all subjects between FA for the LSLF and age, with FA increasing with age. These findings point to a significant alteration in long-distance white matter connectivity in children and adults with ASD, potentially underscoring the relationship between alterations in white matter diffusion and the ASD phenotype. These results also suggest that the white matter alterations in autism may be subtle and related to the developmental trajectory.

Relationship between genotype and arcuate fasciculus morphology in six young children with global developmental delay: Preliminary DTI stuy

PURPOSE

To investigate whether different genetic mutations observed in children with global developmental delay (GD) are associated with unique patterns of the arcuate fasciculus dysmorphology.

MATERIALS AND METHODS

Six children with GD (age: 36.8 ± 14.1 months, 5 boys) having mutations in MID1, CDK4, SFRP1, EN2, RXRG-GLRB, or MECP2, and five children with typical development (TD, age: 38.5 ± 20.5 months, 4 boys) underwent a 3 Tesla MRI including diffusion weighted imaging (DWI). Five language pathway segments in the left hemisphere, "C₁ : Broca's to Wernicke's area," "C₂ : Broca's to premotor area," "C₃ : premotor to Wernicke's area," "C₄ : Wernicke's to inferior parietal area," and "C₅ : premotor to inferior parietal area" were objectively identified using the DWI "maximum a posteriori probability" classifier.

RESULTS

Affinity propagation clustering analysis found that three arcuate pathway segments, C_1,2,4 , of MID1, CDK4, EN2, and MECP2 had a similar pattern of volume ratio while those of SFRP1 and RXRG-GLRB had a heterogeneous pattern of volume ratio (net similarity = -0.01). Using receiver operating characteristic curve analysis, the fiber ratios of C_1,2,4 showed a high probability to discriminate between GD and TD, yielding an accuracy of 0.91, 0.91, 1.00, respectively. The fiber volumes of C₁ and C₄ showed a strong correlation with expressive language (R²  = 0.6019; P-value = 0.033) and receptive language (R²  = 0.6379; P-value = 0.028), respectively.

CONCLUSION

The findings of the present study provide preliminary evidence to suggest that different segments of the arcuate fasciculus are formed under the regulation of different genes which, when mutated, may result in developmental delay. J. Magn. Reson. Imaging 2016;44:1504-1512.

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics.

Multimodal Diffusion-MRI and MEG Assessment of Auditory and Language System Development in Autism Spectrum Disorder

BACKGROUND

Auditory processing and language impairments are prominent in children with autism spectrum disorder (ASD). The present study integrated diffusion MR measures of white-matter microstructure and magnetoencephalography (MEG) measures of cortical dynamics to investigate associations between brain structure and function within auditory and language systems in ASD. Based on previous findings, abnormal structure-function relationships in auditory and language systems in ASD were hypothesized.

METHODS

Evaluable neuroimaging data was obtained from 44 typically developing (TD) children (mean age 10.4 ± 2.4 years) and 95 children with ASD (mean age 10.2 ± 2.6 years). Diffusion MR tractography was used to delineate and quantitatively assess the auditory radiation and arcuate fasciculus segments of the auditory and language systems. MEG was used to measure (1) superior temporal gyrus auditory evoked M100 latency in response to pure-tone stimuli as an indicator of auditory system conduction velocity, and (2) auditory vowel-contrast mismatch field (MMF) latency as a passive probe of early linguistic processes.

RESULTS

Atypical development of white matter and cortical function, along with atypical lateralization, were present in ASD. In both auditory and language systems, white matter integrity and cortical electrophysiology were found to be coupled in typically developing children, with white matter microstructural features contributing significantly to electrophysiological response latencies. However, in ASD, we observed uncoupled structure-function relationships in both auditory and language systems. Regression analyses in ASD indicated that factors other than white-matter microstructure additionally contribute to the latency of neural evoked responses and ultimately behavior. RESULTS also indicated that whereas delayed M100 is a marker for ASD severity, MMF delay is more associated with language impairment.

