Resolving mesoscale brainstem-prefrontal-striatal pathways underlying decisions upon salient events using submillimeter-resolution fMRI.

Code ↔ Paper

8 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 8 matches · 6 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted

[1] § Methods › ROI analysis ↔ align_surf_ba.sh, lines 63–115 · score 0.91 · PALS B12, ventrolateral prefrontal cortex, medial prefrontal cortex, mPFC, dorsolateral prefrontal cortex, ventral prefrontal cortex
[2] § Results › Laminar effect in the prefrontal cortex during superhigh-stake decisions ↔ align_surf_ba.sh, lines 63–115 · score 0.79 · dorsolateral prefrontal cortex, ventral prefrontal cortex, mPFC, vlPFC, ventrolateral, BA
[3] § Methods › Laminar analysis ↔ fig6_data_plot.ipynb, the whole file · a weak match · score 0.71 · laminar profiles, dlPFC, vPFC, cortical depth, superficial, deep
[4] § Results › Laminar effect in the prefrontal cortex during superhigh-stake decisions ↔ fig6_data_plot.ipynb, the whole file · a weak match · score 0.69 · laminar profiles, dlPFC, vPFC, cortical depth, SEM, ANOVA
[5] § Results › Laminar effect in the prefrontal cortex during superhigh-stake decisions ↔ fig7_AR_data_plot.ipynb, the whole file · a weak match · score 0.66 · rejected SH, dlPFC, accepted SH, ANOVAs, superficial, deep
[6] § Methods › Laminar analysis ↔ fig7_AR_data_plot.ipynb, the whole file · a weak match · score 0.63 · laminar profiles, dlPFC, cortical depth, superficial, deep, layers
[7] § Methods › Laminar analysis ↔ reconall_mtepi.sh, the whole file · a weak match · score 0.58 · anatomical MT, FreeSurfer, binned, GM, volume, EPI
[8] § Methods › ROI analysis ↔ reconall_mtepi.sh, the whole file · a weak match · score 0.52 · anatomical MT, FreeSurfer, recon, EPI

