Head movement compensation in real-time magnetoencephalographic recordings
نویسندگان
چکیده
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 estimation This work explains the technical details and validates each of these steps.
منابع مشابه
Auditory Compensation for Head Rotation Is Incomplete
Hearing is confronted by a similar problem to vision when the observer moves. The image motion that is created remains ambiguous until the observer knows the velocity of eye and/or head. One way the visual system solves this problem is to use motor commands, proprioception, and vestibular information. These "extraretinal signals" compensate for self-movement, converting image motion into head-c...
متن کاملSubject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron
We describe a system that localizes a single dipole to reasonable accuracy from noisy magnetoencephalographic (MEG) measurements in real time. At its core is a multilayer perceptron (MLP) trained to map sensor signals and head position to dipole location. Including head position overcomes the previous need to retrain the MLP for each subject and session. The training dataset was generated by ma...
متن کاملFast robust subject-independent magnetoencephalographic source localization using an artificial neural network.
We describe a system that localizes a single dipole to reasonable accuracy from noisy magnetoencephalographic (MEG) measurements in real time. At its core is a multilayer perceptron (MLP) trained to map sensor signals and head position to dipole location. Including head position overcomes the previous need to retrain the MLP for each subject and session. The training dataset was generated by ma...
متن کاملVideo-based head movement compensation for novel haploscopic eye-tracking apparatus.
PURPOSE To describe a video-based head-tracking technique to compensate for torsional, horizontal, and vertical in-plane head movements during pupil/iris-tracking video-oculography with a tilting haploscope. METHODS Custom software was developed for image acquisition and off-line analysis for a novel haploscopic viewing device. Head movements were constrained to the frontal plane with the use...
متن کاملFlexible head-casts for high spatial precision MEG
BACKGROUND In combination with magnetoencephalographic (MEG) data, accurate knowledge of the brain's structure and location provide a principled way of reconstructing neural activity with high temporal resolution. However, measuring the brain's location is compromised by head movement during scanning, and by fiducial-based co-registration with magnetic resonance imaging (MRI) data. The uncertai...
متن کامل