During the course of an experiment, several hundred of these types of brain
volumes are acquired, one roughly every two seconds or so.
So basically what we have is we make 100,000 measurements over the brain at
one time point.
Then two seconds later we do it again, etc., etc., for
a couple of hundred time points.
So another way of looking at this,
is we can extract the information from a single voxel.
And as I said, a single voxel represents a spatial location.
So if we take the same voxel across time, we're actually studying what's going on
and how the intensity is changing across that voxel in that spatial location.
So by doing this, we can extract the time series of these intensities and
study to see whether or not there's something in that time series that's
related to the task that we performed.
So in my little example, I was saying we were doing finger tapping, resting,
finger tapping, resting.
Then we might look for a voxel where the activation is going
up while we're finger tapping and going down while we're resting.
Such as in this little cartoon where we see this sort of boxcar activation.
So one of the interesting things is that,
this shows you that fMRI data analysis is fundamentally a time series problem.
Because the data from every voxel is a time series, in this case.
However, it's sort of a time series problem on steroids.
Because what we have is, every voxel of the brain has its own time series and
there's about 100,000 different voxels.
So basically, we're dealing with about 100,000 different time series that we're
studying and looking for at a task-related behavior.
So what is this signal that we get in this time series mean?
Well the most common approach towards fMRI I used is what's called
the Blood Oxygenation Level Dependent or BOLD contrast.
BOLD fMRI measures the ratio of oxygenated to deoxygenated hemoglobin in the blood.
It's important to note that BOLD fMRI doesn't measure neuronal activation
directly.
Instead what it does, is it measures the metabolic demands or
the oxygen consumption of active neurons.
Where neurons are active, they need access to oxygen to replenish their energy.
And it's this oxygen consumption that we can see, so which is a side effect of
the neuronal activation that we're actually interested in studying.