Data · dataset · 2025
Dataset required for CMM and GC-Net simulations
Listed in ScienceDB
Description
Instructions for Using the Dataset to Reproduce the Paper’s Results.Paper: Human and artificial visual systems share a computational principle for transforming binocular disparity into depth representationnature.com/articles/s42003-025-08474-1Dataset Contents.The dataset comprises pre-simulated data files necessary for reproducing the figures presented in the paper. The contents of the dataset and their corresponding roles are as follows:· BEM_canonical: Contains cross-correlation weights based on the binocular energy model (Supplementary Figure 4).· checkpoint: Includes the pretrained GC-Net model.· CMM: Stores cross-correlation and cross-matching responses to random dot stereograms (RDSs), used in Figure 3.· epoch_7_iter_22601: Outputs from GC-Net used in Figures 4 and 5.· MVPA: Provides decoding results for Figure 2 and Supplementary Figures 1 and 2.· rds: Contains the generated RDS stimuli used for simulations (general use).· S2N: fMRI percent signal change data used in Supplementary Figure 3.· VTC_extract_smoothed: Smoothed VTC data extracted from BrainVoyager (general use).· VTC_normalized: Normalized VTC data (general use).· VTC_stimID: Parameters describing the stimulus presentation corresponding to the VTC data (general use).· wavelet: Contains wavelet analysis data (Supplementary Figure 5).Python Code Repository.The Python code for generating the figures in the paper is available on GitHub and can be cloned from the following link:github.com/wundari/CMM_modelRepository Folder Structure Overview.The top-level structure of the cloned repository includes the following primary folders:· Codes/· Data/· Plots/Please refer to the file folder_tree_structure.txt for the detailed folder hierarchy and organization.Organizing Dataset Files.After cloning the repository, organize the dataset as follows:Step 1: Move the following folders into the CMM_model/Data/ directory:· BEM_canonical· CMM· MVPA· rds· S2N· VTC_extract_smoothed· VTC_normalized· VTC_stimID· waveletStep 2: Create the following directory path:CMM_model/Codes/Python/gcnet/results/sceneflow/monkaa/shift_1.5_median_wrt_leftThen move the following folders into that directory:· checkpoint· epoch_7_iter_22601For additional details and step-by-step instructions on running the Python scripts to reproduce the paper’s plots, please visit the GitHub repository: github.com/wundari/CMM_model
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.26480 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Design 68%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.26480 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3303 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (68%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |