Differences in steady-state glutamate levels and variability between ‘non-task-active’ control conditions: Evidence from ¹H fMRS of the prefrontal cortex
Jonathan D Lynn1, Eric A Woodcock2,3, Chaitali Anand1, Dalal Khatib4, and Jeffrey A Stanley5

1Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, United States, 2Yale University, New Haven, CT, United States, 3Wayne State University, Detroit, MI, United States, 4Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, United States, 5Psychiatry and Behavavioral Neurosciences, Wayne State University, Detroit, MI, United States


Proton functional magnetic resonance spectroscopy (1H fMRS) is capable of detecting dynamic changes in brain glutamate related to task engagement compared to a “non-task-active” control condition. The selection of an appropriate control condition is critical, which may confound the magnitude change in glutamate modulation. The purpose of this 1H fMRS study was to compare the steady-state levels of glutamate and its variability in the left dorsolateral prefrontal cortex during four different putative control conditions. Results show significant differences in the glutamate level and variability between conditions, emphasizing the importance of the control condition for the detection of task-evoked glutamate modulation.


1H fMRS is a powerful technique for characterizing dynamic changes in brain metabolite levels related to task engagement with a temporal resolution of under a minute. Several recent ¹H fMRS studies have consistently reported elevated glutamate – the primary excitatory neurotransmitter – during neural-activity promoting, ‘task-active’ conditions in focal brain regions, relative to control conditions1,2,3,4. The magnitude and direction of change in the task-evoked glutamate modulation does depend on the comparison “non-task-active” control condition in eliciting a stable, steady-state glutamate level. However, the ‘control’ condition from these studies do vary with respect to constraining behavior and it is unclear whether the acquired steady-state glutamate levels truly reflect a ‘non-task–active’ condition. Using 1H fMRS, this study compared steady-state levels and variability of glutamate in the dlPFC between four different putative control paradigms with the hypothesis that glutamate levels are highly susceptible to the behavioral constraint imposed on the ‘control’ condition.


Sixteen healthy adult volunteers (9 males; mean age: 24.3 ± 3.5years), participated in morning ¹H fMRS scanning sessions (9:30-11:30am) using a 3T Siemens Verio system with a 32-channel volume head-coil. Following a structural T1- weighted scan (MPRAGE), a single-voxel (15x20x15mm) was prescribed in the left dlPFC using the AVP approach5, followed by B0-field shimming using FASTESTMAP. Four consecutive ¹H fMRS scans were acquired during different behavioral constraints, including: a) relaxed with eyes closed; b) visual fixation (centered crosshair); c) visual fixation to a flashing checkerboard (3Hz); and d) finger-tapping to periodic stimulus (1Hz; right-hand index finger). The order of conditions b) and d) were counter-balanced. 1H fMRS spectra (N=13) were continuously acquired every 16s (PRESS with OVS and VAPOR, TE=23ms, TR=4.0s, 4 averages/spectrum; 2048 data points; 208s/condition). Prior to quantification, spectra from 2 to 13 were averaged into consecutive pairs to give a 32s temporal resolution (Figure 2). LCModel (v6.3) was used to quantify the metabolite levels, which were expressed in institutional units relative to the unsuppressed water signal. The primary outcome variables of interest were mean glutamate levels and percent coefficient of variation (CV%) from the 6 paired measurements for each condition.


Descriptive data are presented mean ± 1SD. Geometric voxel overlap indicated highly precise (mean % overlap with the template voxel = 92.3±4.7%) and reliable (overlap across all subjects = 88.6%) (Figure 3). Mean voxel grey matter tissue composition was 36.8 ± 3.8%). Mean signal-to-noise (11.7 ± 2.0), full-width half-maximum (4.8 ± 1.0 Hz), and Cramer-Rao lower bound (7 ± 1%) values demonstrated 1H fMRS spectra were fit reliably and did not differ across conditions. Based on a repeated measure analysis, the condition term for glutamate levels failed to reach significance (Χ2 = 5.09; p=.17). However, post-hoc comparisons indicated glutamate levels were significantly lower during the visual fixation crosshair condition (11.6 ± 0.9) compared to both the visual fixation flashing checkerboard (12.2 ± 0.9; p=.0080) and finger-tapping (12.0 ± 0.9; p=.023) conditions (Figure 4). The condition term for the glutamate variability (CV%) failed to reach significance (Χ2 = 6.60, p=.086) (Figure 5). However, post-hoc analyses demonstrated significantly lower glutamate variability during the visual fixation flashing checkerboard compared to both the eyes closed (p=.0037) and finger-tapping (p=.035) conditions. Finally, glutamate levels during the visual fixation crosshair condition were significantly less variable than the eyes closed condition (p=.0087) (Figure 5).


The motivation of this study was to investigate whether differences in steady-state glutamate levels and its temporal variability in the dlPFC can be detected across four putative ‘control’ conditions. These ‘control’ conditions were chosen because the dlPFC is not the dominant brain region engaged in their implementation. We found mean glutamate levels were qualitatively the lowest during the visual fixation crosshair condition: significantly lower than the flashing checkerboard and finger-tapping conditions. Moreover, the two visual fixation conditions (crosshair and flashing checkerboard) produced the least glutamate variability: significantly lower than the eyes closed condition. The differences in glutamate levels were likely due to the shifting of the excitatory and inhibitory balance (E/I balance) in the brain6,7,8,9 implying that the four ‘control’ conditions differed in their level of engagement of the left dlPFC by shifting the E/I drive. This study provides evidence that steady-state glutamate levels are sensitive to behavioral constraints of ‘non-task-active’ control conditions, and highlights the importance of behavioral paradigms for task-based ¹H fMRS.


The authors would like to thank Caroline Zajac-Benitez, and the participants in the scanning sessions. This study was supported in part by the Lycaki-Young Funds from the State of Michigan.


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The four ¹H fMRS putative ‘control’ conditions acquired as separate scans from left to right include: relaxed with eyes closed, visual fixation crosshair, visual fixation flashing checkerboard and motor finger tapping.

Depiction of a typical 1H MRS spectrum acquired with eight averages yielding a 32s temporal resolution. The acquired spectrum in black is superimposed on the LCModel fitted spectrum in red. Below includes the glutamate signal (Glu) in blue and the residual of the fitting in grey. The chemical shift axis in ppm is depicted at the bottom. The location of the dlPFC voxel is shown on the right.

Voxel overlap across all subjects depicted in the template brain. Red-to-white color gradient represents percentage of voxel overlap across subjects (white = 100% voxel overlap; red = 0% voxel overlap).

Mean (±SEM) levels of glutamate based on the six 32s acquisitions per subjects for each condition and expressed in institutional units (IU). Significant differences from the post-hoc analyses between conditions are noted with ‘*’ (p<.05) and ‘**’ (p<.001).

The mean (±SEM) variability of glutamate expressed a CV% based on the six 32s acquisitions per subject for each condition. Significant differences from the post-hoc analyses between conditions are noted with ‘*’ (p<.05), ‘**’ (p<.005) and ‘***’ (p<.001).

Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)