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Modulation of brain oxidative and glycolytic metabolisms using a finger tapping task: an ASL-fMRI and fMRS study1Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 2Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 3Fondation Campus Biotech Geneva, Geneva, Switzerland, 4Spinoza Centre for Neuroimaging, Amsterdam, Netherlands
Synopsis
Using [Lac] and [Glu] as markers of glycolytic and oxidative metabolisms, respectively, we investigated the involvement of each of these pathways during a finger tapping task at different frequencies. We measured BOLD and CBF data and metabolite concentrations at 7T. BOLD and CBF signals increased for increasing finger tapping frequencies as well as [Lac]. The [Glu] changes were smaller and, with the current number of participants, did not follow the same trend.
Introduction
Understanding brain metabolism is primordial if we want to draw accurate conclusions on neuronal activity from traditional fMRI data. Two main pathways generate the fundamental bricks of energy in brain cells: glycolysis and oxidative metabolism (TCA cycle). Several studies have shown that glycolysis might be favored in case of increased neuronal activity and might directly provide energy for neurotransmission1,2. It has been suggested that lactate (Lac) and glutamate (Glu) represent good markers of glycolytic and oxidative metabolisms, respectively3,4. To investigate the involvement of glycolysis in neuronal activity, we performed a combined fMRI-fMRS study during a finger tapping task at different levels of intensity.Methods
6 healthy participants (1 man, 20.5±1.6 years old) were scanned on a head-only 7-Tesla/68cm MRI scanner (Siemens Medical Solutions, Germany) using a 32-channel head coil (Nova Medical USA). An MP2RAGE5 anatomical scan (TR/TE/TI1/TI2 5500/1.87/750/2350ms, matrix 256x240x160, 1x1x1mm3) was first acquired. For the fMRS acquisition, first- and second order shims were adjusted with FAST(EST)MAP (shim VOI: 23x22x21 mm3)6,7. 1H-MR spectra were acquired using a semi-adiabatic SPECIAL sequence8 (TR/TE=3500/16ms, VOI=20×20×17mm3, 257×2 scans). To ensure sufficient B1 for the fMRS acquisition, a dielectric pad was placed over the primary motor cortex. BOLD and ASL data were acquired with a 2D FAIR ASL sequence9 (3*3*6 mm voxels, matrix 192x192x30, oblique slab, TR/TE:3000/11ms, TI1/T2:800/1800ms). For both fMRS and fMRI/ASL, the participants were asked to perform finger tapping following a visual cue on the screen at three different frequencies: 1, 2 and 3 Hz (see Figure 1A&B for the timings). Physiological traces were recorded using external sensors. ASL data were corrected for motion and scaled to obtain quantitative values10. Statistical analysis was performed with a GLM approach (spm12) including regressors for the BOLD signal change, CBF signal change, CBF baseline, motion, physiological noise and a constant term11. BOLD and CBF signal changes were extracted using the fMRS voxel as a ROI (Figure 1C). The spectra were checked for quality, corrected for phase, small B0 drifts, averaged (three last minutes of each block) and quantified using LCModel (Stephen Provencher, Inc., Oakville,Canada) with a basis set including 20 different metabolites and an experimental measured macromolecular baseline. Only Lac and Glu, with a Crámer-Rao lower bound (CRLB) <30%, were considered for further analysis.Results
Increased stimulation intensities translated to increased BOLD and CBF signals (Figure 2A). The responses extracted from the ROI (fMRS voxel) show similar trends (Figure 2B). As expected, the relative CBF changes are one order of magnitude higher than the BOLD changes, but CNR is considerably lower. Regarding the metabolite changes, [Lac] changes is also coupled to the stimulus intensity with higher changes observed for higher intensities (+13.7% for 1Hz, +33.7% for 2Hz, +48.0% for 3Hz, relative to the first baseline period; Figure 3B). With the current number of datapoints and averages, [Glu] changes are less evident as [Glu] changes are usually only of a few percent. Nevertheless, a larger [Glu] change is found going from 1Hz to 2Hz (+1.43%), which is no longer present from 2Hz to 3Hz (-0.33%; i.e. not change – or decrease; Figure 3C).Discussion
The obtained BOLD and CBF results are in accordance with previous studies showing a similar, positive relationship between the stimulus intensity and these blood-related signals during a similar motor task12 and visual stimulation13. This confirms that the task used in the current study allow us to modulate the metabolic costs in the motor cortex. Overall, [Lac] and [Glu] increased during a positive BOLD response, consistent with previous fMRS studies3,14. Additionally, we measured [Lac] changes which were highly modulated by stimulation intensities, suggesting a tight regulation of glycolytic metabolism in such conditions. Although [Glu] changes seems to be dependent on the frequency of the motor task, the differences are very small and barely significant (or not). More participants are required in order to draw final conclusions on the different involvements of the glycolytic and oxidative metabolisms.Acknowledgements
This work was supported by the Centre d'Imagerie BioMédicale (CIBM) of the UNIL, UNIGE, HUG, CHUV, and EPFL and the Leenaards and Jeantet Foundations and the Swiss National Science Foundation Grant 31003A_149983References
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