OSCR

Learning dynamically regulates stimulus discrimination of ventral striatal D1 receptor expressing neurons.

Code ↔ Paper

3 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 3 matches · 2 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § RESULTS › D1 MSN activation on CS- trials impairs stimulus discrimination ↔ AnalyzeBehavior.m, the whole file · a weak match · score 0.62 · lick probability, ChR2, CS licking, lick selectivity, discrimination, Behavior
  2. [2] § MATERIALS AND METHODS › Quantification and statistical analysis ↔ AnalyzeNeuralActivity.m, lines 1–20 · score 0.57 · modulated cells, cue modulation, firing rate, neural activity, trial blocks, tagged
  3. [3] § RESULTS › Mice learn a stimulus discrimination task in a single session ↔ AnalyzeBehavior.m, the whole file · a weak match · score 0.53 · CS lick probabilities, lick selectivity, trial block, delay, mice, discriminate

Paper

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

The paper is loaded when this pane is shown.

The authors' code

MATLAB · 106 lines · 4.3 KB · CC-BY-4.0 · 2 matches

  1. function [lickProb_cue1_perSub,lickProb_cue2_perSub,lickSelectivity_perSub] = AnalyzeBehavior(group,trials,bins)
  2. % Cue discrimination: analysis of behavior
  3. % Calculates lick probability and selectivity
  4. % Inputs:
  5. % group: 'D1', 'D2', 'All', 'ChR2 (laser)', 'ChR2 (no laser)', 'Control (laser)', or 'Control (no laser)'
  6. % trials: default is one 25-trial block (1:25, 26:50, 51:75, or 76:100)
  7. % bins: isi (12:35), cue (12:20), delay (22:35), post-reward (36:40)
  8. % Outputs:
  9. % lickProb_cue1_perSub: lick probability to CS+ (per subject)
  10. % lickProb_cue2_perSub: lick probability to CS- (per subject)
  11. % lickSelectivity: lick selectivity in Hz (per subject)
  13. load('Data_Behavior.mat')
  14. startTime = (bins(1) - 11) * 0.1; % converts first bin to seconds
  15. endTime = (bins(end) - 10) * 0.1; % converts last bin to seconds and extends 100 ms
  17. %% Selected data
  18. if isequal(group,'D1')
  19. cue1times_perSub = cue1times_D1; % D1 CS+ times
  20. cue2times_perSub = cue2times_D1; % D1 CS- times
  21. lickTimes_perSub = lickTimes_D1;
  22. elseif isequal(group,'D2')
  23. cue1times_perSub = cue1times_D2; % D2 CS+ times
  24. cue2times_perSub = cue2times_D2; % D2 CS- times
  25. lickTimes_perSub = lickTimes_D2;
  26. elseif isequal(group,'All')
  27. cue1times_perSub = [cue1times_D1; cue1times_D2]; % D2 CS+ times
  28. cue2times_perSub = [cue2times_D1; cue2times_D2]; % D2 CS- times
  29. lickTimes_perSub = [lickTimes_D1 lickTimes_D2];
  30. elseif isequal(group,'ChR2 (laser)')
  31. cue1times_perSub = cue1times_optoLaser;
  32. cue2times_perSub = cue2times_optoLaser;
  33. lickTimes_perSub = lickTimes_optoLaser;
  34. elseif isequal(group,'ChR2 (no laser)')
