Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla

Human brain functional MRS reveals interplay of metabolites implicated in neurotransmission and neuroenergetics

While functional MRI (fMRI) localizes brain activation and deactivation, functional MRS (fMRS) provides insights into the underlying metabolic conditions. There is much interest in measuring task-induced and resting levels of metabolites implicated in neuroenergetics (e.g., lactate, glucose, or β-hydroxybutyrate (BHB)) and neurotransmission (e.g., γ-aminobutyric acid (GABA) or pooled glutamate and glutamine (Glx)). Ultra-high magnetic field (e.g., 7T) has boosted the fMRS quantification precision, reliability, and stability of spectroscopic observations using short echo-time (TE) ¹H-MRS techniques. While short TE ¹H-MRS lacks sensitivity and specificity for fMRS at lower magnetic fields (e.g., 3T or 4T), most of these metabolites can also be detected by J-difference editing (JDE) ¹H-MRS with longer TE to filter overlapping resonances. The ¹H-MRS studies show that JDE can detect GABA, Glx, lactate, and BHB at 3T, 4T and 7T. Most recently, it has also been demonstrated that JDE ¹H-MRS is capable of reliable detection of metabolic changes in different brain areas at various magnetic fields. Combining fMRS measurements with fMRI is important for understanding normal brain function, but also clinically relevant for mechanisms and/or biomarkers of neurological and neuropsychiatric disorders. We provide an up-to-date overview of fMRS research in the last three decades, both in terms of applications and technological advances. Overall the emerging fMRS techniques can be expected to contribute substantially to our understanding of metabolism for brain function and dysfunction.

Metabolic underpinnings of activated and deactivated cortical areas in human brain

Neuroimaging with functional MRI (fMRI) identifies activated and deactivated brain regions in task-based paradigms. These patterns of (de)activation are altered in diseases, motivating research to understand their underlying biochemical/biophysical mechanisms. Essentially, it remains unknown how aerobic metabolism of glucose to lactate (aerobic glycolysis) and excitatory-inhibitory balance of glutamatergic and GABAergic neuronal activities vary in these areas. In healthy volunteers, we investigated metabolic distinctions of activating visual cortex (VC, a task-positive area) using a visual task and deactivating posterior cingulate cortex (PCC, a task-negative area) using a cognitive task. We used fMRI-guided J-edited functional MRS (fMRS) to measure lactate, glutamate plus glutamine (Glx) and γ-aminobutyric acid (GABA), as indicators of aerobic glycolysis and excitatory-inhibitory balance, respectively. Both lactate and Glx increased upon activating VC, but did not change upon deactivating PCC. Basal GABA was negatively correlated with BOLD responses in both brain areas, but during functional tasks GABA decreased in VC upon activation and GABA increased in PCC upon deactivation, suggesting BOLD responses in relation to baseline are impacted oppositely by task-induced inhibition. In summary, opposite relations between BOLD response and GABAergic inhibition, and increases in aerobic glycolysis and glutamatergic activity distinguish the BOLD response in (de)activated areas.

No time for drifting: Comparing performance and applicability of signal detrending algorithms for real-time fMRI

As a consequence of recent technological advances in the field of functional magnetic resonance imaging (fMRI), results can now be made available in real-time. This allows for novel applications such as online quality assurance of the acquisition, intra-operative fMRI, brain-computer-interfaces, and neurofeedback. To that aim, signal processing algorithms for real-time fMRI must reliably correct signal contaminations due to physiological noise, head motion, and scanner drift. The aim of this study was to compare performance of the commonly used online detrending algorithms exponential moving average (EMA), incremental general linear model (iGLM) and sliding window iGLM (iGLM^window). For comparison, we also included offline detrending algorithms (i.e., MATLAB's and SPM8's native detrending functions). Additionally, we optimized the EMA control parameter, by assessing the algorithm's performance on a simulated data set with an exhaustive set of realistic experimental design parameters. First, we optimized the free parameters of the online and offline detrending algorithms. Next, using simulated data, we systematically compared the performance of the algorithms with respect to varying levels of Gaussian and colored noise, linear and non-linear drifts, spikes, and step function artifacts. Additionally, using in vivo data from an actual rt-fMRI experiment, we validated our results in a post hoc offline comparison of the different detrending algorithms. Quantitative measures show that all algorithms perform well, even though they are differently affected by the different artifact types. The iGLM approach outperforms the other online algorithms and achieves online detrending performance that is as good as that of offline procedures. These results may guide developers and users of real-time fMRI analyses tools to best account for the problem of signal drifts in real-time fMRI.

