Potential Locations for Non-Invasive Brain Stimulation in Treating Schizophrenia: A Resting-State Functional Connectivity Analysis.
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ABSTRACT:
SUBMITTER: Ning Y
PROVIDER: S-EPMC8715096 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Objectives:Noninvasive brain stimulation (NIBS) is an emerging tool for treating autism spectrum disorder (ASD). Exploring new stimulation targets may improve the efficacy of NIBS for ASD. Materials and Methods:We first conducted a meta-analysis on 170 functional magnetic resonance imaging studies to identify ASD-associated brain regions. We then performed resting state functional connectivity analysis on 70 individuals with ASD to investigate brain surface regions correlated with these ASD-associated regions and identify potential NIBS targets for ASD. Results:We found that the medial prefrontal cortex, angular gyrus, dorsal lateral prefrontal cortex, inferior frontal gyrus, superior parietal lobe, postcentral gyrus, precentral gyrus, middle temporal gyrus, superior temporal sulcus, lateral occipital cortex, and supplementary motor area/paracentral gyrus are potential locations for NIBS in ASD. Conclusion:Our findings may shed light on the development of new NIBS targets for ASD.
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Project description:Impaired connectivity is proposed to underlie pathophysiology of schizophrenia. Existing studies on functional connectivity show inconsistent results. We examined functional connectivity in a clinically homogenous sample of 34 early course schizophrenia patients compared with/to 19 healthy controls using resting state functional magnetic resonance imaging (rsfMRI). Mean duration of illness for schizophrenia patients was 4 ± 1.78 years. Following a comprehensive clinical assessment, rsfMRI data were acquired using a 3.0 T magnetic resonance imaging scanner, and analyzed using FSL version 5.01 software (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl). Compared to healthy controls, schizophrenia patients had significantly decreased functional connectivity in the left fronto-parietal network, lateral and medial visual network, motor network, default mode network and auditory network. Our data suggests significant functional hypoconnectivity in selected brain networks in early schizophrenia patients compared to controls. It is likely that the observed functional hypoconnectivity may be associated with features of schizophrenia other than those examined in this study. It is possible that hypoconnectivity is necessary but not sufficient to the clinical manifestation of schizophrenia. The examination of functional connectivity as a biomarker should be extended to a wider array of disease phenotypes to better understand its significance.
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Project description:Background and purposeTraumatic brain injury (TBI) can lead to movement and balance deficits. In addition to physical therapy, brain-based neurorehabilitation efforts have begun to show promise in improving these deficits. The present study investigated the effectiveness of translingual neural stimulation (TLNS) on patients with mild-to-moderate TBI (mmTBI) and related brain connectivity using a resting-state functional connectivity (RSFC) approach.MethodsResting-state images with 5-min on GE750 3T scanner were acquired from nine participants with mmTBI. Paired t-test was used for calculating changes in RSFC and behavioral scores before and after the TLNS intervention. The balance and movement performances related to mmTBI were evaluated by Sensory Organization Test (SOT) and Dynamic Gait Index (DGI).ResultsCompared to pre-TLNS intervention, significant behavioral changes in SOT and DGI were observed. The analysis revealed increased RSFC between the left postcentral gyrus and left inferior parietal lobule and left Brodmann Area 40, as well as the increased RSFC between the right culmen and right declive, indicating changes due to TLNS treatment. However, there were no correlations between the sensory/somatomotor (or visual or cerebellar) network and SOT/DGI behavioral performance.ConclusionsAlthough the limited sample size may have led to lack of significant correlations with functional assessments, these results provide preliminary evidence that TLNS in conjunction with physical therapy can induce brain plasticity in TBI patients with balance and movement deficits.
