Functional magnetic resonance imaging has been one of the tools of choice for neuroscientists investigating brain activity – its scan data can be processed into colorful brain images showing which areas of the brain are active at a given time. fMRI has had some drawbacks – equipment that is costly and massive, a relatively time-consuming procedure, and limited spatial resolution. Now, the latter problem is being addressed by new, higher resolution fMRI machines. A press release from Stanford University describes research with the new equipment that has allowed a much more detailed understanding of the fusiform gyrus, a brain area thought to be responsible for recognizing faces.

Using high-resolution functional magnetic resonance imaging, Grill-Spector and colleagues imaged regions of the brain at a magnification of 27 to 70 times smaller than a traditional fMRI scan. Like viewing a grain of sugar rather than the whole cube, this allowed the team to “zoom in” on a hybrid of neural patches, each of which responds to a different category of objects.

“We were able to see things we haven’t before,” said Grill-Spector. “What’s really cool is these structures are very selective in their responses — and only to one kind of object.”

Each of the participants in the study was shown images of faces, four-legged animals, cars and abstract sculptures, along with scrambled or “noise” images. The researchers found that overall, twice as many of the patches are predisposed to faces versus inanimate objects, and that the patches that respond to faces outnumber those that respond to animals by 50 percent. Furthermore, same-selectivity patches are not physically connected, implying a “face area” may not even exist.

“These results are very exciting and suggest that the visual cortex contains finer category-selective subdivisions than previously believed,” said Brad Duchaine, PhD, of the Institute of Cognitive Neuroscience at University College London, who was not involved in the research.

While this work deals with facial recognition, it is indicative of how high-resolution fMRI may impact research into many other brain structures and their interactions with each other. Will this new level of resolution help find the Holy Grail of neuromarketing, the elusive “buy button”? That’s highly doubtful, since the brain’s decision-making process is far more complex than activating a single spot in the brain. Nevertheless, new levels of detail may enable neuromarketers to better understand the reactions of subjects to products, brands, and advertisements. In essence, over time fMRI is being transformed from a relatively blunt instrument into one capable of considerable refinement.

One consequence of a much higher resolution fMRI is that we are likely to see much more complexity just as in the face recognition study. Initial studies are likely to raise more new questions than generate clear answers. In the long run, though, these higher resolution scans will greatly benefit fields like neuroeconomics and neuromarketing, not to mention neuroscience in general.