Literature DB >> 19515949

Inhibition and recurrent excitation in a computational model of sparse bursting in song nucleus HVC.

Leif Gibb1, Timothy Q Gentner, Henry D I Abarbanel.   

Abstract

The telencephalic premotor nucleus HVC is situated at a critical point in the pattern-generating premotor circuitry of oscine songbirds. A striking feature of HVC's premotor activity is that its projection neurons burst extremely sparsely. Here we present a computational model of HVC embodying several central hypotheses: 1) sparse bursting is generated in bistable groups of recurrently connected robust nucleus of the arcopallium (RA)-projecting (HVCRA) neurons; 2) inhibitory interneurons terminate bursts in the HVCRA groups; and 3) sparse sequences of bursts are generated by the propagation of waves of bursting activity along networks of HVCRA neurons. Our model of sparse bursting places HVC in the context of central pattern generators and cortical networks using inhibition, recurrent excitation, and bistability. Importantly, the unintuitive result that inhibitory interneurons can precisely terminate the bursts of HVCRA groups while showing relatively sustained activity throughout the song is made possible by a specific constraint on their connectivity. We use the model to make novel predictions that can be tested experimentally.

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Year:  2009        PMID: 19515949      PMCID: PMC2746786          DOI: 10.1152/jn.00670.2007

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  57 in total

1.  Stable propagation of synchronous spiking in cortical neural networks.

Authors:  M Diesmann; M O Gewaltig; A Aertsen
Journal:  Nature       Date:  1999-12-02       Impact factor: 49.962

2.  Fate of new neurons in adult canary high vocal center during the first 30 days after their formation.

Authors:  J R Kirn; Y Fishman; K Sasportas; A Alvarez-Buylla; F Nottebohm
Journal:  J Comp Neurol       Date:  1999-08-30       Impact factor: 3.215

3.  Targeted neuronal death affects neuronal replacement and vocal behavior in adult songbirds.

Authors:  C Scharff; J R Kirn; M Grossman; J D Macklis; F Nottebohm
Journal:  Neuron       Date:  2000-02       Impact factor: 17.173

Review 4.  Stereological methods for estimating the total number of neurons and synapses: issues of precision and bias.

Authors:  M J West
Journal:  Trends Neurosci       Date:  1999-02       Impact factor: 13.837

5.  A quantitative description of membrane current and its application to conduction and excitation in nerve.

Authors:  A L HODGKIN; A F HUXLEY
Journal:  J Physiol       Date:  1952-08       Impact factor: 5.182

6.  Dynamical model of birdsong maintenance and control.

Authors:  Henry D I Abarbanel; Sachin S Talathi; Gabriel Mindlin; Misha Rabinovich; Leif Gibb
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2004-11-22

7.  Brain stem feedback in a computational model of birdsong sequencing.

Authors:  Leif Gibb; Timothy Q Gentner; Henry D I Abarbanel
Journal:  J Neurophysiol       Date:  2009-06-24       Impact factor: 2.714

8.  Electrophysiological characteristics of classes of neuron in the HVc of the zebra finch.

Authors:  M Kubota; I Taniguchi
Journal:  J Neurophysiol       Date:  1998-08       Impact factor: 2.714

9.  Individual variation in neuron number predicts differences in the propensity for avian vocal imitation.

Authors:  B C Ward; E J Nordeen; K W Nordeen
Journal:  Proc Natl Acad Sci U S A       Date:  1998-02-03       Impact factor: 11.205

10.  Multiple cell types distinguished by physiological, pharmacological, and anatomic properties in nucleus HVc of the adult zebra finch.

Authors:  P Dutar; H M Vu; D J Perkel
Journal:  J Neurophysiol       Date:  1998-10       Impact factor: 2.714

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  24 in total

1.  Serotonin, via HTR2 receptors, excites neurons in a cortical-like premotor nucleus necessary for song learning and production.

Authors:  William E Wood; Peter V Lovell; Claudio V Mello; David J Perkel
Journal:  J Neurosci       Date:  2011-09-28       Impact factor: 6.167

2.  Brain stem feedback in a computational model of birdsong sequencing.

Authors:  Leif Gibb; Timothy Q Gentner; Henry D I Abarbanel
Journal:  J Neurophysiol       Date:  2009-06-24       Impact factor: 2.714

3.  Interplay of inhibition and excitation shapes a premotor neural sequence.

Authors:  Georg Kosche; Daniela Vallentin; Michael A Long
Journal:  J Neurosci       Date:  2015-01-21       Impact factor: 6.167

4.  Independent premotor encoding of the sequence and structure of birdsong in avian cortex.

Authors:  Mark J Basista; Kevin C Elliott; Wei Wu; Richard L Hyson; Richard Bertram; Frank Johnson
Journal:  J Neurosci       Date:  2014-12-10       Impact factor: 6.167

Review 5.  Breathtaking Songs: Coordinating the Neural Circuits for Breathing and Singing.

Authors:  Marc F Schmidt; Franz Goller
Journal:  Physiology (Bethesda)       Date:  2016-11-01

6.  Model of the songbird nucleus HVC as a network of central pattern generators.

Authors:  Eve Armstrong; Henry D I Abarbanel
Journal:  J Neurophysiol       Date:  2016-08-17       Impact factor: 2.714

7.  Morphological characterization of HVC projection neurons in the zebra finch (Taeniopygia guttata).

Authors:  Sam E Benezra; Rajeevan T Narayanan; Robert Egger; Marcel Oberlaender; Michael A Long
Journal:  J Comp Neurol       Date:  2018-04-16       Impact factor: 3.215

8.  Somatostatin-Expressing Interneurons Enable and Maintain Learning-Dependent Sequential Activation of Pyramidal Neurons.

Authors:  Avital Adler; Ruohe Zhao; Myung Eun Shin; Ryohei Yasuda; Wen-Biao Gan
Journal:  Neuron       Date:  2019-02-18       Impact factor: 17.173

Review 9.  At the interface of the auditory and vocal motor systems: NIf and its role in vocal processing, production and learning.

Authors:  Brian Lewandowski; Alexei Vyssotski; Richard H R Hahnloser; Marc Schmidt
Journal:  J Physiol Paris       Date:  2013-04-17

10.  HTR2 receptors in a songbird premotor cortical-like area modulate spectral characteristics of zebra finch song.

Authors:  William E Wood; Thomas K Roseberry; David J Perkel
Journal:  J Neurosci       Date:  2013-02-13       Impact factor: 6.167

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