Altered functional connectivity of the language network in ASD: role of classical language areas and cerebellum

Intrinsic Functional Connectivity of Dentate Nuclei in Autism Spectrum Disorder

Cerebellar abnormalities are commonly reported in autism spectrum disorder (ASD). Dentate nuclei (DNs) are key structures in the anatomical circuits linking the cerebellum to the extracerebellum. Previous resting-state functional connectivity (RsFc) analyses reported DN abnormalities in high-functioning ASD (HF-ASD). This study examined the RsFc of the DN in young adults with HF-ASD compared with healthy controls (HCs) with the aim to expand upon previous findings of DNs in a dataset using advanced, imaging acquisition methods that optimize spatiotemporal resolution and statistical power. Additional seed-to-voxel analyses were carried out using motor and nonmotor DN coordinates reported in previous studies as seeds. We report abnormal dentato-cerebral and dentato-cerebellar functional connectivity in ASD. Our results expand and, in part, replicate previous descriptions of DN RsFc abnormalities in this disorder and reveal correlations between DN-cerebral RsFc and ASD symptom severity.

Cerebellar Modulation of Mesolimbic Dopamine Transmission Is Functionally Asymmetrical

Cerebral and cerebellar hemispheres are known to be asymmetrical in structure and function, and previous literature supports that asymmetry extends to the neural dopamine systems. Using in vivo fixed potential amperometry with carbon fiber microelectrodes in anesthetized mice, the current study assessed hemispheric lateralization of stimulation-evoked dopamine in the nucleus accumbens (NAc) and the influence of the cerebellum in regulating this reward-associated pathway. Our results suggest that cerebellar output can modulate mesolimbic dopamine transmission, and this modulation contributes to asymmetrically lateralized dopamine release. Dopamine release did not differ between hemispheres when evoked by medial forebrain bundle (MFB) stimulation; however, dopamine release was significantly greater in the right NAc relative to the left when evoked by electrical stimulation of the cerebellar dentate nucleus (DN). Furthermore, cross-hemispheric talk between the left and right cerebellar DN does not seem to influence mesolimbic release given that lidocaine infused into the DN opposite to the stimulated DN did not alter release. These studies may provide a neurochemical mechanism for studies identifying the cerebellum as a relevant node for reward, motivational behavior, saliency, and inhibitory control. An increased understanding of the lateralization of dopaminergic systems may reveal novel targets for pharmacological interventions in neuropathology of the cerebellum and extending projections.

Emerging connections between cerebellar development, behaviour and complex brain disorders

The human cerebellum has a protracted developmental timeline compared with the neocortex, expanding the window of vulnerability to neurological disorders. As the cerebellum is critical for motor behaviour, it is not surprising that most neurodevelopmental disorders share motor deficits as a common sequela. However, evidence gathered since the late 1980s suggests that the cerebellum is involved in motor and non-motor function, including cognition and emotion. More recently, evidence indicates that major neurodevelopmental disorders such as intellectual disability, autism spectrum disorder, attention-deficit hyperactivity disorder and Down syndrome have potential links to abnormal cerebellar development. Out of recent findings from clinical and preclinical studies, the concept of the 'cerebellar connectome' has emerged that can be used as a framework to link the role of cerebellar development to human behaviour, disease states and the design of better therapeutic strategies.

Cerebellar neural markers of susceptibility to social isolation and positive affective processing

Chronic loneliness predicts mood disturbances and onset of major depressive disorder. However, little research has examined the neural correlates of individual difference in susceptibility to perceiving loneliness. In addition, the role of cerebellum, which is heavily implicated in social, cognitive and affective processes, in loneliness is unclear. We studied 99 healthy individuals divided into susceptible, concordant and robust groups depending on whether the participant’s loneliness level was greater, comparable or less than her/his objective social isolation level. The cerebellar gray matter structure, functional activity and connectivity patterns during performing an emotion stroop task were examined. We found greater posterior and medial cerebellar volume in the susceptible group than the other groups. In addition, the posterior and medial cerebellar activities when processing positive versus neutral words exhibited significant interactive effects of both loneliness and social network, and susceptibility to isolation. Loneliness and social network also had positive effects on the right posterior cerebellar functional connectivity with the visual and premotor cortices. Our findings provide novel evidence on the intricate role of the cerebellum in loneliness and susceptibility to isolation, suggesting that socio-cognitive processes of the cerebellum in the hedonic domain may be a key mechanism underlying loneliness proneness.

Do the Dento-Thalamic Connections of Genetic Absence Epilepsy Rats from Strasbourg Differ from Those of Control Wistar Rats?

The thalamo-cortical circuit is important in the genesis of absence epilepsy. This circuit can be influenced by connecting pathways from various parts of central nervous system. The aim of the present study is to define the dento-thalamic connections in Wistar animals and compare the results with genetic absence epilepsy rats from Strasbourg (GAERS) using the biotinylated dextran amine (BDA) tracer. We injected BDA into the dentate nucleus of 13 (n = 6 Wistar and n = 7 GAERS) animals. The dento-thalamic connections in the Wistar animals were denser and were connected to a wider range of thalamic nuclei compared with GAERS. The dentate nucleus was bilaterally connected to the central (central medial [CM], paracentral [PC]), ventral (ventral medial [VM], ventral lateral [VL], and ventral posterior lateral [VPL]), and posterior (Po) thalamic nuclei in Wistar animals. The majority of these connections were dense contralaterally and scarce ipsilaterally. Contralateral connections were present with the parafascicular (PF), ventral posterior medial, ventral anterior (VA), and central lateral (CL) thalamic nuclei in Wistar animals. Whereas in GAERS, bilateral connections were observed with the VL and CM. Contralateral connections were present with the PC, VM, VA, and PF thalamic nuclei in GAERS. The CL, VPL, and Po thalamic nucleus connections were not observed in GAERS. The present study showed weak/deficit dento-thalamic connections in GAERS compared with control Wistar animals. The scarce information flow from the dentate nucleus to thalamus in GAERS may have a deficient modulatory role on the thalamus and thus may affect modulation of the thalamo-cortical circuit.

The language network in autism: Atypical functional connectivity with default mode and visual regions

Autism spectrum disorders (ASDs) are neurodevelopmental disorders associated with atypical brain connectivity. Although language abilities vary widely, they are impaired or atypical in most children with ASDs. Underlying brain mechanisms, however, are not fully understood. The present study examined intrinsic functional connectivity (iFC) of the extended language network in a cohort of 52 children and adolescents with ASDs (ages 8-18 years), using resting-state functional magnetic resonance imaging. We found that, in comparison to typically developing peers (n = 50), children with ASDs showed increased connectivity between some language regions. In addition, seed-to-whole brain analyses revealed increased connectivity of language regions with posterior cingulate cortex (PCC) and visual regions in the ASD group. Post hoc effective connectivity analyses revealed a mediation effect of PCC on the iFC between bilateral inferior frontal and visual regions in an ASD subgroup. This finding qualifies and expands on previous reports of recruitment of visual areas in language processing in ASDs. In addition, increased iFC between PCC and visual regions was linked to lower language scores in this ASD subgroup, suggesting that increased connectivity with visual cortices, mediated by default mode regions, may be detrimental to language abilities. Autism Res 2019, 12: 1344-1355. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: We examined the functional connectivity between regions of the language network in children with autism spectrum disorders (ASDs) compared to typically developing peers. We found connectivity to be intact between core language in the ASD group, but also showed abnormally increased connectivity between regions of an extended language network. Additionally, connectivity was increased with regions associated with brain networks responsible for self-reflection and visual processing.

