Recording from
the Whole Brain
Neuroscientists also rely on
techniques that can provide detailed portraits of the whole brain—without in
any way disrupting the brain’s functioning. There’s actually a wide array of
such techniques, each with its own strengths and limitations: Some tell us the
exact shapes and positions of brain structures but give no information about
how active those brain sites are at the moment; others do the reverse—they
provide information about activity levels but not about the exact anatomy. Some
techniques are exquisitely accurate in locating where the brain is especially active, but they’re less exact about when exactly the activity is occurring.
Other techniques reverse this pattern and give us tem-poral information, but
not spatial.
As we’ve discussed, communication
from one neuron to the next typically relies on chemical signals. However,
communication within each neuron (e.g., communica-tion down the axon) relies on
an electrical signal. The amount of current involved here is minute—but, of
course, many millions of neurons are all active at the same time, and the
current generated by all of them together is great enough to be detected by
sensitive electrodes placed on the surface of the scalp. This is the basis for electroencephalography—a recording of
voltage changes occurring at the scalp that reflect activity in the brain
underneath. The result of this procedure is an electroencephalogram, or EEG
(Figure 3.22).
EEGs tell us, for example, that
there is often a detectable rhythm in the brain’s elec-trical activity—a rhythm
that results from many, many neurons all firing at more or less the same rate.
To detect the brain’s rhythms, we
need to record the brain activity over a period of several seconds or longer.
Sometimes, though, researchers want to ask how the brain responds electrically
to a specific event that takes place at a particular moment in time. In this
case, we can measure the changes in the EEG in the brief period just before,
during, and after the event. These changes are referred to as an event-related potential (ERP).
Let’s be clear that an EEG is a
record of activity throughout the brain. The EEG therefore includes the brain’s
response to our experimental stimulus, but it also includes the electrical
result of all of the brain’s other activities—for example, the brain’s control
of heart rate during the experimental procedure, the brain’s monitor-ing of
body temperature, and so on. How can we remove this “background noise” from the
EEG to reveal just the bit of brain activity we’re interested in—namely, the
brain’s response to our experimental stimulus? We do this by presenting the
stimu-lus over and over, and collecting ERPs from each presentation. We can
then average together the results of all these recordings, based on the idea
that this will “cancel out” all of the brain’s background activities and thus
isolate the brain’s response to our signal. In this way we can measure rather
precisely the pattern of electrical changes in the brain caused, say, by
listening to a musical phrase or deciding to launch a particular movement.
Our understanding of the linkage
between brain and behavior has been revolution-ized by the development of neuroimaging techniques. These provide
remarkable three-dimensional portraits of the brain’s anatomy and functioning,
with absolutely no invasion of brain tissue and with the brain’s owner awake
and fully conscious throughout the procedure.
One technique for imaging brain
anatomy is the CT (computerized
tomography)scan, also known as aCAT
(computerized axial tomography) scan(Figure 3.23A).In thistechnique, researchers take a series of X-ray pictures of
the brain, each from a differ-ent angle, and then use a computer to construct a
detailed composite portrait from these images. These scans, which yield precise
information about the exact shape and position of structures within a brain,
are immensely useful for medical diagnosis (e.g., in detecting tumors or
structural abnormalities) and for research (e.g., for locating the brain damage
that is the source of a patient’s behavioral or cognitive difficulties).
A more widely used neuroimaging
technique is magnetic resonance
imaging(MRI). MRI scans are safer than CT scans because they don’t involve
X-rays. Instead,the person is placed in a strong magnetic field; this aligns
the spinning of the nuclei of atoms that make up the brain tissue. Then a brief
pulse of electromagnetic energy (a radio wave) is used to disrupt these spins.
After the disruption, the spins of the nuclei shift back into alignment with
the magnetic field; as this shift happens, the atoms give off electromagnetic
energy. This energy is recorded by detectors arrayed around the person’s head,
analyzed by a computer, and assembled into a three-dimensional representation
of the brain that can show the healthy tissue as well as tumors, tissue
degeneration, and the blood clots or leaks that may signal strokes (Figure
3.23B).
CT and MRI scans provide precise anatomical depictions; but they cannot tell us about the brain’s moment-by-moment functioning, including which areas of the brain are particularly active at any point in time and which are less active. To record this kind of brain activity, experimenters use other techniques, including positron emissiontomography (PET) scans. In a PET scan, the participant is injected with a safe dose ofsome radioisotope—often an isotope of a sugar that resembles glucose, the brain’s metabolic fuel. The PET scan then keeps track of how this radioactivity is distributed across the brain. The key idea here is that the brain cells that are more active at any moment will need to use more glucose and so, in this setup, will absorb more radioac-tivity. By keeping track of the pattern of radioactivity, we can know where the glucose is being used, and hence we can know which regions within the brain are particularly active.
A newer technique called functional MRI (fMRI) scanning adapts
standard MRI procedures to study brain activity (Figure 3.24). In most cases,
fMRI scans rely on the fact that hemoglobin—the molecule that carries oxygen in
the bloodstream—is less sensitive to magnetism when it is actually transporting
an oxygen molecule than when it is not. By keeping track of the hemoglobin,
therefore, detectors can measure the ratio of oxygenated to deoxygenated blood;
this ratio yields a measurement called the blood-oxygenation-level-dependent
signal, or BOLDsignal. When
neural regions are especially active, this ratio increases because theactive
tissue is demanding more oxygen. By tracking the BOLD signal, therefore, we can
measure activity in the brain.
One advantage of fMRI scans over
PET scans lies in their spatial precision, and fMRI scans can identify
locations within 3 or 4 millimeters. A larger advantage, though, lies in fMRI’s
ability to tell when the brain
activity took place. PET scans sum-marize the brain’s activity level over a
period of 40 seconds or so; and they cannot tell us when, within this time
window, the activity took place. The BOLD signal, in con-trast, provides
measurements across just a few seconds; and this greater temporal precision is
one of several reasons that fMRI scans are used far more often than PET. (We
should note that an EEG record yields even more precise information about
timing, but—unlike an fMRI—it cannot tell us exactly where in the brain the
activity is taking place.)
Whether we’re relying on PET
scans or fMRI scans, though, we need to keep a com-plication in view: The
entire brain is active all of the time—its cells are always using glu-cose and
always needing oxygen. This is because neurons are living cells and require
energy to sustain themselves and, in particular, to maintain their resting
potential. What PET and fMRI seek to measure, therefore, are the increases beyond this constant state of
activity. In other words, the measurement is not “which areas are active when
someone is (say) listening to music?” Instead, the measurement is “which areas
become more active when someone is
listening to music?” These increases are typically assessed by a process that,
in the end, resembles simple subtraction: Researchers measure the brain’s
activity when someone is engaged in the task that’s being investigated, and
they subtract from this value a measurement of the brain’s activity when the
person is not engaged in the task. Of course, it’s important to design this
baseline measurement carefully, so that (like any control condition) it is
identical to the experimental condition in all ways except for the factor that
the researchers are especially interested in. Thus, careful design of the
control condition becomes part of the craft of using neuroimaging techniques.
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