Separable and integrated pleasantness coding for appetitive and aversive odors across olfactory and ventral prefrontal cortices.

Code ↔ Paper

4 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 4 matches · 1 of them tie a paragraph to a whole file, not to given lines: a weak match, whose lines are not tinted

[1] § Methods › Cross-decoding analyses ↔ common_functions/invnorm_reslice_masks.m, lines 1–129 · score 0.69 · MNI space, native spaces, inverse normalized
[2] § Methods › Regions of interest (ROI) ↔ common_functions/invnorm_reslice_masks.m, lines 1–129 · score 0.64 · native space, inverse normalized, atlas, insula, masks, voxels
[3] § Methods › Representational similarity analyses (RSA) ↔ common_functions/discontinued_scripts/ARC_binandRSAcomparision.m, lines 269–346 · score 0.55 · linear regression, neural activity, iterations, RSA, bins, correlation
[4] § Methods › Basic decoding analyses ↔ common_functions/ARC_regress_nested.m, the whole file · a weak match · score 0.53 · Pearson correlation, cross validation, split, trained, accuracy, regression

Paper

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

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The authors' code

MATLAB · 167 lines · 6.2 KB · MIT · 2 matches

function out = invnorm_reslice_masks(maskDir, maskFiles, anatDir, varargin)
% invnorm_reslice_masks
% Inverse-normalize atlas/mask(s) to subject native space, then reslice to a
% chosen reference image (e.g., anat or first functional).
%
% Inputs
% maskDir : folder containing mask(s) defined in normalized/MNI space
% maskFiles : char or cellstr of mask filenames (e.g., 'insula.nii' or {'insula.nii','DLPFC.nii'})
% anatDir : subject's anatomical folder (contains y_*.nii, anatomical .nii)
%
% Name/Value options
% 'AnatFilePattern' : cellstr patterns to find native anat (default {'s*.nii','means*.nii'})
% 'DefFilePattern' : cellstr patterns to find forward def field y_*.nii (default {'y_*.nii','y_s*.nii','y_means*.nii'})
% 'InvDefName' : inverse def filename to write (default 'y_inverse.nii')
% 'DoMakeInverse' : true/false, make inverse if missing (default true)
% 'RefImage' : full path to image used for reslicing (default: auto-pick in anatDir)
% 'RefPattern' : patterns to find ref image if RefImage not given (default {'rf*.nii','s*.nii'})
% 'BB' : bounding box for write (default [-78 -112 -85; 78 95 85])
% 'Vox' : voxel size for write (default [1 1 1])
% 'InterpWrite' : interpolation for write (0=nearest) (default 0; keeps masks binary-ish)
% 'InterpReslice' : interpolation for reslice (default 0)
% 'CopyWToAnat' : move w* masks to anatDir after write (default false)
% 'ReslicePrefix' : prefix for resliced output (default 'r')
%
% Output (struct)
% out.invDef : path to inverse deformation
% out.wMasks : cellstr paths to inverse-normalized masks (w*)
% out.rwMasks : cellstr paths to resliced masks (r w*)
% out.refImage : path used for reslicing
%
% Requires SPM12 on MATLAB path.
% --- defaults & parsing ---
ip = inputParser;
addParameter(ip,'AnatFilePattern', {'s*.nii','means*.nii'});
addParameter(ip,'DefFilePattern', {'y_*.nii','y_s*.nii','y_means*.nii'});
addParameter(ip,'InvDefName', 'y_inverse.nii');
addParameter(ip,'DoMakeInverse', true);
addParameter(ip,'RefImage', '');
addParameter(ip,'RefPattern', {'rf*.nii','s*.nii'});
addParameter(ip,'BB', [-78 -112 -85; 78 95 85]);
addParameter(ip,'Vox', [1 1 1]);
addParameter(ip,'InterpWrite', 0);
addParameter(ip,'InterpReslice', 0);
addParameter(ip,'CopyWToAnat', false);
addParameter(ip,'ReslicePrefix', 'r');
parse(ip, varargin{:});
