Reduced lateralization of multiple functional brain networks in autistic males.

BACKGROUND: Autism spectrum disorder has been linked to a variety of organizational and developmental deviations in the brain. One such organizational difference involves hemispheric lateralization, which may be localized to language-relevant regions of the brain or distributed more broadly. METHODS: In the present study, we estimated brain hemispheric lateralization in autism based on each participant's unique functional neuroanatomy rather than relying on group-averaged data. Additionally, we explored potential relationships between the lateralization of the language network and behavioral phenotypes including verbal ability, language delay, and autism symptom severity. We hypothesized that differences in hemispheric asymmetries in autism would be limited to the language network, with the alternative hypothesis of pervasive differences in lateralization. We tested this and other hypotheses by employing a cross-sectional dataset of 118 individuals (48 autistic, 70 neurotypical). Using resting-state fMRI, we generated individual network parcellations and estimated network asymmetries using a surface area-based approach. A series of multiple regressions were then used to compare network asymmetries for eight significantly lateralized networks between groups. RESULTS: We found significant group differences in lateralization for the left-lateralized Language (d = -0.89), right-lateralized Salience/Ventral Attention-A (d = 0.55), and right-lateralized Control-B (d = 0.51) networks, with the direction of these group differences indicating less asymmetry in autistic males. These differences were robust across different datasets from the same participants. Furthermore, we found that language delay stratified language lateralization, with the greatest group differences in language lateralization occurring between autistic males with language delay and neurotypical individuals. CONCLUSIONS: These findings evidence a complex pattern of functional lateralization differences in autism, extending beyond the Language network to the Salience/Ventral Attention-A and Control-B networks, yet not encompassing all networks, indicating a selective divergence rather than a pervasive one. Moreover, we observed an association between Language network lateralization and language delay in autistic males.

ENIGMA's simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury.

Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.

Multimodal Analysis of Secondary Cerebellar Alterations After Pediatric Traumatic Brain Injury.

Importance: Traumatic brain injury (TBI) is known to cause widespread neural disruption in the cerebrum. However, less is known about the association of TBI with cerebellar structure and how such changes may alter executive functioning. Objective: To investigate alterations in subregional cerebellum volume and cerebral white matter microstructure after pediatric TBI and examine subsequent changes in executive function. Design, Setting, and Participants: This retrospective cohort study combined 12 data sets (collected between 2006 and 2020) from 9 sites in the Enhancing Neuroimaging Genetics Through Meta-Analysis Consortium Pediatric TBI working group in a mega-analysis of cerebellar structure. Participants with TBI or healthy controls (some with orthopedic injury) were recruited from trauma centers, clinics, and institutional trauma registries, some of which were followed longitudinally over a period of 0.7 to 1.9 years. Healthy controls were recruited from the surrounding community. Data analysis occurred from October to December 2022. Exposure: Accidental mild complicated-severe TBI (msTBI) for those in the TBI group. Some controls received a diagnosis of orthopedic injury. Main Outcomes and Measures: Volume of 18 cerebellar lobules and vermal regions were estimated from 3-dimensional T1-weighted magnetic resonance imaging (MRI) scans. White matter organization in 28 regions of interest was assessed with diffusion tensor MRI. Executive function was measured by parent-reported scores from the Behavior Rating Inventory of Executive Functioning. Results: A total of 598 children and adolescents (mean [SD] age, 14.05 [3.06] years; range, 5.45-19.70 years; 386 male participants [64.5%]; 212 female participants [35.5%]) were included in the study, with 314 participants in the msTBI group, and 284 participants in the non-TBI group (133 healthy individuals and 151 orthopedically injured individuals). Significantly smaller total cerebellum volume (d = -0.37; 95% CI, -0.52 to -0.22; P < .001) and subregional cerebellum volumes (eg, corpus medullare; d = -0.43; 95% CI, -0.58 to -0.28; P < .001) were observed in the msTBI group. These alterations were primarily seen in participants in the chronic phase (ie, >6 months postinjury) of injury (total cerebellar volume, d = -0.55; 95% CI, -0.75 to -0.35; P < .001). Smaller cerebellum volumes were associated with higher scores on the Behavior Rating Inventory of Executive Functioning Global Executive Composite score (ß = -208.9 mm3; 95% CI, -319.0 to -98.0 mm3; P = .008) and Metacognition Index score (ß = -202.5 mm3; 95% CI, -319.0 to -85.0 mm3; P = .02). In a subset of 185 participants with longitudinal data, younger msTBI participants exhibited cerebellum volume reductions (ß = 0.0052 mm3; 95% CI, 0.0013 to 0.0090 mm3; P = .01), and older participants slower growth rates. Poorer white matter organization in the first months postinjury was associated with decreases in cerebellum volume over time (ß=0.52 mm3; 95% CI, 0.19 to 0.84 mm3; P = .005). Conclusions and Relevance: In this cohort study of pediatric msTBI, our results demonstrated robust cerebellar volume alterations associated with pediatric TBI, localized to the posterior lobe. Furthermore, longitudinal cerebellum changes were associated with baseline diffusion tensor MRI metrics, suggesting secondary cerebellar atrophy. These results provide further understanding of secondary injury mechanisms and may point to new opportunities for intervention.

