Alterations of Functional Connectivity in Autism and Attention-Deficit/Hyperactivity Disorder Revealed by Multi-Voxel Pattern Analysis.

Background: Autism and attention-deficit/hyperactivity disorder (ADHD) are comorbid neurodevelopmental disorders that share common and distinct neurobiological mechanisms, with disrupted brain connectivity patterns being a hallmark feature of both conditions. It is challenging to gain a mechanistic understanding of the underlying disorder, because brain connectivity changes in autism and ADHD are heterogeneous. Objectives: The present resting state functional MRI (rs-fMRI) study focuses on investigating the shared and distinct resting state-fMRI connectivity (rsFC) patterns in autistic and ADHD adults using multi-voxel pattern analysis (MVPA). By identifying spatial patterns of fMRI activity across a given time course, MVPA is an innovative and powerful method for generating seed regions of interest (ROIs) without a priori hypotheses. Methods: We performed a data-driven, whole-brain, connectome-wide MVPA on rs-fMRI data collected from 15 autistic, 19 ADHD, and 15 neurotypical (NT) young adults. Results: MVPA identified cerebellar vermis 9, precuneus, and the right cerebellum VI for autistic versus NT, right inferior frontal gyrus and vermis 9 for ADHD versus NT, and right dorsolateral prefrontal cortex for autistic versus ADHD as significant clusters. Post hoc seed-to-voxel analyses using these clusters as seed ROIs were performed for further characterization of group differences. The cerebellum VI, vermis, and precuneus in autistic adults, and the vermis and frontal regions in ADHD showed different connectivity patterns in comparison with NT. Conclusions: The study characterizes the rsFC profile of cerebellum with key cortical areas in autism and ADHD, and it emphasizes the importance of studying the role of the functional connectivity of the cerebellum in neurodevelopmental disorders.

Cerebello-cerebral Functional Connectivity Networks in Major Depressive Disorder: a CAN-BIND-1 Study Report.

Neuroimaging studies have demonstrated aberrant structure and function of the "cognitive-affective cerebellum" in major depressive disorder (MDD), although the specific role of the cerebello-cerebral circuitry in this population remains largely uninvestigated. The objective of this study was to delineate the role of cerebellar functional networks in depression. A total of 308 unmedicated participants completed resting-state functional magnetic resonance imaging scans, of which 247 (148 MDD; 99 healthy controls, HC) were suitable for this study. Seed-based resting-state functional connectivity (RsFc) analysis was performed using three cerebellar regions of interest (ROIs): ROI1 corresponded to default mode network (DMN)/inattentive processing; ROI2 corresponded to attentional networks, including frontoparietal, dorsal attention, and ventral attention; ROI3 corresponded to motor processing. These ROIs were delineated based on prior functional gradient analyses of the cerebellum. A general linear model was used to perform within-group and between-group comparisons. In comparison to HC, participants with MDD displayed increased RsFc within the cerebello-cerebral DMN (ROI1) and significantly elevated RsFc between the cerebellar ROI1 and bilateral angular gyrus at a voxel threshold (p < 0.001, two-tailed) and at a cluster level (p < 0.05, FDR-corrected). Group differences were non-significant for ROI2 and ROI3. These results contribute to the development of a systems neuroscience approach to the diagnosis and treatment of MDD. Specifically, our findings confirm previously reported associations between MDD, DMN, and cerebellum, and highlight the promising role of these functional and anatomical locations for the development of novel imaging-based biomarkers and targets for neuromodulation therapies. ClinicalTrials.gov TRN: NCT01655706; Date of Registration: August 2nd, 2012.

Resting-State Functional Connectivity in Relapsing-Remitting Multiple Sclerosis with Mild Disability: A Data-Driven, Whole-Brain Multivoxel Pattern Analysis Study.

