Abstract
The way in which information about behavior is represented at different levels of the motor pathway, remains among the fundamental unresolved problems of motor coding and sensorimotor integration. Insight into this matter is essential for understanding complex learned behaviors such as speech or birdsong. A major challenge in motor coding has been to identify an appropriate framework for characterizing behavior. In this work we discuss a novel approach linking biomechanics and neurophysiology to explore motor control of songbirds. We present a model of song production based on gestures that can be related to physiological parameters that the birds can control. This physical model for the vocal structures allows a reduction in the dimensionality of the behavior, being a powerful approach for studying sensorimotor integration. Our results also show how dynamical systems models can provide insight into neurophysiological analysis of vocal motor control. In particular, our work challenges the actual understanding of how the motor pathway of the songbird systems works and proposes a novel perspective to study neural coding for song production.
Change history
08 October 2018
The data in Figure 1a were originally published in Ana Amador and Daniel Margoliash, Journal of Neuroscience 33 (27) (2013) 11136?11144; https://doi.org/10.1523/JNEUROSCI.5906-12.2013 .
08 October 2018
The data in Figure 1a were originally published in Ana Amador and Daniel Margoliash, Journal of Neuroscience 33 (27) (2013) 11136���11144; https://doi.org/10.1523/JNEUROSCI.5906-12.2013 .
08 October 2018
The data in Figure 1a were originally published in Ana Amador and Daniel Margoliash, Journal of Neuroscience 33 (27) (2013) 11136���11144; https://doi.org/10.1523/JNEUROSCI.5906-12.2013 .
08 October 2018
The data in Figure 1a were originally published in Ana Amador and Daniel Margoliash, Journal of Neuroscience 33 (27) (2013) 11136���11144; https://doi.org/10.1523/JNEUROSCI.5906-12.2013 .
References
A.J. Doupe, P.K. Kuhl, Ann. Rev. Neurosci. 22, 567 (1999)
H.P. Zeigler, P. Marler, Neuroscience of Birdsong (Cambridge University Press, Cambridge, 2012)
R. Mooney, Learn. Memory 16, 655 (2009)
G.B. Mindlin, R. Laje, The Physics of Birdsong (Springer-Verlag, Berlin, 2005)
T. Gardner, G. Cecchi, M. Magnasco, R. Laje, G.B. Mindlin, Phys. Rev. Lett. 87, 208101 (2001)
G.B. Mindlin, T.J. Gardner, F. Goller, R. Suthers, Phys. Rev. E 68, 41908 (2003)
M.A. Trevisan, G.B. Mindlin, F. Goller, Phys. Rev. Lett. 96, 58103 (2006)
A. Amador, Y. Sanz Perl, G.B. Mindlin, D. Margoliash, Nature 495, 59 (2013)
L.M. Alonso, J.A. Alliende, F. Goller, G.B. Mindlin, Phys. Rev. E 79, 41929 (2009)
Y.S. Perl, E.M. Arneodo, A. Amador, F. Goller, G.B. Mindlin, Phys. Rev. E 84, 051909 (2011)
A. Amador, F. Goller, G.B. Mindlin, J. Neurophysiol. 99, 2383 (2008)
F. Goller, O.N. Larsen, Proc. Natl. Acad. Sci. USA 94, 14787 (1997)
I.R. Titze, J. Acoust. Soc. Am. 83, 1536 (1988)
A. Amador, G.B. Mindlin, Chaos 18, 043123 (2008)
S.H. Strogatz, Nonlinear Dynamics and Chaos: with Applications to Physics, Biology, Chemistry and Engineering (Perseus Books, Cambridge, 1994)
F. Goller, R.A. Suthers, J. Neurophysiol. 76, 287 (1996)
A. Amador, D. Margoliash, J. Neurosci. 33, 11136 (2013)
J. Guckenheimer, P. Holmes, Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields (Springer, 1997)
J.D. Sitt, E.M. Arneodo, F. Goller, G.B. Mindlin, Phys. Rev. E 81, 31927 (2010)
J.D. Sitt, A. Amador, F. Goller, G.B. Mindlin, Phys. Rev. E 78, 011905 (2008)
N.H. Fletcher, T. Riede, R.A. Suthers, J. Acoust. Soc. Am. 119, 1005 (2006)
T.W. Troyer, Nature 495, 56 (2013)
R.H.R. Hahnloser, A.A. Kozhevnikov, M.S. Fee, Nature 419, 65 (2002)
M.A. Long, M.S. Fee, Nature 456, 189 (2008)
M.A. Goldin, L.M. Alonso, J.A. Alliende, F. Goller, G.B. Mindlin, PLoS One 8, e67814 (2013)
R.S. Hartley, R.A. Suthers, J. Neurobiol. 21, 1236 (1990)
F.C. Hoppensteadt, E.M. Izhikevich, Weakly Connected Neural Networks (Springer, 1997)
T. Riede, F. Goller, Brain Lang 115, 69 (2010)
D. Margoliash, J. Neurosci. 6, 1643 (1986)
D. Margoliash, M. Konishi, Proc. Natl. Acad. Sci. USA 82, 5997 (1985)
M.O. Magnasco, O. Piro, G.A. Cecchi, Phys. Rev. Lett. 102, 258102 (2009)
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Amador, A., Mindlin, G.B. Low dimensional dynamics in birdsong production. Eur. Phys. J. B 87, 300 (2014). https://doi.org/10.1140/epjb/e2014-50566-5
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DOI: https://doi.org/10.1140/epjb/e2014-50566-5