Paper

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

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The authors' code

Shell · 115 lines · 4 KB · no license · 2 matches

#!/bin/sh
dataDIR=/media/yuhui/LCT
cd ${dataDIR}
for patID in subj*; do
{
patDir=${dataDIR}/${patID}
anatDIR=${dataDIR}/${patID}/mt.sft
funcDIR=${dataDIR}/${patID}/bold.sft
sumaDir=${dataDIR}/${patID}/mt.sft/SUMA
cd ${dataDIR}
for hemi in lh rh; do
{
cd ${dataDIR}
SUBJECTS_DIR=${dataDIR}
## PALS_B12_Brodmann.annot ######################################
echo "++ PALS_B12_Brodmann.annot applied to ${hemi} of ${patID} ..."
# inverse, from Yeo_JNeurophysiol11_FreeSurfer to individual
cd ${dataDIR}
mri_surf2surf --srcsubject Yeo_JNeurophysiol11_FreeSurfer/fsaverage \
--trgsubject ${patID}/mt.sft/Surf_uni \
--sval-annot Yeo_JNeurophysiol11_FreeSurfer/fsaverage/label/${hemi}.PALS_B12_Brodmann.annot \
--tval ${patID}/mt.sft/Surf_uni/label/${hemi}.PALS_B12_Brodmann.annot \
--hemi ${hemi}
mri_surf2surf --srcsubject Yeo_JNeurophysiol11_FreeSurfer/fsaverage \
--trgsubject ${patID}/mt.sft/Surf_uni \
--sval-annot Yeo_JNeurophysiol11_FreeSurfer/fsaverage/label/${hemi}.Yeo2011_7Networks_N1000.annot \
--tval ${patID}/mt.sft/Surf_uni/label/${hemi}.Yeo2011_7Networks_N1000.annot \
--hemi ${hemi}
SUBJECTS_DIR=${anatDIR}
cd ${anatDIR}
mri_label2vol \
--annot Surf_uni/label/${hemi}.PALS_B12_Brodmann.annot \
--subject Surf_uni --identity --temp Surf_uni/mri/T1.mgz \
--hemi ${hemi} --proj frac -0.1 1.1 0.01 \
--o ${sumaDir}/PALS_B12_Brodmann.${hemi}.nii.gz
mri_label2vol \
--annot Surf_uni/label/${hemi}.Yeo2011_7Networks_N1000.annot \
--subject Surf_uni --identity --temp Surf_uni/mri/T1.mgz \
--hemi ${hemi} --proj frac -0.1 1.1 0.01 \
--o ${sumaDir}/Yeo2011_7Networks_N1000.${hemi}.nii.gz
}&
done
wait
cd ${sumaDir}
3dcalc -a Yeo2011_7Networks_N1000.lh.nii.gz -b Yeo2011_7Networks_N1000.rh.nii.gz \
-expr "a+b*iszero(a)" -prefix Yeo2011_7Networks_N1000.nii.gz -overwrite
3dROIMaker -overwrite \
-nifti \
-inflate 2 \
-refset Yeo2011_7Networks_N1000.nii.gz \
-inset Yeo2011_7Networks_N1000.nii.gz \
-prefix Yeo2011_7Networks_N1000.d2
rm Yeo2011_7Networks_N1000.d2_GM.* Yeo2011_7Networks_N1000.d2_GMI.niml.lt
3dcalc -a Yeo2011_7Networks_N1000.d2_GMI.nii.gz -expr "step(amongst(a,7))" \
-prefix default_network.nii.gz -overwrite
3dcalc -a Yeo2011_7Networks_N1000.d2_GMI.nii.gz -expr "step(amongst(a,6))" \
-prefix frontoparietal_network.nii.gz -overwrite
3dcalc -a Yeo2011_7Networks_N1000.d2_GMI.nii.gz -expr "step(amongst(a,5))" \
-prefix limbic_network.nii.gz -overwrite
3dcalc -a Yeo2011_7Networks_N1000.d2_GMI.nii.gz -expr "step(amongst(a,4))" \
-prefix ventralatten_network.nii.gz -overwrite
for atlas in PALS_B12_Brodmann.lh PALS_B12_Brodmann.rh; do
{
3dROIMaker -overwrite \
-nifti \
-inflate 2 \
-refset ${atlas}.nii.gz \
-inset ${atlas}.nii.gz \
-prefix ${atlas}.d2
rm ${atlas}.d2_GM.* ${atlas}.d2_GMI.niml.lt
}&
done
wait
cd ${sumaDir}
# The dorsolateral prefrontal cortex is composed of the BA8, BA9, BA10, and BA46
3dcalc -a PALS_B12_Brodmann.lh.d2_GMI.nii.gz -b PALS_B12_Brodmann.rh.d2_GMI.nii.gz \
-expr "step(amongst(a,2,5,43,46)+amongst(b,3,6,44,47))" \
-prefix PALS_dlpfc.nii.gz -overwrite
# The ventrolateral prefrontal cortex is composed of areas BA45, BA47, and BA44
3dcalc -a PALS_B12_Brodmann.lh.d2_GMI.nii.gz -b PALS_B12_Brodmann.rh.d2_GMI.nii.gz \
-expr "step(amongst(a,16,26,15)+amongst(b,17,27,16))" \
-prefix PALS_vlpfc.nii.gz -overwrite
# The medial prefrontal cortex (mPFC) is composed of BA12, BA25,
# and anterior cingulate cortex: BA32, BA33, BA24
3dcalc -a PALS_B12_Brodmann.lh.d2_GMI.nii.gz -b PALS_B12_Brodmann.rh.d2_GMI.nii.gz \
-expr "step(amongst(a,44,41,42)+amongst(b,45,42,43))" \
-prefix PALS_mpfc.nii.gz -overwrite
# The ventral prefrontal cortex is composed of areas BA11, BA13, and BA14.[1]
# (Also see the definition of the orbitofrontal cortex.)
3dcalc -a PALS_B12_Brodmann.lh.d2_GMI.nii.gz -b PALS_B12_Brodmann.rh.d2_GMI.nii.gz \
-expr "step(amongst(a,45)+amongst(b,46))" \
-prefix PALS_vpfc.nii.gz -overwrite
}&
done
wait