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Project description:Stroke causes direct structural damage to local brain networks and indirect functional damage to distant brain regions. Neuroplasticity after stroke involves molecular changes within perilesional tissue that can be influenced by regions functionally connected to the site of injury. Spontaneous functional recovery can be enhanced by rehabilitative strategies, which provides experience-driven cell signaling in the brain that enhances plasticity. Functional neuroimaging in humans and rodents has shown that spontaneous recovery of sensorimotor function after stroke is associated with changes in resting-state functional connectivity (RS-FC) within and across brain networks. At the molecular level, GABAergic inhibitory interneurons can modulate brain plasticity in peri-infarct and remote brain regions. Among this cell-type, a decrease in parvalbumin (PV)-immunoreactivity has been associated with improved behavioral outcome. Subjecting rodents to multisensory stimulation through exposure to an enriched environment (EE) enhances brain plasticity and recovery of function after stroke. Yet, how multisensory stimulation relates to RS-FC has not been determined. In this study, we investigated the effect of EE on recovery of RS-FC and behavior in mice after stroke, and if EE-related changes in RS-FC were associated with levels of PV-expressing neurons. Photothrombotic stroke was induced in the sensorimotor cortex. Beginning 2 days after stroke, mice were housed in either standard environment (STD) or EE for 12 days. Housing in EE significantly improved lost tactile-proprioceptive function compared to mice housed in STD environment. RS-FC in the mouse was measured by optical intrinsic signal imaging 14 days after stroke or sham surgery. Stroke induced a marked reduction in RS-FC within several perilesional and remote brain regions. EE partially restored interhemispheric homotopic RS-FC between spared motor regions, particularly posterior secondary motor. Compared to mice housed in STD cages, EE exposure lead to increased RS-FC between posterior secondary motor regions and contralesional posterior parietal and retrosplenial regions. The increased regional RS-FC observed in EE mice after stroke was significantly correlated with decreased PV-immunoreactivity in the contralesional posterior motor region. In conclusion, experimental stroke and subsequent housing in EE induces dynamic changes in RS-FC in the mouse brain. Multisensory stimulation associated with EE enhances RS-FC among distinct brain regions relevant for recovery of sensorimotor function and controlled movements that may involve PV/GABA interneurons. Our results indicate that targeting neural circuitry involving spared motor regions across hemispheres by neuromodulation and multimodal sensory stimulation could improve rehabilitation after stroke.
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Project description:Background: Seed-based studies on resting-state functional connectivity (rsFC) in schizophrenia have shown disrupted connectivity involving a number of brain networks; however, the results have been controversial. Methods: We conducted a meta-analysis based on independent component analysis (ICA) brain templates to evaluate dysconnectivity within resting-state brain networks in patients with schizophrenia. Seventy-six rsFC studies from 70 publications with 2,588 schizophrenia patients and 2,567 healthy controls (HCs) were included in the present meta-analysis. The locations and activation effects of significant intergroup comparisons were extracted and classified based on the ICA templates. Then, multilevel kernel density analysis was used to integrate the results and control bias. Results: Compared with HCs, significant hypoconnectivities were observed between the seed regions and the areas in the auditory network (left insula), core network (right superior temporal cortex), default mode network (right medial prefrontal cortex, and left precuneus and anterior cingulate cortices), self-referential network (right superior temporal cortex), and somatomotor network (right precentral gyrus) in schizophrenia patients. No hyperconnectivity between the seed regions and any other areas within the networks was detected in patients, compared with the connectivity in HCs. Conclusions: Decreased rsFC within the self-referential network and default mode network might play fundamental roles in the malfunction of information processing, while the core network might act as a dysfunctional hub of regulation. Our meta-analysis is consistent with diffuse hypoconnectivities as a dysregulated brain network model of schizophrenia.
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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).
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Project description:Studies of large-scale brain functional connectivity using the resting-state functional magnetic resonance imaging have advanced our understanding of human brain functions. Although the evidence of dynamic functional connectivity is accumulating, the variations of functional connectivity over time have not been well characterized. In the present study, we aimed to associate the variations of functional connectivity with the intrinsic activities of resting-state networks during a single resting-state scan by comparing functional connectivity differences between when a network had higher and lower intrinsic activities. The activities of the salience network, default mode network (DMN), and motor network were associated with changes of resting-state functional connectivity. Higher activity of the salience network was accompanied by greater functional connectivity between the fronto-parietal regions and the DMN regions, and between the regions within the DMN. Higher DMN activity was associated with less connectivity between the regions within the DMN, and greater connectivity between the regions within the fronto-parietal network. Higher motor network activity was correlated with greater connectivity between the regions within the motor network, and smaller connectivity between the DMN regions and fronto-parietal regions, and between the DMN regions and the motor regions. In addition, the whole brain network modularity was positively correlated with the motor network activity, suggesting that the brain is more segregated as sub-systems when the motor network is intrinsically activated. Together, these results demonstrate the association between the resting-state connectivity variations and the intrinsic activities of specific networks, which can provide insights on the dynamic changes in large-scale brain connectivity and network configurations.
