Tatsuya Daikoku: “Neurophysiological and Computational Understanding of Uncertainty/Entropy encoding in Language- and Music-Statistical Learning: Towards Medical and Educational applications by a Brain-Computer Interface”
12:15 〜 13:00
CiNet 1F Conference Room
Max Planck Institute for Human Cognitive and Brain Sciences
Host PI: Yukie Nagai
The brain models sequential phenomena as a hierarchy of dynamical systems that encode a causal chain structure in the sensorium to maintain low entropy/uncertainty, and predicts a future state based on the internalized statistical model. This prediction is in keeping with the theory of statistical learning (SL) in the brain. The SL is a learning system of transitional probabilities of sequential phenomena such as music and language, and has been considered an implicit and domain-general mechanism that is innate in human’s brain. It is also interdisciplinary notion that covers information technology, artificial intelligence, musicology, and linguistics as well as psychology and neuroscience. Here, I show a line of our neurophysiological and computational studies of SL. Furthermore, I discusses how statistically acquired knowledge is related to creativities of language, music, and motor activities. Then, I propose the innovative approaches for educational and medical application, using a combined method of neuroimaging and machine learning.
The Friday Lunch Seminar is CiNet's main regular meeting series, held every week at 12:15 in the beautiful main lecture theatre on the ground floor at CiNet. The talks are typically 40mins long and orientated towards an inter-disciplinary audience. They are informal, social, and most people bring their own lunch to eat during the talk. They are open to anyone who is feeling curious and wants to come, regardless of where you work.