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Correction published on 24 November 2011, see Materials 2011, 4(11), 2057-2060.
Open AccessArticle

Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla

by Yury Koush 1,2,4,*, Mark A. Elliott 4 and Klaus Mathiak 1,2,3
Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany
JARA, Translational Brain Medicine, 52074 Aachen, Germany
Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, 52425 Jülich, Germany
Center for Magnetic Resonance and Optical Imaging (CMROI), Department of Radiology, University of Pennsylvania, PA 19104, USA
Author to whom correspondence should be addressed.
Materials 2011, 4(9), 1548-1563;
Received: 21 June 2011 / Revised: 23 August 2011 / Accepted: 5 September 2011 / Published: 15 September 2011
(This article belongs to the Special Issue High Field Magnetic Resonance Methods and Materials)
Echo-planar imaging (EPI) in fMRI is regularly used to reveal BOLD activation in presubscribed regions of interest (ROI). The response is mediated by relative changes in T2* which appear as changes in the image pixel intensities. We have proposed an application of functional single-voxel proton spectroscopy (fSVPS) for real-time studies at ultra-high MR field which can be comparable to the EPI BOLD fMRI technique. A spin-echo SVPS protocol without water suppression was acquired with 310 repetitions on a 7T Siemens MR scanner (TE/TR = 20/1000 ms, flip angle α = 90°, voxel size 10 × 10 × 10 mm3). Transmitter reference voltage was optimized for the voxel location. Spectral processing of the water signal free induction decay (FID) using log-linear regression was used to estimate the T2* change between rest and activation of a functional task. The FID spectrum was filtered with a Gaussian window around the water peak, and log-linear regression was optimized for the particular ROI by adoption of the linearization length. The spectroscopic voxel was positioned on an ROI defined from a real-time fMRI EPI BOLD localizer. Additional online signal processing algorithms performed signal drift removal (exponential moving average), despiking and low-pass filtering (modified Kalman filter) and, finally, the dynamic feedback signal normalization. Two functional tasks were used to estimate the sensitivity of the SVPS method compared to BOLD signal changes, namely the primary motor cortex (PMC, left hand finger tapping) and visual cortex (VC, blinking checkerboard). Four healthy volunteers performed these tasks and an additional session using real-time signal feedback modulating their activation level of the PMC. Results show that single voxel spectroscopy is able to provide a good and reliable estimation of the BOLD signal changes. Small data size and FID signal processing instead of processing entire brain volumes as well as more information revealed from the acquired total water spectrum, i.e., direct estimation of the T2* values and B0 changes, make SVPS proton spectroscopy suitable and advantageous for real-time neurofeedback studies. Particular challenges of ultra-high field spectroscopy due to the non-linearity in the spectral information, e.g., poor main magnetic field homogeneity and the absence of motion correction for the SVPS sequence may lead to the special artifacts in the control signal which still need to be addressed. The contrast to noise ratio (CNR), experimental statistic (t-values) and percent signal change were used as quality parameters to estimate the method performance. The potential and challenges of the spectroscopic approach for fMRI studies needs to be further investigated. View Full-Text
Keywords: neurofeedback; signal processing; spectroscopy; imaging neurofeedback; signal processing; spectroscopy; imaging
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Koush, Y.; Elliott, M.A.; Mathiak, K. Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla. Materials 2011, 4, 1548-1563.

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