The symposium on "Music Cognition: Learning and Processing" brings together interdisciplinary perspectives on the cognitive processes involved in music perception and learning. Here’s a breakdown of key topics:
Beat Induction
Henkjan Honing’s research highlights that beat induction—the ability to perceive and anticipate rhythmic patterns—might be an innate human trait, specific to music. His studies on infants reveal that even newborns expect rhythmic cycles, supporting the notion that beat perception is fundamental and not merely learned.
Implicit Learning in Music and Language
Martin Rohrmeier and Patrick Rebuschat focus on the implicit learning of music, which parallels language acquisition. They argue that both music and linguistic knowledge are often acquired incidentally, without conscious awareness. Their research uses Artificial Grammar experiments to explore how individuals implicitly grasp musical and linguistic structures.
Neural Correlates of Music Learning
Psyche Loui’s work examines how the brain adapts to new musical systems. Using artificial scales like the Bohlen-Pierce scale, her studies show how humans quickly develop expectations for unfamiliar musical structures, as reflected by neural responses. This suggests that the brain uses generalized learning mechanisms to process new music.
Computational Modeling of Music Cognition
Geraint Wiggins, Marcus Pearce, and Daniel Müllensiefen present a computational model that predicts human pitch expectations and melody segmentation using machine learning. Their model, based on transition probabilities and a multiple viewpoint framework, mirrors human cognitive processes in music perception and aligns with neural data.
The symposium underscores how music cognition intertwines with broader cognitive sciences, offering insights into innate musical abilities, implicit learning, neural adaptations, and computational modeling of cognitive processes.
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