opt = ip.Results;
if ischar(maskFiles), maskFiles = {maskFiles}; end
% --- init SPM ---
spm('defaults','fmri');
try, spm_jobman('initcfg'); end
% --- locate anat file & forward deformation ---
anatFile = find_first(anatDir, opt.AnatFilePattern, true);
defFile = find_first(anatDir, opt.DefFilePattern, true);
% --- inverse deformation: create if missing ---
invDef = fullfile(anatDir, opt.InvDefName);
if ~exist(invDef,'file')
if ~opt.DoMakeInverse
error('Inverse deformation not found: %s', invDef);
end
matlabbatch = [];
matlabbatch{1}.spm.util.defs.comp{1}.inv.comp{1}.def = {defFile};
matlabbatch{1}.spm.util.defs.comp{1}.inv.space = {anatFile};
matlabbatch{1}.spm.util.defs.out{1}.savedef.ofname = opt.InvDefName;
matlabbatch{1}.spm.util.defs.out{1}.savedef.savedir.saveusr = {anatDir};
spm_jobman('run', matlabbatch);
end
% --- apply inverse deformation to masks (write) ---
resampleList = cellfun(@(f) fullfile(maskDir,f), maskFiles, 'uni', false);
matlabbatch = [];
matlabbatch{1}.spm.spatial.normalise.write.subj.def = {invDef};
matlabbatch{1}.spm.spatial.normalise.write.subj.resample = resampleList(:);
matlabbatch{1}.spm.spatial.normalise.write.woptions.bb = opt.BB;
matlabbatch{1}.spm.spatial.normalise.write.woptions.vox = opt.Vox;
matlabbatch{1}.spm.spatial.normalise.write.woptions.interp = opt.InterpWrite;
spm_jobman('run', matlabbatch);
% paths to written masks (prefix 'w')
wMasks = cellfun(@(f) fullfile(maskDir, ['w' strip_gz(f)]), maskFiles, 'uni', false);
% optionally move w* to anatDir
if opt.CopyWToAnat
for i=1:numel(wMasks)
tgt = fullfile(anatDir, get_filename(wMasks{i}));
if ~strcmp(wMasks{i}, tgt)
if exist(tgt,'file'), delete(tgt); end
movefile(wMasks{i}, tgt);
wMasks{i} = tgt;
end
end
end
% --- pick reslice reference ---
if ~isempty(opt.RefImage)
refImage = opt.RefImage;
else
refImage = find_first(anatDir, opt.RefPattern, true);
end
refCell = {sprintf('%s,1', refImage)};
% --- reslice to reference (coreg write) ---
matlabbatch = [];
matlabbatch{1}.spm.spatial.coreg.write.ref = refCell;
matlabbatch{1}.spm.spatial.coreg.write.source = wMasks(:);
matlabbatch{1}.spm.spatial.coreg.write.roptions.interp = opt.InterpReslice;
matlabbatch{1}.spm.spatial.coreg.write.roptions.wrap = [0 0 0];
matlabbatch{1}.spm.spatial.coreg.write.roptions.mask = 0;
matlabbatch{1}.spm.spatial.coreg.write.roptions.prefix = opt.ReslicePrefix;
spm_jobman('run', matlabbatch);
% resliced outputs have prefix 'r' (default), applied to the *current* mask paths
rwMasks = prepend_prefix(wMasks, opt.ReslicePrefix);
% --- (optional) quick orientation sanity check ---
% v = spm_vol([{refImage}; rwMasks(:)]);
% spm_check_orientations([v{:}]);
% --- out ---
out = struct('invDef',invDef, 'wMasks',{wMasks}, 'rwMasks',{rwMasks}, 'refImage',refImage);
end
% ===== helpers =====
function f = find_first(dirpath, patterns, mustExist)
if ischar(patterns), patterns = {patterns}; end
f = '';
for i=1:numel(patterns)
dd = dir(fullfile(dirpath, patterns{i}));
if ~isempty(dd)
f = fullfile(dirpath, dd(1).name);
break;
end
end
if mustExist && isempty(f)
error('File not found in %s for patterns: %s', dirpath, strjoin(patterns, ', '));
end
end
function s = strip_gz(fname)
% remove trailing .gz if present
[p,n,e] = fileparts(fname);
if strcmpi(e,'.gz')
[~,n2,e2] = fileparts(n);
s = [n2 e2];
else
s = [n e];
end
end
function n = get_filename(pth)
[~,n,ext] = fileparts(pth);
n = [n ext];
end
function out = prepend_prefix(paths, prefix)
out = cell(size(paths));
for i=1:numel(paths)
[p,n,e] = fileparts(paths{i});
out{i} = fullfile(p, [prefix n e]);
end
end

