scholarly journals Resting-State fMRI in MS: General Concepts and Brief Overview of Its Application

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Emilia Sbardella ◽  
Nikolaos Petsas ◽  
Francesca Tona ◽  
Patrizia Pantano
Keyword(s):  
Multiple Sclerosis ◽  
Resting State ◽  
Brain Function ◽  
Region Of Interest ◽  
Resting State Fmri ◽  
Research Field ◽  
Clinical Impairment ◽  
The Central Nervous System ◽  
Brain Functional Connectivity ◽  
The Brain

Brain functional connectivity (FC) is defined as the coherence in the activity between cerebral areas under a task or in the resting-state (RS). By applying functional magnetic resonance imaging (fMRI), RS FC shows several patterns which define RS brain networks (RSNs) involved in specific functions, because brain function is known to depend not only on the activity within individual regions, but also on the functional interaction of different areas across the whole brain. Region-of-interest analysis and independent component analysis are the two most commonly applied methods for RS investigation. Multiple sclerosis (MS) is characterized by multiple lesions mainly affecting the white matter, determining both structural and functional disconnection between various areas of the central nervous system. The study of RS FC in MS is mainly aimed at understanding alterations in the intrinsic functional architecture of the brain and their role in disease progression and clinical impairment. In this paper, we will examine the results obtained by the application of RS fMRI in different multiple sclerosis (MS) phenotypes and the correlations of FC changes with clinical features in this pathology. The knowledge of RS FC changes may represent a substantial step forward in the MS research field, both for clinical and therapeutic purposes.

scholarly journals High spatial correlation in brain connectivity between micturition and resting states within bladder-related networks using 7 T MRI in multiple sclerosis women with voiding dysfunction

2021 ◽  
Author(s):  
Zhaoyue Shi ◽  
Khue Tran ◽  
Christof Karmonik ◽  
Timothy Boone ◽  
Rose Khavari
Keyword(s):  
Multiple Sclerosis ◽  
Resting State ◽  
Voiding Dysfunction ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Functional Magnetic Resonance ◽  
Non Invasive ◽  
Potential Alternative ◽  
The Brain

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).

scholarly journals Morphological MRI phenotypes of multiple sclerosis differ in resting-state brain function

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Daniela Pinter ◽  
Christian F. Beckmann ◽  
Franz Fazekas ◽  
Michael Khalil ◽  
Alexander Pichler ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Resting State ◽  
Brain Function ◽  
Resting State Fmri ◽  
Resting State Functional Connectivity ◽  
Hyperintense Lesion ◽  
Sensorimotor Network ◽  
Predominately White ◽  
Disconnection Syndrome

Abstract We aimed to assess differences in resting-state functional connectivity (FC) between distinct morphological MRI-phenotypes in multiple sclerosis (MS). Out of 180 MS patients, we identified those with high T2-hyperintense lesion load (T2-LL) and high normalized brain volume (NBV; a predominately white matter damage group, WMD; N = 37) and patients with low T2-LL and low NBV (N = 37; a predominately grey matter damage group; GMD). Independent component analysis of resting-state fMRI was used to test for differences in the sensorimotor network (SMN) between MS MRI-phenotypes and compared to 37 age-matched healthy controls (HC). The two MS groups did not differ regarding EDSS scores, disease duration and distribution of clinical phenotypes. WMD compared to GMD patients showed increased FC in all sub-units of the SMN (sex- and age-corrected). WMD patients had increased FC compared to HC and GMD patients in the central SMN (leg area). Only in the WMD group, higher EDSS scores and T2-LL correlated with decreased connectivity in SMN sub-units. MS patients with distinct morphological MRI-phenotypes also differ in brain function. The amount of focal white matter pathology but not global brain atrophy affects connectivity in the central SMN (leg area) of the SMN, consistent with the notion of a disconnection syndrome.

