Social cognition in Multiple Sclerosis is associated to changes in brain connectivity: A resting-state fMRI study

2020 ◽  
Vol 45 ◽  
pp. 102333
Author(s):  
Tomas P. Labbe ◽  
Mariana Zurita ◽  
Cristian Montalba ◽  
Ethel L. Ciampi ◽  
Juan P. Cruz ◽  
...  
Neuroscience ◽  
2018 ◽  
Vol 382 ◽  
pp. 80-92 ◽  
Author(s):  
Arkan Al-Zubaidi ◽  
Marcus Heldmann ◽  
Alfred Mertins ◽  
Kamila Jauch-Chara ◽  
Thomas F. Münte

PLoS ONE ◽  
2012 ◽  
Vol 7 (1) ◽  
pp. e28196 ◽  
Author(s):  
Cheng Luo ◽  
Chuan Qiu ◽  
Zhiwei Guo ◽  
Jiajia Fang ◽  
Qifu Li ◽  
...  

2018 ◽  
Author(s):  
Ling George ◽  
Lee Ivy ◽  
Guimond Synthia ◽  
Lutz Olivia ◽  
Tandon Neeraj ◽  
...  

AbstractBackgroundSocial cognitive ability is a significant determinant of functional outcome and deficits in social cognition are a disabling symptom of psychotic disorders. The neurobiological underpinnings of social cognition are not well understood, hampering our ability to ameliorate these deficits.ObjectiveUsing ‘resting-state’ fMRI (functional magnetic resonance imaging) and a trans-diagnostic, data-driven analytic strategy, we sought to identify the brain network basis of emotional intelligence, a key domain of social cognition.MethodsStudy participants included 60 participants with a diagnosis of schizophrenia or schizoaffective disorder and 46 healthy comparison participants. All participants underwent a resting-state fMRI scan. Emotional Intelligence was measured using the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). A connectome-wide analysis of brain connectivity examined how each individual brain voxel’s connectivity correlated with emotional intelligence using multivariate distance matrix regression (MDMR).ResultsWe identified a region in the left superior parietal lobule (SPL) where individual network topology predicted emotional intelligence. Specifically, the association of this region with the Default Mode Network predicted higher emotional intelligence and association with the Dorsal Attention Network predicted lower emotional intelligence. This correlation was observed in both schizophrenia and healthy comparison participants.ConclusionPrevious studies have demonstrated individual variance in brain network topology but the cognitive or behavioral relevance of these differences was undetermined. We observe that the left SPL, a region of high individual variance at the cytoarchitectonic level, also demonstrates individual variance in its association with large scale brain networks and that network topology predicts emotional intelligence.


Author(s):  
Zhaoyue Shi ◽  
Khue Tran ◽  
Christof Karmonik ◽  
Timothy Boone ◽  
Rose Khavari

Abstract Background Several studies have reported brain activations and functional connectivity (FC) during micturition using functional magnetic resonance imaging (fMRI) and concurrent urodynamics (UDS) testing. However, due to the invasive nature of UDS procedure, non-invasive resting-state fMRI is being explored as a potential alternative. The purpose of this study is to evaluate the feasibility of utilizing resting states as a non-invasive alternative for investigating the bladder-related networks in the brain. Methods We quantitatively compared FC in brain regions belonging to the bladder-related network during the following states: ‘strong desire to void’, ‘voiding initiation (or attempt at voiding initiation)’, and ‘voiding (or continued attempt of voiding)’ with FC during rest in nine multiple sclerosis women with voiding dysfunction using fMRI data acquired at 7 T and 3 T. Results The inter-subject correlation analysis showed that voiding (or continued attempt of voiding) is achieved through similar network connections in all subjects. The task-based bladder-related network closely resembles the resting-state intrinsic network only during voiding (or continued attempt of voiding) process but not at other states. Conclusion Resting states fMRI can be potentially utilized to accurately reflect the voiding (or continued attempt of voiding) network. Concurrent UDS testing is still necessary for studying the effects of strong desire to void and initiation of voiding (or attempt at initiation of voiding).


2020 ◽  
Vol 303 ◽  
pp. 111140 ◽  
Author(s):  
Rafael Penadés ◽  
Bàrbara Segura ◽  
Anna Inguanzo ◽  
Clemente García-Rizo ◽  
Rosa Catalán ◽  
...  

2016 ◽  
Vol 22 (13) ◽  
pp. 1695-1708 ◽  
Author(s):  
Anthony Faivre ◽  
Emmanuelle Robinet ◽  
Maxime Guye ◽  
Celia Rousseau ◽  
Adil Maarouf ◽  
...  

Background: The compensatory effect of brain functional connectivity enhancement in relapsing-remitting multiple sclerosis (RRMS) remains controversial. Objective: To characterize the relationships between brain functional connectivity changes and disability progression in RRMS. Methods: Long-range connectivity, short-range connectivity, and density of connections were assessed using graph theoretical analysis of resting-state functional magnetic resonance imaging (fMRI) data acquired in 38 RRMS patients (disease duration: 120 ± 32 months) and 24 controls. All subjects were explored at baseline and all patients and six controls 2 years later. Results: At baseline, levels of long-range and short-range brain functional connectivity were higher in patients compared to controls. During the follow-up, decrease in connections’ density was inversely correlated with disability progression. Post-hoc analysis evidenced differential evolution of brain functional connectivity metrics in patients according to their level of disability at baseline: while patients with lowest disability at baseline experienced an increase in all connectivity metrics during the follow-up, patients with higher disability at baseline showed a decrease in the connectivity metrics. In these patients, decrease in the connectivity metrics was associated with disability progression. Conclusion: The study provides two main findings: (1) brain functional connectivity enhancement decreases during the disease course after reaching a maximal level, and (2) decrease in brain functional connectivity enhancement participates in disability progression.


NeuroImage ◽  
2016 ◽  
Vol 141 ◽  
pp. 408-415 ◽  
Author(s):  
Wi Hoon Jung ◽  
Kristin Prehn ◽  
Zhuo Fang ◽  
Marc Korczykowski ◽  
Joseph W. Kable ◽  
...  

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