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@ARTICLE{Hanuschkin:19176,
author = {Hanuschkin, A. and Diesmann, M. and Morrison, A.},
title = {{A} reafferent and feed-forward model of song syntax
generation in the {B}engalese finch},
journal = {Journal of computational neuroscience},
volume = {31},
issn = {0929-5313},
address = {Dordrecht [u.a.]},
publisher = {Springer Science + Business Media B.V},
reportid = {PreJuSER-19176},
pages = {509 - 532},
year = {2011},
note = {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.},
abstract = {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.},
keywords = {Action Potentials: physiology / Animals / Feedback,
Physiological / Female / Finches: physiology / High Vocal
Center: physiology / Male / Models, Neurological / Nerve
Net: physiology / Neural Networks (Computer) / Semantics /
Vocalization, Animal: physiology / J (WoSType)},
cin = {INM-6},
ddc = {610},
cid = {I:(DE-Juel1)INM-6-20090406},
pnm = {Neurowissenschaften (FUEK255) / 333 - Pathophysiological
Mechanisms of Neurological and Psychiatric Diseases
(POF2-333) / BRAINSCALES - Brain-inspired multiscale
computation in neuromorphic hybrid systems (269921)},
pid = {G:(DE-Juel1)FUEK255 / G:(DE-HGF)POF2-333 /
G:(EU-Grant)269921},
shelfmark = {Mathematical $\&$ Computational Biology / Neurosciences},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:21404048},
pmc = {pmc:PMC3232349},
UT = {WOS:000297820900003},
doi = {10.1007/s10827-011-0318-z},
url = {https://juser.fz-juelich.de/record/19176},
}