scholarly journals Altered Functional Connectivity in White and Gray Matter in Patients With Multiple Sclerosis

2020 ◽  
Vol 14 ◽  
Author(s):  
Jing Huang ◽  
Muwei Li ◽  
Qiongge Li ◽  
Zhipeng Yang ◽  
Bowen Xin ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Functional Connectivity ◽  
Gray Matter ◽  
Correlation Coefficients ◽  
Temporal Correlation ◽  
Resting State Fmri ◽  
Lesion Volume ◽  
Healthy Controls ◽  
Functional Changes ◽  
Time Courses

Background: Functional magnetic resonance imaging (fMRI) has been widely used to assess neural activity changes in gray matter (GM) in patients with multiple sclerosis (MS); however, brain function alterations in white matter (WM) relatively remain under-explored.Purpose: This work aims to identify the functional connectivity in both the WM and the GM of patients with MS using fMRI and the correlations between these functional changes and cumulative disability as well as the lesion ratio.Materials and Methods: For this retrospective study, 37 patients with clinically definite MS and 43 age-matched healthy controls were included between 2010 and 2014. Resting-state fMRI was performed. The WFU Pick and JHU Eve atlases were used to define 82 GM and 48 WM regions in common spaces, respectively. The time courses of blood oxygen level-dependent (BOLD) signals were averaged over each GM or WM region. The averaged time courses for each pair of GM and WM regions were correlated. All 82 × 48 correlations for each subject formed a functional correlation matrix.Results: Compared with the healthy controls, the MS patients had a decreased temporal correlation between the WM and the GM regions. Five WM bundles and four GM regions had significantly decreased mean correlation coefficients (CCs). More specifically, the WM functional alterations were negatively correlated with the lesion volume in the bilateral fornix, and the mean GM-averaged CCs of the WM bundles were inversely correlated with the lesion ratio (r = −0.36, P = 0.012). No significant correlation was found between WM functional alterations and the paced auditory serial addition test score, Expanded Disease Severity Scale score, and Multiple Sclerosis Severity Score (MSSS) in MS.Conclusions: These findings highlight current gaps in our knowledge of the WM functional alterations in patients with MS and may link WM function with pathological mechanisms.

scholarly journals Disrupted White Matter Functional Connectivity With the Cerebral Cortex in Migraine Patients

2022 ◽  
Vol 15 ◽  
Author(s):  
Zhaoxia Qin ◽  
Huai-Bin Liang ◽  
Muwei Li ◽  
Yue Hu ◽  
Jing Wu ◽  
...  
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Gray Matter ◽  
Resting State ◽  
Correlation Coefficients ◽  
Blood Oxygenation ◽  
Healthy Controls ◽  
Functional Connections ◽  
Time Courses ◽  
Cortical Regions

Background: In attempts to understand the migraine patients’ overall brain functional architecture, blood oxygenation level-dependent (BOLD) signals in the white matter (WM) and gray matter (GM) were considered in the current study. Migraine, a severe and multiphasic brain condition, is characterized by recurrent attacks of headaches. BOLD fluctuations in a resting state exhibit similar temporal and spectral profiles in both WM and GM. It is feasible to explore the functional interactions between WM tracts and GM regions in migraine.Methods: Forty-eight migraineurs without aura (MWoA) and 48 healthy controls underwent resting-state functional magnetic resonance imaging. Pearson’s correlations between the mean time courses of 48 white matter (WM) bundles and 82 gray matter (GM) regions were computed for each subject. Two-sample t-tests were performed on the Pearson’s correlation coefficients (CC) to compare the differences between the MWoA and healthy controls in the GM-averaged CC of each bundle and the WM-averaged CC of each GM region.Results: The MWoAs exhibited an overall decreased average temporal CC between BOLD signals in 82 GM regions and 48 WM bundles compared with healthy controls, while little was increased. In particular, WM bundles such as left anterior corona radiata, left external capsule and bilateral superior longitudinal fasciculus had significantly decreased mean CCs with GM in MWoA. On the other hand, 16 GM regions had significantly decreased mean CCs with WM in MWoA, including some areas that are parts of the somatosensory regions, auditory cortex, temporal areas, frontal areas, cingulate cortex, and parietal cortex.Conclusion: Decreased functional connections between WM bundles and GM regions might contribute to disrupted functional connectivity between the parts of the pain processing pathway in MWoAs, which indicated that functional and connectivity abnormalities in cortical regions may not be limited to GM regions but are instead associated with functional abnormalities in WM tracts.