Resting-State fMRI Networks in Children with Tuberous Sclerosis Complex

BACKGROUND AND PURPOSE

There are no published studies examining resting state networks (RSNs) and their relationship with neurodevelopmental metrics in tuberous sclerosis complex (TSC). We aimed to identify major resting-state functional magnetic resonance imaging (rs-fMRI) networks in infants with TSC and correlate network analyses with neurodevelopmental assessments, autism diagnosis, and seizure history.

METHODS

Rs-fMRI data from 34 infants with TSC, sedated with propofol during the scan, were analyzed to identify auditory, motor, and visual RSNs. We examined the correlations between auditory, motor, and visual RSNs at approximately 11.5 months, neurodevelopmental outcome at approximately 18.5 months, and diagnosis of autism spectrum disorders at approximately 36 months of age.

RESULTS

RSNs were obtained in 76.5% (26/34) of infants. We observed significant negative correlations between auditory RSN and auditory comprehension test scores (p = .038; r = -.435), as well as significant positive correlations between motor RSN and gross motor skills test scores (p = .023; r = .564). Significant positive correlations between motor RSNs and gross motor skills (p = .012; r = .754) were observed in TSC infants without autism, but not in TSC infants with autism, which could suggest altered motor processing. There were no significant differences in RSNs according to seizure history.

CONCLUSIONS

Negative correlation between auditory RSN, as well as positive correlation between motor RSN and developmental outcome measures might reflect different brain mechanisms and, when identified, may be helpful in predicting later function. A larger study of TSC patients with a healthy control group is needed before auditory and motor RSNs could be considered as neurodevelopmental outcome biomarkers.

Purkinje cell number-correlated cerebrocerebellar circuit anomaly in the valproate model of autism

While cerebellar alterations may play a crucial role in the development of core autism spectrum disorder (ASD) symptoms, their pathophysiology on the function of cerebrocerebellar circuit loops is largely unknown. We combined multimodal MRI (9.4 T) brain assessment of the prenatal rat valproate (VPA) model and correlated immunohistological analysis of the cerebellar Purkinje cell number to address this question. We hypothesized that a suitable functional MRI (fMRI) paradigm might show some altered activity related to disrupted cerebrocerebellar information processing. Two doses of maternal VPA (400 and 600 mg/kg, s.c.) were used. The higher VPA dose induced 3% smaller whole brain volume, the lower dose induced 2% smaller whole brain volume and additionally a focal gray matter density decrease in the cerebellum and brainstem. Increased cortical BOLD responses to whisker stimulation were detected in both VPA groups, but it was more pronounced and extended to cerebellar regions in the 400 mg/kg VPA group. Immunohistological analysis revealed a decreased number of Purkinje cells in both VPA groups. In a detailed analysis, we revealed that the Purkinje cell number interacts with the cerebral BOLD response distinctively in the two VPA groups that highlights atypical function of the cerebrocerebellar circuit loops with potential translational value as an ASD biomarker.

A Working Hypothesis for the Role of the Cerebellum in Impulsivity and Compulsivity

Growing evidence associates cerebellar abnormalities with several neuropsychiatric disorders in which compulsive symptomatology and impulsivity are part of the disease pattern. Symptomatology of autism, addiction, obsessive-compulsive (OCD), and attention deficit/hyperactivity (ADHD) disorders transcends the sphere of motor dysfunction and essentially entails integrative processes under control of prefrontal-thalamic-cerebellar loops. Patients with brain lesions affecting the cortico-striatum thalamic circuitry and the cerebellum indeed exhibit compulsive symptoms. Specifically, lesions of the posterior cerebellar vermis cause affective dysregulation and deficits in executive function. These deficits may be due to impairment of one of the main functions of the cerebellum, implementation of forward internal models of the environment. Actions that are independent of internal models may not be guided by predictive relationships or a mental representation of the goal. In this review article, we explain how this deficit might affect executive functions. Additionally, regionalized cerebellar lesions have been demonstrated to impair other brain functions such as the emergence of habits and behavioral inhibition, which are also altered in compulsive disorders. Similar to the infralimbic cortex, clinical studies and research in animal models suggest that the cerebellum is not required for learning goal-directed behaviors, but it is critical for habit formation. Despite this accumulating data, the role of the cerebellum in compulsive symptomatology and impulsivity is still a matter of discussion. Overall, findings point to a modulatory function of the cerebellum in terminating or initiating actions through regulation of the prefrontal cortices. Specifically, the cerebellum may be crucial for restraining ongoing actions when environmental conditions change by adjusting prefrontal activity in response to the new external and internal stimuli, thereby promoting flexible behavioral control. We elaborate on this explanatory framework and propose a working hypothesis for the involvement of the cerebellum in compulsive and impulsive endophenotypes.

Exploring quantitative group-wise differentiation of Alzheimer's disease and behavioural variant frontotemporal dementia using tract-specific microstructural white matter and functional connectivity measures at multiple time points

Objectives

This study explored group-wise quantitative measures of tract-specific white matter (WM) microstructure and functional default mode network (DMN) connectivity to establish an initial indication of their clinical applicability for early-stage and follow-up differential diagnosis of Alzheimer’s disease (AD) and behavioural variant frontotemporal dementia (bvFTD).

Methods

Eleven AD and 12 bvFTD early-stage patients and 18 controls underwent diffusion tensor imaging and resting state functional magnetic resonance imaging at 3 T. All AD and 6 bvFTD patients underwent the same protocol at 1-year follow-up. Functional connectivity measures of DMN and WM tract-specific diffusivity measures were determined for all groups. Exploratory analyses were performed to compare all measures between the three groups at baseline and between patients at follow-up. Additionally, the difference between baseline and follow-up diffusivity measures in AD and bvFTD patients was compared.

Results

Functional connectivity of the DMN was not different between groups at baseline and at follow-up. Diffusion abnormalities were observed widely in bvFTD and regionally in the hippocampal cingulum in AD. The extent of the differences between bvFTD and AD was diminished at follow-up, yet abnormalities were still more pronounced in bvFTD. The rate of change was similar in bvFTD and AD.

Conclusions

This study provides a tentative indication that quantitative tract-specific microstructural WM abnormalities, but not quantitative functional connectivity of the DMN, may aid early-stage and follow-up differential diagnosis of bvFTD and AD. Specifically, pronounced microstructural changes in anterior WM tracts may characterise bvFTD, whereas microstructural abnormalities of the hippocampal cingulum may characterise AD.

Key Points

• The clinical applicability of quantitative brain imaging measures for early-stage and follow-up differential diagnosis of dementia subtypes was explored using a group-wise approach.

• Quantitative tract-specific microstructural white matter abnormalities, but not quantitative functional connectivity of the default mode network, may aid early-stage and follow-up differential diagnosis of behavioural variant frontotemporal dementia and Alzheimer’s disease.

• Pronounced microstructural white matter (WM) changes in anterior WM tracts characterise behavioural variant frontotemporal dementia, whereas microstructural WM abnormalities of the hippocampal cingulum in the absence of other WM changes characterise Alzheimer’s disease.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06061-7) contains supplementary material, which is available to authorized users.

Comparing directed functional connectivity between groups with confirmatory subgrouping GIMME

Connectivity modeling in functional neuroimaging has become widely used method of analysis for understanding functional architecture. One method for deriving directed connectivity models is Group Iterative Multiple Model Estimation (GIMME; Gates and Molenaar, 2012). GIMME looks for commonalities across the sample to detect signal from noise and arrive at edges that exist across the majority in the group ("group-level edges") and individual-level edges. In this way, GIMME obtains generalizable results via the group-level edges while also allowing for between subject heterogeneity in connectivity, moving the field closer to obtaining reliable personalized connectivity maps. In this article, we present a novel extension of GIMME, confirmatory subgrouping GIMME, which estimates subgroup-level edges for a priori known groups (e.g. typically developing controls vs. clinical group). Detecting edges that consistently exist for individuals within predefined subgroups aids in interpretation of the heterogeneity in connectivity maps and allows for subgroup-specific inferences. We describe this algorithm, as well as several methods to examine the results. We present an empirical example that finds similarities and differences in resting state functional connectivity among four groups of children: typically developing controls (TDC), children with autism spectrum disorder (ASD), children with Inattentive (ADHD-I) and Combined (ADHD-C) Type ADHD. Findings from this study suggest common involvement of the left Broca's area in all the clinical groups, as well as several unique patterns of functional connectivity specific to a given disorder. Overall, the current approach and proof of principle findings highlight a novel and reliable tool for capturing heterogeneity in complex mental health disorders.

