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Drug-induced changes in connectivity to midbrain dopamine cells revealed by rabies monosynaptic tracing.

Code ↔ Paper

11 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 11 matches
  1. [1] § Materials and methods › Dimensionality reduction of RABV input data ↔ 10-gene-expression-analysis-cocaine.ipynb, lines 375–384 · score 0.74 · anterior cortex, DStr, LDT, PVH, LHb, VP
  2. [2] § Materials and methods › Experimental procedures › Stereotaxic surgery ↔ 2-DAT-Cre vs GAD2-Cre and vGluT2-Cre-euclidean.ipynb, lines 263–277 · score 0.71 · vGluT2, GAD2 Cre, DAT Cre, mPFC, cTRIO, Amygdala
  3. [3] § Materials and methods › Experimental procedures › Stereotaxic surgery ↔ 0-data-exploration-master-euclidean.ipynb, lines 2482–2537 · score 0.62 · vGluT2, mPFC, cTRIO, GAD2 Cre, DAT Cre, NAcLat
  4. [4] § Results › A single injection of an addictive drug changes brain-wide input patterns to VTADA cells ↔ 2-DAT-Cre vs GAD2-Cre and vGluT2-Cre-euclidean.ipynb, lines 263–277 · score 0.61 · vGluT2, GAD2 Cre, DAT Cre, isoflurane anesthetized, cocaine, cell
  5. [5] § Results › Exploring gene expression patterns that predict changes in RABV input labeling ↔ 11-gene-expression-analysis-comparison-controls.ipynb, lines 911–914 · score 0.57 · ligand gated ion, voltage gated ion, ion channel, gene expression
  6. [6] § Results › A single injection of an addictive drug changes brain-wide input patterns to VTADA cells ↔ 10-gene-expression-analysis-cocaine.ipynb, lines 375–384 · score 0.55 · DStr, PVH, LHb, VP, CeA, PO
  7. [7] § Results › Exploring gene expression patterns that predict changes in RABV input labeling ↔ 11-gene-expression-analysis-comparison-controls.ipynb, lines 1145–1186 · score 0.55 · exocytosis genes, linear regressions, endo, gene expression, ratios, drug
  8. [8] § Results › Dimensionality reduction methods identify differences in inputs of VTA cell populations ↔ 2-DAT-Cre vs GAD2-Cre and vGluT2-Cre-euclidean.ipynb, lines 540–550 · score 0.55 · Euclidean distance, GAD2 Cre, DAT Cre, PCA
  9. [9] § Results › Dimensionality reduction methods identify differences in inputs of VTA cell populations ↔ 2-DAT-Cre vs GAD2-Cre and vGluT2-Cre-euclidean.ipynb, lines 299–351 · score 0.54 · standard deviation, GAD2 Cre, DAT Cre, error, Dimensionality
  10. [10] § Results › Exploring gene expression patterns that predict changes in RABV input labeling ↔ 11-gene-expression-analysis-comparison-controls.ipynb, lines 911–914 · score 0.51 · ligand gated ion, voltage gated ion, ion channel, Gene Expression
  11. [11] § Results › Dimensionality reduction methods identify differences in inputs of VTA cell populations ↔ 10-gene-expression-analysis-cocaine.ipynb, lines 400–438 · score 0.50 · anterior cortex, LHb, VP, CeA, PO, EP

Paper

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The authors' code

Jupyter notebook · 687 lines · 748 KB · MIT · 4 matches

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It can be read at the source: 2-DAT-Cre vs GAD2-Cre and vGluT2-Cre-euclidean.ipynb.

Overview

Authors: Katrina Bartas1, Pieter Derdeyn1, Guilian Tian2, Jose J Vasquez2, Ghalia Azouz2, Cindy M Yamamoto2, May Hui2, Kevin T Beier2,3,4,5
ORCID iDs: Pieter Derdeyn, Jose J Vasquez, May Hui, Kevin T Beier
  1. Program in Mathematical, Computational, and Systems Biology, University of California, Irvine Irvine United States
  2. Department of Physiology and Biophysics, University of California, Irvine Irvine United States
  3. Department of Biomedical Engineering, University of California, Irvine Irvine United States
  4. Department of Neurobiology and Behavior, University of California, Irvine Irvine United States
  5. Department of Pharmaceutical Sciences, University of California, Irvine Irvine United States
Institutions: University of California, Irvine (United States)
Journal: eLife, volume 13, article RP93664
Dates: published online 15 May 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.7554/elife.93664 · PMID 42138352 · PMCID PMC13179063 · OpenAlex W4394581287
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: mouse (organism), other condition (population), cellular / molecular (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions, Preprocessing, Evoked potentials, Connectivity
Keywords: addictive drugs, input mapping, rabies virus, ketamine/xylazine, cellular activity, connectomics, Mouse
MeSH: Dopaminergic Neurons*, Mesencephalon*, Rabies virus*, Animals, Male, Mice, Mice, Inbred C57BL (* major topic)
Journal subjects: Neuroscience
Topic: Neurotransmitter Receptor Influence on Behavior (Cellular and Molecular Neuroscience, Neuroscience), according to OpenAlex
Funding: National Institutes of Health (R00 DA041445, DP2 AG067666, R01 DA054374, R01 DA056599, R01 NS130044, T32 GM008620, F30 DA056215, T32 GM136624); Tobacco-Related Disease Research Program (T31KT1437, T31P1426); American Parkinson's Disease Foundation (APDA-5589562); Alzheimer's Association (AARG-NTF-20-685694); New Vision Research (CCAD2020-002); BrightFocus Foundation (A2022031S); Brain and Behavior Research Foundation (NARSAD 26845); U.S. National Science Foundation (GRFP DGE-1839285)
Citations: cited by 1 paper (Europe PMC); 88 references in the paper
Research resources: pAAV2-8 RRID:Addgene_112864, RRID:Addgene_113694, pAAV2-5 RRID:Addgene_232922, HEK293T RRID:CVCL_0063, C57BL/6J RRID:IMSR_JAX:000664, DAT-Cre RRID:IMSR_JAX:006660, vGluT2-Cre RRID:IMSR_JAX:016963, GAD2-Cre RRID:IMSR_JAX:028867

