![]() ![]() Studies of timing in western music have largely focussed on the use of a piano ( Repp 1995 Shafer, 1984), largely due to the simple relation between movement, note sounded, and the possibility of mechanical measurement. Similarly, when using Musical Instrument Digital Interface ( midi a universal interface to a wide range of electronic musical instruments) devices, variability and latency in the system can cause issues when relaying the device’s output to the participant in real-time. When using acoustic instruments, for example, additional data capture devices need to be considered, along with methods of extracting onset locations from the musical signal. This research can also involve a variety of input devices, each with a unique set of methodological constraints. A subset of sensorimotor timing studies often involves research around timing in musical production. More recently movement timing study methods have ranged from switching devices such as computer keyboard keys, push button switches, resistive and capacitive contact switches to sensors such as force transducers and motion tracking cameras capable of characterising the dynamics as well as the timing of the movements. Stevens (1886) collected data using Morse code signal set transmission key presses (see next section for further detail). Where previously the theoretical interest focused on understanding component sources of variance in the individual (i.e., timer, memory, attention, input, and output delays), the new paradigms raise questions about forms of timing linkage, including feedback correction and anticipatory adjustments, that keep participants moving together. Although the majority of these studies has focused on individual performance, recently there has been growing interest in the relation between the timing of multiple individuals attempting to synchronise their joint performance, with the goal of achieving coherent ensemble timing (see Elliott, Chua, & Wing, 2016, for a review of this emerging area in the context of mathematical models). The goals of the research include characterising influences on timing accuracy in terms of mean and variability and also understanding the nature of patterns in the variation. Many papers (e.g., see Repp & Su (2013), for review) subsequent to Stevens (1886) have examined paced and unpaced finger tapping. This includes distinct tendencies to short-term alternation between shorter and longer intervals (at faster tempos) and longer term drift around the target interval (at slower tempos). Moreover, he observed that the variability is not purely random but has a characteristic patterning. He showed that timing is highly adjustable but is subject to variability in produced intervals, which increases as the target interval lengthens. Stevens presented his results graphically as time series of intervals between successive responses. Participants tapped with a metronome set to various tempo values for a number of repetitions and then tapped on their own to reproduce the metronome tempo as accurately as possible. In a classic paper on sensorimotor timing, Stevens (1886) used a combination of paced and unpaced tapping over a range of tempos to describe what we would now recognise as characteristic attributes of movement timing. This chapter provides a comprehensive overview of methods developed to capture, process, analyse, and model individual and group timing. Its study requires accurate measurement of the times of events (often called responses) based on the movement or acoustic record. Accurate timing of movement in the hundreds of milliseconds range is a hallmark of human activities such as music and dance.
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