Juvenile zebra finches learn the underlying structural regularities of their fathers' song

The Temporal Organization of Learned Vocal Behavior Is Predicted by Species Rather Than Experience

Birdsong is hierarchically organized in time, like speech and other communication behaviors. Syllables are produced in sequences to form song motifs and bouts. While syllables are copied from tutors, the factors that determine song temporal organization, including syllable sequencing (syntax), are unknown. Here, we tested the roles of learning and species genetics in song organization. We manipulated juvenile song experience and genetics in three species of estrildid finches (zebra finches, Taeniopygia guttata castanotis; long-tailed finches, Poephila acuticauda; Bengalese finches, Lonchura striata var. domestica). We analyzed the adult songs of male birds that were: (1) tutored by conspecifics; (2) untutored; (3) tutored by heterospecifics; and (4) genetic hybrids. Song macrostructure, syllable sequencing, and syllable timing were quantified and compared within and across species. Results showed that song organization was consistent within a species and differed across species, regardless of experience. Temporal features did not differ between tutored and untutored birds of the same species. The songs of birds tutored by other species were composed of heterospecific syllables produced in sequences typical of conspecific songs. The songs of genetic hybrids showed the organization of both parental species, despite the fact that only males sing. Results indicate that song organization is predicted by species rather than experience.

What do zebra finches learn besides singing? Systematic mapping of the literature and presentation of an efficient associative learning test

The process of learning in birds has been extensively studied, with a focus on species such as pigeons, parrots, chickens, and crows. In recent years, the zebra finch has emerged as a model species in avian cognition, particularly in song learning. However, other cognitive domains such as spatial memory and associative learning could also be critical to fitness and survival, particularly during the intensive juvenile period. In this systematic review, we provide an overview of cognitive studies on zebra finches, with a focus on domains other than song learning. Our findings indicate that spatial, associative, and social learning are the most frequently studied domains, while motoric learning and inhibitory control have been examined less frequently over 30 years of research. All of the 60 studies included in this review were conducted on captive birds, limiting the generalizability of the findings to wild populations. Moreover, only two of the studies were conducted on juveniles, highlighting the need for more research on this critical period of learning. To address this research gap, we propose a high-throughput method for testing associative learning performance in a large number of both juvenile and adult zebra finches. Our results demonstrate that learning can occur in both age groups, thus encouraging researchers to also perform cognitive tests on juveniles. We also note the heterogeneity of methodologies, protocols, and subject exclusion criteria applied by different researchers, which makes it difficult to compare results across studies. Therefore, we call for better communication among researchers to develop standardised methodologies for studying each cognitive domain at different life stages and also in their natural conditions.

Calcium-binding proteins typify the dopaminergic neuronal subtypes in the ventral tegmental area of zebra finch, Taeniopygia guttata

Calcium-binding proteins (CBPs) regulate neuronal function in midbrain dopamine (DA)-ergic neurons in mammals by buffering and sensing the intracellular Ca²⁺ , and vesicular release. In birds, the equivalent set of neurons are important in song learning, directed singing, courtship, and energy balance, yet the status of CBPs in these neurons is unknown. Herein, for the first time, we probe the nature of CBPs, namely, Calbindin-, Calretinin-, Parvalbumin-, and Secretagogin-expressing DA neurons in the ventral tegmental area (VTA) and substantia nigra (SN) in the midbrain of zebra finch, Taeniopygia guttata. qRT-PCR analysis of ventral midbrain tissue fragment revealed higher Calbindin- and Calretinin-mRNA levels compared to Parvalbumin and Secretagogin. Application of immunofluorescence showed CBP-immunoreactive (-i) neurons in VTA (anterior [VTAa], mid [VTAm], caudal [VTAc]), SN (compacta [SNc], and reticulata [SNr]). Compared to VTAa, higher Calbindin- and Parvalbumin-immunoreactivity (-ir), and lower Calretinin-ir were observed in VTAm and VTAc. Secretagogin-ir was highly localized to VTAa. In SN, Calbindin- and Calretinin-ir were higher in SNc, SNr was Parvalbumin enriched, and Secretagogin-ir was not detected. Weak, moderate, and intense tyrosine hydroxylase (TH)-i VTA neurons were demarcated as subtypes 1, 2, and 3, respectively. While subtype 1 TH-i neurons were neither Calbindin- nor Calretinin-i, ∼80 and ∼65% subtype 2 and ∼30 and ∼45% subtype 3 TH-i neurons co-expressed Calbindin and Calretinin, respectively. All TH-i neuronal subtypes co-expressed Parvalbumin with reciprocal relationship with TH-ir. We suggest that the CBPs may determine VTA DA neuronal heterogeneity and differentially regulate their activity in T. guttata.

