A diffusion tensor imaging study of the cerebellar pathways in children with autism spectrum disorder

Motor Signature Differences Between Autism Spectrum Disorder and Developmental Coordination Disorder, and Their Neural Mechanisms

Autism spectrum disorder (ASD) and Developmental Coordination Disorder (DCD) are distinct clinical groups with overlapping motor features. We attempted to (1) differentiate children with ASD from those with DCD, and from those typically developing (TD) (ages 8-17; 18 ASD, 16 DCD, 20 TD) using a 5-min coloring game on a smart tablet and (2) identify neural correlates of these differences. We utilized standardized behavioral motor assessments (e.g. fine motor, gross motor, and balance skills) and video recordings of a smart tablet task to capture any visible motor, behavioral, posture, or engagement differences. We employed machine learning analytics of motor kinematics during a 5-min coloring game on a smart tablet. Imaging data was captured using functional magnetic resonance imaging (fMRI) during action production tasks. While subject-rated motor assessments could not differentiate the two clinical groups, machine learning computational analysis provided good predictive discrimination: between TD and ASD (76% accuracy), TD and DCD (78% accuracy), and ASD and DCD (71% accuracy). Two kinematic markers which strongly drove categorization were significantly correlated with cerebellar activity. Findings demonstrate unique neuromotor patterns between ASD and DCD relate to cerebellar function and present a promising route for computational techniques in early identification. These are promising preliminary results that warrant replication with larger samples.

Disrupted Human-Dog Interbrain Neural Coupling in Autism-Associated Shank3 Mutant Dogs

Dogs interact with humans effectively and intimately. However, the neural underpinnings for such interspecies social communication are not understood. It is known that interbrain activity coupling, i.e., the synchronization of neural activity between individuals, represents the neural basis of social interactions. Here, previously unknown cross-species interbrain activity coupling in interacting human-dog dyads is reported. By analyzing electroencephalography signals from both dogs and humans, it is found that mutual gaze and petting induce interbrain synchronization in the frontal and parietal regions of the human-dog dyads, respectively. The strength of the synchronization increases with growing familiarity of the human-dog dyad over five days, and the information flow analysis suggests that the human is the leader while the dog is the follower during human-dog interactions. Furthermore, dogs with Shank3 mutations, which represent a promising complementary animal model of autism spectrum disorders (ASD), show a loss of interbrain coupling and reduced attention during human-dog interactions. Such abnormalities are rescued by the psychedelic lysergic acid diethylamide (LSD). The results reveal previously unknown interbrain synchronizations within an interacting human-dog dyad which may underlie the interspecies communication, and suggest a potential of LSD for the amelioration of social impairment in patients with ASD.

Altered prefrontal and cerebellar parvalbumin neuron counts are associated with cognitive changes in male rats

Exposure to valproic acid (VPA), a common anti-seizure medication, in utero is a risk factor for autism spectrum disorder (ASD). People with ASD often display changes in the cerebellum, including volume changes, altered circuitry, and changes in Purkinje cell populations. ASD is also characterized by changes in the medial prefrontal cortex (mPFC), where excitatory/inhibitory balance is often altered. This study exposed rats to a high dose of VPA during gestation and assessed cognition and anxiety-like behaviors during young adulthood using a set-shifting task and the elevated plus maze. Inhibitory parvalbumin-expressing (PV +) neuron counts were assessed in the mPFC and cerebellar lobules VI and VII (Purkinje cell layers), which are known to modulate cognition. VPA males had increased PV + counts in crus I and II of lobule VII. VPA males also had decreased parvalbumin-expressing neuron counts in the mPFC. It was also found that VPA-exposed rats, regardless of sex, had increased parvalbumin-expressing Purkinje cell counts in lobule VI. In males, this was associated with impaired intra-dimensional shifting on a set-shifting task. Purkinje cell over proliferation may be contributing to the previously observed increase in volume of Lobule VI. These findings suggest that altered inhibitory signaling in cerebellar-frontal circuits may contribute to the cognitive deficits that occur within ASD.

Abnormality of Early White Matter Development in Tuberous Sclerosis Complex and Autism Spectrum Disorder: Longitudinal Analysis of Diffusion Tensor Imaging Measures

Background: Abnormalities in white matter development may influence development of autism spectrum disorder in tuberous sclerosis complex (TSC). Our goals for this study were as follows: (1) use data from a longitudinal neuroimaging study of tuberous sclerosis complex (TACERN) to develop optimized linear mixed effects models for analyzing longitudinal, repeated diffusion tensor imaging metrics (fractional anisotropy, mean diffusivity) pertaining to select white matter tracts, in relation to positive Autism Diagnostic Observation Schedule-Second Edition classification at 36 months, and (2) perform an exploratory analysis using optimized models applied to all white matter tracts from these data. Methods: Eligible participants (3-12 months) underwent brain magnetic resonance imaging (MRI) at repeated time points from ages 3 to 36 months. Positive Autism Diagnostic Observation Schedule-Second Edition classification at 36 months was used. Linear mixed effects models were fine-tuned separately for fractional anisotropy values (using fractional anisotropy corpus callosum as test outcome) and mean diffusivity values (using mean diffusivity right posterior limb internal capsule as test outcome). Fixed effects included participant age, within-participant longitudinal age, and autism spectrum disorder diagnosis. Results: Analysis included data from n = 78. After selecting separate optimal models for fractional anisotropy and mean diffusivity values, we applied these models to fractional anisotropy and mean diffusivity of all 27 white matter tracts. Fractional anisotropy corpus callosum was related to positive Autism Diagnostic Observation Schedule-Second Edition classification (coefficient = 0.0093, P = .0612), and mean diffusivity right inferior cerebellar peduncle was related to positive Autism Diagnostic Observation Schedule-Second Edition classification (coefficient = -0.00002071, P = .0445), though these findings were not statistically significant after multiple comparisons correction. Conclusion: These optimized linear mixed effects models possibly implicate corpus callosum and cerebellar pathology in development of autism spectrum disorder in tuberous sclerosis complex, but future studies are needed to replicate these findings and explore contributors of heterogeneity in these models.

Cerebellum Lecture: the Cerebellar Nuclei-Core of the Cerebellum

The cerebellum is a key player in many brain functions and a major topic of neuroscience research. However, the cerebellar nuclei (CN), the main output structures of the cerebellum, are often overlooked. This neglect is because research on the cerebellum typically focuses on the cortex and tends to treat the CN as relatively simple output nuclei conveying an inverted signal from the cerebellar cortex to the rest of the brain. In this review, by adopting a nucleocentric perspective we aim to rectify this impression. First, we describe CN anatomy and modularity and comprehensively integrate CN architecture with its highly organized but complex afferent and efferent connectivity. This is followed by a novel classification of the specific neuronal classes the CN comprise and speculate on the implications of CN structure and physiology for our understanding of adult cerebellar function. Based on this thorough review of the adult literature we provide a comprehensive overview of CN embryonic development and, by comparing cerebellar structures in various chordate clades, propose an interpretation of CN evolution. Despite their critical importance in cerebellar function, from a clinical perspective intriguingly few, if any, neurological disorders appear to primarily affect the CN. To highlight this curious anomaly, and encourage future nucleocentric interpretations, we build on our review to provide a brief overview of the various syndromes in which the CN are currently implicated. Finally, we summarize the specific perspectives that a nucleocentric view of the cerebellum brings, move major outstanding issues in CN biology to the limelight, and provide a roadmap to the key questions that need to be answered in order to create a comprehensive integrated model of CN structure, function, development, and evolution.

