NeuroImage
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Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be important to identify MCI patients at high risk for conversion to AD. In this study, we present a novel magnetic resonance imaging (MRI)-based method for predicting the MCI-to-AD conversion from one to three years before the clinical diagnosis. ⋯ Our aggregate biomarker based on MRI data together with baseline cognitive measurements and age achieved a 10-fold cross-validated AUC score of 0.9020 in discriminating pMCI from sMCI. The results presented in this study demonstrate the potential of the suggested approach for early AD diagnosis and an important role of MRI in the MCI-to-AD conversion prediction. However, it is evident based on our results that combining MRI data with cognitive test results improved the accuracy of the MCI-to-AD conversion prediction.
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Our visual system takes into account the effects of Earth gravity to interpret biological motion (BM), but the neural substrates of this process remain unclear. Here we measured functional magnetic resonance (fMRI) signals while participants viewed intact or scrambled stick-figure animations of walking, running, hopping, and skipping recorded at normal or reduced gravity. ⋯ Effective connectivity analysis suggests that predictive coding of gravity effects underlies BM interpretation. This process might be implemented by a family of snapshot neurons involved in action monitoring.
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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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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.
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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.