scholarly journals A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures

2014 ◽  
Author(s):  
Krzysztof Jacek Gorgolewski ◽  
Natacha Mendes ◽  
Domenica Wilfling ◽  
Elisabeth Wladimirow ◽  
Claudine J. Gauthier ◽  
...  
Keyword(s):  
High Spatial Resolution ◽  
Resting State Fmri ◽  
7 Tesla ◽  
Physiological Changes ◽  
Physiological Measures ◽  
Affective States ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Experimental Protocol ◽  
Brain Scans

Here we present a test-retest dataset of functional magnetic resonance imaging (fMRI) data acquired at rest. 22 participants were scanned during two sessions spaced one week apart. Each session includes two 1.5 mm isotropic whole-brain scans and one 0.75 mm isotropic scan of the prefrontal cortex, giving a total of six timepoints. Additionally, the dataset includes measures of mood, sustained attention, blood pressure, respiration, pulse, and the content of self-generated thoughts (mind wandering). This data enables the investigation of sources of both intra- and inter-session variability not only limited to physiological changes, but also including alterations in cognitive and affective states, at high spatial resolution. The dataset is accompanied by a detailed experimental protocol and source code of all stimuli used.

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 A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Krzysztof J Gorgolewski ◽  
Natacha Mendes ◽  
Domenica Wilfling ◽  
Elisabeth Wladimirow ◽  
Claudine J Gauthier ◽  
...  
Keyword(s):  
High Resolution ◽  
Resting State ◽  
Resting State Fmri ◽  
7 Tesla ◽  
Physiological Measures

scholarly journals How Do We Empathize with Someone Who Is Not Like Us? A Functional Magnetic Resonance Imaging Study

2010 ◽  
Vol 22 (2) ◽  
pp. 362-376 ◽  
Author(s):  
Claus Lamm ◽  
Andrew N. Meltzoff ◽  
Jean Decety
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Affective State ◽  
Anterior Cingulate ◽  
Affective Processing ◽  
Affective States ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Affective Stimuli

Previous research on the neural underpinnings of empathy has been limited to affective situations experienced in a similar way by an observer and a target individual. In daily life we also interact with people whose responses to affective stimuli can be very different from our own. How do we understand the affective states of these individuals? We used functional magnetic resonance imaging to assess how participants empathize with the feelings of patients who reacted with no pain to surgical procedures but with pain to a soft touch. Empathy for pain of these patients activated the same areas (insula, medial/anterior cingulate cortex) as empathy for persons who responded to painful stimuli in the same way as the observer. Empathy in a situation that was aversive only for the observer but neutral for the patient recruited areas involved in self–other distinction (dorsomedial prefrontal cortex) and cognitive control (right inferior frontal cortex). In addition, effective connectivity between the latter and areas implicated in affective processing was enhanced. This suggests that inferring the affective state of someone who is not like us can rely upon the same neural structures as empathy for someone who is similar to us. When strong emotional response tendencies exist though, these tendencies have to be overcome by executive functions. Our results demonstrate that the fronto-cortical attention network is crucially involved in this process, corroborating that empathy is a flexible phenomenon which involves both automatic and controlled cognitive mechanisms. Our findings have important implications for the understanding and promotion of empathy, demonstrating that regulation of one's egocentric perspective is crucial for understanding others.

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.

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