Tract- and gray matter- based spatial statistics show white matter and gray matter microstructural differences in autistic males.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental condition commonly studied in the context of early childhood. As ASD is a life-long condition, understanding the characteristics of brain microstructure from adolescence into adulthood and associations to clinical features is critical for improving outcomes across the lifespan. In the current work, we utilized Tract Based Spatial Statistics (TBSS) and Gray Matter Based Spatial Statistics (GBSS) to examine the white matter (WM) and gray matter (GM) microstructure in neurotypical (NT) and autistic males. Methods: Multi-shell diffusion MRI was acquired from 78 autistic and 81 NT males (12-to-46-years) and fit to the DTI and NODDI diffusion models. TBSS and GBSS were performed to analyze WM and GM microstructure, respectively. General linear models were used to investigate group and age-related group differences. Within the ASD group, relationships between WM and GM microstructure and measures of autistic symptoms were investigated. Results: All dMRI measures were significantly associated with age across WM and GM. Significant group differences were observed across WM and GM. No significant age-by-group interactions were detected. Within the ASD group, positive relationships with WM microstructure were observed with ADOS-2 Calibrated Severity Scores. Conclusion: Using TBSS and GBSS our findings provide new insights into group differences of WM and GM microstructure in autistic males from adolescence into adulthood. Detection of microstructural differences across the lifespan as well as their relationship to the level of autistic symptoms will deepen to our understanding of brain-behavior relationships of ASD and may aid in the improvement of intervention options for autistic adults.

Test-retest reliability of FreeSurfer-derived volume, area and cortical thickness from MPRAGE and MP2RAGE brain MRI images.

Background and purpose: Large MRI studies often pool data gathered from widely varying imaging sequences. Pooled data creates a potential source of variation in structural analyses which may cause misinterpretation of findings. The purpose of this study is to determine if data acquired using different scan sequences, head coils and scanners offers consistent structural measurements. Materials and methods: Participants (163 right-handed males: 82 typically developing controls, 81 participants with autism spectrum disorder) were scanned on the same day using an MPRAGE sequence with a 12-channel headcoil on a Siemens 3T Trio scanner and an MP2RAGE sequence with a 64-channel headcoil on a Siemens 3T Prisma scanner. Segmentation was performed using FreeSurfer to identify regions exhibiting variation between sequences on measures of volume, surface area, and cortical thickness. Intraclass correlation coefficient (ICC) and mean percent difference (MPD) were used as test-retest reproducibility measures. Results: ICC for total brain segmented volume yielded a 0.99 intraclass correlation, demonstrating high overall volumetric reproducibility. Comparison of individual regions of interest resulted in greater variation. Volumetric variability, although low overall, was greatest in the entorhinal cortex (ICC = 0.71), frontal (ICC = 0.60) and temporal (ICC = 0.60) poles. Surface area variability was greatest in the insula (ICC = 0.65), temporal (ICC = 0.64) and frontal (ICC = 0.68) poles. Cortical thickness was most variable in the frontal (ICC = 0.41) and temporal (ICC = 0.35) poles. Conclusion: Data collected on different scanners and head coils using MPRAGE and MP2RAGE are generally consistent for surface area and volume estimates. However, regional variability may constrain accuracy in some regions and cortical thickness measurements exhibit higher generalized variability.

Sex-dependent structure of socioemotional salience, executive control, and default mode networks in preschool-aged children with autism.

