There is a variety of empirical tests for music and language which may serve as validation of the IDyOT approach. For example, an IDyOT with greater hierarchical depth of processing, or more training examples, may be used to predict listeners with differing degrees of expertise or development, respectively; one hypothesis, for example, would be that there is a cutoff in terms of hierarchical memory depth beyond which language will be dysfunctional. In music, an IDyOT exposed to a large corpus may process musical structure at a higher level than an IDyOT exposed to a small corpus, in the same way that expert listeners tend to perceive music in terms of more semiotic structure; in this case, IDyOT's behavior could be compared with existing results on human behavior. In addition to modeling listeners with more or less musical training, IDyOT may be used to model the musical perception and expectations of listeners with different cultural backgrounds. Further, IDyOT may be used to model subjective metricization, to test whether an encultured IDyOT exhibits the same subjective metricization behavior as similarly encultured humans.

In contrast to specifically modeling listeners with divergent expectations (afforded from different cultural backgrounds or degrees of musical expertise), IDyOT may be used to simulate interaction between "average" listeners, or those of a comparable hypothetical listening background. Exposing trained IDyOTs to conversational dialogue should afford predictions of the timings associated with observed turn-taking and of human judgments in end-of-turn prediction experiments. Similarly, it should be able to generate expressive timing for synthesized speech that correlates with human affective response to timing deviations.

In similar vein, timing may be used to disambiguate language incrementally, as follows. Consider the following discourse fragments1 :

In fragment 1, the onset of the final /k/ phoneme of "bank" will appear somewhat earlier than the initial /k/ of "catching" in fragment 2, and thus the predicted meaning of the two sentences may changed at this very low level, as in the very eagerly predictive Cohort Theory (Marslen-Wilson, 1984) and its descendents. IDyOT theory predicts this and models the effect of the change in time explicitly, as illustrated in **Figure 4**. Note, however, that, on balance, semantic implication is usually somewhat stronger in disambiguating, as discussed by Wiggins and Forth (2015).

In the domain of music, IDyOT may be run as a participant in a tapping synchronization study, with the hypothesis that human-human pairings are indistinguishable from human-computer or computer-computer pairings. This sort of experiment would not only confirm the accuracy of the underlying mechanisms of IDyOT, but demonstrate the validity of the model when scaled up to behavioral interaction. More generally, we would hope that other known effects such as the scaling of timing errors proportionally to duration magnitude would be an emergent property of IDyOT's processing of sensory input, or that IDyOT can model how temporal predictions are modulated by non-temporal factors such that surprise, attention, high-level expectation from top-down knowledge.

In addition to modeling production and synchronization, as in a tapping study, IDyOT may be used to simulate human perceptual characteristics, such as the perception of similarity. Hypotheses could examine the formation of the model's geometrical space and probabilistic scaling of dimensions by testing whether the high level patterns captured by IDyOT are reflective of schematic perception of rhythmic variations, or of generalization and classification of linguistic information.

Another avenue of research with regard to language would be to test anomalies in perception and/or in the signal itself. And because IDyOT theory proposes that attention is regulated by information contained within the signal, its predictions can be experimentally validated with methods such as EEG (e.g., ERP Mismatched Negativity—MMN—analyses) or eyetracking measurements, as these techniques capture the real-time dynamics of information processing. In one such experiment, IDyOT should be able to reliably detect a deviant item within a repetitive sequence, and therefore should accurately predict MMN response in oddball paradigms (Näätänen et al., 2007), for example. Rather than predicting neural response to anomalies, one may also predict human cognition at the behavioral level, by exposing a trained IDyOT to garden-path sentences, as discussed previously, or to semantically equivalent sentences which vary in hierarchical periodic temporal structure. In this later case, one would test whether IDyOT produces temporal responses comparable to humans (e.g., who make different end-of-sentence predictions). And finally, rather than testing ambiguous or unexpected sentence endings, one may also expose a trained IDyOT to nonsense words, to see whether the model, like humans, creates perceptual chunks, perceptually imposing more regularity in time than exists in the signal.

In the music information retrieval literature (see www.ismir. net), there is significant interest in so-called "beat tracking" the automated detection of beat in (mostly popular) music, for the purpose of finding similar music for listeners. This not unsuccessful literature (e.g., Dixon, 2001, 2007; Davies and Plumbley, 2007) affords a rich vein of models against which to compare IDyOT's entrainment mechanism. Similarly, psychological (Povel and Essens, 1985) and neuroscientific (Patel and Iversen, 2014) comparators exist.

### 6.2. Predicting Behavior from IDyOT

Following Honing (2006), once a model has been validated, the researcher should push the model toward the extremes of its parameters, to discover unexpected predictions about human behavior. This is a valuable step in testing and exploring a model's performance, because surprising predictions (1) may inform us about hitherto unknown (or not well understood) human cognitive mechanisms, and (2) will further validate the model in a broader range of behavioral contexts, by pushing the boundaries of what is known, not simply modeling expected behavior.

### 6.3. Correspondence with Neural Function

Our methodology is to model cognitive function abstracted from its substrate. However, it is useful to consider cognitive predictions in context of their hypothetical neurophysiological implementation, even though they are separated from it.

The function of IDyOT, however abstract, entails memory representations that increase in size with time. These representations, though not literal recordings of sensory experience, are very high-dimensional, because they connect all aspects of all features of sensory input together, where correlated. Unless one admits mysticism or quantum theory at the physical level of the brain (which we do not), this very dense interconnectedness entails the availability of brain volume which is strongly supralinear with respect to time, because every neural assembly (Hebb, 1949) has to be connected to every other relevant neural assembly, across modalities, between senses, and so on. This, we claim, is a necessary requirement of the established ability for veridical memory: we could not remember detail of a sonata or soliloquy unless it were so at some level of abstraction (notes/chords and words, respectively). Various antidotes to this effect may be proposed. For example: the low level detail of the memory may be discarded in favor of more abstract representations; or the layering of structures may be restricted to a given number of layers; or the connections

1This example is oversimplified from a phonologist's perspective, because the /aN/ in "bank" and "bang," would in reality change subtly to reflect what is coming next, but it serves to make the point here.

between correlated sensory features may be limited; and so on. This affords a rich plethora of detailed hypotheses that may be tested in relation to comparative brain size of extant species with various cognitive capacities. This, in its own right, may be expected to elucidate the quality of the model in respect to these capacities; subsequently, in careful comparison with similar extinct species, it may be possible to chart a path relating increase in brain size with the development of successively more advanced cognitive capacities.

For example, it is known that dogs can perceive, remember, and associate meaning with words (that is, sequences of phonemes). But there is no evidence that they can compose words into meaningful phrase interpretations; indeed, quite the contrary. Our model would produce this effect when limited to only a few layers of chunking above the audio: sequences of phonemes, such as "walkies" would be memorable, but longer composed phrases and sentences would not. On the other hand, our theory affords much deeper construction when more layers are allowed (Wiggins and Forth, 2015).

Given this evolutionary account, one can formulate experiments based on IDyOT's ability to learn sequential structures (such as language or music) in which dependent variables relate to cortex volume: for example, the depth of layering can be limited, or the alphabets of the various layers can be limited, or both. These restrictions would be expected to limit the ability of the system to learn, and thence to predict. This approach, in particular, allows us to distinguish IDyOT from models whose parameters (e.g., node number in neural networks) are less specifically related to the function of the theory.

### 6.4. Evolving IDyOTs

From a modeling perspective, evolution may be thought of as a long-term parameter search within the IDyOT architecture and processing framework. When multiple IDyOTs exist in a genetic system, evolving freely, some will discover parameterization that allows for more efficient, evolutionarily adaptive behavior than others. Studies could be constructed such that IDyOTs with different temporal-predictive capacities will compete to survive, while the parameters of well-synced models are passed on to future generations by simulated breeding. The algorithmic parameters and probabilistic weightings underlying predictive processing may be randomly varied across agents to see which variations yield the most adaptive IDyOTs. Then, again, those whose predictions facilitate accurate communication or behavior

### REFERENCES

may pass their algorithmic idiosyncrasies on to their IDyOT children.

In particular, parameters such as depth of hierarchy and retention of detail in symbol creation can be varied, and their effect on the predictions of the system studied. The most interesting possibility here is modeling the evolution of the neocortex: in the style of Bown and Wiggins (2005), an evolutionary computation system may be set up that allows simulation of not only cognitive function, but also the behavior of populations. Thus, evolution may be simulated quite literally in silico, albeit at a functional level, and the relationship between biological affordances and effects studied in ways that are not accessible in vivo.

### 7. SUMMARY

In this paper, we have presented a novel model of timing in a predictive cognitive architecture. We have described in some detail how the temporal predictions allow efficient processing of ambiguous and/or noisy perceptual signals, and we have related the mechanisms to both linguistic and musical rhythm. Finally, we have proposed methods by which the approach will be evaluated, which constitutes the future work of the IDyOT project.

### AUTHOR CONTRIBUTIONS

JF invented the conceptual space representation and wrote about it, and also proposed much of the testing section; KA underpinned the theory with empirical research from psychology and neuroscience, and also contributed a lot to the testing section; MP supplied the linguistic grounding; GW invented the core model and wrote the sections summarizing it, and those on timing, using illustrations suggested by MP, and neural implementation. The rest of the writing was a team effort.

### ACKNOWLEDGMENTS

The authors are supported by the projects Lrn2Cre8 and ConCreTe, which acknowledge the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under FET grant numbers 610859 and 611733, respectively. Thanks to Sarah Hawkins and Dan Stowell for stimulating related discussions and useful information.

Available online at: http://www.ling.cam.ac.uk/sarah/docs/hawkins-smith-01. pdf

Kipling, R. (1993). Just So Stories, New Edn. Ware, UK: Wordsworth Editions Ltd.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer JL and the handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.

Copyright © 2016 Forth, Agres, Purver and Wiggins. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Commentary: Beta-Band Oscillations Represent Auditory Beat and Its Metrical Hierarchy in Perception and Imagery

Sundeep Teki 1 \* and Tadeusz W. Kononowicz 2

1 Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK, 2 CEA.DSV.I2BM.NeuroSpin - Institut National de la Santé et de La Recherche Médicale Cognitive Neuroimaging Unit, Gif sur Yvette, France

Keywords: timing and time perception, rhythm perception, music perception, magnetoencephalography, predictive coding, beta oscillations, beat perception

#### **A commentary on**

#### **Beta-Band Oscillations Represent Auditory Beat and Its Metrical Hierarchy in Perception and Imagery**

by Fujioka, T., Ross, B., and Trainor, L. J. (2015). J. Neurosci. 35, 15187–15198. doi: 10.1523/JNEUROSCI.2397-15.2015

#### Edited by:

Andrea Ravignani, Vrije Universiteit Brussel, Belgium

#### Reviewed by:

Hugo Merchant, National Autonomous University of Mexico, Mexico Takako Fujioka, Stanford University, USA

> \*Correspondence: Sundeep Teki<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Auditory Cognitive Neuroscience, a section of the journal Frontiers in Neuroscience

> Received: 04 March 2016 Accepted: 09 August 2016 Published: 23 August 2016

#### Citation:

Teki S and Kononowicz TW (2016) Commentary: Beta-Band Oscillations Represent Auditory Beat and Its Metrical Hierarchy in Perception and Imagery. Front. Neurosci. 10:389. doi: 10.3389/fnins.2016.00389 The ability to predict the timing of natural sounds is essential for accurate comprehension of speech and music (Allman et al., 2014). Rhythmic activity in the beta range (12–30 Hz) is crucial for encoding the temporal structure of regular sound sequences (Fujioka et al., 2009, 2012; Bartolo et al., 2014; Teki, 2014; Bartolo and Merchant, 2015). Specifically, the power of induced beta oscillations in the auditory cortex is dynamically modulated according to the temporal pattern of beats (Fujioka et al., 2012), such that beat-related induced beta power decreases after the beat and then increases preceding the next beat as depicted in **Figure 1A**. However, it is not known whether beta oscillations encode the beat positions in metrical sequences with physically or subjectively accented beats (i.e., "upbeat" and "downbeat") and whether this is accomplished in a predictive manner or not.

In a recent study, Fujioka et al. (2015) used magnetoencephalography to examine the role of induced beta oscillations in representing "what" and "when" information in musical sequences with different metrical contexts, i.e., a march and a waltz. Musically trained participants listened to 12 beat sequences of metrically accented beats, where every second (march) or third (waltz) beat was louder, along with unaccented beats at the same intensity. The paradigm consisted of two phases: A perception phase where accented beats were presented in march or waltz contexts and participants were required to actively perceive the meter, followed by an imagery phase where unaccented beats were presented at a softer intensity and participants had to subjectively imagine the meter.

Similar to their previous study (Fujioka et al., 2012), the authors found that event-related beta desynchronization (ERD) follows the beat, i.e., beta ERD response showed a sharp decrease after the stimulus, attained a minima with a latency of ∼200 ms, and subsequently recovered with a shallow slope (see Figure 2 in Fujioka et al., 2015). This result has been previously demonstrated (Fujioka et al., 2009, 2012), and extended by other groups using electrophysiological recordings in humans (e.g., Iversen et al., 2009), and macaques (Bartolo et al., 2014; Bartolo and Merchant, 2015), as well as demonstrating a role for induced beta oscillations in time production (Arnal et al., 2015; Kononowicz and van Rijn, 2015). This result was valid for both the march and waltz conditions in the perception and even more importantly in the imagery phase, implying a top-down mechanism.

**44**

FIGURE 1 | Schematic depiction of the time course of induced beta oscillatory activity for a hypothetical sound sequence (indicated by vertical bars in gray, in the order, upbeat, downbeat, and upbeat), in accordance to the "predictive timing" and "event tagging" mechanisms. Presented pattern is based on previous studies such as Fujioka et al. (2012). (A) Predictive timing theory (e.g., Arnal and Giraud, 2012) suggests that beta power should peak before each sound, such that the rebound of beta power could be predictive of the timing of the upcoming sound, regardless of the salience of the sound. (B) A hypothesized predictive code that also encodes the identity of the salient events in a sequence may show modulation of the stereotypical beta ERD response in panel (A), expressed in terms of differential magnitude (here, greater beta suppression) before the salient event. As opposed to panel (A) beta power is not modulated in the same manner before upbeats and downbeats, allowing the encoding of "what" and "when" information in a manner consistent with the predictive timing framework (e.g., Arnal and Giraud, 2012). (C) Event tagging proposal (Iversen et al., 2009; Hanslmayr and Staudigl, 2014) suggests that beta power encodes accented events and should peak after the accented sounds, which is in contradiction with the predictive coding of "what" information depicted in panel (B).

Significantly, the authors claimed that the beta ERD response in the auditory cortex differentiates between the positions of the downbeat and the following beat (see Figures 3, 4 in Fujioka et al., 2015).

The novel result reported by Fujioka et al. (2015) is that the beta ERD response in auditory cortex can distinguish between accented beat positions in metrical sequences. However, the underlying mechanisms are far from clear. Fujioka et al. (2015) explain their results using predictive coding theory (Bastos et al., 2012) but an alternative "event tagging" mechanism (Iversen et al., 2009; see Repp, 2005 and Repp and Su, 2013 for a review on mechanisms for metrical processing), may also account for metrical interpretation of beat-based sequences.

We consider the results of Fujioka et al. (2015) in the light of these two mechanisms, i.e., predictive timing and event tagging (**Figure 1**). The predictive coding framework posits that beta oscillations are associated with anticipatory behavior and predictive coding (Arnal and Giraud, 2012). An internal model is established that conveys top-down predictions based on modulation of beta power with the goal of predicting the next event as shown in **Figure 1A**. However, if the predictive code were to also represent the identity of the salient event (i.e., what) in addition to its timing (i.e., when), one may hypothesize a modulation of the beta ERD response before the downbeat, which might be expressed in terms of differential magnitude as shown in **Figure 1B**. Such a response, that is specific to the downbeat would predict both the identity and timing of accented beats.

According to the event tagging framework (Hanslmayr and Staudigl, 2014), beta oscillations encode salient events (e.g., downbeat) as depicted in **Figure 1C**. Specifically, desynchronization of induced beta power may reflect memory formation (Hanslmayr and Staudigl, 2014) or an active change in sensorimotor processing (Pfurtscheller and Lopes da Silva, 1999). During rhythm perception, where encoding the beat in memory is critical (Teki and Griffiths, 2014, 2016) the structure of the metrical accents and salient events may be represented by the depth of beta desynchronization. Therefore, the largest beta desynchronization may be expected to occur after the downbeat (**Figure 1C**). In the present study, the amount of beta desynchronization was found to be largest after the accented tones. Therefore, the reported results are consistent with the event tagging framework, suggesting that subjectively and physically accented events invoke changes in the encoding of these events (Pfurtscheller and Lopes da Silva, 1999; Repp, 2005).

However, it is plausible that the predictive timing and event tagging mechanisms may operate in concert. To confirm this hypothesis, one needs to assess whether any prediction, implemented as beta rebound, occurs before the accented tones (**Figure 1B**). In the current study, it is difficult to determine whether there is robust beta synchronization before the accented tones. Careful observation of the results (Figures 3, 4 in Fujioka et al., 2015) suggests that beta power is not modulated before the downbeat in either of the two metrical conditions, neither in the perception nor in the imagery phase, except for a weak effect for the waltz-perception condition in right auditory cortex.

It is therefore not evident whether beta ERD carries predictive information about salient events, in addition to their timing. Therefore, future studies should also focus on other (nonsensory) brain regions, like the supplementary motor area or basal ganglia that are implicated in encoding rhythmic patterns (Grahn and Brett, 2007; Teki et al., 2011; Crowe et al., 2014; Merchant et al., 2015), as it is possible that different regions may recruit distinct mechanisms.

Overall, this study has provided significant insights about the neural representation of musical sequences. Beta oscillations have repeatedly been shown to track the timing of events in sound sequences but whether they can differentiate between beat positions, i.e., also encode categorical information about the events has been highlighted by the present study. It is important to build upon the current results and identify the precise role of beta oscillations with respect to encoding of

### REFERENCES

"when" and "what" information in natural sound sequences, and future research may benefit highly from the current study.

### AUTHOR CONTRIBUTIONS

All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.

### ACKNOWLEDGMENTS

ST is supported by the Wellcome Trust (WT106084/Z/14/Z; Sir Henry Wellcome Postdoctoral Fellowship). TK is supported by ERC-YSt-263584 awarded to Virginie van Wassenhove.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Teki and Kononowicz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# A Comparative Analysis of the Universal Elements of Music and the Fetal Environment

#### David Teie\*

School of Music, University of Maryland, College Park, College Park, MD, USA

Although the idea that pulse in music may be related to human pulse is ancient and has recently been promoted by researchers (Parncutt, 2006; Snowdon and Teie, 2010), there has been no ordered delineation of the characteristics of music that are based on the sounds of the womb. I describe features of music that are based on sounds that are present in the womb: tempo of pulse (pulse is understood as the regular, underlying beat that defines the meter), amplitude contour of pulse, meter, musical notes, melodic frequency range, continuity, syllabic contour, melodic rhythm, melodic accents, phrase length, and phrase contour. There are a number of features of prenatal development that allow for the formation of long-term memories of the sounds of the womb in the areas of the brain that are responsible for emotions. Taken together, these features and the similarities between the sounds of the womb and the elemental building blocks of music allow for a postulation that the fetal acoustic environment may provide the bases for the fundamental musical elements that are found in the music of all cultures. This hypothesis is supported by a one-to-one matching of the universal features of music with the sounds of the womb: (1) all of the regularly heard sounds that are present in the fetal environment are represented in the music of every culture, and (2) all of the features of music that are present in the music of all cultures can be traced to the fetal environment.

Keywords: origin of music, womb, pulse, music, rhythm

#### Colwyn Trevarthen, University of Edinburgh, UK Matz Lennart Larsson, Örebro University Hospital, Sweden

Reviewed by:

Edited by: Andrea Ravignani,

\*Correspondence: David Teie<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Auditory Cognitive Neuroscience, a section of the journal Frontiers in Psychology

Vrije Universiteit Brussel, Belgium

Received: 13 February 2016 Accepted: 20 July 2016 Published: 09 August 2016

#### Citation:

Teie D (2016) A Comparative Analysis of the Universal Elements of Music and the Fetal Environment. Front. Psychol. 7:1158. doi: 10.3389/fpsyg.2016.01158

## THE QUESTION OF THE ORIGINS OF MUSIC

It is reasonable to postulate that the characteristics of music that are common to the music of all cultures must have a common origin. Is there a correlation between the acoustic features of the common elements of music and the acoustic features of sounds that are present in the natural world? If so, is there a consistent and universal aspect of human development that would allow those sounds from the environment to be implanted as templates of recognition in the brains of peoples of diverse and widely separated cultures? Finally, if that common environment is prenatal, does the neurological development of the fetus allow for the absorption and retention of information from the womb? If the prenatal acoustic environment contains characteristic sounds that are the bases for some of the elements of music, then it should be possible to match, one-for-one, the sounds of the womb to those elements that can be found in the music of all cultures.

This hypothesis is not intended to be complete nor exclusionary. The scope is restricted to the elements of music that may be traced to the sonic environment during fetal development;

it does not attempt to address the various expressions and uses of music or narrative expression such as those that are found in social connections, communicative support, kinetic synchrony, and motivation. A variety of well-supported explanations for our enjoyment of music such as expectation, maternal and social bonding, and development of narrative through shared activity may be understood as parallel to and not contrary to the bases outlined below. The proposition that the origin of the common elements of music may be found in the sonic environment of the womb is not inconsistent with a host of other valid premises and observations concerning the developments of the many culturally diverse languages of music.

### OUTLINE OF HYPOTHESIS

This outlines a proposal that there is a fetal origin of the fundamental building blocks of music. The sounds heard by the fetus for four months before birth may permanently etch the foundations of music into the collection of brain structures that form what is commonly known as the limbic system. These structures are primarily responsible for our emotions and are almost fully formed at birth (Huang et al., 2006). The features of fetal development that make it possible for the fetus to hear sounds, remember (subconsciously) those sounds in adulthood, and respond to them emotionally have been demonstrated in studies that are cited below. When these features are added together and compared to the construct of music it is reasonable to conclude that the part of our brains that is responsible for emotions retains information from and recognizes the sonic environment of the womb.

The prevalent sounds of the fetal environment are pulse, respiration, footfalls, and the mother's voice. McDermott (2008) identified several universal properties of music: pulse, hierarchal organization of scales (tonality), infant-directed song, dance, and meter. To McDermott's list I propose adding: amplitude contour of pulse instrument, prevalence of discrete singlefrequency units (musical notes), varied pitches and rhythms in the melodies (prosody), the 200–900 Hz frequency range of melodic instruments, and continuity. The following is an outline of the musical elements that are based on the sounds of the womb: pulse (pulse is understood as the regular, underlying beat that defines the meter), amplitude contour of pulse, meter, musical notes, elements related to prosody (syllabic contour, melodic rhythm, melodic accents, phrase length, and phrase contour), melodic frequency range, and continuity. All of these universal features of music can be traced to the womb and all of the sounds heard in the womb are represented in the music of all cultures. **Table 1** outlines the sounds heard in the womb and the corollary features of music.

### LIMBIC SYSTEM DEVELOPMENT MEMORY

In light of anatomical studies that have emphasized the interconnections between ventral limbic circuits and the motor

#### TABLE 1 | Sounds of the womb and their corollaries in music.

control connections between striatum and motor cortex (Gunnar and Nelson, 1992), I propose that the acoustic information that pervades the development of structures responsible for our emotions as well as structures near the brainstem responsible for repetitive movement are the sources and origins of pulse, meter, and rhythm in music. The elements of music that are most universal are musical representations of sounds that are heard during the time when the limbic structures are formed in the developing brain. The following conditions allow for the formation of lasting fetal acoustic memories: The human fetus is able to hear at 24 weeks, providing 4 months of constant sound exposure (Birnholz and Benacerraf, 1983) prior to birth. The sound of the maternal heartbeat is 25 db above basal noise, dominating the fetal environment (Querleu et al., 1988). The maternal voice is heard in the uterus nearly four times more strongly than it is heard externally (Richards et al., 1992). In utero research and analysis has shown consistent evidence that the fetus responds to the sound of the mother's heartbeat (Porcaro et al., 2006) and that infants also respond to the prosodic features of speech (see below).

The combination of three features of human fetal development make it possible for the sounds of the womb to provide a lasting template of recognition: (1) the dearth of competing sensory information in the fetal environment allows sound to be a primary source of varied and ever-present information entering the developing brain, (2) information that is well-organized when incoming while a brain structure is plastic will tend to remain organized in the brain, and (3) the limbic structures are well-developed at birth. 3D brain imaging technology used by scientists in Baltimore (Huang et al., 2006) showed that the structures of the limbic system are almost completely formed at birth. The limbic fibers, the cingulum and the fornix, are two of the most dominant tracts in the fetal brain and their entire trajectories are already developed at 19 gestational weeks. "Early formation of the limbic system is well known, and it is expected that limbic fibers are well formed at 19–20 gestational weeks." – Huang et al. (2006, p. 36). The brain structures responsible for our emotions are able to retain information long before the upper cortical structures. A logical conclusion to the summed effects is that brain structures responsible for emotions and that are well developed at birth may remember and later respond to sounds that resemble those of the fetal environment.

A regular and repeated pulse is one of the universal traits of music is even though it is not found in human vocalizations. Intrauterine recordings taken in humans and animals have shown that the sounds of the mother's vocalizations, breathing, heartbeat, body movements, footfalls, and digestion are all audible to the fetus (Parncutt, 2006). In-utero research and analysis has consistently shown that the fetus responds to the sound of the mother's heartbeat. Sound measurements taken in the womb have shown that the sound of the mother's heartbeat in the womb is 25db above the baseline noise (Querleu et al., 1988).

The sound and sensation of maternal footfalls as experienced by the fetus may provide information that informs the origin of the deep connection between dance and music. The interconnections between motor control and limbic structures mentioned above may provide the framework for retention of the tactile sensations of walking as felt in the womb in combination with the pulsing sounds of footfalls. The sonic-tactile association in the fetal brain will tend to be strong in keeping with the famous principle of neurological development that "neurons that fire together wire together". Since adults take about 10,000 steps per day (Tudor-Locke and Myers, 2001) the presentation of the sound/sensory stimuli to the fetus is ubiquitous under normal circumstances. Music is often played at tempos similar to walking (Changizi, 2011) and it is reasonable to propose that one of the bases for this connection results from the concurrent stimuli of the tactile and sonic sensations of maternal footfalls informing the developing brain of the fetus.

The regular and constantly repeated sounds of maternal respiration create a repetitive acoustic framework that is broader and less specific than the heartbeat and possibly provides a basis for the recognition of more generalized pulse in music. Instruments that create amplitude contours that resemble that of a heartbeat such as drums made from stretched material over a resonating cylinder struck with a beater commonly keep the musical pulse.

The narrow spectrum of types of sounds that we humans respond to becomes apparent when we compare our time scale to other species. The ruby throated hummingbird has a resting heart rate of 615 beats per minute (Odum, 1945). If hummingbirds had their own music, it seems likely that it would be incomprehensively fast to our ears. The repetition rates of the pulses found in human music on the other hand (40– 240 beats per minute) coincide with the slowest (respiration) and fastest (footfalls of running) pulses that can be heard in the womb. Human music seems to be built to the human scale.

The fetal environment provides little information that is significantly varied for the senses of sight, smell, or taste. Hearing is the exception to this dearth of information; sounds are always present. The patterns of speech heard in the womb are constantly changing and are available to be learned by the fetus. The heartbeat, although more consistent than speech or footfalls, also provides varied information that is constantly available to the fetus.

### THE DRUM

The drum is an example of an instrument that was invented and adopted for use in music in every culture. The similar construction of the drums from widely separated cultures demonstrate the common recognition of the sound of pulse that informed the development of the features of the instrument. The amplitude contour of the drum is such that it conforms to the sound of the pulse as heard from the womb. Over the centuries of the development of instruments, musicians found that stretching a skin over something round makes the sound die away more slowly (longer decay). It was also discovered that elongating the round skin holder into a cylinder made the sound more resonant and could give it a pitch (the tube resonates and lengthens the decay even more). And if it were struck with a cushioned beater the beginning of the sound would be less sudden (longer onset). Each of these modifications was made in order to create a pulse sound that we perceive as "good". Recognition is the key point here. Why does a drum sound "better" than a stick hitting a table? The answer may be: because we recognize the drum sound, each of us who can hear heard it constantly for four months before we were born.

The construction of a drum enables it to create a heartbeatlike amplitude contour of the pulse instrument. Drums have been similarly constructed in many different cultures. (1) The onset of sound is graduated by a cushioned beater, a stretched animal skin, or both. (2) The decay of sound is elongated with a resonating chamber.

Geographically separated peoples came up with the same basic drum design. Three thousand years ago as the Greeks were drawing images on vessels of people playing the tympanon, the Chinese of the Shang Dynasty were making drums out of clay and stretched alligator skin. These parallel developments occurred well before the silk route had established a connection between the cultures of the East and West. Meanwhile the cross-rhythms of the Niger-Congo peoples were being played on Djembe drums that would not be seen by Europeans until the 15th century. That was around the time Westerners began invading the Americas where they found that drums had been made by all of the aboriginal Americans: from the Inuit and Ojibwe in the North, to the Lakota in the plains, the Aztecs between the continents and the Incas in the South.

To explain the parallel development in widely separated cultures of a musical instrument with a singular, basic design, and that was meant to be struck in repeating patterns of pulse and meter suggests a common root among all people. This commonality must be fundamental enough to supersede all linguistic, racial, and cultural differences. Furthermore, since all emotional responses begin with recognition, and since the preference for the sound of the drum is universal, then it is most logical to conclude that the template of sound that is recognized was formed in an environment that we all share. Emotional responses follow salient recognition; it would seem that the sound created by a drum triggers such recognition.

Below are a few figures and descriptions that outline the similarities between the amplitude contour of the human heartbeat and the drum:

**Figure 1A** above shows the spike of a transient sound made by one stick hitting another; this sounds "not so good" to us. For comparison, **Figure 1B** shows the amplitude contour of a human heartbeat. The amplitude contour of **Figure 1C** is created by a cushioned beater striking a drum. When skin is stretched over a round collar and placed over a resonating cylinder, the resonance of the cylinder amplifies and elongates the decay of the sound. Striking the skin with a cushioned beater creates a graduated onset. The resulting amplitude contour resembles that of the heartbeat as heard in the womb (onset 0.02 s, decay 0.06 s). In its completed form, when the onset is graduated as well as the decay, this sounds "just right" to us. The feelings of "good", or "just right", like all emotional responses, begin with recognition. It is possible that we recognize the sound that was imbued in our growing brains.

Tactile response is present in contemporary music that is presented in high decibel levels. The musicians of these genres are seeking sound levels that are not only able to be heard, but are also able to be felt. In an interview with the author, Dickie Peterson, one of the original band members of a predecessor of heavy metal music, reported that they wanted to create music that could be felt. The desire for tactile sense of music may be traced to the sensations of the womb. The maternal heartbeat creates a pressure wave that not only can be clearly heard but may also be felt by the fetus. The dense, liquid-filled environment of the womb allows for a pressure wave emanating from the maternal heartbeat to travel through the tissue of her womb into and through the body of the fetus.

### METER

The differently paced and constantly overlapping pulses of heartbeats, inhalation, and exhalation create patterns of strong and weak beats. In the womb the inhalation is louder than the exhalation. When the inhalation sounds simultaneously with the heartbeat, the combination forms the strongest sound, exhalation with the heartbeat is somewhat strong, and the heartbeat alone is weakest. As a result, it is reasonable to conclude that music has evolved to include repeating patterns of strong and weak beats that resemble those in the fetal environment. The combination of heartbeats and breathing heard in the womb may be the basis for musical meters.

From this perspective, the combinations of strong and weak pulses found in the primary meters would be derived from the sounds of respiration combined with the sound of the heartbeat. Strong-weak is duple meter. **ONE** two THREE four (1 strongest − 2 weak − 3 strong − 4 weak) is known as "common time" in Western music. When respiration and heartbeat are combined: 1 inhalation + heartbeat – 2 heartbeat alone − 3 exhalation + heartbeat − 4 heartbeat alone, the result is common time and this is consistent with normal human heart and respiratory rates (approximately four heartbeats/respiratory cycle).

The prevailing duality of pulse in Western music is the same duality found in the human rhythms of heartbeats, breathing, and walking. When respiration and heart beat are combined we have (**Table 2**):

Perhaps common time is common to us all. Theoretically, the possible combinations of tempos and stresses that are available are infinite, yet the spacing, stresses, and tempos of common time are the very same as the combined pulsations that are often heard in the womb. Other meters that are used in music can also be traced to other combinations of the strong and weak beats created intermittently by the varied combinations of heartbeat and respiration. The ratio of (1) STRONG – (2) weak is 2/4 time, and (1) STRONG – (2) weak – (3) weak is 3/4 time.

Footfalls also create pulses that can be heard and felt by the fetus and may combine with the heartbeat to create overlaps that also augment the strength of some beats. Naturally, not all mothers have the same heart/respiration ratios and the synchronicity of the beats is constantly changing. The heartbeat is faster when walking and the pressure waves created by the footsteps of a pregnant mother are audible to the fetus (Parncutt, 2006). The faster pace of the heartbeat combined with the even pulses of footfalls creates a relatively quick 2/4 m. Even the rarely heard footfalls of running may be found in the developing brain's list of recognized combined pulses.

A weak beat placed where the silence occurs between the duple pulses of the heart creates a triple meter. Here is a visual approximation using "lubb, dub", the traditional vocal approximation of the sound of the heartbeats used by physicians:

These mixed meters may also traceable to the fetal sonic environment. 6/8 is a combination of triple/duple (**1** 2 3 **4** 5 6) combining the LUBB – dub - silence of a quickened heartbeat with inhalation and exhalation.

It has been noted that the music of some cultures such as some Balkan cultures have music that does not use common meters. Irregular meters may also be derived from the combination of heartbeat and respiration. It should be noted that symmetrical rhythms are not common, even in Balkan music; the rhythms of Balkan music are primarily duple. Generally there is a distinction between underlying pulse rhythm and melodic rhythm, but this may be a case where they mingle. The Balkan exception may be due to the melodic rhythm in the language, since Greek allows for more irregularities between stressed and unstressed syllables than English (Patel, 2008).

### MELODY

The maternal voice heard by the fetus in the womb may provide the foundation of musical notes and melody. The pitches created by the vocal chords of the mother are distinct and loud in the fetal environment. A team of researchers from the University of Florida headed by Douglas Richards managed to convince eight bedridden mothers-to-be to have microphones inserted into the uterus and placed near the head of the fetus. The mothers were asked to speak in a loud voice as the intrauterine sound level was recorded. They found that the average mother's voice in the womb is 77.2 dB, nearly four times greater than the intensity measured in the air at a distance of 24 inches (Richards et al., 1992). A spoken sentence is heard in the womb as a pattern of discrete pitches in a variety of melodic contours and rhythms.

### DISCRETE, SINGLE-FREQUENCY SEGMENTS (MUSICAL NOTES)

Discrete, single-frequency segments (notes) are found in the music of all cultures. The mother's speech that is heard in the womb consists primarily of single-frequency segments created by the vowels between the consonants (Querleu et al., 1988). These units may provide the singular basis for notes in music. We do not find music from any culture that consists primarily of sliding pitches. Mammalian vocalizations generally consist of syllables that have contoured frequencies (sliding pitches) such as a cat's meow or a dog's submissive whimper as well as the human vocalizations such as moaning and weeping (Parvizi et al., 2001). Despite this preference for contoured frequencies in emotional vocalizations, human music contains a preponderance of discrete single-frequency units.

This variance between the characteristics of emotionally generated vocalizations and the characteristics of music might be explained by the womb origin of music. The prevalence of discrete single-frequency segments is a feature of the music of all cultures. One of the prominent features of Schubert's melodic style is that he gave each syllable in the lyrics only one note. Irving Berlin, who was described by George Gershwin as "America's Schubert" used the same one-to-one note/melody standard as Schubert. Accordingly, most languages are made up of predominantly single-pitch segments separated by consonants.

The preference for discrete single-frequency segments in music may be accounted for when acoustical properties of the womb are considered. The middle and lower frequencies of the mother's speech emanating from the maternal vocal chords are carried directly to the ears of the fetus through the medium of the liquid and tissue of the womb that is approximately five times more efficient than air. The high frequency sounds of the consonants such as "ch", "t", "s", and "sh" formed at the opening of the mouth are significantly attenuated when transferred from the air to the tissue and further attenuated by the absorption of sound by the surrounding tissues in the womb. Due to this attenuation, the consonants of speech are nearly inaudible in the womb but the "melody" of the pitches created by the vowels between the consonants is clearly audible and would sound something like humming discrete single-frequency pitches.

When we compare the features of maternal speech as it is heard in the womb to the features of melodies that are found in the music of a wide variety of cultures we find compelling similarities. Indeed, it is a supportable assertion that the contours and prosody of specific languages as heard by the fetus are nearly identical to the melodic contours of the music associated with that language. All of the commonly found features of musical melodies are present in the mother's voice as it is heard in the womb. Speech is produced in predominantly consonant intervals and contains implied tonalities (Schwartz and Purves, 2004; Bowling et al., 2009). As a consequence, the melodies heard in the womb are primarily harmonically consonant.

