Mary Beth Nebel

Evaluating dynamic bivariate correlations in resting-state fMRI: a comparison study and a new approach.

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been an increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought that this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-window technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove to be useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data.

Disruption of functional organization within the primary motor cortex in children with autism

Accumulating evidence suggests that motor impairments are prevalent in autism spectrum disorder (ASD), relate to the social and communicative deficits at the core of the diagnosis and may reflect abnormal connectivity within brain networks underlying motor control and learning. Parcellation of resting‐state functional connectivity data using spectral clustering approaches has been shown to be an effective means of visualizing functional organization within the brain but has most commonly been applied to explorations of normal brain function. This article presents a parcellation of a key area of the motor network, the primary motor cortex (M1), a key area of the motor control network, in adults, typically developing (TD) children and children with ASD and introduces methods for selecting the number of parcels, matching parcels across groups and testing group differences. The parcellation is based solely on patterns of connectivity between individual M1 voxels and all voxels outside of M1, and within all groups, a gross dorsomedial to ventrolateral organization emerged within M1 which was left–right symmetric. Although this gross organizational scheme was present in both groups of children, statistically significant group differences in the size and segregation of M1 parcels within regions of the motor homunculus corresponding to the upper and lower limbs were observed. Qualitative comparison of the M1 parcellation for children with ASD with that of younger and older TD children suggests that these organizational differences, with a lack of differentiation between lower limb/trunk regions and upper limb/hand regions, may be due, at least in part, to a delay in functional specialization within the motor cortex. Hum Brain Mapp 35:567–580, 2014.

Perceptual and Neural Response to Affective Tactile Texture Stimulation in Adults with Autism Spectrum Disorders

Autism spectrum disorders (ASD) are associated with differences in sensory sensitivity and affective response to sensory stimuli, the neural basis of which is still largely unknown. We used psychophysics and functional magnetic resonance imaging (fMRI) to investigate responses to somatosensory stimulation with three textured surfaces that spanned a range of roughness and pleasantness in a sample of adults with ASD and a control group. While psychophysical ratings of roughness and pleasantness were largely similar across the two groups, the ASD group gave pleasant and unpleasant textures more extreme average ratings than did controls. In addition, their ratings for a neutral texture were more variable than controls, indicating they are less consistent in evaluating a stimulus that is affectively ambiguous. Changes in brain blood oxygenation level‐dependent (BOLD) signal in response to stimulation with these textures differed substantially between the groups, with the ASD group exhibiting diminished responses compared to the control group, particularly for pleasant and neutral textures. For the most unpleasant texture, the ASD group exhibited greater BOLD response than controls in affective somatosensory processing areas such as the posterior cingulate cortex and the insula. The amplitude of response in the insula in response to the unpleasant texture was positively correlated with social impairment as measured by the Autism Diagnostic Interview‐Revised (ADI‐R). These results suggest that people with ASD tend to show diminished response to pleasant and neutral stimuli, and exaggerated limbic responses to unpleasant stimuli, which may contribute to diminished social reward associated with touch, perpetuating social withdrawal, and aberrant social development. Autism Res 2012,5:231–244.

Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging

Successful automated diagnoses of attention deficit hyperactive disorder (ADHD) using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictability of ADHD using imaging biomarkers and discuss the scientific and diagnostic impacts of the research. We created a prediction model using the landmark ADHD 200 data set focusing on resting state functional connectivity (rs-fc) and structural brain imaging. We predicted ADHD status and subtype, obtained by behavioral examination, using imaging data, intelligence quotients and other covariates. The novel contributions of this manuscript include a thorough exploration of prediction and image feature extraction methodology on this form of data, including the use of singular value decompositions (SVDs), CUR decompositions, random forest, gradient boosting, bagging, voxel-based morphometry, and support vector machines as well as important insights into the value, and potentially lack thereof, of imaging biomarkers of disease. The key results include the CUR-based decomposition of the rs-fc-fMRI along with gradient boosting and the prediction algorithm based on a motor network parcellation and random forest algorithm. We conjecture that the CUR decomposition is largely diagnosing common population directions of head motion. Of note, a byproduct of this research is a potential automated method for detecting subtle in-scanner motion. The final prediction algorithm, a weighted combination of several algorithms, had an external test set specificity of 94% with sensitivity of 21%. The most promising imaging biomarker was a correlation graph from a motor network parcellation. In summary, we have undertaken a large-scale statistical exploratory prediction exercise on the unique ADHD 200 data set. The exercise produced several potential leads for future scientific exploration of the neurological basis of ADHD.

