Visualization of human visual processing by MEG and fMRI
Sunao Iwaki
National Institute of Advanced Industrial Science and Technology (AIST), Japan
Information processing which takes place in neural networks in the human cerebral cortical areas
plays a key role in perception, cognition, attention, memory and language. To investigate these
crucial functions in the human brain, several noninvasive techniques were developed recently;
however, none of these noninvasive techniques is capable of achieving sufficient temporal and
spatial resolution at the same time to illustrate precise neural dynamics taking place in the living
human brain.
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(fMRI) makes it possible to visualize the
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spatial distribution of the human brain
activities precisely in the range of few
millimeters in typical, but fMRI measures
the
hemodynamic
change
(blood
Spatial resolution [mm]
Functional magnetic resonance imaging
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oxygenation level dependent (BOLD)
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signals), which is an indirect measure of
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the neural activity that peaks a few
seconds after the onset of the neural firing
Non-uniqueness of the
MEG/EEG inverse problem
MEG/EEG
fMRI
Slow hemodynamic
response
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Desirable spatiotemporal resolution to
visualize macroscopic brain activities
related to the human cognitive function
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Temporal resolution [s]
in the area, and therefore has limited
temporal resolution.
On the other hand, although electroencephalography (EEG) and
magnetoencephalography (MEG) can provide direct observation of the temporal changes in
post-synaptic neural activities with good temporal resolution in the order of milliseconds, the
principal difficulty in interpreting EEG and/or MEG data is on solving the inverse problem, where
spatial distribution of the neural activities in the brain is reconstructed from the EEG or MEG
distribution measured at the sensor locations. Because of the ill-posedness of the problem, we have
to introduce prior knowledge of brain activity to obtain a unique solution.
This presentation describes a technique to introduce three-dimensional structural models of the
human brain from structural MRI scans and spatial distribution of the brain activities from functional
MRI scans to impose neurophysiologically plausible constraints on the MEG/EEG inverse problem.
Also, we present an example of MEG inverse solution in which functional prior from fMRI
experiments as well as the 3-D cortical surface model from structural MRI are used to improve
spatial accuracy in visualizing human brain activities while perceiving 3-D object from 2-D
random-dot motion.