scholarly journals The effect of global signal regression on DCM estimates of noise and effective connectivity from resting state fMRI

2019 ◽  
Author(s):  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Adeel Razi ◽  
Karl Friston ◽  
Daniele Marinazzo
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Effective Connectivity ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Measurement Noise ◽  
Resting State Networks ◽  
Cross Sectional ◽  
Global Signal ◽  
Leibler Divergence

AbstractThe influence of the global BOLD signal on resting state functional connectivity in fMRI data remains a topic of debate, with little consensus. In this study, we assessed the effects of global signal regression (GSR) on effective connectivity within and between resting-state networks – as estimated with dynamic causal modelling (DCM) for resting state fMRI (rsfMRI). DCM incorporates a forward (generative) model that quantifies the contribution of different types of noise (including global measurement noise), effective connectivity, and (neuro)vascular processes to functional connectivity measurements. DCM analyses were applied to two different designs; namely, longitudinal and cross-sectional designs. In the modelling of longitudinal designs, we included four extensive longitudinal resting state fMRI datasets with a total number of 20 subjects. In the analysis of cross-sectional designs, we used rsfMRI data from 361 subjects from the Human Connectome Project. We hypothesized that (1) GSR would have no discernible impact on effective connectivity estimated with DCM, and (2) GSR would be reflected in the parameters representing global measurement noise. Additionally, we performed comparative analyses of the informative value of data with and without GSR. Our results showed negligible to small effects of GSR on connectivity within small (separately estimated) RSNs. For between-network connectivity, we found two important effects: the effect of GSR on between-network connectivity (averaged over all connections) was negligible to small, while the effect of GSR on individual connections was non-negligible. Contrary to our expectations, we found either no effect (in the longitudinal designs) or a non-specific (cross-sectional design) effect of GSR on parameters representing (global) measurement noise. Data without GSR were found to be more informative than data with GSR; however, in small resting state networks the precision of posterior estimates was greater using data after GSR. In conclusion, GSR is a minor concern in DCM studies; however, individual between-network connections (as opposed to average between-network connectivity) and noise parameters should be interpreted quantitatively with some caution. The Kullback-Leibler divergence of the posterior from the prior, together with the precision of posterior estimates, might offer a useful measure to assess the appropriateness of GSR, when nuancing data features in resting state fMRI.

scholarly journals Local GABA concentration is related to network-level resting functional connectivity

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Charlotte J Stagg ◽  
Velicia Bachtiar ◽  
Ugwechi Amadi ◽  
Christel A Gudberg ◽  
Andrei S Ilie ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Primary Motor Cortex ◽  
Empirical Studies ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Resonance Spectroscopy ◽  
Resting State Networks ◽  
Inhibitory Neurotransmitter ◽  
Motor Network

Anatomically plausible networks of functionally inter-connected regions have been reliably demonstrated at rest, although the neurochemical basis of these ‘resting state networks’ is not well understood. In this study, we combined magnetic resonance spectroscopy (MRS) and resting state fMRI and demonstrated an inverse relationship between levels of the inhibitory neurotransmitter GABA within the primary motor cortex (M1) and the strength of functional connectivity across the resting motor network. This relationship was both neurochemically and anatomically specific. We then went on to show that anodal transcranial direct current stimulation (tDCS), an intervention previously shown to decrease GABA levels within M1, increased resting motor network connectivity. We therefore suggest that network-level functional connectivity within the motor system is related to the degree of inhibition in M1, a major node within the motor network, a finding in line with converging evidence from both simulation and empirical studies.

scholarly journals Personalized intrinsic network topography mapping and functional connectivity deficits in Autism Spectrum Disorder

2017 ◽  
Author(s):  
Erin W. Dickie ◽  
Stephanie H. Ameis ◽  
Joseph D. Viviano ◽  
Dawn E. Smith ◽  
Navona Calarco ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Brain Disorders ◽  
Resting State Networks ◽  
Cross Sectional ◽  
Novel Approach ◽  
Specific Variation ◽  
Spatial Locations

