From the Harvard Gazette:
Rhythm research has implications for both audio engineering and neural clocks, said Holger Hennig, a postdoctoral fellow in the laboratory of Eric Heller in the Physics Department at Harvard, and first author of a study of the Ghanaian and other drummers in the journal Physics Today. Software for computer-generated music includes a “humanizing” function, which adds random deviations to the beat to give it a more human, “imperfect” feel. But these variations tend to make the music sound “off” and artificial. The fact that listeners are turned off by “humanized” music led Hennig and colleagues at the Max Planck Institute for Dynamics and Self-Organization in Germany to wonder whether human error in musical rhythm might show a pattern. Perhaps the “humanizing” features of computer-generated rhythms fail because they produce the wrong kind of errors — deviations unlike the kind humans produce. There are rhythms inherent in the human brain, which may affect our musical rhythm. The primal bio-rhythm in the neurons of the Ghanaian drummer might be echoed in the rhythm of his music, the physicists suspected.When they analyzed the drummer’s playing statistically, Hennig and colleagues found that his errors were correlated across long timescales: tens of seconds to minutes. A given beat depended not just on the timing of the previous beat, but also on beats that occurred minutes before.
Thhe research article: Hennig H, Fleischmann R, Fredebohm A, Hagmayer Y, Nagler J, et al. (2011) The Nature and Perception of Fluctuations in Human Musical Rhythms. PLoS ONE 6(10): e26457. doi:10.1371/journal.pone.0026457
Abstract: Although human musical performances represent one of the most valuable achievements of mankind, the best musicians perform imperfectly. Musical rhythms are not entirely accurate and thus inevitably deviate from the ideal beat pattern. Nevertheless, computer generated perfect beat patterns are frequently devalued by listeners due to a perceived lack of human touch. Professional audio editing software therefore offers a humanizing feature which artificially generates rhythmic fluctuations. However, the built-in humanizing units are essentially random number generators producing only simple uncorrelated fluctuations. Here, for the first time, we establish long-range fluctuations as an inevitable natural companion of both simple and complex human rhythmic performances. Moreover, we demonstrate that listeners strongly prefer long-range correlated fluctuations in musical rhythms. Thus, the favorable fluctuation type for humanizing interbeat intervals coincides with the one generically inherent in human musical performances.