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.

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 individuals. 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 individuals with language delay and neurotypical individuals.

Limitations

The generalizability of our findings is restricted due to the male-only sample and greater representation of individuals with high verbal and cognitive performance.

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. Furthermore, a differential relationship was identified between Language network lateralization and specific symptom profiles (namely, language delay) of autism.

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.

Gray matter microstructure differences in autistic males: A gray matter based spatial statistics study

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition. Understanding the brain's microstructure and its relationship to clinical characteristics is important to advance our understanding of the neural supports underlying ASD. In the current work, we implemented Gray-Matter Based Spatial Statistics (GBSS) to examine and characterize cortical microstructure and assess differences between typically developing (TD) and autistic males.

METHODS

A multi-shell diffusion MRI (dMRI) protocol was acquired from 83 TD and 70 autistic males (5-to-21-years) and fit to the DTI and NODDI models. GBSS was performed for voxelwise analysis of cortical gray matter (GM). General linear models were used to investigate group differences, while age-by-group interactions assessed age-related differences between groups. Within the ASD group, relationships between cortical microstructure and measures of autistic symptoms were investigated.

RESULTS

All dMRI measures were significantly associated with age across the GM skeleton. Group differences and age-by-group interactions are reported. Group-wise increases in neurite density in autistic individuals were observed across frontal, temporal, and occipital regions of the right hemisphere. Significant age-by-group interactions of neurite density were observed within the middle frontal gyrus, precentral gyrus, and frontal pole. Negative relationships between neurite dispersion and the ADOS-2 Calibrated Severity Scores (CSS) were observed within the ASD group.

DISCUSSION

Findings demonstrate group and age-related differences between groups in neurite density in ASD across right-hemisphere brain regions supporting cognitive processes. Results provide evidence of altered neurodevelopmental processes affecting GM microstructure in autistic males with implications for the role of cortical microstructure in the level of autistic symptoms.

CONCLUSION

Using dMRI and GBSS, our findings provide new insights into group and age-related differences of the GM microstructure in autistic males. Defining where and when these cortical GM differences arise will contribute to our understanding of brain-behavior relationships of ASD and may aid in the development and monitoring of targeted and individualized interventions.

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.

Evidence for normal extra-axial cerebrospinal fluid volume in autistic males from middle childhood to adulthood

Autism spectrum disorder has long been associated with a variety of organizational and developmental abnormalities in the brain. An increase in extra-axial cerebrospinal fluid volume in autistic individuals between the ages of 6 months and 4 years has been reported in recent studies. Increased extra-axial cerebrospinal fluid volume was predictive of the diagnosis and severity of the autistic symptoms in all of them, irrespective of genetic risk for developing the disorder. In the present study, we explored the trajectory of extra-axial cerebrospinal fluid volume from childhood to adulthood in both autism and typical development. We hypothesized that an elevated extra-axial cerebrospinal fluid volume would be found in autism persisting throughout the age range studied. We tested the hypothesis by employing an accelerated, multi-cohort longitudinal data set of 189 individuals (97 autistic, 92 typically developing). Each individual had been scanned between 1 and 5 times, with scanning sessions separated by 2-3 years, for a total of 439 T1-weighted MRI scans. A linear mixed-effects model was used to compare developmental, age-related changes in extra-axial cerebrospinal fluid volume between groups. Inconsistent with our hypothesis, we found no group differences in extra-axial cerebrospinal fluid volume in this cohort of individuals 3 to 42 years of age. Our results suggest that extra-axial cerebrospinal fluid volume in autistic individuals is not increased compared with controls beyond four years of age.

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.

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.

Generalizability and reproducibility of functional connectivity in autism

Background

Autism is hypothesized to represent a disorder of brain connectivity, yet patterns of atypical functional connectivity show marked heterogeneity across individuals.

Methods

We used a large multi-site dataset comprised of a heterogeneous population of individuals with autism and typically developing individuals to compare a number of resting-state functional connectivity features of autism. These features were also tested in a single site sample that utilized a high-temporal resolution, long-duration resting-state acquisition technique.

Results

No one method of analysis provided reproducible results across research sites, combined samples, and the high-resolution dataset. Distinct categories of functional connectivity features that differed in autism such as homotopic, default network, salience network, long-range connections, and corticostriatal connectivity, did not align with differences in clinical and behavioral traits in individuals with autism. One method, lag-based functional connectivity, was not correlated to other methods in describing patterns of resting-state functional connectivity and their relationship to autism traits.

Conclusion

Overall, functional connectivity features predictive of autism demonstrated limited generalizability across sites, with consistent results only for large samples. Different types of functional connectivity features do not consistently predict different symptoms of autism. Rather, specific features that predict autism symptoms are distributed across feature types.

Electronic supplementary material

The online version of this article (10.1186/s13229-019-0273-5) contains supplementary material, which is available to authorized users.

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.

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.

Robust Motion Correction Strategy for Structural MRI in Unsedated Children Demonstrated with Three-dimensional Radial MPnRAGE

Purpose To develop and evaluate a retrospective method to minimize motion artifacts in structural MRI. Materials and Methods The motion-correction strategy was developed for three-dimensional radial data collection and demonstrated with MPnRAGE, a technique that acquires high-resolution volumetric magnetization-prepared rapid gradient-echo, or MPRAGE, images with multiple tissue contrasts. Forty-four pediatric participants (32 with autism spectrum disorder [mean age ± standard deviation, 13 years ± 3] and 12 age-matched control participants [mean age, 12 years ± 3]) were imaged without sedation. Images with and images without retrospective motion correction were scored by using a Likert scale (0-4 for unusable to excellent) by two experienced neuroradiologists. The Tenengrad metric (a reference-free measure of image sharpness) and statistical analyses were performed to determine the effects of performing retrospective motion correction. Results MPnRAGE T1-weighted images with retrospective motion correction were all judged to have good or excellent quality. In some cases, retrospective motion correction improved the image quality from unusable (Likert score of 0) to good (Likert score of 3). Overall, motion correction improved mean Likert scores from 3.0 to 3.8 and reduced standard deviations from 1.1 to 0.4. Image quality was significantly improved with motion correction (Mann-Whitney U test; P < .001). Intraclass correlation coefficients for absolute agreement of Tenengrad scores with reviewers 1 and 2 were 0.92 and 0.88 (P < .0005 for both), respectively. In no cases did the retrospective motion correction induce severe image degradation. Conclusion Retrospective motion correction of MPnRAGE data were shown to be highly effective for consistently improving image quality of T1-weighted MRI in unsedated pediatric participants, while also enabling multiple tissue contrasts to be reconstructed for structural analysis. © RSNA, 2018 Online supplemental material is available for this article.

