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jeremymanning merged 1 commit into from
Oct 29, 2026
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Add the release-specific Zenodo DOI badge #187

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1 change: 1 addition & 0 deletions README.md
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<sub>Illustrative movie-viewing analysis: an HTFA template (K = 50) fitted to 12 adults watching Pixar's <i>Partly Cloudy</i>, from Nilearn's <code>development_fmri</code> dataset, viewed from the left, above and right. Inter-subject functional correlation (ISFC) measures correlations between participants' factor time courses at matching moments of the film. Edges show the strongest 5% of factor pairs (|ISFC| &ge; 0.137; red positive, blue negative). Node size represents factor width; node colour identifies communities in the positive-ISFC graph. See the <a href="https://htfa.readthedocs.io/en/latest/tutorials/10_dynamic_isfc_animation.html">ISFC tutorial</a> for the analysis workflow.</sub>

[![PyPI version](https://img.shields.io/pypi/v/htfa.svg)](https://pypi.org/project/htfa/)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.23772196.svg)](https://doi.org/10.5281/zenodo.23772196)
[![tests](https://github.com/ContextLab/htfa/actions/workflows/tests.yml/badge.svg)](https://github.com/ContextLab/htfa/actions/workflows/tests.yml)
[![Documentation Status](https://readthedocs.org/projects/htfa/badge/?version=latest)](https://htfa.readthedocs.io/en/latest/?badge=latest)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/ContextLab/htfa/blob/main/LICENSE)
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