openmedical/registry
← registry

MEG-group-decode

imported

software/meg-group-decode

Train Wavenet-based group-level models on MEG data, and uncover neuroscientifically interpretable information.

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

MEG-group-decode project image
GitHub preview card for ricsinaruto/MEG-group-decode. 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
decoding · deep-learning · meg · neuroimaging · neuroscience
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.

  • MEG-transfer-decodingdecoding · meg · neuroimaging · neuroscience

    Explore the differences between sliding window and full-epoch models on MEG data and use PFI to uncover neuroscientific insights.

  • conpymeg · neuroimaging · neuroscience

    Python package for power mapping and functional connectivity using DICS

  • MEGAPmeg · neuroimaging · neuroscience

    MEGAP: A Comprehensive Pipeline for Automatic Pre-processing of Large-scale MEG Data

  • niseqmeg · neuroimaging · neuroscience

    group sequential tests for neuroimaging

  • online_neuroimaging_resourcesmeg · neuroimaging · neuroscience

    a laundry list of resources for MRI, fMRI, EEG, MEG...

  • spm-docsmeg · neuroimaging · neuroscience

    SPM Documentation

sources
  1. api.github.com/repos/ricsinaruto/MEG-group-decode
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2024-01-18, 14 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/11.json→ .entries["meg-group-decode"]

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