An exhaustive, automatically-compiled snapshot of every open-source project, tool and team building brain–computer interfaces in public — discovered, relevance-filtered and ranked from public GitHub signals.
Its repositories, the people building them, and how they connect — live from public GitHub, every fact source-backed.
Change across tracked snapshots (2026-09-23 → 2026-10-01) — measured, not estimated.
The most relevant projects the radar surfaces, placed by two raw GitHub signals. The vertical axis is reach (stars, log scale); the horizontal axis is engagement — forks per star, i.e. how much the community builds on a project rather than just watching it.
Colour encodes category. Positions are relative to the projects shown. This is a descriptive ecosystem map from public signals — not a quality, vision, or clinical ranking.
How strongly each repo signals a genuine BCI focus, from an explicit statement (L3) down to weak adjacency held for review (L0).
What open BCI is actually written in — by number of tracked projects.
Two lenses on the tracked projects — how star reach concentrates, and how recently each project was last pushed.
| # | Project | 7-day | Stars | Category |
|---|---|---|---|---|
| 1 | callbacked/kinesis | +14 | 101 | Hardware & Acquisition |
| 2 | Neuradock/eeg-workstation-agent | +2 | 15 | Hardware & Acquisition |
| 3 | GBeurier/nirs4all | +2 | 40 | Decoding & ML |
Every score below is produced by axonos-brs, an open crate, from the evidence shown beside it. Both are published, so any row here can be recomputed from public data — and a disagreement is a bug report this project cannot argue with.
| Project | Score | Evidence that put it here |
|---|---|---|
| pieeg-club/PiEEG-server | 95 | Explicit BCI topic (bci, brain-computer) +55 · Field standard/format (LSL) +45 · Named BCI hardware (ads1299) +45 · BCI paradigm (Neurofeedback) +40 |
| CheickDiakite-yikes/neurodecodekit | 94 | Explicit BCI topic (brain-computer, brain-computer-interface) +55 · Field standard/format (BIDS, FIF/MNE) +45 · Acquisition modality (EEG, MEG) +40 · Neuro term (neural-decoding) +25 |
| OS-EEG-COLLECT/eeg-collect | 94 | Explicit BCI topic (brain-computer, brain-computer-interface) +55 · Field standard/format (OpenBCI) +45 · Named BCI hardware (cyton, openbci) +45 · Acquisition modality (EEG) +40 |
| mne-rt-org/mne-rt | 94 | Explicit BCI topic (bci, brain-computer) +55 · Field standard/format (FIF/MNE) +45 · Acquisition modality (EEG, MEG) +40 · BCI paradigm (Neurofeedback) +40 |
| brainflow-dev/BrainFlowAndroidTest | 93 | Explicit BCI topic (bci) +55 · Field standard/format (BrainFlow, OpenBCI) +45 · Named BCI hardware (openbci) +45 · Acquisition modality (EEG, EMG) +40 |
| toniIepure25/Imagina | 93 | Explicit BCI topic (bci, brain-computer) +55 · Field standard/format (LSL) +45 · Acquisition modality (EEG) +40 · BCI paradigm (Neurofeedback) +40 |
| brainflow-dev/brainflow | 90 | Explicit BCI topic (bci, brain-computer) +55 · Field standard/format (BrainFlow) +45 · Acquisition modality (EEG, EMG) +40 |
| josephreggy23-coder/IBL-Brain-Wide-Map | 90 | Field standard/format (NWB) +45 · Named BCI hardware (neuropixels) +45 · Acquisition modality (spikes/LFP) +40 · Neuro term (neural-decoding) +25 |
