Resting-state Functional Connectivity Data Research Articles

Assessing periadolescent memory ability and characterizing the development of a functional brain network vulnerable to Alzheimer’s disease

AbstractBackgroundIn typically presenting Alzheimer’s disease (AD), pathological changes to the hippocampus (Hc) and its associated functional brain networks result in impaired declarative/relational memory. While it is known that risk factors for AD (genetic, environmental, etc.) can impact hippocampal resting‐state functional connectivity (RSFC) later in life, the development of the hippocampus and its connections to other brain regions may also be influenced by such risk factors. The goal the current study was to characterize the neurodevelopmental changes in this hippocampal network during the periadolescent epoch and determine whether the observed changes were associated with declarative/relational memory ability. Therefore, we utilized a cross‐sectional approach to test whether individual differences in hippocampal RSFC covary with outcomes on a test of relational memory ability in periadolescent children.MethodData were drawn from an ongoing NIA‐funded project: the Polygenic Risk of Alzheimer’s Disease in Nebraska Kids (PRANK) study. Our analysis was carried out using data from healthy periadolescent participants (N=90; age 8‐13 years). We assessed declarative/relational memory with Cambridge Cognition’s Paired Associates Learning (PAL) task. To conduct the resting‐state functional MRI analyses, we used a seed‐based approach with the bilateral hippocampus as the seed region of interest. We then analyzed the hippocampal RSFC data to and assessed covariance of individual patterns of hippocampal RSFC with memory performance measured with the PAL task.ResultOur preliminary findings, largely consistent with previous work, demonstrate patterns of hippocampal RSFC sharing territory with the ventral and lateral portions of the default mode network (DMN). In addition, we observed evidence of regional covariance between hippocampal RSFC and PAL task performance.ConclusionThe preliminary findings of the ongoing PRANK study indicate that hippocampal RSFC covaries regionally with hippocampal‐dependent memory ability in periadolescent children. Future work from the PRANK study aims to understand whether genetic and polygenic risk factors for AD influence this hippocampal network development. To do so, we will utilize participants’ AD polygenic risk scores, and determine whether those scores are related to individual differences in hippocampal RSFC.

Brief intensive social gaze training reorganizes functional brain connectivity in boys with fragile X syndrome.

Boys with fragile X syndrome (FXS), the leading known genetic cause of autism spectrum disorder (ASD), demonstrate significant impairments in social gaze and associated weaknesses in communication, social interaction, and other areas of adaptive functioning. Little is known, however, concerning the impact of behavioral treatments for these behaviors on functional brain connectivity in this population. As part of a larger study, boys with FXS (mean age 13.23±2.31years) and comparison boys with ASD (mean age 12.15±2.76years) received resting-state functional magnetic resonance imaging scans prior to and following social gaze training administered by a trained behavior therapist in our laboratory. Network-agnostic connectome-based predictive modeling of pretreatment resting-state functional connectivity data revealed a set of positive (FXS > ASD) and negative (FXS < ASD) edges that differentiated the groups significantly and consistently across all folds of cross-validation. Following administration of the brief training, the FXS and ASD groups demonstrated reorganization of connectivity differences. The divergence in the spatial pattern of reorganization response, based on functional connectivity differences pretreatment, suggests a unique pattern of response to treatment in the FXS and ASD groups. These results provide further support for implementing targeted behavioral treatments to ameliorate syndrome-specific behavioral features in FXS.

Reliability and similarity of resting state functional connectivity networks imaged using wearable, high-density diffuse optical tomography in the home setting

