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Electroencephalogram (EEG) microstate analysis is a promising and effective spatio-temporal method that can segment signals into several quasi-stable classes, providing a great opportunity to investigate short-range and long-range neural dynamics. However, there are still many controversies in terms of reproducibility and reliability when selecting different parameters or datatypes.In this study, five electrode configurations (91, 64, 32, 19, and 8 channels) were used to measure the reliability of microstate analysis at different electrode densities during propofol-induced sedation.First, the microstate topography and parameters at five different electrode densities were compared in the baseline (BS) condition and the moderate sedation (MD) condition, respectively. The intraclass correlation coefficient (ICC) and coefficient of variation (CV) were introduced to quantify the consistency of the microstate parameters. Second, statistical analysis and classification between BS and MD were performed to determine whether the microstate differences between different conditions remained stable at different electrode densities, and ICC was also calculated between the different conditions to measure the consistency of the results in a single condition.The results showed that in both the BS or MD condition, respectively, there were few significant differences in the microstate parameters among the 91-, 64-, and 32-channel configurations, with most of the differences observed between the 19- or 8-channel configurations and the other configurations. The ICC and CV data also showed that the consistency among the 91-, 64-, and 32-channel configurations was better than that among all five electrode configurations after including the 19- and 8-channel configurations. Furthermore, the significant differences between the conditions in the 91-channel configuration remained stable at the 64- and 32-channel resolutions, but disappeared at the 19- and 8-channel resolutions. In addition, the classification and ICC results showed that the microstate analysis became unreliable with fewer than 20 electrodes.The findings of this study support the hypothesis that microstate analysis of different brain states is more reliable with higher electrode densities; the use of a small number of channels is not recommended.

Given the importance of emotion regulation in affective disorders, emotion regulation is at the focus of attempts to identify brain biomarkers of disease risk, treatment response, and brain development. However, to be useful as an indicator for individual characteristics of brain functions – particularly as a biomarker in a clinical context – ensuring reliability is a key challenge. Here, we systematically evaluated test-retest reliability of task-based functional magnetic resonance imaging (fMRI) activity within neural networks associated with emotion generation and regulation across three sessions. Acquiring fMRI data at ultra-high field (7T), we examined region- and voxel-wise test-retest reliability of brain activity in response to a well-established emotion regulation task for predefined region-of-interests (ROIs) implicated in four neural networks. Test-retest reliability varied considerably across the emotion regulation networks and respective ROIs. However, core emotion regulation regions, including the ventrolateral and dorsolateral prefrontal cortex (vlPFC and dlPFC) as well as the middle temporal gyrus (MTG) showed high reliability. Our findings thus support the role of these prefrontal and temporal regions as promising candidates for the study of individual differences in emotion regulation as well as for neurobiological biomarkers in clinical neuroscience research.

Oscillatory activity in the beta frequency range (15–30 Hz) recorded from human sensorimotor cortex is of increasing interest as a putative biomarker of motor system function and dysfunction. Despite its increasing use in basic and clinical research, surprisingly little is known about the test-retest reliability of spectral power and peak frequency measures of beta oscillatory signals from sensorimotor cortex. Establishing that these beta measures are stable over time in healthy populations is a necessary precursor to their use in the clinic. Here, we used scalp electroencephalography (EEG) to evaluate intra-individual reliability of beta-band oscillations over six sessions, focusing on changes in beta activity during movement (Movement-Related Beta Desynchronization, MRBD) and after movement termination (Post-Movement Beta Rebound, PMBR). Subjects performed visually-cued unimanual wrist flexion and extension. We assessed Intraclass Correlation Coefficients (ICC) and between-session correlations for spectral power and peak frequency measures of movement-related and resting beta activity. Movement-related and resting beta power from both sensorimotor cortices was highly reliable across sessions. Resting beta power yielded highest reliability (average ICC=0.903), followed by MRBD (average ICC=0.886) and PMBR (average ICC=0.663). Notably, peak frequency measures yielded lower ICC values compared to the assessment of spectral power, particularly for movement-related beta activity (ICC=0.386–0.402). Our data highlight that power measures of movement-related beta oscillations are highly reliable, while corresponding peak frequency measures show greater intra-individual variability across sessions. Importantly, our finding that beta power estimates show high intra-individual reliability over time serves to validate the notion that these measures reflect meaningful individual differences that can be utilised in basic research and clinical studies. [ABSTRACT FROM AUTHOR]

