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Sökning: WFRF:(Weiskopf Nikolaus)

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  • Callaghan, Martina F, et al. (författare)
  • Example dataset for the hMRI toolbox
  • 2019
  • Ingår i: Data in Brief. - : Elsevier BV. - 2352-3409.
  • Tidskriftsartikel (refereegranskat)abstract
    • The hMRI toolbox is an open-source toolbox for the calculation of quantitative MRI parameter maps from a series of weighted imaging data, and optionally additional calibration data. The multi-parameter mapping (MPM) protocol, incorporating calibration data to correct for spatial variation in the scanner’s transmit and receive fields, is the most complete protocol that can be handled by the toolbox. Here we present a dataset acquired with such a full MPM protocol, which is made freely available to be used as a tutorial by following instructions provided on the associated toolbox wiki pages, which can be found at http://hMRI.info, and following the theory described in: hMRI – A toolbox for quantitative MRI in neuroscience and clinical research.
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  • Fritz, Francisco J, et al. (författare)
  • Effects of temperature in the estimation of inhomogeneous magnetic transfer (ihMT) in post-mortem human brain
  • 2022
  • Ingår i: Proceedings of the 2022 ISMRM & ISMRT Annual Meeting and Exhibition. ; 30
  • Konferensbidrag (refereegranskat)abstract
    • Inhomogeneous magnetic transfer (ihMT) is more sensitive to myelin macromolecules than standard MT proxies. Measuring ihMT in the multi-parameter mapping protocol allows calculating ihMT from MT saturation (MTsat) maps and thus inherently correct for the undesired dependencies on flip angle and the longitudinal relaxation rate. Further validation of this new ihMT metric requires measurement of MPM-based ihMT of human post-mortem material. Here, we showed that ihMT of a whole human post-mortem brain is feasible but can lead totemperature increase in the specimen, which is particularly pronounced in white matter.
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  • Haugg, Amelie, et al. (författare)
  • Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?
  • 2020
  • Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 41:14, s. 3839-3854
  • Tidskriftsartikel (refereegranskat)abstract
    • Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.
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