Overt social interaction and resting state in young adult males with autism: core and contextual neural features

Conversation is an important and ubiquitous social behaviour. Individuals with autism spectrum disorder (autism) without intellectual disability often have normal structural language abilities but deficits in social aspects of communication like pragmatics, prosody, and eye contact. Previous studies of resting state activity suggest that intrinsic connections among neural circuits involved with social processing are disrupted in autism, but to date no neuroimaging study has examined neural activity during the most commonplace yet challenging social task: spontaneous conversation. Here we used functional MRI to scan autistic males (n = 19) without intellectual disability and age- and IQ-matched typically developing control subjects (n = 20) while they engaged in a total of 193 face-to-face interactions. Participants completed two kinds of tasks: conversation, which had high social demand, and repetition, which had low social demand. Autistic individuals showed abnormally increased task-driven interregional temporal correlation relative to controls, especially among social processing regions and during high social demand. Furthermore, these increased correlations were associated with parent ratings of participants' social impairments. These results were then compared with previously-acquired resting state data (56 autism, 62 control subjects). While some interregional correlation levels varied by task or rest context, others were strikingly similar across both task and rest, namely increased correlation among the thalamus, dorsal and ventral striatum, somatomotor, temporal and prefrontal cortex in the autistic individuals, relative to the control groups. These results suggest a basic distinction. Autistic cortico-cortical interactions vary by context, tending to increase relative to controls during task and decrease during test. In contrast, striato- and thalamocortical relationships with socially engaged brain regions are increased in both task and rest, and may be core to the condition of autism.

Characterization of Autism Spectrum Disorder across the Age Span by Intrinsic Network Patterns

Autism spectrum disorder (ASD) is characterized by abnormal functional organization of brain networks, which may underlie the cognitive and social impairments observed in affected individuals. The present study characterizes unique intrinsic connectivity within- and between- neural networks in children through to adults with ASD, relative to controls. Resting state fMRI data were analyzed in 204 subjects, 102 with ASD and 102 age- and sex-matched controls (ages 7-40 years), acquired on a single scanner. ASD was assessed using the autism diagnostic observation schedule (ADOS). BOLD correlations were calculated between 47 regions of interest, spanning seven resting state brain networks. Partial least squares (PLS) analyses evaluated the association between connectivity patterns and ASD diagnosis as well as ASD severity scores. PLS demonstrated dissociable connectivity patterns in those with ASD, relative to controls. Similar patterns were observed in the whole cohort and in a subgroup analysis of subjects under 18 years of age. Greater inter-network connectivity was seen in ASD with greater intra-network connectivity in controls. In conclusion, stronger inter-network and weaker intra-network resting state-fMRI BOLD correlations characterize ASD and may differentiate control and ASD cohorts. These findings are relevant to understanding ASD as a disruption of network topology.

Abnormal Cortico-Cerebellar Functional Connectivity in Autism Spectrum Disorder

The cerebral cortex and the cerebellum are spatially remote areas that are connected by complex circuits that link both primary and associative areas. Previous studies have revealed abnormalities in autism spectrum disorder (ASD); however, it is not clear whether cortico-cerebellar connectivity is differentially manifested in the disorder. To explore this issue, we investigated differences in intrinsic cortico-cerebellar functional connectivity between individuals with typical development (TD) and those with ASD. To this end, we used functional magnetic resonance imaging (fMRI) of 708 subjects under a resting state protocol provided by the ABIDE I Consortium. We found that people with ASD had diminished functional connectivity between the cerebellum and the following cortical regions: (i) right fusiform gyrus, (ii) right postcentral gyrus, (iii) right superior temporal gyrus, (iv) right middle temporal gyrus, and (v) left middle temporal gyrus. All of these regions are involved in many cognitive systems that contribute to commonly affected functions in ASD. For right fusiform gyrus, right superior temporal gyrus, and left middle temporal gyrus, we reproduced the results in an independent cohort composed of 585 subjects of the ABIDE II Consortium. Our results points toward a consistent atypical cortico-cerebellar connectivity in ASD.

Evaluation of Altered Functional Connections in Male Children With Autism Spectrum Disorders on Multiple-Site Data Optimized With Machine Learning

No univocal and reliable brain-based biomarkers have been detected to date in Autism Spectrum Disorders (ASD). Neuroimaging studies have consistently revealed alterations in brain structure and function of individuals with ASD; however, it remains difficult to ascertain the extent and localization of affected brain networks. In this context, the application of Machine Learning (ML) classification methods to neuroimaging data has the potential to contribute to a better distinction between subjects with ASD and typical development controls (TD). This study is focused on the analysis of resting-state fMRI data of individuals with ASD and matched TD, available within the ABIDE collection. To reduce the multiple sources of heterogeneity that impact on understanding the neural underpinnings of autistic condition, we selected a subgroup of 190 subjects (102 with ASD and 88 TD) according to the following criteria: male children (age range: 6.5-13 years); rs-fMRI data acquired with open eyes; data from the University sites that provided the largest number of scans (KKI, NYU, UCLA, UM). Connectivity values were evaluated as the linear correlation between pairs of time series of brain areas; then, a Linear kernel Support Vector Machine (L-SVM) classification, with an inter-site cross-validation scheme, was carried out. A permutation test was conducted to identify over-connectivity and under-connectivity alterations in the ASD group. The mean L-SVM classification performance, in terms of the area under the ROC curve (AUC), was 0.75 ± 0.05. The highest performance was obtained using data from KKI, NYU and UCLA sites in training and data from UM as testing set (AUC = 0.83). Specifically, stronger functional connectivity (FC) in ASD with respect to TD involve (p < 0.001) the angular gyrus with the precuneus in the right (R) hemisphere, and the R frontal operculum cortex with the pars opercularis of the left (L) inferior frontal gyrus. Weaker connections in ASD group with respect to TD are the intra-hemispheric R temporal fusiform cortex with the R hippocampus, and the L supramarginal gyrus with L planum polare. The results indicate that both under- and over-FC occurred in a selected cohort of ASD children relative to TD controls, and that these functional alterations are spread in different brain networks.

Investigating the Correspondence of Clinical Diagnostic Grouping With Underlying Neurobiological and Phenotypic Clusters Using Unsupervised Machine Learning

Many brain-based disorders are traditionally diagnosed based on clinical interviews and behavioral assessments, which are recognized to be largely imperfect. Therefore, it is necessary to establish neuroimaging-based biomarkers to improve diagnostic precision. Resting-state functional magnetic resonance imaging (rs-fMRI) is a promising technique for the characterization and classification of varying disorders. However, most of these classification methods are supervised, i.e., they require a priori clinical labels to guide classification. In this study, we adopted various unsupervised clustering methods using static and dynamic rs-fMRI connectivity measures to investigate whether the clinical diagnostic grouping of different disorders is grounded in underlying neurobiological and phenotypic clusters. In order to do so, we derived a general analysis pipeline for identifying different brain-based disorders using genetic algorithm-based feature selection, and unsupervised clustering methods on four different datasets; three of them-ADNI, ADHD-200, and ABIDE-which are publicly available, and a fourth one-PTSD and PCS-which was acquired in-house. Using these datasets, the effectiveness of the proposed pipeline was verified on different disorders: Attention Deficit Hyperactivity Disorder (ADHD), Alzheimer's Disease (AD), Autism Spectrum Disorder (ASD), Post-Traumatic Stress Disorder (PTSD), and Post-Concussion Syndrome (PCS). For ADHD and AD, highest similarity was achieved between connectivity and phenotypic clusters, whereas for ASD and PTSD/PCS, highest similarity was achieved between connectivity and clinical diagnostic clusters. For multi-site data (ABIDE and ADHD-200), we report site-specific results. We also reported the effect of elimination of outlier subjects for all four datasets. Overall, our results suggest that neurobiological and phenotypic biomarkers could potentially be used as an aid by the clinician, in additional to currently available clinical diagnostic standards, to improve diagnostic precision. Data and source code used in this work is publicly available at https://github.com/xinyuzhao/identification-of-brain-based-disorders.git.

