Introduction

In task-based functional MRI (fMRI) studies, a task-positive region is where the BOLD signal is greater during experimental versus rest epochs, and a task-negative region is where the BOLD signal is greater during rest versus experimental epochs. The task-negative region is also referred to as the default mode network (DMN). Functional MRS (fMRS) using short TE non-edited ¹H-MRS protocols, has reproducibly detected lactate increase during sensory-induced activations^1-3 and evoked modulations of the BOLD signal^4-6. Here we investigated the metabolic basis of (de)activation paradigms in non-DMN and DMN areas using ¹H-MRS acquisitions at 4T of J-edited lactate and diffusion-weighted water (i.e., BOLD signal).

Methods

Ten healthy volunteers (8 male, age 30.5±3.0) participated in two fMRI runs and two fMRS runs spanning over three days. First, we used fMRI at 3T to localize the visual cortex (VC, non-DMN area) and the posterior cingulate cortex (PCC, DMN area), using activation (visual flashing checkerboard) and deactivation (auditory emotion perception) paradigms, respectively. The fMRI and fMRS runs consisted of three 2.7 min VC (or PCC) stimulation epochs interleaved with three 2.7 min fixation (or rest) epochs, respectively (16.2 min in total). For VC activation paradigm, the whole-screen flashing (8 Hz) checkerboard was used as visual stimuli (visual angle 15×18°). Subjects were asked to fixate a grey dot in the center of the screen and press a response button when the dot’s color changed to green⁷. For PCC deactivation paradigm, participants listened to short sentences audio-emotion portrayals⁸ with eyes closed, and they were asked to press the response button each time a specific emotion, contempt, disgust or surprise, was identified, which occurred 3-5 times per activation epoch. Bilateral VC and PCC (de)activations were identified using statistical parametric mapping (SPM12). A single fMRS voxel was placed around the identified VC and PCC areas. All experiments were performed at the MRRC (Yale University) on a 3T Siemens Prisma scanner using 64-channels head coil and 4T Bruker spectrometer using single-channel quadrature surface head coil. For fMRI, we used single-shot gradient-echo T2*-weighted EPI (648 scans, TR = 1.5 s, TE = 30 ms, voxel size = 2×2×2 mm). For fMRS we used J-difference editing (180 paired spectra, TR = 2.7s, TE = 144ms, VC voxel size = 40.9±3.8×22.9±0.6×22.5±0.7 mm, PCC voxel size = 34.6±0.7×28.0±1.0×28.4±0.8 mm). Each pair of the water-suppressed J-edited spectra was followed by the diffusion-weighted STEAM⁹ water spectra acquisition (TE = 20 ms, b = 1400 s/mm²) with 200ms delay between the two MRS acquisitions (to minimize residual eddy current effects, etc). Prior to fMRS acquisitions, we acquired B0 field map and water spectrum, adjusted basic frequency and shimming globally and locally, and optimized RF power. J-edited spectra were corrected for a basic frequency drift, aligned, phase-corrected, apodized (gaussian 2 Hz, exponential 2 Hz) and averaged to 30 pairs. Individual spectra were centered and aligned to the group average reference NAA peak. The residual BOLD linewidth narrowing was estimated using line-shape differences in NAA peak between the (de)activation and rest and nulled using exponential linewidth adjustment. The same corrections were applied to the lactate spectra. Lactate integrals were estimated using LCM quantification. The integrals of the modelled lactate (1.32±0.15 ppm), were normalized to the corresponding NAA integrals (2.01±0.15 ppm). STEAM water spectra underwent the same spectra preprocessing procedure. To estimate the T2*, we applied water peak linewidth linear approximation using logarithm of the water FID^4-6.

Results

In VC, we found a significant diffusion-weighted water (i.e., BOLD signal) increase during visual stimulation as compared to fixation (Fig. 1, t = 4.5, p < 0.01, ΔBOLD% = 0.9±0.2%), which was associated with significantly increased lactate levels (Fig. 2A-C, t = 2.6, p < 0.05, Δlactate% = 16.0±7.8%). In PCC, we found a significant diffusion-weighted water (i.e., BOLD signal) decrease during auditory emotional stimulation as compared to rest (Fig 1, t = 2.2, p = 0.05, ΔBOLD% = -0.5±0.2%), but no lactate changes (Fig. 2D-F, t = 1.1, p = 0.32, Δlactate% = 3.6±2.9%). It should be noted that the ΔBOLD% from diffusion-weighted ¹H-MRS is somewhat smaller due to the partial volume effect and diffusion weighted acquisition to suppress the signal from large vessels^10,11.

Discussion and Conclusion

In VC (non-DMN area, activation) we detected increase of BOLD signal and lactate. In PCC (DMN area, deactivation) we identified decrease of BOLD signal but no change in lactate. Notably, visual stimulation-induced lactate changes are in good agreement with prior non-edited spectra^1-3. These results suggest similar degree of aerobic glycolysis in both DMN and non-DMN areas.

Acknowledgements

This study was supported by the Swiss National Science Foundation (P300PB_161083) and the National Institute of Health, USA (R01 NS-100106, R01 MH-067528, R21 MH-110862, P30 NS-052519).