Measuring self-similarity in empirical signals to understand musical beat perception.

ABSTRACT: Experiencing music often entails the perception of a periodic beat. Despite being a widespread phenomenon across cultures, the nature and neural underpinnings of beat perception remain largely unknown. In the last decade, there has been a growing interest in developing methods to probe these processes, particularly to measure the extent to which beat-related information is contained in behavioral and neural responses. Here, we propose a theoretical framework and practical implementation of an analytic approach to capture beat-related periodicity in empirical signals using frequency-tagging. We highlight its sensitivity in measuring the extent to which the periodicity of a perceived beat is represented in a range of continuous time-varying signals with minimal assumptions. We also discuss a

SUBMITTER: Lenc T 

PROVIDER: S-EPMC11760665 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature