scholarly journals Power spectra reveal distinct BOLD resting‐state time courses in white matter

2021 ◽  
Author(s):  
Muwei Li ◽  
Yurui Gao ◽  
Zhaohua Ding ◽  
John C. Gore
Keyword(s):  
White Matter ◽  
Resting State ◽  
Functional Integration ◽  
Power Spectra ◽  
Spectral Measurements ◽  
State Time ◽  
Power Spectral ◽  
Time Courses ◽  
Two Peaks

AbstractAccurate characterization of the time courses of BOLD signal changes is crucial for the analysis and interpretation of functional MRI data. While several studies have shown that white matter (WM) exhibits distinct BOLD responses evoked by tasks, there have been no comprehensive investigations into the time courses of spontaneous signal fluctuations in WM. We measured the power spectra of the resting‐state time courses in a set of regions within WM identified as showing synchronous signals using independent components analysis. In each component, a clear separation between voxels into two categories was evident, based on their power spectra: one group exhibited a single peak, the other had an additional peak at a higher frequency. Their groupings are location‐specific, and their distributions reflect unique neurovascular and anatomical configurations. Importantly, the two categories of voxels differed in their engagement in functional integration, revealed by differences in the number of inter‐ regional connections based on the two categories separately. Moreover, the power spectral measurements in voxels with two peaks in specific components predict specific human behaviors. Taken together, these findings suggest WM signals are heterogeneous in nature and depend on local structural‐vascular‐functional associations.

scholarly journals Power spectra reveal distinct BOLD resting-state time courses in white matter

2021 ◽  
Vol 118 (44) ◽  
pp. e2103104118
Author(s):  
Muwei Li ◽  
Yurui Gao ◽  
Zhaohua Ding ◽  
John C. Gore
Keyword(s):  
White Matter ◽  
Resting State ◽  
Functional Integration ◽  
Power Spectra ◽  
Blood Oxygen Level Dependent ◽  
Blood Oxygen Level ◽  
State Time ◽  
Components Analysis ◽  
Time Courses

Accurate characterization of the time courses of blood-oxygen-level–dependent (BOLD) signal changes is crucial for the analysis and interpretation of functional MRI data. While several studies have shown that white matter (WM) exhibits distinct BOLD responses evoked by tasks, there have been no comprehensive investigations into the time courses of spontaneous signal fluctuations in WM. We measured the power spectra of the resting-state time courses in a set of regions within WM identified as showing synchronous signals using independent components analysis. In each component, a clear separation between voxels into two categories was evident, based on their power spectra: one group exhibited a single peak, and the other had an additional peak at a higher frequency. Their groupings are location specific, and their distributions reflect unique neurovascular and anatomical configurations. Importantly, the two categories of voxels differed in their engagement in functional integration, revealed by differences in the number of interregional connections based on the two categories separately. Taken together, these findings suggest WM signals are heterogeneous in nature and depend on local structural-vascular-functional associations.

scholarly journals Regular cannabis and alcohol use is associated with resting-state time course power spectra in incarcerated adolescents

2017 ◽  
Vol 178 ◽  
pp. 492-500 ◽  
Author(s):  
Sandra Thijssen ◽  
Barnaly Rashid ◽  
Shruti Gopal ◽  
Prashanth Nyalakanti ◽  
Vince D. Calhoun ◽  
...  
Keyword(s):  
Alcohol Use ◽  
Resting State ◽  
Time Course ◽  
Power Spectra ◽  
State Time ◽  
Incarcerated Adolescents

scholarly journals Dynamic variations of resting-state BOLD signal spectra in white matter

2021 ◽  
Author(s):  
Muwei Li ◽  
Yurui Gao ◽  
Adam W Anderson ◽  
Zhaohua Ding ◽  
John C Gore
Keyword(s):  
White Matter ◽  
Resting State ◽  
Linear Models ◽  
Temporal Frequency ◽  
Hierarchical Structures ◽  
Blood Oxygenation ◽  
Hemodynamic Response Function ◽  
Time Courses ◽  
Spectral Patterns ◽  
Over Time

Recent studies have demonstrated that the mathematical model used for analyzing and interpreting fMRI data in gray matter (GM) is inappropriate for detecting or describing blood-oxygenation-level-dependent (BOLD) signals in white matter (WM). In particular the hemodynamic response function (HRF) which serves as the regressor in general linear models is different in WM compared to GM. We recently reported measurements of the frequency contents of resting-state time courses in WM that showed distinct power spectra which depended on local structural-vascular-functional associations. In addition, multiple studies of GM have revealed how functional connectivity between regions, as measured by the correlation between BOLD time series, varies dynamically over time. We therefore investigated whether and how BOLD signals from WM in a resting state varied over time. We measured voxel-wise spectrograms, which reflect the time-varying spectral patterns of WM time courses. The results suggest that the spectral patterns are non-stationary but could be categorized into five modes that recurred over time. These modes showed distinct spatial distributions of their occurrences and durations, and the distributions were highly consistent across individuals. In addition, one of the modes exhibited a strong coupling of its occurrence between GM and WM across individuals, and two communities of WM voxels were identified according to the hierarchical structures of transitions among modes. Moreover, the total number of transitions in each community predicts specific human behaviors. Last, these modes are coupled to the shape of instantaneous HRFs. Our findings extend previous studies and reveal the non-stationary nature of spectral patterns of BOLD signals over time, providing a spatial-temporal-frequency characterization of resting-state signals in WM.