The structure of large-scale intrinsic connectivity networks is atypical in adolescents diagnosed with autism spectrum disorder (ASD or autism). However, the degree to which alterations occur in younger children, and whether these differences vary by sex, is unknown. We utilized structural magnetic resonance imaging (MRI) data from a sex- and age- matched sample of 122 autistic and 122 typically developing (TD) children (2-4 years old) to investigate differences in underlying network structure in preschool-aged autistic children within three large scale intrinsic connectivity networks implicated in ASD: the Socioemotional Salience, Executive Control, and Default Mode Networks. Utilizing structural covariance MRI (scMRI), we report network-level differences in autistic versus TD children, and further report preliminary findings of sex-dependent differences within network topology.

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.

Diagnosis and Management of Suspected Pediatric Autoimmune Encephalitis: A Comprehensive, Multidisciplinary Approach and Review of Literature.

Autoimmune encephalitis is an increasingly recognized entity in children. When treated promptly, favorable outcomes are seen in a majority of pediatric patients. However, recognition of autoimmune encephalitis in young patients is challenging. Once autoimmune encephalitis is suspected, additional difficulties exist regarding timing of treatment initiation and duration of treatment, as evidence to guide management of these patients is emerging. Here, we review available literature regarding pediatric autoimmune encephalitis and present our institution's comprehensive approach to the evaluation and management of the disease. These guidelines were developed through an iterative process involving both pediatric neurologists and rheumatologists.

White Matter Disruption in Pediatric Traumatic Brain Injury: Results from ENIGMA Pediatric Moderate to Severe Traumatic Brain Injury.

OBJECTIVE: Our study addressed aims: (1) test the hypothesis that moderate-severe TBI in pediatric patients is associated with widespread white matter (WM) disruption; (2) test the hypothesis that age and sex impact WM organization after injury; and (3) examine associations between WM organization and neurobehavioral outcomes. METHODS: Data from ten previously enrolled, existing cohorts recruited from local hospitals and clinics were shared with the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Pediatric msTBI working group. We conducted a coordinated analysis of diffusion MRI (dMRI) data using the ENIGMA dMRI processing pipeline. RESULTS: Five hundred and seven children and adolescents (244 with complicated mild to severe TBI [msTBI] and 263 controls) were included. Patients were clustered into three post-injury intervals: acute/subacute - <2 months, post-acute - 2-6 months, chronic - 6+ months. Outcomes were dMRI metrics and post-injury behavioral problems as indexed by the Child Behavior Checklist (CBCL). Our analyses revealed altered WM diffusion metrics across multiple tracts and all post-injury intervals (effect sizes ranging between d=-0.5 to -1.3). Injury severity is a significant contributor to the extent of WM alterations but explained less variance in dMRI measures with increasing time post-injury. We observed a sex-by-group interaction: females with TBI had significantly lower fractional anisotropy in the uncinate fasciculus than controls (𝞫=0.043), which coincided with more parent-reported behavioral problems (𝞫=-0.0027). CONCLUSIONS: WM disruption after msTBI is widespread, persistent, and influenced by demographic and clinical variables. Future work will test techniques for harmonizing neurocognitive data, enabling more advanced analyses to identify symptom clusters and clinically-meaningful patient subtypes.

A 16-year study of longitudinal volumetric brain development in males with autism.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with unknown brain etiology. Our knowledge to date about structural brain development across the lifespan in ASD comes mainly from cross-sectional studies, thereby limiting our understanding of true age effects within individuals with the disorder that can only be gained through longitudinal research. The present study describes FreeSurfer-derived volumetric findings from a longitudinal dataset consisting of 607 T1-weighted magnetic resonance imaging (MRI) scans collected from 105 male individuals with ASD (349 MRIs) and 125 typically developing male controls (258 MRIs). Participants were six to forty-five years of age at their first scan, and were scanned up to 5 times over a period of 16 years (average inter-scan interval of 3.7 years). Atypical age-related volumetric trajectories in ASD included enlarged gray matter volume in early childhood that approached levels of the control group by late childhood, an age-related increase in ventricle volume resulting in enlarged ventricles by early adulthood and reduced corpus callosum age-related volumetric increase resulting in smaller corpus callosum volume in adulthood. Larger corpus callosum volume was related to a lower (better) ADOS score at the most recent study visit for the participants with ASD. These longitudinal findings expand our knowledge of volumetric brain-based abnormalities in males with ASD, and highlight the need to continue to examine brain structure across the lifespan and well into adulthood.

Challenges and opportunities for neuroimaging in young patients with traumatic brain injury: a coordinated effort towards advancing discovery from the ENIGMA pediatric moderate/severe TBI group.

Traumatic brain injury (TBI) is a major cause of death and disability in children in both developed and developing nations. Children and adolescents suffer from TBI at a higher rate than the general population, and specific developmental issues require a unique context since findings from adult research do not necessarily directly translate to children. Findings in pediatric cohorts tend to lag behind those in adult samples. This may be due, in part, both to the smaller number of investigators engaged in research with this population and may also be related to changes in safety laws and clinical practice that have altered length of hospital stays, treatment, and access to this population. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Pediatric Moderate/Severe TBI (msTBI) group aims to advance research in this area through global collaborative meta-analysis of neuroimaging data. In this paper, we discuss important challenges in pediatric TBI research and opportunities that we believe the ENIGMA Pediatric msTBI group can provide to address them. With the paucity of research studies examining neuroimaging biomarkers in pediatric patients with TBI and the challenges of recruiting large numbers of participants, collaborating to improve statistical power and to address technical challenges like lesions will significantly advance the field. We conclude with recommendations for future research in this field of study.

Changes in the Auditory Association Cortex in Dementing Illnesses.

OBJECTIVE: To evaluate the relationship between degree of cognitive impairment and gray-matter density changes in the auditory cortex. STUDY DESIGN: Retrospective case-control. PATIENTS: Six hundred sixty-three patients of a tertiary referral center cognitive disorders clinic. INTERVENTION: Magnetic resonance imaging. MAIN OUTCOME MEASURES: Ratios of gray matter density of the primary auditory cortex (A1) to whole brain and auditory association cortex (AAC) to whole brain in patients with Alzheimer's disease (AD) compared with mild cognitive impairment (MCI) and patients with a mini-mental state exam (MMSE) scores ≤25 versus >25. RESULTS: After multivariate analysis, a statistically significant difference between AAC to brain ratios for patients with a MMSE ≤25 (n = 325) compared with >25 (n = 269) was found, with values -0.03 (95% CI -0.04 to -0.02, p < 0.0001) on the left and -0.04 (95% CI -0.06 to -0.03, p < 0.0001) on the right. The adjusted average difference of left and right AAC to brain ratios between AD patients (n = 218) compared with MCI patients (n = 121) was also statistically significant, at -0.03 (95% CI -0.05 to -0.01, p = 0.004) and -0.05 (95% CI -0.07 to -0.03, p < 0.0001), respectively. There was no statistically significant difference in the left or right A1 to brain ratios between the MMSE groups or between the AD and MCI groups. CONCLUSIONS: The AAC for patients with MMSE ≤25 and for those with AD shows decreased gray matter density when compared with patients with better cognitive function. No difference was detected in A1, raising the possibility that patients may have intact neural hearing, but impaired ability to interpret sounds.

Targeted gene panel sequencing for the rapid diagnosis of acutely ill infants.

BACKGROUND: Exome/genome sequencing (ES/GS) have been recently used in neonatal and pediatric/cardiac intensive care units (NICU and PICU/CICU) to diagnose and care for acutely ill infants, but the effectiveness of targeted gene panels for these purposes remains unknown. METHODS: RapSeq, a newly developed panel targeting 4,503 disease-causing genes, was employed on selected patients in our NICU/PICU/CICU. Twenty trios were sequenced from October 2015 to March 2017. We assessed diagnostic yield, turnaround times, and clinical consequences. RESULTS: A diagnosis was made in 10/20 neonates (50%); eight had de novo variants (ASXL1, CHD, FBN1, KMT2D, FANCB, FLNA, PAX3), one was a compound heterozygote for CHAT, and one had a maternally inherited GNAS variant. Preliminary reports were generated by 9.6 days (mean); final reports after Sanger sequencing at 16.3 days (mean). In all positive infants, the diagnosis changed management. In a case with congenital myasthenia, diagnosis and treatment occurred at 17 days versus 7 months in a historical control. CONCLUSIONS: This study shows that a gene panel that includes the majority of known disease-causing genes can rapidly identify a diagnosis in a large number of tested infants. Due to simpler deployment and interpretation and lower costs, this approach might represent an alternative to ES/GS in the NICU/PICU/CICU.

Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale.

The identification of autistic individuals using resting state functional connectivity networks can provide an objective diagnostic method for autism spectrum disorder (ASD). The present state-of-the-art machine learning model using deep learning has a classification accuracy of 70.2% on the ABIDE (Autism Brain Imaging Data Exchange) data set. In this paper, we explore the utility of topological features in the classification of ASD versus typically developing control subjects. These topological features have been shown to provide a complementary source of discriminative information in applications such as 2D object classification and social network analysis. We evaluate the performance of three different representations of topological features - persistence diagrams, persistence images, and persistence landscapes - for autism classification using neural networks, support vector machines and random forests. We also propose a hybrid approach of augmenting topological features with functional correlations, which typically outperforms the models that use functional correlations alone. With this approach, even with a simple 3-layer neural network, we are able to achieve a classification accuracy of 69.2% on the ABIDE data set. However, our experiments also show that the improvement due to topological features is not always statistically significant. Therefore, we offer a cautionary tale to the practitioners regarding the limited discriminative power of topological features derived from fMRI data for the classification of autism.

Beery VMI and Brain Volumetric Relations in Autism Spectrum Disorder.

Although diminished proficiency on tasks that require visual-motor integration (VMI) has been reported in individuals with autism spectrum disorder (ASD), very few studies have examined the association between VMI performance and neuroanatomical regions of interest (ROI) involved in motor and perceptual functioning. To address these issues, the current study included an all-male sample of 41 ASD (ages 3-23 years) and 27 typically developing (TD) participants (ages 5-26 years) who completed the Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery VMI) as part of a comprehensive neuropsychological battery. All participants underwent 3.0 T magnetic resonance imaging (MRI) with image quantification (FreeSurfer software v5.3). The groups were statistically matched on age, handedness, and intracranial volume (ICV). ASD participants performed significantly lower on VMI and IQ measures compared with the TD group. VMI performance was significantly correlated with FSIQ and PIQ in the TD group only. No pre-defined neuroanatomical ROIs were significantly different between groups. Significant correlations were observed in the TD group between VMI and total precentral gyrus gray matter volume (r = .51, p = .006) and total frontal lobe gray matter volume (r = .46, p = .017). There were no significant ROI correlations with Beery VMI performance in ASD participants. At the group level, despite ASD participants exhibiting reduced visuomotor abilities, no systematic relation with motor or sensory-perceptual ROIs was observed. In the TD group, results were consistent with the putative role of the precentral gyrus in motor control along with frontal involvement in planning, organization, and execution monitoring, all essential for VMI performance. Given that similar associations between VMI and ROIs were not observed in those with ASD, neurodevelopment in ASD group participants may not follow homogenous patterns making correlations in these brain regions unlikely to be observed.

Social Responsiveness Scale (SRS) in Relation to Longitudinal Cortical Thickness Changes in Autism Spectrum Disorder.

The relationship between brain development and clinical heterogeneity in autism (ASD) is unknown. This study examines the Social Responsiveness Scale (SRS) in relation to the longitudinal development of cortical thickness. Participants (N = 91 ASD, N = 56 TDC; 3-39 years at first scan) were scanned up to three times over a 7-year period. Mixed-effects models examined cortical thickness in relation to SRS score. ASD participants with higher SRS scores showed regionally increased age-related cortical thinning. Regional thickness differences and reduced age-related cortical thinning were found in predominantly right lateralized regions in ASD with decreasing SRS scores over time. Our findings emphasize the importance of examining clinical phenotypes in brain-based studies of ASD.

Riemannian Regression and Classification Models of Brain Networks Applied to Autism.

Functional connectivity from resting-state functional MRI (rsfMRI) is typically represented as a symmetric positive definite (SPD) matrix. Analysis methods that exploit the Riemannian geometry of SPD matrices appropriately adhere to the positive definite constraint, unlike Euclidean methods. Recently proposed approaches for rsfMRI analysis have achieved high accuracy on public datasets, but are computationally intensive and difficult to interpret. In this paper, we show that we can get comparable results using connectivity matrices under the log-Euclidean and affine-invariant Riemannian metrics with relatively simple and interpretable models. On ABIDE Preprocessed dataset, our methods classify autism versus control subjects with 71.1% accuracy. We also show that Riemannian methods beat baseline in regressing connectome features to subject autism severity scores.

