OSCR

Population connective field modeling reveals proto-retinotopic visual cortex organization in the prenatal human brain.

Code ↔ Paper

20 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 20 matches · 2 of them tie a paragraph to a whole file without given lines: weak matches, whose lines are not tinted
  1. [1] § RESULTS › Population CF modeling ↔ code/pipeline/03_retinotopyanalysis/spin_cf_parameter_null_multigroup.py, lines 1 to 40 · score 0.88 · nearest V1 vertices, fitted V1 center, fitted CF parameters, spherical surface, generate empirical, recomputed · Report a mismatch
  2. [2] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Retinotopic template projection ↔ code/pipeline/00_HCP/HCP_native_to_fsaverage.sh, the whole file · a weak match · score 0.74 · fs LR space, fsaverage space, deformed, rotated, sphere, native · Report a mismatch
  3. [3] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Retinotopic template projection ↔ code/pipeline/00_HCP/HCP_parameter_to_fsaverage.sh, the whole file · a weak match · score 0.74 · fs LR space, fsaverage space, deformed, rotated, sphere, HCP · Report a mismatch
  4. [4] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Null model estimation on simulated data ↔ code/pipeline/01_dataprep/simulation_alternativebolddata/simulated_model_smooth_surf.py, lines 116 to 203 · score 0.72 · Cholesky decomposition, Gaussian filter, smoothed, kernel, timepoints, simulated · Report a mismatch
  5. [5] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Null model estimation on simulated data ↔ code/pipeline/Fetal/01_dataprep/simulation_alternativebolddata/simulated_model_smooth_surf.py, lines 118 to 205 · score 0.72 · Cholesky decomposition, Gaussian filter, smoothed, kernel, timepoints, simulated · Report a mismatch
  6. [6] § MATERIALS AND METHODS › Data preprocessing › Robustness of the segmentation, surface reconstruction, and registration results ↔ surface_to_template_alignment/align_to_template.sh, lines 66 to 154 · score 0.67 · week template, template space, surface templates, dHCP, alignment, fsaverage · Report a mismatch
  7. [7] § MATERIALS AND METHODS › Data preprocessing › Robustness of the segmentation, surface reconstruction, and registration results ↔ surface_to_template_alignment/align_to_template_no_volumetric_initialisation.sh, lines 68 to 134 · score 0.66 · week template, template space, surface templates, dHCP, alignment, transformed · Report a mismatch
  8. [8] § MATERIALS AND METHODS › Data preprocessing › HCP: Adolescent and adult images › Structural image preprocessing ↔ code/pipeline/01_dataprep/surfaceprojection/project_bold_to_surface.sh, lines 89 to 134 · score 0.64 · PostFreeSurfer, ribbon volume, native space, FSL, mesh, maps · Report a mismatch
  9. [9] § MATERIALS AND METHODS › Data preprocessing › HCP: Adolescent and adult images › Structural image preprocessing ↔ code/pipeline/Fetal/01_dataprep/surfaceprojection/project_bold_to_surface.sh, lines 89 to 134 · score 0.64 · PostFreeSurfer, ribbon volume, native space, FSL, mesh, maps · Report a mismatch
  10. [10] § RESULTS › Population CF modeling ↔ code/pipeline/03_retinotopyanalysis/spin_test_model_fit.py, lines 475 to 587 · score 0.63 · polar angle circular, polar angle error, permutation, spin, fitted, empirical · Report a mismatch
  11. [11] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Local gradient analysis ↔ code/pipeline/Fetal/03_retinotopyanalysis/calculate_gradient.py, lines 183 to 264 · score 0.62 · neighboring vertices, connected vertices, gradient, vectors, sum, squared · Report a mismatch
  12. [12] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Local gradient analysis ↔ code/pipeline/03_retinotopyanalysis/calculate_gradient.py, lines 178 to 238 · score 0.61 · neighboring vertices, connected vertices, gradient, vectors, sum, squared · Report a mismatch
  13. [13] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Retinotopic template projection ↔ surface_to_template_alignment/align_to_template_no_volumetric_initialisation.sh, lines 68 to 134 · score 0.58 · week template, template space, dHCP, warp, hemispheres, transformation · Report a mismatch
  14. [14] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Registration of functional images from volume to surface space ↔ code/pipeline/01_dataprep/surfaceprojection/project_bold_to_surface.sh, lines 89 to 134 · score 0.57 · ribbon constrained mapping, FSL, FLIRT, affine, anatomical, warped · Report a mismatch
  15. [15] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Registration of functional images from volume to surface space ↔ code/pipeline/Fetal/01_dataprep/surfaceprojection/project_bold_to_surface.sh, lines 89 to 134 · score 0.57 · ribbon constrained mapping, FSL, FLIRT, affine, anatomical, warped · Report a mismatch
  16. [16] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Population CF model estimation ↔ code/pipeline/00_HCP/ccf_model/ccflogic.py, lines 66 to 113 · score 0.56 · residual sum, variance explained, candidate, spread, squares, fitting · Report a mismatch
  17. [17] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Population CF model estimation ↔ code/pipeline/Fetal/02_ccfanalysis/ccf_model/ccflogic.py, lines 66 to 113 · score 0.56 · residual sum, variance explained, candidate, spread, squares, fitting · Report a mismatch
  18. [18] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Population CF model estimation ↔ code/pipeline/00_HCP/ccf_model/meshgraph.py, lines 63 to 88 · score 0.53 · Dijkstra algorithm, surface mesh, shortest, distance, model, vertex · Report a mismatch
  19. [19] § MATERIALS AND METHODS › Data preprocessing › Data analysis › Population CF modeling analysis › Population CF model estimation ↔ code/pipeline/create_vis.py, lines 67 to 92 · score 0.53 · Dijkstra algorithm, surface mesh, shortest, distance, vertex · Report a mismatch
  20. [20] § RESULTS › Controlling for anatomical differences, data quality and site effects ↔ figures/Figure_S3/Figure_tSNR_raincloud.py, lines 45 to 123 · score 0.51 · sSNR, tSNR, S3, bootstrapped, adolescent, neonatal · Report a mismatch