align_surf_ba.sh at commit e22e6e9, no license · at the source

Overview

Authors: Yuhui Chai^1,2, Joshua Oon Soo Goh^3,4,5,6, Bradley P. Sutton^1,2,7,8

ORCID iDs: Yuhui Chai, Joshua Oon Soo Goh, Bradley P. Sutton

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign,Urbana, IL USA
Carle Illinois Advanced Imaging Center, University of Illinois and Carle Health,Urbana, IL USA
Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine,Taipei, Taiwan
Department of Psychology, National Taiwan University,Taipei, Taiwan
Neurobiology and Cognitive Science Center, National Taiwan University,Taipei, Taiwan
Center for Artificial Intelligence and Advanced Robotics, National Taiwan University,Taipei, Taiwan
Department of Bioengineering, Grainger College of Engineering, University of Illinois at Urbana-Champaign,Urbana, IL USA
Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign,Urbana, IL USA

Institutions: University of Illinois Urbana-Champaign (United States); National Taiwan University (Taiwan)

Journal: Nature communications, volume 17, issue 1, article 5911

Dates: received 24 October 2025; accepted 16 April 2026; published online 30 April 2026

Type: Research article · Language: English

License: CC BY-NC-ND

Identifiers: DOI 10.1038/s41467-026-72605-3 · PMID 42062280 · PMCID PMC13338228 · OpenAlex W7159639077

Open access: gold, a free copy (OpenAlex)

Status: code verified

Categories: fMRI (modality), human (organism), cognitive (subfield)

Methods: Statistics, Preprocessing, fMRI & imaging

Keywords: Decision, Motivation

MeSH: Brain Stem*, Corpus Striatum*, Decision Making*, Magnetic Resonance Imaging*, Prefrontal Cortex*, Adult, Brain Mapping, Choice Behavior, Female, Humans, Male, Neural Pathways, Young Adult (* major topic)

Topic: Neural and Behavioral Psychology Studies (Cognitive Neuroscience, Neuroscience), according to OpenAlex

Funding: U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB) (R03EB034324)

Citations: cited by 1 paper (Europe PMC); 81 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.

Repositories

Its files are read in the Code ↔ Paper reader above, with 8 matches between paragraphs and lines of code.

yuhuichai/lct

License: none: the authors keep all their rights

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: e22e6e927c35f45c0da64afbc729dbdbb5e4dfed, 17 February 2026

Languages: Jupyter (18), Python (7), Shell (7), MATLAB (2)

Size: 55 files, 34 scripts

Software Heritage: not archived

Found in: “Code availability”

Holds: README, 18 notebooks

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

Tools: NumPy (25 files), Matplotlib (18 files), pandas (16 files), SciPy (11 files), statsmodels (9 files), AFNI (7 files), PsychoPy (7 files), ANTs (2 files), FreeSurfer (2 files), SPM (2 files)

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

35 files

AR_SH_fig5.ipynb, Jupyter, 181 lines
LCT_task/ADMT_practice_lastrun.py, Python, 3,409 lines
LCT_task/ADMT_r1_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r2_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r3_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r4_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r5_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r6_lastrun.py, Python, 1,721 lines
RT_fig3.ipynb, Jupyter, 206 lines
align_surf_ba.sh, Shell, 115 lines, 2 matches
behavior_AR_RT.ipynb, Jupyter, 232 lines
fig2_data_plot.ipynb, Jupyter, 98 lines
fig3_data_plot.ipynb, Jupyter, 83 lines
fig4_data_plot.ipynb, Jupyter, 85 lines
fig5_data_plot.ipynb, Jupyter, 87 lines
fig6_data_plot.ipynb, Jupyter, 116 lines, 2 matches
fig7_AR_data_plot.ipynb, Jupyter, 112 lines, 2 matches
fig7_gainloss_data_plot.ipynb, Jupyter, 117 lines
gainloss_fig4.ipynb, Jupyter, 223 lines
glm_lottery.sh, Shell, 150 lines
iti_isi_jitter.ipynb, Jupyter, 132 lines
layerProfile_acceptreject.ipynb, Jupyter, 229 lines
layerProfile_choice_outcome.ipynb, Jupyter, 221 lines
layerProfile_gainloss.ipynb, Jupyter, 194 lines
layer_MT.sh, Shell, 83 lines
mc_job.m, MATLAB, 1,335 lines
mc_run.m, MATLAB, 50 lines
motion_censor_bold.sh, Shell, 72 lines
mtepi.sh, Shell, 41 lines
reconall_mtepi.sh, Shell, 87 lines, 2 matches
roiProfile_control_v1.ipynb, Jupyter, 217 lines
split_ctrl_dant.sh, Shell, 108 lines
stake_fig2.ipynb, Jupyter, 252 lines
stakedif_figS3.ipynb, Jupyter, 256 lines
README.md, Text, 100 lines

