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. Author manuscript; available in PMC: 2017 Feb 8.
Published in final edited form as: Curr Biol. 2016 Jan 7;26(3):309–318. doi: 10.1016/j.cub.2015.12.037

The Forebrain Song System Mediates Predictive Call Timing in Female and Male Zebra Finches

Jonathan I Benichov 1,2,*, Sam E Benezra 3,4, Daniela Vallentin 3,4, Eitan Globerson 5,6, Michael A Long 3,4, Ofer Tchernichovski 1
PMCID: PMC4747672  NIHMSID: NIHMS749923  PMID: 26774786

SUMMARY

The dichotomy between vocal learners and non-learners is a fundamental distinction in the study of animal communication. Male zebra finches (Taeniopygia guttata) are vocal learners that acquire a song resembling their tutors’, whereas females can only produce innate calls. The acoustic structure of short calls, produced by both males and females, is not learned. However, these calls can be precisely coordinated across individuals. To examine how birds learn to synchronize their calls, we developed a vocal robot that exchanges calls with a partner bird. Because birds answer the robot with stereotyped latencies, we could program it to disrupt each bird’s responses by producing calls that are likely to coincide with the bird’s. Within minutes, the birds learned to avoid this disruptive masking (jamming) by adjusting the timing of their responses. Notably, females exhibited greater adaptive timing plasticity than males. Further, when challenged with complex rhythms containing jamming elements, birds dynamically adjusted the timing of their calls in anticipation of jamming. Blocking the song system cortical output dramatically reduced the precision of birds’ response timing and abolished their ability to avoid jamming. Surprisingly, we observed this effect in both males and females, indicating that the female song system is functional rather than vestigial. We suggest that descending forebrain projections, including the song-production pathway, function as a general-purpose sensorimotor communication system. In the case of calls, it enables plasticity in vocal timing to facilitate social interactions, whereas in the case of songs, plasticity extends to developmental changes in vocal structure.

INTRODUCTION

The acoustic structures of most animal vocalizations are not learned. The ability to match vocal sounds to sensory templates is rare, although recent studies show evidence for vocal learning in a growing number of species [1-3]. Vocal coordination is much more common, having been recognized in many species that are vocal non-learners such as cicadas [4], frogs [5], and marmosets [6]. Here we investigate the hypothesis that vocal coordination is mechanistically, and perhaps evolutionarily [7,8], linked to vocal learning.

We examine call coordination in zebra finches, taking advantage of their sexual dimorphism. Males are vocal learners that acquire their songs by imitation, but females are vocal non-learners that cannot sing and produce only innate calls [9,10]. Short affiliative contact calls (‘tets’ and ‘stacks’) are the most frequently produced vocalizations among both sexes [9,11]. Although the forebrain song system is not required for producing short calls [12] or responding to them [10], birds appear to show plasticity in the timing of their calls. As in many social species that are vocal non-learners, the temporal patterns of calls produced by a group of zebra finches can be highly structured [13,14] which may reflect social bonds [15-17], reproductive state[18], and social hierarchy [19,20].

To test how male and female zebra finches learn to synchronize their calls, we presented them with a vocal robot that we initially programed to produce calls in a simple isochronous pattern. This allowed the bird to exchange back-and-forth (antiphonal) calls with the robot. We then programmed the robot to produce call patterns designed to disruptively interfere with this communication channel (Movie S1), prompting the birds to adjust the timing of their responses. Challenging birds with more complex call patterns allowed us to further test for a capacity to dynamically adjust call timing and predictively avoid jamming by calling in patterns that conform to the presented rhythm. Finally, we tested if the forebrain song system, which is thought to be dedicated to vocal learning, is required for the control and for the predictive adjustment of call timing. We compared the effects of blocking or inactivating the song system on vocal timing plasticity between males and females. Results prompt a reevaluation of the context in which forebrain mechanisms enable vocal plasticity.