Paper

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The authors' code

Shell · 202 lines · 12 KB · MIT · 2 matches

  1. #!/bin/bash
  3. # script to align native surfaces with template space & resample native surfaces with template topology
  4. # output: native giftis resampled with template topology
  6. Usage() {
  7. echo "align_to_template.sh <topdir> <subjid> <session> <age> <volumetric template> <surface template> <pre_rotation> <outdir> <config> <script dir> < MSM bin> <wb bin>"
  8. echo " script to align native surfaces with template space & resample native surfaces with template topology "
  9. echo " input args: "
  10. echo " topdir: top directory where subject directories are located "
  11. echo " subjid : subject id "
  12. echo " session: subject scan session "
  13. echo " age: in weeks gestation - this will determine which week of the spatio-temporal template the data will first mapped to"
  14. echo " template age: target age for the median template"
  15. echo " surface template: path to the top level directory of the dHCP surface template"
  16. echo " pre_rotation : txt file containing rotational transform between MNI and FS_LR space (i.e. file rotational_transforms/week40_toFS_LR_rot.%hemi%.txt ) "
  17. echo " outdir : base directory where output will be sent "
  18. echo " config : base config file "
  19. echo " script dir: path to scripts"
  20. echo " MSM bin: msm binary"
  21. echo " wb bin : workbench binary"
  22. echo "output: 1) surface registrations; 2) native giftis resampled with template topology "
  23. }
  25. if [ "$#" -lt 11 ]; then
  26. echo "$#"
  27. Usage
  28. exit
  29. fi
  31. topdir=$1;shift
  32. subjid=$1;shift
  33. session=$1;shift
  34. age=$1;shift
  35. templateage=$1;shift
  36. templatespherepath=$1;shift
  37. pre_rotation=$1;shift
  38. outdir=$1; shift
  39. config=$1; shift
  40. SURF2TEMPLATE=$1;shift
  41. MSMBIN=$1; shift
  42. WB_BIN=$1; shift
  44. mkdir -p $outdir $outdir/volume_dofs $outdir/surface_transforms
  46. ########## DEFINE PATHS TO VARIABLES ##########
  48. echo native_volume=${topdir}/sub-${subjid}/ses-$session/anat/sub-${subjid}_ses-${session}_T2w.nii.gz
  49. native_volume=${topdir}/sub-${subjid}/ses-$session/anat/sub-${subjid}_ses-${session}_T2w.nii.gz
  51. # native spheres
  52. echo native_sphereL=${topdir}/sub-${subjid}/ses-${session}/anat/Native/sub-${subjid}_ses-${session}_hemi-left_sphere.surf.gii
  53. echo native_sphereR=${topdir}/sub-${subjid}/ses-${session}/anat/Native/sub-${subjid}_ses-${session}_hemi-right_sphere.surf.gii
  55. native_sphereL=${topdir}/sub-${subjid}/ses-${session}/anat/Native/sub-${subjid}_ses-${session}_hemi-left_sphere.surf.gii
  56. native_sphereR=${topdir}/sub-${subjid}/ses-${session}/anat/Native/sub-${subjid}_ses-${session}_hemi-right_sphere.surf.gii
  59. echo native spheres $native_sphere_L $native_sphere_R
  61. # native spheres rotated into FS_LR space
  62. echo native_rot_sphereL=${topdir}/sub-${subjid}/ses-$session/anat/Native/sub-${subjid}_ses-${session}_hemi-left_sphere.rot.surf.gii
  63. echo native_rot_sphereR=${topdir}/sub-${subjid}/ses-$session/anat/Native/sub-${subjid}_ses-${session}_hemi-right_sphere.rot.surf.gii