  35. cue1times_perSub = cue1times_optoNoLaser;
  36. cue2times_perSub = cue2times_optoNoLaser;
  37. lickTimes_perSub = lickTimes_optoNoLaser;
  38. elseif isequal(group,'Control (laser)')
  39. cue1times_perSub = cue1times_controlLaser;
  40. cue2times_perSub = cue2times_controlLaser;
  41. lickTimes_perSub = lickTimes_controlLaser;
  42. elseif isequal(group,'Control (no laser)')
  43. cue1times_perSub = cue1times_controlNoLaser;
  44. cue2times_perSub = cue2times_controlNoLaser;
  45. lickTimes_perSub = lickTimes_controlNoLaser;
  46. end
  47. numSubs = size(cue1times_perSub,1); % number of subjects (mice)
  48. numTrials = length(trials);
  49. totalTime = endTime - startTime;
  51. %% Loop through subjects to calculate lick responses
  52. lickProb_cue1_perSub = zeros(numSubs,1); lickProb_cue2_perSub = lickProb_cue1_perSub;
  53. lickNum_cue1_perSub = lickProb_cue1_perSub; lickNum_cue2_perSub = lickProb_cue1_perSub;
  54. for nSub = 1:numSubs
  55. lickTimes = lickTimes_perSub{nSub}; % raw lick times for single subject
  57. for nCue = 1:2
  58. if nCue==1
  59. cueTimes = cue1times_perSub(nSub,:); % CS+
  60. cueTimes = cueTimes(trials);
  61. elseif nCue==2
  62. cueTimes = cue2times_perSub(nSub,:); % CS-
  63. cueTimes = cueTimes(trials);
  64. end
  66. lickNum_perTrial = zeros(1,numTrials);
  67. for nTrial = 1:numTrials
  68. eventTime = cueTimes(nTrial);
  69. lick_ind = find(lickTimes < (eventTime + endTime) & lickTimes > eventTime + startTime);
  70. lickNum_perTrial(nTrial) = length(lick_ind);
  71. end
  73. lickProb = length(find(lickNum_perTrial>0))/numTrials; % lick probability
  74. mean_lickNum = mean(lickNum_perTrial); % lick number
  76. if nCue==1 % CS+
  77. lickProb_cue1_perSub(nSub) = lickProb;
  78. lickNum_cue1_perSub(nSub) = mean_lickNum;
  79. elseif nCue==2 % CS-
  80. lickProb_cue2_perSub(nSub) = lickProb;
  81. lickNum_cue2_perSub(nSub) = mean_lickNum;
  82. end
  83. end
  84. end
  85. lickSelectivity_perSub = (lickNum_cue1_perSub - lickNum_cue2_perSub)/totalTime;
  87. lickProb_cue1 = mean(lickProb_cue1_perSub);
  88. % lickNum_cue1 = mean(lickNum_cue1_perSub);
  90. lickProb_cue2 = mean(lickProb_cue2_perSub);
  91. % lickNum_cue2 = mean(lickNum_cue2_perSub);
  93. lickSelectivity = mean(lickSelectivity_perSub);
  95. % Results summary
  96. cue1_str = ['CS+ lick probability: ' num2str(round(lickProb_cue1,2)) '.\n'];
  97. cue2_str = ['CS- lick probability: ' num2str(round(lickProb_cue2,2)) '.\n'];
  98. selectivity_str = ['Lick selectivity: ' num2str(round(lickSelectivity,2)) ' Hz.\n'];
  100. fprintf('***************************************************************\n')
  101. fprintf([group ' subjects, trials ' num2str(trials(1)) '-' num2str(trials(end)) ':\n'])
  102. fprintf(cue1_str)
  103. fprintf(cue2_str)
  104. fprintf(selectivity_str)
  106. end

