Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

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, 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 propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, 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. This property is shared with other complex sequential behaviors. 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 sequences with higher-order dependencies

Parallels in the sequential organization of birdsong and human speech.

Human speech possesses a rich hierarchical structure that allows for meaning to be altered by words spaced far apart in time. Conversely, the sequential structure of nonhuman communication is thought to follow non-hierarchical Markovian dynamics operating over only short distances. Here, we show that human speech and birdsong share a similar sequential structure indicative of both hierarchical and Markovian organization. We analyze the sequential dynamics of song from multiple songbird species and speech from multiple languages by modeling the information content of signals as a function of the sequential distance between vocal elements. Across short sequence-distances, an exponential decay dominates the information in speech and birdsong, consistent with underlying Markovian processes. At longer sequence-distances, the decay in information follows a power law, consistent with underlying hierarchical processes. Thus, the sequential organization of acoustic elements in two learned vocal communication signals (speech and birdsong) shows functionally equivalent dynamics, governed by similar processes

Network dynamics in the neural control of birdsong

Sequences of stereotyped actions are central to the everyday lives of humans and animals, from the kingfisher's dive to the performance of a piano concerto. Lashley asked how neural circuits managed this feat nearly 6 decades ago, and to this day it remains a fundamental question in neuroscience. Toward answering this question, vocal performance in the songbird was used as a model to study the performance of learned, stereotyped motor sequences. The first component of this work considers the song motor cortical zone HVC in the zebra finch, an area that sends precise timing signals to both the descending motor pathway, responsible for stereotyped vocal performance in the adult, and the basal ganglia, which is responsible for both motor variability and song learning. Despite intense interest in HVC, previous research has exclusively focused on describing the activity of small numbers of neurons recorded serially as the bird sings. To better understand HVC network dynamics, both single units and local field potentials were sampled across multiple electrodes simultaneously in awake behaving zebra finches. The local field potential and spiking data reveal a stereotyped spatio-temporal pattern of inhibition operating on a 30 ms time-scale that coordinates the neural sequences in principal cells underlying song. The second component addresses the resilience of the song circuit through cutting the motor cortical zone HVC in half along one axis. Despite this large-scale perturbation, the finch quickly recovers and sings a near-perfect song within a single day. These first two studies suggest that HVC is functionally organized to robustly generate neural dynamics that enable vocal performance. The final component concerns a statistical study of the complex, flexible songs of the domesticated canary. This study revealed that canary song is characterized by specific long-range correlations up to 7 seconds long-a time-scale more typical of human music than animal vocalizations. Thus, the neural sequences underlying birdsong must be capable of generating more structure and complexity than previously thought

Animal vocal sequences: not the Markov chains we thought they were.

Many animals produce vocal sequences that appear complex. Most researchers assume that these sequences are well characterized as Markov chains (i.e. that the probability of a particular vocal element can be calculated from the history of only a finite number of preceding elements). However, this assumption has never been explicitly tested. Furthermore, it is unclear how language could evolve in a single step from a Markovian origin, as is frequently assumed, as no intermediate forms have been found between animal communication and human language. Here, we assess whether animal taxa produce vocal sequences that are better described by Markov chains, or by non-Markovian dynamics such as the 'renewal process' (RP), characterized by a strong tendency to repeat elements. We examined vocal sequences of seven taxa: Bengalese finches Lonchura striata domestica, Carolina chickadees Poecile carolinensis, free-tailed bats Tadarida brasiliensis, rock hyraxes Procavia capensis, pilot whales Globicephala macrorhynchus, killer whales Orcinus orca and orangutans Pongo spp. The vocal systems of most of these species are more consistent with a non-Markovian RP than with the Markovian models traditionally assumed. Our data suggest that non-Markovian vocal sequences may be more common than Markov sequences, which must be taken into account when evaluating alternative hypotheses for the evolution of signalling complexity, and perhaps human language origins.This is the author's accepted manuscript and will be under embargo until the 20th of August 2015. This final version is published by Royal Society Publishing here: http://dx.doi.org/10.1098/rspb.2014.1370

Acoustic sequences in non-human animals: a tutorial review and prospectus.

