María Florencia Assaneo

This study examines how music and speech are tracked by slow and fast brain oscillations in different cortical regions using ECoG data.

The paper investigates reactive inhibitory control preceding stuttered speech using MEG, finding increased beta power in R-preSMA associated with stuttering severity and trial outcomes.

The paper proposes that adaptive oscillators serve as Bayesian priors for rhythmic inference, demonstrating their ability to model human behavior better than existing models.

This study uses MEG and neural decoding to investigate speech imagery, revealing stages of processing and internal feedback loops in speech planning and production.

The paper investigates auditory temporal processing and auditory-motor interactions, finding that optimal performance occurs in the theta range and that auditory-motor coupling extends this range.

The paper identifies individual differences in neural substrates for statistical word form learning using fMRI and shows that a fronto-parietal network selectively enhances performance.

The paper shows that silent reading involves articulatory processing at the single-phoneme level, as evidenced by correlations between fixation durations and vocal transition durations during pseudoword reading.

This paper tracks oral tract movements during speech using Hall-effect sensors and uses the data to synthesize intelligible speech.

The paper shows that auditory-motor synchrony during speech perception is restricted to a specific frequency range, around 4.5 Hz, which matches the average syllable rate across languages.