GABA Modulates Frequency-Dependent Plasticity in Humans

Frequency-dependent reorganization of the primary somatosensory cortex, together with perceptual changes, arises following repetitive sensory stimulation. Here, we investigate the role of GABA in this process. We co-stimulated two finger tips and measured GABA and Glx using magnetic resonance (MR) spectroscopy at the beginning and end of the stimulation. Participants performed a perceptual learning task before and after stimulation. There were 2 sessions with stimulation frequency either at or above the resonance frequency of the primary somatosensory cortex (23 and 39 Hz, respectively). Perceptual learning occurred following above resonance stimulation only, while GABA reduced during this condition. Lower levels of early GABA were associated with greater perceptual learning. One possible mechanism underlying this finding is that cortical disinhibition “unmasks” lateral connections within the cortex to permit adaptation to the sensory environment. These results provide evidence in humans for a frequency-dependent inhibitory mechanism underlying learning and suggest a mechanism-based approach for optimizing neurostimulation frequency

Dynamic contrast-enhanced MRI of synovitis in knee osteoarthritis: repeatability, discrimination and sensitivity to change in a prospective experimental study

Abstract: Objectives: Evaluate test-retest repeatability, ability to discriminate between osteoarthritic and healthy participants, and sensitivity to change over 6 months, of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) biomarkers in knee OA. Methods: Fourteen individuals aged 40–60 with mild-moderate knee OA and 6 age-matched healthy volunteers (HV) underwent DCE-MRI at 3 T at baseline, 1 month and 6 months. Voxelwise pharmacokinetic modelling of dynamic data was used to calculate DCE-MRI biomarkers including Ktrans and IAUC60. Median DCE-MRI biomarker values were extracted for each participant at each study visit. Synovial segmentation was performed using both manual and semiautomatic methods with calculation of an additional biomarker, the volume of enhancing pannus (VEP). Test-retest repeatability was assessed using intraclass correlation coefficients (ICC). Smallest detectable differences (SDDs) were calculated from test-retest data. Discrimination between OA and HV was assessed via calculation of between-group standardised mean differences (SMD). Responsiveness was assessed via the number of OA participants with changes greater than the SDD at 6 months. Results: Ktrans demonstrated the best test-retest repeatability (Ktrans/IAUC60/VEP ICCs 0.90/0.84/0.40, SDDs as % of OA mean 33/71/76%), discrimination between OA and HV (SMDs 0.94/0.54/0.50) and responsiveness (5/1/1 out of 12 OA participants with 6-month change > SDD) when compared to IAUC60 and VEP. Biomarkers derived from semiautomatic segmentation outperformed those derived from manual segmentation across all domains. Conclusions: Ktrans demonstrated the best repeatability, discrimination and sensitivity to change suggesting that it is the optimal DCE-MRI biomarker for use in experimental medicine studies. Key Points: • Dynamic contrast-enhanced MRI (DCE-MRI) provides quantitative measures of synovitis in knee osteoarthritis which may permit early assessment of efficacy in experimental medicine studies. • This prospective observational study compared DCE-MRI biomarkers across domains relevant to experimental medicine: test-retest repeatability, discriminative validity and sensitivity to change. • The DCE-MRI biomarker Ktransdemonstrated the best performance across all three domains, suggesting that it is the optimal biomarker for use in future interventional studies

GABA concentrations in the anterior temporal lobe predict human semantic processing

Abstract There is now considerable convergent evidence from multiple methodologies and clinical studies that the human anterior temporal lobe (ATL) is a semantic representational hub. However, the neurochemical nature of the ATL in the semantic processing remains unclear. The current study investigated the neurochemical mechanism underlying semantic processing in the ATL. We combined functional magnetic resonance imaging (fMRI) with resting-state magnetic resonance spectroscopy (MRS) to measure task-related blood-oxygen level-dependent (BOLD) signal changes during sematic processing and resting-state GABA concentrations in the ATL. Our combined fMRI and MRS investigation showed that the stronger ATL BOLD response induced by the semantic task, the lower GABA concentration in the same region. Moreover, individuals with higher GABA concentration in the ATL showed better semantic performance and stronger BOLD-related fluctuations in the semantic network. Our data demonstrated that the resting-state GABA concentration predicts neural changes in the human ATL and task performance during semantic processing. Our findings indicate that individuals with higher GABA may have a more efficient semantic processing leading to better task performance and imply that GABAergic neurochemical processes are potentially crucial to the neurobiological contribution of the ATL to semantic cognition

Neurochemical profiles of the anterior temporal lobe predict response of repetitive transcranial magnetic stimulation on semantic processing.