AbstractBackgroundRecent advances demonstrate individually specific variation in brain architecture in healthy individuals using fMRI data. To our knowledge, the effects of individually specific variation in complex brain disorders have not been previously reported.MethodsWe developed a novel approach (Personalized Intrinsic Network topography, PINT) for localizing individually specific resting state networks using conventional resting state fMRI scans. Using cross-sectional data from participants with ASD (n=393) and TD controls (n=496) across 15 sites we tested: 1) effect of diagnosis and age on the variability of intrinsic network locations and 2) whether prior findings of functional connectivity differences in ASD as compared to TD remain after PINT application.ResultsWe found greater variability in the spatial locations of resting state networks within individuals with ASD as compared to TD. In TD participants, variability decreased from childhood into adulthood, and increased again in late-life, following a ‘U-shaped’ pattern, which was not present in those with ASD. Comparison of intrinsic connectivity between groups revealed that the application of PINT decreased the number of hypo-connected regions in ASD.ConclusionsOur results provide a new framework for measuring altered brain functioning in neurodevelopmental disorders that may have implications for tracking developmental course, phenotypic heterogeneity, and ultimately treatment response. We underscore the importance of accounting for individual variation in the study of complex brain disorders.

scholarly journals Strengthened thalamoparietal functional connectivity in patients with hemifacial spasm: a cross-sectional resting-state fMRI study

2020 ◽  
Vol 93 (1108) ◽  
pp. 20190887 ◽  
Author(s):  
Xuan Niu ◽  
Hui Xu ◽  
Chenguang Guo ◽  
Tong Yang ◽  
Dustin Kress ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Hemifacial Spasm ◽  
Resting State ◽  
Resting State Fmri ◽  
Association Cortex ◽  
Resting State Networks ◽  
Supramarginal Gyrus ◽  
Resting State Functional Connectivity ◽  
Cross Sectional ◽  
The Right

Objective: In spite of the well-known importance of thalamus in hemifacial spasm (HFS), the thalamic resting-state networks in HFS is still rarely mentioned. This study aimed to investigate resting-state functional connectivity (FC) of the thalamus in HFS patients and examine its association with clinical measures. Methods: 25 HFS patients and 28 matched healthy controls underwent functional MRI at rest. Using the left and right thalamus as seed regions respectively, we compared the thalamic resting-state networks between patient and control groups using two independent sample t-test. Results: Compared with controls, HFS patients exhibited strengthened bilateral thalamus-seeded FC with the parietal cortex. Enhanced FC between right thalamus and left somatosensory association cortex was linked to worse motor disturbance, and the increased right thalamus-right supramarginal gyrus connection were correlated with improvement of affective symptoms. Conclusion: Our findings indicate that the right thalamus–left somatosensory association cortex hyperconnectivity may represent the underlying neuroplasticity related to sensorimotor dysfunction. In addition, the upregulated FC between the right thalamus and right supramarginal gyrus in HFS, is part of the thalamo-default mode network pathway involved in emotional adaptation. Advances in knowledge: This study provides new insights on the integrative role of thalamo-parietal connectivity, which participates in differential neural circuitry as a mechanism underlying motor and emotional functions in HFS patients.

scholarly journals Altered hypothalamus functional connectivity with limbic system in fibromyalgia and the modulation effect of intervention

2020 ◽  
Author(s):  
Jian Kong ◽  
Yiting Huang ◽  
Jiao Liu ◽  
Siyi Yu ◽  
Ming Cheng ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Limbic System ◽  
Resting State ◽  
Tai Chi ◽  
Effective Connectivity ◽  
Resting State Fmri ◽  
Trial Registration ◽  
Modulation Effect ◽  
Resting State Functional Connectivity ◽  
Before And After

Abstract Background: This study aims to investigate the resting state functional connectivity (rsFC) changes of the hypothalamus in Fibromyalgia patients and the modulation effect of effective treatments. Methods: Fibromyalgia patients and matched healthy controls (HC’s) were recruited. Resting state fMRI data were collected from fibromyalgia patients before and after a 12-week Tai Chi intervention and once from HC’s. Results: Data analysis showed that fibromyalgia patients displayed significantly decreased medial hypothalamus (MH) rsFC with the thalamus and amygdala when compared to HC’s at baseline. After the intervention, fibromyalgia patients showed increased (normalized) MH rsFC in the thalamus and amygdala. Effective connectivity analysis showed disrupted MH and thalamus interaction in fibromyalgia, which nonetheless could be partially restored by Tai Chi. Conclusions: Elucidating the role of the diencephalon and limbic system in the pathophysiology and development of fibromyalgia may facilitate the development of new treatment methods for this prevalent disorder. Trial registration: Trial registration ClinicalTrials.gov Identifier: NCT02407665. Registered 3 April 2015 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02407665

scholarly journals Large-scale DCMs for resting-state fMRI

2017 ◽  
Vol 1 (3) ◽  
pp. 222-241 ◽  
Author(s):  
Adeel Razi ◽  
Mohamed L. Seghier ◽  
Yuan Zhou ◽  
Peter McColgan ◽  
Peter Zeidman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Effective Connectivity ◽  
Directed Graphs ◽  
Resting State Fmri ◽  
Causal Modeling ◽  
Large Graphs ◽  
Model Inversion ◽  
Graph Theoretic

