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Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke.

ABSTRACT: Focal brain lesions can have important remote effects on the function of distant brain regions. The resulting network dysfunction may contribute significantly to behavioral deficits observed after stroke. This study investigates the behavioral significance of changes in the coherence of spontaneous activity in distributed networks after stroke by measuring resting state functional connectivity (FC) using functional magnetic resonance imaging.In acute stroke patients, we measured FC in a dorsal attention network and an arm somatomotor network, and determined the correlation of FC with performance obtained in a separate session on tests of attention and motor function. In particular, we compared the behavioral correlation with intrahemispheric FC to the behavioral correlation with interhemispheric FC.In the attention network, disruption of interhemispheric FC was significantly correlated with abnormal detection of visual stimuli (Pearson r with field effect = -0.624, p = 0.002). In the somatomotor network, disruption of interhemispheric FC was significantly correlated with upper extremity impairment (Pearson r with contralesional Action Research Arm Test = 0.527, p = 0.036). In contrast, intrahemispheric FC within the normal or damaged hemispheres was not correlated with performance in either network. Quantitative lesion analysis demonstrated that our results could not be explained by structural damage alone.These results suggest that lesions cause state changes in the spontaneous functional architecture of the brain, and constrain behavioral output. Clinically, these results validate using FC for assessing the health of brain networks, with implications for prognosis and recovery from stroke, and underscore the importance of interhemispheric interactions.

SUBMITTER: Carter AR

PROVIDER: S-EPMC2927671 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

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Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke.

Carter Alex R AR Astafiev Serguei V SV Lang Catherine E CE Connor Lisa T LT Rengachary Jennifer J Strube Michael J MJ Pope Daniel L W DL Shulman Gordon L GL Corbetta Maurizio M

Annals of neurology 20100301 3

<h4>Objective</h4>Focal brain lesions can have important remote effects on the function of distant brain regions. The resulting network dysfunction may contribute significantly to behavioral deficits observed after stroke. This study investigates the behavioral significance of changes in the coherence of spontaneous activity in distributed networks after stroke by measuring resting state functional connectivity (FC) using functional magnetic resonance imaging.<h4>Methods</h4>In acute stroke pati ...[more]

PMID: 20373348

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Project description:Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep conditions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory" of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circuit and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, nodes and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB-131115-H0075 on November 15, 2013.

Project description:BackgroundMigraineurs often exhibited abnormalities in cognition, emotion, and resting-state functional connectivity (rsFC), whereas patients with tension-type headache (TTH) rarely exhibited these abnormalities. The aim of this study is to explore whether rsFC alterations in brain regions related to cognition and emotion could be used to distinguish patients with migraine from patients with TTH.MethodsIn this study, Montreal Cognitive Assessment (MoCA), Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), and rsFC analyses were used to assess the cognition, anxiety, and depression of 24 healthy controls (HCs), 24 migraineurs, and 24 patients with TTH. Due to their important roles in neuropsychological functions, the bilateral amygdala and hippocampus were chosen as seed regions for rsFC analyses. We further assessed the accuracy of the potential rsFC alterations for distinguishing migraineurs from non-migraineurs (including HCs and patients with TTH) by the receiver operating characteristic (ROC) analysis. Associations between headache characteristics and rsFC features were calculated using a multi-linear regression model. This clinical trial protocol has been registered in the Chinese Clinical Trial Registry (registry number: ChiCTR1900024307, Registered: 5 July 2019-Retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=40817).ResultsMigraineurs showed lower MoCA scores (p = 0.010) and higher SAS scores (p = 0.017) than HCs. Migraineurs also showed decreased rsFC in the bilateral calcarine/cuneus, lingual gyrus (seed: left amygdala), and bilateral calcarine/cuneus (seed: left hippocampus) in comparison to HCs and patients with TTH. These rsFC features demonstrated significant distinguishing capabilities and got a sensitivity of 82.6% and specificity of 81.8% with an area under the curve (AUC) of 0.868. rsFC alterations showed a significant correlation with headache frequency in migraineurs (p = 0.001, Pc = 0.020).ConclusionThe rsFC of amygdala and hippocampus with occipital lobe can be used to distinguish patients with migraine from patients with TTH.Clinical trial registration[http://www.chictr.org.cn/showproj.aspx?proj=40817], identifier [ChiCTR1900024307].

Project description:Introduction: The selection of an appropriate window size, window function, and functional connectivity (FC) metric in the sliding window method is not straightforward due to the absence of ground truth. Methods: A previously proposed wavelet-based method was accordingly adjusted for estimating time-varying FC (TVFC) and was applied to a large high-quality, low-motion dataset of 400 resting-state functional magnetic resonance imaging data. Specifically, the wavelet coherence magnitude and relative phase were averaged across wavelet (frequency) scales to yield TVFC and synchronization patterns. To assess whether the observed fluctuations in TVFC were statistically significant (dynamic FC [dFC]; the distinction between TVFC and dFC is intentional), surrogate data were generated using the multivariate phase randomization (MVPR) and multivariate autoregressive randomization (MVAR) methods to define the null hypothesis of dFC absence. Results: By averaging across all frequencies, core regions of the default mode network (DMN; medial prefrontal and posterior cingulate cortices, inferior parietal lobes, hippocampal formation) were found to exhibit dFC (test-retest reproducibility of 90%) and were also synchronized in activity (-15° ≤ phase ≤15°). When averaging across distinct frequency bands, the same dynamic connections were identified, with the majority of them identified in the frequency range (0.01, 0.198) Hz, though with lower test-retest reproducibility (<66%). Additional analysis suggested that MVPR method better preserved properties (p < 10-10), including time-averaged coherence, of the original data compared with MVAR approach. Conclusions: The wavelet-based approach identified dynamic associations between the core DMN regions with fewer choices in parameters, compared with sliding window method. Impact statement We employed a wavelet-based method, previously used in the literature, and proposed modifications to assess time-varying functional connectivity in resting-state functional magnetic resonance imaging. With this approach, dynamic connections within the default mode network were identified, involving the medial prefrontal and posterior cingulate cortices, inferior parietal lobes, and hippocampal formation, which were also highly consistent in test-retest analysis (test-retest reproducibility of 90%), without the need to select window size, window function, and functional connectivity metric as with the sliding window method, whereby no consensus on the appropriate choices of hyperparameters currently exists in the literature.

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Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke.

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Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke.

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