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Experience-dependent change pervades early human development. Though trajectories of developmental change have been well charted in many domains, the episode-to-episode schedules of experiences on which they are hypothesized to depend have not. Here, we took up this issue in a domain known to be governed in part by early experiences: music. Using a corpus of longform audio recordings, we parameterized the daily schedules of music encountered by 35 infants ages 6-12 months. We discovered that everyday music episodes, as well as the interstices between episodes, typically persisted less than a minute, with most daily schedules also including some very extended episodes and interstices. We also discovered that infants encountered music episodes in a bursty rhythm, rather than a periodic or random rhythm, over the day. These findings join a suite of recent discoveries from everyday vision, motor, and language that expand our imaginations beyond artificial learning schedules and enable theorists to model the history-dependence of developmental process in ways that respect everyday sensory histories. Future theories about how infants build knowledge across multiple episodes can now be parameterized using these insights from infants' everyday lives., (© 2022 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

Infants enculturate to their soundscape over the first year of life, yet theories of how they do so rarely make contact with details about the sounds available in everyday life. Here, we report on properties of a ubiquitous early ecology in which foundational skills get built: music. We captured daylong recordings from 35 infants ages 6-12 months at home and fully double-coded 467 h of everyday sounds for music and its features, tunes, and voices. Analyses of this first-of-its-kind corpus revealed two distributional properties of infants' everyday musical ecology. First, infants encountered vocal music in over half, and instrumental in over three-quarters, of everyday music. Live sources generated one-third, and recorded sources three-quarters, of everyday music. Second, infants did not encounter each individual tune and voice in their day equally often. Instead, the most available identity cumulated to many more seconds of the day than would be expected under a uniform distribution. These properties of everyday music in human infancy are different from what is discoverable in environments highly constrained by context (e.g., laboratories) and time (e.g., minutes rather than hours). Together with recent insights about the everyday motor, language, and visual ecologies of infancy, these findings reinforce an emerging priority to build theories of development that address the opportunities and challenges of real input encountered by real learners., (© 2021 The Authors. Developmental Science published by John Wiley & Sons Ltd.)

Learning and discovery seem often to begin with noting patterns. Human infants are skilled at pattern detection, even patterns only definable at an abstract level, which is key to their acquisition of complex knowledge systems such as language and music. However, research examining infants' abstract rule learning has generated inconsistent results. We propose that apparent domain differences in infants' abstract rule learning may be the result of extraneous stimulus variation and discrepancies in the methodologies employed across studies probing this skill. We discuss how a behavioral methodology indexing infants' online learning would be valuable in furthering understanding of infants' (as well as adults') abstract rule learning and its neurophysiological concomitants. We outline current research aimed at developing such an index, and we propose future research, pairing such techniques with neurophysiological methods, aimed at shining more light on human skill at discovering structure.

Everyday experiences are the experiences available to shape developmental change. Remarkable advances in devices used to record infants' and toddlers' everyday experiences, as well as in repositories to aggregate and share such recordings across teams of theorists, have yielded a potential gold mine of insights to spur next-generation theories of experience-dependent change. Making full use of these advances, however, currently requires manual annotation. Manually annotating many hours of everyday life is a dedicated pursuit requiring significant time and resources, and in many domains is an endeavor currently lacking foundational facts to guide potentially consequential implementation decisions. These realities make manual annotation a frequent barrier to discoveries, as theorists instead opt for narrower scoped activities. Here, we provide theorists with a framework for manually annotating many hours of everyday life designed to reduce both theoretical and practical overwhelm. We share insights based on our team's recent adventures in the previously uncharted territory of everyday music. We identify principles, and share implementation examples and tools, to help theorists achieve scalable solutions to challenges that are especially fierce when annotating extended timescales. These principles for quantifying everyday ecologies will help theorists collectively maximize return on investment in databases of everyday recordings and will enable a broad community of scholars—across institutions, skillsets, experiences, and working environments—to make discoveries about the experiences upon which development may depend. [ABSTRACT FROM AUTHOR]