  65. native_rot_sphereL=${topdir}/sub-${subjid}/ses-$session/anat/Native/sub-${subjid}_ses-${session}_hemi-left_sphere.rot.surf.gii
  66. native_rot_sphereR=${topdir}/sub-${subjid}/ses-$session/anat/Native/sub-${subjid}_ses-${session}_hemi-right_sphere.rot.surf.gii
  68. # native data
  69. echo native_dataL=${topdir}/sub-${subjid}/ses-$session/anat/Native/sub-${subjid}_ses-${session}_hemi-left_sulc.shape.gii
  70. echo native_dataR=${topdir}/sub-${subjid}/ses-$session/anat/Native/sub-${subjid}_ses-${session}_hemi-right_sulc.shape.gii
  72. native_dataL=${topdir}/sub-${subjid}/ses-$session/anat/Native/sub-${subjid}_ses-${session}_hemi-left_sulc.shape.gii
  73. native_dataR=${topdir}/sub-${subjid}/ses-$session/anat/Native/sub-${subjid}_ses-${session}_hemi-right_sulc.shape.gii
  75. # surface template files - assumes directory structure consistent with dHCP surface template
  76. echo templatesphereL=$templatespherepath/week-${age}_hemi-left_space-dhcpSym_dens-32k_sphere.surf.gii
  77. echo templatesphereR=$templatespherepath/week-${age}_hemi-right_space-dhcpSym_dens-32k_sphere.surf.gii
  78. echo templatedataL=$templatespherepath/week-${age}_hemi-left_space-dhcpSym_dens-32k_sulc.shape.gii
  79. echo templatedataR=$templatespherepath/week-${age}_hemi-right_space-dhcpSym_dens-32k_sulc.shape.gii
  81. templatesphereL=$templatespherepath/week-${age}_hemi-left_space-dhcpSym_dens-32k_sphere.surf.gii
  82. templatesphereR=$templatespherepath/week-${age}_hemi-right_space-dhcpSym_dens-32k_sphere.surf.gii
  83. templatedataL=$templatespherepath/week-${age}_hemi-left_space-dhcpSym_dens-32k_sulc.shape.gii
  84. templatedataR=$templatespherepath/week-${age}_hemi-right_space-dhcpSym_dens-32k_sulc.shape.gii
  86. # pre-rotations
  87. echo pre_rotationL=$(echo ${pre_rotation} | sed "s/%hemi%/L/g")
  88. echo pre_rotationR=$(echo ${pre_rotation} | sed "s/%hemi%/R/g")
  90. pre_rotationL=$(echo ${pre_rotation} | sed "s/%hemi%/L/g")
  91. pre_rotationR=$(echo ${pre_rotation} | sed "s/%hemi%/R/g")
  94. ########## ROTATE LEFT AND RIGHT HEMISPHERES INTO APPROXIMATE ALIGNMENT WITH SURFACE TEMPLATE SPACE ##########
  96. echo ${WB_BIN} -surface-apply-affine $native_sphereL $pre_rotationL ${native_rot_sphereL}
  99. ${WB_BIN} -surface-apply-affine $native_sphereL $pre_rotationL ${native_rot_sphereL}
  100. ${WB_BIN} -surface-modify-sphere ${native_rot_sphereL} 100 ${native_rot_sphereL} -recenter
  101. ${WB_BIN} -surface-apply-affine $native_sphereR $pre_rotationR ${native_rot_sphereR}
  102. ${WB_BIN} -surface-modify-sphere ${native_rot_sphereR} 100 ${native_rot_sphereR} -recenter
  105. ########## RUN MSM NON-LINEAR ALIGNMENT TO TEMPLATE FOR LEFT AND RIGHT HEMISPHERES ##########
  108. for hemi in left right; do
  110. if [ "$hemi" == "left" ]; then
  111. inmesh=$native_rot_sphereL
  112. refmesh=$templatesphereL
  113. refdata=$templatedataL
  114. indata=$native_dataL
  115. outname=$outdir/surface_transforms/sub-${subjid}_ses-${session}_hemi-left_from-native_to-dhcpSym${templateage}_dens-32k_mode-
  117. else
  118. inmesh=$native_rot_sphereR
