Lesions Causing Alice in Wonderland Syndrome Map to a Common Brain Network Linking Body and Size Perception.

OBJECTIVE: Alice in Wonderland syndrome (AIWS) profoundly affects human perception of size and scale, particularly regarding one's own body and the environment. Its neuroanatomical basis has remained elusive, partly because brain lesions causing AIWS can occur in different brain regions. Here, we aimed to determine if brain lesions causing AIWS map to a distributed brain network. METHODS: A retrospective case-control study analyzing 37 cases of lesion-induced AIWS identified through systematic literature review was conducted. Using resting-state functional connectome data from 1,000 healthy individuals, the whole-brain connections of each lesion were estimated and contrasted with those from a control dataset comprising 1,073 lesions associated with 25 other neuropsychiatric syndromes. Additionally, connectivity findings from lesion-induced AIWS cases were compared with functional neuroimaging results from 5 non-lesional AIWS cases. RESULTS: AIWS-associated lesions were located in various brain regions with minimal overlap (≤33%). However, the majority of lesions (≥85%) demonstrated shared connectivity to the right extrastriate body area, known to be selectively activated by viewing body part images, and the inferior parietal cortex, involved in size and scale judgements. This pattern was uniquely characteristic of AIWS when compared with other neuropsychiatric disorders (family-wise error-corrected p < 0.05) and consistent with functional neuroimaging observations in AIWS due to nonlesional causes (median correlation r = 0.56, interquartile range 0.24). INTERPRETATION: AIWS-related perceptual distortions map to one common brain network, encompassing regions critical for body representation and size-scale processing. These findings lend insight into the neuroanatomical localization of higher-order perceptual functions, and may inform future therapeutic strategies for perceptual disorders. ANN NEUROL 2024.

Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

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.

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.

Complexity of low-frequency blood oxygen level-dependent fluctuations covaries with local connectivity.

Very low-frequency blood oxygen level-dependent (BOLD) fluctuations have emerged as a valuable tool for describing brain anatomy, neuropathology, and development. Such fluctuations exhibit power law frequency dynamics, with largest amplitude at lowest frequencies. The biophysical mechanisms generating such fluctuations are poorly understood. Using publicly available data from 1,019 subjects of age 7-30, we show that BOLD fluctuations exhibit temporal complexity that is linearly related to local connectivity (regional homogeneity), consistently and significantly covarying across subjects and across gray matter regions. This relationship persisted independently of covariance with gray matter density or standard deviation of BOLD signal. During late neurodevelopment, BOLD fluctuations were unchanged with age in association cortex while becoming more random throughout the rest of the brain. These data suggest that local interconnectivity may play a key role in establishing the complexity of low-frequency BOLD fluctuations underlying functional magnetic resonance imaging connectivity. Stable low-frequency power dynamics may emerge through segmentation and integration of connectivity during development of distributed large-scale brain networks.

Parsing Brain Network Specialization: A Replication and Expansion of Wang et al. (2014).

One organizing principle of the human brain is hemispheric specialization, or the dominance of a specific function or cognitive process in one hemisphere or the other. Previously, Wang et al. (2014) identified networks putatively associated with language and attention as being specialized to the left and right hemispheres, respectively; and a dual-specialization of the executive control network. However, it remains unknown which networks are specialized when specialization is examined within individuals using a higher resolution parcellation, as well as which connections are contributing the most to a given network's specialization. In the present study, we estimated network specialization across three datasets using the autonomy index and a novel method of deconstructing network specialization. After examining the reliability of these methods as implemented on an individual level, we addressed two hypotheses. First, we hypothesized that the most specialized networks would include those associated with language, visuospatial attention, and executive control. Second, we hypothesized that within-network contributions to specialization would follow a within-between network gradient or a specialization gradient. We found that the majority of networks exhibited greater within-hemisphere connectivity than between-hemisphere connectivity. Among the most specialized networks were networks associated with language, attention, and executive control. Additionally, we found that the greatest network contributions were within-network, followed by those from specialized networks.