BackgroundWhen characterizing the brain's resting state functional connectivity (RSFC) networks, demonstrating networks' similarity across sessions and reliability across different scan durations is essential for validating results and possibly minimizing the scanning time needed to obtain stable measures of RSFC. Recent advances in optical functional neuroimaging technologies have resulted in fully wearable devices that may serve as a complimentary tool to functional magnetic resonance imaging (fMRI) and allow for investigations of RSFC networks repeatedly and easily in non-traditional scanning environments. MethodsResting-state cortical hemodynamic activity was repeatedly measured in a single individual in the home environment during COVID-19 lockdown conditions using the first ever application of a 24-module (72 sources, 96 detectors) wearable high-density diffuse optical tomography (HD-DOT) system. Twelve-minute recordings of resting-state data were acquired over the pre-frontal and occipital regions in fourteen experimental sessions over three weeks. As an initial validation of the data, spatial independent component analysis was used to identify RSFC networks. Reliability and similarity scores were computed using metrics adapted from the fMRI literature. ResultsWe observed RSFC networks over visual regions (visual peripheral, visual central networks) and higher-order association regions (control, salience and default mode network), consistent with previous fMRI literature. High similarity was observed across testing sessions and across chromophores (oxygenated and deoxygenated haemoglobin, HbO and HbR) for all functional networks, and for each network considered separately. Stable reliability values (described here as a <10% change between time windows) were obtained for HbO and HbR with differences in required scanning time observed on a network-by-network basis. DiscussionUsing RSFC data from a highly sampled individual, the present work demonstrates that wearable HD-DOT can be used to obtain RSFC measurements with high similarity across imaging sessions and reliability across recording durations in the home environment. Wearable HD-DOT may serve as a complimentary tool to fMRI for studying RSFC networks outside of the traditional scanning environment and in vulnerable populations for whom fMRI is not feasible.

Simultaneous Detection and HER2 Profiling of Circulating Breast Cancer Cells in Clinical Patients Using a Rare Cell Sorter.

This study describes a rare cell sorter (RCS) method to detect circulating tumor cells (CTCs) and CTC clusters in whole blood without pretreatment. We collected samples from breast cancer patients at the University of Tsukuba Hospital. A total of 15 whole-blood specimens from patients with breast cancer were collected and analyzed via a microfluidics chip, fluorescence-conjugated antibody staining, and fluorescence microscopy. Of 15 total cases, eight were analyzed by RCS ver3 and seven were analyzed by RCS ver3.5 to reveal potential clinical differences in scanning methods. We then examined the HER2 status on 4 of the 15 patients using our RCS system. RCS efficiently detected all subtypes of CTCs and CTC clusters from the peripheral blood of cancer patients. The concordance rate of HER2 status between tissue and CTCs in 4 tested clinical samples was 100%. RCS is a non-invasive method that allows for simultaneous detection of CTCs, cluster presence, and surface marker (e.g., HER2) status. Frequent sampling is, thus, possible and the large amount of data obtained will be clinically useful to predict response to therapy as well as plan adjunct support therapies in cancer patients.

Structural-functional connectivity bandwidth of the human brain

BackgroundThe human brain is a complex network that seamlessly manifests behaviour and cognition. This network comprises neurons that directly, or indirectly mediate communication between brain regions. Here, we show how multilayer/multiplex network analysis provides a suitable framework to uncover the throughput of structural connectivity (SC) to mediate information transfer—giving rise to functional connectivity (FC). MethodWe implemented a novel method to reconcile SC and FC using diffusion and resting-state functional MRI connectivity data from 484 subjects (272 females, 212 males; age = 29.15 ± 3.47) from the Human Connectome Project. First, we counted the number of direct and indirect structural paths that mediate FC. FC nodes with indirect SC paths were then weighted according to their least restrictive SC path. We refer to this as SC-FC Bandwidth. We then mapped paths with the highest SC-FC Bandwidth across 7 canonical resting-state networks. FindingsWe found that most pairs of FC nodes were connected by SC paths of length two and three (SC paths of length >5 were virtually non-existent). Direct SC-FC connections accounted for only 10% of all SC-FC connections. The majority of FC nodes without a direct SC path were mediated by a proportion of two (44%) or three SC path lengths (39%). Only a small proportion of FC nodes were mediated by SC path lengths of four (5%). We found high-bandwidth direct SC-FC connections show dense intra- and sparse inter-network connectivity, with a bilateral, anteroposterior distribution. High bandwidth SC-FC triangles have a right superomedial distribution within the somatomotor network. High-bandwidth SC-FC quads have a superoposterior distribution within the default mode network. ConclusionOur method allows the measurement of indirect SC-FC using undirected, weighted graphs derived from multimodal MRI data in order to map the location and throughput of SC to mediate FC. An extension of this work may be to explore how SC-FC Bandwidth changes over time, relates to cognition/behavior, and if this measure reflects a marker of neurological injury or psychiatric disorders.

