Abstract: Methods, systems, and devices are disclosed for implementing magnetoencephalography (MEG) source imaging. In one aspect, a method includes determining a covariance matrix based on sensor signal data in the time domain or frequency domain, the sensor signal data representing magnetic-field signals emitted by a brain of a subject and detected by MEG sensors in a sensor array surrounding the brain, defining a source grid containing source locations within the brain that generate magnetic signals, the source locations having a particular resolution, in which a number of source locations is greater than a number of sensors in the sensor array, and generating a source value of signal power for each location in the source grid by fitting the selected sensor covariance matrix, in which the covariance matrix is time-independent based on time or frequency information of the sensor signal data.

Abstract: Techniques and systems are disclosed for implementing multi-core beamforming algorithms. In one aspect, a method of implementing a beamformer technique includes using a spatial filter that contains lead-fields of two simultaneous dipole sources rather than a linear combination of the two to directly compute and obtain optimal source orientations and weights between two highly-correlated sources.

Abstract: Methods, systems, and devices are disclosed for implementing magnetoencephalography (MEG) source imaging. In one aspect, a method includes determining a covariance matrix based on sensor signal data in the time domain or frequency domain, the sensor signal data representing magnetic-field signals emitted by a brain of a subject and detected by MEG sensors in a sensor array surrounding the brain, defining a source grid containing source locations within the brain that generate magnetic signals, the source locations having a particular resolution, in which a number of source locations is greater than a number of sensors in the sensor array, and generating a source value of signal power for each location in the source grid by fitting the selected sensor covariance matrix, in which the covariance matrix is time-independent based on time or frequency information of the sensor signal data.

Abstract: Techniques, devices and systems are disclosed for magnetoencephalography (MEG) source imaging. In one aspect, a method includes selecting signal data associated with one or more frequency bands from a spectrum of the signal data in the frequency domain, in which the signal data represents magnetic signals emitted by a brain of a subject and detected by a plurality of sensors outside the brain, defining locations of sources within the brain that generate the magnetic signals, in which the number of locations of the sources is selected to be greater than the number of sensors, and generating a source value of signal power based on the selected signal data corresponding to a respective location of the locations at the one or more frequencies.

Abstract: Techniques and systems are disclosed for implementing multi-core beamforming algorithms. In one aspect, a method of implementing a beamformer technique includes using a spatial filter that contains lead-fields of two simultaneous dipole sources rather than a linear combination of the two to directly compute and obtain optimal source orientations and weights between two highly-correlated sources.