Identification, Analysis and Characterization of Base Units of Bird Vocal Communication: The White Spectacled Bulbul (Pycnonotus xanthopygos) as a Case Study

Animal vocal communication is a broad and multi-disciplinary field of research. Studying various aspects of communication can provide key elements for understanding animal behavior, evolution, and cognition. Given the large amount of acoustic data accumulated from automated recorders, for which manual annotation and analysis is impractical, there is a growing need to develop algorithms and automatic methods for analyzing and identifying animal sounds. In this study we developed an automatic detection and analysis system based on audio signal processing algorithms and deep learning that is capable of processing and analyzing large volumes of data without human bias. We selected the White Spectacled Bulbul (Pycnonotus xanthopygos) as our bird model because it has a complex vocal communication system with a large repertoire which is used by both sexes, year-round. It is a common, widespread passerine in Israel, which is relatively easy to locate and record in a broad range of habitats. Like many passerines, the Bulbul’s vocal communication consists of two primary hierarchies of utterances, syllables and words. To extract each of these units’ characteristics, the fundamental frequency contour was modeled using a low degree Legendre polynomial, enabling it to capture the different patterns of variation from different vocalizations, so that each pattern could be effectively expressed using very few coefficients. In addition, a mel-spectrogram was computed for each unit, and several features were extracted both in the time-domain (e.g., zero-crossing rate and energy) and frequency-domain (e.g., spectral centroid and spectral flatness). We applied both linear and non-linear dimensionality reduction algorithms on feature vectors and validated the findings that were obtained manually, namely by listening and examining the spectrograms visually. Using these algorithms, we show that the Bulbul has a complex vocabulary of more than 30 words, that there are multiple syllables that are combined in different words, and that a particular syllable can appear in several words. Using our system, researchers will be able to analyze hundreds of hours of audio recordings, to obtain objective evaluation of repertoires, and to identify different vocal units and distinguish between them, thus gaining a broad perspective on bird vocal communication.

Is there such a thing as a 'good statistical learner'?

A growing body of research investigates individual differences in the learning of statistical structure, tying them to variability in cognitive (dis)abilities. This approach views statistical learning (SL) as a general individual ability that underlies performance across a range of cognitive domains. But is there a general SL capacity that can sort individuals from 'bad' to 'good' statistical learners? Explicating the suppositions underlying this approach, we suggest that current evidence supporting it is meager. We outline an alternative perspective that considers the variability of statistical environments within different cognitive domains. Once we focus on learning that is tuned to the statistics of real-world sensory inputs, an alternative view of SL computations emerges with a radically different outlook for SL research.

Vocal learning in songbirds: the role of syllable order in song recognition

Songbird vocal learning has interesting behavioural and neural parallels with speech acquisition in human infants. Zebra finch males sing one unique song that they imitate from conspecific males, and both sexes learn to recognize their father's song. Although males copy the stereotyped syllable sequence of their father's song, the role of sequential information in recognition remains unclear. Here, we investigated father's song recognition after changing the serial order of syllables (switching the middle syllables, first and last syllables, or playing all syllables in inverse order). Behavioural approach and call responses of adult male and female zebra finches to their father's versus unfamiliar songs in playback tests demonstrated significant recognition of father's song with all syllable-order manipulations. We then measured behavioural responses to normal versus inversed-order father's song. In line with our first results, the subjects did not differentiate between the two. Interestingly, when males' strength of song learning was taken into account, we found a significant correlation between song imitation scores and the approach responses to the father's song. These findings suggest that syllable sequence is not essential for recognition of father's song in zebra finches, but that it does affect responsiveness of males in proportion to the strength of vocal learning. This article is part of the theme issue 'Vocal learning in animals and humans'.