Associations Between Early-Life Stress Exposure and Internalizing Symptomatology During the COVID-19 Pandemic: Assessing the Role of Neurobehavioral Mediators

BackgroundThe ongoing COVID-19 pandemic is a major stressor that has been associated with increased risk for psychiatric illness in the general population. Recent work has highlighted that experiences of early-life stress (ELS) may impact individuals’ psychological functioning and vulnerability for developing internalizing psychopathology in response to pandemic-related stress. However, little is known about the neurobehavioral factors that may mediate the association between ELS exposure and COVID-related internalizing symptomatology. The current study sought to examine the mediating roles of pre-pandemic resting-state frontoamygdala connectivity and concurrent emotion regulation (ER) in the association between ELS and pandemic-related internalizing symptomatology. MethodsRetrospective life-stress histories, concurrent self-reported ER strategies (i.e., reappraisal and suppression), concurrent self-reported internalizing symptomatology (i.e., depression- and anxiety-related symptomatology), and resting-state functional connectivity data from a sample of adults (N = 64, mean age = 22.12 years, female = 68.75%) were utilized. ResultsThere were no significant direct associations between ELS and COVID-related internalizing symptomatology. Neither frontoamygdala functional connectivity nor ER strategy use mediated an association between ELS and COVID-related internalizing symptomatology (ps > .05). Exploratory analyses identified a significant moderating effect of reappraisal use on the association between ELS and internalizing symptomatology (β = −0.818, p = .047), such that increased reappraisal use buffered the impact of ELS on psychopathology. ConclusionsWhile frontoamygdala connectivity and ER do not appear to mediate the association between ELS and COVID-related internalizing symptomatology, our findings suggest that the use of reappraisal may buffer against the effect of ELS on mental health during the pandemic.

Multi-Site Mild Traumatic Brain Injury Classification with Machine Learning and Harmonization.

Traumatic brain injury (TBI) can drastically affect an individual's cognition, physical, emotional wellbeing, and behavior. Even patients with mild TBI (mTBI) may suffer from a variety of long-lasting symptoms, which motivates researchers to find better biomarkers. Machine learning algorithms have shown promising results in detecting mTBI from resting-state functional network connectivity (rsFNC) data. However, data collected at multiple sites introduces additional noise called site-effects, resulting in erroneous conclusions. Site errors are controlled through a process called harmonization, but its use in classifying neuroimaging data has been addressed lightly. With the ongoing need to improve mTBI detection, this study shows that harmonization should be integrated into the machine learning process when working with multi-site neuroimaging datasets.

Misconfigured striatal connectivity profiles in smokers

Dysregulation of frontal cortical inputs to the striatum is foundational in the neural basis of substance use disorder (SUD). Neuroanatomical and electrophysiological data increasingly show that striatal nodes receive appreciable input from numerous cortical areas, and that the combinational properties of these multivariate “connectivity profiles” play a predominant role in shaping striatal activity and function. Yet, how abnormal configuration of striatal connectivity profiles might contribute to SUD is unknown. Here, we implemented a novel “connectivity profile analysis” (CPA) approach using resting-state functional connectivity data to facilitate detection of different types of connectivity profile “misconfiguration” that may reflect distinct forms of aberrant circuit plasticity in SUD. We examined 46 nicotine-dependent smokers and 33 non-smokers and showed that both dorsal striatum (DS) and ventral striatum (VS) connectivity profiles with frontal cortex were misconfigured in smokers—but in doubly distinct fashions. DS misconfigurations were stable across sated and acute abstinent states (indicative of a “trait” circuit adaptation) whereas VS misconfigurations emerged only during acute abstinence (indicative of a “state” circuit adaptation). Moreover, DS misconfigurations involved abnormal connection strength rank order arrangement, whereas VS misconfigurations involved abnormal aggregate strength. We found that caudal ventral putamen in smokers uniquely displayed multiple types of connectivity profile misconfiguration, whose interactive magnitude was linked to dependence severity, and that VS misconfiguration magnitude correlated positively with withdrawal severity during acute abstinence. Findings underscore the potential for approaches that more aptly model the neurobiological composition of corticostriatal circuits to yield deeper insights into the neural basis of SUD.