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise - let alone understand - the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, 'Analysing vocal sequences in animals'. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.This review was developed at an investigative workshop, “Analyzing Animal Vocal Communication Sequences” that took place on October 21–23 2013 in Knoxville, Tennessee, sponsored by the National Institute for Mathematical and Biological Synthesis (NIMBioS). NIMBioS is an Institute sponsored by the National Science Foundation, the U.S. Department of Homeland Security, and the U.S. Department of Agriculture through NSF Awards #EF-0832858 and #DBI-1300426, with additional support from The University of Tennessee, Knoxville. In addition to the authors, Vincent Janik participated in the workshop. D.T.B.’s research is currently supported by NSF DEB-1119660. M.A.B.’s research is currently supported by NSF IOS-0842759 and NIH R01DC009582. M.A.R.’s research is supported by ONR N0001411IP20086 and NOPP (ONR/BOEM) N00014-11-1-0697. S.L.DeR.’s research is supported by the U.S. Office of Naval Research. R.F.-i-C.’s research was supported by the grant BASMATI (TIN2011-27479-C04-03) from the Spanish Ministry of Science and Innovation. E.C.G.’s research is currently supported by a National Research Council postdoctoral fellowship. E.E.V.’s research is supported by CONACYT, Mexico, award number I010/214/2012.This is the accepted manuscript. The final version is available at http://dx.doi.org/10.1111/brv.1216

A reafferent and feed-forward model of song syntax generation in the Bengalese finch

Adult Bengalese finches generate a variable song that obeys a distinct and individual syntax. The syntax is gradually lost over a period of days after deafening and is recovered when hearing is restored. We present a spiking neuronal network model of the song syntax generation and its loss, based on the assumption that the syntax is stored in reafferent connections from the auditory to the motor control area. Propagating synfire activity in the HVC codes for individual syllables of the song and priming signals from the auditory network reduce the competition between syllables to allow only those transitions that are permitted by the syntax. Both imprinting of song syntax within HVC and the interaction of the reafferent signal with an efference copy of the motor command are sufficient to explain the gradual loss of syntax in the absence of auditory feedback. The model also reproduces for the first time experimental findings on the influence of altered auditory feedback on the song syntax generation, and predicts song- and species-specific low frequency components in the LFP. This study illustrates how sequential compositionality following a defined syntax can be realized in networks of spiking neurons

A Bird’s Eye View of Human Language Evolution

Comparative studies of linguistic faculties in animals pose an evolutionary paradox: language involves certain perceptual and motor abilities, but it is not clear that this serves as more than an input–output channel for the externalization of language proper. Strikingly, the capability for auditory–vocal learning is not shared with our closest relatives, the apes, but is present in such remotely related groups as songbirds and marine mammals. There is increasing evidence for behavioral, neural, and genetic similarities between speech acquisition and birdsong learning. At the same time, researchers have applied formal linguistic analysis to the vocalizations of both primates and songbirds. What have all these studies taught us about the evolution of language? Is the comparative study of an apparently species-specific trait like language feasible? We argue that comparative analysis remains an important method for the evolutionary reconstruction and causal analysis of the mechanisms underlying language. On the one hand, common descent has been important in the evolution of the brain, such that avian and mammalian brains may be largely homologous, particularly in the case of brain regions involved in auditory perception, vocalization, and auditory memory. On the other hand, there has been convergent evolution of the capacity for auditory–vocal learning, and possibly for structuring of external vocalizations, such that apes lack the abilities that are shared between songbirds and humans. However, significant limitations to this comparative analysis remain. While all birdsong may be classified in terms of a particularly simple kind of concatenation system, the regular languages, there is no compelling evidence to date that birdsong matches the characteristic syntactic complexity of human language, arising from the composition of smaller forms like words and phrases into larger ones

Musical Regularity And Rhythmic Patterns: A Quantitative Analysis Of Birdsong Structure