invnorm_reslice_masks.m at commit 5fd5bf9, under MIT · at the source

Overview

Authors: Vivek Sagar^1,2, Christina M. Zelano¹, Thorsten Kahnt³

ORCID iDs: Vivek Sagar, Christina M. Zelano, Thorsten Kahnt

Institutions: Northwestern University (United States); Dartmouth College (United States); National Institute on Drug Abuse (United States)

Journal: Nature communications, volume 17, issue 1, article 6732

Dates: received 6 January 2025; accepted 22 April 2026; published online 22 May 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.1038/s41467-026-73001-7 · PMID 42173851 · PMCID PMC13385377 · OpenAlex W7162133109

Open access: gold, a free copy (OpenAlex)

Status: code verified

Categories: human (organism), cognitive (subfield)

Methods: Statistics, Machine learning, Preprocessing, Connectivity, fMRI & imaging

Keywords: Olfactory cortex, Cognitive neuroscience

MeSH: Odorants*, Olfactory Cortex*, Olfactory Perception*, Prefrontal Cortex*, Smell*, Amygdala, Brain Mapping, Female, Humans, Magnetic Resonance Imaging, Male, Piriform Cortex (* major topic)

Topic: Olfactory and Sensory Function Studies (Sensory Systems, Neuroscience), according to OpenAlex

Funding: National Institute on Drug Abuse (ZIA DA000642)

Citations: not cited yet (Europe PMC); 68 references in the paper

Abstract

Odor pleasantness is a key driver of approach and avoidance behaviors, raising the question of how pleasantness is represented in olfactory brain areas. To address this question, here we analyzed an existing dataset consisting of perceptual and fMRI responses to 160 odors from three individual participants. We find that piriform cortex, amygdala, orbitofrontal cortex, and ventromedial prefrontal cortex encode the pleasantness of appetitive and aversive odors. However, whereas these pleasantness representations are separable for appetitive and aversive odors in piriform cortex and amygdala, ventral prefrontal cortex (especially area 11) combines information from appetitive and aversive odors and forms a continuous representation of odor salience. These results suggest that distinct pleasantness codes for appetitive and aversive odors in olfactory cortices are integrated into a continuous representation in ventral prefrontal cortices.

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 4 matches between paragraphs and lines of code.

viveksgr/ARC

License: MIT

State: the link answers, verified on 28 September 2026

Evidence: files inventoried

Commit: 5fd5bf96845fa46144e5d972a404e5b5cfb3406f, 19 March 2026

Languages: MATLAB (147), C++ (1)

Size: 207 files, 148 scripts

Software Heritage: not archived

Found in: “Code availability”

Holds: README, license file

Not found: CITATION.cff, environment file, tests, continuous integration, documentation

Tools: Statistics and Machine Learning Toolbox (63 files), SPM (27 files), GLMsingle (3 files), Signal Processing Toolbox (1 file)