Structural-functional connectivity mapping of the insular cortex: a combined data-driven and meta-analytic topic mapping.

In this study, we examined structural and functional profiles of the insular cortex and mapped associations with well-described functional networks throughout the brain using diffusion tensor imaging (DTI) and resting-state functional connectivity (RSFC) data. We used a data-driven method to independently estimate the structural-functional connectivity of the insular cortex. Data were obtained from the Human Connectome Project comprising 108 adult participants. Overall, we observed moderate to high associations between the structural and functional mapping scores of 3 different insular subregions: the posterior insula (associated with the sensorimotor network: RSFC, DTI = 50% and 72%, respectively), dorsal anterior insula (associated with ventral attention: RSFC, DTI = 83% and 83%, respectively), and ventral anterior insula (associated with the frontoparietal: RSFC, DTI = 42% and 89%, respectively). Further analyses utilized meta-analytic decoding maps to demonstrate specific cognitive and affective as well as gene expression profiles of the 3 subregions reflecting the core properties of the insular cortex. In summary, given the central role of the insular in the human brain, our results revealing correspondence between DTI and RSFC mappings provide a complementary approach and insight for clinical researchers to identify dysfunctional brain organization in various neurological disorders associated with insular pathology.

Functional connectome of human cerebellum

Background Neural connectome theory has been widely used in system neuroscience, and prompted our comprehension for the topological organizations of human cerebral cortex. However, how functional connectome is organized topologically in cerebellums remains unclear.Method Resting-state functional connectivity (rs-fcMRI) data were acquired from 1416 healthy adults in two independent samples. In Sample 1 (n = 976), both voxel-wise and node-wise topological properties for functional cerebellar connectome were estimated. Moreover, the network-based topological properties of cerebellum and cerebro-cerebellar topological mapping were investigated, respectively. Given the temporal natures in the neural population, a hidden Markov model (HMM) was further capitalized to uncover the dynamic pattern of cerebellar functional connectome. In order to test the robustness of our findings, we ran all of the analyses in an independent dataset (Sample 2; n = 440).Results We found that Crus I and II exhibited prominently high degree centrality (DC) for cerebellar functional connectome. Further, the cerebellar functional connectome and even the nested network-wise cerebellar connectome was found to be organized by small-world, modular and hierarchical manners significantly. Also, three intrinsic modules were found in cerebellar functional connectome, including attention/executive network, default mode network and task-positive network. In addition, the significant cerebro-cerebellar correlations for small-world organization and hierarchical architecture were found as well. By building cerebro-cerebellar topological mapping, both frontoparietal and subcortical networks were found to be overrepresented into cerebellums than cerebral cortex (3-fold). As for temporal natures, cerebellar functional connectome was observed to be highly flexible and modular, but showed high individual-specific variances in temporal dynamic pattern.Conclusion This study identified the topological architectures and temporal hierarchy of functional cerebellar connectome, and further demonstrated prominent functional cerebro-cerebellar couplings of small-world organization and hierarchical architectures.

Multimodal Neural and Behavioral Data Predict Response to Rehabilitation in Chronic Poststroke Aphasia.