Whole Brain and Corpus Callosum Fractional Anisotropy Differences in Patients with Cognitive Impairment

Diffusion tensor imaging (DTI) is an MRI analysis method that could help assess cognitive impairment (CI) in the ageing population more accurately. In this research, we evaluated fractional anisotropy (FA) of whole brain (WB) and corpus callosum (CC) in patients with normal cognition (NC), mild cognitive impairment (MCI), and moderate/severe cognitive impairment (SCI). In total, 41 participants were included in a cross-sectional study and divided into groups based on Montreal Cognitive Assessment (MoCA) scores (NC group, nine participants, MCI group, sixteen participants, and SCI group, sixteen participants). All participants underwent an MRI examination that included a DTI sequence. FA values between the groups were assessed by analysing FA value and age normative percentile. We did not find statistically significant differences between the groups when analysing CC FA values. Both approaches showed statistically significant differences in WB FA values between the MCI-SCI and MCI-NC groups, where the MCI group participants showed the highest mean FA and highest mean FA normative percentile results in WB.

Associations of Behavioral Problems and White Matter Properties of the Cerebellar Peduncles in Boys and Girls Born Full Term and Preterm

Accumulating evidence suggests that the role of cerebellum includes regulation of behaviors; cerebellar impairment may lead to behavioral problems. Behavioral problems differ by sex: internalizing problems are more common in girls, externalizing problems in boys. Behavioral problems are also elevated in children born preterm (PT) compared to children born full term (FT). The current study examined internalizing and externalizing problems in 8-year-old children in relation to sex, birth-group, fractional anisotropy (FA) of the three cerebellar peduncles (superior, middle, and inferior), and interactions among these predictor variables. Participants (N = 78) were 44 boys (28 PT) and 34 girls (15 PT). We assessed behavioral problems via standardized parent reports and FA of the cerebellar peduncles using deterministic tractography. Internalizing problems were higher in children born PT compared to children born FT (p = .032); the interaction of sex and birth-group was significant (p = .044). When considering the contribution of the mean-tract FA of cerebellar peduncles to behavioral problems, there was a significant interaction of sex and mean-tract FA of the inferior cerebellar peduncle (ICP) with internalizing problems; the slope was negative in girls (p = .020) but not in boys. In boys, internalizing problems were only associated with mean-tract FA ICP in those born preterm (p = .010). We found no other significant associations contributing to internalizing or externalizing problems. Thus, we found sexual dimorphism and birth-group differences in the association of white matter metrics of the ICP and internalizing problems in school-aged children. The findings inform theories of the origins of internalizing behavioral problems in middle childhood and may suggest approaches to treatment at school age.

Classification of Preschoolers with Low-Functioning Autism Spectrum Disorder Using Multimodal MRI Data

Multimodal imaging studies targeting preschoolers and low-functioning autism spectrum disorder (ASD) patients are scarce. We applied machine learning classifiers to parameters from T1-weighted MRI and DTI data of 58 children with ASD (age 3-6 years) and 48 typically developing controls (TDC). Classification performance reached an accuracy, sensitivity, and specificity of 88.8%, 93.0%, and 83.8%, respectively. The most prominent features were the cortical thickness of the right inferior occipital gyrus, mean diffusivity of the middle cerebellar peduncle, and nodal efficiency of the left posterior cingulate gyrus. Machine learning-based analysis of MRI data was useful in distinguishing low-functioning ASD preschoolers from TDCs. Combination of T1 and DTI improved classification accuracy about 10%, and large-scale multi-modal MRI studies are warranted for external validation.

Specific tractography differences in autism compared to developmental coordination disorder

About 85% of children with autism spectrum disorder (ASD) experience comorbid motor impairments, making it unclear whether white matter abnormalities previously found in ASD are related to social communication deficits, the hallmark of ASD, or instead related to comorbid motor impairment. Here we aim to understand specific white matter signatures of ASD beyond those related to comorbid motor impairment by comparing youth (aged 8-18) with ASD (n = 22), developmental coordination disorder (DCD; n = 16), and typically developing youth (TD; n = 22). Diffusion weighted imaging was collected and quantitative anisotropy, radial diffusivity, mean diffusivity, and axial diffusivity were compared between the three groups and correlated with social and motor measures. Compared to DCD and TD groups, diffusivity differences were found in the ASD group in the mid-cingulum longitudinal and u-fibers, the corpus callosum forceps minor/anterior commissure, and the left middle cerebellar peduncle. Compared to the TD group, the ASD group had diffusivity differences in the right inferior frontal occipital/extreme capsule and genu of the corpus callosum. These diffusion differences correlated with emotional deficits and/or autism severity. By contrast, children with DCD showed unique abnormality in the left cortico-spinal and cortico-pontine tracts.Trial Registration All data are available on the National Institute of Mental Health Data Archive: https://nda.nih.gov/edit_collection.html?id=2254 .

Cerebellar Volumes and Sensorimotor Behavior in Autism Spectrum Disorder

Background

Sensorimotor issues are common in autism spectrum disorder (ASD), though their neural bases are not well understood. The cerebellum is vital to sensorimotor control and reduced cerebellar volumes in ASD have been documented. Our study examined the extent to which cerebellar volumes are associated with multiple sensorimotor behaviors in ASD.

Materials and Methods

Fifty-eight participants with ASD and 34 typically developing (TD) controls (8-30 years) completed a structural MRI scan and precision grip testing, oculomotor testing, or both. Force variability during precision gripping as well as absolute error and trial-to-trial error variability of visually guided saccades were examined. Volumes of cerebellar lobules, vermis, and white matter were quantified. The relationships between each cerebellar region of interest (ROI) and force variability, saccade error, and saccade error variability were examined.

Results

Relative to TD controls, individuals with ASD showed increased force variability. Individuals with ASD showed a reduced volume of cerebellar vermis VI-VII relative to TD controls. Relative to TD females, females with ASD showed a reduced volume of bilateral cerebellar Crus II/lobule VIIB. Increased volume of Crus I was associated with increased force variability. Increased volume of vermal lobules VI-VII was associated with reduced saccade error for TD controls but not individuals with ASD. Increased right lobule VIII and cerebellar white matter volumes as well as reduced right lobule VI and right lobule X volumes were associated with greater ASD symptom severity. Reduced volumes of right Crus II/lobule VIIB were associated with greater ASD symptom severity in only males, while reduced volumes of right Crus I were associated with more severe restricted and repetitive behaviors only in females.