RESULTS

Call Interactions

While tracking the development of call interactions between a newly formed pair of birds, we observed that, initially, only a small proportion of calls were answered. Within a few days, however, tightly synchronized vocal coordination [14] emerged, characterized by precise antiphonal calling and higher acoustic stereotypy (Figure 1A). To examine how birds learn to synchronize their calls, we developed a ‘vocal robot’ system [19] that can exchange calls with a bird [20], in modes that are either predictable or adaptive (Figure 1B-C and Movie S1). Exposing birds to a vocal robot that produces isochronous calls at a rate of 1Hz (ICs) induced prompt engagement, with birds answering 34±3.7% of ICs during a 10-minute session (means ± s.e.m. hereafter, n=7 males, 7 females, Figures 1B and S1). These rates are comparable to those of established pairs within social groups [16]. Response latencies varied across birds (medians ranging between 249-466ms), but were fairly stereotyped for each bird, with 50% of answers occurring within an interval of 249±23ms. We observed no gender effect on answer latency or stereotypy (n=7 males & 7 females).

Figure 1. Call exchanges in a live pair and responses to the vocal robot.

Figure 1

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(A) Calls exchanged between a male (blue) and a female zebra finch (red) over the first 4 days housed together. Dots represent the pitch vs. amplitude of short calls. Left: Green lines connect female calls to male answers (when answered within 500ms). Middle: Green lines connect male calls to female answers. Inset: Histograms of response latencies to partner calls within 1000ms. Proportion of partner calls answered. Right: representative sonograms by day. Intervals between calls and answers are shaded in green. (B) Left: Schematic of the vocal robot system. Middle: a male answering robot’s 1Hz isochronous calls (ICs). Right: a female answering robot’s ICs (C) The distribution of a bird’s call responses to the robot’s ICs during a 10-minute session are used to compute an optimal jamming window. The robot then produces jamming calls during this window in the following session. (See also Figure S1).

Jamming Avoidance

The stereotypy of response latencies provided an opportunity to disruptively mask or “jam” call interactions and determine whether birds can adapt their call timing. After obtaining a reliable estimate of a bird’s response latency distribution, we programed the robot to produce call patterns in which each repeating call cycle contains a second (jamming) call exactly when the bird is most likely to respond to the first call (Figures 1C, 2 and S1C). Within a single 10-minute session, birds changed the latencies of their responses to avoid jamming (Figure 2A,B): They produced calls with shorter latencies, longer latencies, or a combination of shorter and longer latencies (Figure 2C-E, H).

Figure 2. Jamming avoidance.

Figure 2

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(A) A male’s call responses (blue) to robot ICs (gray). Top: Responses are aligned by IC cycle onset and presented in sequential rows over a 10-minute session. Middle: The male’s responses (red) to robot call cycles (grey) in which the robot produces jamming calls (yellow). Bottom: Distribution of the bird’s responses during the IC session (blue) and during the jamming call session (red). (B) As in (A) for a female. (C) Examples of jamming avoidance strategies in three birds. Birds’ call timing is plotted relative to a normalized jamming window (yellow). (D) Top: as in (C) pooled across 12 birds. (E) As in (D) comparing call responses across 12 birds for ICs (blue) and catch trials during the jamming session (green). (F) Birds predictively reduce the proportion of calling within the jamming window during catch trials compared to ICs (n=12, paired t-test, ***P<0.001; % decrease in 6 males (red) vs. 6 female (blue), t-test, *P<0.05). (G) Across 12 birds, the average proportion of jamming was lower than expected by chance over the course of a session. (H) A female gradually changes response latencies over the course of a session (First third: bright red. Last third: Dark red) to predictively call between the robot’s jamming call pairs (grey and yellow).

To confirm that this effect is predictive rather than reactive, we incorporated catch trials [21], where the vocal robot intermittently produced only one call within a cycle (with 10% probability) during a session containing jamming calls (Figure S1C). We could then estimate predictive jamming avoidance by measuring the proportion of responses that fall within the expected jamming window during catch trials (Figure 2E). In 12 birds we found that the mean proportion of responses within the expected jamming window decreased from 35±2% for ICs to 13±3% during catch trials (Figure 2F, paired-t test, p<0.001). This avoidance was statistically significant in males (34±3% to 20±5%, n=6, paired-t test, p = 0.014) but greater in females (36±3.5% to 6±2.8%, n=6, paired-t test, p<0.001; t-test females vs. males, p=0.014), indicating more adaptive timing plasticity in the calling behavior of females. Investigating the time course of changes in answer latencies, we found that birds were able to avoid jamming even during the first 30-second block in a session (Figure 2G), suggesting that, like humans, they can predict the timing of upcoming beats even after hearing only a small number of repetitions [22]. However, we also observed a slower refinement of response timing across a session as some birds learned to fit an increasing proportion of their calls precisely in between jamming call pairs (Figure 2H).