  119. refmesh=$templatesphereR
  120. indata=$native_dataR
  121. refdata=$templatedataR
  122. outname=$outdir/surface_transforms/sub-${subjid}_ses-${session}_hemi-right_from-native_to-dhcpSym${templateage}_dens-32k_mode-
  123. fi
  125. if [ ! -f ${outname}sphere.reg.surf.gii ]; then
  126. echo ${MSMBIN} --inmesh=${inmesh} --refmesh=${refmesh} --indata=${indata} --refdata=${refdata} -o ${outname} --conf=${config} --verbose
  127. ${MSMBIN} --inmesh=${inmesh} --refmesh=${refmesh} --indata=${indata} --refdata=${refdata} -o ${outname} --conf=${config}
  128. fi
  130. if [ "$age" != "$templateage" ] ; then
  131. # need to concatenate msm warp to local template with warp from local template to median week template
  132. echo ${WB_BIN} -surface-sphere-project-unproject ${outname}sphere.reg.surf.gii ${refmesh} $templatespherepath/week-to-${templateage}-registrations/${hemi}.${age}-to-${templateage}/${hemi}.${age}-to-${templateage}sphere.reg.surf.gii ${outname}sphere.reg${templateage}.surf.gii
  134. ${WB_BIN} -surface-sphere-project-unproject ${outname}sphere.reg.surf.gii ${refmesh} $templatespherepath/week-to-${templateage}-registrations/${hemi}.${age}-to-${templateage}/${hemi}.${age}-to-${templateage}sphere.reg.surf.gii ${outname}sphere.reg${templateage}.surf.gii
  136. # the output sphere represents the full warp from Native to median week template space - save this
  137. cp ${outname}sphere.reg${templateage}.surf.gii ${topdir}/sub-${subjid}/ses-$session/anat/Native/
  139. else
  141. mv ${outname}sphere.reg.surf.gii ${outname}sphere.reg${templateage}.surf.gii
  143. fi
  145. done
  147. ########## RESAMPLE TEMPLATE TOPOLOGY ON NATIVE SURFACES - OUTPUT IN 'dhcpSym_32k' DIRECTORY ##########
  149. echo mkdir -p ${outdir}/sub-${subjid}/ses-$session/dhcpSym_32k
  150. mkdir -p ${outdir}/sub-${subjid}/ses-$session/dhcpSym_32k
  152. echo nativedir=${topdir}/sub-${subjid}/ses-$session/anat
  153. echo dhcpSym_dir=${outdir}/sub-${subjid}/ses-$session/dhcpSym_32k
  155. nativedir=${topdir}/sub-${subjid}/ses-$session/anat/Native
  156. dhcpSym_dir=${outdir}/sub-${subjid}/ses-$session/dhcpSym_32k
  158. for hemi in left right ; do
  160. # first copy the template sphere to the subjects dhcpSym_32k
  161. # Each subject's template space sphere IS the template! following HCP form.
  163. if [ "$hemi" == "left" ]; then
  165. echo template=$templatespherepath/week-${templateage}_hemi-left_space-dhcpSym_dens-32k_sphere.surf.gii
  166. echo templatemidthickness=$templatespherepath/week-${templateage}_hemi-left_space-dhcpSym_dens-32k_midthickness.surf.gii
  168. template=$templatespherepath/week-${templateage}_hemi-left_space-dhcpSym_dens-32k_sphere.surf.gii
  169. templatemidthickness=$templatespherepath/week-${templateage}_hemi-left_space-dhcpSym_dens-32k_midthickness.surf.gii
  170. else
  171. echo template=$templatespherepath/week-${templateage}_hemi-right_space-dhcpSym_dens-32k_sphere.surf.gii
  172. echo templatemidthickness=$templatespherepath/week-${templateage}_hemi-right_space-dhcpSym_dens-32k_midthickness.surf.gii
  174. template=$templatespherepath/week-${templateage}_hemi-right_space-dhcpSym_dens-32k_sphere.surf.gii