The prosody of languages may form the bases for melodic treatment in music. Newborns of French mothers prefer the

sound of the French language to Russian (Mehler et al., 1988). The newborns still prefer the French language when the speech is filtered to remove the consonant and vowel sounds in order to present maternal speech as it is heard from inside the mother, retaining only the melody, but they do not show a preference for the melody of the French language when played backward, implying that a fetus is able to recognize intervallic relationships and melodic contours.

Evidence for fetal learning of the melodic contours of maternal speech is also found in the cries of newborns that emulate the melodic contours of the mother's language (Mampe et al., 2009). Kathleen Wermke of the University of Würzburg in Germany studied five-day-old infants and discovered that they use the contours of their own mothers' language in their cries (Mampe et al., 2009). Words and combinations of words create recognizable rhythms that are found in the melodic rhythms of musical motives. Cultures whose languages have accented syllables also have corollary accents in their melodies. For example, the definite articles in the Germanic and Romance languages (the sea, die See, la mer) are heard in the musical upbeats at the beginning of many melodies. The music of cultures whose languages do not contain definite articles, rarely have musical upbeats to their melodies. Note the preference for beginning melodies on the beat in the music of Mussorgsky (Russian) and Dvorak (Czech). A number of other commonalities have been found between the melodic rhythms of a culture and the speech rhythms in its language (Huron and Ollen, 2003; Patel and Daniele, 2003).

### FREQUENCY RANGE OF MELODIC INSTRUMENTS

The womb origin of melody might also explain the range of the most commonly used melodic instruments. The frequency range of melodic instruments in a wide variety of cultures is roughly 200–900 Hz, the same as the frequency range of an adult human female voice. The following instruments have strings tuned to pitches in this range: the West African kora, the Chinese guqin, the Indian sitar, the North American Apaches' tsii'edo'a'tl, and the European violin. The flute may be even more ubiquitous. Fossilized bone flutes have been found that date back more than 30,000 years (Atema, 2004). Many musical instruments have been invented and modified over the years to create the kinds of resonance-enhanced richness that remind us of the human voice.

### CONTINUITY

The underlying beats may also provide another hidden universal characteristic of music: nearly all of the music heard in all cultures is continuous. While speech stops and starts, music rarely presents any other than an unbroken stream of sound. Continuity is key to musical appreciation, attention, and subconscious recognition. The acoustic environment of the womb also provides a constant stream of sound that could provide the foundation of recognition that music builds upon. Even when melodies are presented in phrases that are separated from one another, there is continuity in the underlying pulse and accompanimental patterns. In the fetal environment, the maternal voice comes and goes, but the pulse and meter always remain. There are exceptions to the continuity of music, but the silence is typically brief and the tempo of the pulse usually remains.

### TESTS OF THE PRENATAL ROOTS OF MUSIC

To test whether the elements of music are based upon the sounds of the environment during brain development, I conceptualized two studies that compared the responses of a species to music composed for humans and music composed specifically for that species. These studies were carried out by Dr. Charles Snowdon and colleagues at the University of Wisconsin-Madison. If the concept is correct, it should be possible to create music that would be effective for another species that is based upon the sounds that are present as the brain structures of the limbic system of that species are being formed.

The first study compared the responses of cotton-top tamarin monkeys to four types of music: aggressive human music, calming human music, aggressive tamarin music, and calming tamarin music (Snowdon and Teie, 2010, 2013). In addition to the use of instrumental music that was based on vocalizations of each species, I included in the calming music for the tamarin monkeys a pulse that was equal in pacing to the resting heart rate of an adult monkey (200−220 beats per minute). Since the brain of a monkey is 60% of its adult size at birth I included instrumental representations sounds of the womb in the music for the tamarins. As had been the case in most other tests of the effects of human music on other species, the tamarins were indifferent to the human music (McDermott and Hauser, 2007). The calming tamarin music was effective in calming the monkeys and the arousing music led to increased movement and behavior indicative of anxiety. There was one significant exception to the tamarin's indifference to the human music: the only response that was elicited by the human control music was that they were calmed by the aggressive human heavy metal music that has a pulse of 200 beats per minute. This apparent anomaly supports the proposition that the sonic characteristics of the maternal pulse may have a calming effect when presented in music.

The second study was conducted on cats (Snowdon et al., 2015). Since the brain of a newborn cat is only 1/8 the size of what it will be at 10 weeks, the sounds of the womb were presumed to be not salient for cats. A reward-related sound that is present during the development of the cat's brain is the sound of suckling. The music for cats, therefore, included musical instruments designed to resemble the sound of suckling as it would be heard by a nursing kitten. The data on the effect of species-specific music on cats from this study were even stronger than in the tamarin monkey study.

### PROBABILITY THAT THE FEATURES COMMON TO THE WOMB AND MUSIC ARE COINCIDENTAL

A demonstration of the statistical probability that these parameters are connected in a causal relationship would strongly support the theory of the prenatal roots of music. In order to assess that probability it is necessary to deduce the probability that the similarities between the elements of music and the sounds present in the fetal environment are due to coincidence. The first consideration to be accounted for is the number of variables. How many variable features are there in each element? Below is a brief outline of the variables for each element.

Pulse:

Meter:

• The combinations of the accented beats that comprise meters create an infinite number of possible patterns.

Frequency range of melodic instruments:

• The frequency range of melodic instruments would most likely center on our most sensitive hearing range that is used to produce consonants: from 2−4 kHz. Despite this sensitivity, our melodies are usually in the fairly narrow range of 200 to 800 Hz. (This is noted to refute the common assumption that the most common melodic instruments sound in the frequency range of the treble register because it is easier for people to hear in that range).

The determination of coincidence would also need to include the probability that the combination of the abovelisted variables is coincidental. Finally, it would be necessary to assess the probability that these elements are similar in

### REFERENCES

Atema, J. (2004). Old bone flutes, Pan. J. Br. Flute Soc. 23, 18–23.

not only the music of one culture, but in the music of every culture.

Since it is impossible to provide data on the probabilities that a given sonic element would or would not be present in either music or the fetal environment, it is also impossible to present the possibility of the coincidence of the elements as a statistical probability. However, given the large number of variables and the ubiquity of the commonalities between the sounds of the womb and the music of all cultures, the probability that they are similar by coincidence would seem to be astronomically remote.

### CONCLUSION

The questions of the origins of music presented at the beginning of this article are plausibly answered by the prenatal environment. There appears to be a correlation between the acoustic features of the common elements of music found in diverse and widely separated cultures and the acoustic features of sounds that are present in the womb. The neurological development of the fetus allows for the absorption and retention of those sounds to be implanted as templates of recognition in the brain.

I propose that the acoustic parameters of the sounds in the womb are the same as the parameters of universal characteristics of music. It is possible to match, one-for-one, the sounds of the womb to those elements that can be found in the music of all cultures.

### AUTHOR CONTRIBUTIONS

The author confirms being the sole contributor of this work and approved it for publication.

### FUNDING

No institutions have provided funding for any of the work leading to this submission. All of the research and development of the theory was engaged in privately, without compensation or funding.

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Teie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# What Pinnipeds Have to Say about Human Speech, Music, and the Evolution of Rhythm

Andrea Ravignani 1, 2 \*, W. Tecumseh Fitch3 †, Frederike D. Hanke2 †, Tamara Heinrich2 † , Bettina Hurgitsch4 †, Sonja A. Kotz 5, 6 †, Constance Scharff 7 †, Angela S. Stoeger 3 † and Bart de Boer 1

1 Artificial Intelligence Lab, Vrije Universiteit Brussel, Brussels, Belgium, 2 Sensory and Cognitive Ecology, Institute for Biosciences, University of Rostock, Rostock, Germany, 3 Department of Cognitive Biology, University of Vienna, Vienna, Austria, 4 Chemnitz Zoo, Chemnitz, Germany, 5 Basic and Applied NeuroDynamics Lab, Department of Neuropsychology and Psychopharmacology, Maastricht University, Maastricht, Netherlands, 6 Department of Neuropsychology, Max-Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 7 Department of Animal Behavior, Institute of Biology, Freie Universität Berlin, Berlin, Germany

#### Edited by:

Virginia Penhune, Concordia University, Canada

#### Reviewed by:

Hugo Merchant, Universidad Nacional Autónoma de México, Mexico Aniruddh Patel, Tufts University, USA

#### \*Correspondence:

Andrea Ravignani<EMAIL_ADDRESS>
† These authors have contributed equally to this work.

#### Specialty section:

This article was submitted to Auditory Cognitive Neuroscience, a section of the journal Frontiers in Neuroscience

> Received: 04 March 2016 Accepted: 31 May 2016 Published: 20 June 2016

#### Citation:

Ravignani A, Fitch WT, Hanke FD, Heinrich T, Hurgitsch B, Kotz SA, Scharff C, Stoeger AS and de Boer B (2016) What Pinnipeds Have to Say about Human Speech, Music, and the Evolution of Rhythm. Front. Neurosci. 10:274. doi: 10.3389/fnins.2016.00274 Research on the evolution of human speech and music benefits from hypotheses and data generated in a number of disciplines. The purpose of this article is to illustrate the high relevance of pinniped research for the study of speech, musical rhythm, and their origins, bridging and complementing current research on primates and birds. We briefly discuss speech, vocal learning, and rhythm from an evolutionary and comparative perspective. We review the current state of the art on pinniped communication and behavior relevant to the evolution of human speech and music, showing interesting parallels to hypotheses on rhythmic behavior in early hominids. We suggest future research directions in terms of species to test and empirical data needed.

 They flexibly learn new vocalizations and easily perceive and move to rhythm (Bolton, 1894; Fitch, 2009) 1 . Why do humans show these two traits that have only been described in relatively few other animals? Previous research led to conflicting hypotheses on how evolution has shaped human brains and physiology to produce complex vocalizations (Richman, 1993; Fitch, 2000; Galantucci et al., 2006; Fitch and Jarvis, 2013; Manson et al., 2013). Several contrasting hypotheses also exist on how and why human and other animals' brains can perceive complex rhythmic patterns (Merker et al., 2009; Honing et al., 2012; Merchant and Honing, 2013; Patel and Iversen, 2014; Ravignani et al., 2014a). Crucially, these hypotheses differ on assumptions about social structure, ecological conditions, and audiomotor abilities present in early hominids, also providing discordant predictions on rhythm and vocal learning skills in different living species (for reviews see Ravignani et al., 2013a, 2014a; Iversen, 2016; Wilson and Cook, 2016). An influential hypothesis in the field, the vocal learning beat perception and synchronization hypothesis (Patel, 2006), states that vocal production learning (VPL) is a prerequisite for species to be able to extract a pulse from periodic acoustic

1Rhythm is defined as a "serial pattern of durations marked by a series of events" (McAuley, 2010. pp. 166).

events (like an internal metronome), and use this inferred pulse to synchronize movements to these external events in a predictive and flexible way (rhythmical entrainment). In fact, neural pathways between auditory and motor areas of the brain, which originally evolved for VPL, would also enable precisely timed movements to sounds (Kuypers, 1958, 1973; Jürgens et al., 1982). Only a few species are capable of VPL: that is, to modify existing vocalizations and to imitate novel sounds not belonging to their innate repertoire (Janik and Slater, 2000; Van Parijs et al., 2003). Humans, bats (Boughman, 1998; Knörnschild et al., 2010; Vernes, 2016), elephants (Poole et al., 2005; Stoeger et al., 2012), seals (Ralls et al., 1985), dolphins (Reiss and McCowan, 1993; Favaro et al., 2016), and whales (Foote et al., 2006), together with many bird species (Marler, 1970; Todt, 1975; Marler and Peters, 1977; Scharff and Nottebohm, 1991), have been shown capable of vocal learning (Schusterman, 2008; Petkov and Jarvis, 2012; Nowicki and Searcy, 2014).

Model species can be used to test hypotheses on how our ancestors evolved the neuropsychological prerequisites underpinning speech and music (see also Vernes, 2016). One can either pick model species, which are closely related to humans, and hence should share a specific trait by common ancestry (homology), or species that have a similar socioecology to humans, and hence independently evolved a similar trait by convergent evolution (analogy). If a living animal (i) shares much of its evolutionary history with humans, or (ii) was exposed to environmental conditions and evolutionary pressures similar to early hominids, then commonalities in selected behavioral traits may exist between the two (Fitch, 2010, 2014). This comparative approach is extremely powerful as a way of addressing questions such as (a) how humans acquired complex rhythmic and vocal imitation capacities, (b) why distantly related species but not our closest primate relatives evolved these capacities. Several biological factors may provide an answer to these questions, including brain anatomy, body morphology, social structure, habitat, and ecology. Hence suitable model species to investigate rhythm and VPL in our human lineage should, first and foremost, exhibit rhythm and VPL, and possibly be as close as possible to humans in anatomical, ecological, and evolutionary terms. To test the vocal learning—beat perception and synchronization hypothesis against alternative ones, we suggest below why pinnipeds including vocal and less vocal species—provide an excellent group of model species.

