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BCI-real-time-neuroimaging

imported

software/bci-real-time-neuroimaging

Real-time BCI platform used to assess performance of: (1) discrete trial vs continuous pursuit BCI training (2) source (EEG source imaging) vs sensor space decoding (3) continuous robotic arm control

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

BCI-real-time-neuroimaging project image
GitHub preview card for BradleyEdelman/BCI-real-time-neuroimaging. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
GPL-3.0(osi)
Status
maintained
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Repository
github.com/BradleyEdelman/BCI-real-time-neuroimaging
Documentation
unknown
Tags
adaptive-decoding · brain-computer-interface · eeg · machine-learning · mri · real-time-processing · source-reconstruction
Regulatory
unknown
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    Deep Learning toolbox for EEG based Brain-Computer Interface signals decoding and benchmarking

  • arl-eegmodelsbrain-computer-interface · eeg

    This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

  • AugmentedBCIFrameworkbrain-computer-interface · eeg

    The UniPA BCI Framework is an Augmented Brain-Computer Interface framework based on the P300 paradigm with further additional modules to perform the acquisition of eye gaze and physiological features.

  • axonos-community-radarbrain-computer-interface · eeg

    AxonOS Radar — a living, auto-updated map of the open brain-computer-interface field. An AxonOS community project.

sources
  1. api.github.com/repos/BradleyEdelman/BCI-real-time-neuroimaging
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2025-11-11, 3 stars, license reported as GPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/38.json→ .entries["bci-real-time-neuroimaging"]

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