Depletion of brain functional connectivity enhancement leads to disability progression in multiple sclerosis: A longitudinal resting-state fMRI study

2016 ◽  
Vol 22 (13) ◽  
pp. 1695-1708 ◽  
Author(s):  
Anthony Faivre ◽  
Emmanuelle Robinet ◽  
Maxime Guye ◽  
Celia Rousseau ◽  
Adil Maarouf ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Functional Connectivity ◽  
Long Range ◽  
Resting State ◽  
Short Range ◽  
Resting State Fmri ◽  
Disability Progression ◽  
Fmri Study ◽  
Brain Functional Connectivity

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.

scholarly journals Heritability of the human connectome: A connectotyping study

2018 ◽  
Vol 2 (2) ◽  
pp. 175-199 ◽  
Author(s):  
Oscar Miranda-Dominguez ◽  
Eric Feczko ◽  
David S. Grayson ◽  
Hasse Walum ◽  
Joel T. Nigg ◽  
...  
Keyword(s):  
Machine Learning ◽  
Resting State ◽  
Brain Function ◽  
Recent Progress ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Learning Framework ◽  
Novel Approach ◽  
The Brain ◽  
New Strategies

Recent progress in resting-state neuroimaging demonstrates that the brain exhibits highly individualized patterns of functional connectivity—a “connectotype.” How these individualized patterns may be constrained by environment and genetics is unknown. Here we ask whether the connectotype is familial and heritable. Using a novel approach to estimate familiality via a machine-learning framework, we analyzed resting-state fMRI scans from two well-characterized samples of child and adult siblings. First we show that individual connectotypes were reliably identified even several years after the initial scanning timepoint. Familial relationships between participants, such as siblings versus those who are unrelated, were also accurately characterized. The connectotype demonstrated substantial heritability driven by high-order systems including the fronto-parietal, dorsal attention, ventral attention, cingulo-opercular, and default systems. This work suggests that shared genetics and environment contribute toward producing complex, individualized patterns of distributed brain activity, rather than constraining local aspects of function. These insights offer new strategies for characterizing individual aberrations in brain function and evaluating heritability of brain networks.

scholarly journals Aberrant Brain Functional Connectivity Related to Insulin Resistance in Type 2 Diabetes: A Resting-State fMRI Study

Diabetes Care ◽  
2014 ◽  
Vol 37 (6) ◽  
pp. 1689-1696 ◽  
Author(s):  
Yu-Chen Chen ◽  
Yun Jiao ◽  
Ying Cui ◽  
Song-An Shang ◽  
Jie Ding ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Fmri Study ◽  
Brain Functional Connectivity

scholarly journals Wrist and finger motor representations embedded in the cerebral and cerebellar resting-state activation

2021 ◽  
Author(s):  
Toshiki Kusano ◽  
Hiroki Kurashige ◽  
Isao Nambu ◽  
Yoshiya Moriguchi ◽  
Takashi Hanakawa ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Body Part ◽  
Resting State Fmri ◽  
Body Parts ◽  
Finger Movements ◽  
Multiple Components ◽  
Brain Activity Pattern ◽  
Motor Representations ◽  
The Brain

AbstractSeveral functional magnetic resonance imaging (fMRI) studies have demonstrated that resting-state brain activity consists of multiple components, each corresponding to the spatial pattern of brain activity induced by performing a task. Especially in a movement task, such components have been shown to correspond to the brain activity pattern of the relevant anatomical region, meaning that the voxels of pattern that are cooperatively activated while using a body part (e.g., foot, hand, and tongue) also behave cooperatively in the resting state. However, it is unclear whether the components involved in resting-state brain activity correspond to those induced by the movement of discrete body parts. To address this issue, in the present study, we focused on wrist and finger movements in the hand, and a cross-decoding technique trained to discriminate between the multi-voxel patterns induced by wrist and finger movement was applied to the resting-state fMRI. We found that the multi-voxel pattern in resting-state brain activity corresponds to either wrist or finger movements in the motor-related areas of each hemisphere of the cerebrum and cerebellum. These results suggest that resting-state brain activity in the motor-related areas consists of the components corresponding to the elementary movements of individual body parts. Therefore, the resting-state brain activity possibly has a finer structure than considered previously.

Depression and Inflammatory Markers in Veterans With Multiple Sclerosis

2021 ◽  
pp. 109980042110500
Author(s):  
Pamela Newland ◽  
Yelyzaveta Basan ◽  
Ling Chen ◽  
Gregory Wu
Keyword(s):  
Multiple Sclerosis ◽  
Inflammatory Markers ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
The United States ◽  
Biological Mechanisms ◽  
The Central Nervous System ◽  
Brain And Spinal Cord ◽  
The Brain

