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 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 Neuronal variability of Resting State activity in Eating Disorders: increase and decoupling in Ventral Attention Network and relation with clinical symptoms

2019 ◽  
Vol 55 ◽  
pp. 10-17 ◽  
Author(s):  
Angela V. Spalatro ◽  
Federico Amianto ◽  
Zirui Huang ◽  
Federico D’Agata ◽  
Mauro Bergui ◽  
...  
Keyword(s):  
Eating Disorders ◽  
Resting State ◽  
Clinical Symptoms ◽  
Blood Oxygen Level Dependent ◽  
Healthy Controls ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Attention Network ◽  
State Activity ◽  
New Perspective

AbstractBackground:Despite the great number of resting state functional connectivity studies on Eating Disorders (ED), no biomarkers could be detected yet. Therefore, we here focus on a different measure of resting state activity that is neuronal variability. The objective of this study was to investigate neuronal variability in the resting state of women with ED and to correlate possible differences with clinical and psychopathological indices.Methods:58 women respectively 25 with Anorexia Nervosa (AN), 16 with Bulimia Nervosa (BN) and 17 matched healthy controls (CN) were enrolled for the study. All participants were tested with a battery of psychometric tests and underwent a functional Magnetic Resonance Imaging (fMRI) resting state scanning. We investigated topographical patterns of variability measured by the Standard Deviation (SD) of the Blood-Oxygen-Level-Dependent (BOLD) signal (as a measure of neuronal variability) in the resting-state and their relationship to clinical and psychopathological indices.Results:Neuronal variability was increased in both anorectic and bulimic subjects specifically in the Ventral Attention Network (VAN) compared to healthy controls. No significant differences were found in the other networks. Significant correlations were found between neuronal variability of VAN and various clinical and psychopathological indices.Conclusions:We here show increased neuronal variability of VAN in ED patients. As the VAN is relevant for switching between endogenous and exogenous stimuli, our results showing increased neuronal variability suggest unstable balance between body attention and attention to external world. These results offer new perspective on the neurobiological basis of ED. Clinical and therapeutic implication will be discussed.

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 Advanced Meditation Alters Resting-State Brain Network Connectivity Correlating With Improved Mindfulness

2021 ◽  
Vol 12 ◽  
Author(s):  
Ramana V. Vishnubhotla ◽  
Rupa Radhakrishnan ◽  
Kestas Kveraga ◽  
Rachael Deardorff ◽  
Chithra Ram ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Network Connectivity ◽  
Blood Oxygen Level Dependent ◽  
Brain Network ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Default Mode ◽  
Before And After ◽  
Brain Network Connectivity

Purpose: The purpose of this study was to investigate the effect of an intensive 8-day Samyama meditation program on the brain functional connectivity using resting-state functional MRI (rs-fMRI).Methods: Thirteen Samyama program participants (meditators) and 4 controls underwent fMRI brain scans before and after the 8-day residential meditation program. Subjects underwent fMRI with a blood oxygen level dependent (BOLD) contrast at rest and during focused breathing. Changes in network connectivity before and after Samyama program were evaluated. In addition, validated psychological metrics were correlated with changes in functional connectivity.Results: Meditators showed significantly increased network connectivity between the salience network (SN) and default mode network (DMN) after the Samyama program (p < 0.01). Increased connectivity within the SN correlated with an improvement in self-reported mindfulness scores (p < 0.01).Conclusion: Samyama, an intensive silent meditation program, favorably increased the resting-state functional connectivity between the salience and default mode networks. During focused breath watching, meditators had lower intra-network connectivity in specific networks. Furthermore, increased intra-network connectivity correlated with improved self-reported mindfulness after Samyama.Clinical Trials Registration: [https://clinicaltrials.gov], Identifier: [NCT04366544]. Registered on 4/17/2020.

scholarly journals Differential effects of anesthetics on resting state functional connectivity in the mouse

