Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA

In functional magnetic resonance imaging (fMRI) analysis, although the univariate general linear model (GLM) is currently the dominant approach to brain activation detection, there is growing interest in multivariate approaches such as principal component analysis, canonical variate analysis (CVA), independent component analysis and cluster analysis, which have the potential to reveal neural networks and functional connectivity in the brain. To understand the effect of processing options on performance of multivariate model-based fMRI processing pipelines with real fMRI data, we investigated the impact of commonly used fMRI preprocessing steps and optimized the associated multivariate CVA-based, single-subject processing pipelines with the NPAIRS (nonparametric prediction, activation, influence and reproducibility resampling) performance metrics [prediction accuracy and statistical parametric image (SPI) reproducibility] on the Fiswidgets platform. We also compared the single-subject SPIs of univariate GLM with multivariate CVA-based processing pipelines from SPM, FSL.FEAT, NPAIRS.GLM and NPAIRS.CVA software packages (or modules) using a novel second-level CVA. We found that for the block-design data, (a) slice timing correction and global intensity normalization have little consistent impact on the fMRI processing pipeline, but spatial smoothing, temporal detrending or high-pass filtering, and motion correction significantly improved pipeline performance across all subjects; (b) the combined optimization of spatial smoothing, temporal detrending and CVA model parameters on average improved between-subject reproducibility; and (c) the most important pipeline choices include univariate or multivariate statistical models and spatial smoothing. This study suggests that considering options other than simply using GLM with a fixed spatial filter may be of critical importance in determining activation patterns in BOLD fMRI studies.     

Functional phantom for fMRI: a feasibility study

Functional magnetic resonance imaging (fMRI) reveals changes in blood oxygen level-dependent (BOLD) signal after considerable processing. This paper describes the implementation and testing of an fMRI phantom where electric current applied to a thin wire within a proton-rich medium substituted BOLD distortion of the magnetic field; the scanner detects these two distortions as practically identical signal changes. The magnitude of the change depended on the current strength. The phantom has a number of possible applications. Signal changes across sessions, days, instruments and individuals could be monitored. Placing the phantom close to a subject during an fMRI experiment could allow differentiating sensitivity changes in the scanner due to instrumentation from changes in the subject's state and performance during the experiment. The spatial extent of brain activations and effects of various changes in the chain of image formation could be analyzed using current-induced "activations". Furthermore, the phantom could expedite fMRI sequence development by reducing the need to scan human subjects, who introduce uncertainty to the signal. Thus, this fMRI phantom could be useful for both cognitive fMRI studies and scanner calibration.     

To smooth or not to smooth? ROC analysis of perfusion fMRI data

Blood oxygenation level dependent (BOLD) contrast has been widely used for visualizing regional neural activation. Temporal filtering and parameter estimation algorithms are generally used to account for the intrinsic temporal autocorrelation present in BOLD data. Arterial spin labeling perfusion imaging is an emerging methodology for visualizing regional brain function both at rest and during activation. Perfusion contrast manifests different noise properties compared with BOLD contrast, represented by the even distribution of noise power and spatial coherence across the frequency spectrum. Consequently, different strategies are expected to be employed in the statistical analysis of functional magnetic resonance imaging (fMRI) data based on perfusion contrast. In this study, the effect of different analysis methods upon signal detection efficacy, as assessed by receiver operator characteristic (ROC) measures, was examined for perfusion fMRI data. Simulated foci of neural activity of varying amplitude and spatial extent were added to resting perfusion data, and the accuracy of each analysis was evaluated by comparing the results with the known distribution of pseudo-activation. In contrast to the BOLD fMRI, temporal smoothing or filtering reduces the power of perfusion fMRI data analyses whereas spatial smoothing is beneficial to the efficacy of analyses.     

