Carel Ten Cate

The ability to understand relational concepts, such as ‘same’ and ‘different’, is a critical feature of human cognition. To what extent non-human animals can acquire such concepts and which factors influence their learning are still unclear. We examined the acquisition and the breadth of understanding the ‘same–different’ concept in budgerigars ( Melopsittacus undulatus ). Budgerigars trained to discriminate stimulus pairs in which two identical figures were either the same or different size (Experiment 1) successfully generalized the discrimination to novel stimuli belonging to various categories (size, colour, shape, geometric type and number of dots). The results of Experiment 1 thus demonstrate that budgerigars can perceive and generalize the same–different concept across dimensions after training with a limited set of stimuli differing along a single dimension. In contrast, while most budgerigars trained to discriminate two pairs of discs that were either the same or different in colour (Experiment 2) could generalize the discrimination to novel stimuli within the training category (colour), only few generalized the discrimination to another category suggesting a generalization based on perceptual similarity. The results thus show that whether budgerigars generalize a relationship by conceptual or perceptual similarity depends on the nature of the training stimuli.

In humans, mutations of the transcription factor FoxP1 are implicated in speech and language problems. In songbirds, FoxP1 has been linked to male song learning and female preference strength. We found that FoxP1 knockdowns in female HVC and caudomedial mesopallium (CMM) did not alter song discrimination or categorization based on spectral and temporal information. However, this large dataset allowed to validate different cue weights for spectral over temporal information for song recognition.

La neurobiología comparativa nos permite investigar las relaciones entre filogenia y el cerebro, y comprender la evolución de rasgos. Los murciélagos constituyen un grupo atractivo de especies de mamíferos para estudios comparativos, dada su gran diversidad en fenotipos de comportamiento, morfología cerebral y variedad de rasgos especializados. Actualmente, el orden de murciélagos Chiroptera contiene más de 1,450 especies a lo largo de 21 familias y abarcando ca. 65 millones de años de evolución. 194 especies de murciélagos Neotropicales han sido registrados en América Central en la actualidad. Este estudio incluye descripciones macromorfológicas cualitativas y cuantitativas de cerebros de doce especies de seis familias de murciélagos Neotropicales. Estos análisis, que incluyen tinción neuronal usando una técnica histológica en dos especies de diferentes familias (Phyllostomus hastatus y Saccopteryx bilineata), muestran una diversidad sustancial en la macromorfología cerebral, incluida la forma y el tamaño del cerebro, la exposición de las regiones mesencefálicas y la profundidad de las fisuras corticales y cerebelosas. La macromorfología del cerebro puede explicarse en parte por la filogenia, ya que las especies dentro de la misma familia son más similares entre sí. Sin embargo, la macromorfología no puede explicarse solo por el tiempo evolutivo, ya que entre algunas especies de murciélagos filostómidos hay mayores diferencias que entre especies de la familia Emballonuridae, a pesar de tener distancias divergentes comparables en el árbol filogenético. Esto sugiere que se produjeron cambios evolutivos más rápidos en la morfología del cerebro en filostómidos, aunque para confirmar esto es necesario estudiar un mayor número de especies. Nuestros resultados muestran la gran diversidad en la morfología del cerebro que proporcionan los murciélagos para estudios comparativos y evolutivos.

Zebra finches rely mainly on syllable phonology rather than on syllable sequence when they discriminate between two songs. However, they can also learn to discriminate two strings containing the same set of syllables by their sequence. How learning about the phonological characteristics of syllables and their sequence relate to each other and to the composition of the stimuli is still an open question. We compared whether and how the zebra finches’ relative sensitivity for syllable phonology and syllable sequence depends on the differences between syllable strings. Two groups of zebra finches were trained in a Go-Left/Go-Right task to discriminate either between two strings in which each string contained a unique set of song syllables (‘Different-syllables group’) or two strings in which both strings contained the same set of syllables, but in a different sequential order (‘Same-syllables group’). We assessed to what extent the birds in the two experimental groups attend to the spectral characteristics and the sequence of the syllables by measuring the responses to test strings consisting of spectral modifications or sequence changes. Our results showed no difference in the number of trials needed to discriminate strings consisting of either different or identical sets of syllables. Both experimental groups attended to changes in spectral features in a similar way, but the group for which both training strings consisted of the same set of syllables responded more strongly to changes in sequence than the group for which the training strings consisted of different sets of syllables. This outcome suggests the presence of an additional learning process to learn about syllable sequence when learning about syllable phonology is not sufficient to discriminate two strings. Our study thus demonstrates that the relative importance of syllable phonology and sequence depends on how these features vary among stimuli. This indicates cognitive flexibility in the acoustic features that songbirds might use in their song recognition.

Zebra finches rely mainly on syllable phonology rather than on syllable sequence when they discriminate between two songs. However, they can also learn to discriminate two strings of containing the same set of syllables by their sequence. How learning about the phonological characteristics of syllables and their sequence relate to each other and to the composition of the stimuli is still an open question. We compared whether and how the zebra finches’ relative sensitivity for syllable phonology and syllable sequence depends on the differences between syllable strings. Zebra finches were trained in a Go-Left/Go-Right task to discriminate either between two strings in which each string contained a unique set of song syllables or two strings in which both strings contained the same set of syllables, but in a different sequential order. We assessed to what extent the birds in the two experimental groups attend to the spectral characteristics and the sequence of the syllables by measuring the responses to test strings consisting of spectral modifications or sequence changes. Our results showed no difference in the number of trials needed to discriminate strings consisting of either different or identical sets of syllables. Both experimental groups attended to changes in spectral features in a similar way, but the group for which both training strings consisted of the same set of syllables responded more strongly to changes in sequence than the group for which the training strings consisted of different sets of syllables. This outcome suggests the presence of an additional learning process to learn about syllable sequence when learning about syllable phonology is not sufficient to discriminate two strings. Our study thus demonstrates that the relative importance of syllable phonology and sequence depends on which of these features vary among stimuli. This indicates cognitive flexibility in the acoustic features that songbirds might use in their song recognition.

