%0 Journal Article
%A Hanuschkin, A.
%A Diesmann, M.
%A Morrison, A.
%T A reafferent and feed-forward model of song syntax generation in the Bengalese finch
%J Journal of computational neuroscience
%V 31
%@ 0929-5313
%C Dordrecht [u.a.]
%I Springer Science + Business Media B.V
%M PreJuSER-19176
%P 509 - 532
%D 2011
%Z Partially 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.
%X 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.
%K Action Potentials: physiology
%K Animals
%K Feedback, Physiological
%K Female
%K Finches: physiology
%K High Vocal Center: physiology
%K Male
%K Models, Neurological
%K Nerve Net: physiology
%K Neural Networks (Computer)
%K Semantics
%K Vocalization, Animal: physiology
%K J (WoSType)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:21404048
%2 pmc:PMC3232349
%U <Go to ISI:>//WOS:000297820900003
%R 10.1007/s10827-011-0318-z
%U https://juser.fz-juelich.de/record/19176