Neurometabolic Changes in Visual Stimulation: Insights from a 3T Task fMRS Study
Poster No:
2394
Submission Type:
Abstract Submission
Authors:
ITING LEE1, Shang-Hua Lin1, Rong-Rung Kuo1, Ching-Po Lin1,2, Li-Hung Chang1
Institutions:
1Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan, 2Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
First Author:
Co-Author(s):
Ching-Po Lin
Institute of Neuroscience, National Yang Ming Chiao Tung University|Department of Education and Research, Taipei City Hospital
Taipei, Taiwan|Taipei, Taiwan
Institute of Neuroscience, National Yang Ming Chiao Tung University|Department of Education and Research, Taipei City Hospital
Taipei, Taiwan|Taipei, Taiwan
Introduction:
Proton magnetic resonance spectroscopy is a non-invasive technique used to measure the absolute concentrations of neurochemicals in the brain. Previous studies have shown that functional magnetic resonance spectroscopy (fMRS) is sensitive enough to detect task-related regional dynamics changes in neurotransmitters. Although fMRS studies have demonstrated task-related changes in glutamate during visual stimulation (Bednarik, Tkac et al. 2015, Ip, Berrington et al. 2017), most studies have been performed at ultra-high fields (>3T) and using specialized sequences. However, replication will be critical at lower, broader clinical domain intensities. In this study, we use time-resolved analysis to identified similar task-related changes during medium-field visual stimulation in a 3T system. Additionally, we aim to determine the physiological reaction time of neurotransmitters during a visual task and emphasize the significance of attention levels in the paradigm.
Methods:
We recruited five healthy volunteers with visual acuity either normal or corrected-to-normal for the study. A total of 3 MRS sessions were delivered at noon on consecutive days under 3T Prisma-Fit scanner. In this study, visual stimulations were designed to modulate responses in the primary visual cortex, where the MRS voxel-of-interest (VOI) was positioned. The visual stimulation consisted of a baseline-stimulation block design, with a total time of 21.3 min. Throughout the experiment, a central fixation dot remained on the screen and a vigilance task was performed to encourage participants' central fixation and maintain consistent attention levels (Fig. 1). During data processing, to calculate the time course of metabolite concentrations, time-resolved and time-averaged analysis were used. In time-resolved analysis, 16 consecutive averages were summed into one spectrum and analyzed using an LCModel, resulting in a time course of 40 data points with a temporal resolution of 32 s. The first block was used to calculate the baseline signal variation and was therefore excluded from the statistical analysis. In contrast, in time-averaged analysis, 160 consecutive averages yielded a time course of 4 data points with a temporal resolution of 320 s. Spectra with a CRLB over 15% were excluded.
Results:
The time-resolved analysis, in comparison with baseline periods, revealed a statistically significant increase in amplitude of change in Glutamate (Glu) and in the combined Glutamate+Glutamine (Glx) signals measured during visual stimulation periods (Glx [Stimulation: 1.18 ± 0.17/ baseline: –1.33 ± 0.94], p < 0.001; Glu [Stimulation: 1.83 ± 1.01/ baseline: – 0.29 ± 0.94], p < 0.001). On the other hand, GSH, NAA, and creatine did not differ significantly nor did the time-averaged analysis of all the aforementioned
neurometabolites. Further, as measured repeatedly, the functional changes remained consistent. For the physiological reaction time of neurotransmitters, whether in visual stimulation or baseline conditions, the time exceeding the response threshold shows statistically significant breakthroughs in Glx and Glu concentrations compared with the baseline periods. The threshold is set by the baseline signal variation of the first block, reflecting a pure resting condition. The average response time requires approximately two data points (i.e., 64 s). A significant positive correlation was also observed between the time-resolved analysis of Glx concentration and the correction rate of the sustained attention (r = 0.58; p = 0.039).
neurometabolites. Further, as measured repeatedly, the functional changes remained consistent. For the physiological reaction time of neurotransmitters, whether in visual stimulation or baseline conditions, the time exceeding the response threshold shows statistically significant breakthroughs in Glx and Glu concentrations compared with the baseline periods. The threshold is set by the baseline signal variation of the first block, reflecting a pure resting condition. The average response time requires approximately two data points (i.e., 64 s). A significant positive correlation was also observed between the time-resolved analysis of Glx concentration and the correction rate of the sustained attention (r = 0.58; p = 0.039).
Conclusions:
Our results suggest that varying time-course calculations might have influenced our observations of metabolite dynamics during a visual stimulation task on a 3T system. Additionally, we demonstrate the physiological reaction time of neurotransmitters and highlight the impact of attention levels on the concentration of neurotransmitters in the primary visual cortex. This study emphasizes the critical role of data analysis and the experimental paradigm in fMRS studies.
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Task-Independent and Resting-State Analysis 2
Novel Imaging Acquisition Methods:
MR Spectroscopy 1
Perception, Attention and Motor Behavior:
Perception: Visual
Keywords:
Design and Analysis
Experimental Design
Glutamate
Magnetic Resonance Spectroscopy (MRS)
MR SPECTROSCOPY
Perception
Vision
1|2Indicates the priority used for review
Provide references using author date format
Ip, I. B., A. Berrington, A. T. Hess, A. J. Parker, U. E. Emir and H. Bridge (2017). "Combined fMRI-MRS acquires simultaneous glutamate and BOLD-fMRI signals in the human brain." Neuroimage 155: 113-119.