### PINNIPEDS: MORE VOCALLY FLEXIBLE THAN PRIMATES, PHYLOGENETICALLY CLOSER TO HUMANS THAN BIRDS

Traditionally, VPL and rhythmic behavior have been investigated in primates, parrots or songbirds. Monkeys and non-human apes, like chimpanzees, are evolutionarily and cognitively close to humans, but exhibit limited vocal imitation and rhythmic patterning skills (Janik and Slater, 1997; Ravignani et al., 2013a; Repp and Su, 2013; see Gamba et al., 2016, for timing in lemur singing). In contrast, many bird species are excellent at learning to imitatively produce new vocalizations (Petkov and Jarvis, 2012). Moreover, when tested on nonvocal rhythmic tasks requiring precise temporal coordination, birds outperform primates, although direct primate-avian comparisons on identical tasks are lacking at present (Nagasaka et al., 2013; Hoeschele et al., 2015; Benichov et al., 2016; ten Cate et al., 2016). However, the last common ancestor of birds and humans lived about 300 million years ago (Kumar and Hedges, 1998), and birds have evolved a vocal production system (the syrinx) quite different from the human larynx (Fitch, 2010; Elemans et al., 2015). Hence, primates and birds each have only one of the desirable features to understand rhythm and VPL: non-human primates are evolutionary close to humans but exhibit scarce rhythm and VPL capacities, while birds have rhythmic capacities and VPL but are evolutionary distant from humans.

A third taxonomic group, previously overlooked in comparative research on human evolution (cf. Cook et al., 2013; Rouse et al., 2016), may be the solution to this conundrum. Pinnipeds exhibit VPL and rhythmic abilities (**Table 1**), and as mammals they are evolutionary closer to humans than birds: the last common ancestor of humans and pinnipeds lived about 65 MY ago (O'Leary et al., 2013). This clade includes more than 30 species of semiaquatic mammals divided in three families: Phocidae (e.g., harbor and gray seals), Otariidae (e.g., California sea lions and Cape fur seals), and Odobenidae (walruses). Pinniped phylogeny is controversial. However, recent molecular evidence suggests that the first split, separating Phocidae from other pinnipeds, occurred 33 MY ago (Arnason et al., 2006). This relatively old common origin—compare it with the 33 MY between humans and e.g., capuchin monkeys (Glazko and Nei, 2003), has provided ample time to adapt to many different ecological niches and environmental constraints. Accordingly, pinniped species exhibit variation in VPL capacities, social organization, mating systems, and habitats (**Table 1**). These dimensions conveniently have anthropological equivalents, each of them deemed crucial for at least one hypothesis on the evolution of speech and music (Fitch, 2000; Hagen and Bryant, 2003; Patel, 2006; Hagen and Hammerstein, 2009; Merker et al., 2009; Petkov and Jarvis, 2012; Merchant and Honing, 2013; Patel and Iversen, 2014; Ravignani, 2014; Ravignani et al., 2014a,b; for a comparative definition of speech).

Notably, among the pinnipeds, harbor seals (Phoca vitulina) exhibit an excellent trade-off between VPL abilities and phylogenetic proximity to humans: among vocal learners, harbor seals have the closest vocal apparatus to humans (Schneider, 1962; Schneider et al., 1964; Ralls et al., 1985; Fitch, 2000; **Table 1A,B**). A human-raised harbor seal has even learned to imitate some human words and phrases (Ralls et al., 1985; **Table 1C**). So far, harbor seals have not been tested for rhythmic entrainment abilities; however, another pinniped species, the California sea lion (Zalophus californianus) was shown capable of non-vocal audio motor synchronization with precision previously exhibited only by avian species and humans (Cook et al., 2013; Rouse et al., 2016; **Table 1G**). With these few exceptions, pinniped communication, rhythm, and human speech have mostly remained unconnected areas of

TABLE 1 | Features of human speech and music (first column) are related to findings in pinniped biology (second column) to draw comparative conclusions and suggest further research (third column).

research until now. However, a lot of information is available on pinnipeds' natural vocal behavior, making the comparative study of pinniped communication and human speech a field ripe for research. We suggest that pinnipeds are ideal species to understand human speech, rhythm, and complex VPL at different levels (including physiology, behavior, neurobiology, and genetics). Pinnipeds' vocal anatomy, brain evolutionary history, socio-ecology, and broad range of environmental conditions conveniently map to human biology (Schneider, 1962; Ralls et al., 1985; Riedman, 1990; Van Parijs et al., 1999, 2003; Schusterman, 2008; Cook et al., 2013; Sauvé et al., 2015a,b; **Table 1**).

Then, why do humans and harbor seals produce flexible vocalizations? Taking ultimate and proximate causes into account and adopting a comparative approach (**Table 2**), we suggest several strands of empirical research in pinnipeds, which can shed light on the evolution of human rhythmicity.

### FUTURE RESEARCH: WHAT SPECIES TO TEST NEXT, AND IN WHICH TASKS?

### Vocal Production Learning

Pinnipeds produce many types of vocalizations, which can be recorded in air, enabling acoustic data collection with precise individual identification. Research in harbor seals, building on existing evidence on vocal imitation (Ralls et al., 1985), should investigate their ability to learn vocalizations (i) over developmental phases, and (ii) from each other in a social network (Janik and Slater, 2000; Tyack, 2008; **Table 1A–F**). This will reveal how seal vocalizations are imitated and transformed (Fitch, 2015b) similarly to human speech. In parallel, vocal flexibility in Otariids should be investigated across species, testing their ability to imitate new sounds. This will hopefully provide clear support for or against VPL capacities in this pinniped family considered, until now, the least vocally flexible. While performing this research, it will be important to keep an openminded attitude toward vocal learning, as this seems to be a graded ability rather than an all-or-none trait (Petkov and Jarvis, 2012; Fitch, 2015a).

Comparative vocal and brain anatomy in pinnipeds can be fruitful strands of research (**Table 1B,C,F**). The angle of vocal folds with respect to the tracheal air stream is 76◦ (degrees) in harbor seals, while 17.5◦ in sea lions (Schneider et al., 1964). This suggests sea lions have a vocal folds' angle closer to elephants (45◦ ); harbor seals' angle instead is closer to humans (90◦ ) than to sea lions (Herbst et al., 2013). Does this difference in vocal anatomy map to a difference in types of sounds produced or just modalities of sound production?

Neuroanatomy may constitute a fruitful research avenue to understand the mechanisms behind successful entrainment in California sea lions. Although the shape of their brain is similar to that of other carnivores, analyses of brain folding show remarkable differences. In particular, California sea lions have more secondary folds and sulci, and a radically different pattern of folds and fissures than other carnivores such as canids, e.g., dogs, wolves, coyotes, and mustelids e.g., minks (Montie et al., 2009). This suggests evolutionary pressures and potentially similar mechanisms increased the size of the neocortex in sea lions showing an interesting parallel to human evolution. A further open question is how the evolution of different brain structures relates to VPL (Patel, 2014) and social organization across pinniped species.

### Interval Timing and Synchronization

Timing experiments often investigate the attentional and cognitive processes involved in perceiving or estimating single time intervals, either independently or by comparison with a second interval (Grondin, 2010). These experiments have, for instance, shown similarities and differences between humans and other primates in estimating single interval durations in the visual and auditory modality (Merchant et al., 2003; Zarco et al., 2009; Mendez et al., 2011). In pinnipeds, recent data show that a harbor seal and a Cape fur seal (Arctocephalus pusillus) can accurately discriminate time intervals in the visual modality (Heinrich, 2013; **Table 1I**). In contrast, rhythm refers to the structure of multiple

TABLE 2 | The question of why a particular behavioral trait, such as vocal production learning, exists in a species can be answered taking ultimate and proximate causes into account (Tinbergen, 1963).

durational events, i.e., sequences of time intervals. Hence, singleinterval timing research is essential (Merchant and Honing, 2013) though not enough to understand rhythm perception: in fact, perception of one interval influences perception of adjacent intervals (McAuley, 2010). Studying perception, reproduction, and entrainment to isochronous (metronomelike) sequences is the first step when moving from timing to rhythm research. In entrainment experiments, humans and other animals are tested on their ability to synchronize their movements to an external visual or auditory metronomic stimulus. Synchronization can arise spontaneously or be trained by the experimenter. Crucial experimental criteria for successful synchronization are: (i) flexibility, i.e., comparable performance at different tempos, (ii) multimodality i.e., ability to synchronize one's behavior in a sensory modality different from that of the external stimulus, and (iii) predictive rather than reactive behavior, i.e., zero or negative asynchrony, and unperturbed performance when one beat is missing (Patel et al., 2009a,b).

Extending previous entrainment studies in otariids (Cook et al., 2013; Rouse et al., 2016), harbor seals' and walruses' ability to entrain should be tested (**Tables 1G,L**). Successful synchronization in one of these vocal learners (Reichmuth and Casey, 2014) would provide an important data point in support of the VPL—rhythm link (Patel, 2006). Useful out-groups for synchronization experiments could be non-pinniped Canoidea, like dogs, exhibiting almost no VPL (Janik and Slater, 1997; Taylor et al., 2009). Harbor seals' and walruses' inability to synchronize would not refute Patel's hypothesis. However, failure to synchronize would refute alternative hypotheses, postulating individual territorial advertisement or lek displays as crucial factors for the evolution of rhythm (Hagen and Hammerstein, 2009; Ravignani, 2014).

### Natural Isochronous Behavior and Perception of Isochrony

As flexible synchronization requires the ability to represent an isochronous pulse (Iversen and Balasubramaniam, 2016), pinnipeds should be tested on their ability to discriminate between isochronous and non-isochronous temporal patterns. In birds, the ability to recognize isochronicity in acoustic sequences seems to positively correlate with VPL: pigeons perform much worse (Hagmann and Cook, 2010) than other birds capable of VPL, like zebra finches and starlings (Hulse et al., 1984; van der Aa et al., 2015). If this can be generalized, one would analogously expect harbor seals and walruses tested in comparable setups to outperform e.g., California sea lions and Cape fur seals. Finally, pinniped species naturally showing isochronous vocal behavior may be particularly promising to test in order to ascertain how VPL and natural isochronous behavior affect the ability to entrain. While vocalizations in the vocally inflexible Australian and California sea lions can be quite regular, the vocally flexible harbor seals vocalize with much less temporal regularity (Schusterman, 1977; Charrier et al., 2011).

### Meter Perception, Grouping, and Auditory Experience

Meter provides an additional dimension to rhythmic patterns, where individual events in time have different perceptual or acoustic "weights." Meter is defined as hierarchical organization of temporal events (McAuley, 2010). Meter corresponds to hearing events in time as related, forming structured patterns, e.g., the alternation of weak/strong beats in music and stressed/unstressed syllables in speech (Fabb and Halle, 2012). Meter perception can occur in sequences of stimuli that are acoustically identical (Brochard et al., 2003), or instead based on stimuli that alternate in duration, frequency, or amplitude (McAuley, 2010; Toro and Nespor, 2015; Geambasu et al., 2016; Hoeschele and Fitch, 2016).

Humans can perceive a range of metrical patterns but are biased toward specific metrical grouping patterns, partially depending on their native language (Iversen et al., 2008). In particular, a few perceptual laws, such the iambic-trochaic law (de la Mora et al., 2013), may explain most of rhythmic grouping in speech and music (Figure 1 in Supplementary Material). Rats, for instance, exhibit experience-modulated grouping biases: Like humans, they spontaneously group sequences when sounds alternate in pitch, but do not when sounds alternate in duration (de la Mora et al., 2013). However, rats can learn to group sounds of alternating durations: if exposed to short-long sequences, they will show the corresponding iambic bias when tested; if familiarized with long-short, rats will prefer trochaic grouping (Toro and Nespor, 2015).

Meter perception should be investigated across pinnipeds (**Table 1M**). As grouping is influenced by auditory experience, we would expect pinnipeds with a varied conspecific auditory input, like harbor seals, to require little training to discriminate metrical patterns. After probing pinnipeds' predictive timing by having them produce behavioral responses, temporal expectations could be explored by directly tapping into perception. Adapting noninvasive electrophysiology originally developed for humans and non-human primates, one could record event-related potentials corresponding to click sounds repeating at a constant rate, and compare these potentials to those evoked by click trains containing missing clicks or metrically-structured (accented) clicks (Rothermich et al., 2010; Schmidt-Kassow et al., 2011; Schwartze et al., 2011; Honing et al., 2012; Selezneva et al., 2013; Celma-Miralles et al., 2016; Cirelli et al., 2016).

