Statistical Learning is a core cognitive ability that enables humans to unwittingly grasp regularities from a given environment and adapt to them.
Although many studies have been conducted to elucidate the main mechanism of statistical learning, existing studies might not confirm in detail how various areas of the brain interact to enable statistical learning.
Here, a research team led by Professor Jeon Hyun-ae from the Department of Brain Science at DGIST (President Yang Kook) investigated the relationship between statistical learning and the neurological network of the human brain. Through this research, various researches and expansions of cognitive neuroscience are expected in the future by laying the foundation for unlocking the secrets of human ability to learn new rules.
Professor Jeon’s research team wanted to identify which areas of the brain that the neurological networks involved in human statistical learning occur and how the connections between these areas can be conducive to statistical learning. Functional magnetic resonance imaging (fMRI) was used.
Functional magnetic resonance imaging has a high spatial resolution, enabling closer observation of brain regions that are activated during statistical learning.
Using these advantages, the research team found out how the neurological network that connects each area helps in statistical learning, along with the discovery of brain regions involved in statistical learning.
In particular, by applying a network analysis technique differentiated from existing studies, it was possible to present important evidence for the core networks involved in statistical learning and their functions. In this process, we succeeded in presenting more reliable evidence by simultaneously applying data-driven and hypothesis-driven neural network analysis techniques.
As a result, it was found that the regions related to top-down control spread around the superior frontal gyrus and the neurological network between them play a key role in statistical learning.
In particular, it was found that the weaker the connection strength of the corresponding network, the better the statistical learning. It presents an interesting possibility that it can help
Professor Jeon Hyeon-ae said, “This study provides key evidence for the brain neurological mechanisms that enable statistical learning in humans. There will be,” he said.
On the other hand, this study was conducted by Dr. Jeong-tak Park, Department of Brain Science at DGIST as the first author. According to the research result, reduced functional connectivity supports statistical learning of temporally distributed regularities-down)’ was published on the 7th.