Abstract: [11C]NOP-1A is a novel high-affinity PET ligand for imaging nociceptin/orphanin FQ peptide (NOP) receptors. Here, we report reproducibility and reliability measures of binding parameter estimates for [11C]NOP-1A binding in the brain of healthy humans. After intravenous injection of [11C]NOP-1A, PET scans were conducted twice on eleven healthy volunteers on the same (10/11 subjects) or different (1/11 subjects) days. Subjects underwent serial sampling of radial arterial blood to measure parent radioligand concentrations. Distribution volume (V T; a measure of receptor density) was determined by compartmental (one- and two-tissue) modeling in large regions and by simpler regression methods (graphical Logan and bilinear MA1) in both large regions and voxel data. Retest variability and intraclass correlation coefficient (ICC) of V T were determined as measures of reproducibility and reliability respectively. Regional [11C]NOP-1A uptake in the brain was high, with a peak radioactivity concentration of 4–7 SUV (standardized uptake value) and a rank order of putamen>cingulate cortex>cerebellum. Brain time–activity curves fitted well in 10 of 11 subjects by unconstrained two-tissue compartmental model. The retest variability of V T was moderately good across brain regions except cerebellum, and was similar across different modeling methods, averaging 12% for large regions and 14% for voxel-based methods. The retest reliability of V T was also moderately good in most brain regions, except thalamus and cerebellum, and was similar across different modeling methods averaging 0.46 for large regions and 0.48 for voxels having gray matter probability >20%. The lowest retest variability and highest retest reliability of V T were achieved by compartmental modeling for large regions, and by the parametric Logan method for voxel-based methods. Moderately good reproducibility and reliability measures of V T for [11C]NOP-1A make it a useful PET ligand for comparing NOP receptor binding between different subject groups or under different conditions in the same subject. [Copyright &y& Elsevier]

Abstract: The reproducibility of three different aspects of fMRI activations—namely binary activation maps, effect size and spatial distribution of local maxima—was evaluated for an auditory sentence comprehension task with high attention demand on a group of 17 subjects that were scanned on five different occasions. While in the scanner subjects were asked to listen to a series of six short everyday sentences from the CUNY sentence test. Comprehension and attention to the stimuli were monitored after each listen condition epoch by having subjects answer a series of multiple-choice questions. Statistical maps of activation for the listen condition were computed at three different levels: overall results for all imaging sessions, group-level/single-session results for each of the five imaging occasions, and single-subject/single-session results computed for each subject and each scanning occasion independently. The experimental task recruited a distributed bilateral network with processing nodes located in the lateral temporal cortex, inferior frontal cortex, medial BA6, medial occipital cortex and subcortical structures such as the putamen and the thalamus. Reproducibility of these activations at the group level was high (83.95% of the imaged volume was consistently classified as active/inactive across all five imaging sessions), indicating that sites of neuronal activity associated with auditory comprehension can reliably be detected with fMRI in healthy subjects, across repeated measures after group averaging. At the single-subject level reproducibility ranged from moderate to high, although no significant differences were found on behavioral measures across subjects or sessions. This result suggests that contextual differences—i.e., those specific to each imaging session, can modulate our ability to detect fMRI activations associated with speech comprehension in individual subjects. [Copyright &y& Elsevier]