Growing a social brain

It has long been assumed that social animals, such as humans, are born with a brain system that has evolved to support social affiliation. However, the evidence does not necessarily support this assumption. Alternatively, social animals can be defined as those who cannot survive alone and rely on members from their group to regulate their ongoing physiology (or allostasis). The rather simple evolutionary constraint of social dependency for survival can be sufficient to make the social environment vitally salient, and to provide the ultimate driving force for socially crafted brain development and learning. In this Perspective, we propose a framework for sociality and specify a set of hypotheses on the mechanisms of social development and underlying neural systems. The theoretical shift proposed here implies that profound human characteristics, including but not limited to sociality, are acquired at an early age, while social interactions provide key wiring instructions that determine brain development.

Disrupted Cerebrocerebellar Intrinsic Functional Connectivity in Young Adults with High-Functioning Autism Spectrum Disorder: A Data-Driven, Whole-Brain, High-Temporal Resolution Functional Magnetic Resonance Imaging Study

This study examines the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. High temporal resolution fMRI using simultaneous multi-slice acquisition aided unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc. MVPA revealed two clusters (Crus I/II and lobule IX) of abnormal connectivity in the cerebellum that are consistent with the notion of a triple representation of nonmotor processing in the cerebellum. Whole-brain seed-based RsFc analyses informed by these clusters showed significant under connectivity between the cerebellar and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in HF-ASD. The description of functional connectivity abnormalities reported in this study using whole-brain, data-driven analyses has the potential to crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

Reorganization of cerebro-cerebellar circuit in patients with left hemispheric gliomas involving language network: A combined structural and resting-state functional MRI study

The role of cerebellum and cerebro-cerebellar system in neural plasticity induced by cerebral gliomas involving language network has long been ignored. Moreover, whether or not the process of reorganization is different in glioma patients with different growth kinetics remains largely unknown. To address this issue, we utilized preoperative structural and resting-state functional MRI data of 78 patients with left cerebral gliomas involving language network areas, including 46 patients with low-grade glioma (LGG, WHO grade II), 32 with high-grade glioma (HGG, WHO grade III/IV), and 44 healthy controls. Spontaneous brain activity, resting-state functional connectivity and gray matter volume alterations of the cerebellum were examined. We found that both LGG and HGG patients exhibited bidirectional alteration of brain activity in language-related cerebellar areas. Brain activity in areas with increased alteration was significantly correlated with the language and MMSE scores. Structurally, LGG patients exhibited greater gray matter volume in regions with increased brain activity, suggesting a structure-function coupled alteration in cerebellum. Furthermore, we observed that cerebellar regions with decreased brain activity exhibited increased functional connectivity with contralesional cerebro-cerebellar system in LGG patients. Together, our findings provide empirical evidence for a vital role of cerebellum and cerebro-cerebellar circuit in neural plasticity following lesional damage to cerebral language network. Moreover, we highlight the possible different reorganizational mechanisms of brain functional connectivity underlying different levels of behavioral impairments in LGG and HGG patients.

Altered Resting-State Functional Activity in Patients With Autism Spectrum Disorder: A Quantitative Meta-Analysis

Background: There is accumulating evidence showing that patients with autism spectrum disorder (ASD) have obvious changes in resting-state functional brain activity. So far, there have been no meta-analyses of the resting-state brain activity alterations in patients with ASD. We attempted to explore the resting-state functional activity changes in patients with ASD, possibly providing a new perspective for investigating the pathophysiology of patients with ASD.

Methods: We screened relevant studies published before August 2017 in PubMed, Ovid, Web of Science, China National Knowledge Infrastructure (CNKI), and the Wan-fang database. Fifteen resting-state functional neural activity datasets (including 382 patients and 348 healthy controls) were included. Through the use of the effect-size signed differential mapping (ES-SDM) method, we carried out a meta-analysis of resting-state functional activity studies of patients with ASD.

Results: Compared with healthy controls, patients with ASD showed hyperactivity in the right supplementary motor area, middle frontal gyrus, inferior frontal gyrus, the left precentral gyrus, and the bilateral cerebellum hemispheric lobule (VIII/IX), and hypoactivity in the right middle temporal gyrus, superior temporal gyrus, and the left precuneus, posterior cingulate cortex, median cingulate cortex, and bilateral cerebellum (crus I).

Conclusion: This meta-analysis indicates that patients with ASD have significant and robust resting-state brain activity alterations in the language comprehension network, inferior-posterior cerebellum, default mode network (DMN), and cerebellar crus I. These brain regions may serve as specific regions of interest for further studies of ASD, which will allow us to further clarify the neurobiological mechanisms in patients with ASD.

fMRI connectivity of expressive language in young children and adolescents

Studies of language representation in development have shown a bilateral distributed pattern of activation that becomes increasingly left-lateralized and focal from young childhood to adulthood. However, the level by which canonical and extra-canonical regions, including subcortical and cerebellar regions, contribute to language during development has not been well-characterized. In this study, we employed fMRI connectivity analyses (fcMRI) to characterize the distributed network supporting expressive language in a group of young children (age 4-6) and adolescents (age 16-18). We conducted an fcMRI analysis using seed-to-voxel and seed-to-ROI (region of interest) strategies to investigate interactions of left pars triangularis with other brain areas. The analyses showed significant interhemispheric connectivity in young children, with a minimal connectivity of the left pars triangularis to subcortical and cerebellar regions. In contrast, adolescents showed significant connectivity between the left IFG seed and left perisylvian cortex, left caudate and putamen, and regions of the right cerebellum. Importantly, fcMRI analyses indicated significant differences between groups at 3 anatomical clusters, including left IFG, left supramarginal gyrus, and right cerebellar crura, suggesting a role in the functional development of language.