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.

Auditory attention in autism spectrum disorder: An exploration of volumetric magnetic resonance imaging findings

Studies have shown that individuals with autism spectrum disorder (ASD) tend to perform significantly below typically developing individuals on standardized measures of attention, even when controlling for IQ. The current study sought to examine within ASD whether anatomical correlates of attention performance differed between those with average to above-average IQ (AIQ group) and those with low-average to borderline ability (LIQ group) as well as in comparison to typically developing controls (TDC). Using automated volumetric analyses, we examined regional volume of classic attention areas including the superior frontal gyrus, anterior cingulate cortex, and precuneus in ASD AIQ (n = 38) and LIQ (n = 18) individuals along with 30 TDC. Auditory attention performance was assessed using subtests of the Test of Memory and Learning (TOMAL) compared among the groups and then correlated with regional brain volumes. Analyses revealed group differences in attention. The three groups did not differ significantly on any auditory attention-related brain volumes; however, trends toward significant size-attention function interactions were observed. Negative correlations were found between the volume of the precuneus and auditory attention performance for the AIQ ASD group, indicating larger volume related to poorer performance. Implications for general attention functioning and dysfunctional neural connectivity in ASD are discussed.

Relationship between brain stem volume and aggression in children diagnosed with autism spectrum disorder

BACKGROUND

Aggressive behaviors are common in individuals diagnosed with autism spectrum disorder (ASD) and may be phenotypic indicators of different subtypes within ASD. In current research literature for non-ASD samples, aggression has been linked to several brain structures associated with emotion and behavioral control. However, few if any studies exist investigating brain volume differences in individuals with ASD who have comorbid aggression as indicated by standardized diagnostic and behavioral measures.

METHOD

We examined neuroimaging data from individuals rigorously diagnosed with ASD versus typically developing (TD) controls. We began with data from brain volume regions of interest (ROI) taken from previous literature on aggression including the brainstem, amygdala, orbitofrontal cortex, anterior cingulate cortex, and dorsolateral prefrontal cortex. We defined aggression status using the Irritability subscale of the Aberrant Behavior Checklist and used lasso logistic regression to select among these predictor variables. Brainstem volume was the only variable shown to be a predictor of aggression status.

RESULTS

We found that smaller brainstem volumes are associated with higher odds of being in the high aggression group.

CONCLUSIONS

Understanding brain differences in individuals with ASD who engage in aggressive behavior from those with ASD who do not can inform treatment approaches. Future research should investigate brainstem structure and function in ASD to identify possible mechanisms related to arousal and aggression.

Multivariate characterization of white matter heterogeneity in autism spectrum disorder

The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important for interpreting and understanding the neurobiological mechanisms of autism. In the present study, we utilize the Mahalanobis distance, a multidimensional counterpart of the Euclidean distance, as an informative index to characterize individual brain variation and deviation in autism. Longitudinal diffusion tensor imaging data from 149 participants (92 diagnosed with autism spectrum disorder and 57 typically developing controls) between 3.1 and 36.83 years of age were acquired over a roughly 10-year period and used to construct the Mahalanobis distance from regional measures of white matter microstructure. Mahalanobis distances were significantly greater and more variable in the autistic individuals as compared to control participants, demonstrating increased atypicalities and variation in the group of individuals diagnosed with autism spectrum disorder. Distributions of multivariate measures were also found to provide greater discrimination and more sensitive delineation between autistic and typically developing individuals than conventional univariate measures, while also being significantly associated with observed traits of the autism group. These results help substantiate autism as a truly heterogeneous neurodevelopmental disorder, while also suggesting that collectively considering neuroimaging measures from multiple brain regions provides improved insight into the diversity of brain measures in autism that is not observed when considering the same regions separately. Distinguishing multidimensional brain relationships may thus be informative for identifying neuroimaging-based phenotypes, as well as help elucidate underlying neural mechanisms of brain variation in autism spectrum disorders.

MMPI-2 Personality Profiles of High-Functioning Adults With Autism Spectrum Disorders

The Minnesota Multiphasic Personality Inventory-Second Edition was administered to 20 adults with autism spectrum disorders (ASD) who fell in the average to above average range of intelligence and 24 age-, intelligence-, and gender-matched college students. Large group differences, with the ASD group scoring higher, were found on the L validity scale, Clinical Scales 2 (D) and 0 (Si), Content scale Social Discomfort (SOD), Supplementary scale Repression (R), and Personality Psychopathology Five (PSY-5) scale INTR (Introversion). The proportion of ASD adults scoring in the clinical range on these scales was between 25% and 35%. High scores on these scales are consistent with the clinical picture of Asperger syndrome and high-functioning autism in adulthood. Future directions and implications for identifying adults in need of a specialized autism assessment are discussed.

Investigating the Microstructural Correlation of White Matter in Autism Spectrum Disorder

White matter microstructure forms a complex and dynamical system that is critical for efficient and synchronized brain function. Neuroimaging findings in children with autism spectrum disorder (ASD) suggest this condition is associated with altered white matter microstructure, which may lead to atypical macroscale brain connectivity. In this study, we used diffusion tensor imaging measures to examine the extent that white matter tracts are interrelated within ASD and typical development. We assessed the strength of inter-regional white matter correlations between typically developing and ASD diagnosed individuals. Using hierarchical clustering analysis, clustering patterns of the pairwise white matter correlations were constructed and revealed to be different between the two groups. Additionally, we explored the use of graph theory analysis to examine the characteristics of the patterns formed by inter-regional white matter correlations and compared these properties between ASD and typical development. We demonstrate that the ASD sample has significantly less coherence in white matter microstructure across the brain compared to that in the typical development sample. The ASD group also presented altered topological characteristics, which may implicate less efficient brain networking in ASD. These findings highlight the potential of graph theory based network characteristics to describe the underlying networks as measured by diffusion magnetic resonance imaging and furthermore indicates that ASD may be associated with altered brain network characteristics. Our findings are consistent with those of a growing number of studies and hypotheses that have suggested disrupted brain connectivity in ASD.