2019 ◽  
Vol 40 (4) ◽  
pp. 875-884 ◽  
Author(s):  
Hongyu Xie ◽  
David Y Chung ◽  
Sreekanth Kura ◽  
Kazutaka Sugimoto ◽  
Sanem A Aykan ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Chloral Hydrate ◽  
Low Frequency ◽  
Blood Oxygen Level Dependent ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Intrinsic Signal ◽  
Optical Intrinsic Signal ◽  
Important Approach

Blood oxygen level-dependent (BOLD) functional MRI (fMRI) is a standard approach to examine resting state functional connectivity (RSFC), but fMRI in animal models is challenging. Recently, functional optical intrinsic signal imaging—which relies on the same hemodynamic signal underlying BOLD fMRI—has been developed as a complementary approach to assess RSFC in mice. Since it is difficult to ensure that an animal is in a truly resting state while awake, RSFC measurements under anesthesia remain an important approach. Therefore, we systematically examined measures of RSFC using non-invasive, widefield optical intrinsic signal imaging under five different anesthetics in male C57BL/6J mice. We find excellent seed-based, global, and interhemispheric connectivity using tribromoethanol (Avertin) and ketamine–xylazine, comparable to results in the literature including awake animals. Urethane anesthesia yielded intermediate results, while chloral hydrate and isoflurane were both associated with poor RSFC. Furthermore, we found a correspondence between the strength of RSFC and the power of low-frequency hemodynamic fluctuations. In conclusion, Avertin and ketamine–xylazine provide robust and reproducible measures of RSFC in mice, whereas chloral hydrate and isoflurane do not.

scholarly journals Subcortical connectivity in dementia with Lewy bodies and Alzheimer's disease

2013 ◽  
Vol 203 (3) ◽  
pp. 209-214 ◽  
Author(s):  
Eva R. Kenny ◽  
John T. O'Brien ◽  
Michael J. Firbank ◽  
Andrew M. Blamire
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Connectivity ◽  
Resting State ◽  
Dementia With Lewy Bodies ◽  
Lewy Bodies ◽  
Low Frequency ◽  
Blood Oxygen Level Dependent ◽  
Bold Signal ◽  
Blood Oxygen Level

BackgroundResting-state functional magnetic resonance imaging (fMRI) can be used to measure correlations in spontaneous low-frequency fluctuations in the blood oxygen level-dependent (BOLD) signal which represent functional connectivity between key brain areas.AimsTo investigate functional connectivity with regions hypothesised to be differentially affected in dementia with Lewy bodies (DLB) compared with Alzheimer's disease and controls.MethodFifteen participants with probable DLB, 16 with probable Alzheimer's disease and 16 controls were scanned in the resting-state using a 3T scanner. The BOLD signal time-series of fluctuations in seed regions were correlated with all other voxels to measure functional connectivity.ResultsParticipants with DLB and Alzheimer's disease showed greater caudate and thalamic connectivity compared with controls. Those with DLB showed greater putamen connectivity compared with those with Alzheimer's disease and the controls. No regions showed less connectivity in DLB or Alzheimer's disease v. controls, or in DLB v. Alzheimer's disease.ConclusionsAltered connectivity in DLB and Alzheimer's disease provides new insights into the neurobiology of these disorders and may aid in earlier diagnosis.

scholarly journals Mild inflammation causes a reduction in resting-state amplitude of low-frequency fluctuation in healthy adult males

2020 ◽  
Vol 4 ◽  
pp. 239821282094935
Author(s):  
Kristian Stefanov ◽  
John McLean ◽  
Becky Allan ◽  
Jonathan Cavanagh ◽  
Rajeev Krishnadas
Keyword(s):  
Resting State ◽  
Low Frequency ◽  
Blood Oxygen Level Dependent ◽  
Mood States ◽  
Profile Of Mood States ◽  
Blood Oxygen ◽  
Blood Oxygen Level ◽  
Lower Amplitude ◽  
Frequency Fluctuations ◽  
The Right