Circadian Clock Proteins and Melatonin Receptors in Neurons and Glia of the Sapajus apella Cerebellum

Oscillations of brain proteins in circadian rhythms are important for determining several cellular and physiological processes in anticipation of daily and seasonal environmental rhythms. In addition to the suprachiasmatic nucleus, the primary central oscillator, the cerebellum shows oscillations in gene and protein expression. The variety of local circuit rhythms that the cerebellar cortex contains influences functions such as motivational processes, regulation of feeding, food anticipation, language, and working memory. The molecular basis of the cerebellar oscillator has been demonstrated by "clock gene" expression within cells of the cerebellar layers. Genetic and epidemiological evidence suggests that disruption of circadian rhythms in humans can lead to many pathological conditions. Despite this importance, data about clock gene and protein expression in the cerebellum of diurnal (day-active) species, specifically primates, is currently poorly explored, mainly in regard to cellular identity, as well as the relationship with other molecules also involved in cerebellar functions. These studies could contribute to clarification of the possible mechanisms behind cerebellar rhythmicity. Considering that calcium binding proteins (CaBPs) play crucial roles in preserving and modulating cerebellar functions and that clock gene expression can be controlled by afferent projections or paracrine circadian signals such as the hormone melatonin, the present study aimed to describe cellular identities, distribution patterns and day/night expression changes in PER1, PER2, CaBPs, and MT₁ and MT₂ melatonin receptors in the cerebellar cortex of a diurnal primate using conventional fluorescence and peroxidase-antiperoxidase immunocytochemical techniques. PER1 and PER2 immunoreactive (IR) cells were observed in the Purkinje cells of the cerebellum, and MT₁ and MT₂ receptors were localized around Purkinje cells in the Pj layer in Bergmann cells. This identity was confirmed by the S100β-IR of these cells. The highest expression of PER seen in the daytime analysis coincided with the highest expression of melatonin receptors. CaBPs showed day/night morphological and density changes in the cerebellar cortex. The presence of the same temporal variations in the expression of PER in the Pj neurons and in MT₁ and MT₂ receptors in Bergmann cells indicates a possible relation between these cells during the rhythmic processing of the cerebellum, in addition to the CaBP temporal morphological and density changes.

Role of Language-Related Functional Connectivity in Patients with Benign Childhood Epilepsy with Centrotemporal Spikes

Background and Purpose

Benign childhood epilepsy with centrotemporal spikes (BECTS) does not always have a benign cognitive outcome. We investigated the relationship between cognitive performance and altered functional connectivity (FC) in the resting-state brain networks of BECTS patients.

Methods

We studied 42 subjects, comprising 19 BECTS patients and 23 healthy controls. Cognitive performance was assessed using the Korean version of the Wechsler Intelligence Scale for Children-III, in addition to verbal and visuospatial memory tests and executive function tests. Resting-state functional magnetic resonance imaging was acquired in addition to high-resolution structural data. We selected Rolandic and language-related areas as regions of interest (ROIs) and analyzed the seed-based FC to voxels throughout the brain. We evaluated the correlations between the neuropsychological test scores and seed-based FC values using the same ROIs.

Results

The verbal intelligence quotient (VIQ) and full-scale intelligence quotient (FSIQ) were lower in BECTS patients than in healthy controls (p<0.001). The prevalence of subjects with a higher performance IQ than VIQ was significantly higher in BECTS patients than in healthy controls (73.7% vs. 26.1%, respectively; p=0.002). Both the Rolandic and language-related ROIs exhibited more enhanced FC to voxels in the left inferior temporal gyrus in BECTS patients than in healthy controls. A particularly interestingly finding was that the enhanced FC was correlated with lower cognitive performance as measured by the VIQ and the FSIQ in both patients and control subjects.

Conclusions

Our findings suggest that the FC alterations in resting-state brain networks related to the seizure onset zone and language processing areas could be related to adaptive plasticity for coping with cognitive dysfunction.

Using Pattern Classification to Identify Brain Imaging Markers in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social interaction and communication, as well as repetitive and restrictive behaviours. The etiological and phenotypic complexity of ASD has so far hindered the development of clinically useful biomarkers for the condition. Neuroimaging studies have been valuable in establishing a biological basis for ASD. Increasingly, neuroimaging has been combined with 'machine learning'-based pattern classification methods to make individual diagnostic predictions. Moving forward, the hope is that these techniques may not only facilitate the diagnostic process but may also aid in fractionating the ASD phenotype into more biologically homogeneous sub-groups, with defined pathophysiology, predictable outcomes and/or responses to targeted treatments and/or interventions. This review chapter will first introduce 'machine learning' and pattern recognition methods in general, with a focus on their application to diagnostic classification. It will highlight why such approaches to biomarker discovery may have advantages over more conventional analytical methods. Magnetic resonance imaging (MRI) findings of atypical brain structure, function and connectivity in ASD will be briefly reviewed before we describe how pattern recognition has been applied to generate predictive models for ASD. Last, we will discuss some limitations and pitfalls of pattern recognition analyses in ASD and consider how the field can advance beyond the prediction of binary outcomes.

Neonatal and regressive forms of autism: Diseases with similar symptoms but a different etiology

Autistic Spectrum Disorder (ASD) can be a debilitating, life-long neurocognitive disease. ASD is caused by genetic and epigenetic factors and largely unknown and poorly understood environmental triggers. Signs and symptoms of ASD often appear in the first year of life while the disease strikes other infants who had previously been developing normally at around 2years of age. Ozonoff and her colleagues recently suggested that there are three different pathways or trajectories for the development of ASD in infants 6-24months of age. I hypothesize that pathway 1 is caused by in utero insult/injury, pathway 2 by obstetric complications at birth, and pathway 3 by environmental triggers of ASD affecting infants 0-3years of age. Faster progress can be made in elucidating the underlying causes of neonatal and regressive forms of ASD if the diseases are investigated separately, instead of being part of the same disorder.

Cerebellar Contributions to Language in Typical and Atypical Development: A Review

In this review, we present the growing literature suggesting, from a variety of angles, that the cerebellum contributes to higher-order cognitive functions, rather than simply sensorimotor functions, and more specifically to language and its development. The cerebellum's association with language function is determined by the specific cortico-cerebellar connectivity to the right cerebellum from the left cortical hemisphere. The findings we review suggest that the cerebellum plays an important role as part of a broader language network, and also implies that the cerebellum may be a potential new therapeutic target to treat speech and language deficits, especially during development.

Neuroimaging genetic analyses of novel candidate genes associated with reading and language

Neuroimaging measures provide useful endophenotypes for tracing genetic effects on reading and language. A recent Genome-Wide Association Scan Meta-Analysis (GWASMA) of reading and language skills (N=1862) identified strongest associations with the genes CCDC136/FLNC and RBFOX2. Here, we follow up the top findings from this GWASMA, through neuroimaging genetics in an independent sample of 1275 healthy adults. To minimize multiple-testing, we used a multivariate approach, focusing on cortical regions consistently implicated in prior literature on developmental dyslexia and language impairment. Specifically, we investigated grey matter surface area and thickness of five regions selected a priori: middle temporal gyrus (MTG); pars opercularis and pars triangularis in the inferior frontal gyrus (IFG-PO and IFG-PT); postcentral parietal gyrus (PPG) and superior temporal gyrus (STG). First, we analysed the top associated polymorphisms from the reading/language GWASMA: rs59197085 (CCDC136/FLNC) and rs5995177 (RBFOX2). There was significant multivariate association of rs5995177 with cortical thickness, driven by effects on left PPG, right MTG, right IFG (both PO and PT), and STG bilaterally. The minor allele, previously associated with reduced reading-language performance, showed negative effects on grey matter thickness. Next, we performed exploratory gene-wide analysis of CCDC136/FLNC and RBFOX2; no other associations surpassed significance thresholds. RBFOX2 encodes an important neuronal regulator of alternative splicing. Thus, the prior reported association of rs5995177 with reading/language performance could potentially be mediated by reduced thickness in associated cortical regions. In future, this hypothesis could be tested using sufficiently large samples containing both neuroimaging data and quantitative reading/language scores from the same individuals.