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.

Preparation and Characterization of NH2-Terminal Fibrinogen Bβ Fragments from N-DSK of Human Fibrinogen

1984 ◽  
Vol 51 (01) ◽  
pp. 016-021 ◽  
Author(s):  
S Birken ◽  
G Agosto ◽  
B Lahiri ◽  
R Canfield
Keyword(s):  
High Performance ◽  
Gel Filtration ◽  
Ion Exchange Chromatography ◽  
Exchange Chromatography ◽  
Reverse Phase ◽  
Human Fibrinogen ◽  
Human Volunteers ◽  
Cnbr Cleavage ◽  
Two Peaks

SummaryIn order to investigate the early release of NH2-terminal plasmic fragments from the Bβ chain of fibrinogen, substantial quantities of Bβ 1-42 and Bβ 1-21 are required as immunogens, as radioimmunoassay standards and for infusion into human volunteers to determine the half-lives of these peptides. Towards this end methods that employ selective proteolytic cleavage of these fragments from fibrinogen have been developed. Both the N-DSK fragment, produced by CNBr cleavage of fibrinogen, and Bβ 1-118 were employed as substrates for plasmin with the finding of higher yields from N-DSK. Bβ 1-42 and Bβ 1-21 were purified by gel filtration and ion-exchange chromatography on SP-Sephadex using volatile buffers. When the purified preparation of Bβ 1-42 was chromatographed on reverse-phase high performance liquid chromatography, two peaks of identical amino acid composition were separated, presumably due either to pyroglutamate or to amide differences.

Characterization of Ischemic Stroke in CT Images using Image Processing

2017 ◽  
Vol 7 (9) ◽  
pp. 18
Author(s):  
Amal Alzain ◽  
Suhaib Alameen ◽  
Rani Elmaki ◽  
Mohamed E. M. Gar-Elnabi
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Classification Accuracy ◽  
Ct Images ◽  
Gray Level ◽  
Level Variation ◽  
Interactive Data ◽  
The Brain ◽  
Brain Tissues

This study concern to characterize the brain tissues to ischemic stroke, gray matter, white matter and CSF using texture analysisto extract classification features from CT images. The First Order Statistic techniques included sevenfeatures. To find the gray level variation in CT images it complements the FOS features extracted from CT images withgray level in pixels and estimate the variation of thesubpatterns. analyzing the image with Interactive Data Language IDL software to measure the grey level of images. The results show that the Gray Level variation and   features give classification accuracy of ischemic stroke 97.6%, gray matter95.2%, white matter 97.3% and the CSF classification accuracy 98.0%. The overall classification accuracy of brain tissues 97.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate brain tissues names.

CHARACTERIZATION OF COGNITIVE PERFORMANCE, GRAY MATTER VOLUME AND WHITE MATTER MICROSTRUCTURE IN COGNITIVELY UNIMPAIRED ADULTS WITH INSOMNIA SYMPTOMS

2019 ◽  
Vol 15 (7) ◽  
pp. P207-P209
Author(s):  
Oriol Grau-Rivera ◽  
Grégory Operto ◽  
Carles Falcon ◽  
Raffaele Cacciaglia ◽  
Gonzalo Sánchez-Benavides ◽  
...  
Keyword(s):  
White Matter ◽  
Cognitive Performance ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Matter Volume ◽  
White Matter Microstructure ◽  
Insomnia Symptoms

scholarly journals The unbalanced reorganization of weaker functional connections induces the altered brain network topology in schizophrenia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rossana Mastrandrea ◽  
Fabrizio Piras ◽  
Andrea Gabrielli ◽  
Nerisa Banaj ◽  
Guido Caldarelli ◽  
...  
Keyword(s):  
Resting State ◽  
Functional Organization ◽  
Functional Integration ◽  
Brain Network ◽  
Modular Organization ◽  
Node Degree ◽  
Imaging Data ◽  
Brain Disorder ◽  
Functional Connections ◽  
The Brain

AbstractNetwork neuroscience shed some light on the functional and structural modifications occurring to the brain associated with the phenomenology of schizophrenia. In particular, resting-state functional networks have helped our understanding of the illness by highlighting the global and local alterations within the cerebral organization. We investigated the robustness of the brain functional architecture in 44 medicated schizophrenic patients and 40 healthy comparators through an advanced network analysis of resting-state functional magnetic resonance imaging data. The networks in patients showed more resistance to disconnection than in healthy controls, with an evident discrepancy between the two groups in the node degree distribution computed along a percolation process. Despite a substantial similarity of the basal functional organization between the two groups, the expected hierarchy of healthy brains' modular organization is crumbled in schizophrenia, showing a peculiar arrangement of the functional connections, characterized by several topologically equivalent backbones. Thus, the manifold nature of the functional organization’s basal scheme, together with its altered hierarchical modularity, may be crucial in the pathogenesis of schizophrenia. This result fits the disconnection hypothesis that describes schizophrenia as a brain disorder characterized by an abnormal functional integration among brain regions.

scholarly journals A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function

NeuroImage ◽  
2021 ◽  
pp. 118306
Author(s):  
Rachael C. Stickland ◽  
Kristina M. Zvolanek ◽  
Stefano Moia ◽  
Apoorva Ayyagari ◽  
César Caballero-Gaudes ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Cerebrovascular Function
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