scholarly journals Multiple sclerosis reduces synchrony of the magnocellular pathway

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255324
Author(s):  
Masoud Seraji ◽  
Maryam Mohebbi ◽  
Amirhossein Safari ◽  
Bart Krekelberg
Keyword(s):  
Multiple Sclerosis ◽  
Functional Connectivity ◽  
Disease Progression ◽  
Information Transfer ◽  
Demyelinating Disease ◽  
Clinical Symptoms ◽  
Visual Stimuli ◽  
Clustering Coefficient ◽  
Magnocellular Pathway ◽  
Characteristic Path Length

Multiple Sclerosis (MS) is an autoimmune demyelinating disease that damages the insulation of nerve cell fibers in the brain and spinal cord. In the visual system, this demyelination results in a robust delay of visually evoked potentials (VEPs), even in the absence of overt clinical symptoms such as blurred vision. VEPs, therefore, offer an avenue for early diagnosis, monitoring disease progression, and, potentially, insight into the differential impairment of specific pathways. A primary hypothesis has been that visual stimuli driving the magno-, parvo-, and konio-cellular pathways should lead to differential effects because these pathways differ considerably in terms of myelination. Experimental tests of this hypothesis, however, have led to conflicting results. Some groups reported larger latency effects for chromatic stimuli, while others found equivalent effects across stimulus types. We reasoned that this lack of pathway specificity could, at least in part, be attributed to the relatively coarse measure of pathway impairment afforded by the latency of a VEP. We hypothesized that network synchrony could offer a more sensitive test of pathway impairments. To test this hypothesis, we analyzed the synchrony of occipital electroencephalography (EEG) signals during the presentation of visual stimuli designed to bias activity to one of the three pathways. Specifically, we quantified synchrony in the occipital EEG using two graph-theoretic measures of functional connectivity: the characteristic path length (L; a measure of long-range connectivity) and the clustering coefficient (CC; a measure of short-range connectivity). Our main finding was that L and CC were both smaller in the MS group than in controls. Notably, this change in functional connectivity was limited to the magnocellular pathway. The effect sizes (Hedge’s g) were 0.89 (L) and 1.26 (CC) measured with magno stimuli. Together, L and CC define the small-world nature of a network, and our finding can be summarized as a reduction in the small-worldness of the magnocellular network. We speculate that the reduced efficiency of information transfer associated with a reduction in small-worldness could underlie visual deficits in MS. Relating these measures to differential diagnoses and disease progression is an important avenue for future work.

Structural constraints of functional connectivity drive cognitive impairment in the early stages of multiple sclerosis

2020 ◽  
pp. 135245852097180
Author(s):  
Ismail Koubiyr ◽  
Mathilde Deloire ◽  
Bruno Brochet ◽  
Pierre Besson ◽  
Julie Charré-Morin ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Functional Connectivity ◽  
Structure Function ◽  
Diffusion Tensor ◽  
Brain Network ◽  
Clustering Coefficient ◽  
Functional Coupling ◽  
Structural Constraints ◽  
Characteristic Path Length ◽  
Functional Connections

Background: The relationship between structural and functional deficits in multiple sclerosis (MS) is unclear. Objective: This study explored structure-function relationships during the 5 years following a clinically isolated syndrome and their role in cognitive performance. Methods: Thirty-two patients were enrolled after their first neurological episode suggestive of MS and followed for 5 years, along with 10 matched healthy controls. We assessed structural (using diffusion tensor imaging) and functional (using resting-state functional magnetic resonance imaging (fMRI)) brain network metrics, clinical and cognitive scores at each follow-up visit. Structural–functional coupling, calculated as the correlation coefficient between strengths of structural and functional networks, was used to assess structure–function relationships. Results: Structural clustering coefficient was significantly increased after 5 years, whereas characteristic path length decreased. Structural connections decreased after 1 year and increased after 5 years. Functional connections and related path lengths were decreased after 5 years. Structural–functional coupling had increased significantly after 5 years. This structural–functional coupling was associated with cognitive and clinical evolution, with stronger coupling associated with a decline in both domains. Conclusion: Our findings provide novel biological evidence that MS leads to a more constrained anatomical-dependant functional connectivity. The collapse of this network seems to lead to both cognitive worsening and clinical disability.

