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niseq

imported

software/niseq

group sequential tests for neuroimaging

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

niseq project image
GitHub preview card for john-veillette/niseq. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
BSD-3-Clause(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
adaptive-design · eeg · electrocorticography · electroencephalography · fmri · group-sequential-designs · magnetoencephalography · meeg · meg · mne-python · mri · neuroimaging · neuroscience · nilearn · nipy · statistics
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.

  • mne-arieeg · electrocorticography · electroencephalography · magnetoencephalography · meg · neuroimaging

    All-resolutions Inference for M/EEG in Python

  • mne-pythoneeg · electrocorticography · electroencephalography · magnetoencephalography · meg · neuroimaging

    MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

  • braindecodeeeg · electrocorticography · electroencephalography · magnetoencephalography · meg

    Deep learning software to decode EEG, ECG or MEG signals

  • online_neuroimaging_resourceseeg · fmri · meg · mri · neuroimaging · neuroscience

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

  • eyeartifactcorrectioneeg · electroencephalography · magnetoencephalography · meg

    Eye movement and blink-related EEG and MEG artifact correction algorithms

  • MEGaNormeeg · electroencephalography · magnetoencephalography · meg

    MEGaNorm is a Python package for normative modeling on MEG and EEG data.

sources
  1. api.github.com/repos/john-veillette/niseq
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2023-07-20, 9 stars, license reported as BSD-3-Clause. 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["niseq"]

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