Conclusion

Our finding that increased force variability in ASD is associated with greater cerebellar Crus I volumes indicates that disruption of sensory feedback processing supported by Crus I may contribute to skeletomotor differences in ASD. Results showing that volumes of vermal lobules VI-VII are associated with saccade precision in TD but not ASD implicates atypical organization of the brain systems supporting oculomotor control in ASD. Associations between volumes of cerebellar subregions and ASD symptom severity suggest cerebellar pathological processes may contribute to multiple developmental challenges in ASD.

Structure, Function, and Genetics of the Cerebellum in Autism

Autism spectrum disorders are common neurodevelopmental disorders that are defined by core behavioral symptoms but have diverse genetic and environmental risk factors. Despite its etiological heterogeneity, several unifying theories of autism have been proposed, including a central role for cerebellar dysfunction. The cerebellum follows a protracted course of development that culminates in an exquisitely crafted brain structure containing over half of the neurons in the entire brain densely packed into a highly organized structure. Through its complex network of connections with cortical and subcortical brain regions, the cerebellum acts as a sensorimotor regulator and affects changes in executive and limbic processing. In this review, we summarize the structural, functional, and genetic contributions of the cerebellum to autism.

The Role of Diffusion Tensor MR Imaging (DTI) of the Brain in Diagnosing Autism Spectrum Disorder: Promising Results

Autism spectrum disorder (ASD) is a combination of developmental anomalies that causes social and behavioral impairments, affecting around 2% of US children. Common symptoms include difficulties in communications, interactions, and behavioral disabilities. The onset of symptoms can start in early childhood, yet repeated visits to a pediatric specialist are needed before reaching a diagnosis. Still, this diagnosis is usually subjective, and scores can vary from one specialist to another. Previous literature suggests differences in brain development, environmental, and/or genetic factors play a role in developing autism, yet scientists still do not know exactly the pathology of this disorder. Currently, the gold standard diagnosis of ASD is a set of diagnostic evaluations, such as the Autism Diagnostic Observation Schedule (ADOS) or Autism Diagnostic Interview-Revised (ADI-R) report. These gold standard diagnostic instruments are an intensive, lengthy, and subjective process that involves a set of behavioral and communications tests and clinical history information conducted by a team of qualified clinicians. Emerging advancements in neuroimaging and machine learning techniques can provide a fast and objective alternative to conventional repetitive observational assessments. This paper provides a thorough study of implementing feature engineering tools to find discriminant insights from brain imaging of white matter connectivity and using a machine learning framework for an accurate classification of autistic individuals. This work highlights important findings of impacted brain areas that contribute to an autism diagnosis and presents promising accuracy results. We verified our proposed framework on a large publicly available DTI dataset of 225 subjects from the Autism Brain Imaging Data Exchange-II (ABIDE-II) initiative, achieving a high global balanced accuracy over the 5 sites of up to 99% with 5-fold cross validation. The data used was slightly unbalanced, including 125 autistic subjects and 100 typically developed (TD) ones. The achieved balanced accuracy of the proposed technique is the highest in the literature, which elucidates the importance of feature engineering steps involved in extracting useful knowledge and the promising potentials of adopting neuroimaging for the diagnosis of autism.

Adaptive Prediction for Social Contexts: The Cerebellar Contribution to Typical and Atypical Social Behaviors

Social interactions involve processes ranging from face recognition to understanding others' intentions. To guide appropriate behavior in a given context, social interactions rely on accurately predicting the outcomes of one's actions and the thoughts of others. Because social interactions are inherently dynamic, these predictions must be continuously adapted. The neural correlates of social processing have largely focused on emotion, mentalizing, and reward networks, without integration of systems involved in prediction. The cerebellum forms predictive models to calibrate movements and adapt them to changing situations, and cerebellar predictive modeling is thought to extend to nonmotor behaviors. Primary cerebellar dysfunction can produce social deficits, and atypical cerebellar structure and function are reported in autism, which is characterized by social communication challenges and atypical predictive processing. We examine the evidence that cerebellar-mediated predictions and adaptation play important roles in social processes and argue that disruptions in these processes contribute to autism.

Neurobiological and behavioural outcomes of biofeedback-based training in autism: a randomized controlled trial

The human brain has demonstrated the power to structurally change as a result of movement-based interventions. However, it is unclear whether these structural brain changes differ in autistic individuals compared to non-autistic individuals. The purpose of the present study was to pilot a randomized controlled trial to investigate brain, balance, autism symptom severity and daily living skill changes that result from a biofeedback-based balance intervention in autistic adolescents (13-17 years old). Thirty-four autistic participants and 28 age-matched non-autistic participants underwent diagnostic testing and pre-training assessment (neuroimaging, cognitive, autism symptom severity and motor assessments) and were then randomly assigned to 6 weeks of a balance-training intervention or a sedentary-control condition. After the 6 weeks, neuroimaging, symptom severity and motor assessments were repeated. Results found that both the autistic and non-autistic participants demonstrated similar and significant increases in balance times with training. Furthermore, individuals in the balance-training condition showed significantly greater improvements in postural sway and reductions in autism symptom severity compared to individuals in the control condition. Daily living scores did not change with training, nor did we observe hypothesized changes to the microstructural properties of the corticospinal tract. However, follow-up voxel-based analyses found a wide range of balance-related structures that showed changes across the brain. Many of these brain changes were specific to the autistic participants compared to the non-autistic participants, suggesting distinct structural neuroplasticity in response to balance training in autistic participants. Altogether, these findings suggest that biofeedback-based balance training may target postural stability challenges, reduce core autism symptoms and influence neurobiological change. Future research is encouraged to examine the superior cerebellar peduncle in response to balance training and symptom severity changes in autistic individuals, as the current study produced overlapping findings in this brain region.

Contributions of Cerebellar White Matter Microstructure to Social Difficulty in Nonverbal Learning Disability

Emerging evidence suggests that the cerebellum may contribute to variety of cognitive capacities, including social cognition. Nonverbal learning disability (NVLD) is characterized by visual-spatial and social impairment. Recent functional neuroimaging studies have shown that children with NVLD have altered cerebellar resting-state functional connectivity, which is associated with various symptom domains. However, little is known about cerebellar white matter microstructure in NVLD and whether it contributes to social deficits. Twenty-seven children (12 with NVLD, 15 typically developing (TD)) contributed useable diffusion tensor imaging data. Tract-based spatial statistics (TBSS) were used to quantify fractional anisotropy (FA) in the cerebellar peduncles. Parents completed the Child Behavior Checklist, providing a measure of social difficulty. Children with NVLD had greater fractional anisotropy in the left and right inferior cerebellar peduncle. Furthermore, right inferior cerebellar peduncle FA was associated with social impairment as measured by the Child Behavior Checklist Social Problems subscale. Finally, the association between NVLD diagnosis and greater social impairment was mediated by right inferior cerebellar peduncle FA. These findings provide additional evidence that the cerebellum contributes both to social cognition and to the pathophysiology of NVLD.