Gene Therapy Approaches in an Autoimmune Demyelinating Disease: Multiple Sclerosis

2020 ◽  
Vol 19 (6) ◽  
pp. 376-385
Author(s):  
Md. A. Islam ◽  
Shoumik Kundu ◽  
Rosline Hassan
Keyword(s):  
Multiple Sclerosis ◽  
Gene Therapy ◽  
Disease Progression ◽  
Demyelinating Disease ◽  
Human Subjects ◽  
Mice Model ◽  
Focal Lesions ◽  
Protective Function ◽  
Monocytes And Macrophages ◽  
Specific Symptoms

Multiple Sclerosis (MS) is the most common autoimmune demyelinating disease of the Central Nervous System (CNS). It is a multifactorial disease which develops in an immune-mediated way under the influences of both genetic and environmental factors. Demyelination is observed in the brain and spinal cord leading to neuro-axonal damage in patients with MS. Due to the infiltration of different immune cells such as T-cells, B-cells, monocytes and macrophages, focal lesions are observed in MS. Currently available medications treating MS are mainly based on two strategies; i) to ease specific symptoms or ii) to reduce disease progression. However, these medications tend to induce different adverse effects with limited therapeutic efficacy due to the protective function of the blood-brain barrier. Therefore, researchers have been working for the last four decades to discover better solutions by introducing gene therapy approaches in treating MS generally by following three strategies, i) prevention of specific symptoms, ii) halt or reverse disease progression and iii) heal CNS damage by promoting remyelination and axonal repair. In last two decades, there have been some remarkable successes of gene therapy approaches on the experimental mice model of MS - experimental autoimmune encephalomyelitis (EAE) which suggests that it is not far that the gene therapy approaches would start in human subjects ensuring the highest levels of safety and efficacy. In this review, we summarised the gene therapy approaches attempted in different animal models towards treating MS.

Discrepancies in the interpretation of clinical symptoms and signs in the diagnosis of multiple sclerosis. A proposal for standardization

2005 ◽  
Vol 11 (2) ◽  
pp. 227-231 ◽  
Author(s):  
Bernard MJ Uitdehaag ◽  
Ludwig Kappos ◽  
Lars Bauer ◽  
Mark S Freedman ◽  
David Miller ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Demyelinating Disease ◽  
Clinical Symptoms ◽  
Clinical Findings ◽  
Large Trial ◽  
Mri Findings ◽  
Mcdonald Criteria ◽  
Magnetic Resonance Imaging Mri ◽  
Eligibility Assessment

The new McDonald diagnostic criteria for multiple sclerosis (MS) incorporate detailed criteria for the interpretation and classification of magnetic resonance imaging (MRI) findings, but, in contrast, provide no instructions for the interpretation of clinical findings. Because MS according to the McDonald criteria is one of the primary endpoints in a large trial enrolling patients after the first manifestation suggestive for a demyelinating disease (BENEFIT study), it was decided to organize a centralized eligibility assessment for this trial. During this eligibility assessment it was observed that there were marked inconsistencies in the decisions of participating neurologists with respect to the classification of clinical symptoms as being caused by one or more lesions provoking discussions in about one in every five patients. This paper describes these inconsistencies and their sources, and recommends a systematic approach that attempts to reduce the variability in interpreting clinical findings.

scholarly journals Altered Functional Connectivity after Epileptic Seizure Revealed by Scalp EEG

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yi Liang ◽  
Chunli Chen ◽  
Fali Li ◽  
Dezhong Yao ◽  
Peng Xu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Local Area ◽  
Brain Network ◽  
Fuzzy Entropy ◽  
Clustering Coefficient ◽  
Characteristic Path Length ◽  
Functional Brain Network ◽  
Before And After

Epileptic seizures are considered to be a brain network dysfunction, and chronic recurrent seizures can cause severe brain damage. However, the functional brain network underlying recurrent epileptic seizures is still left unveiled. This study is aimed at exploring the differences in a related brain activity before and after chronic repetitive seizures by investigating the power spectral density (PSD), fuzzy entropy, and functional connectivity in epileptic patients. The PSD analysis revealed differences between the two states at local area, showing postseizure energy accumulation. Besides, the fuzzy entropies of preseizure in the frontal, central, and temporal regions are higher than that of postseizure. Additionally, attenuated long-range connectivity and enhanced local connectivity were also found. Moreover, significant correlations were found between network metrics (i.e., characteristic path length and clustering coefficient) and individual seizure number. The PSD, fuzzy entropy, and network analysis may indicate that the brain is gradually impaired along with the occurrence of epilepsy, and the accumulated effect of brain impairment is observed in individuals with consecutive epileptic bursts. The findings of this study may provide helpful insights into understanding the network mechanism underlying chronic recurrent epilepsy.