Intrinsic Visual-Motor Synchrony Correlates With Social Deficits in Autism.

BACKGROUND Imitation, which is impaired in children with autism spectrum disorder (ASD) and critically depends on the integration of visual input with motor output, likely impacts both motor and social skill acquisition in children with ASD; however, it is unclear what brain mechanisms contribute to this impairment. Children with ASD also exhibit what appears to be an ASD-specific bias against using visual feedback during motor learning. Does the temporal congruity of intrinsic activity, or functional connectivity, between motor and visual brain regions contribute to ASD-associated deficits in imitation, motor, and social skills? METHODS We acquired resting-state functional magnetic resonance imaging scans from 100 8- to 12-year-old children (50 ASD). Group independent component analysis was used to estimate functional connectivity between visual and motor systems. Brain-behavior relationships were assessed by regressing functional connectivity measures with social deficit severity, imitation, and gesture performance scores. RESULTS We observed increased intrinsic asynchrony between visual and motor systems in children with ASD and replicated this finding in an independent sample from the Autism Brain Imaging Data Exchange. Moreover, children with more out-of-sync intrinsic visual-motor activity displayed more severe autistic traits, while children with greater intrinsic visual-motor synchrony were better imitators. CONCLUSIONS Our twice replicated findings confirm that visual-motor functional connectivity is disrupted in ASD. Furthermore, the observed temporal incongruity between visual and motor systems, which may reflect diminished integration of visual consequences with motor output, was predictive of the severity of social deficits and may contribute to impaired social-communicative skill development in children with ASD.

Direct and indirect effects of fetal irradiation on cortical gray and white matter volume in the macaque

BACKGROUND Schizophrenia is associated with reductions in thalamic neuronal number and cortical gray matter volume. Exposure of nonhuman primates to x-irradiation in early gestation has previously been shown to decrease thalamic volume and neuronal number. Here we examine whether early gestational irradiation also results in cortical volume reduction. METHODS High-resolution, T1-weighted magnetic resonance scans were collected in adult monkeys 1) exposed to irradiation during the early gestational period (E33-E42) corresponding to thalamic neurogenesis, 2) irradiated in midgestation (E70-81) during neocortical neurogenesis, and 3) not exposed to irradiation. Cortical gray matter and white matter volumes were derived via manual segmentation; frontal and nonfrontal volumes were distinguished via sulcal landmarks. RESULTS Monkeys irradiated in early gestation exhibited a trend reduction in nonfrontal gray matter volume (17%) and significant reductions in white matter volume in frontal (26%) and nonfrontal (36%) lobes. Monkeys irradiated in midgestation had smaller gray (frontal: 28%; nonfrontal: 22%) and white matter (frontal: 29%; nonfrontal: 38%) volumes. CONCLUSIONS The cortical deficits observed in midgestationally irradiated monkeys are consistent with a reduction in cortical neuronal number. Cortical volume reductions following early gestational irradiation may be secondary to reduced thalamic neuronal number and therefore model the thalamocortical pathology of schizophrenia.

Precentral gyrus functional connectivity signatures of autism

Motor impairments are prevalent in children with autism spectrum disorders (ASD) and are perhaps the earliest symptoms to develop. In addition, motor skills relate to the communicative/social deficits at the core of ASD diagnosis, and these behavioral deficits may reflect abnormal connectivity within brain networks underlying motor control and learning. Despite the fact that motor abnormalities in ASD are well-characterized, there remains a fundamental disconnect between the complexity of the clinical presentation of ASD and the underlying neurobiological mechanisms. In this study, we examined connectivity within and between functional subregions of a key component of the motor control network, the precentral gyrus, using resting state functional Magnetic Resonance Imaging data collected from a large, heterogeneous sample of individuals with ASD as well as neurotypical controls. We found that the strength of connectivity within and between distinct functional subregions of the precentral gyrus was related to ASD diagnosis and to the severity of ASD traits. In particular, connectivity involving the dorsomedial (lower limb/trunk) subregion was abnormal in ASD individuals as predicted by models using a dichotomous variable coding for the presence of ASD, as well as models using symptom severity ratings. These findings provide further support for a link between motor and social/communicative abilities in ASD.

