OSCR

Temporally structured motor and auditory representations in covert syllable production.

Code ↔ Paper

14 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 14 matches
  1. [1] § Materials and Methods › Decoding in Source Space. ↔ scripts/extract_vals_ROIs.py, lines 124–140 · score 0.86 · dorsal motor, pSTG, pSTS, aparc_sub, ventral motor, pars
  2. [2] § Results › Motor and Auditory Representations During Inner Speaking. ↔ scripts/extract_vals_ROIs.py, lines 124–140 · score 0.79 · aSTG, dorsal motor, pSTG, pSTS, ventral motor, SMG
  3. [3] § Results › Motor and Auditory Representations During Inner Speaking. ↔ scripts/Fig3GH.py, lines 33–40 · score 0.75 · p.Tri, aSTG, pSTG, pSTS, INS, op
  4. [4] § Materials and Methods › Decoding in Source Space. ↔ scripts/Source_space_decoding.py, lines 400–460 · score 0.71 · logistic regression, cross validation, source space, solver, stratified, classifier
  5. [5] § Materials and Methods › Cosine Similarity Analysis. ↔ scripts/Fig1E_cosine_similarity.py, lines 295–386 · score 0.70 · sided sign flip, cosine, template, separability, topographies, diagonal
  6. [6] § Materials and Methods › Temporal Generalization. ↔ scripts/Source_space_decoding.py, lines 400–460 · score 0.68 · logistic regression, cross validation, folds, solver, stratified, class
  7. [7] § Materials and Methods › Decoding in Source Space. ↔ scripts/Fig3C.py, lines 22–24 · score 0.66 · pSTG, pSTS, ventral motor, vMC, ROI, Figure 3
  8. [8] § Results › A Sequence of Neural Processes Underlies Inner Speaking. ↔ scripts/Fig1E_cosine_similarity.py, lines 529–588 · score 0.66 · hybrid matrix, upper triangle, lower triangle, cosine, topographies, permutation
  9. [9] § Results › A Sequence of Neural Processes Underlies Inner Speaking. ↔ scripts/Fig1F_decoding_source_cluster_peaks_Covert.py, lines 32–41 · score 0.57 · 356–433 ms, 356 ms, covert, peak, decoded, Figure 1
  10. [10] § Results › Passive Viewing vs. Covert Speech: Shared and Distinct Neural Processes. ↔ scripts/Fig1F_decoding_source_cluster_peaks_Covert.py, lines 32–41 · score 0.57 · 356–433 ms, 356 ms, Covert, peak, decoding, Figure 1
  11. [11] § Results › Passive Viewing vs. Covert Speech: Shared and Distinct Neural Processes. ↔ scripts/Fig1D_evokeds.py, lines 59–77 · score 0.56 · 356–433 ms, 356 ms, Covert, peak, Figure 1
  12. [12] § Results › A Sequence of Neural Processes Underlies Inner Speaking. ↔ scripts/Fig1D_evokeds.py, lines 59–77 · score 0.56 · 356–433 ms, 356 ms, peak, covert, Figure 1
  13. [13] § Materials and Methods › Temporal Generalization. ↔ scripts/Sensor_space_decoding.py, lines 90–98 · score 0.53 · logistic regression, lbfgs, solver, classifier, decoding
  14. [14] § Results › Passive Viewing vs. Covert Speech: Shared and Distinct Neural Processes. ↔ scripts/Sensor_space_decoding.py, lines 291–350 · score 0.51 · space decoding, cross validation, ROC AUC, shuffled, stratified, diagonal

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

Python · 853 lines · 25 KB · no license · 2 matches

This file is not shown here: its repository has no license, so its authors keep all their rights to it. Your browser cannot show it from its source either: OSF does not let the page of another site read its files.

It can be read at the source: scripts/extract_vals_ROIs.py.