CONCLUSION

Present findings suggest atypical development of primary auditory as well as auditory language systems in ASD. Findings demonstrate the need for additional multimodal studies to better characterize the different structural features (white matter, gray matter, neurochemical concentration) that contribute to brain activity, both in typical development and in ASD. Finally, the neural latency measures were found to be of clinical significance, with M100 associated with overall ASD severity, and with MMF latency associated with language performance.

White matter volume in the brainstem and inferior parietal lobule is related to motor performance in children with autism spectrum disorder: A voxel-based morphometry study

Many studies have reported poor motor performance in autism spectrum disorder (ASD); however, the underlying brain mechanisms remain unclear. Recent neuroimaging studies have suggested that abnormalities of the white matter (WM) are related to the features of ASD. In this study, we used voxel-based morphometry (VBM) to investigate which WM regions correlate with motor performance in children with ASD, and whether the WM volume in those brain regions differed between children with ASD and typically developing (TD) children. The subjects included 19 children with ASD and 20 TD controls. Motor performance was assessed using the Movement Assessment Battery for Children 2 (M-ABC 2). Children with ASD showed poorer motor performance than did the controls. There was a significant positive correlation between the total test score on the M-ABC 2 and the volume of WM in the brainstem and WM adjacent to the left supramarginal gyrus (SMG). In addition, compared with the TD controls, children with ASD had a decreased volume of WM in the brainstem and adjacent to the left intraparietal sulcus, which is close to the SMG. These findings suggest that structural changes in the WM in the brainstem and left inferior parietal lobule may contribute to poor motor performance in children with ASD. Autism Res 2016, 9: 981-992. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Differentiation of Speech Delay and Global Developmental Delay in Children Using DTI Tractography-Based Connectome

BACKGROUND AND PURPOSE

Pure speech delay is a common developmental disorder which, according to some estimates, affects 5%-8% of the population. Speech delay may not only be an isolated condition but also can be part of a broader condition such as global developmental delay. The present study investigated whether diffusion tensor imaging tractography-based connectome can differentiate global developmental delay from speech delay in young children.

MATERIALS AND METHODS

Twelve children with pure speech delay (39.1 ± 20.9 months of age, 9 boys), 14 children with global developmental delay (39.3 ± 18.2 months of age, 12 boys), and 10 children with typical development (38.5 ± 20.5 months of age, 7 boys) underwent 3T DTI. For each subject, whole-brain connectome analysis was performed by using 116 cortical ROIs. The following network metrics were measured at individual regions: strength (number of the shortest paths), efficiency (measures of global and local integration), cluster coefficient (a measure of local aggregation), and betweeness (a measure of centrality).

RESULTS

Compared with typical development, global and local efficiency were significantly reduced in both global developmental delay and speech delay (P < .0001). The nodal strength of the cognitive network is reduced in global developmental delay, whereas the nodal strength of the language network is reduced in speech delay. This finding resulted in a high accuracy of >83% ± 4% to discriminate global developmental delay from speech delay.

CONCLUSIONS

The network abnormalities identified in the present study may underlie the neurocognitive and behavioral consequences commonly identified in children with global developmental delay and speech delay. Further validation studies in larger samples are required.

Neuroanatomy of Individual Differences in Language in Adult Males with Autism

One potential source of heterogeneity within autism spectrum conditions (ASC) is language development and ability. In 80 high-functioning male adults with ASC, we tested if variations in developmental and current structural language are associated with current neuroanatomy. Groups with and without language delay differed behaviorally in early social reciprocity, current language, but not current autistic features. Language delay was associated with larger total gray matter (GM) volume, smaller relative volume at bilateral insula, ventral basal ganglia, and right superior, middle, and polar temporal structures, and larger relative volume at pons and medulla oblongata in adulthood. Despite this heterogeneity, those with and without language delay showed significant commonality in morphometric features when contrasted with matched neurotypical individuals (n = 57). In ASC, better current language was associated with increased GM volume in bilateral temporal pole, superior temporal regions, dorsolateral fronto-parietal and cerebellar structures, and increased white matter volume in distributed frontal and insular regions. Furthermore, current language-neuroanatomy correlation patterns were similar across subgroups with or without language delay. High-functioning adult males with ASC show neuroanatomical variations associated with both developmental and current language characteristics. This underscores the importance of including both developmental and current language as specifiers for ASC, to help clarify heterogeneity.