| CerebusOSS/CereLink | 88 | Explicit BCI topic (brain-computer, brain-computer-interface) +55 · Named BCI hardware (blackrock) +45 · Neuro term (neural-signal) +25 · Neuro-anchored 'neural' phrase (e.g. neural interface/signal/decoding) +25 |
| spdlearn/spd_learn | 88 | Explicit BCI topic (bci, brain-computer) +55 · Acquisition modality (EEG) +40 · Neuro term (neural-decoding) +25 · Neuro-anchored 'neural' phrase (e.g. neural interface/signal/decoding) +25 |
| zubara/mneflow | 88 | Explicit BCI topic (brain-computer, brain-computer-interface) +55 · Field standard/format (FIF/MNE) +45 · Acquisition modality (EEG, MEG) +40 |
| BurhanxGodhra/bci-ssl-pretrain | 87 | Explicit BCI topic (bci, brain-computer) +55 · Acquisition modality (EEG) +40 · BCI paradigm (Motor imagery) +40 |
| beukkung/Motor-imagery-EEG-Classification | 86 | Explicit BCI topic (brain-computer, brain-computer-interface) +55 · Acquisition modality (EEG) +40 · BCI paradigm (Motor imagery) +40 |
| neural-interfaces26/neural-interfaces26.github.io | 86 | Explicit BCI topic (bci, brain-computer) +55 · Acquisition modality (EEG, EMG) +40 · Neuro-anchored 'neural' phrase (e.g. neural interface/signal/decoding) +25 |
| omar4a/NeuroTechASU | 86 | Explicit BCI topic (bci) +55 · Acquisition modality (EEG) +40 · BCI paradigm (Motor imagery, P300) +40 |
| pieeg-club/EEGwithRaspberryPI | 85 | Explicit BCI topic (bci) +55 · Named BCI hardware (ads1299) +45 · Acquisition modality (EEG) +40 |
| pieeg-club/ironbci | 85 | Explicit BCI topic (bci) +55 · Named BCI hardware (ads1299) +45 · Acquisition modality (EEG) +40 |
| windwerfer/neurofeed | 84 | Field standard/format (BrainFlow, LSL) +45 · Named BCI hardware (muse-headband) +45 · Acquisition modality (EEG) +40 |
| Mentalab-hub/explorepy | 82 | Explicit BCI topic (bci, brain-computer) +55 · Acquisition modality (EEG, EMG) +40 |
| AxonOS-org/axonos-kernel | 80 | Explicit BCI topic (bci, brain-computer) +55 · Field standard/format (EDF) +45 |
| sccn/eeglab | 80 | Field standard/format (EEGLAB) +45 · Acquisition modality (ECoG, EEG) +40 · Neuro term (electrophysiological, electrophysiology) +25 |
| AxonOS-BCI/axonos-community-radar | 78 | Explicit BCI topic (bci, brain-computer) +55 · Acquisition modality (EEG) +40 |
| BananaPuke/pdf-brain | 78 | Explicit BCI topic (bci, brain-computer) +55 · Acquisition modality (EEG) +40 |
| Neuradock/eeg-workstation | 78 | Explicit BCI topic (bci, brain-computer) +55 · Acquisition modality (EEG) +40 |
| Neuradock/eeg-workstation-agent | 78 | Explicit BCI topic (bci, brain-computer) +55 · Acquisition modality (EEG) +40 |
| NeuroTechX/moabb | 78 | Explicit BCI topic (bci, brain-computer) +55 · Acquisition modality (EEG) +40 |
| mne-tools/mne-denoise | 78 | Field standard/format (FIF/MNE) +45 · Acquisition modality (EEG, MEG) +40 · Neuro term (electrophysiology) +25 |
| Elata-Biosciences/elata-bio-sdk | 77 | Explicit BCI topic (brain-computer, brain-computer-interface) +55 · Acquisition modality (EEG) +40 |
| pyRiemann/pyRiemann | 77 | Explicit BCI topic (brain-computer, brain-computer-interface) +55 · Acquisition modality (EEG) +40 |
| vlawhern/arl-eegmodels | 77 | Explicit BCI topic (brain-computer, brain-computer-interface) +55 · Acquisition modality (EEG) +40 |
| neurotuning/GEDAI-master | 76 | Field standard/format (EEGLAB, FieldTrip) +45 · Acquisition modality (EEG, EMG, EOG) +40 |
