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Neural, Muscular and Computational Mechanisms of Vocal Control

Weekly Seminar | Not Open to the Public
Who Should Attend: 


Samuel Sober, Ph.D.
Associate Professor of Biology
Emory University, Decatur, Georgia


Samuel Sober, Ph.D. - Figure

The brain uses sensory feedback to calibrate the performance of complex behaviors. However, the biological and computational bases of sensorimotor learning remain mysterious. Our lab uses behavioral, physiological, biomechanical, and computational techniques to investigate motor control and vocal learning in songbirds. My talk will cover three ongoing lines of investigation into how songbirds correct vocal errors and precisely coordinate the acoustics of vocal production. First, our behavioral studies demonstrate that songbirds use vocal variability to constrain the speed and extent of vocal learning, and that a simple but powerful computational framework (iterative Bayesian inference) can account for the dynamics of learning across a number of experimental conditions. Second, neurophysiological recordings and computational analyses suggest that neurons in the motor system employ a millisecond-resolution spike timing code to regulate vocal behavior. Furthermore, single-unit recordings from muscle tissue in behaving animals and in vitro measures of muscle function demonstrate how the nervous system uses millisecond-scale spike timing to exploit the biomechanics of the vocal system. Third, comparative studies of a wide range of songbird and nonsongbird species (ranging in size from finches to ostriches) demonstrate that all species tested employ the same physical mechanism of sound production, and that this mechanism is identical to the one used to produce human speech. These data indicate that despite the different evolutionary origins of their vocal organs, humans and birds have converged upon the same physical mechanisms for producing communication sounds. Finally, I will present a survey of ongoing and future research projects, emphasizing how combining a wide range of experimental and analytical techniques to examine a complex natural behavior can yield important general insights into neural function.



Samuel J. Sober, Simon Sponberg, Ilya Nemenman, and Lena H. Ting
Millisecond Spike Timing Codes for Motor Control
Trends Neurosci. 2018 Oct; 41(10): 644–648.
Srivastava KH, Holmes CM, Vellema M, Pack AR, Elemans CP, Nemenman I, Sober SJ.
Motor control by precisely timed spike patterns.
Proc Natl Acad Sci U S A. 2017 Jan 31;114(5):1171-1176. doi: 10.1073/pnas.1611734114. Epub 2017 Jan 18.
Zhou, B., Hofmann, D., Pinkoviezky, I., Sober, S. J., & Nemenman, I.
Chance, long tails, and inference in a non-Gaussian, Bayesian theory of vocal learning in songbirds.
Proc Natl Acad Sci U S A. 2018 Sep 4;115(36):E8538-E8546. doi: 10.1073/pnas.1713020115. Epub 2018 Aug 20.


Tuesday, March 19, 2019 - 12:30pm


Burke Neurological Institute
785 Mamaroneck Avenue
White Plains, NY 10605
United States
Conference Room: 
Billings Building – Rosedale

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Lindsey Echevarria