A Critical, Event-Related Appraisal of Denoising in Resting-State fMRI Studies

2020 ◽  
Vol 30 (10) ◽  
pp. 5544-5559 ◽  
Author(s):  
Jonathan D Power ◽  
Charles J Lynch ◽  
Babatunde Adeyemo ◽  
Steven E Petersen
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Critical Event ◽  
Head Motion ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Decay Properties ◽  
Signal Decay ◽  
Biological Variables ◽  
Related Approach

Abstract This article advances two parallel lines of argument about resting-state functional magnetic resonance imaging (fMRI) signals, one empirical and one conceptual. The empirical line creates a four-part organization of the text: (1) head motion and respiration commonly cause distinct, major, unwanted influences (artifacts) in fMRI signals; (2) head motion and respiratory changes are, confoundingly, both related to psychological and clinical and biological variables of interest; (3) many fMRI denoising strategies fail to identify and remove one or the other kind of artifact; and (4) unremoved artifact, due to correlations of artifacts with variables of interest, renders studies susceptible to identifying variance of noninterest as variance of interest. Arising from these empirical observations is a conceptual argument: that an event-related approach to task-free scans, targeting common behaviors during scanning, enables fundamental distinctions among the kinds of signals present in the data, information which is vital to understanding the effects of denoising procedures. This event-related perspective permits statements like “Event X is associated with signals A, B, and C, each with particular spatial, temporal, and signal decay properties”. Denoising approaches can then be tailored, via performance in known events, to permit or suppress certain kinds of signals based on their desirability.

scholarly journals Customized head molds reduce motion during resting state fMRI scans

2018 ◽  
Author(s):  
Jonathan D Power ◽  
Benjamin Silver ◽  
Melanie R. Silverman ◽  
Eliana L. Ajodan ◽  
Dienke J. Bos ◽  
...  
Keyword(s):  
Resting State ◽  
Standard Procedure ◽  
Resting State Fmri ◽  
Motion Artifacts ◽  
Head Motion ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Quality Indices ◽  
Age Range ◽  
Head Coil

Head motion causes artifacts in functional magnetic resonance imaging (fMRI) scans, a problem especially relevant for task-free resting state paradigms and for developmental, aging, and clinical populations. In a cohort spanning 7-28 years old (mean age 15) we produced customized head-anatomy-specific Styrofoam molds for each subject that inserted into an MRI head coil. We scanned these subjects under two conditions: using our standard procedure of packing the head coil with foam padding about the head to reduce head motion, and using the customized molds to reduce head motion. Here we report the effects found in our first 13 subjects. In 12 of 13 subjects, the molds reduced head motion throughout the scan, and reduced the fraction of a scan with substantial motion (i.e., volumes with motion notably above baseline levels of motion). Motion was reduced in all 6 head position estimates, especially in rotational, left-right, and superior-inferior directions. Motion was reduced throughout the full age range studied, including children, adolescents, and young adults. In terms of the fMRI data itself, quality indices improved with the head mold on, scrubbing analyses detected less distance-dependent artifact in scans with the head mold on, and distant-dependent artifact was less evident in the scans with the molds on, both for the entire scan and also during only low-motion volumes. Subjects found the molds comfortable. Head molds are thus effective tools for reducing head motion, and motion artifacts, during fMRI scans.

scholarly journals Correlation between the Effects of Acupuncture atTaichong(LR3) and Functional Brain Areas: A Resting-State Functional Magnetic Resonance Imaging Study Using True versus Sham Acupuncture

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Chunxiao Wu ◽  
Shanshan Qu ◽  
Jiping Zhang ◽  
Junqi Chen ◽  
Shaoqun Zhang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Data Processing ◽  
Resting State ◽  
Resting State Fmri ◽  
Sham Acupuncture ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Brain Areas

Functional magnetic resonance imaging (fMRI) has been shown to detect the specificity of acupuncture points, as proved by numerous studies. In this study, resting-state fMRI was used to observe brain areas activated by acupuncture at theTaichong(LR3) acupoint. A total of 15 healthy subjects received brain resting-state fMRI before acupuncture and after sham and true acupuncture, respectively, at LR3. Image data processing was performed using Data Processing Assistant for Resting-State fMRI and REST software. The combination of amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) was used to analyze the changes in brain function during sham and true acupuncture. Acupuncture at LR3 can specifically activate or deactivate brain areas related to vision, movement, sensation, emotion, and analgesia. The specific alterations in the anterior cingulate gyrus, thalamus, and cerebellar posterior lobe have a crucial effect and provide a valuable reference. Sham acupuncture has a certain effect on psychological processes and does not affect brain areas related to function.