Dynamic Adjustments to Complex Rhythms

Social acoustic environments often contain complex temporal contingencies[23]. We wondered if songbirds are capable of taking higher order information into account while patterning their communication calls from moment to moment. To determine whether birds adjust their response timing in a generalized way or can alter it dynamically in a context-dependent fashion, we programmed the vocal robot to produce jamming calls embedded in complex rhythm patterns. Presenting birds with non-isochronous call patterns, containing alternating jamming and non-jamming elements, we found that birds specifically decrease their answer latencies prior to jamming calls (Figure 3). We observed these dynamic adaptations of latencies within a single 10-minute session and over a range of tempos, with cycles of 1-2 seconds (each cycle is a repeating unit of a single call followed by a pair containing a jamming call, Figures 3A,C and S2A). For example, keeping the one second cycle used before, we programmed the robot to produce a dense pattern of calls (Fig. 3A), with alternating call intervals of 400ms and 200ms. This way, the bird was presented with longer or shorter alternating windows where it could answer while avoiding jamming. We could then test if the bird anticipates the alternating patterns within the 200ms after the robot calls, immediately before the jamming window. In that 200ms interval, the bird’s median response latency for single calls in the rhythm (calls followed by longer intervals) was similar to that for ICs (singles in rhythm: 140±1.1ms; ICs: 147±10.6ms). For those rhythmic calls that were followed by a jamming call after 200ms, however, response latencies were shorter (125± 0.8ms; Figure 3B). Therefore, the bird appeared to alternate between faster and slower responses, conforming to the rhythm produced by the vocal robot.

Figure 3. Rhythm adaptation.

Figure 3

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(A) A rhythm pattern of rapidly alternating single calls and jamming call pairs (jamming calls in yellow), produced by a vocal robot (1s cycles, 200ms jamming latency; see also Figure S2). (B) Top: A male’s call responses to the rhythm pattern shown in (A); Green: Responses to the single robot calls. Red: Responses to the jamming call pairs. Middle: Distribution of bird’s responses. Bottom: Cumulative responses within the 200ms following robot call onsets for single calls (green) and the first calls in jamming pairs (red), showing shorter answer latencies prior to jamming. (C) A robot rhythm pattern as in (A) but with slower 2s cycle and 250ms jamming latency. (D) Cumulative responses to the slowly alternating rhythm in 6 birds (green, single calls; red, jamming pairs). (E) Median response latencies for each bird following ICs (blue), single calls in a rhythm (green), and the calls that precede jamming calls in a rhythm (red; Paired t-tests, n=6, *p <0.05).

To rule out the possibility that this difference between latencies is due to a refractory effect from previous responses to jamming calls, we tested six birds for dynamic adaptation in cycles that were twice as long (Figures 3C-D and S2B): Following single calls in the rhythm, median latencies were similar to those for ICs (single calls in rhythm: 203.6±4.9, ICs: 213.8±4.2, paired t-test, n=6, NS, p=0.27). For rhythmic calls that were followed by a jamming call, however, birds accelerated their responses during the same interval, in anticipation of jamming calls (Figure 3E, 193.5±4.0, ICs vs. jamming calls in rhythm, paired t-test, n=6, p=0.022; Singles vs. jamming, p=0.026). This predictive response acceleration occurred in both males and females (Figure 3D,E), indicating that both can adapt their vocal response latencies in real-time to coordinate with complex rhythms. In contrast to reflexive jamming avoidance responses, such as those seen in electric fish [24], zebra finches used varied strategies to adapt their call latencies in an anticipatory way. This surprisingly high degree of sensory-motor flexibility may suggest pallial (i.e. cortical) involvement.

