Biomedical Engineering Reference
In-Depth Information
information not obtainable with other functional brain imaging techniques. Most
notably, MEG and EEG track neural population activity on millisecond timescales,
revealing large-scale dynamics that are crucial for understanding brain function.
Furthermore, by applying modern inverse algorithms, it is possible to obtain three-
dimensional images, which are reasonable estimates of neural activity. Such images
are extremely useful for answering many questions on brain science.
While MEG is mainly sensitive to tangential currents in the brain closer to the
surface and relatively insensitive to the conductive properties of the skull, EEG is
primarily sensitive to radial sources while being highly sensitive to the conductive
properties of the brain, skull, and scalp. Therefore, MEG and EEG can be viewed
as being complementary in terms of the sensitivity to underlying neural activity.
However, since magnetic fields generated from neurons are not distorted by the
heterogeneous electrical properties of a brain, thesemagnetic fields can be considered
an undistorted signature of underlying cortical activity.
In addition, there are several practical or physiological reasons why neuroscien-
tists prefer MEG to EEG. First, MEG setup time is very short, because MEG mea-
surement does not require much preparation in attaching and checking electrodes, as
is needed in performing EEG measurement. This simplifies matters both for exper-
imenters and subjects. Second, the anatomical location of primary sensory cortices
in sulci makes MEG ideally suited for electrophysiological studies. Furthermore,
with whole-head sensor arrays, MEG is also well-suited to investigate hemispheric
lateralization effects. Therefore, this chapter is primarily dedicated to giving a review
of the methodologies associated with MEG.
1.2 Sensing Magnetic Fields from the Brain
The long apical dendrites of cortical pyramidal cells are arranged perpendicularly to
the cortical surface and parallel to each other. This fortuitous anatomical arrangement
of these cells allows the magnetic fields to sum up to magnitudes large enough to
detect at the scalp. Synchronously fluctuating dendritic currents result in equivalent
current dipoles that produce suchmagnetic fields. However, biomagnetic fields froma
brain are extremely small, (in range of tens-to-hundreds of femto-Tesla (fT)) which
is about seven orders of magnitude smaller than the earth's magnetic field. As a
result, appropriate data collection necessitates a magnetically shielded room and
highly sensitive detectors known as superconducting quantum interference devices
(SQUIDs). Biomagnetic fields from a brain are typically sensed using detection coils
called flux transformers or magnetometers, which are positioned close to the scalp
and connected to SQUIDs. A SQUID acts as a magnetic-field-to-voltage converter,
and its nonlinear response is linearized by flux-locked loop electronics. SQUIDs
have a sensitivity of up to 5 femto-Tesla per square root of Hz, which is adequate for
the detection of brain-generated magnetic fields.
MEG sensors are often configured for measuring differential magnetic fields
so as to reduce ambient noise in measurements. Such sensors are referred to as