scholarly journals Word-finding difficulty is a prevalent disease-related deficit in early multiple sclerosis

2019 ◽  
Vol 26 (13) ◽  
pp. 1752-1764 ◽  
Author(s):  
Rachel Brandstadter ◽  
Michelle Fabian ◽  
Victoria M Leavitt ◽  
Stephen Krieger ◽  
Anusha Yeshokumar ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Gray Matter ◽  
Objective Assessment ◽  
Lesion Volume ◽  
Healthy Controls ◽  
Patient Report ◽  
Word Finding ◽  
Cognitive Complaint ◽  
Two Samples ◽  
Patient Reported

Background: Persons with multiple sclerosis (MS) commonly report word-finding difficulty clinically, yet this language deficit remains underexplored. Objective: To investigate the prevalence and nature of word-finding difficulty in persons with early MS on three levels: patient report, cognitive substrates, and neuroimaging. Methods: Two samples of early MS patients ( n = 185 and n = 55; ⩽5 years diagnosed) and healthy controls ( n = 50) reported frequency/severity of cognitive deficits and underwent objective assessment with tasks of rapid automatized naming (RAN), measuring lexical access speed, memory, word generation, and cognitive efficiency. High-resolution brain magnetic resonance imaging (MRI) derived measurements of regional cortical thickness, global and deep gray matter volume, and T2 lesion volume. Relationships among patient-reported word-finding difficulty, cognitive performance, and neural correlates were examined. Results: Word-finding difficulty was the most common cognitive complaint of MS patients and the only complaint reported more by patients than healthy controls. Only RAN performance discriminated MS patients with subjective word-finding deficits from those without subjective complaints and from healthy controls. Thinner left parietal cortical gray matter independently predicted impaired RAN performance, driven primarily by the left precuneus. Conclusion: Three levels of evidence (patient-report, objective behavior, regional gray matter) support word-finding difficulty as a prevalent, measurable, disease-related deficit in early MS linked to left parietal cortical thinning.

scholarly journals Insulin Resistance-Associated Interhemispheric Functional Connectivity Alterations in T2DM: A Resting-State fMRI Study

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Wenqing Xia ◽  
Shaohua Wang ◽  
Andrea M. Spaeth ◽  
Hengyi Rao ◽  
Pin Wang ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Functional Connectivity ◽  
Resting State ◽  
Correlation Coefficients ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Model Assessment ◽  
Healthy Controls ◽  
Resting State Functional Connectivity

We aim to investigate whether decreased interhemispheric functional connectivity exists in patients with type 2 diabetes mellitus (T2DM) by using resting-state functional magnetic resonance imaging (rs-fMRI). In addition, we sought to determine whether interhemispheric functional connectivity deficits associated with cognition and insulin resistance (IR) among T2DM patients. We compared the interhemispheric resting state functional connectivity of 32 T2DM patients and 30 healthy controls using rs-fMRI. Partial correlation coefficients were used to detect the relationship between rs-fMRI information and cognitive or clinical data. Compared with healthy controls, T2DM patients showed bidirectional alteration of functional connectivity in several brain regions. Functional connectivity values in the middle temporal gyrus (MTG) and in the superior frontal gyrus were inversely correlated with Trail Making Test-B score of patients. Notably, insulin resistance (log homeostasis model assessment-IR) negatively correlated with functional connectivity in the MTG of patients. In conclusion, T2DM patients exhibit abnormal interhemispheric functional connectivity in several default mode network regions, particularly in the MTG, and such alteration is associated with IR. Alterations in interhemispheric functional connectivity might contribute to cognitive dysfunction in T2DM patients.

scholarly journals Altered Dynamic Functional Connectivity of Cuneus in Schizophrenia Patients: A Resting-State fMRI Study

2021 ◽  
Vol 11 (23) ◽  
pp. 11392
Author(s):  
Charles Okanda Nyatega ◽  
Li Qiang ◽  
Mohammed Jajere Adamu ◽  
Ayesha Younis ◽  
Halima Bello Kawuwa
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Low Frequency ◽  
Temporal Correlation ◽  
Resting State Fmri ◽  
Mental Condition ◽  
Middle Temporal Gyrus ◽  
Healthy Controls ◽  
Dynamic Functional Connectivity ◽  
Sliding Windows