Background: Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results. Objectives: The aim of the present study was to investigate RSFC differences between people with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC). Methods: We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HCs. Results: Significant group differences were noted in RSFC in three clusters distributed in the following regions: anterior cingulate gyrus, right middle frontal gyrus, and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network-specific abnormalities, specifically in the anterior cingulate cortex and the default mode network. Conclusions: The network-wide RSFC abnormalities we report agree with the previous findings in RRMS, the cognitive and clinical implications of which are discussed herein. Impact statement This study investigated resting-state functional connectivity (RSFC) in relapsing-remitting multiple sclerosis (RRMS) people with mild disability (expanded disability status scale ≤4). Whole-brain connectome-wide multivoxel pattern analysis was used for assessing RSFC. Compared with healthy controls, we were able to identify three regions of interest for significant differences in connectivity patterns, which were then extracted as a mask for whole-brain seed-to-voxel analysis. A reduced connectivity was noted in the RRMS group, particularly in the anterior cingulate cortex and the default mode network regions, providing insights into the RSFC abnormalities in RRMS.

Treatment Response of Transcranial Magnetic Stimulation in Intellectually Capable Youth and Young Adults with Autism Spectrum Disorder: A Systematic Review and Meta-Analysis.

To examine current clinical research on the use of transcranial magnetic stimulation (TMS) in the treatment of pediatric and young adult autism spectrum disorder in intellectually capable persons (IC-ASD). We searched peer-reviewed international literature to identify clinical trials investigating TMS as a treatment for behavioral and cognitive symptoms of IC-ASD. We identified sixteen studies and were able to conduct a meta-analysis on twelve of these studies. Seven were open-label or used neurotypical controls for baseline cognitive data, and nine were controlled trials. In the latter, waitlist control groups were often used over sham TMS. Only one study conducted a randomized, parallel, double-blind, and sham controlled trial. Favorable safety data was reported in low frequency repetitive TMS, high frequency repetitive TMS, and intermittent theta burst studies. Compared to TMS research of other neuropsychiatric conditions, significantly lower total TMS pulses were delivered in treatment and neuronavigation was not regularly utilized. Quantitatively, our multivariate meta-analysis results report improvement in cognitive outcomes (pooled Hedges' g = 0.735, 95% CI = 0.242, 1.228; p = 0.009) and primarily Criterion B symptomology of IC-ASD (pooled Hedges' g = 0.435, 95% CI = 0.359, 0.511; p < 0.001) with low frequency repetitive TMS to the dorsolateral prefrontal cortex. The results of our systematic review and meta-analysis data indicate that TMS may offer a promising and safe treatment option for pediatric and young adult patients with IC-ASD. However, future work should include use of neuronavigation software, theta burst protocols, targeting of various brain regions, and robust study design before clinical recommendations can be made.

Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior.

Sedentary behaviors are increasing at the cost of millions of dollars spent in health care and productivity losses due to physical inactivity-related deaths worldwide. Understanding the mechanistic predictors of sedentary behaviors will improve future intervention development and precision medicine approaches. It has been posited that humans have an innate attraction towards effort minimization and that inhibitory control is required to overcome this prepotent disposition. Consequently, we hypothesized that individual differences in the functional connectivity of brain regions implicated in inhibitory control and physical effort decision making at the beginning of an exercise intervention in older adults would predict the change in time spent sedentary over the course of that intervention. In 143 healthy, low-active older adults participating in a 6-month aerobic exercise intervention (with three conditions: walking, dance, stretching), we aimed to use baseline neuroimaging (resting state functional connectivity of two a priori defined seed regions), and baseline accelerometer measures of time spent sedentary to predict future pre-post changes in objectively measured time spent sedentary in daily life over the 6-month intervention. Our results demonstrated that functional connectivity between (1) the anterior cingulate cortex and the supplementary motor area and (2) the right anterior insula and the left temporoparietal/temporooccipital junction, predicted changes in time spent sedentary in the walking group. Functional connectivity of these brain regions did not predict changes in time spent sedentary in the dance nor stretch and tone conditions, but baseline time spent sedentary was predictive in these conditions. Our results add important knowledge toward understanding mechanistic associations underlying complex out-of-session sedentary behaviors within a walking intervention setting in older adults.

Enriching activities during childhood are associated with variations in functional connectivity patterns later in life.