Longitudinal development of manual motor ability in autism spectrum disorder from childhood to mid-adulthood relates to adaptive daily living skills

Many individuals with autism spectrum disorder (ASD) exhibit motor difficulties, but it is unknown whether manual motor skills improve, plateau, or decline in ASD in the transition from childhood into adulthood. Atypical development of manual motor skills could impact the ability to learn and perform daily activities across the life span. This study examined longitudinal grip strength and finger tapping development in individuals with ASD (n = 90) compared to individuals with typical development (n = 56), ages 5 to 40 years old. We further examined manual motor performance as a possible correlate of current and future daily living skills. The group with ASD demonstrated atypical motor development, characterized by similar performance during childhood but increasingly poorer performance from adolescence into adulthood. Grip strength was correlated with current adaptive daily living skills, and Time 1 grip strength predicted daily living skills eight years into the future. These results suggest that individuals with ASD may experience increasingly more pronounced motor difficulties from adolescence into adulthood and that manual motor performance in ASD is related to adaptive daily living skills.

Confirmation of the Factor Structure and Measurement Invariance of the Children's Scale of Hostility and Aggression: Reactive/Proactive in Clinic-Referred Children With and Without Autism Spectrum Disorder

OBJECTIVE

The measurement of aggression in its different forms (e.g., physical and verbal) and functions (e.g., impulsive and instrumental) is given little attention in subjects with developmental disabilities (DD). In this study, we confirm the factor structure of the Children's Scale for Hostility and Aggression: Reactive/Proactive (C-SHARP) and demonstrate measurement invariance (consistent performance across clinical groups) between clinic-referred groups with and without autism spectrum disorder (ASD). We also provide evidence of the construct validity of the C-SHARP.

METHODS

Caregivers provided C-SHARP, Child Behavior Checklist (CBCL), and Proactive/Reactive Rating Scale (PRRS) ratings for 644 children, adolescents, and young adults 2-21 years of age. Five types of measurement invariance were evaluated within a confirmatory factor analytic framework. Associations among the C-SHARP, CBCL, and PRRS were explored.

RESULTS

The factor structure of the C-SHARP had a good fit to the data from both groups, and strict measurement invariance between ASD and non-ASD groups was demonstrated (i.e., equivalent structure, factor loadings, item intercepts and residuals, and latent variance/covariance between groups). The C-SHARP Problem Scale was more strongly associated with CBCL Externalizing than with CBCL Internalizing, supporting its construct validity. Subjects classified with the PRRS as both Reactive and Proactive had significantly higher C-SHARP Proactive Scores than those classified as Reactive only, who were rated significantly higher than those classified by the PRRS as Neither Reactive nor Proactive. A similar pattern was observed for the C-SHARP Reactive Score.

CONCLUSIONS

This study provided evidence of the validity of the C-SHARP through confirmation of its factor structure and its relationship with more established scales. The demonstration of measurement invariance demonstrates that differences in C-SHARP factor scores were the result of differences in the construct rather than to error or unmeasured/nuisance variables. These data suggest that the C-SHARP is useful for quantifying subtypes of aggressive behavior in children, adolescents, and young adults with DD.

Mesial temporal lobe and memory function in autism spectrum disorder: an exploration of volumetric findings

Studies have shown that individuals with autism spectrum disorder (ASD) tend to perform significantly below typical developing individuals on standardized measures of memory, even when not significantly different on measures of IQ. The current study sought to examine within ASD whether anatomical correlates of memory performance differed between those with average-to-above-average IQ (AIQ group) and those with low-average to borderline ability (LIQ group) as well as in relations to typically developing comparisons (TDC). Using automated volumetric analyses, we examined regional volume of classic memory areas including the hippocampus, parahippocampal gyrus, entorhinal cortex, and amygdala in an all-male sample AIQ (n = 38) and LIQ (n = 18) individuals with ASD along with 30 typically developing comparisons (TDC). Memory performance was assessed using the Test of Memory and Learning (TOMAL) compared among the groups and then correlated with regional brain volumes. Analyses revealed group differences on almost all facets of memory and learning as assessed by the various subtests of the TOMAL. The three groups did not differ on any region of interest (ROI) memory-related brain volumes. However, significant size-memory function interactions were observed. Negative correlations were found between the volume of the amygdala and composite, verbal, and delayed memory indices for the LIQ ASD group, indicating larger volume related to poorer performance. Implications for general memory functioning and dysfunctional neural connectivity in ASD are discussed.

Beery VMI performance in autism spectrum disorder

Few studies have examined the visuomotor integration (VMI) abilities of individuals with autism spectrum disorder (ASD). An all-male sample consisting of 56 ASD participants (ages 3-23 years) and 36 typically developing (TD) participants (ages 4-26 years) completed the Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery VMI) as part of a larger neuropsychological battery. Participants were also administered standardized measures of intellectual functioning and the Social Responsiveness Scale (SRS), which assesses autism and autism-like traits. The ASD group performed significantly lower on the Beery VMI and on all IQ measures compared to the TD group. VMI performance was significantly correlated with full scale IQ (FSIQ), performance IQ (PIQ), and verbal IQ (VIQ) in the TD group only. However, when FSIQ was taken into account, no significant Beery VMI differences between groups were observed. Only one TD participant scored 1.5 standard deviations (SDs) below the Beery VMI normative sample mean, in comparison to 21% of the ASD sample. As expected, the ASD group was rated as having significantly higher levels of social impairment on the SRS compared to the TD group across all major domains. However, level of functioning on the SRS was not associated with Berry VMI performance. These findings demonstrate that a substantial number of individuals with ASD experience difficulties compared to TD in performing VMI-related tasks, and that VMI is likely affected by general cognitive ability. The fact that lowered Beery VMI performance occurred only within a subset of individuals with ASD and did not correlate with SRS would indicate that visuomotor deficits are not a core feature of ASD, even though they present at a higher rate of impairment than observed in TD participants.

WIDE RANGE ACHIEVEMENT TEST IN AUTISM SPECTRUM DISORDER: TEST-RETEST STABILITY

The principal goal of this descriptive study was to establish the test-retest stability of the Reading, Spelling, and Arithmetic subtest scores of the Wide Range Achievement Test (WRAT-3) across two administrations in individuals with autism spectrum disorder. Participants (N = 31) were males ages 6-22 years (M = 15.2, SD = 4.0) who were part of a larger ongoing longitudinal study of brain development in children and adults with autism spectrum disorder (N = 185). Test-retest stability for all three subtests remained consistent across administration periods (M = 31.8 mo., SD = 4.1). Age at time of administration, time between administrations, and test form did not significantly influence test-retest stability. Results indicated that for research involving individuals with autism spectrum disorder with a full scale intelligence quotient above 75, the WRAT-3 Spelling and Arithmetic subtests have acceptable test-retest stability over time and the Reading subtest has moderate test-retest stability over time.

