scholarly journals COVID-19 and the Brain: A Psychological and Resting-state fMRI Study of the Whole-brain Functional Connectivity

2021 ◽  
pp. 1-29
Author(s):  
Mohammad Niroumand Sarvandani ◽  
◽  
Javad Sheikhi Koohsar ◽  
Raheleh Rafaiee ◽  
Maryam Saeedi ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Cognitive Assessment ◽  
Neural Circuits ◽  
Resting State Fmri ◽  
Montreal Cognitive Assessment ◽  
Whole Brain ◽  
Neuropsychological Status ◽  
The Mean ◽  
The Relationship

Background: Coronavirus 2019 (COVID-19) spreads rapidly worldwide and causes severe acute respiratory syndrome. The current study aimed at evaluating the relationship between the whole-brain functional connections in resting state and cognitive impairments in patients with COVID-19 compared with that of a healthy control group. Methods: Resting-state fMRI and Montreal cognitive assessment (MoCA) data were obtained from 29 patients of the acute stage of COVID-19 on the third day of admission and 20 healthy controls. Cross-correlation of the mean resting-state signals was determined in the voxels of 23 IC (Independent Components) of brain neural circuits. To assess cognitive function and neuropsychological status, MoCA was performed on all participants. The relationship between rs-fMRI information, neuropsychological status, and paraclinical data were analyzed. Results: The COVID-19 group got a lower mean MoCA score and showed a significant reduction in the functional connectivity of the IC14 (P <0.001) and IC38 (P <0.001) regions compared with controls. The increase of functional connectivity was observed in the COVID-19 group compared with controls at baseline in the default mode network (DMN) IC00 (P <0.001) and dorsal attention network (DAN) IC08 (P <0.001) regions. Furthermore, alternation of functional connectivity in the mentioned ICs was significantly correlated with the mean Montreal Cognitive Assessment (MoCA) scores and inflammatory parameters-ie, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP). Conclusions: Functional connectivity abnormalities in four brain neural circuits associated with cognitive impairment and increased inflammatory markers in patients with COVID-19.

scholarly journals Whole-brain dynamics in aging: disruptions in functional connectivity and the role of the rich club

2020 ◽  
Author(s):  
Anira Escrichs ◽  
Carles Biarnes ◽  
Josep Garre-Olmo ◽  
José Manuel Fernández-Real ◽  
Rafel Ramos ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Rich Club ◽  
Brain Functional Network ◽  
Age Related ◽  
Age Range ◽  
The Brain

AbstractNormal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state fMRI studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent (BOLD) signals to analyze resting-state fMRI data from 620 subjects divided into two groups (‘middle-age group’ (n=310); age range, 50-65 years vs. ‘older group’ (n=310); age range, 66-91 years). Applying the Intrinsic-Ignition Framework to assess the effect of spontaneous local activation events on local-global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.

scholarly journals Propagating patterns of intrinsic activity along macroscale gradients coordinate functional connections across the whole brain

2020 ◽  
Author(s):  
Behnaz Yousefi ◽  
Shella Keilholz
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Spatial Organization ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Intrinsic Activity ◽  
Resting State Networks ◽  
Whole Brain ◽  
Functional Connections ◽  
Driving Mechanisms

The intrinsic activity of the human brain, observed with resting-state fMRI (rsfMRI) and functional connectivity, exhibits macroscale spatial organization such as resting-state networks (RSNs) and functional connectivity gradients (FCGs). Dynamic analysis techniques have shown that the time-averaged maps captured by functional connectivity are mere summaries of time-varying patterns with distinct spatial and temporal characteristics. A better understanding of these patterns might provide insight into aspects of the brain intrinsic activity that cannot be inferred by functional connectivity, RSNs or FCGs. Here, we describe three spatiotemporal patterns of coordinated activity across the whole brain obtained by averaging similar ~20-second-long segments of rsfMRI timeseries. In each of these patterns, activity propagates along a particular macroscale FCG, simultaneously across the cortical sheet and in most other brain regions. In some areas, like the thalamus, the propagation suggests previously-undescribed FCGs. The coordinated activity across areas is consistent with known tract-based connections, and nuanced differences in the timing of peak activity between brain regions point to plausible driving mechanisms. The magnitude of correlation within and particularly between RSNs is remarkably diminished when these patterns are regressed from the rsfMRI timeseries, a quantitative demonstration of their significant role in functional connectivity. Taken together, our results suggest that a few recurring patterns of propagating intrinsic activity along macroscale gradients give rise to and coordinate functional connections across the whole brain.

scholarly journals A Whole-Brain Regression Method to Identify Individual and Group Variations in Functional Connectivity

2020 ◽  
Author(s):  
Yi Zhao ◽  
Brian S. Caffo ◽  
Bingkai Wang ◽  
Chiang-shan R. Li ◽  
Xi Luo
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Statistical Power ◽  
Resting State Fmri ◽  
Regression Method ◽  
Resting State Functional Connectivity ◽  
Whole Brain ◽  
Human Connectome Project ◽  
Group Ica ◽  
Brain Functional Connectivity