Availability: 1 check, the latest on 28 September 2026: the link answers

28 September 2026: the link answers

150 files

ARC_RSA_analyses.m, MATLAB, 735 lines
ARC_createsingletrials.m, MATLAB, 173 lines
ARC_decoding_analyses.m, MATLAB, 426 lines
additional_controls/ARC_create_behav_corr.m, MATLAB, 42 lines
additional_controls/ARC_sniff_control.m, MATLAB, 120 lines
additional_controls/debug_rsafdr.m, MATLAB, 45 lines
common_functions/ARC_RSA_analyses.m, MATLAB, 572 lines
common_functions/ARC_RSA_binned_searchl.m, MATLAB, 134 lines
common_functions/ARC_RSA_func.m, MATLAB, 41 lines
common_functions/ARC_RSA_pvals.m, MATLAB, 45 lines
common_functions/ARC_RSA_pvals_diff.m, MATLAB, 56 lines
common_functions/ARC_applyFunctionToUpperTriangle.m, MATLAB, 23 lines
common_functions/ARC_average_chunks.m, MATLAB, 23 lines
common_functions/ARC_balanceClasses.m, MATLAB, 28 lines
common_functions/ARC_barplot.m, MATLAB, 37 lines
common_functions/ARC_barplot_sig.m, MATLAB, 73 lines
common_functions/ARC_bidirectionalFDR.m, MATLAB, 72 lines
common_functions/ARC_binAndTransform.m, MATLAB, 14 lines
common_functions/ARC_binAndTransformQuantiles.m, MATLAB, 28 lines
common_functions/ARC_binAndTransformQuantiles_shuff.m, MATLAB, 34 lines
common_functions/ARC_binAndTransform_numctrl.m, MATLAB, 41 lines
common_functions/ARC_binAndTransform_numctrl_colrow.m, MATLAB, 43 lines
common_functions/ARC_binAndTransform_shuff.m, MATLAB, 21 lines
common_functions/ARC_binAndTransform_shuffcoarse.m, MATLAB, 36 lines
common_functions/ARC_binAndTransform_shuffcoarse_old.m, MATLAB, 17 lines
common_functions/ARC_binAndTransform_sz.m, MATLAB, 22 lines
common_functions/ARC_boxplot_groups.m, MATLAB, 61 lines
common_functions/ARC_build_behav_RSM.m, MATLAB, 43 lines
common_functions/ARC_cellAvg3D.m, MATLAB, 32 lines
common_functions/ARC_classifyVoxelSign.m, MATLAB, 51 lines
common_functions/ARC_combine2conds.m, MATLAB, 102 lines
common_functions/ARC_combinePValues3D.m, MATLAB, 31 lines
common_functions/ARC_compareCorrIndep.m, MATLAB, 42 lines
common_functions/ARC_compareMatFiles.m, MATLAB, 49 lines
common_functions/ARC_computePValueOneTailed.m, MATLAB, 18 lines
common_functions/ARC_computeWeights_tsc.m, MATLAB, 29 lines
common_functions/ARC_configROI_mask.m, MATLAB, 16 lines
common_functions/ARC_createOFC_mask.m, MATLAB, 12 lines
common_functions/ARC_createplt.m, MATLAB, 13 lines
common_functions/ARC_createsingletrials.m, MATLAB, 150 lines
common_functions/ARC_createsingletrials2.m, MATLAB, 154 lines
common_functions/ARC_customcmap.m, MATLAB, 41 lines
common_functions/ARC_decoding_pvals.m, MATLAB, 74 lines
common_functions/ARC_decoding_pvals_tsc.m, MATLAB, 58 lines
common_functions/ARC_decoding_pvals_zsc.m, MATLAB, 59 lines
common_functions/ARC_denoisePCA.m, MATLAB, 18 lines
common_functions/ARC_diff2conds_dfweighted.m, MATLAB, 85 lines
common_functions/ARC_diff2conds_lessConservative.m, MATLAB, 79 lines
common_functions/ARC_extractLabels.m, MATLAB, 8 lines