scholarly journals Network variants are similar between task and rest states

2020 ◽  
Author(s):  
Brian T. Kraus ◽  
Diana Perez ◽  
Zach Ladwig ◽  
Benjamin A. Seitzman ◽  
Ally Dworetsky ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Functional Networks ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Brain Organization ◽  
Precision Data ◽  
Specific Effects ◽  
Multiple Tasks ◽  
Over Time

AbstractRecent work has demonstrated that individual-specific variations in functional networks (that we call “network variants”) can be identified in individuals using functional magnetic resonance imaging (fMRI). These network variants exhibit reliability over time with resting-state fMRI data. These properties have suggested that network variants may be trait-like markers of individual differences in brain organization. Another test of this conclusion would be to examine if network variants are stable between task and rest states. Here, we use precision data from the Midnight Scan Club (MSC) to demonstrate that (1) task data can be used to identify network variants reliably, (2) these network variants show substantial spatial overlap with those observed in rest, although state-specific effects are present, (3) network variants assign to similar canonical functional networks in different states, and (4) single tasks or a combination of multiple tasks produce similar network variants to rest. Together, these findings further reinforce the trait-like nature of network variants and demonstrate the utility of using task data to define network variants.

scholarly journals Investigating the effects of healthy cognitive aging on brain functional connectivity using 4.7 T resting-state functional Magnetic Resonance Imaging

2020 ◽  
Author(s):  
Stanislau Hrybouski ◽  
Ivor Cribben ◽  
John McGonigle ◽  
Fraser Olsen ◽  
Rawle Carter ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Connectivity ◽  
Functional Magnetic Resonance Imaging ◽  
Age Differences ◽  
Resting State ◽  
Cognitive Aging ◽  
Resting State Fmri ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging

ABSTRACTIntroductionFunctional changes in the aging human brain have been previously reported using functional magnetic resonance imaging (fMRI). Earlier resting-state fMRI studies revealed an age-associated weakening of intra-system functional connectivity (FC) and age-associated strengthening of inter-system FC. However, the majority of such FC studies did not investigate the relationship between age and network amplitude, without which correlation-based measures of FC can be challenging to interpret. Consequently, the main aim of this study was to investigate how three primary measures of resting-state fMRI signal – network amplitude, network topography, and inter-network FC – are affected by healthy cognitive aging.MethodsWe acquired resting-state fMRI data on a 4.7 T scanner for 105 healthy participants representing the entire adult lifespan (18-85 years of age). To study age differences in network structure, we combined ICA-based network decomposition with sparse graphical models.ResultsOlder adults displayed lower blood-oxygen-level-dependent (BOLD) signal amplitude in all functional systems with sensorimotor networks showing the largest age differences. Our age comparisons of network topography and inter-network FC demonstrated a substantial amount of age-invariance in the brain’s functional architecture. Despite architecture similarities, old adults displayed a loss of communication efficiency in our inter-network FC comparisons, driven primarily by FC reduction in frontal and parietal association cortices. Together, our results provide a comprehensive overview of age effects on fMRI-based FC.

scholarly journals Resting state connectivity during total sleep deprivation: A functional magnetic resonance study

2020 ◽  
Author(s):  
Vivianne Jakobsson
Keyword(s):  
Magnetic Resonance ◽  
Sleep Deprivation ◽  
Resting State ◽  
Resting State Fmri ◽  
Head Motion ◽  
Functional Magnetic Resonance ◽  
Global Signal ◽  
Significant Difference ◽  
Before And After ◽  
Eyes Open

Introduction: Sleep deprivation is a common problem that may have serious consequences. In this study, functional magnetic resonance imaging (fMRI), a technique frequently used to study networks in the brain, was used to investigate the resting state of the sleep deprived brain, in order to discover whether this state affects the intrinsic connectivity and the global signal variability (GSV). Aims: To investigate whether GSV increases with sleep deprivation. Material and Methods: In this cross over study 18 healthy participants, age 20 – 30, underwent in randomized order resting-state fMRI for 20min before and after 24h sleep deprivation. We extracted the global signal, calculated the standard deviation per participant, and analysed it with respect to sleep depraved yes/no, head motion, eyes open/closed and self-evaluation of sleepiness using Karolinska Sleepiness Score (KSS). Results: We found that GSV was higher during sleep deprivation (0.3362 ± 0.0241, p<0.0001) without KSS data. With KSS, sleep deprivation was not significant (0.0619 ± 0.1145, p=0.5889). High KSS rating had a significant effect on GSV (0.1497 ± 0.0409, p=0.0003), as had head motion (1.7974 ± 0.1539, p<0.0001). There was no significant difference between having eyes open or closed (0.0126 ± 0.0578, p=0.8278), and no significant increase for each time period of 20s in the scanner (0.0065 ± 0.0021, p=0.0029). Conclusions: We found that the global signal variation is increased by sleep deprivation and sleepiness. More specific conclusions cannot be made from our data so far.

