scholarly journals Percent amplitude of fluctuation: a simple measure for resting-state fMRI signal at single voxel level

2017 ◽  
Author(s):  
Xi-Ze Jia ◽  
Gong-Jun Ji ◽  
Wei Liao ◽  
Ya-Ting Lv ◽  
Jue Wang ◽  
...  
Keyword(s):  
Frequency Band ◽  
Resting State ◽  
Blood Oxygenation ◽  
Future Application ◽  
Bold Signal ◽  
Fmri Signal ◽  
Eyes Closed ◽  
Percent Signal Change ◽  
Single Voxel ◽  
Global Mean

AbstractThe amplitude of low-frequency fluctuation (ALFF) measures resting-state functional magnetic resonance imaging (RS-fMRI) signal of each voxel. However, the unit of blood oxygenation level-dependent (BOLD) signal is arbitrary and hence ALFF is sensitive to the scale of raw signal. A well-accepted standardization procedure is to divide each voxel’s ALFF by the global mean ALFF. However, this makes the individual voxel’s ALFF dependent on the global mean. Although Fractional ALFF (fALFF), proposed as a ratio of the ALFF to the total amplitude within the full frequency band, offers possible solution of the standardization, it actually mixes with the fluctuation power within the full frequency band and thus cannot reveal the true amplitude characteristics of a given frequency band. We proposed a new standardized, stand-alone, single-voxel metrics for RS-fMRI, namely percent amplitude of fluctuation (PerAF). PerAF is an analog to the percent signal change that has been widely used in the task fMRI communities, which allows it to be a straightforward measurement of BOLD signal fluctuations during resting state. We further conducted a test-retest reliability analysis comparing the relevant metrics, which indicated that PerAF was generally more reliable than the ALFF and fALFF. In a real RS-fMRI application, we further demonstrated that with and without standardization by global mean PerAF yielded prominently different results when comparing eyes open with eyes closed resting conditions, suggesting that future study should provide both with and without global mean standardization. The above results suggest that PerAF is a more reliable, straightforward and promising measurement for voxelwise brain activity-based RS-fMRI studies. For prompting future application of PerAF, we also implemented this method into a user-friendly toolbox REST-PerAF.

scholarly journals Resting States Affect Spontaneous BOLD Oscillations in Sensory and Paralimbic Cortex

2008 ◽  
Vol 100 (2) ◽  
pp. 922-931 ◽  
Author(s):  
Mark McAvoy ◽  
Linda Larson-Prior ◽  
Tracy S. Nolan ◽  
S. Neil Vaishnavi ◽  
Marcus E. Raichle ◽  
...  
Keyword(s):  
Spectral Density ◽  
Resting State ◽  
Retrosplenial Cortex ◽  
Blood Oxygenation ◽  
Bold Signal ◽  
Eyes Closed ◽  
State Type ◽  
Oxygenation Level ◽  
Eyes Open ◽  
Highly Correlated

The brain exhibits spontaneous neural activity that depends on the behavioral state of the organism. We asked whether the blood oxygenation level-dependent (BOLD) signal reflects these modulations. BOLD was measured under three steady-state conditions: while subjects kept their eyes closed, kept their eyes open, or while fixating. The BOLD spectral density was calculated across brain voxels and subjects. Visual, sensory-motor, auditory, and retrosplenial cortex showed modulations of the BOLD spectral density by resting state type. All modulated regions showed greater spontaneous BOLD oscillations in the eyes closed than the eyes open or fixation conditions, suggesting that the differences were endogenously driven. Next, we examined the pattern of correlations between regions whose ongoing BOLD signal was modulated by resting state type. Regional neuronal correlations were estimated using an analytic procedure from the comparison of BOLD–BOLD covariances in the fixation and eyes closed conditions. Most regions were highly correlated with one another, with the exception of the primary visual cortices, which showed low correlations with the other regions. In conclusion, changes in resting state were associated with synchronous modulations of spontaneous BOLD oscillations in cortical sensory areas driven by two spatially overlapping, but temporally uncorrelated signals.