Once considered mere noise, fMRI-based functional connectivity has become a major neuroscience tool in part due to early studies demonstrating its reliability. These fundamental studies revealed only the tip of the iceberg; over the past decade, many test-retest reliability studies have continued to add nuance to our understanding of this complex topic. A summary of these diverse and at times contradictory perspectives is needed. We aimed to summarize the existing knowledge regarding test-retest reliability of functional connectivity at the most basic unit of analysis: the individual edge level. This entailed (1) a meta-analytic estimate of reliability and (2) a review of factors influencing reliability. A search of Scopus was conducted to identify studies that estimated edge-level test-retest reliability. To facilitate comparisons across studies, eligibility was restricted to studies measuring reliability via the intraclass correlation coefficient (ICC). The meta-analysis included a random effects pooled estimate of mean edge-level ICC, with studies nested within datasets. The review included a narrative summary of factors influencing edge-level ICC. From an initial pool of 212 studies, 44 studies were identified for the qualitative review and 25 studies for quantitative meta-analysis. On average, individual edges exhibited a "poor" ICC of 0.29 (95% CI = 0.23 to 0.36). The most reliable measurements tended to involve: (1) stronger, within-network, cortical edges, (2) eyes open, awake, and active recordings, (3) more within-subject data, (4) shorter test-retest intervals, (5) no artifact correction (likely due in part to reliable artifact), and (6) full correlation-based connectivity with shrinkage. This study represents the first meta-analysis and systematic review investigating test-retest reliability of edge-level functional connectivity. Key findings suggest there is room for improvement, but care should be taken to avoid promoting reliability at the expense of validity. By pooling existing knowledge regarding this key facet of accuracy, this study supports broader efforts to improve inferences in the field. • We present the first meta-analytic review of functional connectivity reliability. • On average, individual connections exhibit a "poor" ICC of 0.29. • Study characteristics that influence reliability are summarized and discussed. • Findings suggest room for improvement and need to also consider validity. [ABSTRACT FROM AUTHOR]

Novel MR image acquisition strategies have been investigated to elicit contrast within the thalamus, but direct visualization of individual thalamic nuclei remains a challenge because of their small size and the low intrinsic contrast between adjacent nuclei. We present a step-by-step specific optimization of the 3D MPRAGE pulse sequence at 7T to visualize the intra-thalamic nuclei. We first measured T1 values within different sub-regions of the thalamus at 7T in 5 individuals. We used these to perform simulations and sequential experimental measurements (n=17) to tune the parameters of the MPRAGE sequence. The optimal set of parameters was used to collect high-quality data in 6 additional volunteers. Delineation of thalamic nuclei was performed twice by one rater and MR-defined nuclei were compared to the classic Morel histological atlas. T1 values within the thalamus ranged from 1400ms to 1800ms for adjacent nuclei. Using these values for theoretical evaluations combined with in vivo measurements, we showed that a short inversion time (TI) close to the white matter null regime (TI=670ms) enhanced the contrast between the thalamus and the surrounding tissues, and best revealed intra-thalamic contrast. At this particular nulling regime, lengthening the time between successive inversion pulses (TS=6000ms) increased the thalamic signal and contrast and lengthening the α pulse train time (N*TR) further increased the thalamic signal. Finally, a low flip angle during the gradient echo acquisition (α=4°) was observed to mitigate the blur induced by the evolution of the magnetization along the α pulse train. This optimized set of parameters enabled the 3D delineation of 15 substructures in all 6 individuals; these substructures corresponded well with the known anatomical structures of the thalamus based on the classic Morel atlas. The mean Euclidean distance between the centers of mass of MR- and Morel atlas-defined nuclei was 2.67mm (±1.02mm). The reproducibility of the MR-defined nuclei was excellent with intraclass correlation coefficient measured at 0.997 and a mean Euclidean distance between corresponding centers of mass found at first versus second readings of 0.69mm (±0.38mm). This 7T strategy paves the way to better identification of thalamic nuclei for neurosurgical planning and investigation of regional changes in neurological disorders., (© 2013.)