Analysis of Migraine Induced Monitoring Imaging Data by Multilayer Mixed Cluster Detection

2019 ◽  
Vol 9 (6) ◽  
pp. 1278-1283
Author(s):  
Min Shi ◽  
Dong Dong Yang ◽  
Yuan Zhou ◽  
Huan Zhao ◽  
Yu Fang
Keyword(s):  
Complex Network ◽  
Visual Processing ◽  
Brain Function ◽  
Clinical Symptoms ◽  
Clustering Coefficient ◽  
Hill Climbing ◽  
Ensemble Clustering ◽  
Imaging Data ◽  
Characteristic Path Length ◽  
The Difference

The complex network of resting brain function was constructed by graph theory to study the difference of network topology between migraine patients and normal people. The complex network of brain function of the two groups was constructed respectively, and the average clustering coefficient, characteristic path length, small cosmopolitan, homology, median centrality and other measurement parameters of the two groups of complex networks were calculated and compared. The multi-layer hybrid ensemble clustering detection is introduced for data analysis, and the edge connectivity of consensus is optimized by modular analysis combined with hill climbing algorithm to improve the performance of the multi-layer hybrid ensemble clustering detection process driven by modularity. Conclusion: The abnormal areas of resting brain function network in migraine patients are related to pain management, visual processing and sensory relay, the findings of this study are helpful to better explain the clinical symptoms of migraine.

scholarly journals A Pathogenic Role for Myelin-Specific Cd8+ T Cells in a Model for Multiple Sclerosis

2001 ◽  
Vol 194 (5) ◽  
pp. 669-676 ◽  
Author(s):  
Eric S. Huseby ◽  
Denny Liggitt ◽  
Thea Brabb ◽  
Bryan Schnabel ◽  
Claes Öhlén ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
T Cells ◽  
T Cell ◽  
Cd8 T Cells ◽  
Demyelinating Disease ◽  
Clinical Symptoms ◽  
Autoimmune Encephalomyelitis ◽  
Effector Cells ◽  
Cns Autoimmunity ◽  
The Central Nervous System

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) characterized by plaques of infiltrating CD4+ and CD8+ T cells. Studies of MS and experimental autoimmune encephalomyelitis (EAE), an animal model of MS, focus on the contribution of CD4+ myelin-specific T cells. The role of CD8+ myelin-specific T cells in mediating EAE or MS has not been described previously. Here, we demonstrate that myelin-specific CD8+ T cells induce severe CNS autoimmunity in mice. The pathology and clinical symptoms in CD8+ T cell–mediated CNS autoimmunity demonstrate similarities to MS not seen in myelin-specific CD4+ T cell–mediated EAE. These data suggest that myelin-specific CD8+ T cells could function as effector cells in the pathogenesis of MS.

Disruption of Cortical Connectivity during Remifentanil Administration Is Associated with Cognitive Impairment but Not with Analgesia

2015 ◽  
Vol 122 (1) ◽  
pp. 140-149 ◽  
Author(s):  
Ahmad Khodayari-Rostamabad ◽  
Søren S. Olesen ◽  
Carina Graversen ◽  
Lasse P. Malver ◽  
Geana P. Kurita ◽  
...  
Keyword(s):  
Reaction Time ◽  
Functional Connectivity ◽  
Path Length ◽  
Experimental Pain ◽  
Clustering Coefficient ◽  
Cognitive Test ◽  
Characteristic Path Length ◽  
Network Properties ◽  
Continuous Reaction ◽  
Continuous Reaction Time

Abstract Background: The authors investigated the effect of remifentanil administration on resting electroencephalography functional connectivity and its relationship to cognitive function and analgesia in healthy volunteers. Methods: Twenty-one healthy male adult subjects were enrolled in this placebo-controlled double-blind cross-over study. For each subject, 2.5 min of multichannel electroencephalography recording, a cognitive test of sustained attention (continuous reaction time), and experimental pain scores to bone-pressure and heat stimuli were collected before and after infusion of remifentanil or placebo. A coherence matrix was calculated from the electroencephalogram, and three graph-theoretical measures (characteristic path-length, mean clustering coefficient, and relative small-worldness) were extracted to characterize the overall cortical network properties. Results: Compared to placebo, most graph-theoretical measures were significantly altered by remifentanil at the alpha and low beta range (8 to 18 Hz; all P < 0.001). Taken together, these alterations were characterized by an increase in the characteristic path-length (alpha 17% and low beta range 24%) and corresponding decrements in mean clustering coefficient (low beta range −25%) and relative small-worldness (alpha −17% and low beta range −42%). Changes in characteristic path-lengths after remifentanil infusion were correlated to the continuous reaction time index (r = −0.57; P = 0.009), while no significant correlations between graph-theoretical measures and experimental pain tests were seen. Conclusions: Remifentanil disrupts the functional connectivity network properties of the electroencephalogram. The findings give new insight into how opioids interfere with the normal brain functions and have the potential to be biomarkers for the sedative effects of opioids in different clinical settings.

scholarly journals Proteomics of Multiple Sclerosis: Inherent Issues in Defining the Pathoetiology and Identifying (Early) Biomarkers