Enriching early life experiences (e.g., sport, art, music, volunteering, language learning) during a critical period of brain development may promote structural and functional brain changes that are still present decades later (>60 years). We assessed whether a greater variety of enriching early life activities (EELA) before age 13 years were associated with individual differences in cortical and subcortical (hippocampus and amygdala) structure and function later in life (older adults aged 60-80 years). Results indicated no association between EELA and amygdala and hippocampus volumes, but higher functional connectivity between the amygdala and the insula was associated with more variety of EELA. EELA was not associated with cortical thickness controlling for sex, but sex-specific associations with the right pars opercularis were found. EELA was further associated with variations in functional connectivity patterns of the orbitofrontal cortex, driven by connecitivty to regions within the visual, somatosensory and limbic networks. Early life enriching activities appear to contribute to potential mechanisms of cognitive reserve (functional processes) more so than brain reserve (structure) later in life.

Abnormal Function in Dentate Nuclei Precedes the Onset of Psychosis: A Resting-State fMRI Study in High-Risk Individuals.

OBJECTIVE: The cerebellum serves a wide range of functions and is suggested to be composed of discrete regions dedicated to unique functions. We recently developed a new parcellation of the dentate nuclei (DN), the major output nuclei of the cerebellum, which optimally divides the structure into 3 functional territories that contribute uniquely to default-mode, motor-salience, and visual processing networks as indexed by resting-state functional connectivity (RsFc). Here we test for the first time whether RsFc differences in the DN, precede the onset of psychosis in individuals at risk of developing schizophrenia. METHODS: We used the magnetic resonance imaging (MRI) dataset from the Shanghai At Risk for Psychosis study that included subjects at high risk to develop schizophrenia (N = 144), with longitudinal follow-up to determine which subjects developed a psychotic episode within 1 year of their functional magnetic resonance imaging (fMRI) scan (converters N = 23). Analysis used the 3 functional parcels (default-mode, salience-motor, and visual territory) from the DN as seed regions of interest for whole-brain RsFc analysis. RESULTS: RsFc analysis revealed abnormalities at baseline in high-risk individuals who developed psychosis, compared to high-risk individuals who did not develop psychosis. The nature of the observed abnormalities was found to be anatomically specific such that abnormal RsFc was localized predominantly in cerebral cortical networks that matched the 3 functional territories of the DN that were evaluated. CONCLUSIONS: We show for the first time that abnormal RsFc of the DN may precede the onset of psychosis. This new evidence highlights the role of the cerebellum as a potential target for psychosis prediction and prevention.

Ultra-high field (7T) functional magnetic resonance imaging in amyotrophic lateral sclerosis: a pilot study.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of the central nervous system that results in a progressive loss of motor function and ultimately death. It is critical, yet also challenging, to develop non-invasive biomarkers to identify, localize, measure and/or track biological mechanisms implicated in ALS. Such biomarkers may also provide clues to identify potential molecular targets for future therapeutic trials. Herein we report on a pilot study involving twelve participants with ALS and nine age-matched healthy controls who underwent high-resolution resting state functional magnetic resonance imaging at an ultra-high field of 7 Tesla. A group-level whole-brain analysis revealed a disruption in long-range functional connectivity between the superior sensorimotor cortex (in the precentral gyrus) and bilateral cerebellar lobule VI. Post hoc analyses using atlas-derived left and right cerebellar lobule VI revealed decreased functional connectivity in ALS participants that predominantly mapped to bilateral postcentral and precentral gyri. Cerebellar lobule VI is a transition zone between anterior motor networks and posterior non-motor networks in the cerebellum, and is associated with a wide range of key functions including complex motor and cognitive processing tasks. Our observation of the involvement of cerebellar lobule VI adds to the growing number of studies implicating the cerebellum in ALS. Future avenues of scientific investigation should consider how high-resolution imaging at 7T may be leveraged to visualize differences in functional connectivity disturbances in various genotypes and phenotypes of ALS along the ALS-frontotemporal dementia spectrum.

A comprehensive data-driven analysis framework for detecting impairments in brain function networks with resting state fMRI in HIV-infected individuals on cART.