Objective: Schizophrenia (SZ) is a functional mental condition that has a significant impact on patients’ social lives. As a result, accurate diagnosis of SZ has attracted researchers’ interest. Based on previous research, resting-state functional magnetic resonance imaging (rsfMRI) reported neural alterations in SZ. In this study, we attempted to investigate if dynamic functional connectivity (dFC) could reveal changes in temporal interactions between SZ patients and healthy controls (HC) beyond static functional connectivity (sFC) in the cuneus, using the publicly available COBRE dataset. Methods: Sliding windows were applied to 72 SZ patients’ and 74 healthy controls’ (HC) rsfMRI data to generate temporal correlation maps and, finally, evaluate mean strength (dFC-Str), variability (dFC-SD and ALFF) in each window, and the dwelling time. The difference in functional connectivity (FC) of the cuneus between two groups was compared using a two-sample t-test. Results: Our findings demonstrated decreased mean strength connectivity between the cuneus and calcarine, the cuneus and lingual gyrus, and between the cuneus and middle temporal gyrus (TPOmid) in subjects with SZ. Moreover, no difference was detected in variability (standard deviation and the amplitude of low-frequency fluctuation), the dwelling times of all states, or static functional connectivity (sFC) between the groups. Conclusions: Our verdict suggest that dynamic functional connectivity analyses may play crucial roles in unveiling abnormal patterns that would be obscured in static functional connectivity, providing promising impetus for understanding schizophrenia disease.

Association of Age at Onset With Gray Matter Volume and White Matter Microstructural Abnormalities in People With Multiple Sclerosis

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012869
Author(s):  
Raffaello Bonacchi ◽  
Alessandro Meani ◽  
Elisabetta Pagani ◽  
Olga Marchesi ◽  
Andrea Falini ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Gray Matter ◽  
Linear Models ◽  
Gray Matter Volume ◽  
Age At Onset ◽  
Healthy Controls ◽  
Compensatory Mechanisms ◽  
Cross Sectional ◽  
Matter Volume

Objective:To investigate whether age at onset influences brain gray matter volume (GMV) and white matter (WM) microstructural abnormalities in adult multiple sclerosis (MS) patients, given its influence on clinical phenotype and disease course.Method:In this hypothesis-driven cross-sectional study, we enrolled 67 pediatric-onset MS (POMS) patients and 143 sex- and disease duration (DD)-matched randomly-selected adult-onset MS (AOMS) patients, together with 208 healthy controls. All subjects underwent neurological evaluation and 3T MRI acquisition. MRI variables were standardized based on healthy controls, to remove effects of age and sex. Associations with DD in POMS and AOMS patients were studied with linear models. Time to reach clinical and MRI milestones was assessed with product-limit approach.Results:At DD=1 year, GMV and WM fractional anisotropy (FA) were abnormal in AOMS but not in POMS patients. Significant interaction of age at onset (POMS vs AOMS) into the association with DD was found for GMV and WM FA. The crossing point of regression lines in POMS and AOMS patients was at 20 years of DD for GMV and 14 for WM FA. For POMS and AOMS patients, median DD was 29 and 19 years to reach Expanded Disability Status Scale=3 (p<0.001), 31 and 26 years to reach abnormal Paced Auditory Serial Addition Task-3 (p=0.01), 24 and 18 years to reach abnormal GMV (p=0.04), and 19 and 17 years to reach abnormal WM FA (p=0.36).Conclusions:Younger patients are initially resilient to MS-related damage. Then, compensatory mechanisms start failing with loss of WM integrity, followed by GM atrophy and finally disability.

