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.

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.

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.

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.

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.

A study of diffusion tensor imaging by tissue-specific, smoothing-compensated voxel-based analysis.

Voxel-based analysis (VBA) is commonly used for statistical analysis of image data, including the detection of significant signal differences between groups. Typically, images are co-registered and then smoothed with an isotropic Gaussian kernel to compensate for image misregistration, to improve the signal-to-noise ratio (SNR), to reduce the number of multiple comparisons, and to apply random field theory. Problems with typical implementations of VBA include poor tissue specificity from image misregistration and smoothing. In this study, we developed a new tissue-specific, smoothing-compensated (T-SPOON) method for the VBA of diffusion tensor imaging (DTI) data with improved tissue specificity and compensation for image misregistration and smoothing. When compared with conventional VBA methods, the T-SPOON method introduced substantially less errors in the normalized and smoothed DTI maps. Another confound of the conventional DTI-VBA is that it is difficult to differentiate between differences in morphometry and DTI measures that describe tissue microstructure. T-SPOON VBA decreased the effects of differential morphometry in the DTI VBA studies. T-SPOON and conventional VBA were applied to a DTI study of white matter in autism. T-SPOON VBA results were found to be more consistent with region of interest (ROI) measurements in the corpus callosum and temporal lobe regions. The T-SPOON method may be also applicable to other quantitative imaging maps such as T1 or T2 relaxometry, magnetization transfer, or PET tracer maps.

Diffusion tensor imaging of white matter in the superior temporal gyrus and temporal stem in autism.

Recent MRI studies have indicated that regions of the temporal lobe including the superior temporal gyrus (STG) and the temporal stem (TS) appear to be abnormal in autism. In this study, diffusion tensor imaging (DTI) measurements of white matter in the STG and the TS were compared in 43 autism and 34 control subjects. DTI measures of mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were compared between groups. In all regions, fractional anisotropy was significantly decreased and both mean diffusivity and radial diffusivity were significantly increased in the autism group. These results suggest that white matter microstructure in autism is abnormal in these temporal lobe regions, which is consistent with theories of aberrant brain connectivity in autism.

Diffusion tensor imaging of the corpus callosum in Autism.

The corpus callosum is the largest commissural white matter pathway that connects the hemispheres of the human brain. In this study, diffusion tensor imaging (DTI) was performed on subject groups with high-functioning autism and controls matched for age, handedness, IQ, and head size. DTI and volumetric measurements of the total corpus callosum and subregions (genu, body and splenium) were made and compared between groups. The results showed that there were significant differences in volume, fractional anisotropy, mean diffusivity, and radial diffusivity between groups. These group differences appeared to be driven by a subgroup of the autism group that had small corpus callosum volumes, high mean diffusivity, low anisotropy, and increased radial diffusivity. This subgroup had significantly lower performance IQ measures than either the other individuals with autism or the control subjects. Measurements of radial diffusivity also appeared to be correlated with processing speed measured during the performance IQ tests. The subgroup of autism subjects with high mean diffusivity and low fractional anisotropy appeared to cluster with the highest radial diffusivities and slowest processing speeds. These results suggest that the microstructure of the corpus callosum is affected in autism, which may be related to nonverbal cognitive performance.