At the source: github.com/yuhuichai/LCT/tree/main/LCT_task

afni.nimh.nih.gov

License: none: the authors keep all their rights

State: the link answers, verified on 30 September 2026

Evidence: the link answers

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 30 September 2026: the link answers (HTTP 200)

30 September 2026: the link answers (HTTP 200)

At the source: afni.nimh.nih.gov/

fil.ion.ucl.ac.uk/spm

License: none: the authors keep all their rights

State: the link answers, verified on 30 September 2026

Evidence: the link answers

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 30 September 2026: the link answers (HTTP 200)

30 September 2026: the link answers (HTTP 200)

At the source: fil.ion.ucl.ac.uk/spm/

stnava.github.io/ants

License: none: the authors keep all their rights

State: the link answers, verified on 30 September 2026

Evidence: the link answers

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 30 September 2026: the link answers (HTTP 200)

30 September 2026: the link answers (HTTP 200)

At the source: stnava.github.io/ANTs/

layerfMRI/LAYNII

License: BSD-3-Clause

State: the link answers, verified on 30 September 2026

Evidence: files inventoried

Commit: 8d6096e6443d26d461d57261fa733ce2ffbdb383, 16 September 2026

Languages: C++ (94), C/C++ (19), Shell (2)

Size: 167 files, 115 scripts

Software Heritage: not archived

Found in: “Code availability”

Holds: README, license file, CITATION.cff, environment (Dockerfile), continuous integration