Multiple sclerosis (MS), an inflammatory neurodegenerative disease of the central nervous system (CNS), afflicts over one per thousand people in the United States. The pathology of MS typically involves lesions in several regions, including the brain and spinal cord. The manifestation of MS is variable and carries great potential to negatively impact quality of life (QOL). Evidence that inflammatory markers are related to depression in MS is accumulating. However, there are barriers in precisely identifying the biological mechanisms underlying depression and inflammation. Analysis of cytokines provides one promising approach for understanding the mechanisms that may contribute to MS symptoms. Methods: In this pilot study, we measured salivary levels of interleukin (IL)-6, IL-1beta (β), and IL-10 in 24 veterans with MS. Descriptive statistics were reported and Pearson correlation coefficients were obtained between cytokines and depression. Results: The anti-inflammatory cytokine IL-10 was significantly negatively associated with depression in veterans with MS (r = −0.47, p = .024). Conclusion: Cytokines may be useful for elucidating biological mechanisms associated with the depression and a measure for nurses caring for veterans with MS.

scholarly journals Resting State fMRI: A Valuable Tool for Studying Cognitive Dysfunction in PD

2018 ◽  
Vol 2018 ◽  
pp. 1-5 ◽  
Author(s):  
Kai Li ◽  
Wen Su ◽  
Shu-Hua Li ◽  
Ying Jin ◽  
Hai-Bo Chen
Keyword(s):  
Cognitive Impairment ◽  
Cognitive Dysfunction ◽  
Cognitive Deficits ◽  
Resting State ◽  
Lewy Bodies ◽  
Resting State Fmri ◽  
Underlying Mechanism ◽  
Research Field ◽  
Functional Magnetic Resonance ◽  
Positron Emission

Cognitive impairment is a common disabling symptom in PD. Unlike motor symptoms, the mechanism underlying cognitive dysfunction in Parkinson’s disease (PD) remains unclear and may involve multiple pathophysiological processes. Resting state functional magnetic resonance imaging (rs-fMRI) is a fast-developing research field, and its application in cognitive impairments in PD is rapidly growing. In this review, we summarize rs-fMRI studies on cognitive function in PD and discuss the strong potential of rs-fMRI in this area. rs-fMRI can help reveal the pathophysiology of cognitive symptoms in PD, facilitate early identification of PD patients with cognitive impairment, distinguish PD dementia from dementia with Lewy bodies, and monitor and guide treatment for cognitive impairment in PD. In particular, ongoing and future longitudinal studies would enhance the ability of rs-fMRI in predicting PD dementia. In combination with other modalities such as positron emission tomography, rs-fMRI could give us more information on the underlying mechanism of cognitive deficits in PD.

scholarly journals Brain Function Assessment of Patients with Multiple Sclerosis in the Expanded Disability Status Scale

2020 ◽  
Vol 22 (1) ◽  
pp. 31-35
Author(s):  
Ricardo N. Alonso ◽  
Maria B. Eizaguirre ◽  
Berenice Silva ◽  
Maria C. Pita ◽  
Cecilia Yastremiz ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Brain Function ◽  
Cognitive Assessment ◽  
Functional System ◽  
Expanded Disability Status Scale ◽  
Disability Status ◽  
Before And After ◽  
Survey Results ◽  
Edss Score ◽  
The Brain

Abstract Background: There is no consensus regarding assessment of the brain function functional system (FS) of the Expanded Disability Status Scale (EDSS) in patients with multiple sclerosis (MS). We sought to describe brain function FS assessment criteria used by Argentinian neurologists and, based on the results, propose redefined brain function FS criteria. Methods: A structured survey was conducted of 113 Argentinian neurologists. Considering the survey results, we decided to redefine the brain function FS scoring using the Brief International Cognitive Assessment for MS (BICAMS) battery. For 120 adult patients with MS we calculated the EDSS score without brain function FS (basal EDSS) and compared it with the EDSS score after adding the modified brain function FS (modified EDSS). Results: Of the 93 neurologists analyzed, 14% reported that they did not assess brain function FS, 35% reported that they assessed it through a nonstructured interview, and the remainder used other tools. Significant differences were found in EDSS scores before and after the inclusion of BICAMS (P < .001). Redefining the brain function FS, 15% of patients modified their basal EDSS score, as did 20% of those with a score of 4.0 or less. Conclusions: The survey results show the importance of unifying the brain function FS scoring criteria in calculating the EDSS score. While allowing more consistent brain function FS scoring, including the modified brain function FS led to a change in EDSS score in many patients, particularly in the lower range of EDSS scores. Considering the relevance of the EDSS for monitoring patients with MS and for decision making, it is imperative to further validate the modified brain function FS scoring.

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