The Forebrain Song System Mediates Predictive Call Timing

The forebrain song system exhibits premotor activity when males sing, but also prior to the production of unlearned calls [16]. We therefore suspected that the song system is involved in learned timing adaptation. This could be the case in females too: Zebra finch females do not sing and their song system is assumed to be vestigial [25]. However, because their jamming avoidance and rhythm adaptation performances were similar to - and often better than - those of males, their less anatomically developed song system could perhaps function to guide the coordination of their vocal behavior. In two males and three females we performed bilateral electrolytic lesioning of the robust nucleus of the arcopallium (RA), which is the common final output of the song system [26]. Lesioning RA profoundly affected the timing of responses in all 5 birds. Although the birds remained responsive to the robot calls (Figure S3A,B), the latency of their responses became much less stereotyped (Figures 4A,B and S3C).

Figure 4. Effects of RA lesions on precision and jamming avoidance.

Figure 4

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(A) Left: Control lesion in a male (purple). Control male’s responses to robot’s ICs (grey) prior to (blue) and after bilateral control lesions (purple). Bottom: Overlay of response distributions. Right: RA lesion in a male (orange). Experimental male responses to vocal robot ICs (grey) prior to (blue) and after bilateral RA lesions (orange) Bottom: Overlay of response distributions. (B) As in (A) for a control female and an experimental female. (C) Precision and skewness of responses to ICs in 2 males and 2 females before and after control lesions (n=4, paired t-tests, NS, P>0.65); in 2 males and 3 females after bilateral RA lesions (n=5, paired t-tests, **P<0.01). (D-E) Response distributions for ICs and catch trials pooled over 5 birds (as in Fig. 2E) before (D) and after (E) RA lesions. (F) Percentage of calling within the jamming window for ICs vs. catch trials before (blue, n=5, *P<0.01) and after RA lesions (orange, NS). (G) RA lesions abolish jamming avoidance, measured as the difference in percent of calling within jamming window for ICs and catch trails (n=5, means, s.e.m, **P<0.01). (See also Figures S3 and S4).

To quantify this effect on response time, we calculated a precision measure [49] that estimates deviation from a uniform distribution of response latencies as a z-score. After lesioning, precision of responses to ICs decreases from 4.43 ±0.37 to 1.91±0.25 (paired t-test, n=5 birds, p<0.01, Figure 4C, top). Response latency skewness also decreased, from 1.31± 0.17 to 0.34± 0.13 (paired t-test, n=5, p<0.01, Figure 4C, bottom), indicating higher symmetry and uniformity of response distributions within a cycle (Figure S3C). Both effects were observed in all three females (Figure 4C). In sum, RA lesions appeared to impair the ability to couple the timing of calls to those of the robot, independent of the overall ability to respond. Birds that underwent identical surgical procedures, but received electrolytic lesions outside the song system, at the pallial surface (Figure 4A,B, n = 2 females, 2 males) showed no changes in timing of their responses (Figures 4C and S4).

The lesion-induced loss of response time precision made it more difficult to target responses for jamming. However, we were still able to test whether the birds exhibited any adaptation to jamming calls by comparing IC responses to those from jamming catch trials. The response probability distributions for ICs vs. jamming catch trials, across 5 lesioned birds, show no decrease in the proportion of calling within the expected jamming window (Figure 4E vs. 4D). All five birds showed jamming avoidance prior to but not after lesioning (decrease from ICs to catch before: 22.6±3.8% vs. after RA lesions: -1.2±0.6%, paired t-test, n=5, p<0.01, Figure 4F-G).

