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This approach could also shed light on cognitive phenomena that are difficult to study, such as attention. For example, when a person looks at a picture of a skier on a mountain, he can focus either on the skier in the foreground or on the mountain scenery in the background. Exactly how this happens is a major open question in cognitive neuroscience. Neural activity, and thus the information captured by the fMRI, might change depending on where the person focuses his attention. Computer models developed by Tong have shown early success in predicting where a person is focusing his attention using a similar approach.

In the long term, this technology might be used to study even more ephemeral phenomena, such as dreaming. “It is currently unknown whether processes like dreaming and imagination are realized in the brain in a way that is functionally similar to perception,” says Gallant. “If they are, then the techniques developed in our study should be directly applicable.”

However, Gallant and others caution that the technology is not yet able to actually reconstruct from scratch what a person sees. While researchers are working on this capability, it is largely limited by the resolution of fMRI itself. Current brain-scanning devices have a spatial resolution of approximately one millimeter, an area that contains hundreds of neurons, each responding to different bits of visual information.

One of the most provocative potential applications for this type of “mind reading” technology has been in lie detection–for example, trying to determine directly from brain activity whether a suspect recognizes a photograph of a crime scene that she says she has never visited. (See “Imaging Deception in the Brain.”) Most neuroscientists believe that there isn’t enough data to determine if this is a reliable method of lie detection, and Gallant says that his technology is unlikely to make it any more so. “Any brain-reading device that aims to decode stored memories will inevitably be limited not only by the technology itself, but also by the quality of the stored information.”

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Credit: Technology Review

Tagged: Biomedicine, imaging, neuroscience, MRI

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