Simultaneous Electroencephalographic and Functional Magnetic Resonance Imaging Indicate Impaired Cortical Top–Down Processing in Association with Anesthetic-induced Unconsciousness

2013 ◽  
Vol 119 (5) ◽  
pp. 1031-1042 ◽  
Author(s):  
Denis Jordan ◽  
Rüdiger Ilg ◽  
Valentin Riedl ◽  
Anna Schorer ◽  
Sabine Grimberg ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Resting State ◽  
Characteristic Curve ◽  
Resting State Fmri ◽  
Loss Of Consciousness ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Top Down

Abstract Background: In imaging functional connectivity (FC) analyses of the resting brain, alterations of FC during unconsciousness have been reported. These results are in accordance with recent electroencephalographic studies observing impaired top–down processing during anesthesia. In this study, simultaneous records of functional magnetic resonance imaging (fMRI) and electroencephalogram were performed to investigate the causality of neural mechanisms during propofol-induced loss of consciousness by correlating FC in fMRI and directional connectivity (DC) in electroencephalogram. Methods: Resting-state 63-channel electroencephalogram and blood oxygen level–dependent 3-Tesla fMRI of 15 healthy subjects were simultaneously registered during consciousness and propofol-induced loss of consciousness. To indicate DC, electroencephalographic symbolic transfer entropy was applied as a nonlinear measure of mutual interdependencies between underlying physiological processes. The relationship between FC of resting-state networks of the brain (z values) and DC was analyzed by a partial correlation. Results: Independent component analyses of resting-state fMRI showed decreased FC in frontoparietal default networks during unconsciousness, whereas FC in primary sensory networks increased. DC indicated a decline in frontal–parietal (area under the receiver characteristic curve, 0.92; 95% CI, 0.68–1.00) and frontooccipital (0.82; 0.53–1.00) feedback DC (P < 0.05 corrected). The changes of FC in the anterior default network correlated with the changes of DC in frontal–parietal (rpartial = +0.62; P = 0.030) and frontal–occipital (+0.63; 0.048) electroencephalographic electrodes (P < 0.05 corrected). Conclusion: The simultaneous propofol-induced suppression of frontal feedback connectivity in the electroencephalogram and of frontoparietal FC in the fMRI indicates a fundamental role of top–down processing for consciousness.

scholarly journals Resting-State fMRI in Studies of Acupuncture

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Xiaoling Li ◽  
Lina Cai ◽  
Xiaoxu Jiang ◽  
Xiaohui Liu ◽  
Jingxian Wang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Resting State ◽  
Acupuncture Treatment ◽  
Physiological Mechanism ◽  
Resting State Fmri ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Visual Evidence ◽  
Acupuncture Research ◽  
Acupoint Stimulation

Research exploring the mechanism of acupuncture has been a hot topic in medicine. Resting-state functional magnetic resonance imaging (rs-fMRI) research is a noninvasive and extensive method, which is aimed at the research of the mechanism of acupuncture. Researchers use fMRI technologies to inspect the acupuncture process. The authors reviewed the application of rs-fMRI in acupuncture research in recent 10 years from the aspects of studying acupoints, subjects, acupuncture methods, and intensities. The results found that the application of rs-fMRI in acupuncture research mainly includes research on the onset mechanism of acupuncture treatment; visual evidence of diagnosis and treatment of dominant diseases; efficacy assessments; physiological mechanism of acupoint stimulation; and specific visualization of acupoints.

scholarly journals Resting-state Functional Magnetic Resonance Imaging Correlates of Sevoflurane-induced Unconsciousness