Background:Poststroke recovery depends on multiple factors and varies greatly across individuals. Using machine learning models, this study investigated the independent and complementary prognostic role of different patient-related factors in predicting response to language rehabilitation after a stroke.Methods:Fifty-five individuals with chronic poststroke aphasia underwent a battery of standardized assessments and structural and functional magnetic resonance imaging scans, and received 12 weeks of language treatment. Support vector machine and random forest models were constructed to predict responsiveness to treatment using pretreatment behavioral, demographic, and structural and functional neuroimaging data.Results:The best prediction performance was achieved by a support vector machine model trained on aphasia severity, demographics, measures of anatomic integrity and resting-state functional connectivity (F1=0.94). This model resulted in a significantly superior prediction performance compared with support vector machine models trained on all feature sets (F1=0.82, P<0.001) or a single feature set (F1 range=0.68–0.84, P<0.001). Across random forest models, training on resting-state functional magnetic resonance imaging connectivity data yielded the best F1 score (F1=0.87).Conclusions:While behavioral, multimodal neuroimaging data and demographic information carry complementary information in predicting response to rehabilitation in chronic poststroke aphasia, functional connectivity of the brain at rest after stroke is a particularly important predictor of responsiveness to treatment, both alone and combined with other patient-related factors.

Threat imminence reveals links among unfolding of anticipatory physiological response, cortical-subcortical intrinsic functional connectivity, and anxiety

Excessive expression of fear responses in anticipation of threat occurs in anxiety, but understanding of underlying pathophysiological mechanisms is limited. Animal research indicates that threat-anticipatory defensive responses are dynamically organized by threat imminence and rely on conserved circuitry. Insight from basic neuroscience research in animals on threat imminence could guide mechanistic research in humans mapping abnormal function in this circuitry to aberrant defensive responses in pathological anxiety.50 pediatric anxiety patients and healthy-comparisons (33 females) completed an instructed threat-anticipation task whereby cues signaled delivery of painful (threat) or non-painful (safety) thermal stimulation. Temporal changes in skin-conductance indexed anxiety effects on anticipatory responding as function of threat imminence. Multivariate network analyses of resting-state functional connectivity data from a subsample were used to identify intrinsic-function correlates of anticipatory-response dynamics, within a specific, distributed network derived from translational research on defensive responding.By considering threat imminence, analyses revealed specific anxiety effects. Importantly, pathological anxiety was associated with excessive deployment of anticipatory physiological response as threat, but not safety, outcomes became more imminent. Magnitude of increase in threat-anticipatory physiological responses corresponded with magnitude of intrinsic connectivity within a cortical-subcortical circuit. Moreover, more severe anxiety was associated with stronger associations between anticipatory physiological responding and connectivity that ventromedial prefrontal cortex showed with hippocampus and basolateral amygdala, regions implicated in animal models of anxiety.These findings link basic and clinical research, highlighting variations in intrinsic function in conserved defensive circuitry as a potential pathophysiological mechanism in anxiety.

Measuring the developmental relationship between memory ability and organization of a functional brain network vulnerable to Alzheimer’s disease: Preliminary findings from the PRANK study

AbstractBackgroundThe hallmark memory impairments of typically presenting Alzheimer’s disease (AD) are associated with pathological changes of the hippocampus. While it is known that the hippocampus is necessary for normal relational memory performance, the development of functional brain networks associated with the hippocampus is not well characterized, particularly in the periadolescent epoch. The development of the hippocampus and its associated functional brain network may be influenced by genetic, environmental, or other risk factors for AD, potentially creating vulnerabilities to AD in later life. This project explores the neurodevelopment of this hippocampal network to determine how individual differences in functional connectivity impact relational memory abilities during the periadolescent epoch. Here, we utilized preliminary data from the NIA‐funded Polygenic Risk of Alzheimer’s Disease in Nebraska Kids (PRANK) study, which aims to improve insight regarding how brain and cognitive development is affected by polygenic risk for Alzheimer’s disease. Our continuing study is recruiting healthy periadolescent individuals (8‐13 years of age). Here we report preliminary cross‐sectional findings from the PRANK study exploring how individual differences in hippocampal resting‐state functional connectivity (RSFC) covary with declarative/relational memory ability.MethodAnalyses were conducted on preliminary data from healthy periadolescent participants (n=40). Declarative/relational memory performance was measured with Cambridge Cognition’s Paired Associates Learning (PAL) task. Resting‐state functional MRI data was analyzed using a seed‐based approach with the bilateral hippocampus as the seed region of interest. RSFC data were analyzed to determine their covariance with relational memory ability (operationalized as PAL performance).ResultOur analysis revealed patterns of hippocampal RSFC that were broadly consistent with prior work, sharing the territory of the default mode network (DMN). We also observed regional covariance between hippocampal RSFC and performance on the PAL task.ConclusionThe present work describes preliminary findings of the ongoing PRANK study. Our preliminary observations are consistent with the perspective that hippocampal RSFC covaries with hippocampal‐dependent declarative/relation memory ability among periadolescent children. To understand whether this hippocampal network development is susceptible to genetic risk factors for AD, future work from the PRANK study will utilize participants’ AD polygenic risk scores to determine whether those scores are related to individual differences of hippocampal RSFC.