  175. templatemidthickness=$templatespherepath/week-${templateage}_hemi-right_space-dhcpSym_dens-32k_midthickness.surf.gii
  176. fi
  178. echo cp $template $dhcpSym_dir/sub-${subjid}_ses-${session}_hemi-${hemi}_space-dhcpSym_dens-32k_sphere.surf.gii
  179. cp $template $dhcpSym_dir/sub-${subjid}_ses-${session}_hemi-${hemi}_space-dhcpSym_dens-32k_sphere.surf.gii
  181. transformed_sphere=$outdir/surface_transforms/sub-${subjid}_ses-${session}_hemi-${hemi}_from-native_to-dhcpSym${templateage}_dens-32k_mode-sphere.reg${templateage}.surf.gii
  183. # resample surfaces
  184. for surf in pial wm midthickness inflated vinflated; do
  185. echo ${WB_BIN} -surface-resample $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_${surf}.surf.gii $transformed_sphere $template ADAP_BARY_AREA $dhcpSym_dir/sub-${subjid}_ses-${session}_hemi-${hemi}_space-dhcpSym${templateage}_${surf}.surf.gii -area-surfs $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_midthickness.surf.gii $templatemidthickness
  187. ${WB_BIN} -surface-resample $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_${surf}.surf.gii $transformed_sphere $template ADAP_BARY_AREA $dhcpSym_dir/sub-${subjid}_ses-${session}_hemi-${hemi}_space-dhcpSym${templateage}_${surf}.surf.gii -area-surfs $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_midthickness.surf.gii $templatemidthickness
  188. done
  191. # resample .shape metrics
  192. for metric in sulc curvature thickness desc-corr_thickness myelinmap desc-smoothed_myelinmap desc-medialwall_mask ; do
  193. echo ${WB_BIN} -metric-resample $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_${metric}.shape.gii $transformed_sphere $template ADAP_BARY_AREA $dhcpSym_dir/sub-${subjid}_ses-${session}_hemi-${hemi}_space-dhcpSym${templateage}_${metric}.shape.gii -area-surfs $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_midthickness.surf.gii $templatemidthickness
  195. ${WB_BIN} -metric-resample $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_${metric}.shape.gii $transformed_sphere $template ADAP_BARY_AREA $dhcpSym_dir/sub-${subjid}_ses-${session}_hemi-${hemi}_space-dhcpSym${templateage}_${metric}.shape.gii -area-surfs $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_midthickness.surf.gii $templatemidthickness
  196. done ### LZJW changed output file name ###
  198. # resample .label files
  199. echo ${WB_BIN} -label-resample $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_desc-drawem_dseg.label.gii $transformed_sphere $template ADAP_BARY_AREA $dhcpSym_dir/sub-${subjid}_ses-${session}_hemi-${hemi}_space-dhcpSym${templateage}_desc-drawem_dseg.label.gii -area-surfs $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_midthickness.surf.gii $templatemidthickness
  201. ${WB_BIN} -label-resample $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_desc-drawem_dseg.label.gii $transformed_sphere $template ADAP_BARY_AREA $dhcpSym_dir/sub-${subjid}_ses-${session}_hemi-${hemi}_space-dhcpSym${templateage}_desc-drawem_dseg.label.gii -area-surfs $nativedir/sub-${subjid}_ses-${session}_hemi-${hemi}_midthickness.surf.gii $templatemidthickness
  202. done

