BrainFC: functional connectivity, made visible

BrainFC

fMRI → ROI time series → functional connectivity → matrix, eight-view and interactive 3D reports.

BrainFC is a Python library with a command-line interface and a local graphical interface. Both interfaces use the same processing core. The default installation includes the GUI and an offline API manual. Python 3.11 or newer is required; ordinary users do not need Node.js.

Install and launch

pip install brainfc
brainfc serve

The interface opens at http://127.0.0.1:8766. Choose the built-in demo to generate synthetic NIfTI inputs and a complete report without downloading participant data. The offline manual is available at /reference/ and the HTTP API schema at /docs.

Python API

from brainfc import Config, extract_connectome

# A TSV with a header: rows are time points, columns are ROI signals.
result = extract_connectome(
    "signals.tsv",
    config=Config(detrend=False, standardize=False),
)
matrix = result.connectivity
result.save("results/run-001")

The destination must be new. For volume images, supply an integer-label atlas in the same explicitly named space and confirm that spatial preprocessing is complete. Filtering, confound regression and censoring must match the provenance of the input signals; the example above does not add temporal denoising.

Capabilities

  • Read supported NiBabel volume containers, CIFTI time series, paired GIFTI data/labels, and CSV/TSV/TXT/1D/NPY/NPZ/MAT tables (excluding MAT v7.3).
  • Extract ROI means; apply confound regression, temporal cleaning and censoring while retaining original frame indices.
  • Compute Pearson, Spearman or Ledoit-Wolf partial correlations, with a separate Fisher-z matrix.
  • Export arrays, tables, quality records, input fingerprints, figures and an offline interactive report.
  • Synchronize selected connections and display thresholds between the 3D viewer and eight anatomical views. Display filtering does not modify the complete signed matrix.

Raw DICOM/BIDS spatial preprocessing requires external dcm2niix/fMRIPrep. BrainFC provides command adapters; it does not implement that preprocessing itself. The complete external raw-data chain has not been validated in this release. This package does not provide disease diagnosis or cohort-level inference.

Documentation and source

Licensed under Apache-2.0. The 3D viewer is adapted from Hyper-Brain; BrainFC runs independently. Dataset and atlas licenses remain with their original providers.

Project links

Data verified by PyPI on Sep 12, 2026
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  • Released:
Newer release available (0.5.1)

1 maintainer

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Avatar for xiangminhan from gravatar.com xiangminhan

Credits

Author: BrainFC contributors

GitHub Statistics

Data verified by PyPI on Sep 12, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

Apache-2.0
View SPDX License List

Requires

Python >=3.11

Provides Extra

dev

Tags

bids connectome fmri functional-connectivity neuroimaging

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