Abnormal Brain Dynamics Underlie Speech Production in Children with Autism Spectrum Disorder

A large proportion of children with autism spectrum disorder (ASD) have speech and/or language difficulties. While a number of structural and functional neuroimaging methods have been used to explore the brain differences in ASD with regards to speech and language comprehension and production, the neurobiology of basic speech function in ASD has not been examined. Magnetoencephalography (MEG) is a neuroimaging modality with high spatial and temporal resolution that can be applied to the examination of brain dynamics underlying speech as it can capture the fast responses fundamental to this function. We acquired MEG from 21 children with high‐functioning autism (mean age: 11.43 years) and 21 age‐ and sex‐matched controls as they performed a simple oromotor task, a phoneme production task and a phonemic sequencing task. Results showed significant differences in activation magnitude and peak latencies in primary motor cortex (Brodmann Area 4), motor planning areas (BA 6), temporal sequencing and sensorimotor integration areas (BA 22/13) and executive control areas (BA 9). Our findings of significant functional brain differences between these two groups on these simple oromotor and phonemic tasks suggest that these deficits may be foundational and could underlie the language deficits seen in ASD. Autism Res2016, 9: 249–261. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Abnormal auditory and language pathways in children with 16p11.2 deletion

Copy number variations at chromosome 16p11.2 contribute to neurodevelopmental disorders, including autism spectrum disorder (ASD). This study seeks to improve our understanding of the biological basis of behavioral phenotypes common in ASD, in particular the prominent and prevalent disruption of spoken language seen in children with the 16p11.2 BP4–BP5 deletion. We examined the auditory and language white matter pathways with diffusion MRI in a cohort of 36 pediatric deletion carriers and 45 age-matched controls. Diffusion MR tractography of the auditory radiations and the arcuate fasciculus was performed to generate tract specific measures of white matter microstructure. In both tracts, deletion carriers exhibited significantly higher diffusivity than that of controls. Cross-sectional diffusion parameters in these tracts changed with age with no group difference in the rate of maturation. Within deletion carriers, the left-hemisphere arcuate fasciculus mean and radial diffusivities were significantly negatively correlated with clinical language ability, but not non-verbal cognitive ability. Diffusion metrics in the right-hemisphere arcuate fasciculus were not predictive of language ability. These results provide insight into the link between the 16p11.2 deletion, abnormal auditory and language pathway structures, and the specific behavioral deficits that may contribute to neurodevelopmental disorders such as ASD.

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We examined auditory and language white matter tracts in children with the 16p11.2 BP4–BP5 deletion.

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Diffusivity was enhanced in auditory radiation and arcuate fasciculus.

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Arcuate fasciculus microstructure was correlated with language ability in deletion carriers.

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There are correlations in the brain structure and behavioral phenotype in the 16p11.2 deletion carriers.

Possible functional links among brain- and skull-related genes selected in modern humans

The sequencing of the genomes from extinct hominins has revealed that changes in some brain-related genes have been selected after the split between anatomically-modern humans and Neanderthals/Denisovans. To date, no coherent view of these changes has been provided. Following a line of research we initiated in Boeckx and Benítez-Burraco (2014a), we hypothesize functional links among most of these genes and their products, based on the existing literature for each of the gene discussed. The genes we focus on are found mutated in different cognitive disorders affecting modern populations and their products are involved in skull and brain morphology, and neural connectivity. If our hypothesis turns out to be on the right track, it means that the changes affecting most of these proteins resulted in a more globular brain and ultimately brought about modern cognition, with its characteristic generativity and capacity to form and exploit cross-modular concepts, properties most clearly manifested in language.

