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Using deep learning to identify brain networks mediating cognitive and motor impairments in alcohol use disorder.

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Paper

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

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The authors' code

Python · 2 lines · 138 B · apache

  1. """Backward-compatible re-exports. Implementation: ``multimodal_graph.graph``."""
  2. from multimodal_graph.graph import * # noqa: F401,F403

build_graph.py at commit d574cc0, under apache · at the source

Overview

Authors: Yixin Wang1, Eva M. Müller-Oehring2,3, Stephanie A. Sassoon3,4, Kalin Z. Salinas4, Adolf Pfefferbaum3,4, Edith V. Sullivan4, Qingyu Zhao5, Kilian M. Pohl4
ORCID iDs: Stephanie A. Sassoon, Edith V. Sullivan, Kilian M. Pohl
  1. Department of Bioengineering, Stanford University,Stanford, CA 94305 USA
  2. Dept. of Neurology & Neurological Sciences, Stanford University,Stanford, CA 94304 USA
  3. Center for Health Sciences, SRI International,Menlo Park, CA 94025 USA
  4. Dept. of Psychiatry & Behavioral Sciences, Stanford University,Stanford, CA 95817 USA
  5. Department of Radiology, Weill Cornell Medicine,New York, NY 10065 USA
Institutions: Stanford University (United States); SRI International (United States); Weill Cornell Medicine (United States)
Journal: Translational psychiatry, volume 16, issue 1, article 372
Dates: received 11 June 2025; accepted 30 April 2026; published online 26 May 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41398-026-04101-7 · PMID 42185254 · PMCID PMC13385787 · OpenAlex W7162282833
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), other condition (population), cognitive (subfield)
Methods: Spectral & time-frequency, Connectivity, Statistics, Smoothing, state filtering, decompositions, Machine learning, Preprocessing, fMRI & imaging
Keywords: Scientific community, Neuroscience, Addiction
MeSH: Alcoholism*, Brain*, Cognitive Dysfunction*, Deep Learning*, Nerve Net*, Adult, Executive Function, Female, Humans, Magnetic Resonance Imaging, Male, Memory, Short-Term, Middle Aged, Neural Pathways, Neuropsychological Tests (* major topic)
Topic: EEG and Brain-Computer Interfaces (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: National Institutes of Health (AA05965, DA057567, AA017347, AA028840, AA010723)
Citations: not cited yet (Europe PMC); 108 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.

Wangyixinxin/BrainCog

License: apache
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: d574cc0772666ae12124c9ababd429cc24709447, 29 May 2026
Languages: Python (16)
Size: 21 files, 16 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README, environment (Scripts/requirements.txt)
Not found: license file, CITATION.cff, tests, continuous integration, documentation
Tools: PyTorch (9 files), PyTorch Geometric (6 files), NumPy (4 files), Matplotlib (2 files), NetworkX (2 files), pandas (2 files), scikit-learn (2 files), seaborn (2 files), SciPy (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
17 files
At the source: github.com/Wangyixinxin/BrainCog

Code availability statement

The paper has a code 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/10.1038/s41398-026-04101-7.

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;
  • 16 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • 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

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Data availability statement

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  • it says that the data are available on request

Read it in the paper: doi.org/10.1038/s41398-026-04101-7.

Versions

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 8 authors, 3 keywords, 15 MeSH terms, 1 funder, 87 references.

Cite

This paper

Wang, Y., Müller-Oehring, E. M., Sassoon, S. A., Salinas, K. Z., Pfefferbaum, A., Sullivan, E. V., Zhao, Q., & Pohl, K. M. (2026). Using deep learning to identify brain networks mediating cognitive and motor impairments in alcohol use disorder. Translational psychiatry, 16(1), 372. https://doi.org/10.1038/s41398-026-04101-7

BibTeX

@article{wang2026using,
author = {Wang, Yixin and Müller-Oehring, Eva M. and Sassoon, Stephanie A. and Salinas, Kalin Z. and Pfefferbaum, Adolf and Sullivan, Edith V. and Zhao, Qingyu and Pohl, Kilian M.},
title = {{Using deep learning to identify brain networks mediating cognitive and motor impairments in alcohol use disorder}},
journal = {Translational psychiatry},
year = {2026},
month = may,
volume = {16},
number = {1},
pages = {372},
publisher = {Nature Publishing Group},
issn = {2158-3188},
doi = {10.1038/s41398-026-04101-7},
url = {https://doi.org/10.1038/s41398-026-04101-7},
pmid = {42185254},
pmcid = {PMC13385787}
}

RIS

TY - JOUR
AU - Wang, Yixin
AU - Müller-Oehring, Eva M.
AU - Sassoon, Stephanie A.
AU - Salinas, Kalin Z.
AU - Pfefferbaum, Adolf
AU - Sullivan, Edith V.
AU - Zhao, Qingyu
AU - Pohl, Kilian M.
TI - Using deep learning to identify brain networks mediating cognitive and motor impairments in alcohol use disorder
T2 - Translational psychiatry
J2 - Transl Psychiatry
PY - 2026
DA - 2026/05/26
VL - 16
IS - 1
SP - 372
SN - 2158-3188
PB - Nature Publishing Group
DO - 10.1038/s41398-026-04101-7
UR - https://doi.org/10.1038/s41398-026-04101-7
LA - en
ER -

CSL-JSON

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"author": [
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"family": "Wang",
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