Improved B0 field map estimation for high field EPI

Echo planar imaging (EPI) is an ultrafast magnetic resonance imaging (MRI) technique that allows one to acquire a 2D image in about 100 ms. Unfortunately, the standard EPI images suffer from substantial geometric distortions, mainly originating from susceptibility differences in adjacent tissues. To reduce EPI distortions, correction methods based on a field map, which is a map of the off-resonance frequencies, have been developed. In this work, a nonlinear least squares estimator is used to optimize the estimation of the field map of the B₀ field. The model of the EPI and reference data includes parameters for the phase evolution, the complex magnitude, the relaxation of the MRI signal and the EPI-specific phase difference between odd and even echoes, and from these parameters, additional corrections might be computed. The reference data required to estimate the field map can be acquired with a modified EPI-sequence. The proposed method is tested on simulated as well as experimental data and proves to be significantly more robust against noise, compared to the previously suggested method.     

Retinotopic mapping with spin echo BOLD at 7T

For blood oxygenation level-dependent (BOLD) functional MRI experiments, contrast-to-noise ratio (CNR) increases with increasing field strength for both gradient echo (GE) and spin echo (SE) BOLD techniques. However, susceptibility artifacts and nonuniform coil sensitivity profiles complicate large field-of-view fMRI experiments (e.g., experiments covering multiple visual areas instead of focusing on a single cortical region). Here, we use SE BOLD to acquire retinotopic mapping data in early visual areas, testing the feasibility of SE BOLD experiments spanning multiple cortical areas at 7T. We also use a recently developed method for normalizing signal intensity in T₁-weighted anatomical images to enable automated segmentation of the cortical gray matter for scans acquired at 7T with either surface or volume coils. We find that the CNR of the 7T GE data (average single-voxel, single-scan stimulus coherence: 0.41) is almost twice that of the 3T GE BOLD data (average coherence: 0.25), with the CNR of the SE BOLD data (average coherence: 0.23) comparable to that of the 3T GE data. Repeated measurements in individual subjects find that maps acquired with 1.8-mm resolution at 3T and 7T with GE BOLD and at 7T with SE BOLD show no systematic differences in either the area or the boundary locations for V1, V2 and V3, demonstrating the feasibility of high-resolution SE BOLD experiments with good sensitivity throughout multiple visual areas.     

Precise determination of Stokes shifts in stimulated-Brillouin-scattering-active substances with the use of Brillouin loop lasers pumped by Gaussian monochromatic beams

A method for determination of Stokes shifts in stimulated Brillouin scattering is suggested and implemented; the method is based on the jumplike behavior of the spatial structure of the emission of a Brillouin loopscheme laser upon change in the loop length in the vicinity of Δk _B L=π(2n+1), where Δk _B is the Brillouin shift,L is the loop length, andn is an integer.     

Depression recognition using resting-state and event-related fMRI signals

Purpose

This paper aimed to develop a method for depression detection using blood-oxygen-level-dependent (BOLD) response estimated from event-related signals and resting-state functional magnetic resonance imaging (fMRI) signals together.

Materials and Methods

Thirteen patients with unipolar depression and matched healthy subjects were recruited. Resting state data of each subject were collected. Thereafter, event-related paradigm was undertaken using sad facial stimuli. The resting-state fMRI signal was deemed as the baseline of each subject's activity. Coefficient marks were designed to sort and select temporal independent components of event-related signals. Thereafter, stimulus-evoked BOLD response components inside event-related signal were extracted and taken as features to discriminate depressive patients from healthy controls.

Results

Accuracy rate for depression recognition was 77.27% with P value of .017 for whole-brain analysis and 81.82% with P value of .009 for region-of-interest analysis. The effectiveness and the superiority of the proposed method for disease recognition were demonstrated via the performance comparison with three other typical methods.

Conclusions

The proposed model was effective in depression recognition.     

