A reafferent and feed-forward model of song syntax generation in the Bengalese finch

Adult Bengalese finches generate a variable song that obeys a distinct and individual syntax. The syntax is gradually lost over a period of days after deafening and is recovered when hearing is restored. We present a spiking neuronal network model of the song syntax generation and its loss, based on the assumption that the syntax is stored in reafferent connections from the auditory to the motor control area. Propagating synfire activity in the HVC codes for individual syllables of the song and priming signals from the auditory network reduce the competition between syllables to allow only those transitions that are permitted by the syntax. Both imprinting of song syntax within HVC and the interaction of the reafferent signal with an efference copy of the motor command are sufficient to explain the gradual loss of syntax in the absence of auditory feedback. The model also reproduces for the first time experimental findings on the influence of altered auditory feedback on the song syntax generation, and predicts song- and species-specific low frequency components in the LFP. This study illustrates how sequential compositionality following a defined syntax can be realized in networks of spiking neurons

Stepwise acquisition of vocal combinatorial capacity in songbirds and human infants

Human language, as well as birdsong, relies on the ability to arrange vocal elements in novel sequences. However, little is known about the ontogenetic origin of this capacity. We tracked the development of vocal combinatorial capacity in three species of vocal learners, combining an experimental approach in zebra finches with an analysis of natural development of vocal transitions in Bengalese finches and pre-lingual human infants and found a common, stepwise pattern of acquiring vocal transitions across species. In our first study, juvenile zebra finches were trained to perform one song and then the training target was altered, prompting the birds to swap syllable order, or insert a new syllable into a string. All birds solved these permutation tasks in a series of steps, gradually approximating the target sequence by acquiring novel pair-wise syllable transitions, sometimes too slowly to fully accomplish the task. Similarly, in the more complex songs of Bengalese finches, branching points and bidirectional transitions in song-syntax were acquired in a stepwise manner, starting from a more restrictive set of vocal transitions. The babbling of pre-lingual human infants revealed a similar developmental pattern: instead of a single developmental shift from reduplicated to variegated babbling (i.e., from repetitive to diverse sequences), we observed multiple shifts, where each novel syllable type slowly acquired a diversity of pair-wise transitions, asynchronously over development. Collectively, these results point to a common generative process that is conserved across species, suggesting that the long-noted gap between perceptual versus motor combinatorial capabilities in human infants1 may arise from the challenges in constructing new pair-wise transitions

An adapting auditory-motor feedback loop can contribute to generating vocal repetition

Consecutive repetition of actions is common in behavioral sequences. Although integration of sensory feedback with internal motor programs is important for sequence generation, if and how feedback contributes to repetitive actions is poorly understood. Here we study how auditory feedback contributes to generating repetitive syllable sequences in songbirds. We propose that auditory signals provide positive feedback to ongoing motor commands, but this influence decays as feedback weakens from response adaptation during syllable repetitions. Computational models show that this mechanism explains repeat distributions observed in Bengalese finch song. We experimentally confirmed two predictions of this mechanism in Bengalese finches: removal of auditory feedback by deafening reduces syllable repetitions; and neural responses to auditory playback of repeated syllable sequences gradually adapt in sensory-motor nucleus HVC. Together, our results implicate a positive auditory-feedback loop with adaptation in generating repetitive vocalizations, and suggest sensory adaptation is important for feedback control of motor sequences

Stochastic dynamics and delta-band oscillations in clustered spiking networks

Following experimental measurements of clustered connectivity in the cortex, recent studies have found that clustering connections in simulated spiking networks causes transitions between high and low firing-rate states in subgroups of neurons. An open question is to what extent the sequence of transitions in such networks can be related to existing statistical and mechanical models of sequence generation. In this thesis we present several studies of the relationship between connection structure and network dynamics in balanced spiking networks. We investigate which qualities of the network connection matrix support the generation of state sequences, and which properties determine the specific structure of transitions between states. We find that adding densely overlapping clusters with equal levels of recurrent connectivity to a network with dense inhibition can produce sequential winner-takes-all dynamics in which high-activity states pass between correlated clusters. This activity is reflected in the power spectrum of spiking activity as a peak in the low-frequency delta range. We describe and verify sequence dynamics with a Markov chain framework, and compare them mechanically to “latching” models of sequence generation. Additionally we quantify the chaos of clustered networks and find that minimally separated states diverge in distinct stages. The results clarify the computational capabilities of clustered spiking networks and their relationship to experimental findings. We conclude that the results provide a supporting intermediate link between abstract models and biological instances of sequence generation

Network dynamics in the neural control of birdsong

Sequences of stereotyped actions are central to the everyday lives of humans and animals, from the kingfisher's dive to the performance of a piano concerto. Lashley asked how neural circuits managed this feat nearly 6 decades ago, and to this day it remains a fundamental question in neuroscience. Toward answering this question, vocal performance in the songbird was used as a model to study the performance of learned, stereotyped motor sequences. The first component of this work considers the song motor cortical zone HVC in the zebra finch, an area that sends precise timing signals to both the descending motor pathway, responsible for stereotyped vocal performance in the adult, and the basal ganglia, which is responsible for both motor variability and song learning. Despite intense interest in HVC, previous research has exclusively focused on describing the activity of small numbers of neurons recorded serially as the bird sings. To better understand HVC network dynamics, both single units and local field potentials were sampled across multiple electrodes simultaneously in awake behaving zebra finches. The local field potential and spiking data reveal a stereotyped spatio-temporal pattern of inhibition operating on a 30 ms time-scale that coordinates the neural sequences in principal cells underlying song. The second component addresses the resilience of the song circuit through cutting the motor cortical zone HVC in half along one axis. Despite this large-scale perturbation, the finch quickly recovers and sings a near-perfect song within a single day. These first two studies suggest that HVC is functionally organized to robustly generate neural dynamics that enable vocal performance. The final component concerns a statistical study of the complex, flexible songs of the domesticated canary. This study revealed that canary song is characterized by specific long-range correlations up to 7 seconds long-a time-scale more typical of human music than animal vocalizations. Thus, the neural sequences underlying birdsong must be capable of generating more structure and complexity than previously thought