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000019176 0247_ $$2DOI$$a10.1007/s10827-011-0318-z
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000019176 041__ $$aeng
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000019176 084__ $$2WoS$$aMathematical & Computational Biology
000019176 084__ $$2WoS$$aNeurosciences
000019176 1001_ $$0P:(DE-HGF)0$$aHanuschkin, A.$$b0
000019176 245__ $$aA reafferent and feed-forward model of song syntax generation in the Bengalese finch
000019176 260__ $$aDordrecht [u.a.]$$bSpringer Science + Business Media B.V$$c2011
000019176 300__ $$a509 - 532
000019176 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
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000019176 3367_ $$2BibTeX$$aARTICLE
000019176 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000019176 3367_ $$2DRIVER$$aarticle
000019176 440_0 $$025129$$aJournal of Computational Neuroscience$$v31$$y3
000019176 500__ $$3POF3_Assignment on 2016-02-29
000019176 500__ $$aPartially funded by DIP F1.2, BMBF Grant 01GQ0420 to BCCN Freiburg, EU Grant 15879 (FACETS), EU Grant 269921 (BrainScaleS), Helmholtz Alliance on Systems Biology (Germany), Next-Generation Supercomputer Project of MEXT (Japan), Neurex, and the Junior Professor Program of Baden-Wurttemberg. The authors would like to thank Jun Nishikawa and Kentaro Katahira for stimulating and fruitful discussions. The computations were conducted on the high performance computer cluster of the CNPSN group at RIKEN BSI, Wako, Japan.
000019176 520__ $$aAdult Bengalese finches generate a variable song that obeys a distinct and individual syntax. The syntax is gradually lost over a period of days after deafening and is recovered when hearing is restored. We present a spiking neuronal network model of the song syntax generation and its loss, based on the assumption that the syntax is stored in reafferent connections from the auditory to the motor control area. Propagating synfire activity in the HVC codes for individual syllables of the song and priming signals from the auditory network reduce the competition between syllables to allow only those transitions that are permitted by the syntax. Both imprinting of song syntax within HVC and the interaction of the reafferent signal with an efference copy of the motor command are sufficient to explain the gradual loss of syntax in the absence of auditory feedback. The model also reproduces for the first time experimental findings on the influence of altered auditory feedback on the song syntax generation, and predicts song- and species-specific low frequency components in the LFP. This study illustrates how sequential compositionality following a defined syntax can be realized in networks of spiking neurons.
000019176 536__ $$0G:(DE-Juel1)FUEK255$$2G:(DE-HGF)$$aNeurowissenschaften (FUEK255)$$cFUEK255$$x0
000019176 536__ $$0G:(DE-HGF)POF2-333$$a333 - Pathophysiological Mechanisms of Neurological and Psychiatric Diseases (POF2-333)$$cPOF2-333$$fPOF II$$x1
000019176 536__ $$0G:(EU-Grant)269921$$aBRAINSCALES - Brain-inspired multiscale computation in neuromorphic hybrid systems (269921)$$c269921$$fFP7-ICT-2009-6$$x2
000019176 588__ $$aDataset connected to Web of Science, Pubmed
000019176 65320 $$2Author$$aHVC
000019176 65320 $$2Author$$aReafferent
000019176 65320 $$2Author$$aFeed-forward network
000019176 65320 $$2Author$$aEfference copy
000019176 65320 $$2Author$$aSyntax generation
000019176 65320 $$2Author$$aSynfire chains
000019176 65320 $$2Author$$aBengalese finch
000019176 65320 $$2Author$$aSpike synchrony
000019176 65320 $$2Author$$aMotor control
000019176 65320 $$2Author$$aCompositionality
000019176 650_2 $$2MeSH$$aAction Potentials: physiology
000019176 650_2 $$2MeSH$$aAnimals
000019176 650_2 $$2MeSH$$aFeedback, Physiological
000019176 650_2 $$2MeSH$$aFemale
000019176 650_2 $$2MeSH$$aFinches: physiology
000019176 650_2 $$2MeSH$$aHigh Vocal Center: physiology
000019176 650_2 $$2MeSH$$aMale
000019176 650_2 $$2MeSH$$aModels, Neurological
000019176 650_2 $$2MeSH$$aNerve Net: physiology
000019176 650_2 $$2MeSH$$aNeural Networks (Computer)
000019176 650_2 $$2MeSH$$aSemantics
000019176 650_2 $$2MeSH$$aVocalization, Animal: physiology
000019176 650_7 $$2WoSType$$aJ
000019176 7001_ $$0P:(DE-Juel1)144174$$aDiesmann, M.$$b1$$uFZJ
000019176 7001_ $$0P:(DE-Juel1)151166$$aMorrison, A.$$b2$$uFZJ
000019176 773__ $$0PERI:(DE-600)1473055-8$$a10.1007/s10827-011-0318-z$$gVol. 31, p. 509 - 532$$p509 - 532$$q31<509 - 532$$tJournal of computational neuroscience$$v31$$x0929-5313$$y2011
000019176 8567_ $$2Pubmed Central$$uhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3232349
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000019176 9141_ $$y2011
000019176 9132_ $$0G:(DE-HGF)POF3-579H$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vAddenda$$x0
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000019176 9201_ $$0I:(DE-Juel1)INM-6-20090406$$gINM$$kINM-6$$lSystembiologie und Neuroinformatik$$x0
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