Central nervous system (CNS) sequelae continue to be common in HIV-infected individuals despite combination antiretroviral therapy (cART). These sequelae include HIV-associated neurocognitive disorder (HAND) and virologic persistence in the CNS. Resting state functional magnetic resonance imaging (rsfMRI) is a widely used tool to examine the integrity of brain function and pathology. In this study, we examined 16 HIV-positive (HIV+) subjects and 12 age, sex, and race matched HIV seronegative controls (HIV-) whole-brain high-resolution rsfMRI along with a battery of neurocognitive tests. A comprehensive data-driven analysis of rsfMRI revealed impaired functional connectivity, with very large effect sizes in executive function, language, and multisensory processing networks in HIV+ subjects. These results indicate the potential of high-resolution rsfMRI in combination with advanced data analysis techniques to yield biomarkers of neural impairment in HIV.

Hyperactivation of Posterior Default Mode Network During Self-Referential Processing in Children at Familial High-Risk for Psychosis.

Patients with schizophrenia spectrum disorders show disturbances in self-referential processing and associated neural circuits including the default mode network (DMN). These disturbances may precede the onset of psychosis and may underlie early social and emotional problems. In this study, we examined self-referential processing in a group of children (7-12 years) at familial high risk (FHR) for psychosis (N = 17), compared to an age and sex-matched group of healthy control (HC) children (N = 20). The participants were presented with a list of adjectives and asked to indicate whether or not the adjectives described them (self-reference condition) and whether the adjectives described a good or bad trait (semantic condition). Three participants were excluded due to chance-level performance on the semantic task, leaving N = 15 FHR and N = 19 HC for final analysis. Functional MRI (fMRI) was used to measure brain activation during self-referential vs. semantic processing. Internalizing and externalizing problems were assessed with the Child Behavior Checklist (CBCL). Evaluating main effects of task (self > semantic) showed activation of medial prefrontal cortex in HC and precuneus/posterior cingulate cortex (PCC) in FHR. Group-comparison yielded significant results for the FHR > HC contrast, showing two clusters of hyperactivation in precuneus/ PCC (p = 0.004) and anterior cerebellum / temporo-occipital cortex (p = 0.009). Greater precuneus/PCC activation was found to correlate with greater CBCL internalizing (r = 0.60, p = 0.032) and total (r = 0.69, p = 0.009) problems. In all, this study shows hyperactivity of posterior DMN during self-referential processing in pre-adolescent FHR children. This finding posits DMN-related disturbances in self-processing as a developmental brain abnormality associated with familial risk factors that predates not just psychosis, but also the prodromal stage. Moreover, our results suggest that early disturbances in self-referential processing may be related to internalizing problems in at-risk children.

Functional Alterations in Cerebellar Functional Connectivity in Anxiety Disorders.

Adolescents with anxiety disorders exhibit excessive emotional and somatic arousal. Neuroimaging studies have shown abnormal cerebral cortical activation and connectivity in this patient population. The specific role of cerebellar output circuitry, specifically the dentate nuclei (DN), in adolescent anxiety disorders remains largely unexplored. Resting-state functional connectivity analyses have parcellated the DN, the major output nuclei of the cerebellum, into three functional territories (FTs) that include default-mode, salience-motor, and visual networks. The objective of this study was to understand whether FTs of the DN are implicated in adolescent anxiety disorders. Forty-one adolescents (mean age 15.19 ± 0.82, 26 females) with one or more anxiety disorders and 55 age- and gender-matched healthy controls completed resting-state fMRI scans and a self-report survey on anxiety symptoms. Seed-to-voxel functional connectivity analyses were performed using the FTs from DN parcellation. Brain connectivity metrics were then correlated with State-Trait Anxiety Inventory (STAI) measures within each group. Adolescents with an anxiety disorder showed significant hyperconnectivity between salience-motor DN FT and cerebral cortical salience-motor regions compared to controls. Salience-motor FT connectivity with cerebral cortical sensorimotor regions was significantly correlated with STAI-trait scores in HC (R2 = 0.41). Here, we report DN functional connectivity differences in adolescents diagnosed with anxiety, as well as in HC with variable degrees of anxiety traits. These observations highlight the relevance of DN as a potential clinical and sub-clinical marker of anxiety.