Abnormal Cerebellar Development in Autism Spectrum Disorders

Autism spectrum disorders (ASD) comprise a group of heterogeneous neurodevelopmental conditions characterized by impaired social interactions and repetitive behaviors with symptom onset in early infancy. The genetic risks for ASD have long been appreciated: concordance of ASD diagnosis may be as high as 90% for monozygotic twins and 30% for dizygotic twins, and hundreds of mutations in single genes have been associated with ASD. Nevertheless, only 5-30% of ASD cases can be explained by a known genetic cause, suggesting that genetics is not the only factor at play. More recently, several studies reported that up to 40% of infants with cerebellar hemorrhages and lesions are diagnosed with ASD. These hemorrhages are overrepresented in severely premature infants, who are born during a period of highly dynamic cerebellar development that encompasses an approximately 5-fold size expansion, an increase in structural complexity, and remarkable rearrangements of local neural circuits. The incidence of ASD-causing cerebellar hemorrhages during this window supports the hypothesis that abnormal cerebellar development may be a primary risk factor for ASD. However, the links between developmental deficits in the cerebellum and the neurological dysfunctions underlying ASD are not completely understood. Here, we discuss key processes in cerebellar development, what happens to the cerebellar circuit when development is interrupted, and how impaired cerebellar function leads to social and cognitive impairments. We explore a central question: Is cerebellar development important for the generation of the social and cognitive brain or is the cerebellum part of the social and cognitive brain itself?

Role of Oligodendrocytes and Myelin in the Pathophysiology of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is an early neurodevelopmental disorder that involves deficits in interpersonal communication, social interaction, and repetitive behaviors. Although ASD pathophysiology is still uncertain, alterations in the abnormal development of the frontal lobe, limbic areas, and putamen generate an imbalance between inhibition and excitation of neuronal activity. Interestingly, recent findings suggest that a disruption in neuronal connectivity is associated with neural alterations in white matter production and myelination in diverse brain regions of patients with ASD. This review is aimed to summarize the most recent evidence that supports the notion that abnormalities in the oligodendrocyte generation and axonal myelination in specific brain regions are involved in the pathophysiology of ASD. Fundamental molecular mediators of these pathological processes are also examined. Determining the role of alterations in oligodendrogenesis and myelination is a fundamental step to understand the pathophysiology of ASD and identify possible therapeutic targets.

Consensus Paper: Cerebellum and Social Cognition

The traditional view on the cerebellum is that it controls motor behavior. Although recent work has revealed that the cerebellum supports also nonmotor functions such as cognition and affect, only during the last 5 years it has become evident that the cerebellum also plays an important social role. This role is evident in social cognition based on interpreting goal-directed actions through the movements of individuals (social "mirroring") which is very close to its original role in motor learning, as well as in social understanding of other individuals' mental state, such as their intentions, beliefs, past behaviors, future aspirations, and personality traits (social "mentalizing"). Most of this mentalizing role is supported by the posterior cerebellum (e.g., Crus I and II). The most dominant hypothesis is that the cerebellum assists in learning and understanding social action sequences, and so facilitates social cognition by supporting optimal predictions about imminent or future social interaction and cooperation. This consensus paper brings together experts from different fields to discuss recent efforts in understanding the role of the cerebellum in social cognition, and the understanding of social behaviors and mental states by others, its effect on clinical impairments such as cerebellar ataxia and autism spectrum disorder, and how the cerebellum can become a potential target for noninvasive brain stimulation as a therapeutic intervention. We report on the most recent empirical findings and techniques for understanding and manipulating cerebellar circuits in humans. Cerebellar circuitry appears now as a key structure to elucidate social interactions.

Functional Outcomes of Cerebellar Malformations

The cerebellum is well-established as a primary center for controlling sensorimotor functions. However, recent experiments have demonstrated additional roles for the cerebellum in higher-order cognitive functions such as language, emotion, reward, social behavior, and working memory. Based on the diversity of behaviors that it can influence, it is therefore not surprising that cerebellar dysfunction is linked to motor diseases such as ataxia, dystonia, tremor, and Parkinson's disease as well to non-motor disorders including autism spectrum disorders (ASD), schizophrenia, depression, and anxiety. Regardless of the condition, there is a growing consensus that developmental disturbances of the cerebellum may be a central culprit in triggering a number of distinct pathophysiological processes. Here, we consider how cerebellar malformations and neuronal circuit wiring impact brain function and behavior during development. We use the cerebellum as a model to discuss the expanding view that local integrated brain circuits function within the context of distributed global networks to communicate the computations that drive complex behavior. We highlight growing concerns that neurological and neuropsychiatric diseases with severe behavioral outcomes originate from developmental insults to the cerebellum.

A Novel Approach to Enhancing Upper Extremity Coordination in Children with Autism Spectrum Disorder

Recent studies examining children diagnosed with Autism Spectrum Disorder (ASD) have revealed kinematic markers highlighting deficits in the preparatory and online phases of upper extremity movements. In the following study, 12 children with high functioning ASD were first assessed (pre-test) on 15 trials of a reciprocal upper extremity Fitts Law target task by flexing and extending their right arm in the horizontal plane between two targets as fast and accurately as possible. Following the initial assessment, the children either continued with 30 additional trials of the target task (control) or were asked to track a sine wave template (experimental). All participants were then assessed on 15 trials of the target test (post-test). Results reveal that tracking the sine wave template during training not only produced faster movements compared to the control but also produced these movements in a more harmonic way.

Resting-State Brain Network Dysfunctions Associated With Visuomotor Impairments in Autism Spectrum Disorder

Background: Individuals with autism spectrum disorder (ASD) show elevated levels of motor variability that are associated with clinical outcomes. Cortical-cerebellar networks involved in visuomotor control have been implicated in postmortem and anatomical imaging studies of ASD. However, the extent to which these networks show intrinsic functional alterations in patients, and the relationship between intrinsic functional properties of cortical-cerebellar networks and visuomotor impairments in ASD have not yet been clarified. Methods: We examined the amplitude of low-frequency fluctuation (ALFF) of cortical and cerebellar brain regions during resting-state functional MRI (rs-fMRI) in 23 individuals with ASD and 16 typically developing (TD) controls. Regions of interest (ROIs) with ALFF values significantly associated with motor variability were identified for for patients and controls respectively, and their functional connectivity (FC) to each other and to the rest of the brain was examined. Results: For TD controls, greater ALFF in bilateral cerebellar crus I, left superior temporal gyrus, left inferior frontal gyrus, right supramarginal gyrus, and left angular gyrus each were associated with greater visuomotor variability. Greater ALFF in cerebellar lobule VIII was associated with less visuomotor variability. For individuals with ASD, greater ALFF in right calcarine cortex, right middle temporal gyrus (including MT/V5), left Heschl's gyrus, left post-central gyrus, right pre-central gyrus, and left precuneus was related to greater visuomotor variability. Greater ALFF in cerebellar vermis VI was associated with less visuomotor variability. Individuals with ASD and TD controls did not show differences in ALFF for any of these ROIs. Individuals with ASD showed greater posterior cerebellar connectivity with occipital and parietal cortices relative to TD controls, and reduced FC within cerebellum and between lateral cerebellum and pre-frontal and other regions of association cortex. Conclusion: Together, these findings suggest that increased resting oscillations within visuomotor networks in ASD are associated with more severe deficits in controlling variability during precision visuomotor behavior. Differences between individuals with ASD and TD controls in the topography of networks showing relationships to visuomotor behavior suggest atypical patterns of cerebellar-cortical specialization and connectivity in ASD that underlies previously documented visuomotor deficits.