Altered dorsal functional connectivity after post-weaning social isolation and resocialization in mice

BackgroundSocial isolation (SI) leads to various mental health disorders. Despite abundant studies on behavioral and neurobiological changes induced by post-weaning SI, the characterization of its imaging correlates, such as resting-state functional connectivity (RSFC), is critically lacking. In addition, the effects of resocialization after isolation remain unclear. Therefore, this study aimed to explore the effects of 1) SI on cortical functional connectivity and 2) subsequent resocialization on behavior and functional connectivity. MethodsBehavioral tests were conducted to validate the post-weaning SI mouse model, which is isolated during the juvenile period. Wide-field optical mapping was performed to observe both neuronal and hemodynamic signals in the cortex under anesthesia. Using seed-based and graph theoretical analyses, RSFC was analyzed. SI mice were then resocialized and the array of behavior and imaging tests was conducted. ResultsBehaviorally, SI mice showed elevated anxiety, social preference, and aggression. RSFC analyses using the seed-based approach revealed decreased cortical functional connectivity in SI mice, especially in the frontal region. Graph network analyses demonstrated significant reduction in network segregation measures. After resocialization, mice exhibited recovered anxiogenic and aggressive behavior, but RSFC data did not show significant changes. ConclusionsWe observed an overall decrease in functional connectivity in SI mice. Moreover, resocialization restored the disruptions in behavioral patterns but functional connectivity was not recovered. To our knowledge, this is the first study to report that, despite the recovering tendencies of behavior in resocialized mice, similar changes in RSFC were not observed. This suggests that disruptions in functional connectivity caused by social isolation remain as long-term sequelae.

Structure and Dynamics of Large-Scale Cognitive Networks in Huntington's Disease.

Huntington's disease is a neurodegenerative disorder characterized by clinical alterations in the motor, behavioral, and cognitive domains. However, the structure and disruptions to large-scale brain cognitive networks have not yet been established. We aimed to profile changes in large-scale cognitive networks in premanifest and symptomatic patients with Huntington's disease. We prospectively recruited premanifest and symptomatic Huntington's disease mutation carriers as well as healthy controls. Clinical and sociodemographic data were obtained from all participants, and resting-state functional connectivity data, using both time-averaged and dynamic functional connectivity, was acquired from whole-brain and cognitively oriented brain parcellations. A total of 64 gene mutation carriers and 23 healthy controls were included; 21 patients with Huntington's disease were classified as premanifest and 43 as symptomatic Huntington's disease. Compared with healthy controls, patients with Huntington's disease showed decreased network connectivity within the posterior hubs of the default-mode network and the medial prefrontal cortex, changes that correlated with cognitive (t=2.25, P=0.01) and disease burden scores (t=-2.42, P=0.009). The salience network showed decreased functional connectivity between insular and supramarginal cortices and also correlated with cognitive (t=2.11, P=0.02) and disease burden scores (t=-2.35, P=0.01). Dynamic analyses showed that network variability was decreased for default-central executive networks, a feature already present in premanifest mutation carriers (dynamic factor 8, P=0.02). Huntington's disease shows an early and widespread disruption of large-scale cognitive networks. Importantly, these changes are related to cognitive and disease burden scores, and novel dynamic functional analyses uncovered subtler network changes even in the premanifest stages.

