scholarly journals Test-retest reliability of resting-state magnetoencephalography power in sensor and source space

2015 ◽  
Vol 37 (1) ◽  
pp. 179-190 ◽  
Author(s):  
María Carmen Martín-Buro ◽  
Pilar Garcés ◽  
Fernando Maestú
Keyword(s):  
Resting State ◽  
Retest Reliability ◽  
Test Retest Reliability

scholarly journals Test–retest reliability of laser evoked pain perception and fMRI BOLD responses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yanzhi Bi ◽  
Xin Hou ◽  
Jiahui Zhong ◽  
Li Hu
Keyword(s):  
Resting State ◽  
Repeated Measures ◽  
Subjective Experience ◽  
Pain Perception ◽  
Primary Motor Cortex ◽  
Intraclass Correlation ◽  
Retest Reliability ◽  
Repeated Measures Design ◽  
Brain Responses ◽  
Test Retest Reliability

AbstractPain perception is a subjective experience and highly variable across time. Brain responses evoked by nociceptive stimuli are highly associated with pain perception and also showed considerable variability. To date, the test–retest reliability of laser-evoked pain perception and its associated brain responses across sessions remain unclear. Here, an experiment with a within-subject repeated-measures design was performed in 22 healthy volunteers. Radiant-heat laser stimuli were delivered on subjects’ left-hand dorsum in two sessions separated by 1–5 days. We observed that laser-evoked pain perception was significantly declined across sessions, coupled with decreased brain responses in the bilateral primary somatosensory cortex (S1), right primary motor cortex, supplementary motor area, and middle cingulate cortex. Intraclass correlation coefficients between the two sessions showed “fair” to “moderate” test–retest reliability for pain perception and brain responses. Additionally, we observed lower resting-state brain activity in the right S1 and lower resting-state functional connectivity between right S1 and dorsolateral prefrontal cortex in the second session than the first session. Altogether, being possibly influenced by changes of baseline mental state, laser-evoked pain perception and brain responses showed considerable across-session variability. This phenomenon should be considered when designing experiments for laboratory studies and evaluating pain abnormalities in clinical practice.

The Effect of General Anesthesia On Test-Retest Reliability of Resting-State FMRI Metrics And Optimization of Scan Length

2021 ◽  
Author(s):  
Faezeh Vedaei ◽  
Mahdi Alizadeh ◽  
Victor M Romo ◽  
Feroze B. Mohamed ◽  
Chengyuan Wu
Keyword(s):  
Resting State ◽  
Intraclass Correlation ◽  
Resting State Fmri ◽  
Frequency Fluctuation ◽  
Retest Reliability ◽  
Factors Affecting ◽  
Fractional Frequency ◽  
Drug Resistant Epilepsy ◽  
Test Retest Reliability ◽  
Scan Length

Abstract Resting-state functional magnetic resonance imaging (rs-fMRI) has been known as a powerful tool in neuroscience. However, exploring the test-retest reliability of the metrics derived from rs-fMRI BOLD signal is essential particularly in the studies of patients with neurological development. Two factors affecting reliability of rs-fMRI measurements including the effect of anesthesia and scan length have been estimated in this study. A total of 9 patients with drug-resistant epilepsy (DRE) of requiring interstitial thermal therapy (LITT) were scanned in two states of awake and under anesthesia. At each state, two rs-fMRI sessions were obtained that each one lasted 15 minutes, and the effect of scan length was evaluated. Voxel-wise rs-fMRI metrics including amplitude of low fractional frequency fluctuation (ALFF), amplitude of low fractional frequency fluctuation (fALFF), functional connectivity (FC), and regional homogeneity (ReHo) were measured. Intraclass correlation coefficient (ICC) was calculated to estimate the reliability between two sessions of scanning for both states. Overall, our finding revealed that reliability improves under anesthesia as well as by increasing the scanning length of the scanning sessions. Furthermore, we showed that the optimal scan length to achieve reliable rs-fMRI measurements was 3.1 – 7.5 minutes shorter in an anesthetized, compared to wakeful state.

scholarly journals Test-retest reliability of task-based and resting-state blood oxygen level dependence and cerebral blood flow measures

PLoS ONE ◽  
2018 ◽  
Vol 13 (11) ◽  
pp. e0206583 ◽  
Author(s):  
Štefan Holiga ◽  
Fabio Sambataro ◽  
Cécile Luzy ◽  
Gérard Greig ◽  
Neena Sarkar ◽  
...  
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Resting State ◽  
Blood Oxygen ◽  
Oxygen Level ◽  
Blood Oxygen Level ◽  
Retest Reliability ◽  
Test Retest Reliability ◽  
Blood Oxygen Level Dependence

scholarly journals Evaluating the sensitivity of functional connectivity measures to motion artifact in resting-state fMRI data

2020 ◽  
Author(s):  
Arun S. Mahadevan ◽  
Ursula A. Tooley ◽  
Maxwell A. Bertolero ◽  
Allyson P. Mackey ◽  
Danielle S. Bassett
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Partial Correlation ◽  
Motion Artifact ◽  
Resting State Fmri ◽  
Alternative Methods ◽  
Fmri Data ◽  
Retest Reliability ◽  
Human Connectome Project ◽  
Test Retest Reliability

