DOI 10.1016/j.xinn.2026.101261
Direct mapping of neural activity via glutamate-weighted magnetic resonance imaging.
Аннотация
Conventional functional magnetic resonance imaging (fMRI) indirectly maps neural activity via blood oxygenation level-dependent (BOLD) contrast. Directly probing glutamate, the primary excitatory neurotransmitter, during task-related stimulation offers a more precise neuroimaging approach. Chemical exchange saturation transfer (CEST), a molecular MRI technique, can provide insights into brain metabolites, including glutamate. While prior studies have attempted to apply CEST in fMRI contexts-either to detect glucose consumption in rats or to probe pH changes in the human brain (with the latter failing to detect significant changes)-none of these efforts successfully addressed the confounding influence of BOLD signal fluctuations on the acquired CEST contrast during task activation. Furthermore, to date, no study has reported task-evoked activation maps based on dynamic glutamate changes detected by CEST-MRI. Here, we are the first to propose and implement a dynamic signal model that integrates both BOLD and CEST effects. Derived from the analysis of temporal response amplitude, we introduce a metric potentially detecting changes in glutamate concentration during neural activity, along with corresponding glutamate-weighted activation maps. Simulation results based on this model show strong agreement with experimental results during block design visual tasks in the human brain on a 3 Tesla scanner, but only when incorporating increased glutamate concentration during the stimulation state. Furthermore, the glutamate-weighted activation maps obtained in our experiments demonstrate a more precise localization of visual cortex regions compared with the classical BOLD contrast activation maps. Our findings provide a potential explanation for the mechanism underlying CEST-fMRI and underscore the potential of this imaging modality to directly map neural activity by leveraging glutamate concentration detection.
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