Altered Cortical Thickness and Tract Integrity of the Mirror Neuron System and Associated Social Communication in Autism Spectrum Disorder

Previous studies using neural activity recording and neuroimaging techniques have reported functional deficits in the mirror neuron system (MNS) for individuals with autism spectrum disorder (ASD). However, a few studies focusing on gray and white matter structures of the MNS have yielded inconsistent results. The current study recruited adolescents and young adults with ASD (aged 15-26 years) and age-matched typically developing (TD) controls (aged 14-25 years). The cortical thickness (CT) and microstructural integrity of the tracts connecting the regions forming the classical MNS were investigated. High-resolution T1-weighted imaging and diffusion spectrum imaging were performed to quantify the CT and tract integrity, respectively. The structural covariance of the CT of the MNS regions revealed a weaker coordination of the MNS network in ASD. A strong correlation was found between the integrity of the right frontoparietal tracts and the social communication subscores measured by the Chinese version of the Social Communication Questionnaire. The results showed that there were no significant mean differences in the CTs and tract integrity between the ASD and TD groups, but revealed a moderate or even reverse age effect on the frontal MNS structures in ASD. In conclusion, aberrant structural coordination may be an underlying factor affecting the function of the MNS in ASD patients. The association between the right frontoparietal tracts and social communication performance implies a neural correlate of communication processing in the autistic brain. This study provides evidence of abnormal MNS structures and their influence on social communication in individuals with ASD.

Connectivity in Autism: A Review of MRI Connectivity Studies

Autism spectrum disorder (ASD) affects 1 in 50 children between the ages of 6 and 17 years. The etiology of ASD is not precisely known. ASD is an umbrella term, which includes both low- (IQ < 70) and high-functioning (IQ > 70) individuals. A better understanding of the disorder and how it manifests in individual subjects can lead to more effective intervention plans to fulfill the individual's treatment needs.Magnetic resonance imaging (MRI) is a non-invasive investigational tool that can be used to study the ways in which the brain develops or deviates from the typical developmental trajectory. MRI offers insights into the structure, function, and metabolism of the brain. In this article, we review published studies on brain connectivity changes in ASD using either resting state functional MRI or diffusion tensor imaging.The general findings of decreases in white matter integrity and in long-range neural coherence are well known in the ASD literature. Nevertheless, the detailed localization of these findings remains uncertain, and few studies link these changes in connectivity with the behavioral phenotype of the disorder. With the help of data sharing and large-scale analytic efforts, however, the field is advancing toward several convergent themes, including the reduced functional coherence of long-range intra-hemispheric cortico-cortical default mode circuitry, impaired inter-hemispheric regulation, and an associated, perhaps compensatory, increase in local and short-range cortico-subcortical coherence.

Increased left hemisphere impairment in high-functioning autism: a tract based spatial statistics study

There is evidence emerging from Diffusion Tensor Imaging (DTI) research that autism spectrum disorders (ASD) are associated with greater impairment in the left hemisphere. Although this has been quantified with volumetric region of interest analyses, it has yet to be tested with white matter integrity analysis. In the present study, tract based spatial statistics was used to contrast white matter integrity of 12 participants with high-functioning autism or Aspergers syndrome (HFA/AS) with 12 typically developing individuals. Fractional Anisotropy (FA) was examined, in addition to axial, radial and mean diffusivity (AD, RD and MD). In the left hemisphere, participants with HFA/AS demonstrated significantly reduced FA in predominantly thalamic and fronto-parietal pathways and increased RD. Symmetry analyses confirmed that in the HFA/AS group, WM disturbance was significantly greater in the left compared to right hemisphere. These findings contribute to a growing body of literature suggestive of reduced FA in ASD, and provide preliminary evidence for RD impairments in the left hemisphere.