Parental Education and Functional Connectivity between Nucleus Accumbens (NAcc) and Frontoparietal Network (FPN)

Introduction: While previous studies have indicated an association between socioeconomic status (SES) and children’s neuroimaging measures, weaker SES effects are shown for Black than White families. This is, in part, due to processes such as stratification, racism, marginalization, and othering of Black people in the US, which act as barriers to translating SES resources into health outcomes. Purpose: This study had two aims: First, to test the association between parental education and the nucleus accumbens (NAcc) resting-state functional connectivity (rsFC) with the frontoparietal network (FPN) in children; and second, to investigate racial heterogeneity in this association. Methods: This cross-sectional study used data from the Adolescent Brain Cognitive Development (ABCD) study. We analyzed the resting-state functional connectivity data of 7959 US pre-adolescents who were between 9 and 10 years old. The main outcome was the NAcc resting-state functional connectivity with FPN. Parental education was considered as an independent variable. Family structure, sex and age were the study covariates. Finally, race was regarded as the moderator. We used mixed-effects regression for data analysis with and without interaction terms between parental education and race. Results: Parental education was associated with higher NAcc resting-state functional connectivity with FPN. Race showed a statistically significant interaction with parental education, suggesting that the effects of parental education on NAcc rsFC with FPN was significantly weaker for Black pre-adolescents compared to White pre-adolescents. Conclusions: In line with Minorities’ Diminished Returns (MDRs), the association between parental education and pre-adolescents’ NAcc rsFC with FPN is weaker in Black pre-adolescents compared to their White counterparts. This finding is of interest because FPN’s rsFC with NAcc may have a role in cognitive flexibility and reward processing. The weaker links between SES indicators and children’s neuroimaging findings for Black than for White families may reflect the racialization of Blacks in the US. Social stratification, racism, and discrimination may minimize the returns of SES in Black communities.

Nucleus Accumbens Functional Connectivity with the Default Mode Network: Black Children’s Diminished Returns of Household Income

Introduction: Although research has established a link between socioeconomic status (SES) and neuroimaging measures, weaker SES effects are shown for Blacks than Whites. This is, in part, due to processes such as stratification, racism, mineralization, and othering of Black people in the US. Purpose: This study had two aims: First to test the association between household income and the nucleus accumbens (NAcc) resting-state functional connectivity with the Default Mode Network (DMN) in children, and second, to investigate racial heterogeneity in this association. Methods: This cross-sectional study used data from the Adolescent Brain Cognitive Development (ABCD) study. We analyzed the resting-state functional connectivity data using Magnetic Resonance Imaging (rsfMRI) of 7903 US pre-adolescents who were between ages 9 and 10 years old. The main outcome was the NAcc resting-state functional connectivity with DMN. The independent variable was household income. Age, sex, and family structure were the study covariates. Race was the moderator. Mixed-effects regression models were used for data analysis with and without interaction terms between household income and race. Results: Higher household income was associated with higher NAcc resting-state functional connectivity with DMN. Race showed a statistically significant interaction with household income suggesting that the NAcc resting-state functional connectivity with DMN was significantly weaker for Black compared to White pre-adolescents. Conclusions: In line with Minorities’ Diminished Returns (MDRs), the association between household income and pre-adolescents NAcc resting-state functional connectivity with DMN is weaker in Black than in White children. This result is of interest because DMN’s functional connectivity with NAcc may have a role in cognitive flexibility and reward processing. The weaker links between SES indicators and neuroimaging findings for Blacks than for Whites may reflect the racialization of Black people in the US. Social stratification, racism, and discrimination may minimize the returns of SES for Black families, who have been oppressed for centuries.

The utility of maraviroc, an antiretroviral agent used to treat HIV, as treatment for opioid abuse? Data from MRI and behavioural testing in rats.