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fMRI time series are almost always affected by signal drifts.

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Signal drifts can be reduced in real-time using different correction methods.

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Robustness of these methods was tested in the presence of different artifacts.

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Incremental GLM (iGLM, iGLM^window) were found optimal in most cases.

Functional MRS with J-edited lactate in human motor cortex at 4 T

While functional MRI (fMRI) localizes regions of brain activation, functional MRS (fMRS) provides insights into metabolic underpinnings. Previous fMRS studies detected task-induced lactate increase using short echo-time non-edited ¹H-MRS protocols, where lactate changes depended on accurate exclusion of overlapping lactate and lipid/macromolecule signals. Because long echo-time J-difference ¹H-MRS detection of lactate is less susceptible to this shortcoming, we posited if J-edited fMRS protocol could reliably detect metabolic changes in the human motor cortex during a finger-tapping paradigm in relation to a reliable measure of basal lactate. Our J-edited fMRS protocol at 4T was guided by an fMRI pre-scan to determine the ¹H-MRS voxel placement in the motor cortex. Because lactate and β-hydroxybutyrate (BHB) follow similar J-evolution profiles we observed both metabolites in all spectra, but only lactate showed reproducible task-induced modulation by 0.07 mM from a basal value of 0.82 mM. These J-edited fMRS results demonstrate good sensitivity and specificity for task-induced lactate modulation, suggesting that J-edited fMRS studies can be used to investigate the metabolic underpinning of human cognition by measuring lactate dynamics associated with activation and deactivation fMRI paradigms across brain regions at magnetic field lower than 7T.

Simultaneous spin-echo and gradient-echo BOLD measurements by dynamic MRS

This study aimed to dissociate the intravascular and extravascular contributions to spin-echo (SE) and gradient-echo (GE) blood oxygenation level-dependent (BOLD) signals at 7 T, using dynamic diffusion-weighted MRS. We simultaneously acquired SE and GE data using a point-resolved spectroscopy sequence with diffusion weightings of 0, 600, and 1200 s/mm² . The BOLD signals were quantified by fitting the free induction decays starting from the SE center to a mono-exponential decay function. Without diffusion weighting, BOLD signals measured with SE and GE increased by 1.6 ± 0.5% (TE_SE  = 40 ms) and 5.2 ± 1.4% (nominal TE_GE  = 40 ms) during stimulation, respectively. With diffusion weighting, the BOLD increase during stimulation measured with SE decreased from 1.6 ± 0.5% to 1.3 ± 0.4% (P < 0.001), whereas that measured by GE was unaffected (P > 0.05); the post-stimulation undershoots in the BOLD signal time courses were largely preserved in both SE and GE measurements. These results demonstrated the feasiblity of simultaneous SE and GE measurements of BOLD signals with and without interleaved diffusion weighting. The results also indicated a predominant extravascular contribution to the BOLD signal time courses, including post-stimulation undershoots in both SE and GE measurements at 7 T.

Event-related dynamics of glutamate and BOLD effects measured using functional magnetic resonance spectroscopy (fMRS) at 3T in a repetition suppression paradigm