common_functions/ARC_extract_roi_trials.m, MATLAB, 17 lines
common_functions/ARC_extract_roi_trials_travg.m, MATLAB, 21 lines
common_functions/ARC_extract_roi_trials_travg_dec.m, MATLAB, 21 lines
common_functions/ARC_fourAxisLDA.m, MATLAB, 66 lines
common_functions/ARC_inversePercentiles.m, MATLAB, 48 lines
common_functions/ARC_load_subject_data.m, MATLAB, 18 lines
common_functions/ARC_main.m, MATLAB, 124 lines
common_functions/ARC_makeDecodingCfg.m, MATLAB, 73 lines
common_functions/ARC_make_default_config.m, MATLAB, 64 lines
common_functions/ARC_make_group_stats.m, MATLAB, 39 lines
common_functions/ARC_matprod.m, MATLAB, 13 lines
common_functions/ARC_mean_posneg_thresholds.m, MATLAB, 28 lines
common_functions/ARC_median_balance_zero.m, MATLAB, 41 lines
common_functions/ARC_multicomputeWeights_onesc.m, MATLAB, 51 lines
common_functions/ARC_multicomputeWeights_shuff.m, MATLAB, 45 lines
common_functions/ARC_multicomputeWeights_tsc.m, MATLAB, 58 lines
common_functions/ARC_multicomputeWeights_tsc_voxwise.m, MATLAB, 43 lines
common_functions/ARC_multicomputeWeights_tsc_voxwise_boot.m, MATLAB, 126 lines
common_functions/ARC_odor_select.m, MATLAB, 52 lines
common_functions/ARC_p2r.m, MATLAB, 28 lines
common_functions/ARC_pcm.m, MATLAB, 112 lines
common_functions/ARC_pcm_cell.m, MATLAB, 94 lines
common_functions/ARC_percentileAbsWeights.m, MATLAB, 30 lines
common_functions/ARC_plotColorGradientLines.m, MATLAB, 34 lines
common_functions/ARC_plotDecoding.m, MATLAB, 18 lines
common_functions/ARC_plotMatrixLines.m, MATLAB, 47 lines
common_functions/ARC_prctile_mat_comp.m, MATLAB, 13 lines
common_functions/ARC_prctile_mat_comp_prc.m, MATLAB, 13 lines
common_functions/ARC_prepareROI.m, MATLAB, 61 lines
common_functions/ARC_projectV1onV2.m, MATLAB, 9 lines
common_functions/ARC_r2t.m, MATLAB, 7 lines
common_functions/ARC_regress_nested.m, MATLAB, 77 lines, 1 match
common_functions/ARC_regress_nested2.m, MATLAB, 85 lines
common_functions/ARC_regress_nested2_backup.m, MATLAB, 83 lines
common_functions/ARC_regress_nested2_normed.m, MATLAB, 90 lines
common_functions/ARC_regress_nested3.m, MATLAB, 85 lines
common_functions/ARC_regress_nested_mdl.m, MATLAB, 66 lines
common_functions/ARC_regress_normed.m, MATLAB, 51 lines
common_functions/ARC_regress_wrapper.m, MATLAB, 33 lines
common_functions/ARC_runDecoding.m, MATLAB, 152 lines
common_functions/ARC_runDecoding_searchl.m, MATLAB, 238 lines
common_functions/ARC_run_RSA_for_subject.m, MATLAB, 174 lines
common_functions/ARC_run_RSA_full.m, MATLAB, 84 lines
common_functions/ARC_scatterDensity.m, MATLAB, 32 lines
common_functions/ARC_searchlight_transform.m, MATLAB, 51 lines
common_functions/ARC_searchlightdec_ROI.m, MATLAB, 81 lines
common_functions/ARC_summarize_beta_and_p.m, MATLAB, 56 lines
common_functions/ARC_summarize_beta_and_p2.m, MATLAB, 72 lines
common_functions/ARC_thresholdPercentages.m, MATLAB, 48 lines
common_functions/ARC_transformMatrix.m, MATLAB, 25 lines
common_functions/ARC_twoAxisLDA.m, MATLAB, 44 lines