Long-term implicit memory for sequential auditory patterns in humans

Memory, on multiple timescales, is critical to our ability to discover the structure of our surroundings, and efficiently interact with the environment. We combined behavioural manipulation and modelling to investigate the dynamics of memory formation for rarely reoccurring acoustic patterns. In a series of experiments, participants detected the emergence of regularly repeating patterns within rapid tone-pip sequences. Unbeknownst to them, a few patterns reoccurred every ~3 min. All sequences consisted of the same 20 frequencies and were distinguishable only by the order of tone-pips. Despite this, reoccurring patterns were associated with a rapidly growing detection-time advantage over novel patterns. This effect was implicit, robust to interference, and persisted for 7 weeks. The results implicate an interplay between short (a few seconds) and long-term (over many minutes) integration in memory formation and demonstrate the remarkable sensitivity of the human auditory system to sporadically reoccurring structure within the acoustic environment.

Individual vocal recognition in zebra finches relies on song syllable structure rather than song syllable order

Many species are able to vocally recognize individual conspecifics and this capacity seems widespread in oscine songbirds. The exact acoustic features used for such recognition are often not clear. In the zebra finch (Taeniopygia guttata), the song motif is composed of a few syllables repeated in a fixed sequential order and song bouts include several repetitions of the motif. Here, we used an operant discrimination task, the GO/NOGO procedure, to show that zebra finches are capable of individual vocal recognition even if the bird has to distinguish males that all produce an imitation of the same song model. Furthermore, we studied whether such individual vocal recognition was based on spectro-temporal details of song syllables, i.e. the local fine structure of the song, or on the sequential order in which song syllables are arranged in the song bout. To this end, we trained male and female zebra finches to discriminate songs of one male conspecific from those of four others. After learning this baseline discrimination, subjects were exposed to a novel set of stimuli originating from the same individuals, in order to test for their capability to generalise. Subjects correctly classified those novel stimuli, illustrating their ability for individual vocal recognition. Then they were exposed to hybrid stimuli combining the syllable sequences of one individual with the spectro-temporal features of another. Behavioural responses of subjects to hybrid stimuli suggest that they rely on spectro-temporal details of syllables and might pay less attention to syllable sequences for individual vocal recognition.

Statistical learning for vocal sequence acquisition in a songbird

Birdsong is a learned communicative behavior that consists of discrete acoustic elements (“syllables”) that are sequenced in a controlled manner. While the learning of the acoustic structure of syllables has been extensively studied, relatively little is known about sequence learning in songbirds. Statistical learning could contribute to the acquisition of vocal sequences, and we investigated the nature and extent of sequence learning at various levels of song organization in the Bengalese finch, Lonchura striata var. domestica. We found that, under semi-natural conditions, pupils (sons) significantly reproduced the sequence statistics of their tutor’s (father’s) songs at multiple levels of organization (e.g., syllable repertoire, prevalence, and transitions). For example, the probability of syllable transitions at “branch points” (relatively complex sequences that are followed by multiple types of transitions) were significantly correlated between the songs of tutors and pupils. We confirmed the contribution of learning to sequence similarities between fathers and sons by experimentally tutoring juvenile Bengalese finches with the songs of unrelated tutors. We also discovered that the extent and fidelity of sequence similarities between tutors and pupils were significantly predicted by the prevalence of sequences in the tutor’s song and that distinct types of sequence modifications (e.g., syllable additions or deletions) followed distinct patterns. Taken together, these data provide compelling support for the role of statistical learning in vocal production learning and identify factors that could modulate the extent of vocal sequence learning.

Sound sequences in birdsong: how much do birds really care?

