Abstract
Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors such as human speech and musical performance, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical properties of the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable labeles, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model; GMM), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex behavioral sequences with higher-order dependencies.
Highlights
Humans can generate complex sequential behaviors such as speech and musical performance
The Bengalese finch song consists of acoustically continuous segments, called ‘‘song elements’’ or ‘‘syllables’’ which are separated by silent intervals
We discuss the implications of our results and possible neural implementation
Summary
Humans can generate complex sequential behaviors such as speech and musical performance. These sequences are typically composed of sequences of actions with complex sequencing rules. A solution to this issue may be given by studying songbirds [1]. Bengalese finches sing with apparently more complex sequencing rules with branching points [2,3,4], than does the zebra finch, whose songs are composed of a stereotyped syllable sequence and extensively used for birdsong studies. Bengalese finch songs have been receiving attention as a model of variable sequential behavior, from neurophysiological [5,6,7,8] and theoretical [9,10,11] view points
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