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Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys.

Code ↔ Paper

1 match 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 1 match
  1. [1] § Methods › Relate neural activity to DDM components ↔ Code/Figure4_splitFR.m, lines 1–115 · score 0.54 · epoch combination, DDM parameter, firing rates, split, fitted, neural

Paper

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The authors' code

MATLAB · 333 lines · 12 KB · no license · 1 match

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Overview

  1. Department of Neuroscience, University of Pennsylvania, Philadelphia, United States
Institutions: University of Pennsylvania (United States)
Journal: eLife, volume 15, article RP109622
Dates: published online 1 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.7554/elife.109622 · PMID 42383848 · PMCID PMC13322701 · OpenAlex W7127539481
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: non-human primate (organism), cognitive (subfield)
Methods: Connectivity, Statistics, Machine learning, Preprocessing, Single-unit activity, calcium imaging, Physiology & signal measures
Keywords: Rhesus macaque
MeSH: Decision Making*, Neurons*, Reward*, Subthalamic Nucleus*, Animals, Macaca mulatta, Male (* major topic)
Topic: Neurological disorders and treatments (Neurology, Medicine), according to OpenAlex
Funding: NEI NIH HHS (P30 EY001583, R01-EY022411, R21EY029091)
Citations: not cited yet (Europe PMC); 50 references in the paper
Research resources: MATLAB RRID:SCR_001622, Python RRID:SCR_008394

Abstract

The subthalamic nucleus (STN) is a part of the indirect and hyperdirect pathways in the basal ganglia (BG) and has been implicated in movement control, impulsivity, and decision-making. We recently demonstrated that, for perceptual decisions, the STN includes at least three subpopulations of neurons with different decision-related activity patterns (Branam et al., 2024). Here, we show that, for decisions that require both perceptual and reward-based processing, many STN neurons are sensitive to both sensory evidence and reward expectations. Within a drift-diffusion framework, three STN subpopulations show different relationships to model components reflecting the formation of the decision variable, dynamics of the decision bound, and non-decision-related processes. Many STN neurons also represent quantities related to decision evaluation, including choice accuracy and reward expectation. These results help to further delineate the multiple roles that STN plays in forming and evaluating complex decisions that combine multiple sources of information.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above, with 1 match between paragraphs and lines of code.

OSF jdk9v

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Languages: MATLAB (37)
Size: 48 files, 37 scripts
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
37 files, to read at the source

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

At the source: osf.io/jdk9v/

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;
  • 37 scripts, each with its path and the digest of its content;
  • 1 match 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.

Data availability

All electrophysiological data and the code for the analyses presented in the paper are deposited at OSF (https://osf.io/jdk9v/).

The following previously published dataset was used:

Ding L. 2026. STN asymmetric reward decision making. Open Science Framework. jdk9v

Reproduced under the paper's license (CC BY), from the paper cited above.

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, pages, dates, 3 authors, 1 keyword, 7 MeSH terms, 1 funder, 50 references, 2 RRIDs.

Cite

This paper

Branam, K., Gold, J. I., & Ding, L. (2026). Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys. eLife, 15, RP109622. https://doi.org/10.7554/elife.109622

BibTeX

@article{branam2026distinct,
author = {Branam, Kathryn and Gold, Joshua I and Ding, Long},
title = {{Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys}},
journal = {eLife},
year = {2026},
month = jul,
volume = {15},
pages = {RP109622},
publisher = {eLife Sciences Publications, Ltd},
issn = {2050-084X},
doi = {10.7554/elife.109622},
url = {https://doi.org/10.7554/elife.109622},
pmid = {42383848},
pmcid = {PMC13322701}
}

RIS

TY - JOUR
AU - Branam, Kathryn
AU - Gold, Joshua I
AU - Ding, Long
TI - Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys
T2 - eLife
J2 - eLife
PY - 2026
DA - 2026/07/01
VL - 15
SP - RP109622
SN - 2050-084X
PB - eLife Sciences Publications, Ltd
DO - 10.7554/elife.109622
UR - https://doi.org/10.7554/elife.109622
LA - en
ER -

CSL-JSON

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