It is likely that the lesioning of song nucleus RA impacted nearby auditory regions within the archopallium, including nucleus AD or RA cup. To address this complication, we examined if the upstream song nucleus HVC, which plays a critical role in song production [28,29] also participates in the regulation of call timing. We recorded from HVC neurons that project to nucleus RA (HVCRA) [30] in three zebra finch males. In all birds we found neurons that fired while the birds produced contact calls in the presence of a female (Figure S4E). Some of those neurons showed short-latency premotor activity, of 10-60ms prior to the calls. Other neurons, however, showed near-zero latency. To determine if HVC projections to RA are necessary for regulating call timing we then disconnected the input from HVC to RA using a procedure that is less likely to compromise auditory regions: We performed bilateral transections of HVCRA projecting axons [29] in 6 adult males. In order to verify that projections were fully severed, we injected a retrograde tracer into nucleus RA immediately after the transection. If transections are complete, the tracer should appear only in the anterior forebrain input to nucleus RA (nucleus LMAN) but not nucleus HVC. In three birds, transection were complete, while in the other three birds medial projections remained intact, as evidenced by histology and the presence of the tracer in nucleus HVC (Figure 5A,B). Interestingly, the three birds that received partial transections showed no impairment in call response precision and were still capable of making adaptive adjustments in call timing to avoid jamming (Figure 5A,C and S4). However, the three birds that received complete HVCRA transections exhibited disrupted call timing, similar to birds with RA lesions, both in the loss of response time precision and reduction of jamming avoidance (Figure 5B-G). Taken together, our results indicate that although the song system is not required for producing call responses, descending forebrain pathways that include the song system, play an essential role in regulating the precise timing needed to predictively coordinate innate calls in both female and male zebra finches.

Figure 5. HVC activity associated with call production and the effects of HVCRA projecting axon transections.

Figure 5

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(A) Partial transections of HVCRA fiber tracts (medial HVCRA tracts intact) allowed retrograde tracer (injected in RA) to reach RA-projecting cells HVC and LMAN. Responses to ICs before (blue) and after (purple) partial transections (n=3) (B) Complete HVCRA transection, verified by absence of tracer within HVC and presence of tracer in LMAN. Responses to ICs before (blue) and after complete bilateral transections (orange, n=3). (C) Complete transections results in decreased precision and skewness of responses to ICs (n=3 birds). Precision is unaffected in transected birds with intact medial projections (n=3). (D) Response distributions for ICs and catch trials (as in Fig. 4F) pooled over three birds before and after (E) complete transections. (F-G) Jamming avoidance is reduced by complete transection of HVCRA projections.

DISCUSSION

Descending Forebrain Pathways Regulate Anticipatory Call Timing

Unlearned calls are produced by primitive brainstem nuclei in many species. However, our findings show that, in zebra finches, regulation of the timing of those calls involves descending forebrain pathways that include the song system. It is unlikely to be a coincidence that the song system is surrounded by auditory centers. Although our investigation focused on the song system, demonstrating activity during calls and loss of function when blocked, anticipatory call timing plasticity is probably driven by the interplay between the forebrain song nuclei and auditory centers that surround them. Several lines of evidence support this view: First, innate short calls are associated with motor activity in both song nucleus RA [16] and in HVCRA projecting cells. It would be interesting to investigate if this activity drives plasticity in vocal timing, perhaps by modulating midbrain and brain stem nuclei, which can generate calls independently of the forebrain [10,12]. Second, electrolytic lesions of RA and elimination of direct projections to RA from HVC profoundly reduce the timing precision of call responses without reducing response rates. Third, call timing plasticity for jamming avoidance is abolished by either RA lesions or by transection of HVCRA projections. Together, these findings suggest that the precise timing required for coordinated calling is driven by the forebrain song system. However, because birds can anticipate the timing of upcoming jamming calls, even after hearing only a small number of repetitions, the regulation of call timing is likely to also rely on the secondary auditory centers that surround the song system. Interestingly, the descending forebrain auditory pathway, which converges on RA cup, is closely associated with vocal learning [32-34]. Therefore, RA cup may be involved in the evaluation of timing error, or in predicting the timing of the robot’s calls. In sum, we suspect that blocking the song system output eliminated the most direct path between the forebrain vocal centers and the primary brainstem vocal motor nuclei (nXIIts, RAm, PAm), hence leaving only non-specific tracts that may lack the precision of the direct drive from the forebrain through RA. In this case, midbrain motor centers (most likely the dorsal medial nucleus, DM) and ascending auditory pathways (dorsal lateral nucleus of the mesencephalon, MLd) can apparently still trigger the production of call responses albeit without the predictive timing control provided by the forebrain [11, 35].