Brain Network Organization Correlates with Autistic Features in Preschoolers with Autism Spectrum Disorders and in Their Fathers: Preliminary Data from a DWI Analysis

Autism Spectrum Disorders (ASD) is a group of neurodevelopmental disorders that is characterized by an altered brain connectivity organization. Autistic traits below the clinical threshold (i.e., the broad autism phenotype; BAP) are frequent among first-degree relatives of subjects with ASD; however, little is known regarding whether subthreshold behavioral manifestations of ASD mirror also at the neuroanatomical level in parents of ASD probands. To this aim, we applied advanced diffusion network analysis to MRI of 16 dyads consisting of a child with ASD and his father in order to investigate: (i) the correlation between structural network organization and autistic features in preschoolers with ASD (all males; age range 1.5-5.2 years); (ii) the correlation between structural network organization and BAP features in the fathers of individuals with ASD (fath-ASD). Local network measures significantly correlated with autism severity in ASD children and with BAP traits in fath-ASD, while no significant association emerged when considering the global measures of brain connectivity. Notably, an overlap of some brain regions that are crucial for social functioning (cingulum, superior temporal gyrus, inferior temporal gyrus, middle frontal gyrus, frontal pole, and amygdala) in patients with ASD and fath-ASD was detected, suggesting an intergenerational transmission of these neural substrates. Overall, the results of this study may help in elucidating the neurostructural endophenotype of ASD, paving the way for bridging connections between underlying genetic and ASD symptomatology.

Cerebellar involvement in autism and ADHD

The cerebellum has long been known for its importance in motor learning and coordination. However, increasing evidence supports a role for the cerebellum in cognition and emotion. Consistent with a role in cognitive functions, the cerebellum has emerged as one of the key brain regions affected in nonmotor disorders, including autism spectrum disorder and attention deficit-hyperactivity disorder. Here, we discuss behavioral, postmortem, genetic, and neuroimaging studies in humans in order to understand the cerebellar contributions to the pathogenesis of both disorders. We also review relevant animal model findings.

Diffusion Tensor Tractography of the Cerebellar Peduncles in Prematurely Born 7-Year-Old Children

The objective of this study was to correlate neurodevelopmental outcome of preterm-born children and their perinatal clinical and imaging characteristics with diffusion magnetic resonance imaging (MRI) measures of the three cerebellar peduncles at age 7. Included in this prospective longitudinal study were 140 preterm-born children (<30 weeks gestation) who underwent neurodevelopmental assessment (IQ, motor, language, working memory) and diffusion-weighted imaging (DWI) at age 7 years. White matter tracts in the superior, middle, and inferior cerebellar peduncles were delineated using regions of interest drawn on T2-weighted images and fractional anisotropy (FA) maps. Diffusion measures (mean diffusivity (MD) and FA) and tract volumes were calculated. Linear regression was used to assess relationships with outcome. The severity of white matter injury in the neonatal period was associated with lower FA in the right superior cerebellar peduncle (SCP) and lower tract volumes of both SCPs and middle cerebellar peduncles (MCPs). In the MCP, higher IQ was associated with lower MD in the whole group and higher FA in right-handed children. In the SCP, lower motor scores were associated with higher MD and higher language scores were associated with higher FA. These associations remained significant in multivariable models. This study adds to the body of literature detailing the importance of cerebellar involvement in cognitive function related to reciprocal connections with supratentorial structures.

From molecules to behavior: An integrative theory of autism spectrum disorder

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders for which various theories have been proposed. Each theory brings valuable insights and has experimental evidence backing it, yet none provides an overarching explanation for each of the pathological aspects involved in ASD. Here we present an integrative theory of ASD, centered on a sequence of events spanning from the molecular to the behavioral level. We propose that an abnormality in the interplay between retinoic acid and sex hormones predisposes an individual to specific molecular malfunctions. In turn, this molecular syndrome generates an altered brain connectivity between the cerebellum, the midbrain dopaminergic areas, and the prefrontal cortex. Lastly, this disconnection would generate specific behavioral traits traditionally involved in ASD. Therefore, this paper represents a step forward in unifying different levels of pathological features into novel integrated testable hypotheses.

Resting-State Functional Connectivity Changes Between Dentate Nucleus and Cortical Social Brain Regions in Autism Spectrum Disorders

Autism spectrum disorders (ASDs) are known to be characterized by restricted and repetitive behaviors and interests and by impairments in social communication and interactions mainly including "theory of mind" (ToM) processes. The cerebellum has emerged as one of the brain regions affected by ASDs. As the cerebellum is known to influence cerebral cortex activity via cerebello-thalamo-cortical (CTC) circuits, it has been proposed that cerebello-cortical "disconnection" could in part underlie autistic symptoms. We used resting-state (RS) functional magnetic resonance imaging (fMRI) to investigate the potential RS connectivity changes between the cerebellar dentate nucleus (DN) and the CTC circuit targets, that may contribute to ASD pathophysiology. When comparing ASD patients to controls, we found decreased connectivity between the left DN and cerebral regions known to be components of the ToM network and the default mode network, implicated in specific aspects of mentalizing, social cognition processing, and higher order emotional processes. Further, a pattern of overconnectivity was also detected between the left DN and the supramodal cerebellar lobules associated with the default mode network. The presented RS-fMRI data provide evidence that functional connectivity (FC) between the dentate nucleus and the cerebral cortex is altered in ASD patients. This suggests that the dysfunction reported within the cerebral cortical network, typically related to social features of ASDs, may be at least partially related to an impaired interaction between cerebellum and key cortical social brain regions.

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.

Alteration of functional connectivity in autism spectrum disorder: effect of age and anatomical distance

Autism spectrum disorder (ASD) is associated with disruption of local- and long-range functional connectivity (FC). The direction of those changes in FC (increase or decrease), however, is inconsistent across studies. Further, age-dependent changes of distance-specific FC in ASD remain unclear. In this study, we used resting-state functional magnetic resonance imaging data from sixty-four typical controls (TC) and sixty-four patients with ASD, whom we further classified into child (<11 years), adolescent (11-18 years) and adult cohorts (>18 years). Functional connectivity (FC) analysis was conducted at voxel level. We employed a three-way analysis of covariance on FC to conduct statistical analyses. Results revealed that patients with ASD had lower FC than TC in cerebellum, fusiform gyrus, inferior occipital gyrus and posterior inferior temporal gyrus. Significant diagnosis-by-distance interaction was observed in ASD patients with reduced short-range and long-range FC in posterior cingulate cortex and medial prefrontal cortex. Importantly, we found significant diagnosis-by-age-by-distance interaction in orbitofrontal cortex with short-range FC being lower in autistic children, but -to a less extent- higher in autistic adults. Our findings suggest a major role of connection length in development changes of FC in ASD. We hope our study will facilitate deeper understanding of the neural mechanisms underlying ASD.

