Songbirds work around computational complexity by learning song vocabulary independently of sequence

Nature Communications
Dina LipkindRichard H R Hahnloser

Abstract

While acquiring motor skills, animals transform their plastic motor sequences to match desired targets. However, because both the structure and temporal position of individual gestures are adjustable, the number of possible motor transformations increases exponentially with sequence length. Identifying the optimal transformation towards a given target is therefore a computationally intractable problem. Here we show an evolutionary workaround for reducing the computational complexity of song learning in zebra finches. We prompt juveniles to modify syllable phonology and sequence in a learned song to match a newly introduced target song. Surprisingly, juveniles match each syllable to the most spectrally similar sound in the target, regardless of its temporal position, resulting in unnecessary sequence errors, that they later try to correct. Thus, zebra finches prioritize efficient learning of syllable vocabulary, at the cost of inefficient syntax learning. This strategy provides a non-optimal but computationally manageable solution to the task of vocal sequence learning.

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Citations

Feb 15, 2019·Topics in Cognitive Science·Dina LipkindClara C Levelt
Jan 10, 2020·Nature·Sepp KollmorgenValerio Mante
Nov 19, 2019·Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences·Adam R FishbeinRobert J Dooling
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May 11, 2019·Scientific Reports·Takuya Isomura, Taro Toyoizumi
Jan 12, 2020·Nature Communications·Jonathan I Benichov, Daniela Vallentin
Mar 13, 2021·Behavioral Ecology : Official Journal of the International Society for Behavioral Ecology·Sándor ZsebőkLászló Zsolt Garamszegi
Jun 18, 2021·Current Biology : CB·Ezequiel M ArneodoTimothy Q Gentner
Jun 2, 2020·Current Opinion in Neurobiology·Richard BertramFrank Johnson
Oct 10, 2021·Neuron·Margot ElmalehMichael A Long

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Software Mentioned

GOLDWAVE
Sound Analysis Pro
MATLAB

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