This is the second installment in a 3-part series (read 1st column here) that discusses some of the mechanisms behind functional magnetic resonance imaging (fMRI) technology. As you may recall, the genesis for this series was reactive…I got mad while sitting on an airplane reading a magazine article about how fMRIs can predict everything from product preferences to political inclination. The article hinted at something I have been noticing with increasing alarm—the confusion about what fMRI can and cannot reveal about information processing in the brain. I decided to write this series hoping that knowledge of the basic science behind fMRI technology could contribute to making more nuanced conclusions about the data it reveals.
Last month, I discussed some of the basic physics behind MRI and described why magnets and radio waves were so important in getting an image. Here I explore how that physics reveals neural activity in the brain. Actually, fMRI does not detect neural activity at all. It only detects changes in blood flow, which may be a source of some of the confusion (more on that in a moment).
To talk about the controversies about what fMRI actually detects (and yes, there are controversies), I will briefly describe the relationship between neural activity and the brain’s hemodynamic properties. I will then move to data that appear to describe the molecular components behind this relationship. Along the way, I will review some basic biochemistry, from glycolysis (remember glycolysis?) to the prostaglandin biosynthetic pathway.
The basic idea behind fMRI and brain activity is simple: when busy brain tissues are processing information, they naturally require more energy than when they are not processing information. At its most atomic level, the activity involves the translocation of ions across cell membranes. To generate the energy needed to pump ions out, neurons need a ready supply of blood-borne glucose and oxygen. Why blood-borne? As you know, neurons do not possess internal energy stores in the form of oxygen and glucose. Any increase in their activity requires dipping into extracellular energy resources. Increasing energy supply is supposed to mean increasing blood flow to the neural tissues that need it.
"Noninvasive imaging, such as fMRI, is a great and powerful technology, but it provides no easy answers in our quest to understand how the brain processes information."
This link between energy needs and blood flow is fundamental to our story: fMRI machines can only detect localized changes in blood flow. The phenomenon is known as a BOLD (blood-oxygen level–dependent) signal. How is a machine that traffics in magnetic fields and radio waves capable of detecting changes in blood flow in the first place? You’ve known the answer since grade school. Hemoglobin-bound iron atoms are found in blood, and because these atoms are metal they are magnetically sensitive. Localized oxygen release is of course greater for actively depolarizing neurons than for inactive neurons. And it is this difference that drives the BOLD signal. There is thus a conceptual link between neural activity and the hemodynamic properties of the brain.
At least we think so. The association with blood flow and neural activity is actually not as clear as is sometimes thought. Two examples come to mind. First, increased neural activity does not always result in an increased hemodynamic signal. There are studies that show that increased neural activity can sometimes result in localized vasoconstriction, not dilation, which creates a reduction in localized blood flow.
A second example comes from an issue that is often glaringly omitted from discussions about brain activity: the role of controlled neural in-hibition. Certain types of processing require a deliberate and sustained quelling of regional neural activity. Such deliberate inhibition requires an increase in energy supply, just as deliberate activation does. How does an fMRI signal, which can only detect increases in blood flow, discriminate between these 2 powerful processes? The short answer is that it sometimes cannot.
Questions can even arise from application. There certainly are data that support a positive correlation of blood flow with neural activity. However, what activity is being measured may depend on experimental design. In some cases, increased blood flow signals an anticipatory rather than a reactive response. In one experiment, participants started showing increases in anticipation of the onset of a specific task before the task had even begun. The experimenters concluded that getting a signal concordant with the task depends on the type and timing of the activity.
Does that mean we should just throw out the idea that neural activity and blood flow are positively correlated? Hardly. All it suggests is that we need a more nuanced understanding of the relationship between the two.