The complex and melodic nature of many birds' songs has raised interest in potential parallels between avian vocal sequences and human speech. The similarities between birdsong and speech in production and learning are well established, but surprisingly little is known about how birds perceive song sequences. One popular laboratory songbird, the zebra finch (Taeniopygia guttata), has recently attracted attention as an avian model for human speech, in part because the male learns to produce the individual elements in its song motif in a fixed sequence. But psychoacoustic evidence shows that adult zebra finches are relatively insensitive to the sequential features of song syllables. Instead, zebra finches and other birds seem to be exquisitely sensitive to the acoustic details of individual syllables to a degree that is beyond human hearing capacity. Based on these findings, we present a finite-state model of zebra finch perception of song syllable sequences and discuss the rich informational capacity of their vocal system. Furthermore, we highlight the abilities of budgerigars (Melopsittacus undulatus), a parrot species, to hear sequential features better than zebra finches and suggest that neurophysiological investigations comparing these species could prove fruitful for uncovering neural mechanisms for auditory sequence perception in human speech. This article is part of the theme issue 'What can animal communication teach us about human language?'

Capacities and neural mechanisms for auditory statistical learning across species

Statistical learning has been proposed as a possible mechanism by which individuals can become sensitive to the structures of language fundamental for speech perception. Since its description in human infants, statistical learning has been described in human adults and several non-human species as a general process by which animals learn about stimulus-relevant statistics. The neurobiology of statistical learning is beginning to be understood, but many questions remain about the underlying mechanisms. Why is the developing brain particularly sensitive to stimulus and environmental statistics, and what neural processes are engaged in the adult brain to enable learning from statistical regularities in the absence of external reward or instruction? This review will survey the statistical learning abilities of humans and non-human animals with a particular focus on communicative vocalizations. We discuss the neurobiological basis of statistical learning, and specifically what can be learned by exploring this process in both humans and laboratory animals. Finally, we describe advantages of studying vocal communication in rodents as a means to further our understanding of the cortical plasticity mechanisms engaged during statistical learning. We examine the use of rodents in the context of pup retrieval, which is an auditory-based and experience-dependent form of maternal behavior.

The evolution of the capacity for language: the ecological context and adaptive value of a process of cognitive hijacking

Language plays a pivotal role in the evolution of human culture, yet the evolution of the capacity for language-uniquely within the hominin lineage-remains little understood. Bringing together insights from cognitive psychology, neuroscience, archaeology and behavioural ecology, we hypothesize that this singular occurrence was triggered by exaptation, or 'hijacking', of existing cognitive mechanisms related to sequential processing and motor execution. Observed coupling of the communication system with circuits related to complex action planning and control supports this proposition, but the prehistoric ecological contexts in which this coupling may have occurred and its adaptive value remain elusive. Evolutionary reasoning rules out most existing hypotheses regarding the ecological context of language evolution, which focus on ultimate explanations and ignore proximate mechanisms. Coupling of communication and motor systems, although possible in a short period on evolutionary timescales, required a multi-stepped adaptive process, involving multiple genes and gene networks. We suggest that the behavioural context that exerted the selective pressure to drive these sequential adaptations had to be one in which each of the systems undergoing coupling was independently necessary or highly beneficial, as well as frequent and recurring over evolutionary time. One such context could have been the teaching of tool production or tool use. In the present study, we propose the Cognitive Coupling hypothesis, which brings together these insights and outlines a unifying theory for the evolution of the capacity for language.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'.

Spontaneous Learning of Visual Structures in Domestic Chicks

Simple Summary

Our aim is to investigate the recognition of the structure of multi-element configurations; one mechanism that supports communicative functions in different species. Cognitive mechanisms involved in this ability might not have evolved specifically for communicative use, but derive from other functions. Thus, it is crucial to study these abilities in species that are not vocal learners and with stimuli from other modalities. We know already that domestic chicks can learn the temporal statistical structure of sequences of visual shapes, however their abilities to encode the spatial structure of visual patterns (configurations composed of multiple visual elements presented simultaneously side-by-side) is much less known. Using filial imprinting learning, we showed that chicks spontaneously recognize the structure of their imprinting stimulus, preferring it to one composed of the same elements in different configurations. Moreover, we found that in their affiliative responses chicks give priority to information located at the stimulus edges, a phenomenon that was so far observed only with temporal sequences. This first evidence of a spontaneous edge bias with spatial stimuli further stresses the importance of studying similarities and differences between the processing of linguistic and nonlinguistic stimuli and of stimuli presented in various sensory modalities.