The effects of respiratory CO2 fluctuations in the resting-state BOLD signal differ between eyes open and eyes closed

2013 ◽  
Vol 31 (3) ◽  
pp. 336-345 ◽  
Author(s):  
Tingying Peng ◽  
Rami Niazy ◽  
Stephen J. Payne ◽  
Richard G. Wise
Keyword(s):  
Resting State ◽  
Bold Signal ◽  
Eyes Closed ◽  
Eyes Open

scholarly journals Modular and state-relevant connectivity in high-frequency resting-state BOLD fMRI data: An independent component analysis

2020 ◽  
Author(s):  
Thomas DeRamus ◽  
Ashkan Faghiri ◽  
Armin Iraji ◽  
Oktay Agcaoglu ◽  
Victor Vergara ◽  
...  
Keyword(s):  
Independent Component Analysis ◽  
Resting State ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Component Analysis ◽  
Independent Component ◽  
Fmri Data ◽  
Bold Signal ◽  
Drift Motion ◽  
Eyes Closed

AbstractResting-state fMRI (rs-fMRI) data are typically filtered at different frequency bins between 0.008∼0.2 Hz (varies across the literature) prior to analysis to mitigate nuisance variables (e.g., drift, motion, cardiac, and respiratory) and maximize the sensitivity to neuronal-mediated BOLD signal. However, multiple lines of evidence suggest meaningful BOLD signal may also be parsed at higher frequencies. To test this notion, a functional network connectivity (FNC) analysis based on a spatially informed independent component analysis (ICA) was performed at seven different bandpass frequency bins to examine FNC matrices across spectra. Further, eyes open (EO) vs. eyes closed (EC) resting-state acquisitions from the same participants were compared across frequency bins to examine if EO vs. EC FNC matrices and randomness estimations of FNC matrices are distinguishable at different frequencies.Results show that FNCs in higher-frequency bins display modular FNC similar to the lowest frequency bin, while r-to-z FNC and FNC-based measures indicating matrix non-randomness were highest in the 0.31-0.46 Hz range relative to all frequency bins above and below this range. As such, the FNC within this range appears to be the most temporally correlated, but the mechanisms facilitating this coherence require further analyses. Compared to EO, EC displayed greater FNC (involved in visual, cognitive control, somatomotor, and auditory domains) and randomness values at lower frequency bins, but this phenomenon flipped (EO > EC) at frequency bins greater than 0.46 Hz, particularly within visual regions.While the effect sizes range from small to large specific to frequency range and resting state (EO vs. EC), with little influence from common artifacts. These differences indicate that unique information can be derived from FNC between BOLD signals at different frequencies relative to a given restingstate acquisition and support the hypothesis meaningful BOLD signal is present at higher frequency ranges.

scholarly journals Time-of-day effects in resting-state fMRI: changes in Effective Connectivity and BOLD signal

2020 ◽  
Author(s):  
Liucija Vaisvilaite ◽  
Vetle Hushagen ◽  
Janne Gronli ◽  
Karsten Specht
Keyword(s):  
Resting State ◽  
Empirical Bayes ◽  
Effective Connectivity ◽  
Resting State Fmri ◽  
Time Of Day ◽  
Blood Oxygenation ◽  
Bold Signal ◽  
Human Connectome Project ◽  
Using Data ◽  
Density Dynamic

The current project explored the hypothesis that time-of-day dependent metabolic variations may contribute to reduced reliability in resting-state fMRI studies. We have investigated time-of-day effects in the spontaneous fluctuations (>0.1Hz) of the blood oxygenation level dependent (BOLD) signal. Using data from the human connectome project (HCP) release S1200, cross-spectral density dynamic causal modelling (DCM) was used to analyze time-dependent effects on the hemodynamic response and effective connectivity parameters. Hierarchical group-parametric empirical Bayes (PEB) found no support for changes in effective connectivity, whereas the hemodynamic parameters exhibited a significant time-of-day dependent effect. We conclude that these findings urge the need to account for the time of data acquisition in future MRI studies.

scholarly journals Variance and Scale-Free Properties of Resting-State BOLD Signal Alter after Fear Memory Acquisition and Extinction

2019 ◽  
Author(s):  
Alina Tetereva ◽  
Sergey Kartashov ◽  
Alexey Ivanitsky ◽  
Olga Martynova
Keyword(s):  
Resting State ◽  
Fear Memory ◽  
Fear Extinction ◽  
Blood Oxygenation ◽  
Fear Learning ◽  
Extinction Procedure ◽  
Recent Experience ◽  
Bold Signal ◽  
Scale Free ◽  
Significant Difference

