Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies

A Potential Neural Substrate for Processing Functional Classes of Complex Acoustic Signals

Categorization is essential to all cognitive processes, but identifying the neural substrates underlying categorization processes is a real challenge. Among animals that have been shown to be able of categorization, songbirds are particularly interesting because they provide researchers with clear examples of categories of acoustic signals allowing different levels of recognition, and they possess a system of specialized brain structures found only in birds that learn to sing: the song system. Moreover, an avian brain nucleus that is analogous to the mammalian secondary auditory cortex (the caudo-medial nidopallium, or NCM) has recently emerged as a plausible site for sensory representation of birdsong, and appears as a well positioned brain region for categorization of songs. Hence, we tested responses in this non-primary, associative area to clear and distinct classes of songs with different functions and social values, and for a possible correspondence between these responses and the functional aspects of songs, in a highly social songbird species: the European starling. Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons. Most importantly, these differential responses corresponded to the functional classes of songs, with increasing activation from non-specific to species-specific and from species-specific to individual-specific sounds. These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members. Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech

Neural Correlates of Experience-Induced Deficits in Learned Vocal Communication

Songbirds are one of the few vertebrate groups (including humans) that evolved the ability to learn vocalizations. During song learning, social interactions with adult models are crucial and young songbirds raised without direct contacts with adults typically produce abnormal songs showing phonological and syntactical deficits. This raises the question of what functional representation of their vocalizations such deprived animals develop. Here we show that young starlings that we raised without any direct contact with adults not only failed to differentiate starlings' typical song classes in their vocalizations but also failed to develop differential neural responses to these songs. These deficits appear to be linked to a failure to acquire songs' functions and may provide a model for abnormal development of communicative skills, including speech

Functional MRI of Auditory Responses in the Zebra Finch Forebrain Reveals a Hierarchical Organisation Based on Signal Strength but Not Selectivity

BACKGROUND: Male songbirds learn their songs from an adult tutor when they are young. A network of brain nuclei known as the 'song system' is the likely neural substrate for sensorimotor learning and production of song, but the neural networks involved in processing the auditory feedback signals necessary for song learning and maintenance remain unknown. Determining which regions show preferential responsiveness to the bird's own song (BOS) is of great importance because neurons sensitive to self-generated vocalisations could mediate this auditory feedback process. Neurons in the song nuclei and in a secondary auditory area, the caudal medial mesopallium (CMM), show selective responses to the BOS. The aim of the present study is to investigate the emergence of BOS selectivity within the network of primary auditory sub-regions in the avian pallium. METHODS AND FINDINGS: Using blood oxygen level-dependent (BOLD) fMRI, we investigated neural responsiveness to natural and manipulated self-generated vocalisations and compared the selectivity for BOS and conspecific song in different sub-regions of the thalamo-recipient area Field L. Zebra finch males were exposed to conspecific song, BOS and to synthetic variations on BOS that differed in spectro-temporal and/or modulation phase structure. We found significant differences in the strength of BOLD responses between regions L2a, L2b and CMM, but no inter-stimuli differences within regions. In particular, we have shown that the overall signal strength to song and synthetic variations thereof was different within two sub-regions of Field L2: zone L2a was significantly more activated compared to the adjacent sub-region L2b. CONCLUSIONS: Based on our results we suggest that unlike nuclei in the song system, sub-regions in the primary auditory pallium do not show selectivity for the BOS, but appear to show different levels of activity with exposure to any sound according to their place in the auditory processing stream

A cortical motor nucleus drives the basal ganglia-recipient thalamus in singing birds

The pallido-recipient thalamus transmits information from the basal ganglia to the cortex and is critical for motor initiation and learning. Thalamic activity is strongly inhibited by pallidal inputs from the basal ganglia, but the role of nonpallidal inputs, such as excitatory inputs from cortex, remains unclear. We simultaneously recorded from presynaptic pallidal axon terminals and postsynaptic thalamocortical neurons in a basal ganglia–recipient thalamic nucleus that is necessary for vocal variability and learning in zebra finches. We found that song-locked rate modulations in the thalamus could not be explained by pallidal inputs alone and persisted following pallidal lesion. Instead, thalamic activity was likely driven by inputs from a motor cortical nucleus that is also necessary for singing. These findings suggest a role for cortical inputs to the pallido-recipient thalamus in driving premotor signals that are important for exploratory behavior and learning.National Institutes of Health (U.S.) (Grant R01DC009183)National Institutes of Health (U.S.) (Grant K99NS067062)Damon Runyon Cancer Research Foundation (Postdoctoral Fellowship)Charles A. King Trust (Postdoctoral Fellowship

Spatial competition shapes the dynamic mutational landscape of normal esophageal epithelium.

