Decoding working memory and replay from MEG signal
Using machine-learning decoding of high-temporal resolution neural signal from M/EEG, we identify neural signatures of content selection and characterize subprocesses of working memory.
learningneurosciencebehavior
The spatiotemporal dynamic of information processing is visible using machine-learning decoding of high-temporal resolution neural signal from M/EEG. Using this approach, we identified a neural signature of content selection and characterize differentiated spatiotemporal constraints for subprocesses of working memory. In a context of learning, this approach allows us to test whether the brain is replaying silently what it just learned, as a replay mechanism to consolidate the new skill.