Neural traffic as voxel-based measure of cerebral functional connectivity in fMRI
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Stimulus (psychology)
Most of functional magnetic resonance imaging(fMRI)studies have employed task-related paradigm to explore brain response to an external stimulus.However,the brain is very active in the absence of any specific experimental tasks and the spontaneous activity exhibits coherent low-frequency synchrony.Studies on resting-state brain activity have provided insight into the intrinsic activity mechanism of the brain.In this study we review recent popular methods on resting-state functional connectivity and their preliminary applications to clinical diseases.
Stimulus (psychology)
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In this paper we present a new algorithm that extends Seitz and Dyer's voxel coloring algorithm. This paper explores a method of voxel coloring which scans only the voxels on the surface of 3D reconstructed scene and the voxels of the nearest neighbors of the 3d reconstructed scene. This method reduces significantly the number of voxels to be processed and retaining the accuracy of actual voxel coloring method. With our algorithm, the time complexity rather than being O(n3), reduces to O(number of voxels on the surface of reconstructed scene). The significant advantage of our algorithm can be seen while increasing the number of voxels (or reducing the size of voxels), for greater accuracy of reconstructed results. We present efficiency measurements for comparisons. Our algorithm can also be used with the Voxel coloring method reported in, increasing significantly the speed of the scan.
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Blood-oxygen-level dependent
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Dynamic functional connectivity
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Mild behavioral impairment (MBI) is associated with accelerated cognitive decline and greater risk of dementia. However, the neural correlates of MBI have not been completely elucidated.The study aimed to investigate the correlation between cognitively normal participants and participants with amnestic mild cognitive impairment (aMCI) using resting-state functional magnetic resonance imaging.The study included 30 cognitively normal participants and 13 participants with aMCI (20 men and 23 women; mean age, 76.9 years). The MBI was assessed using the MBI checklist (MBI-C). Region of interest (ROI)-to-ROI analysis was performed to examine the correlation between MBI-C scores and functional connectivity (FC) of the default mode network, salience network, and frontoparietal control network (FPCN). Age, Mini-Mental State Examination score, sex, and education were used as covariates. A p-value of 0.05, with false discovery rate correction, was considered significant.A negative correlation was observed between the MBI-C total score and FC of the left posterior parietal cortex with the right middle frontal gyrus. A similar result was obtained for the MBI-C affective dysregulation domain score.FPCN dysfunction was detected as a neural correlate of MBI, especially in the affective dysregulation domain. This dysfunction may be associated with cognitive impairment in MBI and conversion of MBI to dementia; however, further longitudinal data are needed to examine this relationship.
Functional Brain Imaging
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The particularity of seafarers' occupation makes their brain functional activities vulnerable to the influence of working environments, which leads to abnormal functional connectivities (FCs) between brain networks. To further investigate the influences of maritime environments on the seafarers' functional brain networks, the functional magnetic resonance imaging (fMRI) datasets of 33 seafarers before and after sailing were used to study FCs among the functional brain networks in this paper. On the basis of making full use of the intrinsic prior information from fMRI data, six resting-state brain functional networks of seafarers before and after sailing were obtained by using group independent component analysis with intrinsic reference, and then the differences between the static and dynamic FCs among these six brain networks of seafarers before and after sailing were, respectively, analyzed from both group and individual levels. Subsequently, the potential dynamic functional connectivity states of seafarers before and after sailing were extracted by using the affine propagation clustering algorithm and the probabilities of state transition between them were obtained simultaneously. The results show that the dynamic FCs among large-scale brain networks have significant difference seafarers before and after sailing both at the group level and individual level, while the static FCs between them varies only at the individual level. This suggests that the maritime environments can indeed affect the brain functional activity of seafarers in real time, and the degree of influence is different for different subjects, which is of a great significance to explore the neural changes of seafarer's brain functional network.
Functional Brain Imaging
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Functional magnetic resonance imaging (fMRI) can be applied to study the functional connectivity of the neural elements which form complex network at a whole brain level. Most analyses of functional resting state networks (RSN) have been based on the analysis of correlation between the temporal dynamics of various regions of the brain. While these models can identify coherently behaving groups in terms of correlation they give little insight into how these groups interact. In this paper we take a different view on the analysis of functional resting state networks. Starting from the definition of resting state as functional coherent groups we search for functional units of the brain that communicate with other parts of the brain in a coherent manner as measured by mutual information. We use the infinite relational model (IRM) to quantify functional coherent groups of resting state networks and demonstrate how the extracted component interactions can be used to discriminate between functional resting state activity in multiple sclerosis and normal subjects.
Dynamic functional connectivity
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Dynamic functional connectivity
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