Cerebellar Dentate Connectivity across Adulthood: A Large-Scale Resting State Functional Connectivity Investigation.
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ABSTRACT:
SUBMITTER: Bernard JA
PROVIDER: S-EPMC8436571 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundCannabis use has been associated with abnormalities in cerebellar mediated motor and non-motor (i.e. cognition and personality) phenomena. Since the cerebellum is a region with high cannabinoid type 1 receptor density, these impairments may reflect alterations of signaling between the cerebellum and other brain regions.AimsWe hypothesized that cerebellar-cortical resting-state functional connectivity (rsFC) would be altered in cannabis users, relative to their non-using peers. It was also hypothesized that differences in rsFC would be associated with cannabis use features, such as age of initiation and lifetime use.MethodsCerebellar-cortical and subcortical rsFCs were computed between 28 cerebellar lobules, defined by a spatially unbiased atlas template of the cerebellum, and individual voxels in the cerebral regions, in 41 regular cannabis users (20 female) and healthy non-using peers (N = 31; 18 female). We also investigated associations between rsFC and cannabis use features (e.g. lifetime cannabis use and age of initiation).ResultsCannabis users demonstrated hyperconnectivity between the anterior cerebellar regions (i.e. lobule I-IV) with the posterior cingulate cortex, and hypoconnectivity between the rest of the cerebellum (i.e. Crus I and II, lobule VIIb, VIIIa, VIIIb, IX, and X) and the cortex. No associations were observed between features of cannabis use and rsFC.ConclusionsCannabis use was associated with altered patterns of rsFC from the cerebellum to the cerebral cortex which may have a downstream impact on behavior and cognition.
| S-EPMC8813046 | biostudies-literature
Project description:ObjectiveTo investigate in a cross-sectional study the contributions of altered cerebellar resting-state functional connectivity (FC) to cognitive impairment in Parkinson disease (PD).MethodsWe conducted morphometric and resting-state FC-MRI analyses contrasting 81 participants with PD and 43 age-matched healthy controls using rigorous quality assurance measures. To investigate the relationship of cerebellar FC to cognitive status, we compared participants with PD without cognitive impairment (Clinical Dementia Rating [CDR] scale score 0, n = 47) to participants with PD with impaired cognition (CDR score ≥0.5, n = 34). Comprehensive measures of cognition across the 5 cognitive domains were assessed for behavioral correlations.ResultsThe participants with PD had significantly weaker FC between the vermis and peristriate visual association cortex compared to controls, and the strength of this FC correlated with visuospatial function and global cognition. In contrast, weaker FC between the vermis and dorsolateral prefrontal cortex was found in the cognitively impaired PD group compared to participants with PD without cognitive impairment. This effect correlated with deficits in attention, executive functions, and global cognition. No group differences in cerebellar lobular volumes or regional cortical thickness of the significant cortical clusters were observed.ConclusionThese results demonstrate a correlation between cerebellar vermal FC and cognitive impairment in PD. The absence of significant atrophy in cerebellum or relevant cortical areas suggests that this could be related to local pathophysiology such as neurotransmitter dysfunction.
| S-EPMC7079688 | biostudies-literature
Project description:Connectivity of the prefrontal cortex (PFC) matures through adolescence, coinciding with emergence of adult executive function and top-down inhibitory control over behavior. Alcohol exposure during this critical period of brain maturation may affect development of PFC and frontolimbic connectivity. Adult rats exposed to adolescent intermittent ethanol (AIE; 5 g/kg ethanol, 25 percent v/v in water, intragastrically, 2-day-on, 2-day-off, postnatal day 25-54) or water control underwent resting-state functional MRI to test the hypothesis that AIE induces persistent changes in frontolimbic functional connectivity under baseline and acute alcohol conditions (2 g/kg ethanol or saline, intraperitoneally administered during scanning). Data were acquired on a Bruker 9.4-T MR scanner with rats under dexmedetomidine sedation in combination with isoflurane. Frontolimbic network regions-of-interest for data analysis included PFC [prelimbic (PrL), infralimbic (IL), and orbitofrontal cortex (OFC) portions], nucleus accumbens (NAc), caudate putamen (CPu), dorsal hippocampus, ventral tegmental area, amygdala, and somatosensory forelimb used as a control region. AIE decreased baseline resting-state connectivity between PFC subregions (PrL-IL and IL-OFC) and between PFC-striatal regions (PrL-NAc, IL-CPu, IL-NAc, OFC-CPu, and OFC-NAc). Acute ethanol induced negative blood-oxygen-level-dependent changes within all regions of interest examined, along with significant increases in functional connectivity in control, but not AIE animals. Together, these data support the hypothesis that binge-like adolescent alcohol exposure causes persistent decreases in baseline frontolimbic (particularly frontostriatal) connectivity and alters sensitivity to acute ethanol-induced increases in functional connectivity in adulthood.