Abstract

Effective communication crucially depends on the ability to produce and recognize structured signals, as apparent in language and birdsong. Although it is not clear to what extent similar syntactic-like abilities can be identified in other animals, recently we reported that domestic chicks can learn abstract visual patterns and the statistical structure defined by a temporal sequence of visual shapes. However, little is known about chicks’ ability to process spatial/positional information from visual configurations. Here, we used filial imprinting as an unsupervised learning mechanism to study spontaneous encoding of the structure of a configuration of different shapes. After being exposed to a triplet of shapes (ABC or CAB), chicks could discriminate those triplets from a permutation of the same shapes in different order (CAB or ABC), revealing a sensitivity to the spatial arrangement of the elements. When tested with a fragment taken from the imprinting triplet that followed the familiar adjacency-relationships (AB or BC) vs. one in which the shapes maintained their position with respect to the stimulus edges (AC), chicks revealed a preference for the configuration with familiar edge elements, showing an edge bias previously found only with temporal sequences.

Relative salience of syllable structure and syllable order in zebra finch song

There is a rich history of behavioral and neurobiological research focused on the 'syntax' of birdsong as a model for human language and complex auditory perception. Zebra finches are one of the most widely studied songbird species in this area of investigation. As they produce song syllables in a fixed sequence, it is reasonable to assume that adult zebra finches are also sensitive to the order of syllables within their song; however, results from electrophysiological and behavioral studies provide somewhat mixed evidence on exactly how sensitive zebra finches are to syllable order as compared, say, to syllable structure. Here, we investigate how well adult zebra finches can discriminate changes in syllable order relative to changes in syllable structure in their natural song motifs. In addition, we identify a possible role for experience in enhancing sensitivity to syllable order. We found that both male and female adult zebra finches are surprisingly poor at discriminating changes to the order of syllables within their species-specific song motifs, but are extraordinarily good at discriminating changes to syllable structure (i.e., reversals) in specific syllables. Direct experience or familiarity with a song, either using the bird's own song (BOS) or the song of a flock mate as the test stimulus, improved both male and female zebra finches' sensitivity to syllable order. However, even with experience, birds remained much more sensitive to structural changes in syllables. These results help to clarify some of the ambiguities from the literature on the discriminability of changes in syllable order in zebra finches, provide potential insight on the ethological significance of zebra finch song features, and suggest new avenues of investigation in using zebra finches as animal models for sequential sound processing.

Constraints on Statistical Learning Across Species

Both human and nonhuman organisms are sensitive to statistical regularities in sensory inputs that support functions including communication, visual processing, and sequence learning. One of the issues faced by comparative research in this field is the lack of a comprehensive theory to explain the relevance of statistical learning across distinct ecological niches. In the current review we interpret cross-species research on statistical learning based on the perceptual and cognitive mechanisms that characterize the human and nonhuman models under investigation. Considering statistical learning as an essential part of the cognitive architecture of an animal will help to uncover the potential ecological functions of this powerful learning process.

Neural activity associated with rhythmicity of song in juvenile male and female zebra finches

Rhythm is an important aspect of both human speech and birdsong. Adult zebra finches show increased neural activity following exposure to arrhythmic compared to rhythmic song in regions similar to the mammalian auditory association cortex and amygdala. This pattern may indicate that birds are detecting errors in the arrhythmic song relative to their learned song template or to more general expectations of song structure. Here we exposed juvenile zebra finches to natural conspecific song (rhythmic) or song with altered inter-syllable intervals (arrhythmic) prior to or during template formation, or afterward as males are matching vocal production to a memorized song template (sensorimotor integration). Before template formation, expression of the immediate early gene ZENK was increased in the caudomedial nidopallium (NCM) of birds exposed to rhythmic relative to arrhythmic song. During template formation, ZENK expression was increased in the caudomedial mesopallium (CMM) of birds exposed to arrhythmic relative to rhythmic song. These results suggest that the youngest birds may be predisposed to respond to a more natural stimulus, and a template may be required for arrhythmic song to elicit increased neural activity. It also appears that functional development across the brain regions investigated continues to maturity.