| ChilloutCharles/BrainFlowsIntoVRChat | 75 | Explicit BCI topic (bci) +55 · Field standard/format (BrainFlow) +45 |
| Julie-Fabre/bombcell | 75 | Named BCI hardware (neuropixels) +45 · Acquisition modality (spikes/LFP) +40 · Neuro term (electrophysiology) +25 |
| brainbench-org/ibl-bwb | 75 | Named BCI hardware (neuropixels) +45 · Acquisition modality (spikes/LFP) +40 · Neuro term (electrophysiology) +25 |
| fieldtrip/fieldtrip | 75 | Field standard/format (BIDS, FieldTrip) +45 · Acquisition modality (ECoG, EEG, MEG) +40 |
| m-beau/NeuroPyxels | 75 | Named BCI hardware (neuropixels) +45 · Acquisition modality (spikes/LFP) +40 · Neuro term (electrophysiology) +25 |
| neuroinformatics-unit/spikewrap | 75 | Named BCI hardware (neuropixels) +45 · Acquisition modality (spikes/LFP) +40 · Neuro term (electrophysiology) +25 |
| ANCPLabOldenburg/BIDS-Manager | 74 | Field standard/format (BIDS, FIF/MNE) +45 · Acquisition modality (EEG, MEG) +40 |
| cbrnr/mnelab | 74 | Field standard/format (FIF/MNE, LSL) +45 · Acquisition modality (EEG, MEG) +40 |
| mne-tools/mne-bids | 74 | Field standard/format (BIDS, FIF/MNE) +45 · Acquisition modality (EEG, MEG) +40 |
Showing the 40 highest-scoring of 119. The full ledger for every project is in data/radar.json.
Real star counts across radar snapshots for the highest-scoring projects — the line grows richer with every scan.
Owners and organisations shipping the most in the open.
| # | Owner | Type | Followers | Projects | Stars | Active | Focus |
|---|---|---|---|---|---|---|---|
| 1 | mne-tools | ORG | 325 | 6 | 4.1k | 6 | Hardware & Acquisition · Signal Processing |
| 2 | brainflow-dev | ORG | 99 | 2 | 1.8k | 2 | Hardware & Acquisition |
| 3 | pieeg-club | ORG | 218 | 3 | 1.6k | 2 | Hardware & Acquisition |
| 4 | sccn | ORG | 227 | 3 | 1k | 3 | Protocols & OS · Hardware & Acquisition |
| 5 | cbrnr | USER | 163 | 2 | 452 | 2 | Hardware & Acquisition |
| 6 | dipterix | USER | 53 | 2 | 73 | 2 | Hardware & Acquisition |
| 7 | AxonOS-org | ORG | 16 | 5 | 33 | 4 | Protocols & OS · Signal Processing |
| 8 | hed-standard | ORG | 22 | 2 | 30 | 2 | Hardware & Acquisition |
| 9 | Neuradock | ORG | 27 | 2 | 17 | 2 | Hardware & Acquisition |
| 10 | calderast | USER | 33 | 2 | 10 | 2 | Other |
Leaderboards from real public signals. Stars and engagement are always available; downloads, teams and funding are fetched per repository during enrichment.
Total release-asset downloads.
Distinct contributors.
7 of 120 projects expose a funding channel — by platform: open collective (4), github (4), custom (3), patreon (2), ko fi (2), tidelift (2), community bridge (2), liberapay (2), issuehunt (2).
Per-category vitals from the same public signals: size, reach, share pushed in the last 30 days, weekly movers both ways, and the median time since last push.
| Category | Projects | Stars | Active % | Rising | Falling | Median push |
|---|---|---|---|---|---|---|
| Hardware & Acquisition ↑ | 58 | 15.5k | 95% | 2 | — | 2d |
| Decoding & ML | 20 | 5.3k | 90% | 1 | — | 3d |
| Other | 20 | 25.8k | 85% | — | — | 5d |
| Protocols & OS ↓ | 12 | 883 | 100% | — | — | 3d |
| Signal Processing | 9 | 795 | 78% | — | — | 2d |
| Real-time & Embedded | 1 | 9 | 100% | — | — | 0d |
Whether the field is legally reusable: a declared SPDX licence, a licence GitHub cannot classify (NOASSERTION), or none at all.
