Spatial variation of changes in test–retest reliability of functional connectivity after global signal regression: The effect of considering hemodynamic delay

Global signal regression (GSR) is a controversial analysis method, since its removal of signal has been observed to reduce the reliability of functional connectivity estimates. Here, we used test–retest reliability to characterize potential differences in spatial patterns between conventional, static GSR (sGSR) and a novel dynamic form of GSR (dGSR). In contrast with sGSR, dGSR models the global signal at a time delay to correct for blood arrival time. Thus, dGSR accounts for greater variation in global signal, removes blood‐flow‐related nuisance signal, and leaves higher quality neuronal signal remaining. We used intraclass correlation coefficients (ICCs) to estimate the reliability of functional connectivity in 462 healthy controls from the Human Connectome Project. We tested across two factors: denoising method used (control, sGSR, and dGSR), and interacquisition interval (between days, or within session while varying phase encoding direction). Reliability was estimated regionally to identify topographic patterns for each condition. sGSR and dGSR provided global reductions in reliability compared with the non‐GSR control. Test–retest reliability was highest in the frontoparietal and default mode regions, and lowest in sensorimotor cortex for all conditions. dGSR provides more effective denoising in regions where both strategies greatly reduce reliability. Both GSR methods substantially reduced test–retest reliability, which was most evident in brain regions that had low reliability prior to denoising. These findings suggest that reliability of interregional correlation is likely inflated by the global signal, which is thought to primarily reflect dynamic blood flow.     

Reliability of task‐evoked neural activation during face‐emotion paradigms: Effects of scanner and psychological processes

Assessing and improving test–retest reliability is critical to efforts to address concerns about replicability of task‐based functional magnetic resonance imaging. The current study uses two statistical approaches to examine how scanner and task‐related factors influence reliability of neural response to face‐emotion viewing. Forty healthy adult participants completed two face‐emotion paradigms at up to three scanning sessions across two scanners of the same build over approximately 2 months. We examined reliability across the main task contrasts using Bayesian linear mixed‐effects models performed voxel‐wise across the brain. We also used a novel Bayesian hierarchical model across a predefined whole‐brain parcellation scheme and subcortical anatomical regions. Scanner differences accounted for minimal variance in temporal signal‐to‐noise ratio and task contrast maps. Regions activated during task at the group level showed higher reliability relative to regions not activated significantly at the group level. Greater reliability was found for contrasts involving conditions with clearly distinct visual stimuli and associated cognitive demands (e.g., face vs. nonface discrimination) compared to conditions with more similar demands (e.g., angry vs. happy face discrimination). Voxel‐wise reliability estimates tended to be higher than those based on predefined anatomical regions. This work informs attempts to improve reliability in the context of task activation patterns and specific task contrasts. Our study provides a new method to estimate reliability across a large number of regions of interest and can inform researchers'' selection of task conditions and analytic contrasts.     

Reproducibility of graph measures derived from resting‐state MEG functional connectivity metrics in sensor and source spaces

Prior studies have used graph analysis of resting‐state magnetoencephalography (MEG) to characterize abnormal brain networks in neurological disorders. However, a present challenge for researchers is the lack of guidance on which network construction strategies to employ. The reproducibility of graph measures is important for their use as clinical biomarkers. Furthermore, global graph measures should ideally not depend on whether the analysis was performed in the sensor or source space. Therefore, MEG data of the 89 healthy subjects of the Human Connectome Project were used to investigate test–retest reliability and sensor versus source association of global graph measures. Atlas‐based beamforming was used for source reconstruction, and functional connectivity (FC) was estimated for both sensor and source signals in six frequency bands using the debiased weighted phase lag index (dwPLI), amplitude envelope correlation (AEC), and leakage‐corrected AEC. Reliability was examined over multiple network density levels achieved with proportional weight and orthogonal minimum spanning tree thresholding. At a 100% density, graph measures for most FC metrics and frequency bands had fair to excellent reliability and significant sensor versus source association. The greatest reliability and sensor versus source association was obtained when using amplitude metrics. Reliability was similar between sensor and source spaces when using amplitude metrics but greater for the source than the sensor space in higher frequency bands when using the dwPLI. These results suggest that graph measures are useful biomarkers, particularly for investigating functional networks based on amplitude synchrony.     

Inverse modeling in magnetic source imaging: Comparison of MUSIC,SAM(g2), and sLORETA to interictal intracranial EEG