2021 ◽  
Vol 22 (14) ◽  
pp. 7377
Author(s):  
Monokesh K. Sen ◽  
Mohammed S. M. Almuslehi ◽  
Peter J. Shortland ◽  
David A. Mahns ◽  
Jens R. Coorssen
Keyword(s):  
Multiple Sclerosis ◽  
Animal Models ◽  
Demyelinating Disease ◽  
Clinical Symptoms ◽  
Literature Mining ◽  
Targeted Therapeutics ◽  
Single Model ◽  
Human Central Nervous System ◽  
Early Biomarkers ◽  
Analytical Approaches

Multiple Sclerosis (MS) is a demyelinating disease of the human central nervous system having an unconfirmed pathoetiology. Although animal models are used to mimic the pathology and clinical symptoms, no single model successfully replicates the full complexity of MS from its initial clinical identification through disease progression. Most importantly, a lack of preclinical biomarkers is hampering the earliest possible diagnosis and treatment. Notably, the development of rationally targeted therapeutics enabling pre-emptive treatment to halt the disease is also delayed without such biomarkers. Using literature mining and bioinformatic analyses, this review assessed the available proteomic studies of MS patients and animal models to discern (1) whether the models effectively mimic MS; and (2) whether reasonable biomarker candidates have been identified. The implication and necessity of assessing proteoforms and the critical importance of this to identifying rational biomarkers are discussed. Moreover, the challenges of using different proteomic analytical approaches and biological samples are also addressed.

scholarly journals Functional Connectivity of EEG in Encephalitis during Slow Biphasic Complexes

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2978
Author(s):  
Giovanni Chiarion ◽  
Luca Mesin
Keyword(s):  
Functional Connectivity ◽  
Path Length ◽  
Inflammatory Diseases ◽  
Clustering Coefficient ◽  
Eeg Rhythms ◽  
Characteristic Path Length ◽  
Slowing Down ◽  
Eeg Functional Connectivity ◽  
Network Patterns ◽  
The Brain

The electroencephalogram (EEG) of patients suffering from inflammatory diseases of the brain may show specific waveforms called slow biphasic complexes (SBC). Recent studies indicated a correlation between the severity of encephalitis and some features of SBCs, such as location, amplitude and frequency of appearance. Moreover, EEG rhythms were found to vary before the onset of an SBC, as if the brain was preparing to the discharge (actually with a slowing down of the EEG oscillation). Here, we investigate possible variations of EEG functional connectivity (FC) in EEGs from pediatric patients with different levels of severity of encephalitis. FC was measured by the maximal crosscorrelation of EEG rhythms in different bipolar channels. Then, the indexes of network patterns (namely strength, clustering coefficient, efficiency and characteristic path length) were estimated to characterize the global behavior when they are measured during SBCs or far from them. EEG traces showed statistical differences in the two conditions: clustering coefficient, efficiency and strength are higher close to an SBC, whereas the characteristic path length is lower. Moreover, for more severe conditions, an increase in clustering coefficient, efficiency and strength and a decrease in characteristic path length were observed in the delta–theta band. These outcomes support the hypothesis that SBCs result from the anomalous coordination of neurons in different brain areas affected by the inflammation process and indicate FC as an additional key for interpreting the EEG in encephalitis patients.

Functional connectivity changes within specific networks parallel the clinical evolution of multiple sclerosis

2013 ◽  
Vol 20 (8) ◽  
pp. 1050-1057 ◽  
Author(s):  
B Basile ◽  
M Castelli ◽  
F Monteleone ◽  
U Nocentini ◽  
C Caltagirone ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Functional Connectivity ◽  
Clinical Symptoms ◽  
Clinical State ◽  
Pathophysiological Mechanism ◽  
Focal Lesions ◽  
Motor Network ◽  
Relapsing Remitting ◽  
Sensory Motor ◽  
Brain Functional Connectivity

Background: In multiple sclerosis (MS), the location of focal lesions does not always correlate with clinical symptoms, suggesting disconnection as a major pathophysiological mechanism. Resting-state (RS) functional magnetic resonance imaging (fMRI) is believed to reflect brain functional connectivity (FC) within specific neuronal networks. Objective: RS-fMRI was used to investigate changes in FC within two critical networks for the understanding of MS disabilities, namely, the sensory-motor network (SMN) and the default-mode network (DMN), respectively, implicated in sensory-motor and cognitive functions. Methods: Thirty-four relapsing–remitting (RR), 14 secondary progressive (SP) MS patients and 25 healthy controls underwent MRI at 3T, including conventional images, T1-weighted volumes, and RS-fMRI sequences. Independent component analysis (ICA) was employed to extract maps of the relevant RS networks for every participant. Group analyses were performed to assess changes in FC within the SMN and DMN in the two MS phenotypes. Results: Increased FC was found in both networks of MS patients. Interestingly, specific changes in either direction were observed also between RR and SP MS groups. Conclusions: FC changes seem to parallel patients’ clinical state and capability of compensating for the severity of clinical/cognitive disabilities.

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