AbstractPrevious studies showed differences in brain dynamics during rest and different tasks. We aimed to find changes of variance and scale-free properties of blood oxygenation level-dependent (BOLD) signal between resting-state sessions before and after fear learning and fear memory extinction in twenty-three healthy right-handed volunteers. During a 1-hour break between MRI-scanning, subjects passed through fear extinction procedure, followed by Pavlovian fear conditioning with weak electrical stimulation. After preprocessing, we extracted the average time course of BOLD signal from 245 regions of interest (ROI) taken from the resting-state functional atlas. The variance of the BOLD signal in and Hurst exponent (H), which reflects the scale-free dynamic, were compared in resting states before after fear learning. Six ROIs showed a significant difference in H after fear extinction, including areas from the fear and memory networks. In consistency with the previous results, H decreased during fear extinction but then increased higher than before, specifically in areas related to fear extinction network, whereas the other ROIs restored H to the initial level. The BOLD signal variance showed distinct behavior: the variance in subcortical regions increased permanently, while cortical areas demonstrated a decreasing variance during fear extinction and the reverse growth in resting state after fear extinction. A limited number of ROIs showed both changes in H and the variance. Our results suggest that the variability and scale-free properties of the BOLD signal are sensitive indicators of the residual brain activity related to the recent experience.

scholarly journals Percent amplitude of fluctuation: A simple measure for resting-state fMRI signal at single voxel level

PLoS ONE ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. e0227021 ◽  
Author(s):  
Xi-Ze Jia ◽  
Jia-Wei Sun ◽  
Gong-Jun Ji ◽  
Wei Liao ◽  
Ya-Ting Lv ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Simple Measure ◽  
Fmri Signal ◽  
Single Voxel

scholarly journals Canonical EEG Microstates Transitions Reflect Switching Among BOLD Resting State Networks and Predict fMRI Signal

2021 ◽  
Author(s):  
Obada Al Zoubi ◽  
Ahmad Mayeli ◽  
Masaya Misaki ◽  
Aki Tsuchiyagaito ◽  
Vadim Zotev ◽  
...  
Keyword(s):  
Machine Learning ◽  
Resting State ◽  
Blood Oxygenation Level Dependent ◽  
Blood Oxygenation ◽  
Learning Approaches ◽  
Resting State Networks ◽  
Functional Interpretation ◽  
Fmri Signal ◽  
Blood Oxygenation Level ◽  
Oxygenation Level

Abstract Objective. Electroencephalography microstates (EEG-ms), which reflect a large topographical representation of coherent electrophysiological brain activity, are widely adopted to study cognitive processes mechanisms and aberrant alterations in brain disorders. EEG-ms topographies are quasi-stable lasting between 60-120 milliseconds. Some evidence suggests that EEG-ms are the electrophysiological signature of resting-state networks (RSNs). However, the spatial and functional interpretation of EEG-ms and their association with functional MRI (fMRI) remains unclear. Approach. In a large cohort of healthy subjects (n = 52), we conducted several statistical and machine learning approaches analyses on the association among EEG-ms spatio-temporal dynamics and the blood-oxygenation-level dependent (BOLD) simultaneous EEG-fMRI data using statistical and machine learning approaches. Main results. Our results using a generalized linear model unraveled that EEG-ms transitions were largely and negatively associated with blood-oxygenation-level dependent (BOLD) signals in the somatomotor, visual, dorsal attention, and ventral attention fMRI networks with limited association within the default mode network. Additionally, a novel recurrent neural network (RNN) confirmed the association between EEG-ms transitioning and fMRI signal while revealing that EEG-ms dynamics can predict BOLD signals and vice versa. Significance. Results suggest that EEG-ms transitions may represent the deactivation of fMRI RSNs and provide evidence that both modalities can measure common aspects of undergoing brain neuronal activities. Moreover, our results may help to better understand the electrophysiological interpretation of EEG-ms and solve several contradicting findings in the literature.

scholarly journals Characteristics of Resting State EEG Power in 80+-Year-Olds of Different Cognitive Status

2021 ◽  
Vol 13 ◽  
Author(s):  
Stephanie Fröhlich ◽  
Dieter F. Kutz ◽  
Katrin Müller ◽  
Claudia Voelcker-Rehage
Keyword(s):  
Frequency Band ◽  
Resting State ◽  
Cognitive Status ◽  
Cognitive Test ◽  
Neuropsychological Screening ◽  
Eyes Closed ◽  
Eeg Reactivity ◽  
Beta Power ◽  
Increased Risk ◽  
Eyes Open

