Data for Autism Spectrum Disorder diagnosis using mamba-based analysis of dynamic functional connectivity state transition sequences

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Authors: Hongyu Chen, Dapeng Cheng, Jintao Wang, Feng Zhao
Cited by: 0

Abstract

1.General OverviewThis repository contains the raw data and source code for the study titled "Autism Spectrum Disorder diagnosis using mamba-based analysis of dynamic functional connectivity state transition sequences". It includes fMRI time-series data, category labels, and the necessary scripts to reproduce the results presented in the manuscript. 2.Data Description Dataset includes: fMRI_data: A 3D array (92x170x116) representing primary fMRI time-series data for 92 individual subjects. labels: Category labels (92x1) for ground truth classification (e.g., Patient vs. Healthy Control). __header__: String metadata including versioning. 3.File Format & Machine Readability All data are provided in machine-readable formats (e.g., .mat, .csv, or .npy) as required by PeerJ. No PDF or image-based raw data are used for analysis. 4.Usage/How to reproduce How to use: Download the .zip file and extract the contents. Ensure you have [Python/MATLAB/R] installed. Please refer to the Example Code section in the README.md file 5.Citation & License If you use this code or data, please cite both the associated PeerJ article and this Zenodo DOI. This work is licensed under [Creative Commons Attribution 4.0 International].

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
4 January 2026
Language
EN
Document type
Dataset