Magnetoencephalography (MEG) is used in the presurgical work‐up of patients with focal epilepsy. In particular, localization of MEG interictal spikes may guide or replace invasive electroencephalography monitoring that is required in difficult cases. From literature, it is not clear which MEG source localization method performs best in this clinical setting. Therefore, we applied three source localization methods to the same data from a large patient group for which a gold standard, interictal spikes as identified in electrocorticography (ECoG), was available. The methods used were multiple signal classification (MUSIC), Synthetic Aperture Magnetometry kurtosis [SAM(g2)], and standardized low‐resolution electromagnetic tomography. MEG and ECoG data from 38 patients with refractory focal epilepsy were obtained. Results of the three source localization methods applied to the interictal MEG data were assigned to predefined anatomical regions. Interictal spikes as identified in ECoG were also assigned to these regions. Identified regions by each MEG method were compared to ECoG. Sensitivity and positive predictive value (PPV) of each MEG method were calculated. All three MEG methods showed a similar overall correlate with ECoG spikes, but the methods differ in which regions they detect. The choice of the inverse model thus has an unexpected influence on the results of magnetic source imaging. Combining inverse methods and seeking consensus can be used to improve specificity at the cost of some sensitivity. Combining MUSIC with SAM(g2) gives the best results (sensitivity = 38% and PPV = 82%). Hum Brain Mapp 34:2032–2044, 2013. © 2012 Wiley Periodicals, Inc.     

Repeatability of parametric methods for [18F]florbetapir imaging in Alzheimer’s disease and healthy controls: A test–retest study

Accumulation of amyloid beta (Aβ) is one of the pathological hallmarks of Alzheimer’s disease (AD), which can be visualized using [¹⁸F]florbetapir positron emission tomography (PET). The aim of this study was to evaluate various parametric methods and to assess their test-retest (TRT) reliability. Two 90 min dynamic [¹⁸F]florbetapir PET scans, including arterial sampling, were acquired (n = 8 AD patient, n = 8 controls). The following parametric methods were used; (reference:cerebellum); Logan and spectral analysis (SA), receptor parametric mapping (RPM), simplified reference tissue model2 (SRTM2), reference Logan (rLogan) and standardized uptake value ratios (SUV_r(50–70)). BP_ND+1, DVR, V_T and SUVr were compared with corresponding estimates (V_T or DVR) from the plasma input reversible two tissue compartmental (2T4k_V_B) model with corresponding TRT values for 90-scan duration. RPM (r² = 0.92; slope = 0.91), Logan (r² = 0.95; slope = 0.84) and rLogan (r² = 0.94; slope = 0.88), and SRTM2 (r² = 0.91; slope = 0.83), SA (r² = 0.91; slope = 0.88), SUVr (r² = 0.84; slope = 1.16) correlated well with their 2T4k_V_B counterparts. RPM (controls: 1%, AD: 3%), rLogan (controls: 1%, AD: 3%) and SUV_r(50–70) (controls: 3%, AD: 8%) showed an excellent TRT reliability. In conclusion, most parametric methods showed excellent performance for [¹⁸F]florbetapir, but RPM and rLogan seem the methods of choice, combining the highest accuracy and best TRT reliability.     

Electroencephalographic analysis of cortico-muscular coherence: reference effect, volume conduction and generator mechanism.

OBJECTIVE: To measure the synchrony between cortical and muscle oscillatory activities, the coherence estimate between EEG and EMG was computed. METHODS: The multichannel electroencephalogram (EEG) and electromyogram (EMG) of the right abductor pollicis brevis muscle were recorded in 5 normal volunteers. Various types of EEG derivation methods were systematically compared to establish a standard method to study cortico-muscular coupling. RESULTS: The use of a reference-free EEG derivation (current source density) greatly improved cortico-muscular coherence. In all subjects, EEGs over the left sensorimotor cortex were coherent with EMG (mean peak frequency: 18.7 Hz, mean highest coherence: 0.124). The time lag from cortex to muscle in 14-50 Hz was 14.3 ms. EEG source derivation revealed that both radial and tangential generators in the precentral cortex might contribute to this phenomenon. In the EEG signals using common average reference, an artifactual coherence peak over the medial frontal area was observed, which might largely be explained by volume conduction from the primary sensorimotor cortex. CONCLUSIONS: We conclude that the current source density or its approximation is preferable to estimate the cortico-muscular coherence and that the interpretation of such coherence using referenced EEGs should be taken with care.     

Generator localization by current source density (CSD): Implications of volume conduction and field closure at intracranial and scalp resolutions

The topographic ambiguity and reference-dependency that has plagued EEG/ERP research throughout its history are largely attributable to volume conduction, which may be concisely described by a vector form of Ohm’s Law. This biophysical relationship is common to popular algorithms that infer neuronal generators via inverse solutions. It may be further simplified as Poisson’s source equation, which identifies underlying current generators from estimates of the second spatial derivative of the field potential (Laplacian transformation). Intracranial current source density (CSD) studies have dissected the “cortical dipole” into intracortical sources and sinks, corresponding to physiologically-meaningful patterns of neuronal activity at a sublaminar resolution, much of which is locally cancelled (i.e., closed field). By virtue of the macroscopic scale of the scalp-recorded EEG, a surface Laplacian reflects the radial projections of these underlying currents, representing a unique, unambiguous measure of neuronal activity at scalp. Although the surface Laplacian requires minimal assumptions compared to complex, model-sensitive inverses, the resulting waveform topographies faithfully summarize and simplify essential constraints that must be placed on putative generators of a scalp potential topography, even if they arise from deep or partially-closed fields. CSD methods thereby provide a global empirical and biophysical context for generator localization, spanning scales from intracortical to scalp recordings.     