common_functions/ARC_voxelPLS.m, MATLAB, 32 lines
common_functions/ARC_voxwise.m, MATLAB, 119 lines
common_functions/SFP_clearLargeVariables.m, MATLAB, 24 lines
common_functions/SFP_multicomputeWeights_shuff.m, MATLAB, 25 lines
common_functions/binop_pvals_by_tail.m, MATLAB, 107 lines
common_functions/blockRowIndices.m, MATLAB, 40 lines
common_functions/bootstrapRidge.m, MATLAB, 46 lines
common_functions/bootstrapRidgeres.m, MATLAB, 56 lines
common_functions/combineRmaps_meta_bi_weighted.m, MATLAB, 53 lines
common_functions/combine_masks_features_aligned.m, MATLAB, 112 lines
common_functions/comparePerformance.m, MATLAB, 46 lines
common_functions/correlateDistanceMatrix2.m, MATLAB, 32 lines
common_functions/create_ARCscatter.m, MATLAB, 45 lines
common_functions/cvLdaLasso.m, MATLAB, 59 lines
common_functions/discontinued_scripts/ARC_Avgtables.m, MATLAB, 31 lines
common_functions/discontinued_scripts/ARC_RSA_timeline.m, MATLAB, 499 lines
common_functions/discontinued_scripts/ARC_RSA_valsep.m, MATLAB, 582 lines
common_functions/discontinued_scripts/ARC_RSA_valsep_traj.m, MATLAB, 245 lines
common_functions/discontinued_scripts/ARC_RSAmaps.m, MATLAB, 390 lines
common_functions/discontinued_scripts/ARC_Rconnectivitymaps.m, MATLAB, 217 lines
common_functions/discontinued_scripts/ARC_binandRSAcomparision.m, MATLAB, 346 lines, 1 match
common_functions/discontinued_scripts/ARC_identitycoding.m, MATLAB, 269 lines
common_functions/discontinued_scripts/ARC_overlaps.m, MATLAB, 131 lines
common_functions/discontinued_scripts/correlateDistanceMatrix.m, MATLAB, 23 lines
common_functions/discontinued_scripts/simulation_repeatability_inst.m, MATLAB, 33 lines
common_functions/fastMaxCorrelation.cpp, C++, 72 lines
common_functions/fdr_benjhoc.m, MATLAB, 51 lines
common_functions/invnorm_reslice_masks.m, MATLAB, 167 lines, 2 matches
common_functions/invprctile.m, MATLAB, 232 lines
common_functions/iter_corr.m, MATLAB, 37 lines
common_functions/make_masks.m, MATLAB, 45 lines
common_functions/nii_extract.m, MATLAB, 70 lines
common_functions/nii_extract2.m, MATLAB, 82 lines
common_functions/nii_extract_list.m, MATLAB, 75 lines
common_functions/pairwise_signedrank.m, MATLAB, 43 lines
common_functions/plotBarWithSignificance.m, MATLAB, 46 lines
common_functions/plot_avg_histograms_by_feature.m, MATLAB, 100 lines
common_functions/plot_pleasantness_correlations.m, MATLAB, 149 lines
common_functions/plot_roi_bars_with_subjects.m, MATLAB, 133 lines
common_functions/plot_varset_roi_lines.m, MATLAB, 59 lines
common_functions/pvals_across_params.m, MATLAB, 127 lines
common_functions/r2p_onetail.m, MATLAB, 31 lines
common_functions/readmeusefulstuff.m, MATLAB, 8 lines
common_functions/regressmeout.m, MATLAB, 16 lines
common_functions/selectLess4AndHalf4.m, MATLAB, 32 lines
common_functions/sfp_decorrelate_sig.m, MATLAB, 23 lines
common_functions/t2p_tail.m, MATLAB, 23 lines
common_functions/vs_normalizer.m, MATLAB, 14 lines
LICENSE.txt, License, 21 lines
README.md, Text, 56 lines