Gray matter trophism, cognitive impairment, and depression in patients with multiple sclerosis

2017 ◽  
Vol 23 (14) ◽  
pp. 1864-1874 ◽  
Author(s):  
Emanuele Pravatà ◽  
Maria A Rocca ◽  
Paola Valsasina ◽  
Gianna C Riccitelli ◽  
Claudio Gobbi ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Gray Matter ◽  
Rating Scale ◽  
Three Dimensional ◽  
Emotional Behavior ◽  
Cortical Atrophy ◽  
Lesion Volume ◽  
Cortical Thinning ◽  
C Statistic

Background: Cognitive impairment and depression frequently affects patients with multiple sclerosis (MS). However, the relationship between the occurrence of depression and cognitive impairment and the development of cortical atrophy has not been fully elucidated yet. Objectives: To investigate the association of cortical and deep gray matter (GM) volume with depression and cognitive impairment in MS. Methods: Three-dimensional (3D) T1-weighted scans were obtained from 126 MS patients and 59 matched healthy controls. Cognitive impairment was assessed using the Brief Repeatable Battery of Neuropsychological Tests and depression with the Montgomery-Asberg Depression Rating Scale (MADRS). Using FreeSurfer and FIRST software, we assessed cortical thickness (CTh) and deep GM volumetry. Magnetic resonance imaging (MRI) variables explaining depression and cognitive impairment were investigated using factorial and classification analysis. Multivariate regression models correlated GM abnormalities with symptoms severity. Results: Compared with controls, MS patients exhibited widespread bilateral cortical thinning involving all brain lobes. Depressed MS showed selective CTh decrease in fronto-temporal regions, whereas cognitive impairment MS exhibited widespread fronto-parietal cortical and subcortical GM atrophy. Frontal cortical thinning was the best predictor of depression ( C-statistic = 0.7), whereas thinning of the right precuneus and high T2 lesion volume best predicted cognitive impairment ( C-statistic = 0.8). MADRS severity correlated with right entorhinal cortex thinning, whereas cognitive impairment severity correlated with left entorhinal and thalamus atrophy. Conclusion: MS-related depression is linked to circumscribed CTh changes in areas deputed to emotional behavior, whereas cognitive impairment is correlated with cortical and subcortical GM atrophy of circuits involved in cognition.

scholarly journals Long-range connections are more severely damaged and relevant for cognition in multiple sclerosis

Brain ◽  
2019 ◽  
Vol 143 (1) ◽  
pp. 150-160 ◽  
Author(s):  
Kim A Meijer ◽  
Martijn D Steenwijk ◽  
Linda Douw ◽  
Menno M Schoonheim ◽  
Jeroen J G Geurts
Keyword(s):  
Multiple Sclerosis ◽  
Functional Connectivity ◽  
Fractional Anisotropy ◽  
Long Range ◽  
Short Range ◽  
Brain Regions ◽  
Healthy Controls ◽  
Network Efficiency ◽  
Structural Network ◽  
The Impact

Abstract An efficient network such as the human brain features a combination of global integration of information, driven by long-range connections, and local processing involving short-range connections. Whether these connections are equally damaged in multiple sclerosis is unknown, as is their relevance for cognitive impairment and brain function. Therefore, we cross-sectionally investigated the association between damage to short- and long-range connections with structural network efficiency, the functional connectome and cognition. From the Amsterdam multiple sclerosis cohort, 133 patients (age = 54.2 ± 9.6) with long-standing multiple sclerosis and 48 healthy controls (age = 50.8 ± 7.0) with neuropsychological testing and MRI were included. Structural connectivity was estimated from diffusion tensor images using probabilistic tractography (MRtrix 3.0) between pairs of brain regions. Structural connections were divided into short- (length &lt; quartile 1) and long-range (length &gt; quartile 3) connections, based on the mean distribution of tract lengths in healthy controls. To determine the severity of damage within these connections, (i) fractional anisotropy as a measure for integrity; (ii) total number of fibres; and (iii) percentage of tract affected by lesions were computed for each connecting tract and averaged for short- and long-range connections separately. To investigate the impact of damage in these connections for structural network efficiency, global efficiency was computed. Additionally, resting-state functional connectivity was computed between each pair of brain regions, after artefact removal with FMRIB’s ICA-based X-noiseifier. The functional connectivity similarity index was computed by correlating individual functional connectivity matrices with an average healthy control connectivity matrix. Our results showed that the structural network had a reduced efficiency and integrity in multiple sclerosis relative to healthy controls (both P &lt; 0.05). The long-range connections showed the largest reduction in fractional anisotropy (z = −1.03, P &lt; 0.001) and total number of fibres (z = −0.44, P &lt; 0.01), whereas in the short-range connections only fractional anisotropy was affected (z = −0.34, P = 0.03). Long-range connections also demonstrated a higher percentage of tract affected by lesions than short-range connections, independent of tract length (P &lt; 0.001). Damage to long-range connections was more strongly related to structural network efficiency and cognition (fractional anisotropy: r = 0.329 and r = 0.447. number of fibres r = 0.321 and r = 0.278. and percentage of lesions: r = −0.219; r = −0.426, respectively) than damage to short-range connections. Only damage to long-distance connections correlated with a more abnormal functional network (fractional anisotropy: r = 0.226). Our findings indicate that long-range connections are more severely affected by multiple sclerosis-specific damage than short-range connections. Moreover compared to short-range connections, damage to long-range connections better explains network efficiency and cognition.