| S-EPMC5760482 | biostudies-literature
Project description:ImportanceMajor depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive.ObjectiveTo investigate network dysfunction in MDD through a meta-analysis of rsFC studies.Data sourcesSeed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data.Study selectionTwenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis.Data extraction and synthesisCoordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network.ResultsMajor depressive disorder was characterized by hypoconnectivity within the frontoparietal network, a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network involved in attending to the external environment. Major depressive disorder was also associated with hyperconnectivity within the default network, a network believed to support internally oriented and self-referential thought, and hyperconnectivity between frontoparietal control systems and regions of the default network. Finally, the MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions.Conclusions and relevanceReduced connectivity within frontoparietal control systems and imbalanced connectivity between control systems and networks involved in internal or external attention may reflect depressive biases toward internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression.
| S-EPMC4456260 | biostudies-literature
Project description:Schizophrenia is a complex mental disorder with disorganized communication among large-scale brain networks, as demonstrated by impaired resting-state functional connectivity (rsFC). Individual rsFC studies, however, vary greatly in their methods and findings. We searched for consistent patterns of network dysfunction in schizophrenia by using a coordinate-based meta-analysis. Fifty-six seed-based voxel-wise rsFC datasets from 52 publications (2115 patients and 2297 healthy controls) were included in this meta-analysis. Then, coordinates of seed regions of interest (ROI) and between-group effects were extracted and coded. Seed ROIs were categorized into seed networks by their location within an a priori template. Multilevel kernel density analysis was used to identify brain networks in which schizophrenia was linked to hyper-connectivity or hypo-connectivity with each a priori network. Our results showed that schizophrenia was characterized by hypo-connectivity within the default network (DN, self-related thought), affective network (AN, emotion processing), ventral attention network (VAN, processing of salience), thalamus network (TN, gating information) and somatosensory network (SS, involved in sensory and auditory perception). Additionally, hypo-connectivity between the VAN and TN, VAN and DN, VAN and frontoparietal network (FN, external goal-directed regulation), FN and TN, and FN and DN were found in schizophrenia. Finally, the only instance of hyper-connectivity in schizophrenia was observed between the AN and VAN. Our meta-analysis motivates an empirical foundation for a disconnected large-scale brain networks model of schizophrenia in which the salience processing network (VAN) plays the core role, and its imbalanced communication with other functional networks may underlie the core difficulty of patients to differentiate self-representation (inner world) and environmental salience processing (outside world).
| S-EPMC5767956 | biostudies-literature
Project description:It is well established that it is possible to observe spontaneous, highly structured, fluctuations in human brain activity from functional magnetic resonance imaging (fMRI) when the subject is 'at rest'. However, characterising this activity in an interpretable manner is still a very open problem. In this paper, we introduce a method for identifying modes of coherent activity from resting state fMRI (rfMRI) data. Our model characterises a mode as the outer product of a spatial map and a time course, constrained by the nature of both the between-subject variation and the effect of the haemodynamic response function. This is presented as a probabilistic generative model within a variational framework that allows Bayesian inference, even on voxelwise rfMRI data. Furthermore, using this approach it becomes possible to infer distinct extended modes that are correlated with each other in space and time, a property which we believe is neuroscientifically desirable. We assess the performance of our model on both simulated data and high quality rfMRI data from the Human Connectome Project, and contrast its properties with those of both spatial and temporal independent component analysis (ICA). We show that our method is able to stably infer sets of modes with complex spatio-temporal interactions and spatial differences between subjects.