Not found: tests, documentation

Availability: 1 check, the latest on 30 September 2026: the link answers

30 September 2026: the link answers

117 files

archive/LN2_COLTRIAN.cpp, C++, 326 lines
archive/LN2_DIFFUSE.cpp, C++, 462 lines
archive/LN2_FLATTEN.cpp, C++, 1,462 lines
archive/LN2_LLOYD.cpp, C++, 668 lines
archive/LN_GRADSMOOTH_ITER.cpp, C++, 434 lines
archive/LN_INFO_standalone_template.cpp, C++, 359 lines
dep/laynii_lib.cpp, C++, 1,726 lines
dep/laynii_lib.h, C/C++, 148 lines
dep/nifti1.h, C/C++, 1,528 lines
dep/nifti2.h, C/C++, 117 lines
dep/nifti2_io.cpp, C++, 5,401 lines
dep/nifti2_io.h, C/C++, 744 lines
dep/znzlib.cpp, C++, 323 lines
dep/znzlib.h, C/C++, 122 lines
ida/dep/idalib.cpp, C++, 57 lines
ida/dep/idalib.h, C/C++, 28 lines
ida/imgui/backends/imgui_impl_opengl3.cpp, C++, 986 lines
ida/imgui/backends/imgui_impl_opengl3.h, C/C++, 67 lines
ida/imgui/backends/imgui_impl_opengl3_loader.h, C/C++, 810 lines
ida/imgui/backends/imgui_impl_sdl2.cpp, C++, 1,068 lines
ida/imgui/backends/imgui_impl_sdl2.h, C/C++, 46 lines
ida/imgui/imconfig.h, C/C++, 131 lines
ida/imgui/imgui.cpp, C++, 3,165 lines
ida/imgui/imgui.h, C/C++, 1,947 lines
ida/imgui/imgui_demo.cpp, C++, 3,697 lines
ida/imgui/imgui_draw.cpp, C++, 4,050 lines
ida/imgui/imgui_internal.h, C/C++, 2,887 lines
ida/imgui/imgui_tables.cpp, C++, 3,583 lines
ida/imgui/imgui_widgets.cpp, C++, 4,113 lines
ida/imgui/imstb_rectpack.h, C/C++, 627 lines
ida/imgui/imstb_textedit.h, C/C++, 1,441 lines
ida/imgui/imstb_truetype.h, C/C++, 5,085 lines
ida/src/ida_GUI.cpp, C++, 1,923 lines
ida/src/ida_GUI.h, C/C++, 9 lines
ida/src/ida_GUI_slices.h, C/C++, 533 lines
ida/src/ida_IO.h, C/C++, 2,348 lines
ida/src/imgui_ini_embed.h, C/C++, 329 lines
ida/src/main.cpp, C++, 215 lines
src/LN2_BORDERIZE.cpp, C++, 348 lines
src/LN2_CHOLMO.cpp, C++, 595 lines
src/LN2_CIRCSHIFT.cpp, C++, 172 lines
src/LN2_COLUMNS.cpp, C++, 1,400 lines
src/LN2_CONNECTED_CLUSTERS.cpp, C++, 343 lines
src/LN2_DESPIKE.cpp, C++, 235 lines
src/LN2_DEVEIN.cpp, C++, 451 lines
src/LN2_DIRECTIONALITY_BIN.cpp, C++, 1,070 lines
src/LN2_FRISGO.cpp, C++, 453 lines
src/LN2_GEODISTANCE.cpp, C++, 579 lines
src/LN2_GRADIENTS.cpp, C++, 223 lines
src/LN2_GRAMAG.cpp, C++, 142 lines
src/LN2_HEXBIN.cpp, C++, 223 lines
src/LN2_IFPOINTS.cpp, C++, 952 lines
src/LN2_INTPRO.cpp, C++, 308 lines
src/LN2_LAPLACIAN.cpp, C++, 196 lines
src/LN2_LAYERDIMENSION.cpp, C++, 250 lines
src/LN2_LAYERS.cpp, C++, 1,868 lines
src/LN2_LAYER_SMOOTH.cpp, C++, 364 lines
src/LN2_MASK.cpp, C++, 244 lines
src/LN2_MULTILATERATE.cpp, C++, 3,180 lines
src/LN2_NEIGHBORS.cpp, C++, 417 lines
src/LN2_PATCH_FLATTEN.cpp, C++, 976 lines
src/LN2_PATCH_FLATTEN_2D.cpp, C++, 577 lines
src/LN2_PATCH_UNFLATTEN.cpp, C++, 179 lines
src/LN2_PEAK_DETECT.cpp, C++, 346 lines
src/LN2_PHASE_GRADIENTS.cpp, C++, 257 lines
src/LN2_PHASE_JOLT.cpp, C++, 491 lines
src/LN2_PHASE_LAPLACIAN.cpp, C++, 291 lines
src/LN2_PROFILE.cpp, C++, 414 lines
src/LN2_RECIPROCAL.cpp, C++, 170 lines
src/LN2_REGRESS_OUT.cpp, C++, 200 lines
src/LN2_RIMIFY.cpp, C++, 179 lines
src/LN2_RIM_BORDERIZE.cpp, C++, 339 lines
src/LN2_RIM_POLISH.cpp, C++, 583 lines
src/LN2_SENSITIVITY.cpp, C++, 125 lines
src/LN2_SKELETONIZE.cpp, C++, 314 lines
src/LN2_SNAPCAST.cpp, C++, 616 lines
src/LN2_SPECIFICITY.cpp, C++, 164 lines
src/LN2_UVD_FILTER.cpp, C++, 462 lines
src/LN2_UVD_LSTSQR.cpp, C++, 291 lines
src/LN2_VORONOI.cpp, C++, 589 lines
src/LN2_WINDOWED_COUNTER_2D.cpp, C++, 259 lines
src/LN2_ZERO_CROSSING.cpp, C++, 401 lines
src/LN2_ZSCORE.cpp, C++, 151 lines
src/LN3_LAYERS.cpp, C++, 1,349 lines
src/LN3_NOLAD.cpp, C++, 318 lines
src/LN_3DCOLUMNS.cpp, C++, 803 lines
src/LN_BOCO.cpp, C++, 360 lines
src/LN_COLUMNAR_DIST.cpp, C++, 748 lines
src/LN_CONLAY.cpp, C++, 253 lines
src/LN_CORREL2FILES.cpp, C++, 127 lines
src/LN_DIRECT_SMOOTH.cpp, C++, 245 lines
src/LN_EXTREMETR.cpp, C++, 130 lines
src/LN_FLOAT_ME.cpp, C++, 94 lines
src/LN_GFACTOR.cpp, C++, 324 lines
src/LN_GRADSMOOTH.cpp, C++, 387 lines
src/LN_GROW_LAYERS.cpp, C++, 896 lines
src/LN_IMAGIRO.cpp, C++, 358 lines
src/LN_INFO.cpp, C++, 205 lines
src/LN_INTPRO.cpp, C++, 255 lines
src/LN_INT_ME.cpp, C++, 79 lines
src/LN_LAYER_SMOOTH.cpp, C++, 668 lines
src/LN_LEAKY_LAYERS.cpp, C++, 251 lines
src/LN_LOITUMA.cpp, C++, 421 lines
src/LN_MP2RAGE_DNOISE.cpp, C++, 210 lines
src/LN_NOISEME.cpp, C++, 140 lines
src/LN_NOISE_KERNEL.cpp, C++, 231 lines
src/LN_PHYSIO_PARS.cpp, C++, 211 lines
src/LN_RAGRUG.cpp, C++, 167 lines
src/LN_SHORT_ME.cpp, C++, 76 lines
src/LN_SKEW.cpp, C++, 282 lines
src/LN_TEMPSMOOTH.cpp, C++, 184 lines
src/LN_TRIAL.cpp, C++, 113 lines
src/LN_ZOOM.cpp, C++, 167 lines
test_data/tests.sh, Shell, 44 lines
test_data/tests_on_windows.sh, Shell, 43 lines
LICENSE, License, 29 lines
README.md, Text, 160 lines

