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preprocessing_pipelines

imported

software/preprocessing-pipelines

Preprocessing Pipelines for EEG (MNE-python), fMRI (nipype), MEG (MNE-python/autoreject) data

Machine-generated from the listed sources and not yet reviewed by a human.

preprocessing_pipelines project image
GitHub preview card for nmningmei/preprocessing_pipelines. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
eeg · fmri-preprocessing · fsl · meg · mne-python · nipype · pipelines · preprocessing · python3
Regulatory
unknown
similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • esineteeg · meg · mne-python

    EEG inverse solution with artificial neural networks. This package works with MNE-Python data structures for easy integration into your MNE-based M/EEG code

  • mne-rsaeeg · meg · mne-python

    Representational Similarity Analysis on MEG and EEG data

  • niseqeeg · meg · mne-python

    group sequential tests for neuroimaging

  • pypesnipype · preprocessing

    Reusable neuroimaging pipelines using nipype

  • intro-to-eegeeg · mne-python

    Introduction to EEG analysis course using MNE-Python

  • neural-signals-101eeg · mne-python

    Beginner tutorial: ML & signal processing on neural signals (EEG) in Python — raw recordings to honest evaluation, in runnable notebooks. MIT.

sources
  1. api.github.com/repos/nmningmei/preprocessing_pipelines
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2021-12-13, 24 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/7.json→ .entries["preprocessing-pipelines"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.