AnalyzeBehavior.m, under CC-BY-4.0 · at the source

Overview

Authors: Tierney B. Daw1,2, Jiayi Cao2, Ruoxian Li2, Sotiris C. Masmanidis1,2,3,4
ORCID iDs: Tierney B. Daw, Jiayi Cao, Ruoxian Li, Sotiris C. Masmanidis
  1. Molecular, Cellular, and Integrative Physiology Graduate Program, University of California, Los Angeles, CA, USA
  2. Department of Neurobiology, University of California, Los Angeles, CA, USA
  3. Department of Bioengineering, University of California, Los Angeles, CA, USA
  4. California Nanosystems Institute, University of California, Los Angeles, CA, USA
Institutions: University of California, Los Angeles (United States); California NanoSystems Institute (United States)
Journal: Science advances, volume 12, issue 29, article eaee3529
Dates: received 30 November 2025; accepted 2 June 2026; published online 15 July 2026; in print July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1126/sciadv.aee3529 · PMID 42455948 · PMCID PMC13371909 · OpenAlex W4416666090
Open access: gold, a free copy (OpenAlex)
Preprint: doi:10.1101/2025.11.21.689812
Status: code verified
Categories: mouse (organism), cellular / molecular (subfield)
Methods: Spectral & time-frequency, Connectivity, Statistics, Evoked potentials, Single-unit activity, calcium imaging
MeSH: Discrimination Learning*, Learning*, Neurons*, Receptors, Dopamine D1*, Ventral Striatum*, Animals, Behavior, Animal, Cues, Male, Medium Spiny Neurons, Mice, Receptors, Dopamine D2, Reward (* major topic)
Journal subjects: Neuroscience, Neurophysiology
Topic: Neurotransmitter Receptor Influence on Behavior (Cellular and Molecular Neuroscience, Neuroscience), according to OpenAlex
Funding: National Institutes of Health (F31MH142117, R01DA060229, R01NS125877, R01NS136137)
Citations: not cited yet (Europe PMC); 53 references in the paper

Abstract

Animals encounter a barrage of sensory stimuli, but only a subset of these are associated with appetitive outcomes. Thus, mechanisms for learning to distinguish reward-paired from unpaired cues are essential for reward-seeking behavior. The ventral striatum plays a critical role in reinforcement learning and stimulus discrimination, but the effect of learning on the selectivity of different cell types remains unclear. We examined ventral striatal D1 and D2 medium spiny neuron (MSN) firing properties as mice learned to distinguish between reward-paired and unpaired cues. As learning progressed within a single session, D1 MSN selectivity increased linearly with behavioral selectivity, while D2 MSNs exhibited modest, behaviorally uncorrelated changes in activity. Altered D1 MSN selectivity was primarily attributed to attenuated excitatory responses to the unrewarded cue, and increasing D1 MSN activity during the unrewarded cue impaired behavioral selectivity. Together, these findings reveal significantly more dynamic contributions of D1 MSNs to stimulus discrimination learning.

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 3 matches between paragraphs and lines of code.

Zenodo 19024141

License: CC-BY-4.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Languages: MATLAB (6)
Size: 10 files, 6 scripts
Software Heritage: not checked
Found in: “Data, code, and materials availability:”
Holds: README
Not found: 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)
6 files
At the source: zenodo.org/records/19024141

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;
  • 6 scripts, each with its path and the digest of its content;
  • 3 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.

Data, code, and materials availability

All data and code needed to evaluate and reproduce the results in the paper are available at https://zenodo.org/records/19024141 online repository. This study did not generate new materials.

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, issue, pages, dates, 4 authors, 13 MeSH terms, 1 funder, 53 references.

Cite

This paper

Daw, T. B., Cao, J., Li, R., & Masmanidis, S. C. (2026). Learning dynamically regulates stimulus discrimination of ventral striatal D1 receptor expressing neurons. Science advances, 12(29), eaee3529. https://doi.org/10.1126/sciadv.aee3529

BibTeX

@article{daw2026learning,
author = {Daw, Tierney B. and Cao, Jiayi and Li, Ruoxian and Masmanidis, Sotiris C.},
title = {{Learning dynamically regulates stimulus discrimination of ventral striatal D1 receptor expressing neurons}},
journal = {Science advances},
year = {2026},
month = jul,
volume = {12},
number = {29},
pages = {eaee3529},
publisher = {American Association for the Advancement of Science},
issn = {2375-2548},
doi = {10.1126/sciadv.aee3529},
url = {https://doi.org/10.1126/sciadv.aee3529},
pmid = {42455948},
pmcid = {PMC13371909}
}