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Project description:Motor imagery (MI) relies on the mental simulation of an action without any overt motor execution (ME), and can facilitate motor learning and enhance the effect of rehabilitation in patients with neurological conditions. While functional magnetic resonance imaging (fMRI) during MI and ME reveals shared cortical representations, the role and functional relevance of the resting-state functional connectivity (RSFC) of brain regions involved in MI is yet unknown. Here, we performed resting-state fMRI followed by fMRI during ME and MI with the dominant hand. We used a behavioral chronometry test to measure ME and MI movement duration and compute an index of performance (IP). Then, we analyzed the voxel-matched correlation between the individual MI parameter estimates and seed-based RSFC maps in the MI network to measure the correspondence between RSFC and MI fMRI activation. We found that inter-individual differences in intrinsic connectivity in the MI network predicted several clusters of activation. Taken together, present findings provide first evidence that RSFC within the MI network is predictive of the activation of MI brain regions, including those associated with behavioral performance, thus suggesting a role for RSFC in obtaining a deeper understanding of neural substrates of MI and of MI ability. Hum Brain Mapp 37:3847-3857, 2016. © 2016 Wiley Periodicals, Inc.
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Project description:The reliability of magnetoencephalography (MEG) resting-state functional connectivity in schizophrenia (SZ) is unknown as previous research has focused on healthy controls (HC). Here, we examined reliability in 26 participants (13-SZ, 13-HC). Eyes opened and eyes closed resting-state data were collected on 4 separate occasions during 2 visits, 1 week apart. For source modeling, we used minimum norm software to apply dynamic statistical parametric mapping. Source analyses compared the following functional connectivity metrics from each data run: coherence (coh), imaginary coherence (imcoh), pairwise phase consistency (ppc), phase-locking value (plv), phase lag index (pli), weighted phase lag index (wpli), and weighted phase lag index debiased (wpli2). Intraclass correlation coefficients (ICCs) were calculated for whole brain, network, and network pair averages. For reliability, ICCs above 0.75 = excellent, above 0.60 = good, above 0.40 = fair, and below 0.40 = poor reliability. We found the reliability of these metrics varied greatly depending on frequency band, network, network pair, and participant group examined. Broadband (1-58 Hz) whole brain averages in both HC and SZ showed excellent reliability for wpli2, and good to fair reliability for ppc, plv, and coh. Broadband network averages showed excellent to good reliability across 1 hour and 1 week for coh, imcoh, ppc, plv, wpli within default mode, cognitive control, and visual networks in HC, while the same metrics had excellent to fair reliability in SZ. Regional network pair averages showed good to fair reliability for coh, ppc, plv within default mode, cognitive control and visual network pairs in HC and SZ. In general, HC had higher reliability compared to SZ, and the default mode, cognitive control, and visual networks had higher reliability compared to somatosensory and auditory networks. Similar reliability levels occurred for both eyes opened and eyes closed resting-states for most metrics. The functional connectivity metrics of coh, ppc, and plv performed best across 1 hour and 1 week in HC and SZ. We also found that SZ had reduced coh, plv, and ppc in the dmn average and pair values indicating dysconnectivity in SZ. These findings encourage collecting both eyes opened and eyes closed resting-state MEG, while demonstrating that clinical populations may differ in reliability.
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Project description:Depleted of dopamine, the dynamics of the parkinsonian brain impact on both 'action' and 'resting' motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the 'effective' connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network-disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses.
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