Evidence map›Paper›PMID 26844835›Full record

ArticleNeuron2016

Sensorimotor Transformations Underlying Variability in Song Intensity during Drosophila Courtship.

Philip Coen, Marjorie Xie, Jan Clemens, Mala Murthy

Abstract read
In one paragraph

Article in Neuron, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

51 citing papers in PubMed.

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  11. Sequencing of distinct wing behaviors duringbioRxiv : the preprint server for biology · 2025
    Article
  12. High-Throughput Tracking of Freely MovingbioRxiv : the preprint server for biology · 2025
    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

4 authors.

Philip CoenPrinceton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA.
Marjorie XiePrinceton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA.
Jan ClemensPrinceton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA.
Mala MurthyPrinceton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA; Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA. Electronic address: mmurthy@princeton.edu.

Funding

How does the brain solve the pattern recognition problem?DP2NS092378 · NINDS · PRINCETON UNIVERSITY · PI MURTHY, MALA · 2014 to 2014
$2.4M
Howard Hughes Medical InstituteNINDS NIH HHS DP2 NS092378
6 · The paper itself

Abstract

Diverse animal species, from insects to humans, utilize acoustic signals for communication. Studies of the neural basis for song or speech production have focused almost exclusively on the generation of spectral and temporal patterns, but animals can also adjust acoustic signal intensity when communicating. For example, humans naturally regulate the loudness of speech in accord with a visual estimate of receiver distance. The underlying mechanisms for this ability remain uncharacterized in any system. Here, we show that Drosophila males modulate courtship song amplitude with female distance, and we investigate each stage of the sensorimotor transformation underlying this behavior, from the detection of particular visual stimulus features and the timescales of sensory processing to the modulation of neural and muscle activity that generates song. Our results demonstrate an unanticipated level of control in insect acoustic communication and uncover novel computations and mechanisms underlying the regulation of acoustic signal intensity.

Indexed as

CourtshipAnimalsDistance PerceptionDrosophilaFemaleFlight, AnimalMaleNeural PathwaysPhotic StimulationSoundTime FactorsVocalization, Animal

Identifiers

PMID26844835
PMCPMC5047376

What OpenQuestion holds

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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 OpenQuestion graph.