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of Bayesian model reduction to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM—with functional connectivity priors—is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

scholarly journals Altered Intrinsic Connectivity Networks in Frontal Lobe Epilepsy: A Resting-State fMRI Study

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xinzhi Cao ◽  
Zhiyu Qian ◽  
Qiang Xu ◽  
Junshu Shen ◽  
Zhiqiang Zhang ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Frontal Lobe ◽  
Resting State ◽  
Healthy Subjects ◽  
Network Connectivity ◽  
Neural Mechanism ◽  
Resting State Fmri ◽  
Control Group ◽  
Frontal Lobe Epilepsy ◽  
The Impact

Examining the resting-state networks (RSNs) may help us to understand the neural mechanism of the frontal lobe epilepsy (FLE). Resting-state functional MRI (fMRI) data were acquired from 46 patients with FLE (study group) and 46 age- and gender-matched healthy subjects (control group). The independent component analysis (ICA) method was used to identify RSNs from each group. Compared with the healthy subjects, decreased functional connectivity was observed in all the networks; however, in some areas of RSNs, functional connectivity was increased in patients with FLE. The duration of epilepsy and the seizure frequency were used to analyze correlation with the regions of interest (ROIs) in the nine RSNs to determine their influence on FLE. The functional network connectivity (FNC) was used to study the impact on the disturbance and reorganization of FLE. The results of this study may offer new insight into the neuropathophysiological mechanisms of FLE.

scholarly journals Variability and reliability of effective connectivity within the core default mode network: A longitudinal spectral DCM study

2018 ◽  
Author(s):  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Simone Kühn ◽  
Adeel Razi ◽  
Karl Friston ◽  
...  
Keyword(s):  
Resting State ◽  
Hemispheric Asymmetry ◽  
Large Scale ◽  
Effective Connectivity ◽  
Brain Networks ◽  
Resting State Fmri ◽  
Global Signal ◽  
Cognitive Behavioural ◽  
Connectivity Patterns ◽  
Within Subjects

AbstractDynamic causal modelling (DCM) for resting state fMRI – namely spectral DCM – is a recently developed and widely adopted method for inferring effective connectivity in intrinsic brain networks. Most research applying spectral DCM has focused on group-averaged connectivity within large-scale intrinsic brain networks; however, the consistency of subject- and session-specific estimates of effective connectivity has not been evaluated. Establishing reliability (within subjects) is crucial for its clinical use; e.g., as a neurophysiological phenotype of disease progression. Effective connectivity during rest is likely to vary due to changes in cognitive, behavioural, and physical states. Determining the sources of fluctuations in effective connectivity may yield greater understanding of brain processes and inform clinical applications about potential confounds. In the present study, we investigated the consistency of effective connectivity within and between subjects, as well as potential sources of variability (e.g., hemispheric asymmetry). We further investigated how standard procedures for data processing and signal extraction affect this consistency. DCM analyses were applied to four longitudinal resting state fMRI datasets. Our sample consisted of 20 subjects with 653 resting state fMRI sessions in total. These data allowed to quantify the robustness of connectivity estimates for each subject, and to draw conclusions beyond specific data features. We found that subjects contributing to all datasets showed systematic and reliable patterns of hemispheric asymmetry. When asymmetry was taken into account, subjects showed very similar connectivity patterns. We also found that various processing procedures (e.g. global signal regression and ROI size) had little effect on inference and reliability of connectivity for the majority of subjects. Bayesian model reduction increased reliability (within-subjects) and stability (between-subjects) of connectivity patterns.

scholarly journals Typhoon-Related Post-Traumatic Stress Disorder and Trauma Might Lead to Functional Integration Abnormalities in Intra- and Inter-Resting State Networks: a Resting-State Fmri Independent Component Analysis

