Song-like activation of syringeal and respiratory muscles during sleep in canaries.

Sleep replay activity involves the reactivation of brain structures with patterns similar to those observed during waking behavior. In this study, we demonstrate that adult male canaries exhibit spontaneous, song-like peripheral reactivation during night sleep. Our findings include: (1) the presence of activity in respiratory muscles, leading to song-like air sac pressure patterns of low amplitude, (2) the simultaneous occurrence of respiratory replay events and reactivation of syringeal muscles, and (3) the reactivation of syringeal muscles without concurrent respiratory system activity.

Response of wild songbirds to songs synthesized with a low-dimensional model.

In this work, we used a dynamical system derived from an avian vocal production model to generate synthetic songs that mimic the Zonotrichia capensis songs. We confirmed that these synthetic renditions elicited behavioral responses similar to those evoked by real songs in wild songbirds of the same species. Specifically, we observed an increase in the singing rate of individual birds when a playback device was introduced into their territories.

Synthesizing avian dreams.

During sleep, sporadically, it is possible to find neural patterns of activity in areas of the avian brain that are activated during the generation of the song. It has recently been found that in the vocal muscles of a sleeping bird, it is possible to detect activity patterns during these silent replays. In this work, we employ a dynamical systems model for song production in suboscine birds in order to translate the vocal muscles activity during sleep into synthetic songs.

The dynamics behind diversity in suboscine songs.

Vocal behavior plays a crucial evolutionary role. In the case of birds, song is critically important in courtship, male-male competition and other key behaviors linked to reproduction. However, under natural conditions, a variety of avian species live in close proximity and share an 'acoustic landscape'.

Multifractal analysis of birdsong and its correlation structure.

The time series recordings of typical songs of songbirds exhibit highly complex and structured behavior, which is characteristic of their species and stage of development, and need to be analyzed by methods that can uncover their correlation structure. Here we analyze a typical song of a canary using Hurst exponents and multifractal analysis, which uncovers the correlation structure of typical song segments. These are then compared with the corresponding quantities from shuffled data, which destroys the temporal correlations and iterative amplitude-adjusted Fourier transform (IAAFT) data.

Birds breathe at an aerodynamic resonance.

We present a dynamical model for the avian respiratory system and report the measurement of its variables in normal breathing canaries (Serinus canaria). Fitting the parameters of the model, we are able to show that the birds in our study breathe at an aerodynamic resonance of their respiratory system. For different respiratory regimes, such as singing, where rapid respiratory gestures are used, the nonlinearities of the model lead to a shift in its resonances toward higher frequency values.

Neural oscillations are locked to birdsong rhythms in canaries.

How vocal communication signals are represented in the cortex is a major challenge for behavioural neuroscience. Beyond a descriptive code, it is relevant to unveil the dynamical mechanism responsible for the neural representation of auditory stimuli. In this work, we report evidence of synchronous neural activity in nucleus HVC, a telencephalic area of canaries (Serinus canaria), in response to auditory playback of the bird's own song.

Synthetic Birdsongs as a Tool to Induce, and Iisten to, Replay Activity in Sleeping Birds.

Birdsong is a complex vocal behavior, which emerges out of the interaction between a nervous system and a highly nonlinear vocal device, the syrinx. In this work we discuss how low dimensional dynamical systems, interpretable in terms of the biomechanics involved, are capable of synthesizing realistic songs. We review the experimental and conceptual steps that lead to the formulation of low dimensional dynamical systems for the song system and describe the tests that quantify their success.

Replay of innate vocal patterns during night sleep in suboscines.

Activation of forebrain circuitry during sleep has been variably characterized as 'pre- or replay' and has been linked to memory consolidation. The evolutionary origins of this mechanism, however, are unknown. Sleep activation of the sensorimotor pathways of learned birdsong is a particularly useful model system because the muscles controlling the vocal organ are activated, revealing syringeal activity patterns for direct comparison with those of daytime vocal activity.

Dynamics behind rough sounds in the song of the Pitangus sulphuratus.

The complex vocalizations found in different bird species emerge from the interplay between morphological specializations and neuromuscular control mechanisms. In this work we study the dynamical mechanisms used by a nonlearner bird from the Americas, the suboscine Pitangus sulphuratus, in order to achieve a characteristic timbre of some of its vocalizations. By measuring syringeal muscle activity, air sac pressure, and sound as the bird sings, we are able to show that the birds of this species manage to lock the frequency difference between two sound sources.

The structure of reconstructed flows in latent spaces.

Reconstructing the flow of a dynamical system from experimental data has been a key tool in the study of nonlinear problems. It allows one to discover the equations ruling the dynamics of a system as well as to quantify its complexity. In this work, we study the topology of the flow reconstructed by autoencoders, a dimensionality reduction method based on deep neural networks that has recently proved to be a very powerful tool for this task.

Dynamical model for the neural activity of singing Serinus canaria.

Vocal production in songbirds is a key topic regarding the motor control of a complex, learned behavior. Birdsong is the result of the interaction between the activity of an intricate set of neural nuclei specifically dedicated to song production and learning (known as the "song system"), the respiratory system and the vocal organ. These systems interact and give rise to precise biomechanical motor gestures which result in song production.

Unusual Avian Vocal Mechanism Facilitates Encoding of Body Size.