Atypical development of white matter microstructure of the corpus callosum in males with autism: a longitudinal investigation

BACKGROUND

The corpus callosum is the largest white matter structure in the brain, and it is the most consistently reported to be atypical in diffusion tensor imaging studies of autism spectrum disorder. In individuals with typical development, the corpus callosum is known to undergo a protracted development from childhood through young adulthood. However, no study has longitudinally examined the developmental trajectory of corpus callosum in autism past early childhood.

METHODS

The present study used a cohort sequential design over 9 years to examine age-related changes of the corpus callosum in 100 males with autism and 56 age-matched males with typical development from early childhood (when autism can first be reliably diagnosed) to mid-adulthood (after development of the corpus callosum has been completed) (3 to 41 years of age).

RESULTS

The group with autism demonstrated a different developmental trajectory of white matter microstructure in the anterior corpus callosum's (genu and body) fractional anisotropy, which suggests atypical brain maturation in these regions in autism. When analyses were broken down by age group, atypical developmental trajectories were present only in the youngest participants (10 years of age and younger). Significant main effects for group were found in terms of decreased fractional anisotropy across all three subregions of the corpus callosum (genu, body, and splenium) and increased mean diffusivity, radial diffusivity, and axial diffusivity in the posterior corpus callosum.

CONCLUSIONS

These longitudinal results suggest atypical early childhood development of the corpus callosum microstructure in autism that transitions into sustained group differences in adolescence and adulthood. This pattern of results provides longitudinal evidence consistent with a growing number of published studies and hypotheses regarding abnormal brain connectivity across the life span in autism.

Brain imaging research in autism spectrum disorders: in search of neuropathology and health across the lifespan

PURPOSE OF REVIEW

Advances in brain imaging research in autism spectrum disorders (ASD) are rapidly occurring, and the amount of neuroimaging research has dramatically increased over the past 5 years. In this review, advances during the past 12 months and longitudinal studies are highlighted.

RECENT FINDINGS

Cross-sectional neuroimaging research provides evidence that the neural underpinnings of the behavioral signs of ASD involve not only dysfunctional integration of information across distributed brain networks but also basic dysfunction in primary cortices.Longitudinal studies of ASD show abnormally enlarged brain volumes and increased rates of brain growth during early childhood in only a small minority of ASD children. There is evidence of disordered development of white matter microstructure and amygdala growth, and at 2 years of age, network inefficiencies in posterior cerebral regions.From older childhood into adulthood, atypical age-variant and age-invariant changes in the trajectories of total and regional brain volumes and cortical thickness are apparent at the group level.

SUMMARY

There is evidence of abnormalities in posterior lobes and posterior brain networks during the first 2 years of life in ASD and, even in older children and adults, dysfunction in primary cortical areas.

Longitudinal volumetric brain changes in autism spectrum disorder ages 6-35 years

Since the impairments associated with autism spectrum disorder (ASD) tend to persist or worsen from childhood into adulthood, it is of critical importance to examine how the brain develops over this growth epoch. We report initial findings on whole and regional longitudinal brain development in 100 male participants with ASD (226 high-quality magnetic resonance imaging [MRI] scans; mean inter-scan interval 2.7 years) compared to 56 typically developing controls (TDCs) (117 high-quality scans; mean inter-scan interval 2.6 years) from childhood into adulthood, for a total of 156 participants scanned over an 8-year period. This initial analysis includes between one and three high-quality scans per participant that have been processed and segmented to date, with 21% having one scan, 27% with two scans, and 52% with three scans in the ASD sample; corresponding percentages for the TDC sample are 30%, 30%, and 40%. The proportion of participants with multiple scans (79% of ASDs and 68% of TDCs) was high in comparison to that of large longitudinal neuroimaging studies of typical development. We provide volumetric growth curves for the entire brain, total gray matter (GM), frontal GM, temporal GM, parietal GM, occipital GM, total cortical white matter (WM), corpus callosum, caudate, thalamus, total cerebellum, and total ventricles. Mean volume of cortical WM was reduced significantly. Mean ventricular volume was increased in the ASD sample relative to the TDCs across the broad age range studied. Decreases in regional mean volumes in the ASD sample most often were due to decreases during late adolescence and adulthood. The growth curve of whole brain volume over time showed increased volumes in young children with autism, and subsequently decreased during adolescence to meet the TDC curve between 10 and 15 years of age. The volume of many structures continued to decline atypically into adulthood in the ASD sample. The data suggest that ASD is a dynamic disorder with complex changes in whole and regional brain volumes that change over time from childhood into adulthood.

Longitudinal changes in cortical thickness in autism and typical development

The natural history of brain growth in autism spectrum disorders remains unclear. Cross-sectional studies have identified regional abnormalities in brain volume and cortical thickness in autism, although substantial discrepancies have been reported. Preliminary longitudinal studies using two time points and small samples have identified specific regional differences in cortical thickness in the disorder. To clarify age-related trajectories of cortical development, we examined longitudinal changes in cortical thickness within a large mixed cross-sectional and longitudinal sample of autistic subjects and age- and gender-matched typically developing controls. Three hundred and forty-five magnetic resonance imaging scans were examined from 97 males with autism (mean age = 16.8 years; range 3-36 years) and 60 males with typical development (mean age = 18 years; range 4-39 years), with an average interscan interval of 2.6 years. FreeSurfer image analysis software was used to parcellate the cortex into 34 regions of interest per hemisphere and to calculate mean cortical thickness for each region. Longitudinal linear mixed effects models were used to further characterize these findings and identify regions with between-group differences in longitudinal age-related trajectories. Using mean age at time of first scan as a reference (15 years), differences were observed in bilateral inferior frontal gyrus, pars opercularis and pars triangularis, right caudal middle frontal and left rostral middle frontal regions, and left frontal pole. However, group differences in cortical thickness varied by developmental stage, and were influenced by IQ. Differences in age-related trajectories emerged in bilateral parietal and occipital regions (postcentral gyrus, cuneus, lingual gyrus, pericalcarine cortex), left frontal regions (pars opercularis, rostral middle frontal and frontal pole), left supramarginal gyrus, and right transverse temporal gyrus, superior parietal lobule, and paracentral, lateral orbitofrontal, and lateral occipital regions. We suggest that abnormal cortical development in autism spectrum disorders undergoes three distinct phases: accelerated expansion in early childhood, accelerated thinning in later childhood and adolescence, and decelerated thinning in early adulthood. Moreover, cortical thickness abnormalities in autism spectrum disorders are region-specific, vary with age, and may remain dynamic well into adulthood.