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.

No difference in extra-axial cerebrospinal fluid volumes across neurodevelopmental and psychiatric conditions in later childhood and adolescence.

BACKGROUND: While autism spectrum disorder has been associated with various organizational and developmental aberrations in the brain, an increase in extra-axial cerebrospinal fluid volume has recently garnered attention. A series of studies indicate that an increased volume between the ages of 6 months and 4 years was both predictive of the autism diagnosis and symptom severity regardless of genetic risk for the condition. However, there remains a minimal understanding regarding the specificity of an increased volume of extra-axial cerebrospinal fluid to autism. METHODS: In the present study, we explored extra-axial cerebrospinal fluid volumes in children and adolescents ages 5-21 years with various neurodevelopmental and psychiatric conditions. We hypothesized that an elevated extra-axial cerebrospinal fluid volume would be found in autism compared with typical development and the other diagnostic group. We tested this hypothesis by employing a cross-sectional dataset of 446 individuals (85 autistic, 60 typically developing, and 301 other diagnosis). An analysis of covariance was used to examine differences in extra-axial cerebrospinal fluid volumes between these groups as well as a group by age interaction in extra-axial cerebrospinal fluid volumes. RESULTS: Inconsistent with our hypothesis, we found no group differences in extra-axial cerebrospinal fluid volume in this cohort. However, in replication of previous work, a doubling of extra-axial cerebrospinal fluid volume across adolescence was found. Further investigation into the relationship between extra-axial cerebrospinal fluid volume and cortical thickness suggested that this increase in extra-axial cerebrospinal fluid volume may be driven by a decrease in cortical thickness. Furthermore, an exploratory analysis found no relationship between extra-axial cerebrospinal fluid volume and sleep disturbances. CONCLUSIONS: These results indicate that an increased volume of extra-axial cerebrospinal fluid may be limited to autistic individuals younger than 5 years. Additionally, extra-axial cerebrospinal fluid volume does not differ between autistic, neurotypical, and other psychiatric conditions after age 4.

Evidence for a Compensatory Relationship between Left- and Right-Lateralized Brain Networks.

The two hemispheres of the human brain are functionally asymmetric. At the network level, the language network exhibits left-hemisphere lateralization. While this asymmetry is widely replicated, the extent to which other functional networks demonstrate lateralization remains a subject of Investigation. Additionally, it is unknown how the lateralization of one functional network may affect the lateralization of other networks within individuals. We quantified lateralization for each of 17 networks by computing the relative surface area on the left and right cerebral hemispheres. After examining the ecological, convergent, and external validity and test-retest reliability of this surface area-based measure of lateralization, we addressed two hypotheses across multiple datasets (Human Connectome Project = 553, Human Connectome Project-Development = 343, Natural Scenes Dataset = 8). First, we hypothesized that networks associated with language, visuospatial attention, and executive control would show the greatest lateralization. Second, we hypothesized that relationships between lateralized networks would follow a dependent relationship such that greater left-lateralization of a network would be associated with greater right-lateralization of a different network within individuals, and that this pattern would be systematic across individuals. A language network was among the three networks identified as being significantly left-lateralized, and attention and executive control networks were among the five networks identified as being significantly right-lateralized. Next, correlation matrices, an exploratory factor analysis, and confirmatory factor analyses were used to test the second hypothesis and examine the organization of lateralized networks. We found general support for a dependent relationship between highly left- and right-lateralized networks, meaning that across subjects, greater left lateralization of a given network (such as a language network) was linked to greater right lateralization of another network (such as a ventral attention/salience network) and vice versa. These results further our understanding of brain organization at the macro-scale network level in individuals, carrying specific relevance for neurodevelopmental conditions characterized by disruptions in lateralization such as autism and schizophrenia.

Binocular rivalry in autistic and socially anxious adults.