At the source: github.com/viveksgr/ARC

Zenodo 19119376

License: MIT

State: the link answers, verified on 28 September 2026

Evidence: files inventoried

Size: 1 file

Software Heritage: not checked

Found in: “Code availability”

Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation

Availability: 1 check, the latest on 28 September 2026: the link answers (HTTP 200)

28 September 2026: the link answers (HTTP 200)

At the source:

Zenodo 19119377

License: MIT

State: the link answers, verified on 28 September 2026

Evidence: files inventoried

Size: 1 file

Software Heritage: not checked

Found in: the references

Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation

Availability: 1 check, the latest on 28 September 2026: the link answers (HTTP 200)

28 September 2026: the link answers (HTTP 200)

At the source:

Code availability

All analyses were performed using custom scripts in MATLAB 2023b and the LibSVM package66 for decoding. Other software packages used in the study were SPM1267, GLMSingle61,62, and Breathmetrics toolbox68. Code for preprocessing and reproducing the results presented in this manuscript is available at https://github.com/viveksgr/ARC and archived on Zenodo 10.5281/zenodo.1911937665.

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

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:

3 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
148 scripts, each with its path and the digest of its content;
4 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

zenodo:7636722, at Zenodo; found in “Data availability”

Data availability

Dataset to reproduce all major findings of the study is available without restriction at https://github.com/viveksgr/ARC and archived on Zenodo 10.5281/zenodo.1911937665. Analyses presented in this manuscript are based on previously published dataset 10.5281/zenodo.763672263. The access request to the raw dataset can be submitted at Zenodo and is subject to a data-use agreement that restricts use to research purposes, prohibits re-identification and redistribution, and requires citation of the associated Zenodo DOI and publication. The timeframe for response to requests is approximately 10 business days.

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, issue, pages, dates, 3 authors, 2 keywords, 12 MeSH terms, 1 funder, 66 references.

Cite

This paper

Sagar, V., Zelano, C. M., & Kahnt, T. (2026). Separable and integrated pleasantness coding for appetitive and aversive odors across olfactory and ventral prefrontal cortices. Nature communications, 17(1), 6732. https://doi.org/10.1038/s41467-026-73001-7

BibTeX

@article{sagar2026separable, author = {Sagar, Vivek and Zelano, Christina M. and Kahnt, Thorsten}, title = {{Separable and integrated pleasantness coding for appetitive and aversive odors across olfactory and ventral prefrontal cortices}}, journal = {Nature communications}, year = {2026}, month = may, volume = {17}, number = {1}, pages = {6732}, publisher = {Nature Publishing Group}, issn = {2041-1723}, doi = {10.1038/s41467-026-73001-7}, url = {https://doi.org/10.1038/s41467-026-73001-7}, pmid = {42173851}, pmcid = {PMC13385377} }

RIS

TY - JOUR AU - Sagar, Vivek AU - Zelano, Christina M. AU - Kahnt, Thorsten TI - Separable and integrated pleasantness coding for appetitive and aversive odors across olfactory and ventral prefrontal cortices T2 - Nature communications J2 - Nat Commun PY - 2026 DA - 2026/05/22 VL - 17 IS - 1 SP - 6732 SN - 2041-1723 PB - Nature Publishing Group DO - 10.1038/s41467-026-73001-7 UR - https://doi.org/10.1038/s41467-026-73001-7 LA - en ER -

CSL-JSON

{ "id": "10.1038/s41467-026-73001-7", "type": "article-journal", "title": "Separable and integrated pleasantness coding for appetitive and aversive odors across olfactory and ventral prefrontal cortices", "container-title": "Nature communications", "author": [ { "family": "Sagar", "given": "Vivek" }, { "family": "Zelano", "given": "Christina M." }, { "family": "Kahnt", "given": "Thorsten" } ], "container-title-short": "Nat Commun", "volume": "17", "issue": "1", "page": "6732", "DOI": "10.1038/s41467-026-73001-7", "PMID": "42173851", "PMCID": "PMC13385377", "ISSN": "2041-1723", "publisher": "Nature Publishing Group", "URL": "https://doi.org/10.1038/s41467-026-73001-7", "language": "en", "issued": { "date-parts": [ [ 2026, 5, 22 ] ] } }

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Separable and integrated pleasantness coding for appetitive and aversive odors across olfactory and ventral prefrontal cortices.

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