Functional Alterations Associated with Structural Abnormalities in Adults with High-Functioning Autism Spectrum Disorder.

Background: The combination of structural and functional analyses is a biologically valid approach that offers methodological advantages in autism spectrum disorder (ASD) neuroimaging science. The paucity of studies combining these methods constitutes an important knowledge gap. In this study, we investigate structural abnormalities and their associated functional differences in a developmentally homogeneous ASD cohort. Methods: Whole-brain voxel-based morphometry (VBM) analyses were performed on 28 ASD participants and 38 age-matched typically developing healthy controls (HC) to derive gray matter (GM) volume differences. The anatomically relevant clusters identified by VBM served as seed regions of interest (ROI) for resting-state functional-connectivity (RsFc) analysis. Results: Whole-brain VBM analyses revealed significant right lateralized GM volume abnormality in the ASD group, with lower GM volumes in cerebellar lobules VIIb/VIIIa (cluster 1) and significantly higher GM volumes in posterior middle/superior temporal gyri (Brodmann area [BA] 21/22, cluster 2) compared with HC. Whole-brain RsFc analysis in high-functioning ASD (HF-ASD) revealed significant hypoconnectivity of the cerebellar VBM cluster with the right cerebral cortical regions of superior parietal lobule (BA 7) and occipital pole (BA 19) (overlapping with dorsal attention and visual networks, respectively). Cerebral cortical VBM cluster (cluster 2) revealed significant hypoconnectivity in HF-ASD with other task-positive cerebral cortical including the left lateral prefrontal cortex (frontoparietal network) and some aspects of the insula (ventral attention network) and ectopic positive connectivity (lack of anticorrelations) with posterior cingulate cortex and medial prefrontal cortex (default mode network). Conclusions: The cerebro-cerebellar intrinsic functional dysconnectivity based on the whole-brain VBM-derived ROIs may advance our understanding of the compensatory mechanisms associated with ASD and offer cerebellum as a potential target for diagnostic, predictive, prognostic, and therapeutic interventions in ASD. Our findings also provide additional support indicating that functional abnormalities as indexed by RsFc exist in ASD, and highlight that there is likely a relationship between structural and functional abnormalities in this disorder. Impact statement Our findings indicate that functional differences as indexed by resting-state functional connectivity exist in autism spectrum disorder (ASD), and highlight that there is likely a relationship between structural and functional abnormalities in this disorder. Future developments in neuroimaging research should continue investigating structural and associated functional differences in ASD, and in this way complement the behavioral characterization of this disorder, potentially improving diagnosis, prognosis, and prediction.

Functional connectome organization predicts conversion to psychosis in clinical high-risk youth from the SHARP program.

The emergence of prodromal symptoms of schizophrenia and their evolution into overt psychosis may stem from an aberrant functional reorganization of the brain during adolescence. To examine whether abnormalities in connectome organization precede psychosis onset, we performed a functional connectome analysis in a large cohort of medication-naive youth at risk for psychosis from the Shanghai At Risk for Psychosis (SHARP) study. The SHARP program is a longitudinal study of adolescents and young adults at Clinical High Risk (CHR) for psychosis, conducted at the Shanghai Mental Health Center in collaboration with neuroimaging laboratories at Harvard and MIT. Our study involved a total of 251 subjects, including 158 CHRs and 93 age-, sex-, and education-matched healthy controls. During 1-year follow-up, 23 CHRs developed psychosis. CHRs who would go on to develop psychosis were found to show abnormal modular connectome organization at baseline, while CHR non-converters did not. In all CHRs, abnormal modular connectome organization at baseline was associated with a threefold conversion rate. A region-specific analysis showed that brain regions implicated in early-course schizophrenia, including superior temporal gyrus and anterior cingulate cortex, were most abnormal in terms of modular assignment. Our results show that functional changes in brain network organization precede the onset of psychosis and may drive psychosis development in at-risk youth.

Functional Territories of Human Dentate Nucleus.