Multiple functional networks modeling for autism spectrum disorder diagnosis

Despite countless studies on autism spectrum disorder (ASD), diagnosis relies on specific behavioral criteria and neuroimaging biomarkers for the disorder are still relatively scarce and irrelevant for diagnostic workup. Many researchers have focused on functional networks of brain activities using resting-state functional magnetic resonance imaging (rsfMRI) to diagnose brain diseases, including ASD. Although some existing methods are able to reveal the abnormalities in functional networks, they are either highly dependent on prior assumptions for modeling these networks or do not focus on latent functional connectivities (FCs) by considering discriminative relations among FCs in a nonlinear way. In this article, we propose a novel framework to model multiple networks of rsfMRI with data-driven approaches. Specifically, we construct large-scale functional networks with hierarchical clustering and find discriminative connectivity patterns between ASD and normal controls (NC). We then learn features and classifiers for each cluster through discriminative restricted Boltzmann machines (DRBMs). In the testing phase, each DRBM determines whether a test sample is ASD or NC, based on which we make a final decision with a majority voting strategy. We assess the diagnostic performance of the proposed method using public datasets and describe the effectiveness of our method by comparing it to competing methods. We also rigorously analyze FCs learned by DRBMs on each cluster and discover dominant FCs that play a major role in discriminating between ASD and NC. Hum Brain Mapp 38:5804-5821, 2017. © 2017 Wiley Periodicals, Inc.

Autism Spectrum Disorder Related Functional Connectivity Changes in the Language Network in Children, Adolescents and Adults

Autism spectrum disorder (ASD) is a neurodevelopmental disability with global implication. Altered brain connectivity in the language network has frequently been reported in ASD patients using task-based functional magnetic resonance imaging (fMRI) compared to typically developing (TD) participants. Most of these studies have focused on a specific age group or mixed age groups with ASD. In the current study, we investigated age-related changes in functional connectivity related measure, degree centrality (DC), in the language network across three age groups with ASD (113 children, 113 adolescents and 103 adults) using resting-state fMRI data collected from the autism brain imaging data exchange repository. We identified regions with significant group-wise differences between ASD and TD groups for three age cohorts using DC based on graph theory. We found that both children and adolescents with ASD showed decreased DC in Broca's area compared to age-matched TD groups. Adults with ASD showed decreased DC in Wernicke's area compared to TD adults. We also observed increased DC in the left inferior parietal lobule (IPL) and left middle temporal gyrus (MTG) for children with ASD compared to TD children and for adults with ASD compared to TD adults, respectively. Overall, functional differences occurred in key language processing regions such as the left inferior frontal gyrus (IFG) and superior temporal gyrus (STG) related to language production and comprehension across three age cohorts. We explored correlations between DC values of our findings with autism diagnostic observation schedule (ADOS) scores related to severity of ASD symptoms in the ASD group. We found that DC values of the left IFG demonstrated negative correlations with ADOS scores in children and adolescents with ASD. The left STG showed significant negative correlations with ADOS scores in adults with ASD. These results might shed light on the language network regions that should be further explored for prognosis, diagnosis, and monitoring of ASD in three age groups.

Altered fractional amplitude of low frequency fluctuation in premenstrual syndrome: A resting state fMRI study

BACKGROUND

Premenstrual syndrome (PMS) is becoming highly prevalent among female and is characterized by emotional, physical and behavior symptoms. Previous evidence suggested functional dysregulation of female brain was expected to be involved in the etiology of PMS. The aim of present study was to evaluate the alterations of spontaneous brain activity in PMS patients based on functional magnetic resonance imaging (fMRI).

METHODS

20 PMS patients and 21 healthy controls underwent resting-state fMRI scanning during luteal phase. All participants were asked to complete a prospective daily record of severity of problems (DRSP) questionnaire.

RESULTS

Compared with healthy controls, the results showed that PMS patients had increased fALFF in bilateral precuneus, left hippocampus and left inferior temporal cortex, and decreased fALFF in bilateral anterior cingulate cortex (ACC) and cerebellum at luteal phase. Moreover, the DRSP scores of PMS patients were negatively correlated with the mean fALFF in ACC and positively correlated with the fALFF in precuneus.

LIMITATIONS

(1) the study did not investigate whether or not abnormal brain activity differences between groups in mid-follicular phase, and within-group changes. between phases.(2) it was relatively limited sample size and the participants were young; (3) fALFF could not provide us with more holistic information of brain network;(4) the comparisons of PMS and premenstrual dysphoric disorder (PMDD) were not involved in the study.

CONCLUSIONS

The present study shows abnormal spontaneous brain activity in PMS patients revealed by fALFF, which could provide neuroimaging evidence to further improve our understanding of the underlying neural mechanism of PMS.

Mapping Critical Language Sites in Children Performing Verb Generation: Whole-Brain Connectivity and Graph Theoretical Analysis in MEG

A classic left frontal-temporal brain network is known to support language processes. However, the level of participation of constituent regions, and the contribution of extra-canonical areas, is not fully understood; this is particularly true in children, and in individuals who have experienced early neurological insult. In the present work, we propose whole-brain connectivity and graph-theoretical analysis of magnetoencephalography (MEG) source estimates to provide robust maps of the pediatric expressive language network. We examined neuromagnetic data from a group of typically-developing young children (n = 15, ages 4–6 years) and adolescents (n = 14, 16–18 years) completing an auditory verb generation task in MEG. All source analyses were carried out using a linearly-constrained minimum-variance (LCMV) beamformer. Conventional differential analyses revealed significant (p < 0.05, corrected) low-beta (13–23 Hz) event related desynchrony (ERD) focused in the left inferior frontal region (Broca’s area) in both groups, consistent with previous studies. Connectivity analyses were carried out in broadband (3–30 Hz) on time-course estimates obtained at the voxel level. Patterns of connectivity were characterized by phase locking value (PLV), and network hubs identified through eigenvector centrality (EVC). Hub analysis revealed the importance of left perisylvian sites, i.e., Broca’s and Wernicke’s areas, across groups. The hemispheric distribution of frontal and temporal lobe EVC values was asymmetrical in most subjects; left dominant EVC was observed in 20% of young children, and 71% of adolescents. Interestingly, the adolescent group demonstrated increased critical sites in the right cerebellum, left inferior frontal gyrus (IFG) and left putamen. Here, we show that whole brain connectivity and network analysis can be used to map critical language sites in typical development; these methods may be useful for defining the margins of eloquent tissue in neurosurgical candidates.

Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review

Ongoing debate exists within the resting-state functional MRI (fMRI) literature over how intrinsic connectivity is altered in the autistic brain, with reports of general over-connectivity, under-connectivity, and/or a combination of both. Classifying autism using brain connectivity is complicated by the heterogeneous nature of the condition, allowing for the possibility of widely variable connectivity patterns among individuals with the disorder. Further differences in reported results may be attributable to the age and sex of participants included, designs of the resting-state scan, and to the analysis technique used to evaluate the data. This review systematically examines the resting-state fMRI autism literature to date and compares studies in an attempt to draw overall conclusions that are presently challenging. We also propose future direction for rs-fMRI use to categorize individuals with autism spectrum disorder, serve as a possible diagnostic tool, and best utilize data-sharing initiatives.

Cerebellar gray matter differentiates children with early language delay in autism

Early language delay (ELD) is one of the earliest indicators of autism spectrum disorder (ASD), and predicts later cognitive and behavioral outcomes. We aimed to determine the neural correlates of ELD in autism, and examine the relationships between gray matter (GM), age of first word/phrase, and core ASD symptoms. We used voxel-based morphometry to examine whole-brain differences in GM in 8-13 year old children with autism (n = 13 ELD; n = 22 non-ELD) and 35 age-matched typically developing (TD) children. Multiple regression analyses examined the relationships between GM, age of first word/phrase, and autism diagnostic observation schedule (ADOS) scores. Composite age of first word/phrase negatively correlated with GM throughout the cerebellum. Both ASD groups (ELD and non-ELD) had reduced GM in right cerebellar Crus I/II when compared to TD children. Left cerebellar Crus I/II was the only region in the brain that differentiated ELD and non-ELD children, with ELD children showing reduced GM relative to both non-ELD and TD groups. Group×score interactions converged in left Crus I/II, such that the non-ELD group showed poorer ADOS scores with increasing GM, whereas the ELD group showed poorer ADOS scores as GM decreased. Reduced GM in right cerebellar Crus I/I was related ASD diagnosis, while children with ELD showed additional reduced GM in left Crus I/II. These findings highlight the importance of specific cerebellar networks in both ASD and early language development, and suggest that bilateral disruption in cerebellar regions that interconnect with fronto-parietal networks could impact language acquisition in ASD. Autism Res 2016, 9: 1191-1204. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