Sensitivity limitations of high-resolution perfusion-based human fMRI at 7 Tesla

The study of the brain's functional organization at laminar and columnar level of the cortex with blood oxygenation-level dependent (BOLD) functional MRI (fMRI) is affected by the contribution of large veins downstream from the microvascular response to brain activity. Blood volume- and especially perfusion-based techniques may reduce this problem because of their reduced sensitivity to venous effects, but may not allow the same spatial resolution because of smaller signal changes associated with brain activity. Here we investigated the practical resolution limits of perfusion-weighted fMRI in human visual stimulation experiments. For this purpose, we used a highly sensitive, single-shot perfusion labeling (SSPL) technique at 7 T and compared sensitivity to detect visual activation at low (2 mm, n = 10) and high (1 mm, n = 8) nominal isotropic spatial, and 3 s temporal, resolution with BOLD in 5½-minute-long experiments. Despite the smaller absolute signal change with activation, 2 mm resolution SSPL yielded comparable sensitivity to BOLD. This was attributed to a superior suppression of physiological noise with SSPL. However, at 1 mm nominal resolution, SSPL sensitivity fell on average at least 42% below that of BOLD, and detection of visual activation was compromised. This is explained by the fact that at high resolution, with both techniques, typically thermal noise rather than physiological noise dominates sensitivity. The observed sensitivity loss implies that to perform 1-mm resolution, perfusion weighted fMRI with a robustness similar to BOLD, scan times that are almost 3 times longer than the comparable BOLD experiment are required. This is in line with or slightly better than previous comparisons between perfusion-weighted fMRI and BOLD. The lower sensitivity has to be weighed against the spatial fidelity advantages of high-resolution perfusion-weighted fMRI.     

False positive control of activated voxels in single fMRI analysis using bootstrap resampling in comparison to spatial smoothing

Functional magnetic resonance imaging (fMRI) is an effective tool for the measurement of brain neuronal activities. To date, several statistical methods have been proposed for analyzing fMRI datasets to select true active voxels among all the voxels appear to be positively activated. Finding a reliable and valid activation map is very important and becomes more crucial in clinical and neurosurgical investigations of single fMRI data, especially when pre-surgical planning requires accurate lateralization index as well as a precise localization of activation map.Defining a proper threshold to determine true activated regions, using common statistical processes, is a challenging task. This is due to a number of variation sources such as noise, artifacts, and physiological fluctuations in time series of fMRI data which affect spatial distribution of noise in an expected uniform activated region. Spatial smoothing methods are frequently used as a preprocessing step to reduce the effect of noise and artifacts. The smoothing may lead to a shift and enlargement of activation regions, and in some extend, unification of distinct regions.In this article, we propose a bootstrap resampling technique for analyzing single fMRI dataset with the aim of finding more accurate and reliable activated regions. This method can remove false positive voxels and present high localization accuracy in activation map without any spatial smoothing and statistical threshold setting.     

Neuronal event detection in fMRI time series using iterative deconvolution techniques

An iterative estimation algorithm for deconvolution of neuronal activity from Blood Oxygen Level Dependent (BOLD) time series data is presented. The algorithm requires knowledge of the hemodynamic impulse response function but does not require knowledge of the stimulation function. The method uses majorization-minimization of a cost function to find an optimal solution to the inverse problem. The cost function includes penalties for the l₁ norm, total variation and negativity. The algorithm is able to identify the occurrence of neuronal activity bursts from BOLD time series accurately. The accuracy of the algorithm was tested in simulations and experimental fMRI data using blocked and event-related designs. The simulations revealed that the algorithm is most sensitive to contrast-to-noise ratio levels and to errors in the assumed hemodynamic model and least sensitive to autocorrelation in the noise. Within normal fMRI conditions, the method is effective for event detection.     

Correlations and accuracy of estimation of spectroscopic constants and term values

A comparison and evaluation of the various methods for reducing spectroscopic data to spectroscopic constants or term values is made with the aid of an analysis of a number of “synthetic” Σ-Σ bands generated from fixed sets of constants with random noise superimposed on the line positions. It is shown that the strong correlations that exist between the upper-state constants B′, D′ and the lower-state constants B₀, D₀ can be effectively broken up by using the difference constants ΔB = B′ - B₀ and ΔD = D′ - D₀, along with ν₀, for representing the upper states. The lower state constants B₀ and D₀ and their standard errors calculated from the combination differences Δ₂F″(J) are shown to be as good as those obtained from direct polynomial fits. If data for a number of bands originating in the same lower state are available, a considerable increase in accuracy of estimating the lower-state constants can be attained by analyzing the bands simultaneously, e.g., using combination differences, provided the data are free from systematic errors. The dependence of the accuracy of determining the constants B₀, D₀, ν₀, ΔB, and ΔD on the extent of the band analyzed was investigated by varying the minimum and maximum J-values. The plots showing this dependence for both the actual errors and standard errors can be used e.g., to assess the band size necessary to attain a desired accuracy for a given constant.Åslund's term-value method is cast in a form which permits simple derivation of explicit formulas for the correlation coefficients connecting all the upper- and lower-state term values, and of explicit relations between the term values and the combination differences. Modifications of the term-value method suitable for the case where one or more transitions originate in an unperturbed state are explored. It is shown that the “difference term values” referred to the lower (unperturbed) state with the same value of J, T_i(J)-T₀(J), are essentially uncorrelated to the lower state constants B₀ and D₀. Since these quantities can be expressed directly as the eigenvalues of the energy matrix for a given J in the presence of perturbations, their use for representing the energies of perturbed rovibronic states is recommended.     