Anatomical connections link the cerebellar cortex with multiple sensory, motor, association, and paralimbic cerebral areas. The majority of fibers that exit cerebellar cortex synapse in dentate nuclei (DN) before reaching extracerebellar structures such as cerebral cortex, but the functional neuroanatomy of human DN remains largely unmapped. Neuroimaging research has redefined broad categories of functional division in the human brain showing that primary processing, attentional (task positive) processing, and default-mode (task negative) processing are three central poles of neural macroscale functional organization. This broad spectrum of human neural processing categories is represented not only in the cerebral cortex, but also in the thalamus, striatum, and cerebellar cortex. Whether functional organization in DN obeys a similar set of macroscale divisions, and whether DN are yet another compartment of representation of a broad spectrum of human neural processing categories, remains unknown. Here, we show for the first time that human DN are optimally divided into three functional territories as indexed by high spatio-temporal resolution resting-state MRI in 77 healthy humans, and that these three distinct territories contribute uniquely to default-mode, salience-motor, and visual cerebral cortical networks. Our findings provide a systems neuroscience substrate for cerebellar output to influence multiple broad categories of neural control.

Improvising at rest: Differentiating jazz and classical music training with resting state functional connectivity.

Jazz improvisation offers a model for creative cognition, as it involves the real-time creation of a novel, information-rich product. Previous research has shown that when musicians improvise, they recruit regions in the Default Mode Network (DMN) and Executive Control Network (ECN). Here, we ask whether these findings from task-fMRI studies might extend to intrinsic differences in resting state functional connectivity. We compared Improvising musicians, Classical musicians, and Minimally Musically Trained (MMT) controls in seed-based functional connectivity and network analyses in resting state functional MRI. We also examined the functional correlates of behavioral performance in musical improvisation and divergent thinking. Seed-based analysis consistently showed higher connectivity in ventral DMN (vDMN) and bilateral ECN in both groups of musically trained individuals as compared to MMT controls, with additional group differences in primary visual network. In particular, primary visual network connectivity to DMN and ECN was highest in Improvisational musicians, as was connectivity between ECN and DMN; in contrast, connectivity between vDMN and frontal pole was highest in Classical musicians. Furthermore, graph-theoretical analysis indicated heightened network measures in both musician groups, with betweenness centrality, clustering, and local efficiency showing highest levels in Classical musicians, and degrees and strengths showing highest levels in Improvisational musicians. Taken together, results suggest that heightened functional connectivity among musicians can be explained by higher within-network connectivity (more tight-knit cortical networks) in Classical musicians, as opposed to more disperse, globally-connected cortical networks in Improvisational musicians.

Association of Intrinsic Brain Architecture With Changes in Attentional and Mood Symptoms During Development.

Importance: Understanding the neurodevelopmental trajectory of psychiatric symptoms is important for improving early identification, intervention, and prevention of mental disorders. Objective: To test whether the strength of the coupling of activation between specific brain regions, as measured by resting-state functional magnetic resonance imaging (fMRI), predicted individual children's developmental trajectories in terms of attentional problems characteristic of attention-deficit/hyperactivity disorder and internalizing problems characteristics of major depressive disorder (MDD). Design, Setting, and Participants: A community cohort of 94 children was recruited from Vanderbilt University between 2010 and 2013. They were followed up longitudinally for 4 years and the data were analyzed from 2016 to 2019. Based on preregistered hypotheses and an analytic plan, we examined whether specific brain connectivity patterns would be associated with longitudinal changes in scores on the Child Behavior Checklist (CBCL), a parental-report assessment used to screen for emotional, behavioral, and social problems and to predict psychiatric illnesses. Main Outcomes and Measures: We used the strength of resting-state fMRI connectivity at age 7 years to predict subsequent changes in CBCL measures 4 years later and investigated the mechanisms of change by associating brain connectivity changes with changes in the CBCL. Results: We analyzed data from a longitudinal brain development study involving children assessed at age 7 years (n = 94; 41 girls [43.6%]) and 11 years (n = 54; 32 girls [59.3%]). As predicted, less positive coupling at age 7 years between the medial prefrontal cortex and dorsolateral prefrontal cortex (DLPFC) was associated with a decrease in attentional symptoms by age 11 years (t49 = 2.38; P = .01; ß = 0.32). By contrast, a less positive coupling between a region implicated in mood, the subgenual anterior cingulate cortex (sgACC), and DLPFC at age 7 years was associated with an increase in internalizing (eg, anxiety/depression) behaviors by age 11 years (t49 = -2.4; P = .01; ß = -0.30). Logistic regression analyses revealed that sgACC-DLPFC connectivity was a more accurate predictor than baseline CBCL measures for progression to a subclinical score on internalization (t50 = -2.61; P = .01; ß = -0.29). We then replicated and extended the sgACC-DLPFC result in an independent sample of children with (n = 25) or without (n = 18) familial risk for MDD. Conclusions and Relevance: These resting-state fMRI metrics are promising biomarkers for the early identification of children at risk of developing MDD or attention-deficit/hyperactivity disorder.