Background: Social anxiousness is a pervasive symptom in both social anxiety disorder and autism spectrum conditions. Binocular rivalry, which occurs when different images are presented to each eye, has been used to explore how visual and cognitive processing differs across various clinical diagnoses. Previous studies have separately explored whether individuals with autism or anxiety experience binocular rivalry in ways that are different from neurotypical individuals. Methods: We applied rivalry paradigms that are similar to those used in previous studies of autism and general anxiety to individuals experiencing symptoms of social anxiousness at clinical or subclinical levels. We also incorporated rivalrous stimuli featuring neutral and emotional facial valances to explore potential overlap of social processing components in social anxiety and autism. Results: We hypothesized that higher levels of social anxiousness would increase binocular rivalry switch rates and that higher levels of autistic traits would decrease switch rates. However, stimulus condition did not affect switch rates in either diagnostic group, and switch rate was not significantly predictive of dimensional measures of either autism or social anxiety. Discussion: This may suggest a common mechanism for atypical visual cognition styles previously associated with social anxiety and autism. Alternatively, differences in switch rates may only emerge at higher trait levels than reported by the participants in our studies. Furthermore, these findings may be influenced by sex differences in our unique sample.

Precision Brain Morphometry Using Cluster Scanning.

Measurement error limits the statistical power to detect group differences and longitudinal change in structural MRI morphometric measures (e.g., hippocampal volume, prefrontal thickness). Recent advances in scan acceleration enable extremely fast T1-weighted scans (~1 minute) to achieve morphometric errors that are close to the errors in longer traditional scans. As acceleration allows multiple scans to be acquired in rapid succession, it becomes possible to pool estimates to increase measurement precision, a strategy known as "cluster scanning." Here we explored brain morphometry using cluster scanning in a test-retest study of 40 individuals (12 younger adults, 18 cognitively unimpaired older adults, and 10 adults diagnosed with mild cognitive impairment or Alzheimer's Dementia). Morphometric errors from a single compressed sensing (CS) 1.0mm scan with 6x acceleration (CSx6) were, on average, 12% larger than a traditional scan using the Alzheimer's Disease Neuroimaging Initiative (ADNI) protocol. Pooled estimates from four clustered CSx6 acquisitions led to errors that were 34% smaller than ADNI despite having a shorter total acquisition time. Given a fixed amount of time, a gain in measurement precision can thus be achieved by acquiring multiple rapid scans instead of a single traditional scan. Errors were further reduced when estimates were pooled from eight CSx6 scans (51% smaller than ADNI). Neither pooling across a break nor pooling across multiple scan resolutions boosted this benefit. We discuss the potential of cluster scanning to improve morphometric precision, boost statistical power, and produce more sensitive disease progression biomarkers.

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.

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.

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.

A Neural Circuit for Spirituality and Religiosity Derived From Patients With Brain Lesions.

BACKGROUND: Over 80% of the global population consider themselves religious, with even more identifying as spiritual, but the neural substrates of spirituality and religiosity remain unresolved. METHODS: In two independent brain lesion datasets (N1 = 88; N2 = 105), we applied lesion network mapping to test whether lesion locations associated with spiritual and religious belief map to a specific human brain circuit. RESULTS: We found that brain lesions associated with self-reported spirituality map to a brain circuit centered on the periaqueductal gray. Intersection of lesion locations with this same circuit aligned with self-reported religiosity in an independent dataset and previous reports of lesions associated with hyper-religiosity. Lesion locations causing delusions and alien limb syndrome also intersected this circuit. CONCLUSIONS: These findings suggest that spirituality and religiosity map to a common brain circuit centered on the periaqueductal gray, a brainstem region previously implicated in fear conditioning, pain modulation, and altruistic behavior.

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group.

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.

Reward, salience, and attentional networks are activated by religious experience in devout Mormons.