At the source: github.com/layerfMRI/LAYNII

Zenodo 19391614

License: CC-BY-4.0

State: the link answers, verified on 30 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

Tools: NumPy (25 files), Matplotlib (18 files), pandas (16 files), SciPy (11 files), statsmodels (9 files), AFNI (7 files), PsychoPy (7 files), ANTs (2 files), FreeSurfer (2 files), SPM (2 files)

Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)

30 September 2026: the link answers (HTTP 200)

35 files

AR_SH_fig5.ipynb, Jupyter, 181 lines
LCT_task/ADMT_practice_lastrun.py, Python, 3,409 lines
LCT_task/ADMT_r1_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r2_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r3_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r4_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r5_lastrun.py, Python, 1,721 lines
LCT_task/ADMT_r6_lastrun.py, Python, 1,721 lines
RT_fig3.ipynb, Jupyter, 206 lines
align_surf_ba.sh, Shell, 115 lines
behavior_AR_RT.ipynb, Jupyter, 232 lines
fig2_data_plot.ipynb, Jupyter, 98 lines
fig3_data_plot.ipynb, Jupyter, 83 lines
fig4_data_plot.ipynb, Jupyter, 85 lines
fig5_data_plot.ipynb, Jupyter, 87 lines
fig6_data_plot.ipynb, Jupyter, 116 lines
fig7_AR_data_plot.ipynb, Jupyter, 112 lines
fig7_gainloss_data_plot.ipynb, Jupyter, 117 lines
gainloss_fig4.ipynb, Jupyter, 223 lines
glm_lottery.sh, Shell, 150 lines
iti_isi_jitter.ipynb, Jupyter, 132 lines
layerProfile_acceptreject.ipynb, Jupyter, 229 lines
layerProfile_choice_outcome.ipynb, Jupyter, 221 lines
layerProfile_gainloss.ipynb, Jupyter, 194 lines
layer_MT.sh, Shell, 83 lines
mc_job.m, MATLAB, 1,335 lines
mc_run.m, MATLAB, 50 lines
motion_censor_bold.sh, Shell, 72 lines
mtepi.sh, Shell, 41 lines
reconall_mtepi.sh, Shell, 87 lines
roiProfile_control_v1.ipynb, Jupyter, 217 lines
split_ctrl_dant.sh, Shell, 108 lines
stake_fig2.ipynb, Jupyter, 252 lines
stakedif_figS3.ipynb, Jupyter, 256 lines
README.md, Text, 100 lines