Systemic inflammation has been associated with negative mood states and human sickness behaviour. Previous studies have shown an association between systemic inflammation and changes in task-related blood-oxygen-level-dependent activity and functional connectivity within large-scale networks. However, no study has examined the effect of inflammation on the magnitude of blood-oxygen-level-dependent low-frequency fluctuations at rest. We used a double-blind placebo-controlled crossover design to randomise 20 male subjects (aged 20–50 years) to receive either a Salmonella typhi vaccine or a placebo saline injection at two separate sessions. All participants underwent a resting-state functional magnetic resonance scan and a measure of inflammation (interleukin 6) and mood (Profile of Mood States) 3 h after injection. We compared the whole brain amplitude of low-frequency fluctuations between the vaccine and placebo conditions using a repeated measures design. Vaccine condition was associated with greater interleukin 6 levels (p < 0.001). Vaccine condition was also associated with lower amplitude of low-frequency fluctuations in the right and left frontal pole, superior frontal gyrus, paracingulate gyrus (Cluster 1) and the right mid and inferior frontal gyrus (Cluster 2) (p < 0.001, false discovery rate corrected). Lower amplitude of low-frequency fluctuations pertaining to first cluster correlated with greater total Profile of Mood States score (worse mood) (r = −0.38; p = 0.04). These results imply possible excitation/inhibition imbalance mechanisms during inflammation that may be a relevant target in psychiatric disease, especially mood disorders.

scholarly journals Abnormal White Matter Blood-Oxygen-Level–Dependent Signals in Chronic Mild Traumatic Brain Injury

2015 ◽  
Vol 32 (16) ◽  
pp. 1254-1271 ◽  
Author(s):  
Serguei V. Astafiev ◽  
Gordon L. Shulman ◽  
Nicholas V. Metcalf ◽  
Jennifer Rengachary ◽  
Christine L. MacDonald ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
White Matter ◽  
Mild Traumatic Brain Injury ◽  
Blood Oxygen Level Dependent ◽  
Blood Oxygen ◽  
Oxygen Level ◽  
Blood Oxygen Level

scholarly journals The Global Signal and Observed Anticorrelated Resting State Brain Networks

2009 ◽  
Vol 101 (6) ◽  
pp. 3270-3283 ◽  
Author(s):  
Michael D. Fox ◽  
Dongyang Zhang ◽  
Abraham Z. Snyder ◽  
Marcus E. Raichle
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Brain Networks ◽  
Blood Oxygen Level Dependent ◽  
Great Promise ◽  
Blood Oxygen Level ◽  
Whole Brain ◽  
Global Signal ◽  
Global Regression

Resting state studies of spontaneous fluctuations in the functional MRI (fMRI) blood oxygen level dependent (BOLD) signal have shown great promise in mapping the brain's intrinsic, large-scale functional architecture. An important data preprocessing step used to enhance the quality of these observations has been removal of spontaneous BOLD fluctuations common to the whole brain (the so-called global signal). One reproducible consequence of global signal removal has been the finding that spontaneous BOLD fluctuations in the default mode network and an extended dorsal attention system are consistently anticorrelated, a relationship that these two systems exhibit during task performance. The dependence of these resting-state anticorrelations on global signal removal has raised important questions regarding the nature of the global signal, the validity of global signal removal, and the appropriate interpretation of observed anticorrelated brain networks. In this study, we investigate several properties of the global signal and find that it is, indeed, global, not residing preferentially in systems exhibiting anticorrelations. We detail the influence of global signal removal on resting state correlation maps both mathematically and empirically, showing an enhancement in detection of system-specific correlations and improvement in the correspondence between resting-state correlations and anatomy. Finally, we show that several characteristics of anticorrelated networks including their spatial distribution, cross-subject consistency, presence with modified whole brain masks, and existence before global regression are not attributable to global signal removal and therefore suggest a biological basis.

Sign in / Sign up

Export Citation Format

Share Document