Evidence map›Paper›PMID 39827274›Full record

ArticleCommunications biology2025

Perineuronal nets in motor circuitry regulate the performance of learned vocalizations in songbirds.

Xinghaoyun Wan, Angela S Wang, Daria-Salina Storch, Vivian Y Li, Jon T Sakata

Abstract read
In one paragraph

Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Critical Periods and Beyond: Dynamic Functions of Perineuronal Nets in Cognition, Development, and Disease.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Review
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

5 authors.

Xinghaoyun WanDepartment of Biology, McGill University, Montreal, QC, Canada.
Angela S WangDepartment of Biology, McGill University, Montreal, QC, Canada.
Daria-Salina StorchDepartment of Biology, McGill University, Montreal, QC, Canada.
Vivian Y LiDepartment of Biology, McGill University, Montreal, QC, Canada.
Jon T SakataDepartment of Biology, McGill University, Montreal, QC, Canada. jon.sakata@mcgill.ca.ORCID http://orcid.org/0000-0003-2285-9310

Funding

Fonds de Recherche du Québec - Nature et Technologies (Quebec Fund for Research in Nature and Technology) PR-284884Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada) 05016
6 · The paper itself

Abstract

The accurate and reliable performance of learned vocalizations (e.g., speech and birdsong) modulates the efficacy of communication in humans and songbirds. Consequently, it is critical to understand the factors that regulate the performance of learned vocalizations. Across taxa, neural circuits underlying motor learning and control are replete with perineuronal nets (PNNs), and we analyzed how PNNs in vocal motor circuitry regulate the performance of learned song in zebra finches. We report that developmental increases in PNN expression in vocal circuitry are associated with developmental increases in song stereotypy. We also document that enzymatically degrading PNNs in the motor nucleus HVC acutely altered song structure (changes in syllable sequencing and production). Collectively, our data reveal a causal contribution of PNNs to the performance of learned behaviors and, given the parallels in the regulation of birdsong and speech, suggest that PNNs in motor circuitry could modulate speech performance.

Indexed as

FinchesLearningNerve NetVocalization, AnimalAnimalsMale

Identifiers

PMID39827274
PMCPMC11743155

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.