Dataset Information

Combined fMRI-MRS acquires simultaneous glutamate and BOLD-fMRI signals in the human brain.

ABSTRACT: Combined fMRI-MRS is a novel method to non-invasively investigate functional activation in the human brain using simultaneous acquisition of hemodynamic and neurochemical measures. The aim of the current study was to quantify neural activity using combined fMRI-MRS at 7T. BOLD-fMRI and semi-LASER localization MRS data were acquired from the visual cortex of 13 participants during short blocks (64s) of flickering checkerboards. We demonstrate a correlation between glutamate and BOLD-fMRI time courses (R=0.381, p=0.031). In addition, we show increases in BOLD-fMRI (1.43±0.17%) and glutamate concentrations (0.15±0.05 I.U., ~2%) during visual stimulation. In contrast, we observed no change in glutamate concentrations in resting state MRS data during sham stimulation periods. Spectral line width changes generated by the BOLD-response were corrected using line broadening. In summary, our results establish the feasibility of concurrent measurements of BOLD-fMRI and neurochemicals using a novel combined fMRI-MRS sequence. Our findings strengthen the link between glutamate and functional activity in the human brain by demonstrating a significant correlation of BOLD-fMRI and glutamate over time, and by showing ~2% glutamate increases during 64s of visual stimulation. Our tool may become useful for studies characterizing functional dynamics between neurochemicals and hemodynamics in health and disease.

SUBMITTER: Ip IB

PROVIDER: S-EPMC5519502 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Combined fMRI-MRS acquires simultaneous glutamate and BOLD-fMRI signals in the human brain.

Ip I Betina IB Berrington Adam A Hess Aaron T AT Parker Andrew J AJ Emir Uzay E UE Bridge Holly H

NeuroImage 20170419

Combined fMRI-MRS is a novel method to non-invasively investigate functional activation in the human brain using simultaneous acquisition of hemodynamic and neurochemical measures. The aim of the current study was to quantify neural activity using combined fMRI-MRS at 7T. BOLD-fMRI and semi-LASER localization MRS data were acquired from the visual cortex of 13 participants during short blocks (64s) of flickering checkerboards. We demonstrate a correlation between glutamate and BOLD-fMRI time cou ...[more]

PMID: 28433623

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Project description:Functional brain network studies using the Blood Oxygen-Level Dependent (BOLD) signal from functional Magnetic Resonance Imaging (fMRI) are becoming increasingly prevalent in research on the neural basis of human cognition. An important problem in functional brain network analysis is to understand directed functional interactions between brain regions during cognitive performance. This problem has important implications for understanding top-down influences from frontal and parietal control regions to visual occipital cortex in visuospatial attention, the goal motivating the present study. A common approach to measuring directed functional interactions between two brain regions is to first create nodal signals by averaging the BOLD signals of all the voxels in each region, and to then measure directed functional interactions between the nodal signals. Another approach, that avoids averaging, is to measure directed functional interactions between all pairwise combinations of voxels in the two regions. Here we employ an alternative approach that avoids the drawbacks of both averaging and pairwise voxel measures. In this approach, we first use the Least Absolute Shrinkage Selection Operator (LASSO) to pre-select voxels for analysis, then compute a Multivariate Vector AutoRegressive (MVAR) model from the time series of the selected voxels, and finally compute summary Granger Causality (GC) statistics from the model to represent directed interregional interactions. We demonstrate the effectiveness of this approach on both simulated and empirical fMRI data. We also show that averaging regional BOLD activity to create a nodal signal may lead to biased GC estimation of directed interregional interactions. The approach presented here makes it feasible to compute GC between brain regions without the need for averaging. Our results suggest that in the analysis of functional brain networks, careful consideration must be given to the way that network nodes and edges are defined because those definitions may have important implications for the validity of the analysis.

Dataset Information

Combined fMRI-MRS acquires simultaneous glutamate and BOLD-fMRI signals in the human brain.

Publications

Combined fMRI-MRS acquires simultaneous glutamate and BOLD-fMRI signals in the human brain.

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