Overview

Authors: Joan Orpella1,2, Francesco Mantegna2,3, Chantal Oderbolz1, M Florencia Assaneo4, David Poeppel2,5
ORCID iDs: Joan Orpella, Francesco Mantegna, Chantal Oderbolz
  1. Department of Neuroscience, Georgetown University Medical Center, Washington, DC 20057
  2. Department of Psychology, New York University, New York, NY 10003
  3. Department of Engineering Science, Oxford University, Oxford OX1 3PJ, Oxfordshire, United Kingdom
  4. Institute of Neurobiology, National Autonomous University of Mexico, Juriquilla 76230, Querétaro, Mexico
  5. Center for Language, Music and Emotion, New York University, New York, NY 10003
Institutions: Georgetown University Medical Center (United States); New York University (United States); University of Oxford (United Kingdom); Universidad Nacional Autónoma de México (Mexico)
Journal: Proceedings of the National Academy of Sciences of the United States of America, volume 123, issue 37, article e2536563123
Dates: received 16 December 2025; accepted 27 July 2026; published online 31 August 2026; in print 15 September 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1073/pnas.2536563123 · PMID 42673473 · PMCID PMC13578806 · OpenAlex W7168277495
Open access: hybrid, a free copy (OpenAlex)
Preprint: osf.io/3vmek
Status: code verified
Categories: MEG (modality), human (organism), cognitive (subfield)
Methods: Spectral & time-frequency, Preprocessing, Statistics, Smoothing, state filtering, decompositions, Machine learning, Evoked potentials, Source localization, fMRI & imaging, Physiology & signal measures
Keywords: speech production, inner speech, magnetoencephalography, decoding, covert speech
MeSH: Auditory Cortex*, Motor Cortex*, Speech*, Speech Perception*, Adult, Female, Humans, Magnetoencephalography, Male, Phonetics, Young Adult (* major topic)
Topic: Neuroscience and Music Perception (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: NSF (2043717); NIDCD NIH HHS (R01 DC005660, 2R01DC05660)
Citations: not cited yet (Europe PMC); 69 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above, with 14 matches between paragraphs and lines of code.

OSF 3vmek

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Languages: Python (14)
Size: 104 files, 14 scripts
Software Heritage: not checked
Found in: “Data, Materials, and Software Availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Matplotlib (13 files), NumPy (13 files), MNE-Python (9 files), SciPy (7 files), pandas (3 files), scikit-learn (3 files), statsmodels (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
14 files, to read at the source

This repository has no license: its authors keep all rights. Read it at the source.

At the source: doi.org/10.17605/OSF.IO/3VMEK

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 14 scripts, each with its path and the digest of its content;
  • 14 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Code and data availability statement

The paper has a code and data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1073/pnas.2536563123.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 5 keywords, 11 MeSH terms, 2 funders, 58 references.

Cite

This paper

Orpella, J., Mantegna, F., Oderbolz, C., Assaneo, M. F., & Poeppel, D. (2026). Temporally structured motor and auditory representations in covert syllable production. Proceedings of the National Academy of Sciences of the United States of America, 123(37), e2536563123. https://doi.org/10.1073/pnas.2536563123

BibTeX

@article{orpella2026temporally,
author = {Orpella, Joan and Mantegna, Francesco and Oderbolz, Chantal and Assaneo, M Florencia and Poeppel, David},
title = {{Temporally structured motor and auditory representations in covert syllable production}},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
year = {2026},
month = aug,
volume = {123},
number = {37},
pages = {e2536563123},
publisher = {National Academy of Sciences},
issn = {0027-8424},
doi = {10.1073/pnas.2536563123},
url = {https://doi.org/10.1073/pnas.2536563123},
pmid = {42673473},
pmcid = {PMC13578806}
}

RIS

TY - JOUR
AU - Orpella, Joan
AU - Mantegna, Francesco
AU - Oderbolz, Chantal
AU - Assaneo, M Florencia
AU - Poeppel, David
TI - Temporally structured motor and auditory representations in covert syllable production
T2 - Proceedings of the National Academy of Sciences of the United States of America
J2 - Proc Natl Acad Sci U S A
PY - 2026
DA - 2026/08/31
VL - 123
IS - 37
SP - e2536563123
SN - 0027-8424
PB - National Academy of Sciences
DO - 10.1073/pnas.2536563123
UR - https://doi.org/10.1073/pnas.2536563123
LA - en
ER -

CSL-JSON

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