The radar reports on itself: every number below comes from data/status.json, committed with each scan.
Every project on the radar, ranked by discovery score. One table, the whole field — the one-click, exhaustive answer.
| # | Project | Category | Stars | Δ7d | Forks | Team | Downloads | Rel. | Activity | Language | Evidence | Active |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | brainflow-dev/brainflow BrainFlow is a library intended to obtain, parse and analyze… | Hardware & Acquisition | 1.8k | +7 | 414 | 69 | 282.4k | 100 | C++ | L3 | ● | |
| 2 | NeuroTechX/moabb Mother of All BCI Benchmarks | Decoding & ML | 1.1k | +2 | 266 | 86 | 30 | 18 | Python | L3 | ● | |
| 3 | BasedHardware/omi AI that sees your screen, listens to your conversations and … | Other | 13.6k | +73 | 2.5k | 414 | 16.9k | 100 | Python | L3 | ● | |
| 4 | NeuroSkill-com/skill NeuroSkill™ — State of Mind Brain-Computer Interface system | Hardware & Acquisition | 103 | +1 | 24 | 5 | 164.8k | 100 | Rust | L3 | ● | |
| 5 | neuropsychology/NeuroKit NeuroKit2: The Python Toolbox for Neurophysiological Signal … | Hardware & Acquisition | 2.4k | +7 | 547 | 106 | — | 31 | Python | L2 | ● | |
| 6 | sccn/liblsl C++ lsl library for multi-modal time-synched data transmissi… | Protocols & OS | 179 | +2 | 90 | 35 | 129.8k | 36 | C++ | L0 | ● | |
| 7 | CerebusOSS/CereLink Blackrock Neurotech Cerebus Link for Neural Signal Processor… | Other | 64 | +1 | 28 | 15 | 6.6k | 42 | C++ | L3 | ● | |
| 8 | cbrnr/sigviewer A viewing application for biosignals | Hardware & Acquisition | 157 | +1 | 42 | 13 | 13.6k | 9 | C++ | L2 | ● | |
| 9 | openmeeg/openmeeg A C++ package for low-frequency bio-electromagnetism solving… | Hardware & Acquisition | 87 | — | 49 | 26 | 768 | 24 | C++ | L2 | ● | |
| 10 | SpikeInterface/spikeinterface A Python-based module for creating flexible and robust spike… | Other | 856 | +6 | 280 | 134 | — | — | Python | L2 | ● | |
| 11 | MouseLand/Kilosort Fast spike sorting with drift correction | Other | 631 | +3 | 296 | 47 | — | 26 | Python | L2 | ● | |
| 12 | cortex-lab/phy phy: interactive visualization and manual spike sorting of l… | Other | 432 | +1 | 187 | 24 | 11 | 1 | Python | L0 | ● | |
| 13 | Mentalab-hub/explorepy Python API for Mentalab biosignal aquisition devices | Hardware & Acquisition | 56 | +1 | 24 | 22 | 1.8k | 34 | Python | L3 | ● | |
| 14 | Julie-Fabre/bombcell Automated quality control, curation and neuron classificatio… | Other | 252 | — | 65 | 19 | — | 13 | Jupyter Notebook | L2 | ● | |
| 15 | scouter-project/scouter Scouter is an open source APM (Application Performance Manag… | Other | 2.2k | — | 570 | 81 | 351.7k | 90 | Java | L3 | ○ | |
| 16 | fooof-tools/fooof Parameterizing neural power spectra into periodic & aperiodi… | Signal Processing | 450 | — | 116 | 16 | — | 15 | Python | L2 | ● | |