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics.

The Disrupted Connectivity Hypothesis of Autism Spectrum Disorders: Time for the Next Phase in Research

During the past decade, the disrupted connectivity theory has generated considerable interest as a pathophysiological model for autism spectrum disorders (ASD). This theory postulates that deficiencies in the way the brain coordinates and synchronizes activity amongst different regions may account for the clinical symptoms of ASD. This review critically examines the current structural and functional connectivity data in ASD and evaluates unresolved assumptions and gaps in knowledge that limit the interpretation of these data. Collectively, studies very often show group alterations in what are thought of as measures of cerebral connectivity, though the patterns of findings vary considerably. We argue that there are three principle needs in this research agenda. First, further basic research is needed to understand the links between measures commonly used (DTI, fMRI, EEG) and other (histological, computational) levels of analysis. Second, speculated causes of inconsistencies in the literature (age, clinical heterogeneity) demand studies that directly evaluate these interpretations. Finally, the field needs well-specified mechanistic models of altered cerebral communication in ASD whose predictions can be tested on multiple levels of analyses.

Quality Assurance using Outlier Detection on an Automatic Segmentation Method for the Cerebellar Peduncles

Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis. In this work, two outlier detection methods aimed to assess the performance of an automatic CP segmentation algorithm are presented. The first one is a univariate non-parametric method using a box-whisker plot. We first categorize automatic segmentation results of a dataset of diffusion tensor imaging (DTI) scans from 48 subjects as either a success or a failure. We then design three groups of features from the image data of nine categorized failures for failure detection. Results show that most of these features can efficiently detect the true failures. The second method-supervised classification-was employed on a larger DTI dataset of 249 manually categorized subjects. Four classifiers-linear discriminant analysis (LDA), logistic regression (LR), support vector machine (SVM), and random forest classification (RFC)-were trained using the designed features and evaluated using a leave-one-out cross validation. Results show that the LR performs worst among the four classifiers and the other three perform comparably, which demonstrates the feasibility of automatically detecting segmentation failures using classification methods.

Characterization of gait and olfactory behaviors in the Balb/c mouse model of autism spectrum disorders

Abnormalities of gait and olfaction have been reported in persons with autism spectrum disorders (ASDs), which could reflect involvement of the cerebellum and nodes related to olfaction (e.g., olfactory bulb and ventral temporal olfactory cortex) in neural circuits subserving social, cognitive, and motor domains of psychopathology in these disorders. We hypothesized that the Balb/c mouse model of ASD would express "abnormalities" of gait and olfaction, relative to the Swiss Webster comparator strain. Contrary to expectation, Balb/c and Swiss Webster mice did not differ in terms of quantitative measurements of gait and mouse rotarod behavior, and Balb/c mice displayed a shorter latency to approach an unscented cotton swab, suggesting that there was no disturbance of its locomotor behavior. However, Balb/c mice showed significant inhibition of locomotor activity in the presence of floral scents, including novel and familiar floral scents, and a socially salient odor (i.e., concentrated mouse urine); the inhibitory effect on the locomotor behavior of the Balb/c mouse was especially pronounced with the salient social odor. Unlike the Swiss Webster strain, mouse urine lacks social salience for the Balb/c mouse strain, a model of ASD, which does not appear to be an artifact of diminished olfactory sensitivity or impaired locomotion.

Cortico-Cerebellar Connectivity in Autism Spectrum Disorder: What Do We Know So Far?

Although the Autism Spectrum Disorder (ASD) is renowned to be a connectivity disorder and a condition characterized by cerebellar involvement, the connectivity between the cerebellum and other cortical brain regions is particularly underexamined. Indeed, converging evidence has recently suggested that the cerebellum could play a key role in the etiopathogenesis of ASD, since cerebellar anomalies have been consistently reported in ASD from the molecular to the behavioral level, and damage to the cerebellum early in development has been linked with signs of autistic features. In addition, current data have shown that the cerebellum is a key structure not only for sensory-motor control, but also for "higher functions," such as social cognition and emotion, through its extensive connections with cortical areas. The disruption of these circuits could be implicated in the wide range of autistic symptoms that the term "spectrum" connotes. In this review, we present and discuss the recent findings from imaging studies that investigated cortico-cerebellar connectivity in people with ASD. The literature is still too limited to allow for definitive conclusions; however, this brief review reveals substantial areas for future studies, underlining currently unmet research perspectives.

Cerebellar Development and Autism Spectrum Disorder in Tuberous Sclerosis Complex

Approximately 50% of patients with the genetic disease tuberous sclerosis complex present with autism spectrum disorder. Although a number of studies have investigated the link between autism and tuberous sclerosis complex, the etiology of autism spectrum disorder in these patients remains unclear. Abnormal cerebellar function during critical phases of development could disrupt functional processes in the brain, leading to development of autistic features. Accordingly, the authors review the potential role of cerebellar dysfunction in the pathogenesis of autism spectrum disorder in tuberous sclerosis complex. The authors also introduce conditional knockout mouse models of Tsc1 and Tsc2 that link cerebellar circuitry to the development of autistic-like features. Taken together, these preclinical and clinical investigations indicate the cerebellum has a profound regulatory role during development of social communication and repetitive behaviors.

Cerebro-cerebellar circuits in autism spectrum disorder

The cerebellum is one of the most consistent sites of abnormality in autism spectrum disorder (ASD) and cerebellar damage is associated with an increased risk of ASD symptoms, suggesting that cerebellar dysfunction may play a crucial role in the etiology of ASD. The cerebellum forms multiple closed-loop circuits with cerebral cortical regions that underpin movement, language, and social processing. Through these circuits, cerebellar dysfunction could impact the core ASD symptoms of social and communication deficits and repetitive and stereotyped behaviors. The emerging topography of sensorimotor, cognitive, and affective subregions in the cerebellum provides a new framework for interpreting the significance of regional cerebellar findings in ASD and their relationship to broader cerebro-cerebellar circuits. Further, recent research supports the idea that the integrity of cerebro-cerebellar loops might be important for early cortical development; disruptions in specific cerebro-cerebellar loops in ASD might impede the specialization of cortical regions involved in motor control, language, and social interaction, leading to impairments in these domains. Consistent with this concept, structural, and functional differences in sensorimotor regions of the cerebellum and sensorimotor cerebro-cerebellar circuits are associated with deficits in motor control and increased repetitive and stereotyped behaviors in ASD. Further, communication and social impairments are associated with atypical activation and structure in cerebro-cerebellar loops underpinning language and social cognition. Finally, there is converging evidence from structural, functional, and connectivity neuroimaging studies that cerebellar right Crus I/II abnormalities are related to more severe ASD impairments in all domains. We propose that cerebellar abnormalities may disrupt optimization of both structure and function in specific cerebro-cerebellar circuits in ASD.