Abstract

Addictive drugs cause long-lasting changes in connectivity from inputs onto ventral tegmental area dopamine cells (VTADA) that contribute to drug-induced behavioral adaptations. However, it is not known which inputs are altered. Here, we used a rabies virus (RABV)-based mapping strategy to quantify RABV-labeled inputs to VTA cells after a single exposure to one of a variety of misused drugs – cocaine, amphetamine, methamphetamine, morphine, and nicotine – and compared the relative global input labeling across conditions. We observed that all tested addictive drugs elicited similar input changes onto VTADA cells, in particular onto DA cells projecting to the lateral shell of the nucleus accumbens and amygdala. In addition, repeated administration of ketamine/xylazine to induce anesthesia induces a change in inputs to VTADA cells that is similar to but different from those elicited by a single exposure to addictive drugs, suggesting that caution should be taken when using ketamine/xylazine-based anesthesia in rodents when assessing motivated behaviors. Furthermore, comparison of viral tracing data to an atlas of gene expression in the adult mouse brain showed that the basal expression patterns of several gene classes, especially calcium channels, were highly correlated with the extent of both addictive drug- or ketamine/xylazine-induced changes in RABV-labeled inputs to VTADA cells. Reducing expression levels of the voltage-gated calcium channel Cacna1e in cells in the nucleus accumbens lateral shell reduced RABV-mediated input labeling of these cells into VTADA cells. These results directly link genes controlling cellular excitability and the extent of input labeling by RABV.

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

Repositories

Its files are read in the Code ↔ Paper reader above, with 11 matches between paragraphs and lines of code.

ejcorn/mouse_abi_tool

License: MIT
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: 5efe587ddbe223518503b28065435da95bfaf7ff, 16 July 2021
Languages: R (11)
Size: 19 files, 11 scripts
Software Heritage: archived
Found in: the text, “Gene expression data access and processing”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: cowplot (1 file), ggplot2 (1 file), tidyverse (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
13 files
At the source: github.com/ejcorn/mouse_abi_tool

ktbartas/Bartas_et_al_eLife_2024

License: MIT
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: 4868c4c1df5cea4574c924df6042999362407284, 2 May 2026
Languages: Jupyter (14)
Size: 22 files, 14 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README, license file, 14 notebooks
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Matplotlib (8 files), NumPy (8 files), pandas (8 files), SciPy (7 files), seaborn (7 files), scikit-learn (3 files), UMAP (3 files), AllenSDK (1 file), Pillow (1 file), statsmodels (1 file), tifffile (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
8 files, not copied: shown from their source

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At the source: github.com/ktbartas/Bartas_et_al_eLife_2024

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:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 19 scripts, each with its path and the digest of its content;
  • 11 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

Datasets cited

Data availability

The current manuscript is largely a computational study, so no data have been generated for most of this manuscript, except for Figure 10; raw data are available for Figure 10 on Dryad at https://doi.org/10.5061/dryad.gxd25481q. Code used for this work is available on GitHub (https://github.com/ktbartas/Bartas_et_al_eLife_2024 copy archived at Bartas and Derdeyn, 2026).

The following dataset was generated:

BartasK DerdeynP BeierKT 2026Drug-induced changes in connectivity to midbrain dopamine cells revealed by rabies monosynaptic tracingDryad Digital Repository10.5061/dryad.gxd25481qPMC1317906342138352

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, 28 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 8 authors, 7 keywords, 7 MeSH terms, 8 funders, 84 references, 8 RRIDs.

Cite

This paper

Bartas, K., Derdeyn, P., Tian, G., Vasquez, J. J., Azouz, G., Yamamoto, C. M., Hui, M., & Beier, K. T. (2026). Drug-induced changes in connectivity to midbrain dopamine cells revealed by rabies monosynaptic tracing. eLife, 13, RP93664. https://doi.org/10.7554/elife.93664

BibTeX

@article{bartas2026drug,
author = {Bartas, Katrina and Derdeyn, Pieter and Tian, Guilian and Vasquez, Jose J and Azouz, Ghalia and Yamamoto, Cindy M and Hui, May and Beier, Kevin T},
title = {{Drug-induced changes in connectivity to midbrain dopamine cells revealed by rabies monosynaptic tracing}},
journal = {eLife},
year = {2026},
month = may,
volume = {13},
pages = {RP93664},
publisher = {eLife Sciences Publications, Ltd},
issn = {2050-084X},
doi = {10.7554/elife.93664},
url = {https://doi.org/10.7554/elife.93664},
pmid = {42138352},
pmcid = {PMC13179063}
}

RIS

TY - JOUR
AU - Bartas, Katrina
AU - Derdeyn, Pieter
AU - Tian, Guilian
AU - Vasquez, Jose J
AU - Azouz, Ghalia
AU - Yamamoto, Cindy M
AU - Hui, May
AU - Beier, Kevin T
TI - Drug-induced changes in connectivity to midbrain dopamine cells revealed by rabies monosynaptic tracing
T2 - eLife
J2 - Elife
PY - 2026
DA - 2026/05/15
VL - 13
SP - RP93664
SN - 2050-084X
PB - eLife Sciences Publications, Ltd
DO - 10.7554/elife.93664
UR - https://doi.org/10.7554/elife.93664
LA - en
ER -

CSL-JSON

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