Learning rhythm and meter: The roles of statistical learning and dynamic entrainment
A lecture by Dr. Benjamin Schultz, Music Cognition Group UvA
Temporal expectancies play a crucial role in perceiving and producing music. Rhythm learning is hypothesized to occur through the statistical learning of temporal intervals but these theories are often insensitive to aspects of beat (i.e., perceived regular pulses at multiple timescales).
The dynamic attending theory states that attentional oscillations synchronize with and adapt to regularities in an auditory scene and suggests that temporal expectancies are formed more readily for rhythms that imply a beat (i.e., metrical rhythms) compared to those that do not (i.e., nonmetrical rhythms). I present two behavioural experiments that show how rhythm and meter are learned through statistical learning and beat entrainment using highly controlled metrical and nonmetrical rhythms that contain identical statistical probabilities but differ in metrical structure. Results demonstrated that metrical and nonmetrical patterns are both learned. However, only one experiment showed that metrical patterns are learned more readily than nonmetrical patterns. In both experiments, abstraction of a metrical framework was evident in the metrical condition. Overall, results indicate that rhythm learning cannot only be explained by statistical learning but also requires dynamic temporal processing (e.g., entrainment).
Benjamin Schultz was previously a post-doctoral fellow working with Caroline Palmer from November 2012 to June 2014 and Isabelle Peretz from July 2014 to July 2015. He received a Bachelor of Arts (2006) and Bachelor of Health Sciences (2008) in Psychology from the University of Adelaide, a PhD (2013) in Auditory Psychology from the MARCS Institute, University of Western Sydney (Prof. Catherine J. Stevens), and a PhD (2013) in Cognitive Psychology from the Université de Lyon 2 (Prof. Barbara Tillmann). His primary research interests include how people learn rhythmic sequences, entrain and move to the beat, and coordinate their speech and actions with others. In particular, he is interested in how people adapt the acoustic properties and the timing of sound productions in response to those of others in speech and music. Benjamin’s current projects examine the mechanisms that underlie acoustic cueing in persons with Parkinson’s Disease and other motor-related deficits (with Sonja Kotz) and plasticity (i.e., neural changes) that occur during rhythm learning (with Henkjan Honing).
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