2018 ◽  
Vol 48 (1) ◽  
pp. 99-110 ◽  
Author(s):  
Jun Ke ◽  
Li Zhang ◽  
Rongfeng Qi ◽  
Qiang Xu ◽  
Yuan Zhong ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Post Traumatic Stress Disorder ◽  
Traumatic Stress ◽  
Resting State ◽  
Effective Connectivity ◽  
Resting State Networks ◽  
Post Traumatic Stress ◽  
Control Groups ◽  
Post Traumatic ◽  
Ptsd Group

Background/Aims: Functional connectivity studies based on region of interest approach suggest altered functional connectivity of the default mode network (DMN), executive control network (ECN), and salience network (SN). The aim of this study is to determine whether intranetwork and internetwork brain connectivity are altered in both post-traumatic stress disorder (PTSD) patients and traumatized subjects without PTSD using a data-driven approach. Methods: Resting-state functional MRI data were acquired for 27 patients with typhoon-related PTSD, 33 trauma-exposed controls (TEC), and 30 healthy controls (HC). Functional connectivity within the DMN, ECN, and SN as well as functional and effective connectivity between these resting-state networks were examined with independent component analysis (ICA), and then compared between groups by conducting analysis of variance. Results: Within the DMN, the TEC group showed decreased and increased functional connectivity in the superior frontal gyrus compared with the PTSD group and the HC group, respectively. The TEC group showed increased angular functional connectivity within the DMN and decreased functional connectivity in the superior temporal gyrus/posterior insula within the SN relative to the HC group. Compared with the TEC group, the PTSD group showed increased functional connectivity in the middle frontal gyrus and supplementary motor area within the ECN as well as in the inferior frontal gyrus/anterior insula within the SN. The PTSD group showed decreased functional connectivity in the supplementary motor area within the SN relative to both control groups. Moreover, the PTSD showed increased excitatory influence from the ECN to DMN compared with both control groups, while the TEC group showed increased inhibitory influence from the DMN to ECN compared with the HC group. Intranetwork functional connectivity within the DMN and SN is altered in traumatized subjects irrespective of PTSD diagnosis. PTSD patients also showed altered intranetwork functional connectivity within the ECN. Conclusions: Distinct changes of effective connectivity between the DMN and ECN in the PTSD group and TEC group may reflect different compensatory mechanisms for rebalance of resting-state networks in the two groups.

scholarly journals Impaired intrinsic functional connectivity between the thalamus and visual cortex in migraine without aura

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Heng-Le Wei ◽  
Xin Zhou ◽  
Yu-Chen Chen ◽  
Yu-Sheng Yu ◽  
Xi Guo ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Migraine Without Aura ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Neural Activation ◽  
Scale Scores ◽  
The Right ◽  
Complex Scenario ◽  
Visual Network

Abstract Background Resting-state functional magnetic resonance imaging (fMRI) has confirmed disrupted visual network connectivity in migraine without aura (MwoA). The thalamus plays a pivotal role in a number of pain conditions, including migraine. However, the significance of altered thalamo-visual functional connectivity (FC) in migraine remains unknown. The goal of this study was to explore thalamo-visual FC integrity in patients with MwoA and investigate its clinical significance. Methods Resting-state fMRI data were acquired from 33 patients with MwoA and 22 well-matched healthy controls. After identifying the visual network by independent component analysis, we compared neural activation in the visual network and thalamo-visual FC and assessed whether these changes were linked to clinical characteristics. We used voxel-based morphometry to determine whether functional differences were dependent on structural differences. Results The visual network exhibited significant differences in regions (bilateral cunei, right lingual gyrus and left calcarine sulcus) by inter-group comparison. The patients with MwoA showed significantly increased FC between the left thalami and bilateral cunei and between the right thalamus and the contralateral calcarine sulcus and right cuneus. Furthermore, the neural activation of the left calcarine sulcus was positively correlated with visual analogue scale scores (r = 0.319, p = 0.043), and enhanced FC between the left thalamus and right cuneus in migraine patients was negatively correlated with Generalized Anxiety Disorder scores (r = − 0.617, p = 0.005). Conclusion Our data suggest that migraine distress is exacerbated by aberrant feedback projections to the visual network, playing a crucial role in migraine physiological mechanisms. The current study provides further insights into the complex scenario of migraine mechanisms.

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