A compact statistical model of the song syntax in Bengalese finch

Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history. Here we analyze the song syntax in a Bengalese finch. We show that the Markov model fails to capture the statistical properties of the syllable sequences. Instead, a state transition model that accurately describes the statistics of the syllable sequences includes adaptation of the self-transition probabilities when states are repeatedly revisited, and allows associations of more than one state to the same syllable. Such a model does not increase the model complexity significantly. Mathematically, the model is a partially observable Markov model with adaptation (POMMA). The success of the POMMA supports the branching chain network hypothesis of how syntax is controlled within the premotor song nucleus HVC, and suggests that adaptation and many-to-one mapping from neural substrates to syllables are important features of the neural control of complex song syntax

Cannabinoid exposure during zebra finch sensorimotor vocal learning persistently alters expression of endocannabinoid signaling elements and acute agonist responsiveness

<p>Abstract</p> <p>Background</p> <p>Previously we have found that cannabinoid treatment of zebra finches during sensorimotor stages of vocal development alters song patterns produced in adulthood. Such persistently altered behavior must be attributable to changes in physiological substrates responsible for song. We are currently working to identify the nature of such physiological changes, and to understand how they contribute to altered vocal learning. One possibility is that developmental agonist exposure results in altered expression of elements of endocannabinoid signaling systems. To test this hypothesis we have studied effects of the potent cannabinoid receptor agonist WIN55212-2 (WIN) on endocannabinoid levels and densities of CB₁immunostaining in zebra finch brain.</p> <p>Results</p> <p>We found that late postnatal WIN treatment caused a long-term global disregulation of both levels of the endocannabinoid, 2-arachidonyl glycerol (2-AG) and densities of CB₁immunostaining across brain regions, while repeated cannabinoid treatment in adults produced few long-term changes in the endogenous cannabinoid system.</p> <p>Conclusions</p> <p>Our findings indicate that the zebra finch endocannabinoid system is particularly sensitive to exogenous agonist exposure during the critical period of song learning and provide insight into susceptible brain areas.</p

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

Bilateral Multi-Electrode Neurophysiological Recordings Coupled to Local Pharmacology in Awake Songbirds

Here we describe a protocol for bilateral multielectrode neurophysiological recordings during intracerebral pharmacological manipulations in awake songbirds. This protocol encompasses fitting adult animals with head-posts and recording chambers, and acclimating them to periods of restraint. The adaptation period is followed by bilateral penetrations of multiple electrodes to obtain acute, sensory-driven neurophysiological responses before versus during the application of pharmacological agents of interest. These local manipulations are achieved by simultaneous and restricted drug infusions carried out independently for each hemisphere. We have used this protocol to elucidate how neurotransmitter and neuroendocrine systems shape the auditory and perceptual processing of natural, learned communication signals. However, this protocol can be used to explore the neurochemical basis of sensory processing in other small vertebrates. Representative results and troubleshooting of key steps of this protocol are presented. Following the animal\u27s recovery from head-post and recording chamber implantation surgery, the length of the procedure is 2 d

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 processing of natural sounds

Natural sounds include animal vocalizations, environmental sounds such as wind, water and fire noises and non-vocal sounds made by animals and humans for communication. These natural sounds have characteristic statistical properties that make them perceptually salient and that drive auditory neurons in optimal regimes for information transmission.Recent advances in statistics and computer sciences have allowed neuro-physiologists to extract the stimulus-response function of complex auditory neurons from responses to natural sounds. These studies have shown a hierarchical processing that leads to the neural detection of progressively more complex natural sound features and have demonstrated the importance of the acoustical and behavioral contexts for the neural responses.High-level auditory neurons have shown to be exquisitely selective for conspecific calls. This fine selectivity could play an important role for species recognition, for vocal learning in songbirds and, in the case of the bats, for the processing of the sounds used in echolocation. Research that investigates how communication sounds are categorized into behaviorally meaningful groups (e.g. call types in animals, words in human speech) remains in its infancy.Animals and humans also excel at separating communication sounds from each other and from background noise. Neurons that detect communication calls in noise have been found but the neural computations involved in sound source separation and natural auditory scene analysis remain overall poorly understood. Thus, future auditory research will have to focus not only on how natural sounds are processed by the auditory system but also on the computations that allow for this processing to occur in natural listening situations.The complexity of the computations needed in the natural hearing task might require a high-dimensional representation provided by ensemble of neurons and the use of natural sounds might be the best solution for understanding the ensemble neural code