At the source:

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:

it points to the authors' code: afni.nimh.nih.gov, fil.ion.ucl.ac.uk/spm, layerfMRI/LAYNII, yuhuichai/lct, stnava.github.io/ants, Zenodo 19391614

Read it in the paper: doi.org/10.1038/s41467-026-72605-3.

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:

6 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
183 scripts, each with its path and the digest of its content;
8 matches between paragraphs of the paper and lines of the code (method lexical-v1);
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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

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osf:2j7av, at OSF; found in “Data availability”

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

it points to a dataset: OSF 2j7av

Read it in the paper: doi.org/10.1038/s41467-026-72605-3.

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 2 keywords, 13 MeSH terms, 1 funder, 76 references.

Cite

This paper

Chai, Y., Goh, J. O. S., & Sutton, B. P. (2026). Resolving mesoscale brainstem-prefrontal-striatal pathways underlying decisions upon salient events using submillimeter-resolution fMRI. Nature communications, 17(1), 5911. https://doi.org/10.1038/s41467-026-72605-3

BibTeX

@article{chai2026resolving, author = {Chai, Yuhui and Goh, Joshua Oon Soo and Sutton, Bradley P.}, title = {{Resolving mesoscale brainstem-prefrontal-striatal pathways underlying decisions upon salient events using submillimeter-resolution fMRI}}, journal = {Nature communications}, year = {2026}, month = apr, volume = {17}, number = {1}, pages = {5911}, publisher = {Nature Publishing Group}, issn = {2041-1723}, doi = {10.1038/s41467-026-72605-3}, url = {https://doi.org/10.1038/s41467-026-72605-3}, pmid = {42062280}, pmcid = {PMC13338228} }

RIS

TY - JOUR AU - Chai, Yuhui AU - Goh, Joshua Oon Soo AU - Sutton, Bradley P. TI - Resolving mesoscale brainstem-prefrontal-striatal pathways underlying decisions upon salient events using submillimeter-resolution fMRI T2 - Nature communications J2 - Nat Commun PY - 2026 DA - 2026/04/30 VL - 17 IS - 1 SP - 5911 SN - 2041-1723 PB - Nature Publishing Group DO - 10.1038/s41467-026-72605-3 UR - https://doi.org/10.1038/s41467-026-72605-3 LA - en ER -

CSL-JSON

{ "id": "10.1038/s41467-026-72605-3", "type": "article-journal", "title": "Resolving mesoscale brainstem-prefrontal-striatal pathways underlying decisions upon salient events using submillimeter-resolution fMRI", "container-title": "Nature communications", "author": [ { "family": "Chai", "given": "Yuhui" }, { "family": "Goh", "given": "Joshua Oon Soo" }, { "family": "Sutton", "given": "Bradley P." } ], "container-title-short": "Nat Commun", "volume": "17", "issue": "1", "page": "5911", "DOI": "10.1038/s41467-026-72605-3", "PMID": "42062280", "PMCID": "PMC13338228", "ISSN": "2041-1723", "publisher": "Nature Publishing Group", "URL": "https://doi.org/10.1038/s41467-026-72605-3", "language": "en", "issued": { "date-parts": [ [ 2026, 4, 30 ] ] } }

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Resolving mesoscale brainstem-prefrontal-striatal pathways underlying decisions upon salient events using submillimeter-resolution fMRI.

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yuhuichai/lct

afni.nimh.nih.gov

fil.ion.ucl.ac.uk/spm

stnava.github.io/ants

layerfMRI/LAYNII

Zenodo 19391614

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