14 DAY TRIAL // In the end, your personality is made of thoughts. But how do thoughts look like? A team of researchers of Carnegie Mellon University has just tried to answer to this is in a research published in PLoS One.
The study was made on 12 subjects enveloped in an MRI scanner, who were presented line drawings of 10 different objects, 5 tools and 5 dwellings, and put to think about their traits. The whole brain neural activity was assessed. The team neglected the data in the brain's visual cortex, focusing on the brain's cognitive areas.
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.
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.
Earlier researches revealed that the brain pattern was different in the cases of broad object categories, like "tools" versus "buildings", but the new study found different patterns in the case of very similar meanings, like two different tools.
The research also tested whether different brains have similar or different activity patterns for different objects. A computer algorithm could detect a subject's thoughts by only using the patterns achieved from the other subjects.
"This part of the study establishes, as never before, that there is a commonality in how different people's brains represent the same object. There has always been a philosophical conundrum as to whether one person's perception of the color blue is the same as another person's. Now we see that there is a great deal of commonality across different people's brain activity corresponding to familiar tools and dwellings", said co-author Tom M. Mitchell, Computer Science Professor and head of the Machine Learning Department in Carnegie Mellon's School of Computer Science.
"We hope to progress to identifying the thoughts associated not just with pictures, but also with words, and eventually sentences", said lead author Svetlana Shinkareva, an assistant professor of psychology at the University of South Carolina.
"We are looking forward to determining how people with autism neurally represent social concepts such as friend and happy. People with autism perceive others in a distinctive way that has been difficult to characterize. This machine learning approach offers a way to discover that characterization", said co-author Marcel Just, neuroscientist Professor and director of the Center for Cognitive Brain Imaging at Carnegie Mellon.