HemiSpec

HemiSpec is a PyPI-first software and workflow toolkit for computing reconstruction-derived hemispheric specificity (ANS/RNS) from preprocessed gray-matter maps. The CLI and GUI are entry points installed into the same Python/PyTorch environment as the package and model cache.

Quick start Install from PyPI Data and models

Workflow overview

Input GM maps → cross-hemispheric DGN reconstruction → ANS/RNS specificity maps → ROI summaries and validation → downstream analyses (age/sex effects, hemisphere classification, behavioral phenotypes, disease vs. control).

Choose your path

• Run HemiSpec

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  Create a PyPI-managed Python/PyTorch environment, then run the synthetic quickstart or launch the package-installed GUI.

  Get started

• Understand ANS/RNS

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  Learn the reconstruction framework, metric definitions, and downstream task analysis.

  Methods

• Model and data assets

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  DGN checkpoints, hemisphere-classifier bundles, and data policy.

  Data and models

• Developer docs

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  Architecture, API design, deployment, and roadmap.

  Developer

Citation

HemiSpec builds on the ANS/RNS framework from Wang et al. 2024 (Patterns). See Citation for the full reference.

HemiSpec v0.1.0 is a public beta; PyPI is the recommended install path, while GitHub Releases archive fallback artifacts. Source: github.com/mqqq333/HemiSpec.

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