|
Neurophysiological and Computational Understanding of Entropy/Uncertainty encoding in Language- and Music-Statistical Learning: Towards Medical and Educational applications by a Brain-Computer Interface| old_uid | 16306 |
|---|
| title | Neurophysiological and Computational Understanding of Entropy/Uncertainty encoding in Language- and Music-Statistical Learning: Towards Medical and Educational applications by a Brain-Computer Interface |
|---|
| start_date | 2018/10/18 |
|---|
| schedule | 14h-15h30 |
|---|
| online | no |
|---|
| location_info | Bât. D, 1er étage, salle Chartreuse (D 1121) |
|---|
| details | Séminaire du département Parole et Cognition. Présentation en anglais |
|---|
| summary | Statistical learning (SL), which is a learning system of transitional probabilities embedded in sequential phenomena such as music and language, has been considered an implicit and domain-general mechanism that is innate in human’s brain. The SL is also interdisciplinary notion including information technology, artificial intelligence, musicology, and linguistics as well as psychology and neuroscience. A line of recent studies suggest that information-theoretical notion of SL can be represented in neurophysiological responses in the framework of predictive coding. Here, I show a line of our neurophysiological and computational studies of SL in music and language. In addition, I discusses how statistically acquired knowledge is related to creativities of language, music, and motor activities. Then, I argues the promising approaches for the application of therapy and pedagogy, using a integrated method of neural and machine-learning approaches. |
|---|
| responsibles | Meyer, Ito |
|---|
| |
|