Cerebro-cerebellar Resting-State Functional Connectivity in Children and Adolescents with Autism Spectrum Disorder

BACKGROUND

The cerebellum plays important roles in sensori-motor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available.

METHODS

We used resting-state functional connectivity magnetic resonance imaging in 56 children and adolescents (28 subjects with ASD, 28 typically developing subjects) 8-17 years old. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensori-motor (premotor/primary motor, somatosensory, superior temporal, and occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal).

RESULTS

There were three main findings: 1) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; 2) partial correlation analyses that emphasized domain specificity (sensori-motor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared with the typically developing group) for sensori-motor ROIs but predominantly reduced connectivity for supramodal ROIs; and 3) this atypical pattern of connectivity was supported by significantly increased noncanonical connections (between sensori-motor cerebral and supramodal cerebellar ROIs and vice versa) in the ASD group.

CONCLUSIONS

Our findings indicate that sensori-motor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition.

The role of cerebellar circuitry alterations in the pathophysiology of autism spectrum disorders

The cerebellum has been repeatedly implicated in gene expression, rodent model and post-mortem studies of autism spectrum disorder (ASD). How cellular and molecular anomalies of the cerebellum relate to clinical manifestations of ASD remains unclear. Separate circuits of the cerebellum control different sensorimotor behaviors, such as maintaining balance, walking, making eye movements, reaching, and grasping. Each of these behaviors has been found to be impaired in ASD, suggesting that multiple distinct circuits of the cerebellum may be involved in the pathogenesis of patients' sensorimotor impairments. We will review evidence that the development of these circuits is disrupted in individuals with ASD and that their study may help elucidate the pathophysiology of sensorimotor deficits and core symptoms of the disorder. Preclinical studies of monogenetic conditions associated with ASD also have identified selective defects of the cerebellum and documented behavioral rescues when the cerebellum is targeted. Based on these findings, we propose that cerebellar circuits may prove to be promising targets for therapeutic development aimed at rescuing sensorimotor and other clinical symptoms of different forms of ASD.

White matter microstructure predicts autistic traits in attention-deficit/hyperactivity disorder

Traits of autism spectrum disorder (ASD) in children with attention-deficit/hyperactivity disorder (ADHD) have previously been found to index clinical severity. This study examined the association of ASD traits with diffusion parameters in adolescent males with ADHD (n = 17), and also compared WM microstructure relative to controls (n = 17). Significant associations (p < 0.05, corrected) were found between fractional anisotropy/radial diffusivity and ASD trait severity (positive and negative correlations respectively), mostly in the right posterior limb of the internal capsule/corticospinal tract, right cerebellar peduncle and the midbrain. No case-control differences were found for the diffusion parameters investigated. This is the first report of a WM microstructural signature of autistic traits in ADHD. Thus, even in the absence of full disorder, ASD traits may index a distinctive underlying neurobiology in ADHD.

Segmentation of the Cerebellar Peduncles Using a Random Forest Classifier and a Multi-object Geometric Deformable Model: Application to Spinocerebellar Ataxia Type 6

The cerebellar peduncles, comprising the superior cerebellar peduncles (SCPs), the middle cerebellar peduncle (MCP), and the inferior cerebellar peduncles (ICPs), are white matter tracts that connect the cerebellum to other parts of the central nervous system. Methods for automatic segmentation and quantification of the cerebellar peduncles are needed for objectively and efficiently studying their structure and function. Diffusion tensor imaging (DTI) provides key information to support this goal, but it remains challenging because the tensors change dramatically in the decussation of the SCPs (dSCP), the region where the SCPs cross. This paper presents an automatic method for segmenting the cerebellar peduncles, including the dSCP. The method uses volumetric segmentation concepts based on extracted DTI features. The dSCP and noncrossing portions of the peduncles are modeled as separate objects, and are initially classified using a random forest classifier together with the DTI features. To obtain geometrically correct results, a multi-object geometric deformable model is used to refine the random forest classification. The method was evaluated using a leave-one-out cross-validation on five control subjects and four patients with spinocerebellar ataxia type 6 (SCA6). It was then used to evaluate group differences in the peduncles in a population of 32 controls and 11 SCA6 patients. In the SCA6 group, we have observed significant decreases in the volumes of the dSCP and the ICPs and significant increases in the mean diffusivity in the noncrossing SCPs, the MCP, and the ICPs. These results are consistent with a degeneration of the cerebellar peduncles in SCA6 patients.

The cerebellum and psychiatric disorders

The cerebellum has been considered for a long time to play a role solely in motor coordination. However, studies over the past two decades have shown that the cerebellum also plays a key role in many motor, cognitive, and emotional processes. In addition, studies have also shown that the cerebellum is implicated in many psychiatric disorders including attention deficit hyperactivity disorder, autism spectrum disorders, schizophrenia, bipolar disorder, major depressive disorder, and anxiety disorders. In this review, we discuss existing studies reporting cerebellar dysfunction in various psychiatric disorders. We will also discuss future directions for studies linking the cerebellum to psychiatric disorders.

Connectivity in Autism: A Review of MRI Connectivity Studies

Autism spectrum disorder (ASD) affects 1 in 50 children between the ages of 6 and 17 years. The etiology of ASD is not precisely known. ASD is an umbrella term, which includes both low- (IQ < 70) and high-functioning (IQ > 70) individuals. A better understanding of the disorder and how it manifests in individual subjects can lead to more effective intervention plans to fulfill the individual's treatment needs.Magnetic resonance imaging (MRI) is a non-invasive investigational tool that can be used to study the ways in which the brain develops or deviates from the typical developmental trajectory. MRI offers insights into the structure, function, and metabolism of the brain. In this article, we review published studies on brain connectivity changes in ASD using either resting state functional MRI or diffusion tensor imaging.The general findings of decreases in white matter integrity and in long-range neural coherence are well known in the ASD literature. Nevertheless, the detailed localization of these findings remains uncertain, and few studies link these changes in connectivity with the behavioral phenotype of the disorder. With the help of data sharing and large-scale analytic efforts, however, the field is advancing toward several convergent themes, including the reduced functional coherence of long-range intra-hemispheric cortico-cortical default mode circuitry, impaired inter-hemispheric regulation, and an associated, perhaps compensatory, increase in local and short-range cortico-subcortical coherence.