Brain activity at rest: a multiscale hierarchical functional organization

2011 ◽  
Vol 105 (6) ◽  
pp. 2753-2763 ◽  
Author(s):  
Gaëlle Doucet ◽  
Mikaël Naveau ◽  
Laurent Petit ◽  
Nicolas Delcroix ◽  
Laure Zago ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Functional Organization ◽  
Brain Activity ◽  
Correlation Coefficients ◽  
Temporal Correlation ◽  
Hierarchical Level ◽  
Spontaneous Brain Activity ◽  
Dorsal Attentional Network

Spontaneous brain activity was mapped with functional MRI (fMRI) in a sample of 180 subjects while in a conscious resting-state condition. With the use of independent component analysis (ICA) of each individual fMRI signal and classification of the ICA-defined components across subjects, a set of 23 resting-state networks (RNs) was identified. Functional connectivity between each pair of RNs was assessed using temporal correlation analyses in the 0.01- to 0.1-Hz frequency band, and the corresponding set of correlation coefficients was used to obtain a hierarchical clustering of the 23 RNs. At the highest hierarchical level, we found two anticorrelated systems in charge of intrinsic and extrinsic processing, respectively. At a lower level, the intrinsic system appears to be partitioned in three modules that subserve generation of spontaneous thoughts (M1a; default mode), inner maintenance and manipulation of information (M1b), and cognitive control and switching activity (M1c), respectively. The extrinsic system was found to be made of two distinct modules: one including primary somatosensory and auditory areas and the dorsal attentional network (M2a) and the other encompassing the visual areas (M2b). Functional connectivity analyses revealed that M1b played a central role in the functioning of the intrinsic system, whereas M1c seems to mediate exchange of information between the intrinsic and extrinsic systems.

High-Order Functional Connectivity Network for Differential Diagnosis of Depression

2019 ◽  
Vol 9 (6) ◽  
pp. 1095-1102
Author(s):  
Jian Yang ◽  
Xu Mao ◽  
Ning Liu ◽  
Ning Zhong
Keyword(s):  
Time Series ◽  
Differential Diagnosis ◽  
Functional Connectivity ◽  
Resting State ◽  
Correlation Time ◽  
Time Window ◽  
Resting State Fmri ◽  
High Order ◽  
Healthy Controls ◽  
Resting State Functional Connectivity

Resting-state functional connectivity (FC) changes dynamically and major depressive disorder (MDD) has abnormality in functional connectivity networks (FCNs), but few existing resting-state fMRI study on MDD utilizes the dynamics, especially for identifying depressive individuals from healthy controls. In this paper, we propose a methodological procedure for differential diagnosis of depression, called HN3D, which is based on high-order functional connectivity networks (HFCN). Firstly, HN3D extracts time series by independent component analysis, and partitions them into overlapped short series by sliding time window. Secondly, it constructs a FCN for each time window and concatenates correlation matrices of all FCNs to generate correlation time series. Then, correlation time series are grouped into different clusters and high-order correlations for HFCN is calculated based on their means. Finally, graph based features of HFCNs are extracted and selected for a linear discriminative classifier. Tested on 21 healthy controls and 20 MDD patients, HN3D achieved its best 100% classification accuracy, which is much higher than results based on stationary FCNs. In addition, most discriminative components of HN3D locate in default mode network and visual network, which are consistent with existing stationary-based results on depression. Though HN3D needs to be studied further, it is helpful for the differential diagnosis of depression and might have potentiality in identifying relevant biomarkers.

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