Altered cerebellar connectivity in autism and cerebellar-mediated rescue of autism-related behaviors in mice

Cerebellar abnormalities, particularly in Right Crus I (RCrusI), are consistently reported in autism spectrum disorders (ASD). Although RCrusI is functionally connected with ASD-implicated circuits, the contribution of RCrusI dysfunction to ASD remains unclear. Here neuromodulation of RCrusI in neurotypical humans resulted in altered functional connectivity with the inferior parietal lobule, and children with ASD showed atypical functional connectivity in this circuit. Atypical RCrusI–inferior parietal lobule structural connectivity was also evident in the Purkinje neuron (PN) TscI ASD mouse model. Additionally, chemogenetically mediated inhibition of RCrusI PN activity in mice was sufficient to generate ASD-related social, repetitive, and restricted behaviors, while stimulation of RCrusI PNs rescued social impairment in the PN TscI ASD mouse model. Together, these studies reveal important roles for RCrusI in ASD-related behaviors. Further, the rescue of social behaviors in an ASD mouse model suggests that investigation of the therapeutic potential of cerebellar neuromodulation in ASD may be warranted.Cerebellar right Crus I (RCrusI) has been implicated in autism spectrum disorder (ASD). RCrusI modulation altered RCrusI–inferior parietal lobule connectivity, and this connectivity was atypical in children with ASD and in a TscI mouse model of ASD. Inhibition of RCrusI in mice led to autism-related behaviors, and RCrusI activation rescued social impairments in TscI mice.

Atypical lateralization of motor circuit functional connectivity in children with autism is associated with motor deficits

BackgroundAtypical lateralization of language-related functions has been repeatedly found in individuals with autism spectrum conditions (ASC). Few studies have, however, investigated deviations from typically occurring asymmetry of other lateralized cognitive and behavioural domains. Motor deficits are among the earliest and most prominent symptoms in individuals with ASC and precede core social and communicative symptoms.MethodsHere, we investigate whether motor circuit connectivity is (1) atypically lateralized in children with ASC and (2) whether this relates to core autistic symptoms and motor performance. Participants comprised 44 right-handed high-functioning children with autism (36 males, 8 females) and 80 typically developing control children (58 males, 22 females) matched on age, sex and performance IQ. We examined lateralization of functional motor circuit connectivity based on homotopic seeds derived from peak activations during a finger tapping paradigm. Motor performance was assessed using the Physical and Neurological Examination for Subtle Signs (PANESS).ResultsChildren with ASC showed rightward lateralization in mean motor circuit connectivity compared to typically developing children, and this was associated with poorer performance on all three PANESS measures.ConclusionsOur findings reveal that atypical lateralization in ASC is not restricted to language functions but is also present in circuits subserving motor functions and may underlie motor deficits in children with ASC. Future studies should investigate whether this is an age-invariant finding extending to adolescents and adults and whether these asymmetries relate to atypical lateralization in the language domain.

Connectivity supporting attention in children with attention deficit hyperactivity disorder

Intra-subject variability (ISV) is the most consistent behavioral deficit in Attention Deficit Hyperactivity Disorder (ADHD). ISV may be associated with networks involved in sustaining task control (cingulo-opercular network: CON) and self-reflective lapses of attention (default mode network: DMN). The current study examined whether connectivity supporting attentional control is atypical in children with ADHD. Group differences in full-brain connection strength and brain–behavior associations with attentional control measures were examined for the late-developing CON and DMN in 50 children with ADHD and 50 typically-developing (TD) controls (ages 8–12 years). Children with ADHD had hyper-connectivity both within the CON and within the DMN. Full-brain behavioral associations were found for a number of between-network connections. Across both groups, more anti-correlation between DMN and occipital cortex supported better attentional control. However, in the TD group, this brain–behavior association was stronger and occurred for a more extensive set of DMN–occipital connections. Differential support for attentional control between the two groups occurred with a number of CON–DMN connections. For all CON–DMN connections identified, increased between-network anti-correlation was associated with better attentional control for the ADHD group, but worse attentional control in the TD group. A number of between-network connections with the medial frontal cortex, in particular, showed this relationship. Follow-up analyses revealed that these associations were specific to attentional control and were not due to individual differences in working memory, IQ, motor control, age, or scan motion. While CON–DMN anti-correlation is associated with improved attention in ADHD, other circuitry supports improved attention in TD children. Greater CON–DMN anti-correlation supported better attentional control in children with ADHD, but worse attentional control in TD children. On the other hand, greater DMN–occipital anti-correlation supported better attentional control in TD children.