Cerebro-cerebellar circuits in autism spectrum disorder

The cerebellum is one of the most consistent sites of abnormality in autism spectrum disorder (ASD) and cerebellar damage is associated with an increased risk of ASD symptoms, suggesting that cerebellar dysfunction may play a crucial role in the etiology of ASD. The cerebellum forms multiple closed-loop circuits with cerebral cortical regions that underpin movement, language, and social processing. Through these circuits, cerebellar dysfunction could impact the core ASD symptoms of social and communication deficits and repetitive and stereotyped behaviors. The emerging topography of sensorimotor, cognitive, and affective subregions in the cerebellum provides a new framework for interpreting the significance of regional cerebellar findings in ASD and their relationship to broader cerebro-cerebellar circuits. Further, recent research supports the idea that the integrity of cerebro-cerebellar loops might be important for early cortical development; disruptions in specific cerebro-cerebellar loops in ASD might impede the specialization of cortical regions involved in motor control, language, and social interaction, leading to impairments in these domains. Consistent with this concept, structural, and functional differences in sensorimotor regions of the cerebellum and sensorimotor cerebro-cerebellar circuits are associated with deficits in motor control and increased repetitive and stereotyped behaviors in ASD. Further, communication and social impairments are associated with atypical activation and structure in cerebro-cerebellar loops underpinning language and social cognition. Finally, there is converging evidence from structural, functional, and connectivity neuroimaging studies that cerebellar right Crus I/II abnormalities are related to more severe ASD impairments in all domains. We propose that cerebellar abnormalities may disrupt optimization of both structure and function in specific cerebro-cerebellar circuits in ASD.

Altered white matter connectivity as a neural substrate for social impairment in Autism Spectrum Disorder

BACKGROUND

Autism Spectrum Disorder (ASD) symptoms have been hypothesized to result from altered brain connectivity. The 'disconnectivity' hypothesis has been used to explain characteristic impairments in socio-emotional function, observed clinically in ASD. Here, we review the evidence for impaired white matter connectivity as a neural substrate for socio-emotional dysfunction in ASD. A review of diffusion tensor imaging (DTI) studies, and focused discussion of relevant post-mortem, structural, and functional neuroimaging studies, is provided.

METHODS

Studies were identified using a sensitive search strategy in MEDLINE, Embase and PsycINFO article databases using the OvidSP database interface. Search terms included database subject headings for the concepts of pervasive developmental disorders, and DTI. Seventy-two published DTI studies examining white matter microstructure in ASD were reviewed. A comprehensive discussion of DTI studies that examined white matter tracts linking socio-emotional structures is presented.

RESULTS

Several DTI studies reported microstructural differences indicative of developmental alterations in white matter organization, and potentially myelination, in ASD. Altered structure within long-range white matter tracts linking socio-emotional processing regions was implicated. While alterations of the uncinate fasciculus and frontal and temporal thalamic projections have been associated with social symptoms in ASD, few studies examined association of tract microstructure with core impairment in this disorder.

CONCLUSIONS

The uncinate fasciculus and frontal and temporal thalamic projections mediate limbic connectivity and integrate structures responsible for complex socio-emotional functioning. Impaired development of limbic connectivity may represent one neural substrate contributing to ASD social impairments. Future efforts to further elucidate the nature of atypical white matter development, and its relationship to core symptoms, may offer new insights into etiological mechanisms contributing to ASD impairments and uncover novel opportunities for targeted intervention.

Left-hemispheric microstructural abnormalities in children with high-functioning autism spectrum disorder

Current theories of the neurobiological basis of autism spectrum disorder (ASD) posit an altered pattern of connectivity in large-scale brain networks. Here we used diffusion tensor imaging to investigate the microstructural properties of the white matter (WM) that mediates interregional connectivity in 36 high-functioning children with ASD (HF-ASD) as compared with 37 controls. By employing an atlas-based analysis using large deformation diffeometric morphic mapping registration, a widespread but left-lateralized pattern of abnormalities was revealed. The mean diffusivity (MD) of water in the WM of HF-ASD children was significantly elevated throughout the left hemisphere, particularly in the outer-zone cortical WM. Across diagnostic groups, there was a significant effect of age on left-hemisphere MD, with a similar reduction in MD during childhood in both typically developing and HF-ASD children. The increased MD in children with HF-ASD suggests hypomyelination and may reflect increased short-range cortico-cortical connections subsequent to early WM overgrowth. These findings also highlight left-hemispheric connectivity as relevant to the pathophysiology of ASD and indicate that the spatial distribution of microstructural abnormalities in HF-ASD is widespread and left-lateralized. This altered left-hemispheric connectivity may contribute to deficits in communication and praxis observed in ASD.

The therapeutic potential of the cerebellum in schizophrenia

The cognitive role of the cerebellum is critically tied to its distributed connections throughout the brain. Accumulating evidence from anatomical, structural and functional imaging, and lesion studies advocate a cognitive network involving indirect connections between the cerebellum and non-motor areas in the prefrontal cortex. Cerebellar stimulation dynamically influences activity in several regions of the frontal cortex and effectively improves cognition in schizophrenia. In this manuscript, we summarize current literature on the cingulocerebellar circuit and we introduce a method to interrogate this circuit combining opotogenetics, neuropharmacology, and electrophysiology in awake-behaving animals while minimizing incidental stimulation of neighboring cerebellar nuclei. We propose the novel hypothesis that optogenetic cerebellar stimulation can restore aberrant frontal activity and rescue impaired cognition in schizophrenia. We focus on how a known cognitive region in the frontal cortex, the anterior cingulate, is influenced by the cerebellum. This circuit is of particular interest because it has been confirmed using tracing studies, neuroimaging reveals its role in cognitive tasks, it is conserved from rodents to humans, and diseases such as schizophrenia and autism appear in its aberrancy. Novel tract tracing results presented here provide support for how these two areas communicate. The primary pathway involves a disynaptic connection between the cerebellar dentate nuclei (DN) and the anterior cingulate cortex. Secondarily, the pathway from cerebellar fastigial nuclei (FN) to the ventral tegmental area, which supplies dopamine to the prefrontal cortex, may play a role as schizophrenia characteristically involves dopamine deficiencies. We hope that the hypothesis described here will inspire new therapeutic strategies targeting currently untreatable cognitive impairments in schizophrenia.

Multiparametric MRI characterization and prediction in autism spectrum disorder using graph theory and machine learning

This study employed graph theory and machine learning analysis of multiparametric MRI data to improve characterization and prediction in autism spectrum disorders (ASD). Data from 127 children with ASD (13.5±6.0 years) and 153 age- and gender-matched typically developing children (14.5±5.7 years) were selected from the multi-center Functional Connectome Project. Regional gray matter volume and cortical thickness increased, whereas white matter volume decreased in ASD compared to controls. Small-world network analysis of quantitative MRI data demonstrated decreased global efficiency based on gray matter cortical thickness but not with functional connectivity MRI (fcMRI) or volumetry. An integrative model of 22 quantitative imaging features was used for classification and prediction of phenotypic features that included the autism diagnostic observation schedule, the revised autism diagnostic interview, and intelligence quotient scores. Among the 22 imaging features, four (caudate volume, caudate-cortical functional connectivity and inferior frontal gyrus functional connectivity) were found to be highly informative, markedly improving classification and prediction accuracy when compared with the single imaging features. This approach could potentially serve as a biomarker in prognosis, diagnosis, and monitoring disease progression.