Proton MR spectroscopy ((1)H-MRS) complements other brain research methods by providing measures of neurometabolites noninvasively in a localized brain area. Improvements in MR scanner technologies, and data acquisition and analysis methods should allow functional (1)H-MRS (fMRS) to measure neurometabolite concentration changes during task-induced brain activation. The aim of the current study was to further develop event-related fMRS at 3T to investigate glutamate dynamics in response to repetition suppression. A secondary aim was to investigate the relationship between blood-oxygen-level-dependent (BOLD) responses and glutamate dynamics in the same paradigm at the same time. A novel approach of interleaved water-suppressed (metabolite) and unsuppressed (water) fMRS was used to simultaneously detect the event-related dynamics of glutamate and BOLD signal to repetition suppression in the lateral occipital cortex of thirteen (N=13) volunteers. On average, (1)H-MRS-visible glutamate increased after novel visual stimuli presentations by 12% and decreased by 11-13% on repeated compared to novel presentations. The BOLD signal, as measured by water peak amplitude changes, showed significant difference between Task and Rest trials, and, on a GLM based analysis of the time series, demonstrated a significant difference between the novel and repeated trials, however appeared to be decoupled from the glutamate response as no correlation was found between the two. These results are the first demonstration that reductions in neuronal activity typical of repetition suppression effects are reflected by reduced glutamatergic and BOLD measures, that glutamate and BOLD responses may not be coupled as previously thought, and that these changes and relationships can be measured simultaneously using event-related fMRS at 3T.

Comparison of real-time water proton spectroscopy and echo-planar imaging sensitivity to the BOLD effect at 3 T and at 7 T

Gradient-echo echo-planar imaging (GE EPI) is the most commonly used approach to assess localized blood oxygen level dependent (BOLD) signal changes in real-time. Alternatively, real-time spin-echo single-voxel spectroscopy (SE SVS) has recently been introduced for spatially specific BOLD neurofeedback at 3 T and at 7 T. However, currently it is not known how neurofeedback based on real-time SE SVS compares to real-time GE EPI-based. We therefore compared both methods at high (3 T) and at ultra-high (7 T) magnetic field strengths. We evaluated standard quality measures of both methods for signals originating from the motor cortex, the visual cortex, and for a neurofeedback condition. At 3 T, the data quality of the real-time SE SVS and GE EPI R2* estimates were comparable. At 7 T, the data quality of the real-time GE EPI acquisitions was superior compared to those of the real-time SE SVS. Despite the somehow lower data quality of real-time SE SVS compared to GE EPI at 7 T, SE SVS acquisitions might still be an interesting alternative. Real-time SE SVS allows for a direct and subject-specific T2* estimation and thus for a physiologically more plausible neurofeedback signal.

Real-time fMRI neurofeedback: progress and challenges

In February of 2012, the first international conference on real time functional magnetic resonance imaging (rtfMRI) neurofeedback was held at the Swiss Federal Institute of Technology Zurich (ETHZ), Switzerland. This review summarizes progress in the field, introduces current debates, elucidates open questions, and offers viewpoints derived from the conference. The review offers perspectives on study design, scientific and clinical applications, rtfMRI learning mechanisms and future outlook.

Real-time automated spectral assessment of the BOLD response for neurofeedback at 3 and 7T

Echo-planar imaging is the dominant functional MRI data acquisition scheme for evaluating the BOLD signal. To date, it remains the only approach providing neurofeedback from spatially localized brain activity. Real-time functional single-voxel proton spectroscopy (fSVPS) may be an alternative for spatially specific BOLD neurofeedback at 7T because it allows for a precise estimation of the local T2* signal, EPI-specific artifacts may be avoided, and the signal contrast may increase. In order to explore and optimize this alternative neurofeedback approach, we tested fully automated real-time fSVPS spectral estimation procedures to approximate T2* BOLD signal changes from the unsuppressed water peak, i.e. lorentzian non-linear complex spectral fit (LNLCSF) in frequency and frequency-time domain. The proposed approaches do not require additional spectroscopic localizers in contrast to conventional T2* approximation based on linear regression of the free induction decay (FID). For methods comparison, we evaluated quality measures for signals from the motor and the visual cortex as well as a real-time feedback condition at high (3T) and at ultra-high (7T) magnetic field strengths. Using these methods, we achieved reliable and fast water peak spectral parameter estimations. At 7T, we observed an absolute increase of spectra line narrowing due to the BOLD effect, but quality measures did not improve due to artifactual line broadening. Overall, the automated fSVPS approach can be used to assess dynamic spectral changes in real-time, and to provide localized T2* neurofeedback at 3 and 7T.