### Percussive Behavior in Harbor Seals

Empirical evidence from human archeology, ethnomusicology and African apes' behavior suggest that percussion may have been the first form of musical expression in our hominid ancestors (Arcadi et al., 1998; Morley, 2003; Fitch, 2009). What was the function of rhythmic drumming in early hominids? A behavioral display in harbor seals may help answer this question: Accompanying vocalizations, harbor seals "drum" on the water, repeatedly slapping their flippers on the sea surface (Riedman, 1990; Wahlberg et al., 2002). Once again, hypotheses on the function of this slapping behavior mimic hypotheses proposed for human drumming (e.g., Kirschner and Tomasello, 2009). Slapping in harbor seals may function as signal in agonistic sexual displays (Riedman, 1990), or as a form of intrasexual competition to attract females (Nikolich, 2015). Another hypothesis regards water drumming as a form of territorial advertisement in agonistic contexts: in fact, during the breeding season, male seals produce slaps in response to other males either intruding a territory, or challenging an intruder (Hayes et al., 2004). Water slapping may hence indirectly play a role in establishing and maintaining dominance hierarchies, similar to chimpanzees' drumming (Arcadi et al., 1998; Ravignani et al., 2013b).

One hypothesis we suggest is that vocal displays and drumming displays may have the same territorial function but be used complementarily. Seals' slaps cover a different frequency band than, and have dramatically different durations from, roars. Slaps last about 0.002 s, contain most frequency between 5 and 20 kHz, and have (in-water) source intensity of 166–199 dB (Wahlberg et al., 2002). In contrast, roars last 2–3 s, are centered at frequencies of 200–300 Hz and have 150 dB intensity (Hayes et al., 2004). How far can each of these sounds travel so that they are still audible by seals? At 200 Hz, seals' hearing threshold is 32 dB (82 dB underwater); the sensitivity is much higher between 5 and 20 kHz, reaching 1–29 dB (60–62 dB in water; Reichmuth et al., 2013). Hence (1) slaps carry much farther than roars, (2) even if a slap and a roar reach a seal with the same sound intensity, a slap will be more conspicuous: slap might be perceived up to 30 times louder than a roar, and (3) slaps could be in principle perceived visually (Nikolich, 2015). Seals' water slaps hence seem to mimic many features of early human's territorial advertisement, which have been hypothesized to underlie the evolution of human musicality (Hagen and Hammerstein, 2009).

Future research should record individuals over time to: (i) analyse the fine-grained temporal structure of series of slaps (Babiszewska et al., 2015); (ii) test whether drumming and its temporal parameters are socially learnt, and if so (iii) compare the social dynamics of two transmitted rhythmic behaviors, across modalities (vocalizations vs. slapping), and (iv) relate waterslapping to similar percussive behaviors present in humans and chimpanzees (Fuhrmann et al., 2014; Whiten, 2015; **Table 1N**). Collection of slapping data will enable to test hypotheses postulating group and mating displays as necessary evolutionary steps toward human musicality (Fitch, 2009; Merker et al., 2009). In fact, if harbor seals' slaps show strong temporal interdependence between individuals, successful entrainment experiments in this species would support the hypothesis that rhythm may have evolved in humans as by-product of temporally-intertwined group displays (Merker et al., 2009).

### CONCLUSIONS

Researchers of human evolution and pinniped communication have been suggesting, unbeknownst to each other, similar hypotheses for the evolution of human speech and music, on the one hand, and pinnipeds' vocal displays and non-vocal communication, on the other hand. Advocating the comparative method and the distinction between proximate and ultimate questions, we have shown how animal research can help formulate and test hypotheses about the evolution of human speech and music. We have briefly reviewed previous findings in pinniped biology, explicitly pointing out their relevance to the human sense of rhythm in music and speech. We have discussed crucial questions that pinniped research should address empirically, possibly using comparable stimuli, tasks, and analysis techniques across species, ultimately shedding light on the origins of rhythmic behaviors in humans.

### AUTHOR CONTRIBUTIONS

Andrea Ravignani wrote the manuscript. All authors provided ideas and edited the manuscript.

### FUNDING

Andrea Ravignani was supported by FWO grant V439315N (to Andrea Ravignani), and European Research Council grant 283435 ABACUS (to Bart de Boer).

### ACKNOWLEDGMENTS

AR is grateful to Peter Cook, Guido Dehnhardt, Maxime Garcia, Alina Gaugg, John Iversen, Vincent Janik, Lars Miersch,

### REFERENCES

Benedikt Niesterok, Ana Rubio Garcia, Ruth Sonnweber, Amanda Stansbury, and Sonja Vernes for helpful discussions, comments, and insights.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fnins. 2016.00274

Rohrmeier, J. A. Hawkins, and I. Cross (Oxford, UK: Oxford University Press), 73–95.

vitulina, roar through playback experiments. Anim. Behav. 67, 1133–1139. doi: 10.1016/j.anbehav.2003.06.019

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Ravignani, Fitch, Hanke, Heinrich, Hurgitsch, Kotz, Scharff, Stoeger and de Boer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Zebra Finches As a Model Species to Understand the Roots of Rhythm

Michelle J. Spierings 1, 2 \* † and Carel ten Cate1, 2 †

*1 Behavioural Biology, Institute Biology Leiden, Leiden University, Leiden, Netherlands, 2 Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands*

Keywords: zebra finches, rhythm per, cognition, song system, vocal learning

### VOCAL TIMING IN ZEBRA FINCHES

Zebra finches are a widely used model species for neurobehavioral research, in particular in relation to song development and auditory processing. Males learn their songs from a tutor. Females don't sing, but do develop learned song preferences. Regardless of the differences, both sexes exchange calls in social interactions. Two fascinating recent studies looked at different aspects of rhythmicity in the production of zebra finch vocalizations (Benichov et al., 2016a; Norton and Scharff, 2016), and together with several studies on the perception of rhythms, they make the zebra finch a promising model species to unravel the roots of rhythm production and perception.

#### Edited by:

*Andrea Ravignani, Vrije Universiteit Brussel, Belgium*

#### Reviewed by:

*Yukiko Kikuchi, Newcastle University, UK Philipp Norton, Free University of Berlin, Germany*

#### \*Correspondence:

*Michelle J. Spierings<EMAIL_ADDRESS>
*† These authors have contributed equally to this work.*

#### Specialty section:

*This article was submitted to Auditory Cognitive Neuroscience, a section of the journal Frontiers in Neuroscience*

> Received: *06 May 2016* Accepted: *08 July 2016* Published: *22 July 2016*

#### Citation:

*Spierings MJ and ten Cate C (2016) Zebra Finches As a Model Species to Understand the Roots of Rhythm. Front. Neurosci. 10:345. doi: 10.3389/fnins.2016.00345*

Norton and Scharff (2016) analyzed the intervals from one note onset to the next one in both isolate and directed zebra finch songs. For each male they were able to derive an isochronous sequence of "time stamps" of which a subset aligned with all note onsets of a male's song. Moreover, these time stamps often also coincided with the transitions between phonetically different gestures within a complex note. This indicates that an isochronous rhythm might underlie zebra finch songs. Benichov et al. (2016a,b) showed that both males and females can dynamically adjust the mutual timing of their calls. Individual birds were housed with a robotic zebra finch that emitted an isochronous call pattern.  The robot was then set to emit "jamming" calls that were produced at the moment when the zebra finch was most likely to respond. All zebra finches adjusted their call pattern to avoid the jamming calls, either by calling earlier, later or both earlier and later. Furthermore, when the robotic finch produced a pattern of alternating single and paired calls, the zebra finches timed their calls differently for the single compared to the paired calls, indicating they apparently detected the alternating pattern of the robot calls and used this to anticipate whether the next call would be single or paired. Interestingly, females performed better than males at these tasks (Benichov et al., 2016a).

Benichov et al. (2016a) next examined the role of the forebrain song system in the timing of calls. The female song system is reduced compared to the male system and lacks, for instance, the largest song nucleus, Area X. However, some nuclei of the song system are present in both sexes, like the RA, a nucleus related to the temporal aspects of zebra finch song learning. Lesioning the RA nucleus in zebra finches made them unable to correctly adjust the timing of their calls, although they were still responsive to the robotic finch. This indicates that for both males and females the RA is actively involved in call synchronization and vocal coordination. Further experiments showed that input to the RA from another forebrain nucleus, the HVC, was necessary to maintain call synchronization (Benichov et al., 2016a). While Norton and Scharff (2016) did not examine the neural basis of the isochronous patterns they observed in male songs, they also suggest that it might originate from the activation pattern of HVC neurons firing to the RA. These HVCRA neurons fire in a rhythmic, clock-like pattern (Long and Fee, 2008). However, as the rhythms observed by Norton and Scharff are 3 to 10 times slower than the firing of these HVC neurons, they propose that additional mechanisms must operate to translate the clocklike firing into the higher complexity observed in the songs.

**64**

Whether animals can perceive beat and rhythmic patterns is a prominent question in relation to understanding the evolution of human musicality (Patel, 2006, 2014; Fitch, 2013; Hoeschele et al., 2015; Honing et al., 2015) and Benichov et al. (2016a,b) suggest that the link between the neural system involved in vocal learning and call synchronization provides the relation between beat perception and auditory-motor coordination as shown in a number of animal species. So, how do the above findings on the presence of rhythms in vocal production in zebra finches relate to studies that addressed the perception of rhythmic auditory patterns?

### RECOGNIZING REGULARITY

Rhythm can be defined as a regular repeated pattern. In its simplest form it is an isochronous series of pulses, like the one produced by the robotic finch. More complicated rhythms can be created by repeating a heterochronous pattern, for example the repetition of single and double pulses as used in Benichov et al. (2016a). Humans are skilled in perceiving various rhythms. We can easily detect whether a pulse or beat pattern is regular or irregular by integrating temporal information over a series of auditory events (e.g., Geiser et al., 2014). We thus have the cognitive ability to abstract a general, global, pattern from a string of sounds, enabling us to classify patterns as regular or not. However, the question whether or to what extent non-human animals are also able to integrate temporal information over a longer series of sounds to classify strings as being regular is still open. A telling example is a study by Hagmann and Cook (2010) that showed that pigeons were unable to learn to discriminate between an isochronous and an irregular pulse pattern. Pigeons are vocal non-learners and this might be the reason for their inability, as it has been suggested that vocal learning and vocal non-learning species might differ in this respect (Patel et al., 2009; Schachner et al., 2009; see also ten Cate et al. (2016) for a review on this relationship for birds). The rhythm perception by zebra finches in the study by Benichov et al. seems to support this view, as they show that the (vocal learning) zebra finches extracted the regularity of the call pattern and used this to time their calling. However, when we combine these findings with several other recent studies on zebra finch perception of regularity the picture becomes more complex.

Nagel et al. (2010) trained female zebra finches to discriminate between two different songs and showed that the females maintained the discrimination over a range of tempo changes. The songs were still categorized correctly up to a 25% speed increase or decrease. These results might indicate rhythm generalization by zebra finches. However, Nagel et al.'s conclusion was that zebra finches maintained the discrimination by attending to the spectral envelope of the songs. Attending to the sequence of local spectral features, rather than any timing pattern may have enabled the discrimination. Whether zebra finches do attend to regularity in the timing of songs was examined by Lampen et al. (2014). They compared ZENK expression in response to playback of rhythmic zebra finch songs, i.e., where all songs in a string had identical inter-element intervals, with the expression in response to arrhythmic songs, i.e., a string of songs in which inter-element intervals vary. Arrhythmic songs resulted in stronger ZENK expression in the caudomedial nidopallium (NCM), the caudomedial mesopallium (CMM), and the nucleus taeniae (Tn). This increased activity in auditory areas of the zebra finch brain might be related to the finding by Benichov et al. (2016a) as, similar to their study, the repeated pattern in the regular song may have initiated predictive timing of the next song rendition, which would be lacking with the arrhythmic song.

### REGULARITY OR INTERVAL DETECTION?

The above mentioned studies may indicate that zebra finches perceive "regularity" as such. However, as also noticed by Benichov et al. (2016b) this need not be the case. The various findings may arise because repeated events with a fixed interval may give rise to a prediction for a next interval of the same absolute duration. So, when the birds respond to the robotic finch they can do so by attending to, and learning about, the absolute interval between successive robot calls, or by detecting other local contiguities of events (Benichov et al., 2016b), without having formed some concept of "regularity." The same accounts for the study by Lampen et al. (2014), in which the zebra finches could also have responded to identical consecutive intervals in a sound string.