On the brain structure heterogeneity of autism: Parsing out acquisition site effects with significance-weighted principal component analysis

Neuroimaging studies have reported structural and physiological differences that could help understand the causes and development of Autism Spectrum Disorder (ASD). Many of them rely on multisite designs, with the recruitment of larger samples increasing statistical power. However, recent large-scale studies have put some findings into question, considering the results to be strongly dependent on the database used, and demonstrating the substantial heterogeneity within this clinically defined category. One major source of variance may be the acquisition of the data in multiple centres. In this work we analysed the differences found in the multisite, multi-modal neuroimaging database from the UK Medical Research Council Autism Imaging Multicentre Study (MRC AIMS) in terms of both diagnosis and acquisition sites. Since the dissimilarities between sites were higher than between diagnostic groups, we developed a technique called Significance Weighted Principal Component Analysis (SWPCA) to reduce the undesired intensity variance due to acquisition site and to increase the statistical power in detecting group differences. After eliminating site-related variance, statistically significant group differences were found, including Broca's area and the temporo-parietal junction. However, discriminative power was not sufficient to classify diagnostic groups, yielding accuracies results close to random. Our work supports recent claims that ASD is a highly heterogeneous condition that is difficult to globally characterize by neuroimaging, and therefore different (and more homogenous) subgroups should be defined to obtain a deeper understanding of ASD. Hum Brain Mapp 38:1208-1223, 2017. © 2016 Wiley Periodicals, Inc.

The Cerebellum and Neurodevelopmental Disorders

Cerebellar dysfunction is evident in several developmental disorders, including autism, attention deficit-hyperactivity disorder (ADHD), and developmental dyslexia, and damage to the cerebellum early in development can have long-term effects on movement, cognition, and affective regulation. Early cerebellar damage is often associated with poorer outcomes than cerebellar damage in adulthood, suggesting that the cerebellum is particularly important during development. Differences in cerebellar development and/or early cerebellar damage could impact a wide range of behaviors via the closed-loop circuits connecting the cerebellum with multiple cerebral cortical regions. Based on these anatomical circuits, behavioral outcomes should depend on which cerebro-cerebellar circuits are affected. Here, we briefly review cerebellar structural and functional differences in autism, ADHD, and developmental dyslexia, and discuss clinical outcomes following pediatric cerebellar damage. These data confirm the prediction that abnormalities in different cerebellar subregions produce behavioral symptoms related to the functional disruption of specific cerebro-cerebellar circuits. These circuits might also be crucial to structural brain development, as peri-natal cerebellar lesions have been associated with impaired growth of the contralateral cerebral cortex. The specific contribution of the cerebellum to typical development may therefore involve the optimization of both the structure and function of cerebro-cerebellar circuits underlying skill acquisition in multiple domains; when this process is disrupted, particularly in early development, there could be long-term alterations of these neural circuits, with significant impacts on behavior.

Core deficits and quality of survival after childhood medulloblastoma: a review

Background

Medulloblastoma is the most common malignant central nervous system tumor in children. Treatment most often includes surgical resection, craniospinal irradiation, and adjuvant chemotherapy. Although survival has improved dramatically, the tumor and its treatments have devastating long-term side effects that negatively impact quality of survival (QoS). The objective was to review the literature on QoS following childhood medulloblastoma.

Methods

This narrative review is based on a Medline database search and examination of the reference lists of papers selected.

Results

Frequent problems after medulloblastoma treatment include medical complications, such as long-term neurological and sensory (hearing loss) impairments; endocrine deficits, including growth problems; and secondary tumors. Neurocognitive impairment is repeatedly reported, with decreasing cognitive performances over time. Although all cognitive domains may be affected, low processing speed, attention difficulties, and working memory difficulties are described as the core cognitive deficits resulting from both cerebellar damage and the negative effect of radiation on white matter development. Long-term psychosocial limitations include low academic achievement, unemployment, and poor community integration with social isolation. Important negative prognostic factors include young age at diagnosis, conventional craniospinal radiotherapy, presence of postoperative cerebellar mutism, and perioperative complications. The influence of environmental factors, such as family background and interventions, remains understudied.

Conclusion

Future studies should focus on the respective impact of radiation, cerebellar damage, genomic and molecular subgroup parameters, and environmental factors on cognitive and psychosocial outcomes. Long-term (probably lifelong) follow-up into adulthood is required in order to monitor development and implement timely, suitable, multi-disciplinary rehabilitation interventions and special education or support when necessary.

Decreased functional connectivity in the language regions in bipolar patients during depressive episodes but not remission

BACKGROUND

Retardation of thought is a crucial clinical feature in patients with bipolar depression, characterized by dysfunctional semantic processing and language communication. However, the underlying neuropathological mechanisms remain largely unknown. The objective of this study was to evaluate the disruption in resting-state functional connectivity in 90 different brain regions during the depressive episodes of bipolar disorder and during disease remission.

METHODS

Applying the whole brain and language regions of interest methods to the resting-state functional magnetic resonance imaging data, we explored the discrepancies in 90 brain regions' functional connectivity in 42 patients with bipolar disorder - 23 experiencing a depressive episode and 19 in remission - and 28 healthy controls matched for gender, age, and education.

RESULTS

Bipolar depressive patients had significantly reduced connectivity strength in the language regions relative to healthy controls. Specifically, the affected regions included the left triangular part of the inferior frontal gyrus, left opercular part of the inferior frontal gyrus, left middle temporal gyrus, and left angular gyrus. However, no significant differences in these regions were observed between bipolar patients in remission and healthy controls. Furthermore, the decreased connectivity strength between the left middle temporal gyrus and right lingual gyrus showed significant positive correlation with the scores on the Hamilton Depression Rating Scale.

LIMITATIONS

Bipolar depressive patients received treatment of benzodiazepines, which may confound the findings.

CONCLUSIONS

Our results illustrated that connectivity disturbances in the language regions may change depending on the disease phase of bipolar disorder.

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.

Perceptual Integration Deficits in Autism Spectrum Disorders Are Associated with Reduced Interhemispheric Gamma-Band Coherence

The integration of visual details into a holistic percept is essential for object recognition. This integration has been reported as a key deficit in patients with autism spectrum disorders (ASDs). The weak central coherence account posits an altered disposition to integrate features into a coherent whole in ASD. Here, we test the hypothesis that such weak perceptual coherence may be reflected in weak neural coherence across different cortical sites. We recorded magnetoencephalography from 20 adult human participants with ASD and 20 matched controls, who performed a slit-viewing paradigm, in which objects gradually passed behind a vertical or horizontal slit so that only fragments of the object were visible at any given moment. Object recognition thus required perceptual integration over time and, in case of the horizontal slit, also across visual hemifields. ASD participants were selectively impaired in the horizontal slit condition, indicating specific difficulties in long-range synchronization between the hemispheres. Specifically, the ASD group failed to show condition-related enhancement of imaginary coherence between the posterior superior temporal sulci in both hemispheres during horizontal slit-viewing in contrast to controls. Moreover, local synchronization reflected in occipitocerebellar beta-band power was selectively reduced for horizontal compared with vertical slit-viewing in ASD. Furthermore, we found disturbed connectivity between right posterior superior temporal sulcus and left cerebellum. Together, our results suggest that perceptual integration deficits co-occur with specific patterns of abnormal global and local synchronization in ASD.