Background:Maraviroc is an antiretroviral agent and C-C chemokine coreceptor 5 (CCR5) antagonist that is currently used to treat human immunodeficiency virus. CCR5/μ-opioid receptor heterodimerization suggests that maraviroc could be a treatment for oxycodone abuse. We treated rats with maraviroc to explore its effect on oxycodone-seeking and its interference with the analgesic effects of oxycodone. We used resting-state blood-oxygen-level-dependent functional connectivity to assess the effect of maraviroc on oxycodone-enhanced coupling in the reward circuitry and performed behavioural tests to evaluate the effect of maraviroc on oxycodone rewarding properties and on oxycodone-seeking after prolonged abstinence.Methods:Two groups of rats were exposed to 8 consecutive days of oxycodone-conditioned place preference training and treatment with maraviroc or vehicle. Two additional groups were trained to self-administer oxycodone for 10 days and then tested for drug seeking after 14 days of abstinence with or without daily maraviroc treatment. We tested the effects of maraviroc on oxycodone analgesia using a tail-flick assay. We analyzed resting-state functional connectivity data using a rat 3-dimensional MRI atlas of 171 brain areas.Results:Maraviroc significantly decreased conditioned place preference and attenuated oxycodone-seeking behaviour after prolonged abstinence. The analgesic effect of oxycodone was maintained after maraviroc treatment. Oxycodone increased functional coupling with the accumbens, ventral pallidum and olfactory tubercles, but this was reduced with maraviroc treatment.Limitations:All experiments were performed in male rats only.Conclusion:Maraviroc treatment attenuated oxycodone-seeking in abstinent rats and reduced functional coupling in the reward circuitry. The analgesic effects of oxycodone were not affected by maraviroc.

Oxytocin, PTSD, and sexual abuse are associated with attention network intrinsic functional connectivity

Childhood maltreatment is linked to Posttraumatic Stress Disorder (PTSD) in adulthood. Neural attention network function contributes to resilience against PTSD following maltreatment; oxytocin administration alters functional connectivity differentially among resilient to PTSD groups. The present study examined intrinsic connectivity between ventral and dorsal neural attention networks (VAN and DAN) to clarify the nature of dysfunction versus resilience in the context of maltreatment-related PTSD, and to explore differential dysfunction related to varied aspects of maltreatment. Oxytocin administration was examined as a factor in these relationships. Resting-state functional connectivity data were collected from 39 adults with maltreatment histories, with and without PTSD, who were randomly assigned to receive oxytocin or placebo. We found that PTSD and sexual abuse (SA) were associated with reduced VAN-DAN connectivity. There were no significant effects with regard to physical abuse. Oxytocin was associated with greater VAN-DAN connectivity strength. These preliminary findings suggest dysfunction within attentional systems in PTSD, as well as following SA. Further, oxytocin may help ameliorate attentional neurocircuitry dysfunction in individuals with PTSD and those with maltreatment histories.

Multivariate Machine Learning Analyses in Identification of Major Depressive Disorder Using Resting-State Functional Connectivity: A Multicentral Study.

Diagnosis of major depressive disorder (MDD) using resting-state functional connectivity (rs-FC) data faces many challenges, such as the high dimensionality, small samples, and individual difference. To assess the clinical value of rs-FC in MDD and identify the potential rs-FC machine learning (ML) model for the individualized diagnosis of MDD, based on the rs-FC data, a progressive three-step ML analysis was performed, including six different ML algorithms and two dimension reduction methods, to investigate the classification performance of ML model in a multicentral, large sample dataset [1021 MDD patients and 1100 normal controls (NCs)]. Furthermore, the linear least-squares fitted regression model was used to assess the relationships between rs-FC features and the severity of clinical symptoms in MDD patients. Among used ML methods, the rs-FC model constructed by the eXtreme Gradient Boosting (XGBoost) method showed the optimal classification performance for distinguishing MDD patients from NCs at the individual level (accuracy = 0.728, sensitivity = 0.720, specificity = 0.739, area under the curve = 0.831). Meanwhile, identified rs-FCs by the XGBoost model were primarily distributed within and between the default mode network, limbic network, and visual network. More importantly, the 17 item individual Hamilton Depression Scale scores of MDD patients can be accurately predicted using rs-FC features identified by the XGBoost model (adjusted R2 = 0.180, root mean squared error = 0.946). The XGBoost model using rs-FCs showed the optimal classification performance between MDD patients and HCs, with the good generalization and neuroscientifical interpretability.