| S-EPMC4349633 | biostudies-literature
Project description:Delineation of large-scale functional networks (FNs) from resting state functional MRI data has become a standard tool to explore the functional brain organization in neuroscience. However, existing methods sacrifice subject specific variation in order to maintain the across-subject correspondence necessary for group-level analyses. In order to obtain subject specific FNs that are comparable across subjects, existing brain decomposition techniques typically adopt heuristic strategies or assume a specific statistical distribution for the FNs across subjects, and therefore might yield biased results. Here we present a novel data-driven method for detecting subject specific FNs while establishing group level correspondence. Our method simultaneously computes subject specific FNs for a group of subjects regularized by group sparsity, to generate subject specific FNs that are spatially sparse and share common spatial patterns across subjects. Our method is built upon non-negative matrix decomposition techniques, enhanced by a data locality regularization term that makes the decomposition robust to imaging noise and improves spatial smoothness and functional coherences of the subject specific FNs. Our method also adopts automatic relevance determination techniques to eliminate redundant FNs in order to generate a compact set of informative sparse FNs. We have validated our method based on simulated, task fMRI, and resting state fMRI datasets. The experimental results have demonstrated our method could obtain subject specific, sparse, non-negative FNs with improved functional coherence, providing enhanced ability for characterizing the functional brain of individual subjects.
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Project description:Background: Although abnormality of cerebellar-cerebral functional connectivity at rest in obsessive-compulsive disorder (OCD) has been hypothesized, only a few studies have investigated the neural mechanism. To verify the findings of previous studies, a large sample of patients with OCD was studied because OCD shows possible heterogeneity. Methods: Forty-seven medication-free patients with OCD and 62 healthy controls (HCs) underwent resting-state functional magnetic imaging scans. Seed-based connectivity was examined to investigate differences in cerebellar-cerebral functional connectivity in OCD patients compared with HCs. Correlations between functional connectivity and the severity of obsessive-compulsive symptoms were analyzed. Results: In OCD, we found significantly increased functional connectivity between the right lobule VI and the left precuneus, which is a component of the default mode network (DMN), compared to HCs. However, there was no correlation between the connectivity of the right lobule VI-left precuneus and obsessive-compulsive severity. Conclusions: These findings suggest that altered functional connectivity between the cerebellum and DMN might cause changes in intrinsic large-scale brain networks related to the traits of OCD.
| S-EPMC8102723 | biostudies-literature
Project description:BackgroundThe cerebellum plays important roles in sensori-motor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available.MethodsWe used resting-state functional connectivity magnetic resonance imaging in 56 children and adolescents (28 subjects with ASD, 28 typically developing subjects) 8-17 years old. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensori-motor (premotor/primary motor, somatosensory, superior temporal, and occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal).ResultsThere were three main findings: 1) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; 2) partial correlation analyses that emphasized domain specificity (sensori-motor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared with the typically developing group) for sensori-motor ROIs but predominantly reduced connectivity for supramodal ROIs; and 3) this atypical pattern of connectivity was supported by significantly increased noncanonical connections (between sensori-motor cerebral and supramodal cerebellar ROIs and vice versa) in the ASD group.ConclusionsOur findings indicate that sensori-motor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition.
| S-EPMC5708535 | biostudies-literature
Project description:Posttraumatic stress disorder (PTSD) is a psychiatric condition that can emerge after exposure to an exceedingly traumatic event. Previous neuroimaging studies have indicated that PTSD is characterized by aberrant resting-state functional connectivity (FC). However, few existing studies on PTSD have examined dynamic changes in resting-state FC related to network formation, interaction, and dissolution over time. In this study, we compared the dynamic resting-state local and large-scale FC between PTSD patients (n = 22) and healthy controls (HC; n = 22; conducted as standard deviation in resting-state local and large-scale FC over a series of sliding windows). Local dynamic FC was examined by calculating the dynamic regional homogeneity (dReHo), and large-scale dynamic FC (dFC) was investigated between regions with significant dReHo group differences. For the PTSD patients, we also investigated the relationship between symptom severity and dFC/dReHo. Our results showed that PTSD patients were characterized by I) increased dynamic (more variable) dReHo in left precuneus (PCu); II) increased dynamic (more variable) dFC between the left PCu and left insula; and III) decreased dFC between left PCu and left inferior parietal lobe (IPL), and decreased dFC between left PCu and right PCu. However, there is no significant correlation between the clinical indicators and dReHo/dFC after the family-wise-error (FWE) correction. These findings provided the initial evidence that PTSD is characterized by aberrant patterns of fluctuating communication within brain system such as the default mode network (DMN) and among different brain systems such as the salience network and the DMN.
| S-EPMC6474202 | biostudies-literature