Statistical learning in songbirds: from self-tutoring to song culture

At the onset of vocal development, both songbirds and humans produce variable vocal babbling with broadly distributed acoustic features. Over development, these vocalizations differentiate into the well-defined, categorical signals that characterize adult vocal behaviour. A broadly distributed signal is ideal for vocal exploration, that is, for matching vocal production to the statistics of the sensory input. The developmental transition to categorical signals is a gradual process during which the vocal output becomes differentiated and stable. But does it require categorical input? We trained juvenile zebra finches with playbacks of their own developing song, produced just a few moments earlier, updated continuously over development. Although the vocalizations of these self-tutored (ST) birds were initially broadly distributed, birds quickly developed categorical signals, as fast as birds that were trained with a categorical, adult song template. By contrast, siblings of those birds that received no training (isolates) developed phonological categories much more slowly and never reached the same level of category differentiation as their ST brothers. Therefore, instead of simply mirroring the statistical properties of their sensory input, songbirds actively transform it into distinct categories. We suggest that the early self-generation of phonological categories facilitates the establishment of vocal culture by making the song easier to transmit at the micro level, while promoting stability of shared vocabulary at the group level over generations.

This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’.

The bottleneck may be the solution, not the problem

As a highly consequential biological trait, a memory "bottleneck" cannot escape selection pressures. It must therefore co-evolve with other cognitive mechanisms rather than act as an independent constraint. Recent theory and an implemented model of language acquisition suggest that a limit on working memory may evolve to help learning. Furthermore, it need not hamper the use of language for communication.

Experimental exposure to urban and pink noise affects brain development and song learning in zebra finches (Taenopygia guttata)

Recently, numerous studies have observed changes in bird vocalizations-especially song-in urban habitats. These changes are often interpreted as adaptive, since they increase the active space of the signal in its environment. However, the proximate mechanisms driving cross-generational changes in song are still unknown. We performed a captive experiment to identify whether noise experienced during development affects song learning and the development of song-control brain regions. Zebra finches (Taeniopygia guttata) were bred while exposed, or not exposed, to recorded traffic urban noise (Study 1) or pink noise (Study 2). We recorded the songs of male offspring and compared these to fathers' songs. We also measured baseline corticosterone and measured the size of song-control brain regions when the males reached adulthood (Study 1 only). While male zebra finches tended to copy syllables accurately from tutors regardless of noise environment, syntax (the ordering of syllables within songs) was incorrectly copied affected by juveniles exposed to noise. Noise did not affect baseline corticosterone, but did affect the size of brain regions associated with song learning: these regions were smaller in males that had been had been exposed to recorded traffic urban noise in early development. These findings provide a possible mechanism by which noise affects behaviour, leading to potential population differences between wild animals occupying noisier urban environments compared with those in quieter habitats.

Automatic Recognition of Element Classes and Boundaries in the Birdsong with Variable Sequences

Researches on sequential vocalization often require analysis of vocalizations in long continuous sounds. In such studies as developmental ones or studies across generations in which days or months of vocalizations must be analyzed, methods for automatic recognition would be strongly desired. Although methods for automatic speech recognition for application purposes have been intensively studied, blindly applying them for biological purposes may not be an optimal solution. This is because, unlike human speech recognition, analysis of sequential vocalizations often requires accurate extraction of timing information. In the present study we propose automated systems suitable for recognizing birdsong, one of the most intensively investigated sequential vocalizations, focusing on the three properties of the birdsong. First, a song is a sequence of vocal elements, called notes, which can be grouped into categories. Second, temporal structure of birdsong is precisely controlled, meaning that temporal information is important in song analysis. Finally, notes are produced according to certain probabilistic rules, which may facilitate the accurate song recognition. We divided the procedure of song recognition into three sub-steps: local classification, boundary detection, and global sequencing, each of which corresponds to each of the three properties of birdsong. We compared the performances of several different ways to arrange these three steps. As results, we demonstrated a hybrid model of a deep convolutional neural network and a hidden Markov model was effective. We propose suitable arrangements of methods according to whether accurate boundary detection is needed. Also we designed the new measure to jointly evaluate the accuracy of note classification and boundary detection. Our methods should be applicable, with small modification and tuning, to the songs in other species that hold the three properties of the sequential vocalization.