align_to_template_no_volumetric_initialisation.sh at commit 39c4ebb, under MIT · at the source

Overview

Authors: So-Hyeon Yoo1, Anne-Sophie Kieslinger1, Michael A. Skeide1,2
ORCID iDs: So-Hyeon Yoo, Michael A. Skeide
  1. Research Group Learning in Early Childhood, Max Planck Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany
  2. Institute for Child and Adolescent Psychiatry, Christian-Albrechts-Universität zu Kiel, 24105, Kiel, Germany
Institutions: Max Planck Institute for Human Cognitive and Brain Sciences (Germany); Christian-Albrechts-Universität zu Kiel (Germany)
Journal: Science advances, volume 12, issue 40, article eaee9300
Dates: received 19 December 2025; accepted 31 August 2026; published online 30 September 2026; in print October 2026
Type: Research article · Language: English
License: CC BY-NC
Identifiers: DOI 10.1126/sciadv.aee9300 · PMID 42814805 · PMCID PMC13626056 · OpenAlex W7214991548
Open access: gold, a free copy (OpenAlex)
Status: code verified (how the code is found and verified)
Categories: human (organism), systems (subfield)
Methods: Connectivity, Statistics, Smoothing, state filtering, decompositions, Machine learning, fMRI & imaging
MeSH: Retina*, Visual Cortex*, Adult, Brain Mapping, Female, Humans, Magnetic Resonance Imaging, Pregnancy, Young Adult (* major topic)
Journal subjects: Neuroscience
Topic: Functional Brain Connectivity Studies (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Alexander von Humboldt-Stiftung (Henriette Herz Scouting Programme); European Research Council ((FP/2007-2013) / ERC Grant Agreement no. [319456]); Deutsche Forschungsgemeinschaft (433758790); Jacobs Foundation (Research Fellowship)
Citations: not cited yet (Europe PMC); 62 references in the paper

Abstract

The visual space is sampled by cortical field maps in which nearby neuronal populations encode nearby locations of images received from the retina. Whether retinotopic cortical organization already emerges in the neonatal or even prenatal human brain is currently unknown. To answer this question in vivo, we applied population connective field modeling to 871 resting-state functional magnetic resonance imaging datasets ranging from prenatal to young adult age. We found topographically organized eccentricity and polar angle connectivity maps in V2 and V3 of the visual cortex as early as the 21st week of gestation. These results highlight that human proto-retinotopic cortical maps develop in the second trimester of pregnancy, predating visual experience.

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

Repositories

Its files are read in the Code ↔ Paper reader above, with 20 matches between paragraphs and lines of code.

ecr05/dHCP_template_alignment

License: MIT
State: the link answers, verified on 30 October 2026
Evidence: files inventoried
Commit: 39c4ebb5cbedf495ec5218afb4ecd7329f15501e, 22 June 2022
Languages: Shell (5), Python (1)
Size: 17 files, 6 scripts
Software Heritage: not archived
Found in: the text, “Retinotopic template projection”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: NumPy (1 file), Connectome Workbench (1 file)
Availability: 2 checks, the latest on 30 October 2026: the link answers
  • 30 October 2026: the link answers
  • 30 September 2026: the link answers
8 files
At the source: github.com/ecr05/dHCP_template_alignment

