Abstract
Neurofeedback- and brain-computer interface (BCI)-based interventions can be implemented using real-time analysis of magnetoencephalographic (MEG) recordings. Head movement during MEG recordings, however, can lead to inaccurate estimates of brain activity, reducing the efficacy of the intervention. Most real-time applications in MEG have utilized analyses that do not correct for head movement. Effective means of correcting for head movement are needed to optimize the use of MEG in such applications. Here we provide preliminary validation of a novel analysis technique, real-time source estimation (rtSE), that measures head movement and generates corrected current source time course estimates in real-time. rtSE was applied while recording a calibrated phantom to determine phantom position localization accuracy and source amplitude estimation accuracy under stationary and moving conditions. Results were compared to off-line analysis methods to assess validity of the rtSE technique. The rtSE method allowed for accurate estimation of current source activity at the source-level in real-time, and accounted for movement of the source due to changes in phantom position. The rtSE technique requires modifications and specialized analysis of the following MEG work flow steps.•Data acquisition•Head position estimation•Source localization•Real-time source estimationThis work explains the technical details and validates each of these steps.
Highlights
Neurofeedback- and brain-computer interface (BCI)-based interventions can be implemented using real-time analysis of magnetoencephalographic (MEG) recordings
While the real-time method for estimating head position does not provide the same value as the offline method, the magnitude of the mean difference between the methods is less than 1 mm in each cardinal axis (x, y, z = 0.003, 0.5, and À0.6 mm, respectively)
The differences in estimated head position are small, in particular when compared to the normal range of head movement experienced during functional neuroimaging (i.e., $1–10 mm)
Summary
Neurofeedback- and brain-computer interface (BCI)-based interventions can be implemented using real-time analysis of magnetoencephalographic (MEG) recordings. MEG data were collected for 326 s with the phantom in a stationary position, all HPI coils active, and no current source active. Experiment 3 tested the accuracy of HPI coil localization and source estimation during real-time analysis in the movement condition.
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