The song system’s involvement in adaptive call timing suggests that vocal learning and call coordination rely on some of the same mechanisms. In both song learning and call coordination, vocal production changes in reference to a sensory ‘template’. In coordinated calling the bird does not reproduce the template, but as with syncopation in music [35], timing is shifted in relation to a predicted pattern. Interestingly, the differences between learning to imitate vocal sounds and coordinating calls can explain specific anatomical differences [25,36-39] between the male and female zebra finch song system: We propose that the female song system functions in call coordination, namely in predictive timing. The male song system functions in vocal learning, which includes both timing and spectral plasticity. Accordingly, song nuclei that are involved exclusively in learning spectral structure should not exist in the female song system. Indeed, the largest song system nucleus, Area X – which is absent from the female brain- is not required for learning time structure in males [25,40]. In contrast, nucleus HVC, nucleus RA, and RA cup are present in both males and females [10,12,25,39] and have all been specifically associated with temporal aspects of song learning [28,31,33,41]. The song system of the female zebra finch, therefore, appears to be specialized for vocal plasticity with respect to timing.

Phylogenetic Perspective on Vocal Learning

The finding that the female song system can support vocal timing plasticity for coordination has several implications for our understanding of the origins of vocal learning. Although females may only have weak HVC to RA projections (which, as we show in males, can be sufficient for control of call timing), they also have descending connections from HVC shelf to RA cup [31,42]. This descending auditory pathway is common to vocal non-learners that lack RA (e.g. pigeons) and vocal learners with RA homologues (e.g. budgerigars). However the descending auditory pathway does not directly project to subcortical vocal production centers in any of these cases. In at least one sub-oscine vocal non-learning species, the eastern phoebe, this pathway exhibits RA-like premotor properties and does project to brainstem vocal production centers. Lesions to this intermediate structure produce subtle but reliable changes to the unlearned song [7]. From this comparative perspective, it appears that the development of a rudimentary forebrain premotor vocal pathway, in close apposition to the descending auditory pathway, was a pivotal step in the evolution of vocal learning [7].

Evidence that the rudimentary female RA is necessary for the coordination of call timing is consistent with findings by Ter Maat et al. (2014) suggesting that the primitive function of nucleus RA might have been to achieve cortical modulation of unlearned vocalizations before it evolved a secondary role in song learning and production [16]. Furthermore, comparative evidence that female singing is ancestral in songbirds [43], suggests that sexual dimorphism in the song system is a more recently derived state. Perhaps, the song system originally functioned in coordinating vocalizations in the context of social bonding [13,18]. Such a putative ancestral function could also explain why females appear to make greater adaptive adjustments to call timing than males: we propose that the female song system is specialized for regulating vocal coordination. Whereas males retained some of this primitive function, the evolution of territorial singing, might conflict with coordination. Perhaps the tendency of males to ‘stand their ground’ explains their inferior performance in the jamming avoidance tests.

Vocal learning and auditory-motor synchronization (e.g., dancing to music) are considered to be evolutionarily and mechanistically linked, perhaps stemming from shared social origins [44-46]. Our results provide direct evidence for a similar link between song learning and call synchronization except that here both phenomena are vocal and are supported by the same sensorimotor pathway. In human beat perception, premotor cortex is implicated in the analysis and prediction of sound timing regularities [35,44]. Evidence for an analogous process in the song system is emerging from recordings from interacting zebra finches [47] as well as the coordinated duets of male and female plain-tailed wrens, in which pre-motor activity may encode shared information about a rapidly alternating partner’s timing intervals [48]. The loss of timing precision and jamming avoidance after blocking the song system in zebra finches may be the consequence of disrupting such an auditory-motor timing prediction mechanism that guides call coordination.

The remarkable vocal coordination capacity we observed in both female and male zebra finch, using controlled behavioral assays, support the idea of a mechanistic continuum from vocal coordination to vocal learning, spanning a functional gap that has separated vocal non-learners from vocal learners. Considering that coordination of unlearned vocalizations, without forebrain control, is relatively widespread across taxa, the likely primitive function of the forebrain song system was to enable plasticity in the timing of social behavior. Such a general-purpose sensorimotor communication system could facilitate vocal interactions on different time scales: In the case of calls, it enables predictive modulation of vocal timing, where as in the case of learned songs, plasticity extends to developmental changes in vocal structure. In this scenario, the ability to make predictive behavioral adjustments from moment to moment, with respect to a social partner, provided the mechanistic basis for vocal learning (i.e. “offline” coordination with the auditory memory of the vocalizations of others). This social coordination hypothesis can also begin to explain some of the evolutionary convergence in the mechanisms of vocal learning and auditory-motor synchronization seen across mammalian and avian brains [6-8,35,44-46].