During aging, progenitor cells acquire mutations, which may generate clones that colonize the surrounding tissue. By middle age, normal human tissues, including the esophageal epithelium (EE), become a patchwork of mutant clones. Despite their relevance for understanding aging and cancer, the processes that underpin mutational selection in normal tissues remain poorly understood. Here, we investigated this issue in the esophageal epithelium of mutagen-treated mice. Deep sequencing identified numerous mutant clones with multiple genes under positive selection, including Notch1, Notch2 and Trp53, which are also selected in human esophageal epithelium. Transgenic lineage tracing revealed strong clonal competition that evolved over time. Clone dynamics were consistent with a simple model in which the proliferative advantage conferred by positively selected mutations depends on the nature of the neighboring cells. When clones with similar competitive fitness collide, mutant cell fate reverts towards homeostasis, a constraint that explains how selection operates in normal-appearing epithelium.This work was supported by grants from the Wellcome Trust to the Wellcome SangerInstitute (098051 and 296194) and Cancer Research UK Programme Grants to P.H.J.(C609/A17257 and C609/A27326). G.P. is supported by a Talento program fellowship from Comunidad de Madrid. B.A.H. and M.W.J.H. are supported by the MedicalResearch Council (Grant-in-Aid to the MRC Cancer unit grant no. MC_UU_12022/9 and NIRG to B.A.H. grant no. MR/S000216/1). M.W.J.H. acknowledges support fromthe Harrison Watson Fund at Clare College, Cambridge. B.A.H. acknowledges support from the Royal Society (grant no. UF130039). I.M. is funded by Cancer Research UK (C57387/A21777). S.D. benefited from the award of an ESPOD fellowship, 2018-21, from the Wellcome Sanger Institute and the European Bioinformatics Institute EMBL-EBI

Prosthetic Avian Vocal Organ Controlled by a Freely Behaving Bird Based on a Low Dimensional Model of the Biomechanical Periphery

Because of the parallels found with human language production and acquisition, birdsong is an ideal animal model to study general mechanisms underlying complex, learned motor behavior. The rich and diverse vocalizations of songbirds emerge as a result of the interaction between a pattern generator in the brain and a highly nontrivial nonlinear periphery. Much of the complexity of this vocal behavior has been understood by studying the physics of the avian vocal organ, particularly the syrinx. A mathematical model describing the complex periphery as a nonlinear dynamical system leads to the conclusion that nontrivial behavior emerges even when the organ is commanded by simple motor instructions: smooth paths in a low dimensional parameter space. An analysis of the model provides insight into which parameters are responsible for generating a rich variety of diverse vocalizations, and what the physiological meaning of these parameters is. By recording the physiological motor instructions elicited by a spontaneously singing muted bird and computing the model on a Digital Signal Processor in real-time, we produce realistic synthetic vocalizations that replace the bird's own auditory feedback. In this way, we build a bio-prosthetic avian vocal organ driven by a freely behaving bird via its physiologically coded motor commands. Since it is based on a low-dimensional nonlinear mathematical model of the peripheral effector, the emulation of the motor behavior requires light computation, in such a way that our bio-prosthetic device can be implemented on a portable platform

Characterization of Synaptically Connected Nuclei in a Potential Sensorimotor Feedback Pathway in the Zebra Finch Song System

Birdsong is a learned behavior that is controlled by a group of identified nuclei, known collectively as the song system. The cortical nucleus HVC (used as a proper name) is a focal point of many investigations as it is necessary for song production, song learning, and receives selective auditory information. HVC receives input from several sources including the cortical area MMAN (medial magnocellular nucleus of the nidopallium). The MMAN to HVC connection is particularly interesting as it provides potential sensorimotor feedback to HVC. To begin to understand the role of this connection, we investigated the physiological relation between MMAN and HVC activity with simultaneous multiunit extracellular recordings from these two nuclei in urethane anesthetized zebra finches. As previously reported, we found similar timing in spontaneous bursts of activity in MMAN and HVC. Like HVC, MMAN responds to auditory playback of the bird's own song (BOS), but had little response to reversed BOS or conspecific song. Stimulation of MMAN resulted in evoked activity in HVC, indicating functional excitation from MMAN to HVC. However, inactivation of MMAN resulted in no consistent change in auditory responses in HVC. Taken together, these results indicate that MMAN provides functional excitatory input to HVC but does not provide significant auditory input to HVC in anesthetized animals. We hypothesize that MMAN may play a role in motor reinforcement or coordination, or may provide modulatory input to the song system about the internal state of the animal as it receives input from the hypothalamus