A recent study conducted by a team of Carnegie Mellon University neuroscientists and computer scientists has identified patterns of activity in the brain whilst looking at particular objects. Participants in the study, while submerged in an MRI scanner, were asked to look at various similarly categorized images, five tools and five dwellings. The categorical similarities in the images were purposeful to see if “specific,” rather than broad-spectrum, objects could be identified. The study was the first of its kind in that previous studies were only able to distinguish between broad categories of objects, such as “tools,” through observing active parts of the brain.
Participants were shown specific images during MRI scanning and asked to think about the functions of those images; during this process the Carnegie Mellon team of scientists were able to identify the exact image that they were looking at. They were able to develop a computer program based upon an algorithm reflecting the patterns of brain activation when looking at particular images that aided them in this process. The scientists were able to predict which image a participant was looking at based on information gathered from “previous participant’s” brain activity, something they were uncertain was possible. The following is an excerpt of an article from Medical News Today that reviews the study:
A team of Carnegie Mellon University computer scientists and cognitive neuroscientists, combining methods of machine learning and brain imaging, have found a way to identify people’s thoughts and perceptions of familiar objects by identifying the patterns of brain activity associated with the objects. This new method, developed over two years under the leadership of neuroscientist Professor Marcel Just and Computer Science Professor Tom M. Mitchell, enables them to identify the mental state associated with a four-second viewing of a line drawing of one of 10 different objects, including five tools and five dwellings.
A dozen study participants enveloped in an MRI scanner were shown drawings of the objects one at a time and asked to think about its properties. As they did that, Just’s and Mitchell’s method was able to accurately determine which of the 10 drawings a participant was viewing based on their characteristic whole-brain neural activation patterns. To make the task more challenging for themselves, the researchers excluded information in the brain’s visual cortex, where raw visual information is available, and focused more on the “thinking” parts of the brain.
The scientists found that the activation pattern evoked by an object wasn’t located in just one place in the brain. For instance, thinking about a hammer activated many locations – i.e. how you swing a hammer activated the motor area, while what a hammer is used for, and the shape of a hammer activated other areas.