Evidence map›Paper›PMID 42630811›Full record

ArticlePatterns (New York, N.Y.)2026

Neural rhythms as priors of speech computations.

Nand Chandravadia, Nabil Imam

Abstract read
In one paragraph

Article in Patterns (New York, N.Y.), 2026. 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. Neural rhythms as priors of speech computations.Patterns (New York, N.Y.) · 2026
    Article
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

2 authors.

Nand ChandravadiaSchool of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Nabil ImamSchool of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endogenous rhythms of auditory neural circuits have a striking resemblance to the temporal modulations of incoming speech signals. Here, we show that these rhythms may serve as priors for speech recognition, encoding knowledge of speech structure in the dynamics of network computations. In a network of coupled oscillators, we find that speech is readily identified when characteristic frequencies of the oscillators match low-frequency circuit rhythms in the auditory cortex. When signal and circuit rhythms are mismatched, speech identification is impaired. Compared to a baseline recurrent neural network without intrinsic oscillations, the coupled oscillatory network has significantly higher performance in speech recognition across languages but not in the recognition of signals that lack speech-like structure, such as urban sounds. Our results suggest a central computational role of brain rhythms in speech processing.

Indexed as

brain rhythmscoupled oscillatorsinductive biasesoscillatory neural networksspeech rhythmswave-RNNs

Identifiers

PMID42630811
PMCPMC13494615

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.