2015 ◽  
Vol 123 (2) ◽  
pp. 346-356 ◽  
Author(s):  
Ben Julian A. Palanca ◽  
Anish Mitra ◽  
Linda Larson-Prior ◽  
Abraham Z. Snyder ◽  
Michael S. Avidan ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Connectivity ◽  
Resting State ◽  
Head Motion ◽  
Bold Signal ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Anesthetic Agents ◽  
The Impact

Abstract Background: Blood oxygen level–dependent (BOLD) functional magnetic resonance imaging (fMRI) has been used to study the effects of anesthetic agents on correlated intrinsic neural activity. Previous studies have focused primarily on intravenous agents. The authors studied the effects of sevoflurane, an inhaled anesthetic. Methods: Resting-state BOLD fMRI was acquired from 10 subjects before sedation and from 9 subjects rendered unresponsive by 1.2% sevoflurane. The fMRI data were analyzed taking particular care to minimize the impact of artifact generated by head motion. Results: BOLD correlations were specifically weaker within the default mode network and ventral attention network during sevoflurane-induced unconsciousness, especially between anterior and posterior midline regions. Reduced functional connectivity between these same networks and the thalamus was also spatially localized to the midline frontal regions. The amplitude of BOLD signal fluctuations was substantially reduced across all brain regions. The importance of censoring epochs contaminated by head motion was demonstrated by comparative analyses. Conclusions: Sevoflurane-induced unconsciousness is associated with both globally reduced BOLD signal amplitudes and selectively reduced functional connectivity within cortical networks associated with consciousness (default mode network) and orienting to salient external stimuli (ventral attention network). Scrupulous attention to minimizing the impact of head motion artifact is critical in fMRI studies using anesthetic agents.

scholarly journals T156. FUNCTIONAL CONNECTIVITY AND RISK OF PSYCHOSIS: AN ACTIVATION LIKELIHOOD ESTIMATION (ALE) META-ANALYSIS OF FUNCTIONAL MAGNETIC RESONANCE IMAGING STUDIES

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S290-S290
Author(s):  
Lorenzo Del Fabro ◽  
André Schmidt ◽  
Giuseppe Delvecchio ◽  
Armando D’Agostino ◽  
Stefan Borgwardt ◽  
...  
Keyword(s):  
At Risk ◽  
High Risk ◽  
Resting State ◽  
Large Scale ◽  
Meta Analysis ◽  
A Priori ◽  
Resting State Fmri ◽  
Healthy Controls ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging

Abstract Background Disrupted communication involving large-scale neural networks is hypothesized to underlie the pathophysiology of schizophrenia, as demonstrated by impaired resting-state functional connectivity (rsFC). Seed-based functional magnetic resonance imaging (fMRI) studies in subjects at increased risk of developing psychosis have begun to identify abnormalities in rsFC, although reported findings remain mixed. The aim of this study was to conduct a meta-analysis of seed-based resting-state fMRI studies to test whether high-risk subjects show rsFC alterations relative to healthy controls within and between the default mode network (DMN), control executive network (CEN), and salience network (SN). Methods A literature search was performed to identify seed-based resting-state fMRI studies comparing subjects with genetic risk factors, psychotic-like experiences, and clinical high-risk for psychosis to healthy controls. Then, coordinates of seed regions were extracted and categorized into networks by their location within a priori templates. Activation likelihood estimate (ALE) analysis examined the reported coordinates for hypo-connectivity and hyper-connectivity with each a priori network. Results The meta-analysis included 15 studies (774 subjects at risk, 628 healthy controls) on clinical high-risk for psychosis, 6 studies (123 subjects at risk, 147 healthy controls) on psychotic-like experiences, and 5 studies (173 subjects at risk, 256 healthy controls) on genetic risk factors of developing psychosis. We found specific patterns of hypo- and hyper-connectivity within and between large-scale networks. Our results showed that subjects with high-risk for psychosis were characterized by hypo-connectivity within the SN and CEN and hyper-connectivity within the DMN and CEN. Network seeds in the DMN, CEN, and SN displayed hyper-connectivity with regions in other networks. The DMN seeds displayed hypo-connectivity with regions in the CEN, while CEN and SN seeds displayed hypo-connectivity with regions in the DMN. Discussion This meta-analysis provides evidence that subjects at risk for psychosis present distinctive abnormalities of hyper- and hypo-connectivity within and between the DMN, CEN and SN, particularly implicating network dys-connectivity as a core deficit underlying the psychopathology of psychosis in the preclinical phase. More studies are needed to investigate whether subjects at risk to develop psychosis present patterns of dysfunction between the rsFC of healthy subjects and that of patients with established psychosis.

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