Researchers have used a novel brain-scanning technique, which combines two existing technologies, to noninvasively map the flow of information in the human brain.
Using this new approach, the MIT researchers scanned individuals' brains as they looked at different images and were able to pinpoint, to the millisecond, when the brain recognizes and categorizes an object, and where these processes occur.
The most commonly used type of brain scan, functional magnetic resonance imaging (fMRI), measures changes in blood flow, revealing which parts of the brain are involved in a particular task. However, it works too slowly to keep up with the brain's millisecond-by-millisecond dynamics.
Another imaging technique, known as magnetoencephalography (MEG), uses an array of hundreds of sensors encircling the head to measure magnetic fields produced by neuronal activity in the brain. These sensors offer a dynamic portrait of brain activity over time, down to the millisecond, but do not tell the precise location of the signals.
To combine the time and location information generated by these two scanners, senior author Aude Oliva, a principal research scientist in MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and Dimitrios Pantazis, a research scientist at MIT's McGovern Institute for Brain Research, used a computational technique called representational similarity analysis, which relies on the fact that two similar objects (such as two human faces) that provoke similar signals in fMRI will also produce similar signals in MEG.
In the study, the researchers scanned 16 human volunteers as they looked at a series of 92 images, including faces, animals, and natural and manmade objects. Each image was shown for half a second.
The study has been published in the journal Nature Neuroscience.