AbstractFunctional connectivity (FC) networks are typically inferred from resting-state fMRI data using the Pearson correlation between BOLD time series from pairs of brain regions. However, alternative methods of estimating functional connectivity have not been systematically tested for their sensitivity or robustness to head motion artifact. Here, we evaluate the sensitivity of six different functional connectivity measures to motion artifact using resting-state data from the Human Connectome Project. We report that FC estimated using full correlation has a relatively high residual distance-dependent relationship with motion compared to partial correlation, coherence and information theory-based measures, even after implementing rigorous methods for motion artifact mitigation. This disadvantage of full correlation, however, may be offset by higher test-retest reliability and system identifiability. FC estimated by partial correlation offers the best of both worlds, with low sensitivity to motion artifact and intermediate system identifiability, with the caveat of low test-retest reliability. We highlight spatial differences in the sub-networks affected by motion with different FC metrics. Further, we report that intra-network edges in the default mode and retrosplenial temporal sub-networks are highly correlated with motion in all FC methods. Our findings indicate that the method of estimating functional connectivity is an important consideration in resting-state fMRI studies and must be chosen carefully based on the parameters of the study.

scholarly journals Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI

2021 ◽  
Vol 12 (1) ◽  
pp. 66
Author(s):  
Lan Yang ◽  
Jing Wei ◽  
Ying Li ◽  
Bin Wang ◽  
Hao Guo ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Resting State Networks ◽  
Functional Magnetic Resonance ◽  
Intra Class Correlation ◽  
Retest Reliability ◽  
Brain Signals ◽  
Human Connectome Project ◽  
Test Retest Reliability ◽  
The Brain

In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much research has studied the analysis of neurodynamic indices, few have investigated its reliability. In this paper, the datasets from the Human Connectome Project have been used to explore the test–retest reliabilities of synchrony and metastability from multiple angles through intra-class correlation (ICC). The results showed that both of these indexes had fair test–retest reliability, but they are strongly affected by the field strength, the spatial resolution, and scanning interval, less affected by the temporal resolution. Denoising processing can help improve their ICC values. In addition, the reliability of neurodynamic indexes was affected by the node definition strategy, but these effects were not apparent. In particular, by comparing the test–retest reliability of different resting-state networks, we found that synchrony of different networks was basically stable, but the metastability varied considerably. Among these, DMN and LIM had a relatively higher test–retest reliability of metastability than other networks. This paper provides a methodological reference for exploring the brain dynamic neural activity by using synchrony and metastability in fMRI signals.

scholarly journals Reduced parietal alpha power and psychotic symptoms: Test-retest reliability of resting-state magnetoencephalography in schizophrenia and healthy controls

2020 ◽  
Vol 215 ◽  
pp. 229-240 ◽  
Author(s):  
Felicha T. Candelaria-Cook ◽  
Megan E. Schendel ◽  
Cesar J. Ojeda ◽  
Juan R. Bustillo ◽  
Julia M. Stephen
Keyword(s):  
Resting State ◽  
Psychotic Symptoms ◽  
Alpha Power ◽  
Healthy Controls ◽  
Retest Reliability ◽  
Test Retest Reliability

scholarly journals Boost in Test-Retest Reliability in Resting State fMRI with Predictive Modeling

2019 ◽  
Author(s):  
Aman Taxali ◽  
Mike Angstadt ◽  
Saige Rutherford ◽  
Chandra Sripada
Keyword(s):  
Predictive Modeling ◽  
Predictive Models ◽  
Resting State ◽  
Imaging Features ◽  
Retest Reliability ◽  
Modeling Methods ◽  
Aggregate Information ◽  
Human Connectome Project ◽  
Test Retest Reliability ◽  
Resting State Connectivity

AbstractRecent studies found low test-retest reliability in fMRI, raising serious concerns among researchers, but these studies mostly focused on reliability of individual fMRI features (e.g., individual connections in resting state connectivity maps). Meanwhile, neuroimaging researchers increasingly employ multivariate predictive models that aggregate information across a large number of features to predict outcomes of interest, but the test-retest reliability of predicted outcomes of these models has not previously been systematically studied. Here we apply ten predictive modeling methods to resting state connectivity maps from the Human Connectome Project dataset to predict 61 outcome variables. Compared to mean reliability of individual resting state connections, we find mean reliability of the predicted outcomes of predictive models is substantially higher for all ten modeling methods assessed. Moreover, improvement was consistently observed across all scanning and processing choices (i.e., scan lengths, censoring thresholds, volume-versus surface-based processing). For the most reliable methods, reliability of predicted outcomes was mostly, though not exclusively, in the “good” range (above 0.60).Finally, we identified three mechanisms that help to explain why predicted outcomes of predictive models have higher reliability than individual imaging features. We conclude that researchers can potentially achieve higher test-retest reliability by making greater use of predictive models.

scholarly journals Age-Related Differences in Test-Retest Reliability in Resting-State Brain Functional Connectivity

PLoS ONE ◽  
2012 ◽  
Vol 7 (12) ◽  
pp. e49847 ◽  
Author(s):  
Jie Song ◽  
Alok S. Desphande ◽  
Timothy B. Meier ◽  
Dana L. Tudorascu ◽  
Svyatoslav Vergun ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Retest Reliability ◽  
Age Related ◽  
Test Retest Reliability ◽  
Brain Functional Connectivity
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