Altered white matter connectivity as a neural substrate for social impairment in Autism Spectrum Disorder

BACKGROUND

Autism Spectrum Disorder (ASD) symptoms have been hypothesized to result from altered brain connectivity. The 'disconnectivity' hypothesis has been used to explain characteristic impairments in socio-emotional function, observed clinically in ASD. Here, we review the evidence for impaired white matter connectivity as a neural substrate for socio-emotional dysfunction in ASD. A review of diffusion tensor imaging (DTI) studies, and focused discussion of relevant post-mortem, structural, and functional neuroimaging studies, is provided.

METHODS

Studies were identified using a sensitive search strategy in MEDLINE, Embase and PsycINFO article databases using the OvidSP database interface. Search terms included database subject headings for the concepts of pervasive developmental disorders, and DTI. Seventy-two published DTI studies examining white matter microstructure in ASD were reviewed. A comprehensive discussion of DTI studies that examined white matter tracts linking socio-emotional structures is presented.

RESULTS

Several DTI studies reported microstructural differences indicative of developmental alterations in white matter organization, and potentially myelination, in ASD. Altered structure within long-range white matter tracts linking socio-emotional processing regions was implicated. While alterations of the uncinate fasciculus and frontal and temporal thalamic projections have been associated with social symptoms in ASD, few studies examined association of tract microstructure with core impairment in this disorder.

CONCLUSIONS

The uncinate fasciculus and frontal and temporal thalamic projections mediate limbic connectivity and integrate structures responsible for complex socio-emotional functioning. Impaired development of limbic connectivity may represent one neural substrate contributing to ASD social impairments. Future efforts to further elucidate the nature of atypical white matter development, and its relationship to core symptoms, may offer new insights into etiological mechanisms contributing to ASD impairments and uncover novel opportunities for targeted intervention.

Independent contribution of individual white matter pathways to language function in pediatric epilepsy patients

BACKGROUND AND PURPOSE

Patients with epilepsy and malformations of cortical development (MCDs) are at high risk for language and other cognitive impairment. Specific impairments, however, are not well correlated with the extent and locale of dysplastic cortex; such findings highlight the relevance of aberrant cortico-cortical interactions, or connectivity, to the clinical phenotype. The goal of this study was to determine the independent contribution of well-described white matter pathways to language function in a cohort of pediatric patients with epilepsy.

MATERIALS AND METHODS

Patients were retrospectively identified from an existing database of pediatric epilepsy patients with the following inclusion criteria: 1. diagnosis of MCDs, 2. DTI performed at 3 T, and 3. language characterized by a pediatric neurologist. Diffusion Toolkit and Trackvis (http://www.trackvis.org) were used for segmentation and analysis of the following tracts: corpus callosum, corticospinal tracts, inferior longitudinal fasciculi (ILFs), inferior fronto-occipital fasciculi (IFOFs), uncinate fasciculi (UFs), and arcuate fasciculi (AFs). Mean diffusivity (MD) and fractional anisotropy (FA) were calculated for each tract. Wilcoxon rank sum test (corrected for multiple comparisons) was used to assess potential differences in tract parameters between language-impaired and language-intact patients. In a separate analysis, a machine learning algorithm (random forest approach) was applied to measure the independent contribution of the measured diffusion parameters for each tract to the clinical phenotype (language impairment). In other words, the importance of each tract parameter was measured after adjusting for the contribution of all other tracts.

RESULTS

Thirty-three MCD patients were included (age range: 3-18 years). Twenty-one patients had intact language, twelve had language impairment. All tracts were identified bilaterally in all patients except for the AF, which was not identified on the right in 10 subjects and not identified on the left in 11 subjects. MD and/or FA within the left AF, UF, ILF, and IFOF differed between language-intact and language-impaired groups. However, only parameters related to the left uncinate, inferior fronto-occipital, and arcuate fasciculi were independently associated with the clinical phenotype.

CONCLUSIONS

Scalar metrics derived from the left uncinate, inferior fronto-occipital, and arcuate fasciculi were independently associated with language function. These results support the importance of these pathways in human language function in patients with MCDs.