Altered resting-state functional connectivity in young children at familial high risk for psychotic illness: A preliminary study.

Multiple lines of evidence suggest that illness development in schizophrenia and other psychotic disorders predates the first psychotic episode by many years. In this study, we examined a sample of 15 pre-adolescent children, ages 7 through 12 years, who are at familial high-risk (FHR) because they have a parent or sibling with a history of schizophrenia or related psychotic disorder. Using multi-voxel pattern analysis (MVPA), a data-driven fMRI analysis, we assessed whole-brain differences in functional connectivity in the FHR sample as compared to an age- and sex-matched control (CON) group of 15 children without a family history of psychosis. MVPA analysis yielded a single cluster in right posterior superior temporal gyrus (pSTG/BA 22) showing significant group-differences in functional connectivity. Post-hoc characterization of this cluster through seed-to-voxel analysis revealed mostly reduced functional connectivity of the pSTG seed to a set of language and default mode network (DMN) associated brain regions including Heschl's gyrus, inferior temporal gyrus extending into fusiform gyrus, (para)hippocampus, thalamus, and a cerebellar cluster encompassing mainly Crus I/II. A height-threshold of whole-brain p < .001 (two-sided), and FDR-corrected cluster-threshold of p < .05 (non-parametric statistics) was used for post-hoc characterization. These findings suggest that abnormalities in functional communication in a network encompassing right STG and associated brain regions are present before adolescence in at-risk children and may be a risk marker for psychosis. Subsequent changes in this functional network across development may contribute to either disease manifestation or resilience in children with a familial vulnerability for psychosis.

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.

Exploring functional connectivity networks with multichannel brain array coils.

The use of multichannel array head coils in functional and structural magnetic resonance imaging (MRI) provides increased signal-to-noise ratio (SNR), higher sensitivity, and parallel imaging capabilities. However, their benefits remain to be systematically explored in the context of resting-state functional connectivity MRI (fcMRI). In this study, we compare signal detectability within and between commercially available multichannel brain coils, a 32-Channel (32Ch), and a 12-Channel (12Ch) at 3T, in a high-resolution regime to accurately map resting-state networks. We investigate whether the 32Ch coil can extract and map fcMRI more efficiently and robustly than the 12Ch coil using seed-based and graph-theory-based analyses. Our findings demonstrate that although the 12Ch coil can be used to reveal resting-state connectivity maps, the 32Ch coil provides increased detailed functional connectivity maps (using seed-based analysis) as well as increased global and local efficiency, and cost (using graph-theory-based analysis), in a number of widely reported resting-state networks. The exploration of subcortical networks, which are scarcely reported due to limitations in spatial-resolution and coil sensitivity, also proved beneficial with the 32Ch coil. Further, comparisons regarding the data acquisition time required to successfully map these networks indicated that scan time can be significantly reduced by 50% when a coil with increased number of channels (i.e., 32Ch) is used. Switching to multichannel arrays in resting-state fcMRI could, therefore, provide both detailed functional connectivity maps and acquisition time reductions, which could further benefit imaging special subject populations, such as patients or pediatrics who have less tolerance in lengthy imaging sessions.