Abnormal lateralization of functional connectivity between language and default mode regions in autism

Background

Lateralization of brain structure and function occurs in typical development, and abnormal lateralization is present in various neuropsychiatric disorders. Autism is characterized by a lack of left lateralization in structure and function of regions involved in language, such as Broca and Wernicke areas.

Methods

Using functional connectivity magnetic resonance imaging from a large publicly available sample (n = 964), we tested whether abnormal functional lateralization in autism exists preferentially in language regions or in a more diffuse pattern across networks of lateralized brain regions.

Results

The autism group exhibited significantly reduced left lateralization in a few connections involving language regions and regions from the default mode network, but results were not significant throughout left- and right-lateralized networks. There is a trend that suggests the lack of left lateralization in a connection involving Wernicke area and the posterior cingulate cortex associates with more severe autism.

Conclusions

Abnormal language lateralization in autism may be due to abnormal language development rather than to a deficit in hemispheric specialization of the entire brain.

Longitudinal processing speed impairments in males with autism and the effects of white matter microstructure

The present study used an accelerated longitudinal design to examine group differences and age-related changes in processing speed in 81 individuals with autism spectrum disorder (ASD) compared to 56 age-matched individuals with typical development (ages 6-39 years). Processing speed was assessed using the Wechsler Intelligence Scale for Children-3rd edition (WISC-III) and the Wechsler Adult Intelligence Scale-3rd edition (WAIS-III). Follow-up analyses examined processing speed subtest performance and relations between processing speed and white matter microstructure (as measured with diffusion tensor imaging [DTI] in a subset of these participants). After controlling for full scale IQ, the present results show that processing speed index standard scores were on average 12 points lower in the group with ASD compared to the group with typical development. There were, however, no significant group differences in standard score age-related changes within this age range. For subtest raw scores, the group with ASD demonstrated robustly slower processing speeds in the adult versions of the IQ test (i.e., WAIS-III) but not in the child versions (WISC-III), even though age-related changes were similar in both the ASD and typically developing groups. This pattern of results may reflect difficulties that become increasingly evident in ASD on more complex measures of processing speed. Finally, DTI measures of whole-brain white matter microstructure suggested that fractional anisotropy (but not mean diffusivity, radial diffusivity, or axial diffusivity) made significant but small-sized contributions to processing speed standard scores across our entire sample. Taken together, the present findings suggest that robust decreases in processing speed may be present in ASD, more pronounced in adulthood, and partially attributable to white matter microstructural integrity.

Multisite functional connectivity MRI classification of autism: ABIDE results

Background: Systematic differences in functional connectivity MRI metrics have been consistently observed in autism, with predominantly decreased cortico-cortical connectivity. Previous attempts at single subject classification in high-functioning autism using whole brain point-to-point functional connectivity have yielded about 80% accurate classification of autism vs. control subjects across a wide age range. We attempted to replicate the method and results using the Autism Brain Imaging Data Exchange (ABIDE) including resting state fMRI data obtained from 964 subjects and 16 separate international sites.

Methods: For each of 964 subjects, we obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the gray matter (26.4 million “connections”) after preprocessing that included motion and slice timing correction, coregistration to an anatomic image, normalization to standard space, and voxelwise removal by regression of motion parameters, soft tissue, CSF, and white matter signals. Connections were grouped into multiple bins, and a leave-one-out classifier was evaluated on connections comprising each set of bins. Age, age-squared, gender, handedness, and site were included as covariates for the classifier.

Results: Classification accuracy significantly outperformed chance but was much lower for multisite prediction than for previous single site results. As high as 60% accuracy was obtained for whole brain classification, with the best accuracy from connections involving regions of the default mode network, parahippocampaland fusiform gyri, insula, Wernicke Area, and intraparietal sulcus. The classifier score was related to symptom severity, social function, daily living skills, and verbal IQ. Classification accuracy was significantly higher for sites with longer BOLD imaging times.

Conclusions: Multisite functional connectivity classification of autism outperformed chance using a simple leave-one-out classifier, but exhibited poorer accuracy than for single site results. Attempts to use multisite classifiers will likely require improved classification algorithms, longer BOLD imaging times, and standardized acquisition parameters for possible future clinical utility.

An evaluation of the left-brain vs. right-brain hypothesis with resting state functional connectivity magnetic resonance imaging

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater “left-brained” or greater “right-brained” network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed.

Penalized likelihood phenotyping: unifying voxelwise analyses and multi-voxel pattern analyses in neuroimaging: penalized likelihood phenotyping

Neuroimage phenotyping for psychiatric and neurological disorders is performed using voxelwise analyses also known as voxel based analyses or morphometry (VBM). A typical voxelwise analysis treats measurements at each voxel (e.g., fractional anisotropy, gray matter probability) as outcome measures to study the effects of possible explanatory variables (e.g., age, group) in a linear regression setting. Furthermore, each voxel is treated independently until the stage of correction for multiple comparisons. Recently, multi-voxel pattern analyses (MVPA), such as classification, have arisen as an alternative to VBM. The main advantage of MVPA over VBM is that the former employ multivariate methods which can account for interactions among voxels in identifying significant patterns. They also provide ways for computer-aided diagnosis and prognosis at individual subject level. However, compared to VBM, the results of MVPA are often more difficult to interpret and prone to arbitrary conclusions. In this paper, first we use penalized likelihood modeling to provide a unified framework for understanding both VBM and MVPA. We then utilize statistical learning theory to provide practical methods for interpreting the results of MVPA beyond commonly used performance metrics, such as leave-one-out-cross validation accuracy and area under the receiver operating characteristic (ROC) curve. Additionally, we demonstrate that there are challenges in MVPA when trying to obtain image phenotyping information in the form of statistical parametric maps (SPMs), which are commonly obtained from VBM, and provide a bootstrap strategy as a potential solution for generating SPMs using MVPA. This technique also allows us to maximize the use of available training data. We illustrate the empirical performance of the proposed framework using two different neuroimaging studies that pose different levels of challenge for classification using MVPA.

