Evidence map›Paper›PMID 21404048›Full record

ArticleJournal of computational neuroscience2011

A reafferent and feed-forward model of song syntax generation in the Bengalese finch.

Alexander Hanuschkin, Markus Diesmann, Abigail Morrison

Abstract read
In one paragraph

Article in Journal of computational neuroscience, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
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  5. Temperature Manipulation in Songbird Brain Implicates the Premotor Nucleus HVC in Birdsong Syntax.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2017
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  14. Long-range order in canary song.PLoS computational biology · 2013
    Article
  15. Variable sequencing is actively maintained in a well learned motor skill.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2012
    Article
  16. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alexander HanuschkinFunctional Neural Circuits Group, Faculty of Biology, Albert-Ludwig University of Freiburg, Schänzlestrasse 1, 79104 Freiburg, Germany. hanuschkin@bccn.uni-freiburg.de
Markus Diesmann
Abigail Morrison

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Feedback, PhysiologicalNeural Networks, ComputerAction PotentialsAnimalsFemaleFinchesHigh Vocal CenterMaleModels, NeurologicalNerve NetSemanticsVocalization, Animal

Identifiers

PMID21404048
PMCPMC3232349

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.