If zebra finches can perceive regularity as such, one would expect that they are not only able to distinguish a regular from an irregular string, but also to transfer this distinction to strings with modified tempos. This has been tested in experiments in which van der Aa et al. (2015) trained zebra finches to discriminate between a set of regular, isochronous pulse strings and a set of irregular pulse strings. The irregularity in these strings was created by varying the duration of inter-pulse-intervals within a string. As expected from the studies discussed above, zebra finches of both sexes could learn to discriminate these strings. But this discrimination broke down when the zebra finches were tested with probe strings with novel tempo transformations. The birds seemed to distinguish and discriminate the different strings based on their specific inter-pulse-interval durations, suggesting that the zebra finches focused on local features, without attending to or learning about the global pattern of regularity-irregularity of the strings (van der Aa et al., 2015).

Another recent experiment on zebra finches used isochronous pulse strings with pulses of two types. These were present in a ratio of 1:3, with the rare type raised in both frequency and amplitude compared to the other (ten Cate et al., 2016). This variation was used to create a string with a fixed number of low tones between two high ones, creating a regular beat pattern, and a string with different numbers of low tones in each interval, making the beat pattern irregular. Again, the zebra finches discriminated these strings. They were next tested with strings in which the location of the beat within the strings or the duration of pulses and inter-pulse-intervals was changed. This revealed that here also, the zebra finches seemed to use different local features, like the inter-beat- or inter-pulse-intervals to distinguish the strings. However, some birds seemed to combine a sensitivity to such local features with one for the more global regularity (ten Cate et al., 2016). Nevertheless, the behavioral experiments so far do not indicate that zebra finches perceive the global pattern of regularity as such. We should therefore be cautious with concluding that the ability of zebra finches (and other non-human species) to distinguish regular from irregular sound patterns is similar to the ability of humans to detect rhythm. However, there may be a continuum among species ranging from those not being able to discriminate regular from irregular sounds up those able of beat detection in more complex rhythms (ten Cate et al., 2016).

### CONCLUSION AND OUTLOOK

The various studies discussed above show that zebra finches are very good at detecting fixed interval durations and can use preceding intervals to predict the next one in a string of sounds. This matches their ability to call and to produce songs with a fixed rhythmic periodicity. Furthermore, specific nuclei of the zebra finch forebrain song system (HVC, RA, CMM, and NCM) seem

### REFERENCES

involved in producing and detecting rhythmicity. However, the results also call for further behavioral and neural studies on the links between perception and production of rhythmic patterns in the zebra finch. Are receivers sensitive to the rhythms underlying songs? And which brain areas are involved in the discrimination of the rhythmic patterns in the experiments of van der Aa et al. (2015) and ten Cate et al. (2016)? Are these perceptual abilities and also the production of the song rhythms observed by Norton and Scharff (2016) affected by interfering with HVC and RA? The zebra finch has proven to be an excellent model species, and is very suitable for addressing these questions. However, we also need comparative studies on other species to understand the types of temporal patterns that birds can detect, how they do so and how this is related to vocal learning (see also Benichov et al., 2016b). Ultimately, this may also shed light on the building blocks from which our human ability for rhythm perception and beat entrainment may have evolved.

### FUNDING

This work was supported by NWO-GW, grant no. 360.70.452.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Spierings and ten Cate. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Finding the Beat: From Socially Coordinated Vocalizations in Songbirds to Rhythmic Entrainment in Humans

#### Jonathan I. Benichov 1 \*, Eitan Globerson2, 3 and Ofer Tchernichovski 1

*1 Department of Psychology, Hunter College, City University of New York, New York, NY, USA, 2 Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel, 3 Jerusalem Academy of Music and Dance, Jerusalem, Israel*

Humans and oscine songbirds share the rare capacity for vocal learning. Songbirds have the ability to acquire songs and calls of various rhythms through imitation. In several species, birds can even coordinate the timing of their vocalizations with other individuals in duets that are synchronized with millisecond-accuracy. It is not known, however, if songbirds can perceive rhythms holistically nor if they are capable of spontaneous entrainment to complex rhythms, in a manner similar to humans. Here we review emerging evidence from studies of rhythm generation and vocal coordination across songbirds and humans. In particular, recently developed experimental methods have revealed neural mechanisms underlying the temporal structure of song and have allowed us to test birds' abilities to predict the timing of rhythmic social signals. Surprisingly, zebra finches can readily learn to anticipate the calls of a "vocal robot" partner and alter the timing of their answers to avoid jamming, even in reference to complex rhythmic patterns. This capacity resembles, to some extent, human predictive motor response to an external beat. In songbirds, this is driven, at least in part, by the forebrain song system, which controls song timing and is essential for vocal learning. Building upon previous evidence for spontaneous entrainment in human and non-human vocal learners, we propose a comparative framework for future studies aimed at identifying shared mechanism of rhythm production and perception across songbirds and humans.

Edited by:

*Andrea Ravignani, Vrije Universiteit Brussel, Belgium*

#### Reviewed by:

*Manfred Hartbauer, Karl-Franzens University Graz, Austria Michelle Spierings, Leiden University, Netherlands*

#### \*Correspondence:

*Jonathan I. Benichov<EMAIL_ADDRESS>
Received: *07 March 2016* Accepted: *17 May 2016* Published: *06 June 2016*

#### Citation:

*Benichov JI, Globerson E and Tchernichovski O (2016) Finding the Beat: From Socially Coordinated Vocalizations in Songbirds to Rhythmic Entrainment in Humans. Front. Hum. Neurosci. 10:255. doi: 10.3389/fnhum.2016.00255* Keywords: songbird vocalizations, zebra finch, social coordination, rhythm, vocal learning, predictive timing, entrainment, rhythm perception

Almost all animals behave in reference to physical and biological rhythms. From the entrainment of a cricket's circadian cycles, to a sandpiper's repeated chasing and retreating from the waves on a shoreline, rhythms, and synchronization are ubiquitous in animal behavior (Strogatz, 2003). Animals do not only adapt to rhythms, but they can also generate coordinated rhythmic patterns, as in the synchronous flashing of fireflies or the antiphonal calling of marmosets (Moiseff and Copeland, 1995; Takahashi et al., 2013). Although rhythms, entrainment, and coordination appear to be widespread, some highly intelligent animals, such as dogs and apes, appear limited in their ability to spontaneously synchronize their actions to a given beat (Merker, 2000; Fitch, 2011), whereas most humans can dance and can synchronize their movements to a broad range of beats with ease. What is it that makes entrainment so easy for a few animal species (Large and Gray, 2015; Wilson and Cook, 2016) including humans, and difficult or impossible for others?

Many animals communicate by exchanging rhythmic calls. Such rhythms might simply arrise from stereotyped back and forth responses to individual stimuli (**Figure 1A**). Alternatively animals might respond to sequences of events (**Figure 1B**) or to temporal pattens (**Figure 1C**), that is, to the overall periodicity of events. In the case of sequences, one may ask if the animal has learned and responded to a simple or a complex string of contiguous events (**Figure 1B**). In the case of rhythm learning, the experimental question is whether the animal is capable of anticipating the timing of events, which may be either equally spaced in time (i.e., isochrounous events, **Figure 1C**, top) or complex(i.e., hierarchically organized events corresponding to a musical meter, **Figure 1C**, bottom).

Here we review emerging evidence from studies of rhythm generation and vocal coordination across songbirds and humans. We start with a brief review of rhythm learning assessment in human subjects, and present the difficulties in using comparable approaches in animal studies of rhythm learning. We then discuss recent approaches to studying how songbirds can coordinate their vocalization in reference to an external beat.

### CHARACTERISTICS OF RHYTHM ENTRAINMENT IN HUMANS

In humans, contrary to many other species, rhythmic entrainment is a universal feature of behavior, observed from a very early age (Fraisse, 1966). Typically, when human subjects are asked to synchronize their movement to a beat, they tend to anticipate it. That is, they tend to act just prior to the onset of the beat, an effect called negative asynchrony (**Figure 1C**, top). Negative asynchrony can be observed after just a few (2–3) introductory beats and typically precedes the stimulus by tens of milliseconds (Fraisse, 1966). This effect can be observed over a fairly broad range of inter-stimulus intervals (ISIs), between 100 and 1800 ms. The lower ISI bound is determined by motor constraints, while the higher bound is believed to be our limited ability to detect periodicity beyond certain tempi (e.g., due to memory and attention constraints). Above the 100–1800 ms range, negative asynchrony partly gives way to positive asynchrony, which reflects responsive, rather than predictive synchronization to the beat (Fraisse, 1982). Another typical human trait in beat perception is the tendency to create a hierarchy of beats, commonly termed meter (**Figure 1C**, bottom). Grouping of beats is also typical of human motor entrainment to a beat. When moving to music, humans tend to perceive levels of hierarchy beyond the basic beat and synchronize their movement to these groups of beats (Palmer and Krumhansl, 1990).

### EVALUATING RHYTHM LEARNING IN NON-HUMAN ANIMALS

When reviewing animal studies of rhythm learning we will broadly consider cases where animals can learn to adjust their behavior with respect to a given rhythm. The choice of

behavioral indicators of rhythmic perception, however, is nontrivial. The basic supposition underlying behavioral paradigms is that perception drives behavior, and, in some cases, is modulated by behavior. In human studies, one can affect behavior by directly instructing subjects to respond to perception with certain informative actions. A non-human animal, however, will respond to a stimulus only if it corresponds to a meaningful event according to some species-typical standards. Lack of response can reflect perceptual or behavioral limitations, but also the lack of motivation to respond. Therefore, in testing animal rhythm perception, it is critical to find auditory stimuli that are salient enough for the animal to respond in an informative manner. In cases where it is possible to elicit reliable responses, studies typically focus on responses as individual events, rather than ongoing patterns.

Entrainment to rhythms can be tested in many presumably reflexive responses which may exhibit the signatures of rhythm perception or recognition of a beat (**Figure 1C**). With behaviors that appear to be periodic, this can be tested simply by shifting the phase of a repeated stimulus or by observing the persistence of the periodic behavior after the removal of the entraining rhythmic stimuli (**Figure 1C**). Such manipulations are, in fact, standard when studying circadian rhythms in animals (Panda, 2002), but rare in animal communication studies. Singing behavior in oscine songbirds is one of the most studied systems of communication. Birdsong is learned, complex, and often highly rhythmic. Remarkably, some songbird species can even coordinate their songs during duets in which they alternate song syllables with millisecond accuracy (Yoshida and Okanoya, 2005; Fortune et al., 2011; Templeton et al., 2013; Rivera-Cáceres, 2015). Inspired by this rich behavior, several recent studies have involved manipulation of rhythmic stimuli to examine rhythm perception and entrainment in songbirds (Lampen et al., 2014; van der Aa et al., 2015; Benichov et al., 2016).

### VOCAL LEARNING AND COORDINATION IN SONGBIRDS

There are about 4000 species of oscine songbirds, many of which produce songs, which are learned, culturally transmitted behaviors (Brenowitz and Beecher, 2005). Songs are extremely diverse in their spectro-temporal features, complexity, and usage across species (Beecher and Brenowitz, 2005). A European nightingale male, for example, typically learns hundreds of different songs, and sings them in an enormously complex succession. A male zebra finch, on the other extreme, typically learns only a single song motif during development. Within those species-specific constraints, each individual bird can be recognized by its unique song, which is often partly learned through imitation, and partially improvised. Interestingly, even the songs of birds raised in complete isolation possess individual rhythm signatures (Fehér et al., 2009).

### The Forebrain Song System Is a Generator of Complex Learned Rhythms

The neuronal mechanisms of song learning and production have been studied in great detail (Brainard and Doupe, 2002; Nottebohm, 2005). It appears that song patterns (Amador et al., 2013) originate in a highly localized brain center, nucleus HVC (used as proper name), which is located in the bird's posterior forebrain (Nottebohm, 2005). Premotor HVC neurons, which project downstream to primary motor centers, are active during singing, and their spikes are extremely sparse and accurate (Kozhevnikov and Fee, 2007). For example, the zebra finch song is composed of a repeated sequence e.g., ABCD, ABCD. . .where each letter represents a syllable type and the repeated unit [ABCD] is called a motif. Each premotor HVC neuron produces only a single short burst of action potentials during a motif, "ticking" at a specific "moment" (e.g., in the middle of syllable C). Collectively, the ticks of these neurons span the entire duration of the song motif and cooling HVC while the bird sings, results in the slowing of the song, with an almost perfectly uniform reduction in tempo across its duration (Long and Fee, 2008). This result suggests that nucleus HVC is the principle generator of song structure. In a recent study (Okubo et al., 2015), the activity of HVC neurons was tracked during developmental song learning. Interestingly, during early development, HVC neurons generate much faster rhythms, often time-locked to a single prototype syllable, which the bird produces in rapid succession (Tchernichovski et al., 2001; Aronov et al., 2008). The prototype syllable then gradually differentiates into several mature syllable types. For example, a chain of prototype syllables XXXX may transform into XX′XX′ , and finally into ABAB. As this differentiation takes place, HVC neurons double their ticking period, such that they gradually shift from bursting once per syllable, to bursting once every other syllable (on either A or B), until eventually, HVC neurons spike only once per song motif (e.g., ABCD. . . ).

