Release date: 2017-06-29
Figure 1: The picture shows the law of brain activation corresponding to the phrase “The witness shouted during the trialâ€. The above picture shows the prediction results. The figure below shows the actual observation results. The two are quite similar.
Figure 2: The graph shows the semantic features of the two sentences A and B. The upper row is the prediction result and the lower row is the actual observation result. The brain prediction law predicted by the model has certain similarities with the actual law.
Figure 3: This program measures the activity of each brain system to determine what type of problem the subject is thinking about.
Figure 4: The figure shows the semantic features of the two sentences C and D. The upper row is the prediction result and the lower row is the actual observation result. The brain prediction law predicted by the model has certain similarities with the actual law.
Researchers at Carnegie Mellon University have developed a brain imaging technology that recognizes complex ideas. The technical explanation that complex ideas are formed by various branches of the brain and not based on language, the new evidence provided by the study shows that each person's brain is expressed in the same way and does not change from language to language.
The study was led by Marcel Just, a psychology professor at Carnegie Mellon University. Studies have shown that when dealing with the phrase "The witness shouted during the trial", the brain uses 42 "meaning components" (also called "semantic features"). The "alphabet" that consists of characters, scale, social interactions, and physical activity. Each type of information is processed by a different brain system. The program measures the activity of each brain system to determine what type of problem the subject is thinking about.
“One of the important advantages of the human brain is the ability to integrate a single concept into complex thinking, not only thinking of 'banana', but also 'I like to eat bananas with friends at night',†Dr. Gast said. We finally found a way to identify complex ideas using functional magnetic resonance imaging (fMRI) signals. We found a link between thinking and the rules of brain activation, and we learned how thinking is composed of what it is.†Previously by Dr. Gast and Research conducted by his team shows that when the brain thinks of familiar things (such as bananas or hammers), the corresponding activation laws involve the brain system we use to deal with these objects.
The researchers recruited seven adult subjects to think about 239 different sentences and used a computer model to assess the association between brain activation patterns and the “meaning units†of each sentence. In this way, the program successfully interprets the "meaning unit" of the 240th sentence. Next, the researchers exchanged the order of the 240 sentences, taking turns to remove a sentence as the final test sentence. The process name is cross-validation. In the end, the program can successfully predict the meaning unit of the 240th sentence with 87% accuracy. Although it has never been exposed to the corresponding brain activation law, the model can also run in reverse, only knowing a certain sentence. In the case of "meaning unit", the corresponding law of brain activation is predicted.
"Our approach overcomes the limitations of functional magnetic resonance imaging techniques by merging signals from temporally similar brain activity, such as reading two words that appear one after another in a sentence. This allows us to interpret more than one for the first time. Complex ideas, including concepts. Next, we may be dedicated to interpreting the subject's thinking, such as judging whether TA is thinking about geology or skateboarding. We are trying to map the minds of all kinds of knowledge in the human brain. â€
Source: Sina Technology
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