NeuroImage
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Randomized Controlled Trial
Characterization of GABAB-receptor mediated neurotransmission in the human cortex by paired-pulse TMS-EEG.
GABAB-receptor (GABABR) mediated inhibition is important in regulating neuronal excitability. The paired-pulse transcranial magnetic stimulation (TMS) protocol of long-interval intracortical inhibition (LICI) likely reflects this GABABergic inhibition. However, this view is based on indirect evidence from electromyographic (EMG) studies. ⋯ P25, N45 and P70) potentials. These findings demonstrate for the first time directly at the system level of the human cortex that GABABR-mediated cortical inhibition contributes to LICI, while GABAAR-mediated inhibition occludes LICI. Paired-pulse TMS-EEG allows investigating cortical GABABR-mediated inhibition more directly and specifically than hitherto possible, and may thus inform on network abnormalities caused by disordered inhibition, e.g. in patients with schizophrenia or epilepsy.
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Gamma-aminobutyric acid (GABA) and glutamate (Glu) are the major neurotransmitters in the brain. They are crucial for the functioning of healthy brain and their alteration is a major mechanism in the pathophysiology of many neuro-psychiatric disorders. Magnetic resonance spectroscopy (MRS) is the only way to measure GABA and Glu non-invasively in vivo. ⋯ To mitigate these problems, we implemented a 3D MEGA-editing MRS imaging sequence with the following three features: a) Real-time motion correction, dynamic shim updates, and selective reacquisition to eliminate subtraction artifacts due to scanner instabilities and subject motion. b) Localization by Adiabatic SElective Refocusing (LASER) to improve the localization accuracy and signal-to-noise ratio. c) K-space encoding via a weighted stack of spirals provides 3D metabolic mapping with flexible scan times. Simulations, phantom and in vivo experiments prove that our MEGA-LASER sequence enables 3D mapping of GABA+ and Glx (Glutamate+Gluatmine), by providing 1.66 times larger signal for the 3.02ppm multiplet of GABA+ compared to MEGA-PRESS, leading to clinically feasible scan times for 3D brain imaging. Hence, our sequence allows accurate and robust 3D-mapping of brain GABA+ and Glx levels to be performed at clinical 3T MR scanners for use in neuroscience and clinical applications.
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Diffusion tractography relies on complex mathematical models that provide anatomical information indirectly, and it needs to be validated. In humans, up to now, tractography has mainly been validated by qualitative comparison with data obtained from dissection. No quantitative comparison was possible because Magnetic Resonance Imaging (MRI) and dissection data are obtained in different reference spaces, and because fiber tracts are progressively destroyed by dissection. Here, we propose a novel method and software (FIBRASCAN) that allow accurate reconstruction of fiber tracts from dissection in MRI reference space. ⋯ This paper presents the robustness of a novel method, FIBRASCAN, for accurate reconstruction of fiber tracts from dissection in the ex vivo MR reference space. This is a major step toward quantitative comparison of MR tractography with dissection results.
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In addition to the BOLD scan, quantitative functional MRI studies require measurement of both cerebral blood volume (CBV) and flow (CBF) dynamics. The ability to detect CBV and CBF responses in a single additional scan would shorten the total scan time and reduce temporal variations. Several approaches for simultaneous CBV and CBF measurement during functional MRI experiments have been proposed in two-dimensional (2D) mode covering one to three slices in one repetition time (TR). ⋯ We estimated this using Bloch simulations and demonstrate that the resulting 3D acquisition can detect activation patterns and relative signal changes of quality comparable to that of the original separate scans. The same was found for temporal signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). This approach provides improved acquisition efficiency when both CBV and CBF responses need to be monitored during a functional task.
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Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. ⋯ These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes.