Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 923

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A comparative study of the behavioral deficits following lesions of various parts of the zebra finch song system: implications for vocal learning

Open access
Scharff, C, Nottebohm, F·1991·The Journal of Neuroscience

Abstract

Song production in song birds is controlled by an efferent pathway. Appended to this pathway is a “recursive loop” that is necessary for song acquisition but not for the production of learned song. Since zebra finches learn their song by imitating external models, we speculated that the importance of the recursive loop for learning might derive from its processing of auditory feedback during song acquisition. This hypothesis was tested by comparing the effects on song in birds deafened early in life and birds with early lesions in either of two nuclei--Area X and the lateral magnocellular nucleus of the anterior neostriatum (LMAN). These nuclei are part of the recursive loop. The three treatments affected song development differently, as reflected by various parameters of the adult song of these birds. Whereas LMAN lesions resulted in songs with monotonous repetitions of a single note complex, songs of Area X-lesioned birds consisted of rambling series of unusually long and variable notes. Furthermore, whereas song of LMAN lesioned birds stabilized early, song stability as seen in intact birds was never achieved in Area X-lesioned birds. Early deafness also resulted in poorly structured and unstable song. We conclude that Area X and LMAN contribute differently to song acquisition: the song variability that is typical of vocal development persists following early deafness or lesions of Area X but ends abruptly following removal of LMAN. Apparently, LMAN plays a crucial role in fostering the kinds of circuit plasticity necessary for learning.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1523/jneurosci.11-09-02896.1991

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

Metadata

Authors
Scharff, C., & Nottebohm, F.
Venue
The Journal of Neuroscience
Published
1991-09-01
Volume
11
Issue
9
Pages
2896-2913
ISSN
  • 0270-6474 (ISSN-L)
  • 1529-2401
OpenAlex
W2135045229
Cited by
923
References
1
FWCI
17.10
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.