RIS

TY - JOUR
AU - Daw, Tierney B.
AU - Cao, Jiayi
AU - Li, Ruoxian
AU - Masmanidis, Sotiris C.
TI - Learning dynamically regulates stimulus discrimination of ventral striatal D1 receptor expressing neurons
T2 - Science advances
J2 - Sci Adv
PY - 2026
DA - 2026/07/15
VL - 12
IS - 29
SP - eaee3529
SN - 2375-2548
PB - American Association for the Advancement of Science
DO - 10.1126/sciadv.aee3529
UR - https://doi.org/10.1126/sciadv.aee3529
LA - en
ER -

CSL-JSON

{
"id": "10.1126/sciadv.aee3529",
"type": "article-journal",
"title": "Learning dynamically regulates stimulus discrimination of ventral striatal D1 receptor expressing neurons",
"container-title": "Science advances",
"author": [
{
"family": "Daw",
"given": "Tierney B."
},
{
"family": "Cao",
"given": "Jiayi"
},
{
"family": "Li",
"given": "Ruoxian"
},
{
"family": "Masmanidis",
"given": "Sotiris C."
}
],
"container-title-short": "Sci Adv",
"volume": "12",
"issue": "29",
"page": "eaee3529",
"DOI": "10.1126/sciadv.aee3529",
"PMID": "42455948",
"PMCID": "PMC13371909",
"ISSN": "2375-2548",
"publisher": "American Association for the Advancement of Science",
"URL": "https://doi.org/10.1126/sciadv.aee3529",
"language": "en",
"issued": {
"date-parts": [
[
2026,
7,
15
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1126/sciadv.aeb5352 [code]
Indirect pathway neurons in the tail of the striatum regulate inhibitory control over sensory driven behavior.
Journal: Science advances
In common: mouse, 7 references
[2] doi:10.1126/sciadv.aed9386 [code]
Shared striatal neurons exhibit context-specific dynamics for internally and externally driven actions.
Journal: Science advances
In common: mouse, 5 references
[3] doi:10.1126/sciadv.aee6579 [code]
Dopamine D2 receptors bypass canonical signaling to directly tune NMDA receptor function and aversive learning.
Journal: Science advances
In common: mouse, cellular / molecular, 4 references
[4] doi:10.7554/elife.108639
The nucleus accumbens shell regulates hedonic feeding via a rostral hotspot.
Journal: eLife
In common: mouse, cellular / molecular, 3 references
[5] doi:10.1016/j.isci.2026.116498 [code]
The Tower Foraging Park: A paradigm for studying cognitive and motor processes underlying behavioral flexibility in freely moving mice.
Journal: iScience
In common: mouse, 3 references
[6] doi:10.1038/s41592-026-03076-z [code]
Neuropixels Opto: combining high-resolution electrophysiology and optogenetics.
Journal: Nature methods
In common: mouse, 3 references
[7] doi:10.1016/j.isci.2026.116598
Complementary δ2-protocadherin expression delineates parallel basal ganglia circuits in primates.
Journal: iScience
In common: 3 references
[8] doi:10.1038/s41467-026-72619-x [code]
An inhibitory brainstem pathway reduces visual detection during background motion.
Journal: Nature communications
In common: mouse, 3 references
[9] doi:10.1073/pnas.2601657123 [code]
Mitofusin-2 in ventral striatal D1 neurons regulates effort-based motivation through sex-specific mitochondrial-synaptic reprogramming.
Journal: Proceedings of the National Academy of Sciences of the United States of America
In common: mouse, cellular / molecular, 2 references
[10] doi:10.3389/fendo.2026.1828487 [code]
Castration-induced nigrostriatal deficits are linked to reduced TrkB and loss of mature spines in the dorsal striatum.
Journal: Frontiers in endocrinology
In common: mouse, cellular / molecular, 2 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.