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      Variability of inter-syllable gaps challenges the branched-chain model of sequence production in Bengalese finches

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      1 , 3 , 2 , , 1 , 2
      BMC Neuroscience
      BioMed Central
      Twenty First Annual Computational Neuroscience Meeting: CNS*2012
      21-26 July 2012

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          Abstract

          Songbirds have emerged as a premier model system for studying how brain circuits learn and produce complex action sequences. The adult song of the most widely studied songbird, the zebra finch (ZF), consists of repeats of a stereotyped sequence of vocal gestures known as syllables. These songs are incredibly precise, with individual syllables and inter-syllable gaps varying in length by roughly 5% (std. dev.). Electrophysiological recordings in singing birds reveal that song related neural activity is also precise, with individual neurons in the premotor nucleus HVC producing one burst of action potentials per song sequence, locked to song acoustics with sub-millisecond precision [1]. This precision and reliability has led to the suggestion that the HVC circuit is organized as a synfire chain, with activity propagating down a chain-like network of strongly connected groups of neurons [2]. Here we examine the songs of a closely related species, the Bengalese finch (BF). These birds also learn sequences of highly stereotyped syllables. However, sequencing is variable and includes ‘branching’ in which some song syllables can be followed by more than one (2-4) subsequent syllables (fig1A). Given the many similarities between species, it has been hypothesized that variable sequencing in BF is accomplished by a branched synfire network in HVC [3] (fig1B). Such a model suggests that timing precision in BFs should be similar to that of ZFs, perhaps with a bit of added variability due to the competition between branches. However, this added variability should not be longer than the maximum latency between successive links in the synfire chain (~20 msec). Figure 1 Variable sequencing of Bengalese finch song A. Transition diagram for single BF; strength of the arrow is proportional to transition probability. B. Branched synfire chain model. C. Median and inter-quartile range of coefficient of variation for BF gaps, BFgaps without branching (transition prob = 1), BF syls, and ZF gaps and syls. To test this, we measured the durations of both syllables and inter-syllable gaps in a large sample of BF songs (32 birds, 52,451 transitions between 303 unique syllable pairs; syllables were hand labeled by visual inspection and durations were determined by a hand-set threshold optimized for each bird.) Overall, the mean and coefficient of variation (CV) for BF inter-syllable gap durations were qualitatively more variable than for BF syllables, ZF syllables or ZF gaps, even at syllable transitions that were not branched (fig 1C). These results contradict the simplest branched synfire chain model of variable sequencing in BFs, and provide significant challenges for more general models based on this idea.

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          Generating variable birdsong syllable sequences with branching chain networks in avian premotor nucleus HVC.

          Z Jin (2009)
          Songs of songbird species such as Bengalese finch consist of sequences of syllables. While syllables are temporally stereotypical, syllable sequences can vary and follow complex, probabilistic transition rules. Recent experiments and computational models suggest that a syllable is encoded in a chain network of projection neurons in premotor nucleus HVC (proper name). Precisely timed spikes propagate along the chain, driving vocalization of the syllable through downstream nuclei. However, the neural basis of the probabilistic transitions between the syllables is not understood. Here we propose that variable syllable sequences are generated through spike propagations in a network in HVC in which the syllable-encoding chain networks are connected into a branching chain pattern. The neurons mutually inhibit each other through the inhibitory HVC interneurons, and are driven by external inputs from nuclei upstream of HVC. At a branching point that connects the final group of a chain to the first groups of several chains, the spike activity selects one branch to continue the propagation. The selection is probabilistic, and is due to the winner-take-all mechanism mediated by the inhibition and noise. The transitions between the chains are Markovian. If the same syllable can be driven by multiple chains, the generated syllable sequences are statistically described by partially observable Markov models. We suggest that the syntax of birdsong syllable sequences is embedded in the connection patterns of HVC projection neurons.
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            Author and article information

            Conference
            BMC Neurosci
            BMC Neurosci
            BMC Neuroscience
            BioMed Central
            1471-2202
            2012
            16 July 2012
            : 13
            : Suppl 1
            : P19
            Affiliations
            [1 ]Department of Physiology, UCSF, San Francisco, CA 94143, USA
            [2 ]Biology Department and Neurosciences Institute, UTSA, San Antonio, Texas, 78249, USA
            [3 ]Department of Neurosurgery, UCSF, San Francisco, CA, 94143, USA
            Article
            1471-2202-13-S1-P19
            10.1186/1471-2202-13-S1-P19
            3403597
            52e6213f-f284-442f-bc5d-552f014dc17c
            Copyright ©2012 Bouchard et al; licensee BioMed Central Ltd.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            Twenty First Annual Computational Neuroscience Meeting: CNS*2012
            Decatur, GA, USA
            21-26 July 2012
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            Neurosciences
            Neurosciences

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