AbstractResting-state functional connectivity is an important and widely used measure of individual and group differences. These differences are typically attributed to various demographic and/or clinical factors. Yet, extant statistical methods are limited to linking covariates with variations in functional connectivity across subjects, especially at the voxel-wise level of the whole brain. This paper introduces a generalized linear model method that regresses whole-brain functional connectivity on covariates. Our approach builds on two methodological components. We first employ whole-brain group ICA to reduce the dimensionality of functional connectivity matrices, and then search for matrix variations associated with covariates using covariate assisted principal regression, a recently introduced covariance matrix regression method. We demonstrate the efficacy of this approach using a resting-state fMRI dataset of a medium-sized cohort of subjects obtained from the Human Connectome Project. The results show that the approach enjoys improved statistical power in detecting interaction effects of sex and alcohol on whole-brain functional connectivity, and in identifying the brain areas contributing significantly to the covariate-related differences in functional connectivity.

scholarly journals Characterizations of resting-state modulatory interactions in the human brain

2015 ◽  
Vol 114 (5) ◽  
pp. 2785-2796 ◽  
Author(s):  
Xin Di (邸新) ◽  
Bharat B. Biswal
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Interaction Analysis ◽  
Region Of Interest ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Processing Efficiency ◽  
Whole Brain ◽  
Positive Effects

Functional connectivity between two brain regions, measured using functional MRI (fMRI), has been shown to be modulated by other regions even in a resting state, i.e., without performing specific tasks. We aimed to characterize large-scale modulatory interactions by performing region-of-interest (ROI)-based physiophysiological interaction analysis on resting-state fMRI data. Modulatory interactions were calculated for every possible combination of three ROIs among 160 ROIs sampling the whole brain. Firstly, among all of the significant modulatory interactions, there were considerably more negative than positive effects; i.e., in more cases, an increase of activity in one region was associated with decreased functional connectivity between two other regions. Next, modulatory interactions were categorized as to whether the three ROIs were from one single network module, two modules, or three different modules (defined by a modularity analysis on their functional connectivity). Positive modulatory interactions were more represented than expected in cases in which the three ROIs were from a single module, suggesting an increase within module processing efficiency through positive modulatory interactions. In contrast, negative modulatory interactions were more represented than expected in cases in which the three ROIs were from two modules, suggesting a tendency of between-module segregation through negative modulatory interactions. Regions that were more likely to have modulatory interactions were then identified. The numbers of significant modulatory interactions for different regions were correlated with the regions' connectivity strengths and connection degrees. These results demonstrate whole-brain characteristics of modulatory interactions and may provide guidance for future studies of connectivity dynamics in both resting state and task state.

scholarly journals Damage to the structural connectome reflected in resting-state fMRI functional connectivity

2020 ◽  
Vol 4 (4) ◽  
pp. 1197-1218
Author(s):  
Anirudh Wodeyar ◽  
Jessica M. Cassidy ◽  
Steven C. Cramer ◽  
Ramesh Srinivasan
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Structural Damage ◽  
Partial Correlation ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Analysis Pipeline ◽  
Structural Connectome ◽  
Relationship Of ◽  
The Relationship

The relationship between structural and functional connectivity has been mostly examined in intact brains. Fewer studies have examined how differences in structure as a result of injury alters function. In this study we analyzed the relationship of structure to function across patients with stroke among whom infarcts caused heterogenous structural damage. We estimated relationships between distinct brain regions of interest (ROIs) from functional MRI in two pipelines. In one analysis pipeline, we measured functional connectivity by using correlation and partial correlation between 114 cortical ROIs. We found fMRI-BOLD partial correlation was altered at more edges as a function of the structural connectome (SC) damage, relative to the correlation. In a second analysis pipeline, we limited our analysis to fMRI correlations between pairs of voxels for which we possess SC information. We found that voxel-level functional connectivity showed the effect of structural damage that we could not see when examining correlations between ROIs. Further, the effects of structural damage on functional connectivity are consistent with a model of functional connectivity, diffusion, which expects functional connectivity to result from activity spreading over multiple edge anatomical paths.

scholarly journals Flexible annotation atlas of the mouse brain: combining and dividing brain structures of the Allen Brain Atlas while maintaining anatomical hierarchy

2020 ◽  
Author(s):  
Norio Takata ◽  
Nobuhiko Sato ◽  
Yuji Komaki ◽  
Hideyuki Okano ◽  
Kenji F. Tanaka
Keyword(s):  
Functional Connectivity ◽  
Mouse Brain ◽  
Resting State ◽  
Brain Structures ◽  
Resting State Fmri ◽  
Brain Atlas ◽  
List Type ◽  
Resting State Functional Connectivity ◽  
Whole Brain ◽  
Link Type

AbstractA brain atlas is necessary for analyzing structure and function in neuroimaging research. Although various annotation volumes (AVs) for the mouse brain have been proposed, it is common in magnetic resonance imaging (MRI) of the mouse brain that regions-of-interest (ROIs) for brain structures (nodes) are created arbitrarily according to each researcher’s necessity, leading to inconsistent ROIs among studies. One reason for such a situation is the fact that earlier AVs were fixed, i.e. combination and division of nodes were not implemented. This report presents a pipeline for constructing a flexible annotation atlas (FAA) of the mouse brain by leveraging public resources of the Allen Institute for Brain Science on brain structure, gene expression, and axonal projection. A mere two-step procedure with user-specified, text-based information and Python codes constructs FAA with nodes which can be combined or divided objectively while maintaining anatomical hierarchy of brain structures. Four FAAs with total node count of 4, 101, 866, and 1,381 were demonstrated. Unique characteristics of FAA realized analysis of resting-state functional connectivity (FC) across the anatomical hierarchy and among cortical layers, which were thin but large brain structures. FAA can improve the consistency of whole brain ROI definition among laboratories by fulfilling various requests from researchers with its flexibility and reproducibility.Highlights–A flexible annotation atlas (FAA) for the mouse brain is proposed.–FAA is expected to improve whole brain ROI-definition consistency among laboratories.–The ROI can be combined or divided objectively while maintaining anatomical hierarchy.–FAA realizes functional connectivity analysis across the anatomical hierarchy.–Codes for FAA reconstruction is available at https://github.com/ntakata/flexible-annotation-atlas–Datasets for resting-state fMRI in awake mice are available at https://openneuro.org/datasets/ds002551

scholarly journals Inflammation is Correlated with Abnormal Functional Connectivity in Unmedicated Bipolar Depression: A Resting State FMRI Study

2020 ◽  
Author(s):  
Guixian Tang ◽  
Pan Chen ◽  
Guanmao Chen ◽  
Shuming Zhong ◽  
Jiaying Gong ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Bipolar Depression ◽  
Serum Levels ◽  
Resting State Fmri ◽  
Precentral Gyrus ◽  
Fmri Study ◽  
The Right ◽  
The Relationship

Abstract Objectives Inflammation might play a role in bipolar disorder (BD), but it remains unclear the relationship between inflammation and brain structural and functional abnormalities in patients with BD. In this study, we focused on the alterations of functional connectivity (FC), peripheral pro-inflammatory cytokines and their correlations to investigate the role of inflammation in FC in BD depression.Methods In this study, 42 unmedicated patients with BD II depression and 62 healthy controls (HCs) were enrolled. Resting-state-functional magnetic resonance imaging (rs-fMRI) was performed in all participants and independent component analysis (ICA) was used. Serum levels of Interleukin-6 (IL-6) and Interleukin-8 (IL-8) were measured in all participants. Correlation between FC values and IL-6 and IL-8 levels in BD was calculated.Results Compared with the HCs, BD II patients showed decreased FC in the left orbitofrontal cortex (OFC) implicating the limbic network and the right precentral gyrus implicating the somatomotor network (SMN). BD II showed increased IL-6 (P = 0.039), IL-8 (P = 0.002) levels. Moreover, abnormal FC in the right precentral gyrus were inversely correlated with the IL-8 (r=-0.458, P = 0.004) levels in BD II. No significant correlation was found between FC in the left OFC and cytokines levels.Conclusions Our findings that serum IL-8 levels is associated with impaired FC in the right precentral gyrus in BD II patients suggest that inflammation might play a crucial role in brain functional abnormalities in BD.

Decreased interhemispheric resting state functional connection in schizophrenic patients with auditory hallucinations

2016 ◽  
Vol 33 (S1) ◽  
pp. S109-S109
Author(s):  
H. Wang ◽  
G. Wang
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Auditory Hallucination ◽  
Superior Temporal Gyrus ◽  
Resting State Fmri ◽  
Functional Connection ◽  
Whole Brain ◽  
Schizophrenic Patients ◽  
Competing Interest ◽  
Normal Controls

IntroductionAuditory hallucination (AH) has been always concerned as a main core symptom of schizophrenia. However, the mechanisms of AH are still unclear.ObjectivesThe aim of this study is to further explore the complicated neuroimaging mechanism of AHs from a new insight by using voxel-mirrored homotopic connectivity (VMHC).MethodsForty-two patients with AH (APG), 26 without AHs (NPG) and 82 normal controls (NC) participated in resting state fMRI scan. Correlation analyses were used to assess the relationships between VMHC and Hoffman scores. Additionally, ROI analysis was used to further know about the functional connectivity between the brain areas with changed interhemispheric FC and the whole brain.ResultsAPG showed reduced VMHC in the parahippocapus, fusiform gyrus, rolandic operculum, insula, heschl's gyrus and superior temporal gyrus (STG). Hoffman score of APG group had negative correlation with VMHC in these regions. Besides, ROI analysis supported decreased interhemispheric FC in schizophrenia with AH and verified functional connectivity abnormalities in schizophrenia.ConclusionsThese findings suggest impairment of interhemispheric coordination and whole brain FC in schizophrenia with AH, which may be implicated to the neuroimaging mechanism of auditory hallucination. Furthermore, this research highly support dysconnectivity hypothesis that schizophrenia related to abnormalities in neuronal connectivity.Disclosure of interestThe authors have not supplied their declaration of competing interest.

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