In this work we study the sound production mechanism of the raspy sounding song of the white-tipped plantcutter (Phytotoma rutila), a species with a most unusual vocalization. The biomechanics involved in the production of this song, and scaling arguments, allowed us to predict the precise way in which body size is encoded in its vocalizations. We tested this prediction through acoustic analysis of recorded songs, computational modeling of its unusual vocal strategy, and inspection of museum specimens captured across southeastern and south-central South America.

Gating related activity in a syringeal muscle allows the reconstruction of zebra finches songs.

Birdsong production involves the simultaneous and precise control of a set of muscles that change the configuration and dynamics of the vocal organ. Although it has been reported that each one of the different muscles is primarily involved in the control of one acoustic feature, recent advances have shown that they act synergistically to achieve the dynamical state necessary for phonation. In this work, we present a set of criteria that allow the extraction of gating-related information from the electromyographic activity of the syringealis ventralis muscle, a muscle that has been shown to be involved in frequency modulation.

Syringeal EMGs and synthetic stimuli reveal a switch-like activation of the songbird's vocal motor program.

The coordination of complex vocal behaviors like human speech and oscine birdsong requires fine interactions between sensory and motor programs, the details of which are not completely understood. Here, we show that in sleeping male zebra finches (), the activity of the song system selectively evoked by playbacks of their own song can be detected in the syrinx. Electromyograms (EMGs) of a syringeal muscle show playback-evoked patterns strikingly similar to those recorded during song execution, with preferred activation instants within the song.

Towards an integrated view of vocal development.

Vocal development is usually studied from the perspective of neuroscience. In this issue, Zhang and Ghazanfar propose a way in which body growth might condition the process. They study the vocalizations of marmoset infants with a wide range of techniques that include computational models and experiments that mimic growth reversal.

From electromyographic activity to frequency modulation in zebra finch song.

Behavior emerges from the interaction between the nervous system and peripheral devices. In the case of birdsong production, a delicate and fast control of several muscles is required to control the configuration of the syrinx (the avian vocal organ) and the respiratory system. In particular, the syringealis ventralis muscle is involved in the control of the tension of the vibrating labia and thus affects the frequency modulation of the sound.

Adult zebra finches rehearse highly variable song patterns during sleep.

Brain activity during sleep is fairly ubiquitous and the best studied possible function is a role in memory consolidation, including motor memory. One suggested mechanism of how neural activity effects these benefits is through reactivation of neurons in patterns resembling those of the preceding experience. The specific patterns of motor activation replayed during sleep are largely unknown for any system.

Nonlinear dynamics in the study of birdsong.

Birdsong, a rich and complex behavior, is a stellar model to understand a variety of biological problems, from motor control to learning. It also enables us to study how behavior emerges when a nervous system, a biomechanical device and the environment interact. In this review, I will show that many questions in the field can benefit from the approach of nonlinear dynamics, and how birdsong can inspire new directions for research in dynamics.

Evolution of Vocal Diversity through Morphological Adaptation without Vocal Learning or Complex Neural Control.

The evolution of complex behavior is driven by the interplay of morphological specializations and neuromuscular control mechanisms [1-3], and it is often difficult to tease apart their respective contributions. Avian vocal learning and associated neural adaptations are thought to have played a major role in bird diversification [4-8], whereas functional significance of substantial morphological diversity of the vocal organ remains largely unexplored. Within the most species-rich order, Passeriformes, "tracheophones" are a suboscine group that, unlike their oscine sister taxon, does not exhibit vocal learning [9] and is thought to phonate with tracheal membranes [10, 11] instead of the two independent sources found in other passerines [12-14].

Temperature manipulation of neuronal dynamics in a forebrain motor control nucleus.

Different neuronal types within brain motor areas contribute to the generation of complex motor behaviors. A widely studied songbird forebrain nucleus (HVC) has been recognized as fundamental in shaping the precise timing characteristics of birdsong. This is based, among other evidence, on the stretching and the "breaking" of song structure when HVC is cooled.

From perception to action in songbird production: dynamics of a whole loop.

Birdsong emerges when a set of highly interconnected brain areas manage to generate a complex output. This consists of precise respiratory rhythms as well as motor instructions to control the vocal organ configuration. In this way, during birdsong production, dedicated cortical areas interact with life-supporting ones in the brainstem, such as the respiratory nuclei.

An integrated model for motor control of song in Serinus canaria.

Birdsong is a learned motor behavior controlled by an interconnected structure of neural nuclei. This pathway is bilaterally organized, with anatomically indistinguishable structures in each brain hemisphere. In this work, we present a computational model whose variables are the average activities of different neural nuclei of the song system of oscine birds.

Average activity of excitatory and inhibitory neural populations.

We develop an extension of the Ott-Antonsen method [E. Ott and T. M.

Difference between the vocalizations of two sister species of pigeons explained in dynamical terms.

Vocal communication is an unique example, where the nonlinear nature of the periphery can give rise to complex sounds even when driven by simple neural instructions. In this work we studied the case of two close-related bird species, Patagioenas maculosa and Patagioenas picazuro, whose vocalizations differ only in the timbre. The temporal modulation of the fundamental frequency is similar in both cases, differing only in the existence of sidebands around the fundamental frequency in the P.