Compared with healthy older adults, patients with Alzheimer's disease show decreased alpha and beta power as well as increased delta and theta power during resting state electroencephalography (rsEEG). Findings for mild cognitive impairment (MCI), a stage of increased risk of conversion to dementia, are less conclusive. Cognitive status of 213 non-demented high-agers (mean age, 82.5 years) was classified according to a neuropsychological screening and a cognitive test battery. RsEEG was measured with eyes closed and open, and absolute power in delta, theta, alpha, and beta bands were calculated for nine regions. Results indicate no rsEEG power differences between healthy individuals and those with MCI. There were also no differences present between groups in EEG reactivity, the change in power from eyes closed to eyes open, or the topographical pattern of each frequency band. Overall, EEG reactivity was preserved in 80+-year-olds without dementia, and topographical patterns were described for each frequency band. The application of rsEEG power as a marker for the early detection of dementia might be less conclusive for high-agers.

scholarly journals The effect of congenital blindness on resting-state functional connectivity revisited

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maria J. S. Guerreiro ◽  
Madita Linke ◽  
Sunitha Lingareddy ◽  
Ramesh Kekunnaya ◽  
Brigitte Röder
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Visual Experience ◽  
Brain Regions ◽  
State Condition ◽  
Resting State Functional Connectivity ◽  
Congenital Blindness ◽  
Eyes Closed ◽  
Congenitally Blind ◽  
Eyes Open

AbstractLower resting-state functional connectivity (RSFC) between ‘visual’ and non-‘visual’ neural circuits has been reported as a hallmark of congenital blindness. In sighted individuals, RSFC between visual and non-visual brain regions has been shown to increase during rest with eyes closed relative to rest with eyes open. To determine the role of visual experience on the modulation of RSFC by resting state condition—as well as to evaluate the effect of resting state condition on group differences in RSFC—, we compared RSFC between visual and somatosensory/auditory regions in congenitally blind individuals (n = 9) and sighted participants (n = 9) during eyes open and eyes closed conditions. In the sighted group, we replicated the increase of RSFC between visual and non-visual areas during rest with eyes closed relative to rest with eyes open. This was not the case in the congenitally blind group, resulting in a lower RSFC between ‘visual’ and non-‘visual’ circuits relative to sighted controls only in the eyes closed condition. These results indicate that visual experience is necessary for the modulation of RSFC by resting state condition and highlight the importance of considering whether sighted controls should be tested with eyes open or closed in studies of functional brain reorganization as a consequence of blindness.

scholarly journals Resting State Alpha Electroencephalographic Rhythms Are Differently Related to Aging in Cognitively Unimpaired Seniors and Patients with Alzheimer’s Disease and Amnesic Mild Cognitive Impairment

2021 ◽  
pp. 1-30
Author(s):  
Claudio Babiloni ◽  
Raffaele Ferri ◽  
Giuseppe Noce ◽  
Roberta Lizio ◽  
Susanna Lopez ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Resting State ◽  
Diagnostic Biomarkers ◽  
Eyes Closed ◽  
Topographical Effects ◽  
And Gender ◽  
International Archive

Background: In relaxed adults, staying in quiet wakefulness at eyes closed is related to the so-called resting state electroencephalographic (rsEEG) rhythms, showing the highest amplitude in posterior areas at alpha frequencies (8–13 Hz). Objective: Here we tested the hypothesis that age may affect rsEEG alpha (8–12 Hz) rhythms recorded in normal elderly (Nold) seniors and patients with mild cognitive impairment due to Alzheimer’s disease (ADMCI). Methods: Clinical and rsEEG datasets in 63 ADMCI and 60 Nold individuals (matched for demography, education, and gender) were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands, as well as fixed beta (14–30 Hz) and gamma (30–40 Hz) bands. Each group was stratified into three subgroups based on age ranges (i.e., tertiles). Results: As compared to the younger Nold subgroups, the older one showed greater reductions in the rsEEG alpha rhythms with major topographical effects in posterior regions. On the contrary, in relation to the younger ADMCI subgroups, the older one displayed a lesser reduction in those rhythms. Notably, the ADMCI subgroups pointed to similar cerebrospinal fluid AD diagnostic biomarkers, gray and white matter brain lesions revealed by neuroimaging, and clinical and neuropsychological scores. Conclusion: The present results suggest that age may represent a deranging factor for dominant rsEEG alpha rhythms in Nold seniors, while rsEEG alpha rhythms in ADMCI patients may be more affected by the disease variants related to earlier versus later onset of the AD.

Sign in / Sign up

Export Citation Format

Share Document