Neurofeedback-based functional near-infrared spectroscopy upregulates motor cortex activity in imagined motor tasks.

Pawan Lapborisuth,Adam Noah,Joy Hirsch,Xian Zhang

doi:10.1117/1.nph.4.2.021107

Abstract

.Neurofeedback is a method for using neural activity displayed on a computer to regulate one’s own brain function and has been shown to be a promising technique for training individuals to interact with brain–machine interface applications such as neuroprosthetic limbs. The goal of this study was to develop a user-friendly functional near-infrared spectroscopy (fNIRS)-based neurofeedback system to upregulate neural activity associated with motor imagery, which is frequently used in neuroprosthetic applications. We hypothesized that fNIRS neurofeedback would enhance activity in motor cortex during a motor imagery task. Twenty-two participants performed active and imaginary right-handed squeezing movements using an elastic ball while wearing a 98-channel fNIRS device. Neurofeedback traces representing localized cortical hemodynamic responses were graphically presented to participants in real time. Participants were instructed to observe this graphical representation and use the information to increase signal amplitude. Neural activity was compared during active and imaginary squeezing with and without neurofeedback. Active squeezing resulted in activity localized to the left premotor and supplementary motor cortex, and activity in the motor cortex was found to be modulated by neurofeedback. Activity in the motor cortex was also shown in the imaginary squeezing condition only in the presence of neurofeedback. These findings demonstrate that real-time fNIRS neurofeedback is a viable platform for brain–machine interface applications.

Highlights

Neurofeedback has recently been a topic of interest among engineers and neuroscientists due to potential benefits in clinical and commercial applications.[1]
We investigated the potential of functional near-infrared spectroscopy (fNIRS) feedback as a platform for brain–machine interface applications by determining changes in hemodynamic responses during motor imagery tasks associated with neural feedback without longitudinal training
Results for imagined ball squeezing without neurofeedback [Fig. 5(b)] showed no significant clusters of activity in the functionally defined small volume in the motor cortex determined by active ball squeezing

Summary

Introduction

Neurofeedback has recently been a topic of interest among engineers and neuroscientists due to potential benefits in clinical and commercial applications.[1]. Previous studies have demonstrated that EEG neurofeedback can be used to teach participants how to control cursor movements in one and two dimensions by modifying neural activity.[6,7,8] a major obstacle in developing EEG brain–machine interface applications lies in the difficulty of localizing signal components associated with actual physiological movements.[9] Prior neuroimaging studies have replicated the results of EEG neurofeedback by teaching participants to control cursor movements in multiple dimensions using fMRI neurofeedback systems based on the blood oxygenation level-dependent (BOLD) signal from the selected region of interest (ROI).[10] Recent experiments have further demonstrated the use of fMRI neurofeedback for teaching participants to control the movement of robotic arms, a task directly related to the control of neuroprosthetics.[5,11] these are encouraging outcomes, EEG’s poor spatial resolution and fMRI’s limited experimental environment are barriers to the use of neurofeedback for the development of brain–machine interface applications

Objectives

Results

Discussion

Conclusion