High-level cognitive and emotional experience arises from brain activity, but the specific brain substrates for religious and spiritual euphoria remain unclear. We demonstrate using functional magnetic resonance imaging scans in 19 devout Mormons that a recognizable feeling central to their devotional practice was reproducibly associated with activation in nucleus accumbens, ventromedial prefrontal cortex, and frontal attentional regions. Nucleus accumbens activation preceded peak spiritual feelings by 1-3 s and was replicated in four separate tasks. Attentional activation in the anterior cingulate and frontal eye fields was greater in the right hemisphere. The association of abstract ideas and brain reward circuitry may interact with frontal attentional and emotive salience processing, suggesting a mechanism whereby doctrinal concepts may come to be intrinsically rewarding and motivate behavior in religious individuals.

Quantifying the Effects of 16p11.2 Copy Number Variants on Brain Structure: A Multisite Genetic-First Study.

BACKGROUND: 16p11.2 breakpoint 4 to 5 copy number variants (CNVs) increase the risk for developing autism spectrum disorder, schizophrenia, and language and cognitive impairment. In this multisite study, we aimed to quantify the effect of 16p11.2 CNVs on brain structure. METHODS: Using voxel- and surface-based brain morphometric methods, we analyzed structural magnetic resonance imaging collected at seven sites from 78 individuals with a deletion, 71 individuals with a duplication, and 212 individuals without a CNV. RESULTS: Beyond the 16p11.2-related mirror effect on global brain morphometry, we observe regional mirror differences in the insula (deletion > control > duplication). Other regions are preferentially affected by either the deletion or the duplication: the calcarine cortex and transverse temporal gyrus (deletion > control; Cohen's d > 1), the superior and middle temporal gyri (deletion < control; Cohen's d < -1), and the caudate and hippocampus (control > duplication; -0.5 > Cohen's d > -1). Measures of cognition, language, and social responsiveness and the presence of psychiatric diagnoses do not influence these results. CONCLUSIONS: The global and regional effects on brain morphometry due to 16p11.2 CNVs generalize across site, computational method, age, and sex. Effect sizes on neuroimaging and cognitive traits are comparable. Findings partially overlap with results of meta-analyses performed across psychiatric disorders. However, the lack of correlation between morphometric and clinical measures suggests that CNV-associated brain changes contribute to clinical manifestations but require additional factors for the development of the disorder. These findings highlight the power of genetic risk factors as a complement to studying groups defined by behavioral criteria.

Violence: heightened brain attentional network response is selectively muted in Down syndrome.

BACKGROUND: The ability to recognize and respond appropriately to threat is critical to survival, and the neural substrates subserving attention to threat may be probed using depictions of media violence. Whether neural responses to potential threat differ in Down syndrome is not known. METHODS: We performed functional MRI scans of 15 adolescent and adult Down syndrome and 14 typically developing individuals, group matched by age and gender, during 50 min of passive cartoon viewing. Brain activation to auditory and visual features, violence, and presence of the protagonist and antagonist were compared across cartoon segments. fMRI signal from the brain's dorsal attention network was compared to thematic and violent events within the cartoons between Down syndrome and control samples. RESULTS: We found that in typical development, the brain's dorsal attention network was most active during violent scenes in the cartoons and that this was significantly and specifically reduced in Down syndrome. When the antagonist was on screen, there was significantly less activation in the left medial temporal lobe of individuals with Down syndrome. As scenes represented greater relative threat, the disparity between attentional brain activation in Down syndrome and control individuals increased. There was a reduction in the temporal autocorrelation of the dorsal attention network, consistent with a shortened attention span in Down syndrome. Individuals with Down syndrome exhibited significantly reduced activation in primary sensory cortices, and such perceptual impairments may constrain their ability to respond to more complex social cues such as violence. CONCLUSIONS: These findings may indicate a relative deficit in emotive perception of violence in Down syndrome, possibly mediated by impaired sensory perception and hypoactivation of medial temporal structures in response to threats, with relative preservation of activity in pro-social brain regions. These findings indicate that specific genetic differences associated with Down syndrome can modulate the brain's response to violence and other complex emotive ideas.

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.