Birdsong is a complex, learned behavior that, like music, has meaningful units at multiple timescales. Birds perform by constructing extended presentations of their phrase repertoire. Each bird\u27s repertoire is built from small units, such as syllables, or groups of syllables with characteristic pitch, rhythm, and timbre. Like a musician each bird has its unique structure of performance that communicates its individual identity. Also contained within a bird\u27s performance, is information about its group identity and species identity. Like a musician\u27s performance, a bird\u27s singing affects the behavioral state of listeners\u27birds perform to attract mates and defend territory. Subjectively, many can appreciate birdsong as musical but what evidence is there that birds have music? What parameters can be chosen to test the presence of musicality in birdsong? Are there quantitative ways to demonstrate musicality in birdsong? In this study I test quantitatively for the presence of musical structure in birdsong by homing in on two distinct features: structural balance and groove. Music is known for its characteristic balance between complexity and regularity. Groove, in the context of genres such as jazz offers a unique, visceral parameter that is known to vary in nuanced ways. I test for musical features based on understanding of how these two parameters manifest in music. Like music, birdsong affects the behavioral state of conspecifics, but what is it in the acoustic signal that serves to affect the behavioral state of bird listeners in a desired manner? By investigating extensive song databases of birds\u27 singing performances, I developed methods that facilitate a deeper understanding of what structures are present within song performances and why they may arise. A key feature of these methods is the capacity for multimodal data processing, as well as analysis at micro and macro levels simultaneously. This facilitates an understanding of the relationship between units and performance level structure. I studied two species to test for the presence of musicality within their vocalizations. In the Australian pied butcherbird I investigated temporal regularity in phrase types and demonstrated a characteristic balance analogous to that found in music. In the thrush nightingale I studied regularity in song rhythms and found that performance nuances used in groove rhythms follow similar principles in the context of music and birdsong alike. Australian pied butcherbird song phrases are built from the rearrangement of shared motifs (syllables or stereotyped groupings of notes). If the function of these motifs is to increase the repertoire of different phrase types, then transition probabilities between phrase types should capture most of the structure of singing performances. Alternatively, phrase types can be seen as varied presentations of shared themes, as often is the case in music. If this is the case, temporal regularity in performing shared motifs should be observed beyond phrase types, as if the transitions between phrases are designed to \u27organize\u27 those motifs over longer time scales. I tested which of those two views can explain more statistical regularity during entire singing performances of wild Australian pied butcherbirds, including thousands of song syllables recorded without interruption for each bird. I found that all birds produced several highly stereotyped phrase types. Most phrase types produced by each bird had shared motifs. Throughout the performance, the temporal gap between a motif\u27s reappearance was much more regular than what was expected by chance. In contrast, regularity in the performance of phrase types was much weaker. I developed a statistical estimate of the extent to which transition probabilities between phrase types are \u27optimized\u27 to maximize regularity in the repetition of shared motifs. I found that the phrase-types syntax is selective in achieving a regular repetition of shared motifs over the entire singing performance of the bird. This effect was stronger in birds with a richer song repertoire, suggesting the intriguing possibility that birds may regulate the temporal diversity of dominant themes in their singing performance in a manner that takes their repertoire size into account. The thrush nightingale is a distant relative of the pied butcherbird so it would be surprising to find similarities in the deep structure of the two species. I test whether or not thrush nightingales distribute motifs throughout a performance uniformly as butcherbirds do. I found that thrush nightingales exhibit more regularity in their distribution of phrase types than what is expected from chance. However, I failed to find a distribution of motif types that was balanced against repertoire size. The thrush nightingale ends many of its song phrases with buzzes (or rattles). Upon closer inspection these buzzes emerge from a diversity of repetitive rhythmic patterns of clicks. These clicks are repeated at a regular pace, or in rhythmic groups of two, three, and four or more and they sound like the complex grooves of a jazz drummer. I tested whether or not these patterns contain timing relationships that coincide with small integer ratios and found a no significant bias for small integer ratios. I tested whether or not the range of rhythmic ratios used could be explained by any systematic trend. I tested whether or not thrush nightingales, like jazz drummers adjust their \u27swing ratio\u27 according to tempo. Swing ratio is a term that describes the non-isochronous manner in which jazz musicians interpret eighth note rhythms, using a \u27long-short\u27 pattern instead of equal timing between beats. Jazz drummers tend to use a longer long segment at slow tempos and more even segments at fast tempos. I found that thrush nightingales have a significant tendency to adjust the swing ratio in the same manner