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive technique used to modulate cortical excitability in the human brain. However, one major challenge with rTMS is that the responses to stimulation are highly variable across individuals. The underlying reasons why responses to rTMS are highly variable between individuals still remain unclear. Here, we investigated whether the response to continuous theta-burst stimulation (cTBS) - an effective rTMS protocol for decreasing cortical excitability - is related to individual differences in glutamate and GABA neurotransmission. We acquired resting-state magnetic resonance spectroscopy (MRS) and functional magnetic resonance imaging (fMRI) during semantic processing. Then, we applied cTBS over the anterior temporal lobe (ATL), a hub for semantic representation, to explore the relationship between the baseline neurochemical profiles in this region and the response to cTBS. We found that the baseline excitation-inhibition balance (glutamate + glutamine/GABA ratio) in the ATL was associated with individual cTBS responsiveness during semantic processing. Specifically, individuals with lower excitation-inhibition balance showed stronger inhibitory effect - poorer semantic performance. Our results revealed that non-responders (subjects who did not show an inhibitory effect of cTBS on subsequent semantic performance) had higher excitatory-inhibitory balance in the ATL, which led to up-regulated task-induced regional activity as well as increased ATL-connectivity with other semantic regions compared to responders. These results disclose that the baseline neurochemical state of a cortical region can be a significant factor in predicting responses to cTBS

Patch based super-resolution of MR spectroscopic images

© 2016 IEEE. In this paper, a new single-image super-resolution method is presented to increase the spatial resolution of metabolite maps computed from magnetic resonance spectroscopic imaging. The proposed method is based on a non-local patch-based strategy that uses a high resolution T1-weighted image to regularise the super-resolution process. The method is implemented in a multi-scale fashion. The accuracy of the method is validated on both phantom and in vivo images. Both qualitative and quantitative validation suggest that the method has potential for clinically relevant neuroimaging applications.Jain S., Sima D., Sanaei Nezhad F., Williams S., Van Huffel S., Maes F., Smeets D., ''Patch based super-resolution of MR spectroscopic images'', Proceedings 13th IEEE international symposium on biomedical imaging - ISBI 2016, pp. 452-456, April 13-16, 2016, Prague, Czech Republic.status: publishe

Number of subjects required in common study designs for functional GABA magnetic resonance spectroscopy in the human brain at 3 Tesla

Magnetic resonance spectroscopy (MRS) is a research tool for measuring the concentration of metabolites such as γ‐aminobutyric acid (GABA) and glutamate in the brain. MEGA‐PRESS has been the preferred pulse sequence for GABA measurements due to low physiological GABA concentrations, hence low signal. To compensate, researchers incorporate long acquisition durations (7–10 min) making functional measurements of this metabolite challenging. Here, the acquisition duration and sample sizes required to detect specific concentration changes in GABA using MEGA‐PRESS at 3 T are presented for both between‐groups and within‐session study designs. 75 spectra were acquired during rest using MEGA‐PRESS from 41 healthy volunteers in 6 different brain regions at 3 T with voxel sizes between 13 and 22 cm3. Between‐group and within‐session variance was calculated for different acquisition durations and power calculations were performed to determine the number of subjects required to detect a given percentage change in GABA/NAA signal ratio. Within‐subject variability was assessed by sampling different segments of a single acquisition. Power calculations suggest that detecting a 15% change in GABA using a 2 min acquisition and a 27 cm3 voxel size, depending on the region, requires between 8 and 93 subjects using a within‐session design. A between‐group design typically requires more participants to detect the same difference. In brain regions with suboptimal shimming, the subject numbers can be up to 4‐fold more. Collecting data for longer than 4 min in brain regions examined in this study is deemed unnecessary, as variance in the signal did not reduce further for longer durations

Patch-based super-resolution of MR spectroscopic images : application to multiple sclerosis

Purpose: Magnetic resonance spectroscopic imaging (MRSI) provides complementary information to conventional magnetic resonance imaging. Acquiring high resolution MRSI is time consuming and requires complex reconstruction techniques. Methods: In this paper, a patch-based super-resolution method is presented to increase the spatial resolution of metabolite maps computed from MRSI. The proposed method uses high resolution anatomical MR images (T1-weighted and Fluid-attenuated inversion recovery) to regularize the super-resolution process. The accuracy of the method is validated against conventional interpolation techniques using a phantom, as well as simulated and in vivo acquired human brain images of multiple sclerosis subjects. Results: The method preserves tissue contrast and structural information, and matches well with the trend of acquired high resolution MRSI. Conclusions: These results suggest that the method has potential for clinically relevant neuroimaging applications