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Proc Natl Acad Sci U S A. 2019 May 7;116(19):9592-9597. doi: 10.1073/pnas.1815910116. Epub 2019 Apr 23.

Variation in sequence dynamics improves maintenance of stereotyped behavior in an example from bird song.

Author information

1
Department of Physics, University of Washington, Seattle, WA 98195; agduffy@uw.edu.
2
Department of Physics, University of Washington, Seattle, WA 98195.
3
Department of Biology, Institute of Neuroscience, University of Oregon, Eugene, OR 97401.
4
Department of Biology, University of Washington, Seattle, WA 98195.
5
Department of Otolaryngology, University of Washington, Seattle, WA 98195.
6
Department of Physiology & Biophysics, University of Washington, Seattle, WA 98195.
7
Institute for Neuroengineering, University of Washington, Seattle, WA 98195.
8
Computational Neuroscience Center, University of Washington, Seattle, WA 98195.

Abstract

Performing a stereotyped behavior successfully over time requires both maintaining performance quality and adapting efficiently to environmental or physical changes affecting performance. The bird song system is a paradigmatic example of learning a stereotyped behavior and therefore is a good place to study the interaction of these two goals. Through a model of bird song learning, we show how instability in neural representation of stable behavior confers advantages for adaptation and maintenance with minimal cost to performance quality. A precise, temporally sparse sequence from the premotor nucleus HVC is crucial to the performance of song in songbirds. We find that learning in the presence of sequence variations facilitates rapid relearning after shifts in the target song or muscle structure and results in decreased error with neuron loss. This robustness is due to the prevention of the buildup of correlations in the learned connectivity. In the absence of sequence variations, these correlations grow, due to the relatively low dimensionality of the exploratory variation in comparison with the number of plastic synapses. Our results suggest one would expect to see variability in neural systems executing stereotyped behaviors, and this variability is an advantageous feature rather than a challenge to overcome.

KEYWORDS:

maintenance learning; motor learning; reinforcement learning; skilled movement; songbird

PMID:
31015294
PMCID:
PMC6511032
[Available on 2019-10-23]
DOI:
10.1073/pnas.1815910116

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