Marcus Thomas Pearce

This study investigates how the brain establishes and updates predictive models of auditory patterns using MEG, finding that model reactivation is faster for familiar patterns and involves auditory, hippocampal, and frontal areas.

This study investigates how auditory contextual memory affects neural representations of predictability in human EEG, showing that predictability is influenced by preceding random tones even after they end.

This study investigates how attention affects musical prediction by comparing neural tracking of long-term and short-term musical learning during dual-task listening.

The paper uses a large dataset to show that music-evoked chills are better predicted by high-level expectation-based surprise than by low-level acoustic features.

This study examines age-related changes in implicit auditory memory by testing response times to novel and repeated tone patterns over 6 months, finding reduced short-term and long-term memory in older adults.

The paper shows that musicianship and melodic predictability increase neural gain in auditory cortex during pitch deviance detection, as revealed by dynamic causal modeling of MEG data.

The paper investigates brain dynamics during musical pattern recognition using MEG, finding increased activity and connectivity in a widespread network over time.

The paper investigates how humans encode and retain sequence statistics in long-term memory through behavioral experiments and a probabilistic model, showing implicit memory for auditory patterns over weeks.

The paper investigates neural responses to melodic surprise in musicians and non-musicians using IDyOM and MEG, finding that sensory adaptation, not probabilistic prediction, drives the N1m component, while later components reflect auditory regularities and expectations.

The paper shows that predictive uncertainty reduces musical prediction error responses similarly in musicians and non-musicians, suggesting dissociable effects of expertise and stimulus uncertainty.

The paper investigates how prediction error responses change in musical contexts with varying pitch uncertainty, finding reduced mismatch negativity in high-uncertainty conditions.

This study shows that musical expertise leads to more subadditive neural responses to complex auditory stimuli, suggesting more integrative processing of acoustic features.