Zenodo 22152241

License: CC-BY-4.0
State: the link answers, verified on 3 October 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Data, code, and materials availability:”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: NumPy (84 files), NiBabel (59 files), pandas (55 files), Nilearn (52 files), SciPy (43 files), Matplotlib (20 files), neuromaps (9 files), seaborn (7 files), Connectome Workbench (7 files), FSL (3 files), statannotations (3 files), statsmodels (3 files), neuroCombat (2 files)
Availability: 1 check, the latest on 3 October 2026: the link answers (HTTP 200)
  • 3 October 2026: the link answers (HTTP 200)
135 files
At the source: zenodo.org/records/22152241

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;
  • 140 scripts, each with its path and the digest of its content;
  • 20 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

The data for this study are available after institutional registration through public links in the NDA. Prenatal and neonatal data are available at https://nda.nih.gov/edit_collection.html?id=3955. Adolescent and adult data are available at https://nda.nih.gov/edit_collection.html?id=2846. All data analysis was performed with custom software using Python 3.11 and various third-party packages (Matplotlib 3.8.3, NumPy 1.26.3, Pandas 2.2.0, SciPy 1.12.0, and niBabel 5.2.0). Brain surfaces were visualized with Nilearn (0.10.4). All code used for data analysis is available from Zenodo, https://zenodo.org/records/22152241 (DOI: 10.5281/zenodo.22152241 (http://dx.doi.org/10.5281/zenodo.22152241)). This study did not generate new materials.

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

Versions

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Version 1, 3 October 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 9 MeSH terms, 4 funders, 62 references.

Cite

This paper

Yoo, S.-H., Kieslinger, A.-S., & Skeide, M. A. (2026). Population connective field modeling reveals proto-retinotopic visual cortex organization in the prenatal human brain. Science advances, 12(40), eaee9300. https://doi.org/10.1126/sciadv.aee9300

BibTeX

@article{yoo2026population,
author = {Yoo, So-Hyeon and Kieslinger, Anne-Sophie and Skeide, Michael A.},
title = {{Population connective field modeling reveals proto-retinotopic visual cortex organization in the prenatal human brain}},
journal = {Science advances},
year = {2026},
month = sep,
volume = {12},
number = {40},
pages = {eaee9300},
publisher = {American Association for the Advancement of Science},
issn = {2375-2548},
doi = {10.1126/sciadv.aee9300},
url = {https://doi.org/10.1126/sciadv.aee9300},
pmid = {42814805},
pmcid = {PMC13626056}
}

RIS

TY - JOUR
AU - Yoo, So-Hyeon
AU - Kieslinger, Anne-Sophie
AU - Skeide, Michael A.
TI - Population connective field modeling reveals proto-retinotopic visual cortex organization in the prenatal human brain
T2 - Science advances
J2 - Sci Adv
PY - 2026
DA - 2026/09/30
VL - 12
IS - 40
SP - eaee9300
SN - 2375-2548
PB - American Association for the Advancement of Science
DO - 10.1126/sciadv.aee9300
UR - https://doi.org/10.1126/sciadv.aee9300
LA - en
ER -

CSL-JSON

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"id": "10.1126/sciadv.aee9300",
"type": "article-journal",
"title": "Population connective field modeling reveals proto-retinotopic visual cortex organization in the prenatal human brain",
"container-title": "Science advances",
"author": [
{
"family": "Yoo",
"given": "So-Hyeon"
},
{
"family": "Kieslinger",
"given": "Anne-Sophie"
},
{
"family": "Skeide",
"given": "Michael A."
}
],
"container-title-short": "Sci Adv",
"volume": "12",
"issue": "40",
"page": "eaee9300",
"DOI": "10.1126/sciadv.aee9300",
"PMID": "42814805",
"PMCID": "PMC13626056",
"ISSN": "2375-2548",
"publisher": "American Association for the Advancement of Science",
"URL": "https://doi.org/10.1126/sciadv.aee9300",
"language": "en",
"issued": {
"date-parts": [
[
2026,
9,
30
]
]
}
}

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