Lorenzo Titone

Max Planck Institute for Human Cognitive and Brain Sciences | CBS · Max Planck Research Group Language Cycles

The human brain tracks regularities in the environment and extrapolates these to predict future events. Prior work on music cognition suggests that low‐frequency (1–8 Hz) brain activity encodes melodic predictions beyond the stimulus acoustics. Building on this work, we aimed to disentangle the frequency‐specific neural dynamics linked to melodic p...

Temporal prediction assists language comprehension. In a series of recent behavioral studies, we have shown that listeners specifically employ rhythmic modulations of prosody to estimate the duration of upcoming sentences, thereby speeding up comprehension. In the current human magnetoencephalography (MEG) study on participants of either sex, we sh...

Neural oscillations reflect fluctuations in excitability, which biases the percept of ambiguous sensory input. Why this bias occurs is still not fully understood. We hypothesized that neural populations representing likely events are more sensitive, and thereby become active on earlier oscillatory phases, when the ensemble itself is less excitable....

Statistical learning is the ability to extract and retain statistical regularities from the environment. In language, extracting statistical regularities—so-called transitional probabilities, TPs—is crucial for segmenting speech and learning new words. To investigate whether neural activity synchronizes with these statistical patterns, so-called ne...

Neural oscillations reflect fluctuations in excitability, which biases the percept of ambiguous sensory input. Why this bias occurs is still not fully understood. We hypothesized that neural populations representing likely events are more sensitive, and thereby become active on earlier oscillatory phases, when the ensemble itself is less excitable....