How learning affects vocalizations is a key question in the study of animal communication and human language. Parallel efforts in birds and humans have taught us much about how vocal learning works on a behavioural and neurobiological level. Subsequent efforts have revealed a variety of cases among mammals in which experience also has a major influence on vocal repertoires. Janik and Slater (Anim. Behav.60, 1–11. (doi:10.1006/anbe.2000.1410)) introduced the distinction between vocal usage and production learning, providing a general framework to categorize how different types of learning influence vocalizations. This idea was built on by Petkov and Jarvis (Front. Evol. Neurosci.4, 12. (doi:10.3389/fnevo.2012.00012)) to emphasize a more continuous distribution between limited and more complex vocal production learners. Yet, with more studies providing empirical data, the limits of the initial frameworks become apparent. We build on these frameworks to refine the categorization of vocal learning in light of advances made since their publication and widespread agreement that vocal learning is not a binary trait. We propose a novel classification system, based on the definitions by Janik and Slater, that deconstructs vocal learning into key dimensions to aid in understanding the mechanisms involved in this complex behaviour. We consider how vocalizations can change without learning, and a usage learning framework that considers context specificity and timing. We identify dimensions of vocal production learning, including the copying of auditory models (convergence/divergence on model sounds, accuracy of copying), the degree of change (type and breadth of learning) and timing (when learning takes place, the length of time it takes and how long it is retained). We consider grey areas of classification and current mechanistic understanding of these behaviours. Our framework identifies research needs and will help to inform neurobiological and evolutionary studies endeavouring to uncover the multi-dimensional nature of vocal learning. This article is part of the theme issue ‘Vocal learning in animals and humans’.

The study of vocal production learning in birds is heavily biased towards oscine songbirds, making the songbird model the reference for comparative studies. However, as vocal learning was probably ancestral in songbirds, interspecific variations might all be variations on a single theme and need not be representative of the nature and characteristics of vocal learning in other bird groups. To assess the possible mechanisms of vocal learning and its evolution therefore requires knowledge about independently evolved incidences of vocal learning. This review examines the presence and nature of vocal production learning in non-songbirds. Using a broad definition of vocal learning and a comparative phylogenetic framework, I evaluate the evidence for vocal learning and its characteristics in non-oscine birds, including well-known vocal learners such as parrots and hummingbirds but also (putative) cases from other taxa. Despite the sometimes limited evidence, it is clear that vocal learning occurs in a range of different, non-related, taxa and can be caused by a variety of mechanisms. It is more widespread than often realized, calling for more systematic studies. Examining this variation may provide a window onto the evolution of vocal learning and increase the value of comparative research for understanding vocal learning in humans. This article is part of the theme issue ‘Vocal learning in animals and humans’.

Acquiring vocalizations by learning them from other individuals is only known from a limited number of animal groups. For birds, oscine and some suboscine songbirds, parrots and hummingbirds demonstrate this ability. Here, we provide evidence for vocal learning in a member of a basal clade of the avian phylogeny: the Australian musk duck (Biziura lobata). A hand-reared individual imitated a slamming door and a human voice, and a female-reared individual imitated Pacific black duck quacks. These sounds have been described before, but were never analysed in any detail and went so far unnoticed by researchers of vocal learning. The imitations were produced during the males' advertising display. The hand-reared male used at least three different vocalizations in the display context, with each one produced in the same stereotyped and repetitive structure as the normal display sounds. Sounds of different origins could be combined in one vocalization and at least some of the imitations were memorized at an early age, well before they were produced later in life. Together with earlier observations of vocal differences between populations and deviant vocalizations in captive-reared individuals, these observations demonstrate the presence of advanced vocal learning at a level comparable to that of songbirds and parrots. We discuss the rearing conditions that may have given rise to the imitations and suggest that the structure of the duck vocalizations indicates a quite sophisticated and flexible control over the vocal production mechanism. The observations support the hypothesis that vocal learning in birds evolved in several groups independently rather than evolving once with several losses. This article is part of the theme issue ‘Vocal learning in animals and humans’.

Rhythmic behaviour is ubiquitous in both human and non-human animals, but it is unclear whether the cognitive mechanisms underlying the specific rhythmic behaviours observed in different species are related. Laboratory experiments combined with highly controlled stimuli and tasks can be very effective in probing the cognitive architecture underlying rhythmic abilities. Rhythmic abilities have been examined in the laboratory with explicit and implicit perception tasks, and with production tasks, such as sensorimotor synchronization, with stimuli ranging from isochronous sequences of artificial sounds to human music. Here, we provide an overview of experimental findings on rhythmic abilities in human and non-human animals, while critically considering the wide variety of paradigms used. We identify several gaps in what is known about rhythmic abilities. Many bird species have been tested on rhythm perception, but research on rhythm production abilities in the same birds is lacking. By contrast, research in mammals has primarily focused on rhythm production rather than perception. Many experiments also do not differentiate between possible components of rhythmic abilities, such as processing of single temporal intervals, rhythmic patterns, a regular beat or hierarchical metrical structures. For future research, we suggest a careful choice of paradigm to aid cross-species comparisons, and a critical consideration of the multifaceted abilities that underlie rhythmic behaviour. This article is part of the theme issue ‘Synchrony and rhythm interaction: from the brain to behavioural ecology’.