Learning-based structurally-guided construction of resting-state functional correlation tensors

Functional magnetic resonance imaging (fMRI) measures changes in blood-oxygenation-level-dependent (BOLD) signals to detect brain activities. It has been recently reported that the spatial correlation patterns of resting-state BOLD signals in the white matter (WM) also give WM information often measured by diffusion tensor imaging (DTI). These correlation patterns can be captured using functional correlation tensor (FCT), which is analogous to the diffusion tensor (DT) obtained from DTI. In this paper, we propose a noise-robust FCT method aiming at further improving its quality, and making it eligible for further neuroscience study. The novel FCT estimation method consists of three major steps: First, we estimate the initial FCT using a patch-based approach for BOLD signal correlation to improve the noise robustness. Second, by utilizing the relationship between functional and diffusion data, we employ a regression forest model to learn the mapping between the initial FCTs and the corresponding DTs using the training data. The learned forest can then be applied to predict the DTI-like tensors given the initial FCTs from the testing fMRI data. Third, we re-estimate the enhanced FCT by utilizing the DTI-like tensors as a feedback guidance to further improve FCT computation. We have demonstrated the utility of our enhanced FCTs in Alzheimer's disease (AD) diagnosis by identifying mild cognitive impairment (MCI) patients from normal subjects.     

Optimized gradient spoiling of UTE VFA-AFI sequences for robust T1 estimation with B1-field correction

Quantifying T₁ relaxation times is a challenge because inhomogeneities of the B₁ field have to be corrected to obtain proper values. It is a particular challenge in tissues with short T₂^⁎ values, for which conventional MRI techniques do not provide sufficient signal. Recently, a B₁-field correction technique called AFI (Actual Flip angle Imaging) has been introduced that can be combined with UTE (ultra-short echo-time) sequences, which have much shorter echo times compared to conventional MRI techniques, allowing quantification of signal in short T₂^⁎ tissues. A disadvantage of AFI is that it requires very long relaxation delays between repetitions to minimize the influence of imperfect spoiling of transverse magnetization on signal behavior. In this work, we propose a novel spoiling scheme for the AFI sequence that efficiently provides accurate B₁ correction maps with strongly reduced acquisition time. We validated the method with both phantom and preliminary in vivo results.     

On the separation of initial and final state effects in photoelectron spectroscopy using an extension of the auger-parameter concept

First, we show that the quantity Δβ(i) = ΔE_A(kii) + 2ΔE_B(i) — ΔE_B(k) is directly related to the final state relaxation contribution ΔE_R(i) of the binding energy shift ΔE_B(i). ΔE_A(kii) is the kinetic energy shift of the Auger transition which corresponds to the decay of a hole state with a hole in level k into a final state with two holes in level i. The shift parameter Δβ(i), which is based on information on two binding energies, is conceptually similar to Wagner's Auger parameter. To establish the relation between Δβ(i) and ΔR(i) one needs, however, less drastic approximations than in the case of Auger parameter shifts. The only approximation necessary is the assumption that ΔR(i) is determined by coulomb contributions.Secondly, we use Δβ (i) to analyse the experimental data of eighteen gaseous phosphorus-containing compounds obtained by Sodhi and Cavell¹. It is shown that ΔR(P_2p) is strongly related to changes in the polarizability of the ligands. The initial state effects derived from our study deviate from those expected on the basis of simple electronegativity considerations.     

