INTRODUCTION

Several studies have suggested that abnormal social processing in multiple psychiatric conditions (e.g. autism) is associated with a decrease in GABA and Glutamate^1–3. This has so far only been studied in associative paradigms (metabolites at rest). While resting-state associations can be insightful, the neurometabolic response of GABA and glutamate is altered in these conditions during social processing may inform altered neurochemical responses in more depth. Thus far, there have been no attempts to determine whether changes in metabolite levels are detectable using fMRS during social processing. Here, we performed Functional Magnetic Resonance Spectroscopy (fMRS) in healthy individuals to assess the temporal GABA+ (GABA + macromolecules) and Glx (Glutamate + Glutamine) response during social processing in-vivo, with a paradigm allowing for assessment in both block and event-related responses.

METHODS

MRS acquisition
Data were acquired from 13 healthy adults aged 18-40 years. fMRS was performed on a Siemens Trio 3T MRI scanner using the MEGA-PRESS sequence (TE/TR 68/2000 ms). Voxels were placed in the right superior temporal sulcus (STS) (4x3x2 cm³), and visual cortex (V1) (3x3x3 cm³). During fMRS, participants viewed four stimulus blocks (fixation cross, social, fixation cross, non-social), which was repeated for both STS and V1 voxels (Fig.1). The first (256 transients) and third block (200 transients) were rest blocks. Within each functional block (second and fourth blocks, 200 transients each), social stimuli were presented as sub-blocks (24 s stimulus-ON, 16 s stimulus-OFF), making these data a combined block and event-related design.

Data analysis
Using an in-house modified version of Gannet⁵, data were pre-processed and fit using standard frequency and phase-correction and fitting approaches within-block and expressed relative to creatine⁶. Static window analysis: Data were analysed in blocks of rest (REST1 and REST2) and functional (FUNC1 and FUNC2). Because each functional block contains both stimulus-ON and stimulus-OFF blocks, we further analysed differences within-block by comparing TR periods corresponding to stimulus-ON and stimulus-OFF, allowing for event-related analysis⁷. Sliding window analysis: Metabolite levels were calculated by averaging the signal over a window width of 50 transients irrespective of stimulus condition with a step size of 5 transients. Statistics: Data were analyzed in R (Version 4.1.1). Data between block (static) and between each time-point and rest (sliding window, Bonferroni-corrected for multiple comparisons) were compared using Wilcoxon signed-rank analysis. Change from zero was assessed by estimating difference from the 95% confidence interval of the rest data. A changepoint analysis (R mcp⁸ package) was performed on sliding window data to assess fluctuations in metabolite levels.

RESULTS

Static window analysis
Based on MRS block, we estimated GABA+/tCr and Glx/tCr and found no change between functional and rest blocks (Fig.2, p > 0.1) We further investigated transients corresponding to stimulus-ON and stimulus-OFF TRs regardless of stimulus type. GABA+/tCr appeared to increase in STS during stimulus-OFF throughout the experiment, but this did not reach statistical significance (Fig.3A, p = 0.12). However, GABA+/tCr in V1 decreased weakly significantly (R -0.28, p = 0.05) during stimulus-ON TRs (Fig.3B).

Sliding window analysis
Overall, we observed a fluctuation of metabolite level with time, and we note when the 95% confidence interval did not overlap with zero (GABA or Glx at REST1). GABA+/tCr was reduced in the second functional block when compared to other blocks in V1 (Fig.4). V1 Glx appeared to fluctuate but not consistently. We found no statistically significant change after Bonferroni correction. We saw a slight increase in GABA+/tCr and Glx/tCr during the second rest and functional block for STS (Fig.5), but observed no statistically significant change. Based on changepoint analysis GABA appeared to reduce in V1, consistent with block design analysis, GABA+ and Glx changed in the latter end of block two in STS. We did not observe any differences in face versus object stimulation in any of the analyses.

DISCUSSION AND CONCLUSION

An observed reduction in GABA in V1 was shown using both block analysis in stimulus-ON TRs and in the second functional block as analysed with sliding window analysis; this reduction could reflect deactivation of GABA production or increased re-uptake of GABA with repeated stimulation allowing for induction of plasticity after repeated visual stimulation (irrespective of social context)^9,10 and is consistent with recent animal work¹¹. The response in STS was not particularly strong and no change was observed for Glx.

We did not observe differences between faces or objects and thus, our findings likely reflect neurochemical responses to ‘basic’ visual processing rather than social processing per se. Our findings additionally suggest a “lag” in the metabolite response to stimulation, and differences in the timing of the responses between regions^12,13. Another likely explanation for the lack of the response (especially for Glx) is that stimuli are simply not salient enough to elicit a metabolite response in STS with sufficient SNR to be measured with MRS.

We believe this is the first fMRS study to investigate regional changes in GABA and glutamate levels during a social processing task. In future work, we aim to use more sophisticated analytical approaches, such as incorporating metabolite-lag as a function of time. Rather than simple fitting, linear combination and single-average approach may also be more sensitive to changes in metabolite.

Acknowledgements

Functional MRS data were previously acquired from a collaborator site (Centre for Human Psychopharmacology, Swinburne University of Technology, Australia). This study was funded by a Swinburne Neuroimaging Access Grant.

References

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