A systematic evaluation of source reconstruction of resting MEG of the human brain with a new high‐resolution atlas: Performance,precision, and parcellation

Noninvasive functional neuroimaging of the human brain can give crucial insight into the mechanisms that underpin healthy cognition and neurological disorders. Magnetoencephalography (MEG) measures extracranial magnetic fields originating from neuronal activity with high temporal resolution, but requires source reconstruction to make neuroanatomical inferences from these signals. Many source reconstruction algorithms are available, and have been widely evaluated in the context of localizing task‐evoked activities. However, no consensus yet exists on the optimum algorithm for resting‐state data. Here, we evaluated the performance of six commonly‐used source reconstruction algorithms based on minimum‐norm and beamforming estimates. Using human resting‐state MEG, we compared the algorithms using quantitative metrics, including resolution properties of inverse solutions and explained variance in sensor‐level data. Next, we proposed a data‐driven approach to reduce the atlas from the Human Connectome Project''s multi‐modal parcellation of the human cortex based on metrics such as MEG signal‐to‐noise‐ratio and resting‐state functional connectivity gradients. This procedure produced a reduced cortical atlas with 230 regions, optimized to match the spatial resolution and the rank of MEG data from the current generation of MEG scanners. Our results show that there is no “one size fits all” algorithm, and make recommendations on the appropriate algorithms depending on the data and aimed analyses. Our comprehensive comparisons and recommendations can serve as a guide for choosing appropriate methodologies in future studies of resting‐state MEG.     

Electro‐acupuncture and its combination with adult stem cell transplantation for spinal cord injury treatment: A summary of current laboratory findings and a review of literature

The incidence and disability rate of spinal cord injury (SCI) worldwide are high, imposing a heavy burden on patients. Considerable research efforts have been directed toward identifying new strategies to effectively treat SCI. Governor Vessel electro‐acupuncture (GV‐EA), used in traditional Chinese medicine, combines acupuncture with modern electrical stimulation. It has been shown to improve the microenvironment of injured spinal cord (SC) by increasing levels of endogenous neurotrophic factors and reducing inflammation, thereby protecting injured neurons and promoting myelination. In addition, axons extending from transplanted stem cell‐derived neurons can potentially bridge the two severed ends of tissues in a transected SC to rebuild neuronal circuits and restore motor and sensory functions. However, every single treatment approach to severe SCI has proven unsatisfactory. Combining different treatments—for example, electro‐acupuncture (EA) with adult stem cell transplantation—appears to be a more promising strategy. In this review, we have summarized the recent progress over the past two decades by our team especially in the use of GV‐EA for the repair of SCI. By this strategy, we have shown that EA can stimulate the nerve endings of the meningeal branch. This would elicit the dorsal root ganglion neurons to secrete excess amounts of calcitonin gene‐related peptide centrally in the SC. The neuropeptide then activates the local cells to secrete neurotrophin‐3 (NT‐3), which mediates the survival and differentiation of donor stem cells overexpressing the NT‐3 receptor, at the injury/graft site of the SC. Increased local production of NT‐3 facilitates reconstruction of host neural tissue such as nerve fiber regeneration and myelination. All this events in sequence would ultimately strengthen the cortical motor‐evoked potentials and restore the motor function of paralyzed limbs. The information presented herein provides a basis for future studies on the clinical application of GV‐EA and adult stem cell transplantation for the treatment of SCI.     

Simplified quantification of [18F]FE-PE2I PET in Parkinson’s disease: Discriminative power,test–retest reliability and longitudinal validity during early peak and late pseudo-equilibrium

Quantification of dopamine transporter (DAT) availability with [¹⁸F]FE-PE2I PET enables the detection of presynaptic dopamine deficiency and provides a potential progression marker for Parkinson`s disease (PD). Simplified quantification is feasible, but the time window of short acquisition protocols may have a substantial impact on the reliability of striatal binding estimates. Dynamic [¹⁸F]FE-PE2I PET data of cross-sectional (33 PD patients, 24 controls), test–retest (9 patients), and longitudinal (12 patients) cohorts were used to assess the variability and reliability of specific binding ratios (SBR) measured during early peak and late pseudo-equilibrium. Receiver operating characteristics area under the curve (PD vs. controls) was high for early (0.996) and late (0.991) SBR. Early SBR provided more favourable effect size, absolute variability, and standard error of measurement than late SBR (caudate: 1.29 vs. 1.23; 6.9% vs. 9.8%; 0.09 vs. 0.20; putamen: 1.75 vs. 1.67; 7.7% vs. 14.0%; 0.08 vs. 0.17). The annual percentage change was comparable for both time windows (−7.2%–8.5%), but decline was significant only for early SBR. Whereas early and late [¹⁸F]FE-PE2I PET acquisitions have similar discriminative power to separate PD patients and controls, the early peak equilibrium acquisition can be recommended if [¹⁸F]FE-PE2I is used to measure longitudinal changes of DAT availability.