Source current estimation from electromagnetic (MEG and EEG) signals is an ill-posed problem that often produces blurry or inaccurately positioned estimates. The two modalities have distinct factors limiting the resolution, e.g., MEG cannot detect radially oriented sources, while EEG is sensitive to accuracy of the head model. This makes combined EEG+MEG estimation techniques desirable, but different acquisition noise statistics, complexity of the head models, and lack of pertinent metrics all complicate the assessment of the resulting improvements.
We have implemented an initial version of software for the integration of magnetic resonance imaging (MRI) and magnetoencephalography (MEG). The package displays MRI images and performs basic image processing. The coordinate systems of the two methods are matched with the help of markers fixed on known head landmarks and a 3D digitiser. The spherical conductor model can be individually fitted to the shape of the brain in the region of interest. The computed source locations can be instantly superimposed on the MRI images during the analysis.
We propose a novel method, fMRI-Informed Regional Estimation (FIRE), which utilizes information from fMRI in E/MEG source reconstruction. FIRE takes advantage of the spatial alignment between the neural and the vascular activities, while allowing for substantial differences in their dynamics. Furthermore, with the regional approach, FIRE can be efficiently applied to a dense grid of sources.
We used a whole-scalp magnetometer with 122 planar gradiometers to study the activity of the visual cortex of five blind humans deprived of visual input since early infancy. Magnetic responses were recorded to pitch changes in a sound sequence when the subjects were either counting these changes or ignoring the stimuli. In two of the blind subjects, magnetic resonance images were also obtained, showing normal visual cortex macroanatomy.
We propose a novel method, fMRI-Informed Regional Estimation (FIRE), which utilizes information from fMRI in E/MEG source reconstruction. FIRE takes advantage of the spatial alignment between the neural and the vascular activities, while allowing for substantial differences in their dynamics. Furthermore, with the regional approach, FIRE can be efficiently applied to a dense grid of sources.
Magnetoencephalographic (MEG) discharges were recorded with multichannel superconducting quantum interference device (SQUID) gradiometers in 13 young candidates for epilepsy surgery. The sources of epileptic activity were related to generators of somatosensory and auditory evoked cortical responses and projected on magnetic resonance imaging (MRI) scans. Seven subjects had restricted or regional MEG foci, located in the frontoopercular (1), sensorimotor (3), perisylvian (1), mesiotemporal (1), or temporooccipital cortex (1).
Multichannel neuromagnetic recordings were used to differentiate signals from the human first (SI) and second (SII) somatosensory cortices and to define representations of body surface in them. The responses from contralateral SI, peaking at 20-40 ms, arose mainly from area 3b, where representations of the leg, hand, fingers, lips and tongue agreed with earlier animal studies and with neurosurgical stimulations and recordings on convexial cortex in man. Representations of the five fingers were limited to a cortical strip of approximately 2 cm in length.
Optimizing outcomes involves rapidly and continuously adjusting behavior based on context. While most behavioral studies focus on immediate task conditions, responses to events are also influenced by recent history. We used magnetoencephalography and a saccadic paradigm to investigate the neural bases of 2 trial history effects that are well characterized in the behavioral eye movement literature: task-switching and the prior-antisaccade effect.
BACKGROUND: Behavioral paradigms applied during human recordings in electro- and magneto- encephalography (EEG and MEG) typically require 1-2 hours of data collection. Over this time scale, the natural fluctuations in brain state or rapid learning effects could impact measured signals, but are seldom analyzed.
At present, one of the most promising windows to the functional organization of the human brain is magnetoencephalography (MEG). By mapping the magnetic field distribution outside the head the sites of neural events can be located with an accuracy of a few millimeters and the temporal evolution of the activation can be traced with a millisecond resolution. This paper reviews some forward field calculation approaches suitable for the interpretation of the brain's electromagnetic signals. Inverse modelling with multiple dipoles is described in detail.