Is the emergence of rhythmic patterns simply mirroring the process of learning to imitate sequences of syllable types? Alternatively, are rhythms the primary skeleton of song production and perception? We do not know. The song system could be either a sequence generator that appears to be rhythmic or a developing rhythm generator, where HVC neurons are, in effect, entrained by the auditory memory of perceived rhythms. If the latter is correct, then through the capacity of song learning, songbirds are endowed with neuronal mechanisms that are specialized for acquiring rhythms. Interestingly, nuclei in the zebra finch auditory association cortex, which are known to be involved in song recognition, are highly sensitive to rhythmic song patterns (Lampen et al., 2014). The authors presented birds with modified songs, where the sequential order of song elements remained unchanged, but song rhythm was perturbed by randomly varying inter-syllable intervals (arrhythmic songs). Hearing arrhythmic songs strongly increased activity in auditory brain areas compared to rhythmically natural songs, supporting the notion that rhythmic structure is a salient feature of birdsong, both for males and non-singing females.

Songbirds are, perhaps, a rare example of animals in which predictive auditory-motor synchronization has evolved. If song learning is indeed a neural entrainment of HVC to memories of perceived rhythms, duet singing could be interpreted as real-time coupling of song rhythms between two birds. For example, in the plain tailed wren, both females and males sing. They learn and perform impressive duets, alternating song syllables in perfect synchrony as if one bird were singing (Rivera-Cáceres, 2015). Notably, premotor HVC neurons are sensitive to the intervals of the dueting partner (Fortune et al., 2011). In sum, the vocal learning capacities of songbirds enable them to create highly complex song patterns, and employ them in social communication, but we don't know if these patterns are primarily perceived and produced as sequences (song syntax), as rhythms (temporal structures), or perhaps as both.

There are few conclusive studies of entrainment to rhythms in non-human animals, most famously in the form of "dancing" in parrots (Patel et al., 2009; Schachner et al., 2009; Hasegawa et al., 2011; Laland et al., 2016). As noted earlier, birdsong is often highly rhythmic, and the song system can be thought of as a sophisticated generator of learned rhythmic behavior. However, once learned, song rhythms become highly stereotyped and difficult to manipulate. In contrast, it is much easier to assess rhythmic vocal abilities when birds are exchanging calls. Zebra finches, for example, rapidly exchange innate short calls and coordinate the timing of their short calls in a pair-specific manner while in a group of calling birds (Elie et al., 2010; Anisimov et al., 2014; Ter Maat et al., 2014). Recently, the vocal coordination capacity of zebra finches has been tested under controlled conditions, in terms that potentially allow for direct comparison to human rhythmic entrainment studies. These experiments showed that zebra finches can coordinate the timing of simple unlearned calls with an imposed beat in a manner that is predictive (Benichov et al., 2016).

In an initial task, individual birds were presented with equally spaced (isochronous) calls (ICs) from a vocal robot (**Figure 2A**) and answered the robot calls with stereotyped latencies. The robot then generated pairs of calls, with intervals that matched the bird's typical response time, thereby maximizing the likelihood of jamming (**Figure 2A**, bottom). Within seconds, birds learned to alter the timing of their responses to avoid jamming (**Figure 2B**). We showed that timing adjustments were predictive, that is, birds anticipated the jamming and shifted timing accordingly (**Figure 2C**). This was verified with "catch" trials, or occasional cycles in which birds hear a single call within a session consisting primarily of jamming call pairs. Further, like humans anticipating a beat, birds typically adjusted their call timing after hearing only a few cycles of the pattern.

Exchanges of calls with the vocal robot typically take the form of antiphonal duets, as opposed to in-phase synchrony. Jamming avoidance can then be thought of as a mechanism for maintaining antiphony. In comparison to human beat perception, call anticipation underlying jamming avoidance may be analogous to the expectation of a beat that underlies temporal shifts in syncopated rhythms (Fitch and Rosenfeld, 2007; Velasco and Large, 2011; Nozaradan et al., 2016). In both cases, events do not occur on the beat, but rather, they are shifted relative to the expectation of the beat. In music this is employed and perceived as accenting, whereas in zebra finches, this anticipation appears to guide antiphonal coordination. These results make sense from an ecological perspective given that zebra finches typically exchange thousands of short calls daily, and their colonies tend to be dense and busy acoustic environments (Elie et al., 2011).

### A COMPARATIVE APPROACH FOR STUDYING BEHAVIORAL MECHANISMS OF RHYTHM LEARNING

Jamming avoidance has been thoroughly studied in several species of weakly-electric fishes (Bullock et al., 1972; Heiligenberg et al., 1996; Zupanc and Bullock, 2006) and frogs (Zelick and

FIGURE 2 | Vocal Robot and jamming avoidance (From Benichov et al., 2016). (A) A bird interacts with isochronous calls (ICs) generated by a vocal robot at rate of 1 Hz. The bird's stereotyped response latencies are used to determine a window of maximum jamming probability (yellow). (B) A bird's responses (blue) across 1000 ms robot IC cycles (gray) and responses (red) across a subsequent session containing jamming robot calls (yellow). The bird shifts its response probability distribution to avoid jamming. (C) Cumulative response distributions across 12 birds, aligned to their window of maximum jamming probability (yellow), for ICs (blue), and for jamming catch trials (green) that contain only a single robot call.

Narins, 1982, 1985). These animals minimize signal overlap with their neighbors by adjusting their intrinsic pacemaker intervals, cycle-by-cycle (Zelick, 1986). Generalized phase resetting and shifting mechanisms constitute responsive forms of coordination. For example, phase adjustment mechanisms can explain how the coqui frog can avoid jamming by preferably calling during brief periods of silence (Zelick and Narins, 1985). Are these animals learning to synchronize their signals (i.e., to cooperate)? Can synchrony arise as an epiphenomenon of competitive interactions (i.e., by suppression)? In the case of chorusing Kaydid bush crickets, females prefer the "leader" male that starts to signal just prior to his competitors, in a manner that resembles negative asynchrony (Greenfield and Roizen, 1993; Fertschai et al., 2007; Hartbauer et al., 2014). In this case, sexual selection for competitive inhibitory mechanisms, which are primarily responsive, may account for the apparent synchrony of the chorus, without the need for prediction.

In zebra finches, vocal robot experiments have shown that birds predictively adjust the timing of their calls when presented with complex rhythms (Benichov et al., 2016). Beyond shifting call timing for repeated jamming call pairs, zebra finches also make anticipatory adjustments for alternating jamming and non-jamming cycles. Birds appear to predict the pattern and reduce response latencies specifically for cycles in which jamming calls occur. These non-generalized (i.e., context-sensitive) shifts in response latencies cannot be explained by responsive mechanisms alone. Rather, they would require mechanisms that can operate on longer time scales (e.g., sequences) or multiple temporally hierarchical levels (e.g., grouping of beats). To our knowledge, such context-sensitive plasticity has not been observed in signaling insects, electric fish, or frogs.

Despite the impressive context-sensitive plasticity in songbird call timing, there is no conclusive evidence that they can perceive rhythms holistically, as humans do. The human ability to perceive rhythms and exhibit spontaneous sensorimotor entrainment has certain hallmarks: it is predictive, occurs across multiple hierarchical timescales, and exhibits predictive negative asynchrony enabled by endogenous representation of an isochronous beat (Semjen et al., 1998; Merker et al., 2009; Nozaradan et al., 2016). It also occurs within a specific range of tempi (Fraisse, 1982). These features can provide a starting point for comparative studies. Along these lines, van der Aa et al. tested rhythm perception in songbirds, and found that zebra finches could not generalize a distinction between isochronous and irregular beats across tempi, namely, they failed to categorize rhythms based on their common global temporal patterns (van der Aa et al., 2015). Humans, in contrast, can easily perform such tasks without any prior training regardless of cultural background (Merker et al., 2009). These results suggest that songbirds attend to local timing events in a sequence but not to global rhythm patterns.

A "sequence-based" explanation could potentially account for predicative call timing plasticity (Benichov et al., 2016). In this scenario birds detect local contiguities of events and adjust their call timing according to a rule of succession. For example, a bird might learn to answer more quickly after hearing a long interval and more slowly after hearing a short interval (**Figure 1B**). Even though zebra finches attend to local acoustic patterns during passive listening, it remains possible that they can synchronize their calls to a given beat in the context of vocal interactions. Indeed, preliminary evidence may suggest a rhythm entrainment mechanism: when zebra finches interact with a vocal robot, a surprising proportion of calls occur just before the next anticipated robot call, as in negative asynchrony or anticipatory "leading" (**Figure 2C**, secondary peak in IC responses). To further test if call timing reflects predictive entrainment to the previously heard robot rhythm, we are currently analyzing persistent call patterns produced by birds after a robot call pattern has been terminated (**Figure 1C**).

### A COMPARATIVE APPROACH FOR STUDYING BRAIN MECHANISMS OF RHYTHM LEARNING

MEG and EEG studies in humans have shown neural entrainment to an external beat (Honing et al., 2014; Doelling and Poeppel, 2015; Nozaradan et al., 2016). No similar phenomenon has been reported in non-human animals that exhibit spontaneous rhythm synchronization or in songbirds. The lack of evidence in songbirds studies might mirror technical difficulties: As discussed earlier, the forebrain song system is a highly specialized vocal learning network. However, song learning proceeds over weeks, and is difficult to manipulate from moment to moment. The vocal robot approach for studying rhythm adaptation, and possibly entrainment of calls, could facilitate such comparative experiments.

Recent studies have identified zebra finch brain areas that drive call timing and interestingly, the forebrain song system appears to play a major role. The first evidence for song system involvement came from electrophysiological studies, showing the final premotor output nucleus, RA (robust nucleus of the archopallium), is active during the exchange of unlearned short calls (Ter Maat et al., 2014). These findings were surprising given that birds can exchange such calls even after the output of the forebrain song system has been blocked (Simpson and Vicario, 1990; Aronov et al., 2008). However, performing jamming avoidance experiments while the song system is lesioned or blocked results in complete loss of a bird's ability to synchronize its calls with a robot partner (Benichov et al., 2016). While birds remain responsive to the robot calls, their latencies become significantly less stereotyped. This was accompanied by the dramatic loss of the ability to avoid jamming. The precise timing of call coordination, therefore, relies on forebrain circuits that also underlie song learning.

What could this mean? Interestingly, female zebra finches, who do not sing, are extremely good at avoiding jamming.  Could the female "song system" be involved in vocal coordination? The female zebra finch forebrain vocal nuclei are not well developed (Nottebohm and Arnold, 1976; Wade and Arnold, 2004), yet blocking nucleus RA disrupted call timing and jamming avoidance, as it did in males. Therefore, the female song system, which was assumed to be vestigial, functions in call coordination and is perhaps more highly specialized for the task than the male's forebrain vocal pathway. Together, findings suggest that the song system involvement in the coordination of unlearned calls reflects the interplay between sensory prediction and motor control. Consequently, blocking the cortical output of the song production pathway results in the temporal uncoupling of the birds' calls from the robot's, as measured by a loss of response precision and predictive timing adjustments. This occurred without affecting the birds' tendency to respond to robot calls. As the search for the neural mechanisms of call coordination narrows down, it should be possible to test if single neurons can be entrained to an imposed beat in songbirds, and to compare the results directly to human studies of neuronal entrainment.

In comparison to humans, the behavioral results obtained after blocking the song system may in some ways be analogous to the rhythm deficits seen in some human subjects who have difficulty synchronizing to an external beat (Amos, 2013) or have been identified as "beat deaf " (Phillips-Silver et al., 2011). Understanding the roles of sensorimotor networks underlying temporal deficits in songbirds may provide insights for related human research. At this point, it is too early to judge the extent to which the control of adaptive call timing is localized to the song system. Other brain areas, particularly, the descending auditory pathway (Mello et al., 1998), which surrounds the song system,

### REFERENCES

is likely to be involved as well. This would be consistent with reports of top-down modulation of auditory processing in human subjects (Tervaniemi et al., 2009). However, since the song system has the capacity to generate and perhaps entrain to song rhythms, an extension of this capacity to call timing adjustments would be a reasonable explanation for the anatomical convergence of the two. In sum, it should now be possible to test if neuronal activity in any of the forebrain song nuclei can be entrained to rhythms produced by a vocal robot in behaving birds. If successful, such experiments should allow for direct comparisons to human rhythm learning experiments, both at neuronal and behavioral levels.

### AUTHOR CONTRIBUTIONS

All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.

### FUNDING