Improving BOLD sensitivity with real-time multi-echo echo-planar imaging - Towards a cleaner neurofeedback signal

Real-time functional magnetic resonance imaging (rtfMRI) suffers from known issues related to T2*-weighted single-echo echo-planar imaging (EPI). These include image dropout in areas with increased local magnetic susceptibility susceptibility gradients; suboptimal whole-brain blood oxygen level-dependent (BOLD) contrast due to average T2*-weighting; and confounders like subject motion and physiology. During fMRI neurofeedback a metric calculated from real-time brain activity is presented visually to the subject in the scanner. To prevent sham feedback, new methods should focus on improving BOLD signal quality in real-time. In this work, presented as a poster at the 11th annual meeting of the ISMRM Benelux chapter (17 January 2019), we present our work on real-time multi-echo fMRI and its usefulness in increasing the temporal signal-to-noise ratio (tSNR) of rtfMRI

Quality and denoising in real-time fMRI neurofeedback: a methods review

Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localized and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. Maximization of neurofeedback learning effects in accordance with operant conditioning requires the feedback signal to be closely contingent on real brain activity, which necessitates the use of effective real-time fMRI denoising methods to prevent sham feedback. In this work we investigated the state of denoising and data quality control practices in rtfMRI-NF, focusing on a set of 99 recent studies as well as published real-time fMRI algorithms and toolboxes. We found that less than a third of the studies implemented a set of standard real-time fMRI denoising steps; poor adherence to best practices regarding methods reporting; and an absence of methodological studies quantifying and comparing the contribution of denoising steps to the quality of the neurofeedback signal. Additionally, only 6 out of 99 studies reported the use of advanced real-time physiological noise correction methods. Recognising an absence of curated information regarding denoising and quality in rtfMRI-NF, we reviewed a list of acquisition and data processing steps as well as data quality metrics available to researchers. Advances in the field of rtfMRI-NF research depend on reproducibility of methods and results. To this end, we recommend that future rtfMRI-NF studies report implementation, and motivate exclusion, of a set of standard real-time fMRI denoising steps; ensure the quality of the neurofeedback signal by calculating and reporting community-informed quality metrics and applying offline control checks; and adhere to open science principles of methods and data sharing and the use and development of open-source rtfMRI-NF software

Gradient artefact correction and evaluation of the EEG recorded simultaneously with fMRI data using optimised moving-average.

Over the past years, coregistered EEG-fMRI has emerged as a powerful tool for neurocognitive research and correlated studies, mainly because of the possibility of integrating the high temporal resolution of the EEG with the high spatial resolution of fMRI. However, additional work remains to be done in order to improve the quality of the EEG signal recorded simultaneously with fMRI data, in particular regarding the occurrence of the gradient artefact. We devised and presented in this paper a novel approach for gradient artefact correction based upon optimised moving-average filtering (OMA). OMA makes use of the iterative application of a moving-average filter, which allows estimation and cancellation of the gradient artefact by integration. Additionally, OMA is capable of performing the attenuation of the periodic artefact activity without accurate information about MRI triggers. By using our proposed approach, it is possible to achieve a better balance than the slice-average subtraction as performed by the established AAS method, regarding EEG signal preservation together with effective suppression of the gradient artefact. Since the stochastic nature of the EEG signal complicates the assessment of EEG preservation after application of the gradient artefact correction, we also propose a simple and effective method to account for it

'Ensemble' iterative relaxation matrix approach: A new NMR refinement protocol applied to the solution structure of crambin

The structure in solution of crambin, a small protein of 46 residues, has been determined from 2D NMR data using an iterative relaxation matrix approach (IRMA) together with distance geometry, distance bound driven dynamics, molecular dynamics, and energy minimization. A new protocol based on an 'ensemble' approach is proposed and compared to the more standard initial rate analysis approach and a 'single structure' relaxation matrix approach. The effects of fast local motions are included and R-factor calculations are performed on NOE build-ups to describe the quality of agreement between theory and experiment. A new method for stereospecific assignment of prochiral groups, based on a comparison of theoretical and experimental NOE intensities, has been applied. The solution structure of crambin could be determined with a precision (rmsd from the average structure) of 0.7 Å on backbone atoms and 1.1 Å on all heavy atoms and is largely similar to the crystal structure with a small difference observed in the position of the side chain of Tyr-29 which is determined in solution by both J-coupling and NOE data. Regions of higher structural variability (suggesting higher mobility) are found in the solution structure, in particular for the loop between the two helices (Gly-20 to Pro-22)

1H NMR characterization of two crambin species

Crambin displays amino acid heterogeneity at positions 22 (Pro or Ser) and 25 (Leu or Ile). Using reversed phase HPLC the crambin mixture can be resolved into two protein fractions. It is shown by amino acid analysis and NMR spectroscopy that these fractions represent single proteins (Ser-22/Ile-25 and Pro-22/ Leu-25 species). A first characterization of the 1H-NMR spectra of these species is presented

'Ensemble' iterative relaxation matrix approach: A new NMR refinement protocol applied to the solution structure of crambin

The structure in solution of crambin, a small protein of 46 residues, has been determined from 2D NMR data using an iterative relaxation matrix approach (IRMA) together with distance geometry, distance bound driven dynamics, molecular dynamics, and energy minimization. A new protocol based on an 'ensemble' approach is proposed and compared to the more standard initial rate analysis approach and a 'single structure' relaxation matrix approach. The effects of fast local motions are included and R-factor calculations are performed on NOE build-ups to describe the quality of agreement between theory and experiment. A new method for stereospecific assignment of prochiral groups, based on a comparison of theoretical and experimental NOE intensities, has been applied. The solution structure of crambin could be determined with a precision (rmsd from the average structure) of 0.7 Å on backbone atoms and 1.1 Å on all heavy atoms and is largely similar to the crystal structure with a small difference observed in the position of the side chain of Tyr-29 which is determined in solution by both J-coupling and NOE data. Regions of higher structural variability (suggesting higher mobility) are found in the solution structure, in particular for the loop between the two helices (Gly-20 to Pro-22)