Neurofeedback using functional spectroscopy

Oliver Hinds, Paul Wighton*, M. Dylan Tisdall, Aaron Hess, Hans Breiter, André Van Der Kouwe

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Neurofeedback based on real-time measurement of the blood oxygenation level-dependent (BOLD) signal has potential for treatment of neurological disorders and behavioral enhancement. Commonly used methods are based on functional magnetic resonance imaging (fMRI) sequences that sacrifice speed and accuracy for whole-brain coverage, which is unnecessary in most applications. We present multivoxel functional spectroscopy (MVFS): a system for computing the BOLD signal from multiple volumes of interest (VOI) in real-time that improves speed and accuracy of neurofeedback. MVFS consists of a FS pulse sequence, a BOLD reconstruction component, a neural activation estimator, and a stimulus system. The FS pulse sequence is a single-voxel, magnetic resonance spectroscopy sequence without water suppression that has been extended to allow acquisition of a different VOI at each repetition and real-time subject head motion compensation. The BOLD reconstruction component determines the T2* decay rate, which is directly related to BOLD signal strength. The neural activation estimator discounts nuisance signals and scales the activation relative to the amount of ROI noise. Finally, the neurofeedback system presents neural activation-dependent stimuli to experimental subjects with an overall delay of less than 1 s. Here, we present the MVFS system, validation of certain components, examples of its usage in a practical application, and a direct comparison of FS and echo-planar imaging BOLD measurements. We conclude that in the context of realtime BOLD imaging, MVFS can provide superior accuracy and temporal resolution compared with standard fMRI methods.

Original languageEnglish (US)
Pages (from-to)138-148
Number of pages11
JournalInternational Journal of Imaging Systems and Technology
Volume24
Issue number2
DOIs
StatePublished - Jun 2014

Keywords

  • biofeedback
  • fMRI
  • spectroscopy

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Software
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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  • Cite this

    Hinds, O., Wighton, P., Dylan Tisdall, M., Hess, A., Breiter, H., & Van Der Kouwe, A. (2014). Neurofeedback using functional spectroscopy. International Journal of Imaging Systems and Technology, 24(2), 138-148. https://doi.org/10.1002/ima.22088