scMRI reveals large-scale brain network abnormalities in autism

Autism is a complex neurological condition characterized by childhood onset of dysfunction in multiple cognitive domains including socio-emotional function, speech and language, and processing of internally versus externally directed stimuli. Although gross brain anatomic differences in autism are well established, recent studies investigating regional differences in brain structure and function have yielded divergent and seemingly contradictory results. How regional abnormalities relate to the autistic phenotype remains unclear. We hypothesized that autism exhibits distinct perturbations in network-level brain architecture, and that cognitive dysfunction may be reflected by abnormal network structure. Network-level anatomic abnormalities in autism have not been previously described. We used structural covariance MRI to investigate network-level differences in gray matter structure within two large-scale networks strongly implicated in autism, the salience network and the default mode network, in autistic subjects and age-, gender-, and IQ-matched controls. We report specific perturbations in brain network architecture in the salience and default-mode networks consistent with clinical manifestations of autism. Extent and distribution of the salience network, involved in social-emotional regulation of environmental stimuli, is restricted in autism. In contrast, posterior elements of the default mode network have increased spatial distribution, suggesting a ‘posteriorization’ of this network. These findings are consistent with a network-based model of autism, and suggest a unifying interpretation of previous work. Moreover, we provide evidence of specific abnormalities in brain network architecture underlying autism that are quantifiable using standard clinical MRI.

Corpus Callosum Area in Children and Adults with Autism

Despite repeated findings of abnormal corpus callosum structure in autism, the developmental trajectories of corpus callosum growth in the disorder have not yet been reported. In this study, we examined corpus callosum size from a developmental perspective across a 30-year age range in a large cross-sectional sample of individuals with autism compared to a typically developing sample. Midsagittal corpus callosum area and the 7 Witelson subregions were examined in 68 males with autism (mean age 14.1 years; range 3-36 years) and 47 males with typical development (mean age 15.3 years; range 4-29 years). Controlling for total brain volume, increased variability in total corpus callosum area was found in autism. In autism, increased midsagittal areas were associated with reduced severity of autism behaviors, higher intelligence, and faster speed of processing (p=0.003, p=0.011, p=0.013, respectively). A trend toward group differences in isthmus development was found (p=0.029, uncorrected). These results suggest that individuals with autism benefit functionally from increased corpus callosum area. Our cross-sectional examination also shows potential maturational abnormalities in autism, a finding that should be examined further with longitudinal datasets.

Diffusion tensor imaging in autism spectrum disorder: a review

White matter tracts of the brain allow neurons and neuronal networks to communicate and function with high efficiency. The aim of this review is to briefly introduce diffusion tensor imaging methods that examine white matter tracts and then to give an overview of the studies that have investigated white matter integrity in the brains of individuals with autism spectrum disorder (ASD). From the 48 studies we reviewed, persons with ASD tended to have decreased fractional anisotropy and increased mean diffusivity in white matter tracts spanning many regions of the brain but most consistently in regions such as the corpus callosum, cingulum, and aspects of the temporal lobe. This decrease in fractional anisotropy was often accompanied by increased radial diffusivity. Additionally, the review suggests possible atypical lateralization in some white matter tracts of the brain and a possible atypical developmental trajectory of white matter microstructure in persons with ASD. Clinical implications and future research directions are discussed.

ASD, a psychiatric disorder, or both? Psychiatric diagnoses in adolescents with high-functioning ASD

Varied presentations of emotion dysregulation in autism complicate diagnostic decision making and may lead to inaccurate psychiatric diagnoses or delayed autism diagnosis for high-functioning children. This pilot study aimed to determine the concordance between prior psychiatric diagnoses and the results of an autism-specific psychiatric interview in adolescents with high-functioning autism. Participants included 35 predominantly Caucasian and male verbal 10- to 17-year-olds with a confirmed autism spectrum disorder and without intellectual disability. The average age of autism spectrum diagnosis was 11 years old. Lifetime psychiatric diagnoses were established via the Autism Comorbidity Interview, developed to identify comorbid conditions within the context of autism. Autism Comorbidity Interview results were compared to parent report of prior community psychiatric diagnoses. Approximately 60% of prior psychiatric diagnoses were not supported on the Autism Comorbidity Interview; the lowest diagnostic concordance was for prior bipolar disorder and obsessive-compulsive disorder diagnoses. Although 51% of children met Autism Comorbidity Interview criteria for at least one psychiatric disorder, rates of prior diagnoses were much higher, with 77% having at least one prior psychiatric diagnosis and 60% having two or more. Although many participants met criteria for comorbid psychiatric disorders, the majority of previous psychiatric diagnoses were not supported when autism-related manifestations were systematically taken into account. These findings require replication and may not generalize to lower functioning and earlier diagnosed children with autism spectrum disorder. Results emphasize the importance of increasing awareness of the manifestations of high-functioning autism in order to improve accuracy of diagnosis and appropriateness of interventions.

Intact Prototype Formation but Impaired Generalization in Autism

Cognitive processing in autism has been characterized by a difficulty with the abstraction of information across multiple stimuli or situations and subsequent generalization to new stimuli or situations. This apparent difficulty leads to the suggestion that prototype formation, a process of creating a mental summary representation of multiple experienced stimuli that go together in a category, may be impaired in autism. Adults with high functioning autism and a typically developing comparison group matched on age and IQ completed a random dot pattern categorization task. Participants with autism demonstrated intact prototype formation in all four ways it was operationally defined, and this performance was not significantly different from that of control participants. However, participants with autism categorized dot patterns that were more highly distorted from the category prototypes less accurately than did control participants. These findings suggest, at least within the constraints of the random dot pattern task, that although prototype formation may not be impaired in autism, difficulties may exist with the generalization of what has been learned about a category to novel stimuli, particularly as they become less similar to the category's prototype.

Memory functioning in children and adolescents with autism

OBJECTIVE

Memory functioning in children and adolescents ages 5-19 with autism (n = 50) and typically developing controls (n = 36) was assessed using a clinical assessment battery, the Test of Memory and Learning (TOMAL).

METHOD

Participant groups were statistically comparable in age, nonverbal IQ, handedness, and head circumference, and were administered the TOMAL.

RESULTS

Test performance on the TOMAL demonstrated broad differences in memory functioning in the autism group, across multiple task formats, including verbal and nonverbal, immediate and delayed, attention and concentration, sequential recall, free recall, associative recall, and multiple-trial learning memory. All index and nearly all subtest differences remained significant even after comparing a subset of the autism group (n = 36) and controls that were matched for verbal IQ (p > .05). However, retention of previously remembered information after a delay was similar in autism and controls.