Ground state rotational energies of C3v quasi-spherical top molecules: Applications to 16OPF3 and PH3

Rotational spectra of the quasi-spherical symmetric molecules, ¹⁶OPF₃ and PH₃, are analyzed with all the data currently available. In both cases the current formulation that uses rotational contact transformations to completely diagonalize the ground state energy matrix appears to be inadequate, due to the smallness of the quantity |;A₀ ? B₀|. This quantity represents only 5% of A₀ or B₀ in the case of OPF₃ and 11% in the case of PH₃. Thus, both analyses require the resonance terms in ΔK = ±3 and/or ΔK = ±6 to be taken into account through diagonalization of the energy matrix. The ground state parameters as well as the ground state energies are given for both molecules.     

Sensitivity enhancement in quadrupolar nuclei double resonance detection

NMR imaging of quadrupolar nuclei in liquid system has received less attention than the imaging ofS=1/2 nuclei due to difficulties associated with the quadrupolar interaction. The¹⁰B spatial distribution in Na₂ ¹⁰B₁₂H₁₁SH in phantom has been obtained using an indirect J-coupling Double Resonance method. This procedure allows one to localize the quadrupolar nuclei by observing the protons J-coupled with them. The sensitivity gain in the indirect spatial localization of the¹⁰B nuclei with respect to to the direct one, is here computed and verified on the Na₂ ¹⁰B₁₂H₁₁SH images.     

The influence of CO adsorption on the galvanomagnetic and magnetic properties of evaporated nickel films

The influence of CO adsorption on the ordinary Hall coefficient, R_HO, the extraordinary Hall coefficient, R_HE, the perpendicular magnetoresistivity ΔR_{mag O} and the saturation magnetization, B_S, of Ni films with thicknesses between 1 and 200 nm has been studies as a function of the CO coverage at 77 and 273 K. There is a maximum in ΔR_HE at a coverage of about half a monolayer. ΔR_HO, ΔΔR_{mag O} and ΔB_S exhibit an oscillating behaviour.     

Empirical field mapping for gradient nonlinearity correction of multi-site diffusion weighted MRI

BackgroundAchieving inter-site / inter-scanner reproducibility of diffusion weighted magnetic resonance imaging (DW-MRI) metrics has been challenging given differences in acquisition protocols, analysis models, and hardware factors.PurposeMagnetic field gradients impart scanner-dependent spatial variations in the applied diffusion weighting that can be corrected if the gradient nonlinearities are known. However, retrieving manufacturer nonlinearity specifications is not well supported and may introduce errors in interpretation of units or coordinate systems. We propose an empirical approach to mapping the gradient nonlinearities with sequences that are supported across the major scanner vendors.Study typeProspective observational study.SubjectsA spherical isotropic diffusion phantom, and a single human control volunteer.Field strength/sequence3 T (two scanners). Stejskal-Tanner spin echo sequence with b-values of 1000, 2000 s/mm² with 12, 32, and 384 diffusion gradient directions per shell.AssessmentWe compare the proposed correction with the prior approach using manufacturer specifications against typical diffusion pre-processing pipelines (i.e., ignoring spatial gradient nonlinearities). In phantom data, we evaluate metrics against the ground truth. In human and phantom data, we evaluate reproducibility across scans, sessions, and hardware.Statistical testsWilcoxon rank-sum test between uncorrected and corrected data.ResultsIn phantom data, our correction method reduces variation in mean diffusivity across sessions over uncorrected data (p < 0.05). In human data, we show that this method can also reduce variation in mean diffusivity across scanners (p < 0.05).ConclusionOur method is relatively simple, fast, and can be applied retroactively. We advocate incorporating voxel-specific b-value and b-vector maps should be incorporated in DW-MRI harmonization preprocessing pipelines to improve quantitative accuracy of measured diffusion parameters.     

Electronegativity and tetragonal distortions in AIIBIVCV2 semiconductors

Empirical correlations are established between the tetragonal distortions 2-c/a and dielectrically defined electronegativities based on polarizabilities of AⁿB^8-n compounds. Optical data, including the birefringence parameter δn = n_e - n_o, are summarized. No simple relation is found to exist between δn and the principal optical gaps and tetragonal distortions of seven chalcopyrite compounds.