Evaluation of Differences in Temporal Synchrony Between Brain Regions in Individuals With Autism and Typical Development.

Importance: Despite reports of widespread but heterogeneous atypicality of functional connectivity in individuals with autism, little is known regarding the temporal dynamics of functional brain connections and how they relate to autistic traits. Objective: To investigate differences in temporal synchrony between brain regions in individuals with autism and those with typical development. Design, Setting, and Participants: This cohort study, conducted at the University of Utah, included 90 adolescent and adult male participants. A larger sample from the multisite Autism Brain Imaging Data Exchange (ABIDE) was also used as a replication sample. The study includes data acquired between December 2016 and April 2018. Aggregate data included in the replication sample were released to the public in August 2012 (ABIDE I) and June 2016 (ABIDE II). Data analysis were conducted between January 2018 and April 2018. Exposures: Male individuals diagnosed as having autism (n = 52) and typically developing male individuals (n = 38). Main Outcomes and Measures: Long duration (30 minutes/individual) of multiband, multiecho functional magnetic resonance imaging was acquired to estimate functional connectivity between brain regions. Sustained connectivity, a measure of functional connectivity duration, as well as lagged temporal dynamics related to functional connectivity, were compared between groups for 361 gray matter regions of interest and a 17-network parcellation. Lagged findings were replicated in the larger ABIDE sample (n = 1402). Sustained connectivity findings were also associated with behavioral and cognitive variables. Results: In 52 males with autism (mean [SD] age, 27.73 [8.66] years) and 38 control males with typical development (mean [SD] age, 27.09 [7.49] years), increases in both sustained and functional connectivity at several lags were found in individuals with autism compared with the control group. Group differences in functional connectivity were replicated in the larger ABIDE data set at a 6-second lag. Measures of symptom severity in individuals with autism were positively associated with sustained connectivity values. In the control group, sustained connectivity was negatively associated with cognitive processing. A replication sample (n = 1402) composed of 579 individuals with autism (80 female and 499 male; mean [SD] age, 15.08 [6.89] years) and 823 in the control group (211 female and 612 male; mean [SD] age, 15.06 [6.79] years) from the ABIDE data set was also analyzed. Conclusions and Relevance: Whereas the magnitude of functional connectivity in autism is variable across brain regions, participant samples, and development, prolonged temporal synchrony of functional connections is reproducibly observed in autism, suggesting a potential mechanism for core symptoms.

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

The thalamus is a key sensorimotor relay area that is implicated in autism spectrum disorder (ASD). However, it is unknown how the thalamus and white-matter structures that contain thalamo-cortical fiber connections (e.g., the internal capsule) develop from childhood into adulthood and whether this microstructure relates to basic motor challenges in ASD. We used diffusion weighted imaging in a cohort-sequential design to assess longitudinal development of the thalamus, and posterior- and anterior-limbs of the internal capsule (PLIC and ALIC, respectively) in 89 males with ASD and 56 males with typical development (3-41 years; all verbal). Our results showed that the group with ASD exhibited different developmental trajectories of microstructure in all regions, demonstrating childhood group differences that appeared to approach and, in some cases, surpass the typically developing group in adolescence and adulthood. The PLIC (but not ALIC nor thalamus) mediated the relation between age and finger-tapping speed in both groups. Yet, the gap in finger-tapping speed appeared to widen at the same time that the between-group gap in the PLIC appeared to narrow. Overall, these results suggest that childhood group differences in microstructure of the thalamus and PLIC become less robust in adolescence and adulthood. Further, finger-tapping speed appears to be mediated by the PLIC in both groups, but group differences in motor speed that widen during adolescence and adulthood suggest that factors beyond the microstructure of the thalamus and internal capsule may contribute to atypical motor profiles in ASD. Autism Res 2018, 11: 450-462. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Microstructure of the thalamus, a key sensory and motor brain area, appears to develop differently in individuals with autism spectrum disorder (ASD). Microstructure is important because it informs us of the density and organization of different brain tissues. During childhood, thalamic microstructure was distinct in the ASD group compared to the typically developing group. However, these group differences appeared to narrow with age, suggesting that the thalamus continues to dynamically change in ASD into adulthood.