CONCLUSIONS

These findings indicate that performance on measures of episodic memory is broadly reduced in autism, and support the conclusion that information encoding and organization, possibly due to inefficient cognitive processing strategies, rather than storage and retrieval, are the primary factors that limit memory performance in autism.

Functional connectivity magnetic resonance imaging classification of autism

Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear whether functional connectivity is sufficiently robust to be used as a diagnostic or prognostic metric in individual patients with autism. We obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the entire grey matter (26.4 million connections) in a well-characterized set of 40 male adolescents and young adults with autism and 40 age-, sex- and IQ-matched typically developing subjects. A single resting state blood oxygen level-dependent scan of 8 min was used for the classification in each subject. A leave-one-out classifier successfully distinguished autism from control subjects with 83% sensitivity and 75% specificity for a total accuracy of 79% (P = 1.1 × 10(-7)). In subjects <20 years of age, the classifier performed at 89% accuracy (P = 5.4 × 10(-7)). In a replication dataset consisting of 21 individuals from six families with both affected and unaffected siblings, the classifier performed at 71% accuracy (91% accuracy for subjects <20 years of age). Classification scores in subjects with autism were significantly correlated with the Social Responsiveness Scale (P = 0.05), verbal IQ (P = 0.02) and the Autism Diagnostic Observation Schedule-Generic's combined social and communication subscores (P = 0.05). An analysis of informative connections demonstrated that region of interest pairs with strongest correlation values were most abnormal in autism. Negatively correlated region of interest pairs showed higher correlation in autism (less anticorrelation), possibly representing weaker inhibitory connections, particularly for long connections (Euclidean distance >10 cm). Brain regions showing greatest differences included regions of the default mode network, superior parietal lobule, fusiform gyrus and anterior insula. Overall, classification accuracy was better for younger subjects, with differences between autism and control subjects diminishing after 19 years of age. Classification scores of unaffected siblings of individuals with autism were more similar to those of the control subjects than to those of the subjects with autism. These findings indicate feasibility of a functional connectivity magnetic resonance imaging diagnostic assay for autism.

Atypical diffusion tensor hemispheric asymmetry in autism

BACKGROUND

Biological measurements that distinguish individuals with autism from typically developing individuals and those with other developmental and neuropsychiatric disorders must demonstrate very high performance to have clinical value as potential imaging biomarkers. We hypothesized that further study of white matter microstructure (WMM) in the superior temporal gyrus (STG) and temporal stem (TS), two brain regions in the temporal lobe containing circuitry central to language, emotion, and social cognition, would identify a useful combination of classification features and further understand autism neuropathology.

METHODS

WMM measurements from the STG and TS were examined from 30 high-functioning males satisfying full criteria for idiopathic autism aged 7-28 years and 30 matched controls and a replication sample of 12 males with idiopathic autism and 7 matched controls who participated in a previous case-control diffusion tensor imaging (DTI) study. Language functioning, adaptive functioning, and psychotropic medication usage were also examined.

RESULTS

In the STG, we find reversed hemispheric asymmetry of two separable measures of directional diffusion coherence, tensor skewness, and fractional anisotropy. In autism, tensor skewness is greater on the right and fractional anisotropy is decreased on the left. We also find increased diffusion parallel to white matter fibers bilaterally. In the right not left TS, we find increased omnidirectional, parallel, and perpendicular diffusion. These six multivariate measurements possess very high ability to discriminate individuals with autism from individuals without autism with 94% sensitivity, 90% specificity, and 92% accuracy in our original and replication samples. We also report a near-significant association between the classifier and a quantitative trait index of autism and significant correlations between two classifier components and measures of language, IQ, and adaptive functioning in autism.

Decreased interhemispheric functional connectivity in autism

The cortical underconnectivity theory asserts that reduced long-range functional connectivity might contribute to a neural mechanism for autism. We examined resting-state blood oxygen level-dependent interhemispheric correlation in 53 males with high-functioning autism and 39 typically developing males from late childhood through early adulthood. By constructing spatial maps of correlation between homologous voxels in each hemisphere, we found significantly reduced interhemispheric correlation specific to regions with functional relevance to autism: sensorimotor cortex, anterior insula, fusiform gyrus, superior temporal gyrus, and superior parietal lobule. Observed interhemispheric connectivity differences were better explained by diagnosis of autism than by potentially confounding neuropsychological metrics of language, IQ, or handedness. Although both corpus callosal volume and gray matter interhemispheric connectivity were significantly reduced in autism, no direct relationship was observed between them, suggesting that structural and functional metrics measure different aspects of interhemispheric connectivity. In the control but not the autism sample, there was decreasing interhemispheric correlation with subject age. Greater differences in interhemispheric correlation were seen for more lateral regions in the brain. These findings suggest that long-range connectivity abnormalities in autism are spatially heterogeneous and that transcallosal connectivity is decreased most in regions with functions associated with behavioral abnormalities in autism. Autism subjects continue to show developmental differences in interhemispheric connectivity into early adulthood.

Associations between IQ, total and regional brain volumes, and demography in a large normative sample of healthy children and adolescents

In the course of efforts to establish quantitative norms for healthy brain development by magnetic resonance imaging (MRI) (Brain Development Cooperative Group, 2006), previously unreported associations of parental education and temporal and frontal lobe volumes with full scale IQ and its verbal and performance subscales were discovered. Our findings were derived from the largest, most representative MRI sample to date of healthy children and adolescents, ages 4 years 10 months to 18 years 4 months. We first find that parental education has a strong association with IQ in children that is not mediated by total or regional brain volumes. Second, we find that our observed correlations between temporal gray matter, temporal white matter and frontal white matter volumes with full scale IQ, between 0.14 to 0.27 in children and adolescents, are due in large part to their correlations with performance IQ and not verbal IQ. The volumes of other lobar gray and white matter, subcortical gray matter (thalamus, caudate nucleus, putamen, and globus pallidus), cerebellum, and brainstem do not contribute significantly to IQ variation. Third, we find that head circumference is an insufficient index of cerebral volume in typically developing older children and adolescents. The relations between total and regional brain volumes and IQ can best be discerned when additional variables known to be associated with IQ, especially parental education and other demographic measures, are considered concurrently.