EXPERIMENTAL PROCEDURES

Animal care

All experiments were performed in accordance with guidelines of The US National Institutes of Health and have been reviewed and approved by the Institutional Animal Care and Use Committees of Hunter College of the City University of New York and New York University Langone Medical Center.

Analysis of a Synchronized Pair

Call interactions were recorded continuously using Sound Analysis Pro 2011 (SAP). Birds’ call onsets and durations were identified semi-automatically and analyzed using Matlab 7. Call feature calculation and cluster analysis were performed using SAP. Cluster information was used to elucidate bird identity. We then used Matlab 7 for analysis of call answers (calls within a 500ms window) for 500 consecutive calls, selected pseudorandomly from each of the four days.

Vocal Robot

We developed an interactive vocal robot application in LabVIEW (Supplemental Material, Code to be made available) which delivers patterns of calls at programmable intervals that can be tailored (manually or automatically) to match (or avoid) answer latencies of individual birds (Figures 1, S1 and S2, Movie S1).

Computation of the Jamming Window

Each bird’s calls were recorded over a ten-minute session of isochronous robot calls and were used to calculate the jamming window. Call response onsets and offsets were coded relative to the onset of the previous robot call. These onsets and durations were summed across all cycles in a session to produce a response probability distribution. The jamming window was defined as the 100ms interval with the highest response density. The window onset is the latency of the jamming call delivered in each 1s cycle during the next session of jamming calls. Jamming percentages were calculated as the proportion of total calling activity falling with the bounds of the jamming window. Catch trials were calculated as above. Response latencies and skewness were calculated in Matlab 7 using the onsets of responses, relative to the previous robot call. For responses to single calls and jamming calls in a rhythm, we calculated median latencies for responses with onsets prior to the expected jamming window.

Precision Score

Precision scores were calculated as in Vallentin et al. [49] for each session using the proportion of all response onset latency differences that were within ±50ms (approx. duration of a call). This proportion was used to compute a Z-score, relative to a distribution of proportions from 1000 simulated sessions containing an equal number of uniformly distributed pseudorandom latencies. The precision score is expressed as the square root of this Z-score.

RA Lesions

Electrolytic RA and control lesions were performed bilaterally in anesthetized males and in females.

Electrophysiological Recording in HVC

Intracellular recordings from four antidromically identified HVCRA neurons in three freely behaving adult males were obtained using a motorized intracellular microdrive. A detailed description of this approach can be found in Vallentin & Long, 2015 [30].

Transection of HVC to RA projections

Transection of axonal projections from nucleus HVC to nucleus RA were performed bilaterally in adult males (as described in Aronov, 2008 [29]). (Also see Supplemental Experimental Procedures).

Supplementary Material

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Download video file (15.3MB, mp4)
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Highlights.

  • Zebra finches can learn to modify the timing of their innate calls.

  • Birds dynamically adjust call timing in anticipation of complex rhythm patterns.

  • Non-singing females exhibit strong call timing plasticity.

  • The song control system is necessary for precise anticipatory call timing.

Acknowledgments

We thank B. Papaconstantinou for assistance with data analysis as well as C. Alexander and M. Hauber for reading and commenting on the manuscript. Supported by NIH, NSF, PSC-CUNY grants to OT and by an NIH grant to M.A.L.

Footnotes

AUTHOR CONTRIBUTIONS

J.I.B., O.T., M.A.L., S.E.B., and E.G. designed the research. J.I.B., S.E.B., & D.V. performed experiments. J.I.B., S.E.B., D.V., E.G., M.A.L. & O.T. analyzed data. J.I.B. and O.T. wrote the original manuscript and all authors helped revise it.

The authors declare no conflicting financial interests.

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