SIGNIFICANCE STATEMENT

The weak central coherence account proposes a tendency of individuals with autism spectrum disorders (ASDs) to focus on details at the cost of an integrated coherent whole. Here, we provide evidence, at the behavioral and the neural level, that visual integration in object recognition is impaired in ASD, when details had to be integrated across both visual hemifields. We found enhanced interhemispheric gamma-band coherence in typically developed participants when communication between cortical hemispheres was required by the task. Importantly, participants with ASD failed to show this enhanced coherence between bilateral posterior superior temporal sulci. The findings suggest that visual integration is disturbed at the local and global synchronization scale, which might bear implications for object recognition in ASD.

The Oscillopathic Nature of Language Deficits in Autism: From Genes to Language Evolution

Autism spectrum disorders (ASD) are pervasive neurodevelopmental disorders involving a number of deficits to linguistic cognition. The gap between genetics and the pathophysiology of ASD remains open, in particular regarding its distinctive linguistic profile. The goal of this article is to attempt to bridge this gap, focusing on how the autistic brain processes language, particularly through the perspective of brain rhythms. Due to the phenomenon of pleiotropy, which may take some decades to overcome, we believe that studies of brain rhythms, which are not faced with problems of this scale, may constitute a more tractable route to interpreting language deficits in ASD and eventually other neurocognitive disorders. Building on recent attempts to link neural oscillations to certain computational primitives of language, we show that interpreting language deficits in ASD as oscillopathic traits is a potentially fruitful way to construct successful endophenotypes of this condition. Additionally, we will show that candidate genes for ASD are overrepresented among the genes that played a role in the evolution of language. These genes include (and are related to) genes involved in brain rhythmicity. We hope that the type of steps taken here will additionally lead to a better understanding of the comorbidity, heterogeneity, and variability of ASD, and may help achieve a better treatment of the affected populations.

Risk Factors Associated With Language in Autism Spectrum Disorder: Clues to Underlying Mechanisms

PURPOSE

Identifying risk factors associated with neurodevelopmental disorders is an important line of research, as it will lead to earlier identification of children who could benefit from interventions that support optimal developmental outcomes. The primary goal of this review was to summarize research on risk factors associated with autism spectrum disorder (ASD).

METHOD

The review focused on studies of infants who have older siblings with ASD, with particular emphasis on risk factors associated with language impairment that affects the majority of children with ASD. Findings from this body of work were compared to the literature on specific language impairment.

RESULTS

A wide range of risk factors has been found for ASD, including demographic (e.g., male, family history), behavioral (e.g., gesture, motor) and neural risk markers (e.g., atypical lateralization for speech and reduced functional connectivity). Environmental factors, such as caregiver interaction, have not been found to predict language outcomes. Many of the risk markers for ASD are also found in studies of risk for specific language impairment, including demographic, behavioral, and neural factors.

CONCLUSIONS

There are significant gaps in the literature and limitations in the current research that preclude direct cross-syndrome comparisons. Future research directions are outlined that could address these limitations.

The Cerebellum and Neurodevelopmental Disorders

Cerebellar dysfunction is evident in several developmental disorders, including autism, attention deficit-hyperactivity disorder (ADHD), and developmental dyslexia, and damage to the cerebellum early in development can have long-term effects on movement, cognition, and affective regulation. Early cerebellar damage is often associated with poorer outcomes than cerebellar damage in adulthood, suggesting that the cerebellum is particularly important during development. Differences in cerebellar development and/or early cerebellar damage could impact a wide range of behaviors via the closed-loop circuits connecting the cerebellum with multiple cerebral cortical regions. Based on these anatomical circuits, behavioral outcomes should depend on which cerebro-cerebellar circuits are affected. Here, we briefly review cerebellar structural and functional differences in autism, ADHD, and developmental dyslexia, and discuss clinical outcomes following pediatric cerebellar damage. These data confirm the prediction that abnormalities in different cerebellar subregions produce behavioral symptoms related to the functional disruption of specific cerebro-cerebellar circuits. These circuits might also be crucial to structural brain development, as peri-natal cerebellar lesions have been associated with impaired growth of the contralateral cerebral cortex. The specific contribution of the cerebellum to typical development may therefore involve the optimization of both the structure and function of cerebro-cerebellar circuits underlying skill acquisition in multiple domains; when this process is disrupted, particularly in early development, there could be long-term alterations of these neural circuits, with significant impacts on behavior.

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.

Language comprehension and brain function in individuals with an optimal outcome from autism

Although Autism Spectrum Disorder (ASD) is generally a lifelong disability, a minority of individuals with ASD overcome their symptoms to such a degree that they are generally indistinguishable from their typically-developing peers. That is, they have achieved an Optimal Outcome (OO). The question addressed by the current study is whether this normalized behavior reflects normalized brain functioning, or alternatively, the action of compensatory systems. Either possibility is plausible, as most participants with OO received years of intensive therapy that could alter brain networks to align with typical function or work around ASD-related neural dysfunction. Individuals ages 8 to 21 years with high-functioning ASD (n = 23), OO (n = 16), or typical development (TD; n = 20) completed a functional MRI scan while performing a sentence comprehension task. Results indicated similar activations in frontal and temporal regions (left middle frontal, left supramarginal, and right superior temporal gyri) and posterior cingulate in OO and ASD groups, where both differed from the TD group. Furthermore, the OO group showed heightened “compensatory” activation in numerous left- and right-lateralized regions (left precentral/postcentral gyri, right precentral gyrus, left inferior parietal lobule, right supramarginal gyrus, left superior temporal/parahippocampal gyrus, left middle occipital gyrus) and cerebellum, relative to both ASD and TD groups. Behaviorally normalized language abilities in OO individuals appear to utilize atypical brain networks, with increased recruitment of language-specific as well as right homologue and other systems. Early intensive learning and experience may normalize behavioral language performance in OO, but some brain regions involved in language processing may continue to display characteristics that are more similar to ASD than typical development, while others show characteristics not like ASD or typical development.

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fMRI study of "optimal outcome" (OO) youth with no symptoms of autism spectrum disorder.

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Results show “compensatory” language activation in some areas in OO.

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OO youth also had some “residual ASD” patterns of activation (OO, ASD > TD).

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There was no evidence of areas of normalized brain function (OO, TD ≠ ASD).

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Early treatment may normalize behavior but not brain in some individuals with ASD.

Consensus paper: radiological biomarkers of cerebellar diseases

Hereditary and sporadic cerebellar ataxias represent a vast and still growing group of diseases whose diagnosis and differentiation cannot only rely on clinical evaluation. Brain imaging including magnetic resonance (MR) and nuclear medicine techniques allows for characterization of structural and functional abnormalities underlying symptomatic ataxias. These methods thus constitute a potential source of radiological biomarkers, which could be used to identify these diseases and differentiate subgroups of them, and to assess their severity and their evolution. Such biomarkers mainly comprise qualitative and quantitative data obtained from MR including proton spectroscopy, diffusion imaging, tractography, voxel-based morphometry, functional imaging during task execution or in a resting state, and from SPETC and PET with several radiotracers. In the current article, we aim to illustrate briefly some applications of these neuroimaging tools to evaluation of cerebellar disorders such as inherited cerebellar ataxia, fetal developmental malformations, and immune-mediated cerebellar diseases and of neurodegenerative or early-developing diseases, such as dementia and autism in which cerebellar involvement is an emerging feature. Although these radiological biomarkers appear promising and helpful to better understand ataxia-related anatomical and physiological impairments, to date, very few of them have turned out to be specific for a given ataxia with atrophy of the cerebellar system being the main and the most usual alteration being observed. Consequently, much remains to be done to establish sensitivity, specificity, and reproducibility of available MR and nuclear medicine features as diagnostic, progression and surrogate biomarkers in clinical routine.

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.