Volumetric and voxel-based morphometry findings in autism subjects with and without macrocephaly

This study sought to replicate Herbert et al. (2003a), which found increased overall white matter (WM) volume in subjects with autism, even after controlling for head size differences. To avoid the possibility that greater WM volume in autism is merely an epiphenomena of macrocephaly overrepresentation associated with the disorder, the current study included control subjects with benign macrocephaly. The control group also included subjects with a reading disability to insure cognitive heterogeneity. WM volume in autism was significantly larger, even when controlling for brain volume, rate of macrocephaly, and other demographic variables. Autism and controls differed little on whole-brain WM voxel-based morphometry (VBM) analyses suggesting that the overall increase in WM volume was non-localized. Autism subjects exhibited a differential pattern of IQ relationships with brain volumetry findings from controls. Current theories of brain overgrowth and their importance in the development of autism are discussed in the context of these findings.

Microstructural connectivity of the arcuate fasciculus in adolescents with high-functioning autism

The arcuate fasciculus is a white matter fiber bundle of great importance in language. In this study, diffusion tensor imaging (DTI) was used to infer white matter integrity in the arcuate fasciculi of a group of subjects with high-functioning autism and a control group matched for age, handedness, IQ, and head size. The arcuate fasciculus for each subject was automatically extracted from the imaging data using a new volumetric DTI segmentation algorithm. The results showed a significant increase in mean diffusivity (MD) in the autism group, due mostly to an increase in the radial diffusivity (RD). A test of the lateralization of DTI measurements showed that both MD and fractional anisotropy (FA) were less lateralized in the autism group. These results suggest that white matter microstructure in the arcuate fasciculus is affected in autism and that the language specialization apparent in the left arcuate of healthy subjects is not as evident in autism, which may be related to poorer language functioning.

Cosine series representation of 3D curves and its application to white matter fiber bundles in diffusion tensor imaging

We present a novel cosine series representation for encoding fiber bundles consisting of multiple 3D curves. The coordinates of curves are parameterized as coefficients of cosine series expansion. We address the issue of registration, averaging and statistical inference on curves in a unified Hilbert space framework. Unlike traditional splines, the proposed method does not have internal knots and explicitly represents curves as a linear combination of cosine basis. This simplicity in the representation enables us to design statistical models, register curves and perform subsequent analysis in a more unified statistical framework than splines.The proposed representation is applied in characterizing abnormal shape of white matter fiber tracts passing through the splenium of the corpus callosum in autistic subjects. For an arbitrary tract, a 19 degree expansion is usually found to be sufficient to reconstruct the tract with 60 parameters.

Decreased left posterior insular activity during auditory language in autism

BACKGROUND AND PURPOSE

Individuals with autism spectrum disorders often exhibit atypical language patterns, including delay of speech onset, literal speech interpretation, and poor recognition of social and emotional cues in speech. We acquired functional MR images during an auditory language task to evaluate systematic differences in language-network activation between control and high-functioning autistic populations.

MATERIALS AND METHODS

Forty-one right-handed male subjects (26 high-functioning autistic subjects, 15 controls) were studied by using an auditory phrase-recognition task, and areas of differential activation between groups were identified. Hand preference, verbal intelligence quotient (IQ), age, and language-function testing were included as covariables in the analysis.

RESULTS

Control and autistic subjects showed similar language-activation networks, with 2 notable differences. Control subjects showed significantly increased activation in the left posterior insula compared with autistic subjects (P < .05, false discovery rate), and autistic subjects showed increased bilaterality of receptive language compared with control subjects. Higher receptive-language scores on standardized testing were associated with greater activation of the posterior aspect of the left Wernicke area. A higher verbal IQ was associated with greater activation of the bilateral Broca area and involvement of the prefrontal cortex and lateral premotor cortex.

CONCLUSIONS

Control subjects showed greater activation of the posterior insula during receptive language, which may correlate with impaired emotive processing of language in autism. Subjects with autism showed greater bilateral activation of receptive-language areas, which was out of proportion to the differences in hand preference in autism and control populations.

Overrepresentation of mood and anxiety disorders in adults with autism and their first-degree relatives: what does it mean?

Research indicates that relatives of individuals with autism have higher rates of affective disorders than both the general population and families of children with other developmental disabilities. In addition, individuals with autism have high rates of co-morbid mood and anxiety disorders. This study sought to identify possible reasons for these previous findings by documenting the presence of affective disorders in both probands (the individuals with autism) and their family members. A sub-sample of 17 adults with autism and their first-degree relatives from the Baltimore Family Study of Autism completed a structured psychiatric interview. The results indicated that the rates of mood and anxiety disorders were 35 and 77%, respectively, for probands, and these disorders were present in at least one first-degree relative at rates of 71 and 29%, respectively. Exploring patterns within families revealed that 80% of probands with a mother who had a mood disorder history also had a mood disorder themselves, compared to only 16% of probands whose mothers did not have a mood disorder history. The results must be considered preliminary given the small sample size. Replicating these findings in a larger sample would help clarify whether a true increased risk of mood disorder exists, which would have potential implications for prevention efforts and understanding possible genetic mechanisms.

Efficient parametric encoding scheme for white matter fiber bundles

We present a novel parametric encoding scheme for efficiently recording white matter fiber bundle information obtained from diffusion tensor imaging. The coordinates of fiber tracts are parameterized using a cosine series expansion. For an arbitrary tract, a 19 degree expansion is found to be sufficient to reconstruct the tract with an average error of about 0.26 mm. Then each tract is fully parameterized with 60 parameters, which results in a substantial data reduction. Unlike traditional splines, the proposed method does not have internal knots and explicitly represents the tract as a linear combination of basis functions. This simplicity in the representation enables us to design statistical models, register tracts and perform subsequent analysis in a more streamlined mathematical framework. As an illustration, we apply the proposed method in characterizing abnormal tracts that pass through the splenium of the corpus callosum in autistic subjects.

Classification in DTI using shapes of white matter tracts

Diffusion Tensor Imaging (DTI) provides unique information about the underlying tissue structure of brain white matter in vivo, including both the geometry of fiber bundles as well as quantitative information about tissue properties as characterized by measures such as tensor orientation, anisotropy, and size. Our objective in this paper is to evaluate the utility of shape representations of white matter tracts extracted from DTI data for classification of clinically different population groups (here autistic vs control). As a first step, our algorithm extracts fiber bundles passing through approximately marked regions of interest on affinely aligned brain volumes. The subsequent analysis is entirely based on the geometric modeling of the extracted tracts. A key advantage of using such an abstraction is that it allows us to capture invariant features of brains allowing for efficient large sample size studies. We demonstrate that with the use of an appropriate representation of the tract shapes, classifiers can be built with reasonable prediction accuracies without making heavy use of the spatial normalization machinery needed when using voxel based features.