| 17 | cwindolf/dartsort A modular spike sorter written in Python and PyTorch | Decoding & ML | 29 | — | 16 | 39 | — | 39 | Python | L2 | ● | |
| 18 | mne-tools/mne-rsa Representational Similarity Analysis on MEG and EEG data | Hardware & Acquisition | 88 | — | 16 | 8 | 75 | 5 | Python | L2 | ● | |
| 19 | Eden-Kramer-Lab/spectral_connectivity Frequency domain estimation and functional and directed conn… | Signal Processing | 137 | — | 49 | 12 | — | 14 | Python | L2 | ● | |
| 20 | brainstorm-tools/brainstorm3 Brainstorm software: MEG, EEG, fNIRS, ECoG, sEEG and electro… | Hardware & Acquisition | 487 | — | 190 | 61 | — | 1 | MATLAB | L2 | ● | |
| 21 | gifale95/BERG Trained encoding models to generate in silico neural respons… | Hardware & Acquisition | 55 | +1 | 8 | 3 | — | 19 | Python | L2 | ● | |
| 22 | sccn/eeglab EEGLAB is an open source signal processing environment for e… | Hardware & Acquisition | 799 | +2 | 275 | 62 | — | — | MATLAB | L2 | ● | |
| 23 | LollosoSi/bruxism-detector This small suite helps you detect bruxism and interrupt it. | Decoding & ML | 44 | +1 | 1 | 2 | 107 | 22 | C++ | L2 | ● | |
| 24 | dipterix/threeBrain 3D Visualization of Brain MRI | Hardware & Acquisition | 52 | — | 10 | 3 | 19 | 13 | R | L2 | ● | |
| 25 | pieeg-club/ironbci Wearable (BLE) Brain-Computer Interface, ADS1299 and STM32 w… | Hardware & Acquisition | 631 | +1 | 66 | 4 | — | — | Python | L3 | ● | |
| 26 | mne-tools/mne-python MNE: Magnetoencephalography (MEG) and Electroencephalography… | Hardware & Acquisition | 3.5k | +5 | 1.6k | 468 | — | 67 | Python | L2 | ● | |
| 27 | ChilloutCharles/BrainFlowsIntoVRChat BrainFlow code that sends your brain's relaxation, focus met… | Protocols & OS | 346 | — | 30 | 9 | — | — | Python | L3 | ● | |
| 28 | yzhaoinuw/sleep_scoring Desktop app for scoring mouse sleep from EEG, EMG, and norep… | Hardware & Acquisition | 7 | — | 1 | 2 | 58 | 24 | Python | L2 | ● | |
| 29 | mne-tools/mne-icalabel Automatic labeling of ICA components in Python. | Hardware & Acquisition | 123 | — | 20 | 13 | — | 12 | — | Python | L2 | ● |
| 30 | mne-tools/mne-cpp MNE-CPP: The C++ framework for real-time functional brain im… | Hardware & Acquisition | 177 | +1 | 143 | 65 | 20.5k | 19 | C++ | L2 | ● | |
| 31 | pieeg-club/PiEEG-server One-line install for real-time biosignals: acquisition, proc… | Hardware & Acquisition | 56 | — | 17 | 4 | — | 42 | TypeScript | L3 | ● | |
| 32 | braindecode/braindecode Deep learning software to decode EEG, ECG or MEG signals | Decoding & ML | 1.3k | +4 | 282 | 83 | 28 | 17 | Python | L2 | ● | |
| 33 | beacon-biosignals/PyMNE.jl Julia interface to MNE-Python via PythonCall | Hardware & Acquisition | 30 | — | 7 | 7 | — | 9 | Julia | L2 | ● | |
| 34 | spdlearn/spd_learn SPDlearn: A Geometric Deep Learning Python Library for Neura… | Decoding & ML | 41 | +1 | 9 | 7 | — | 2 | Python | L3 | ● | |
| 35 | mne-tools/mne-denoise Artifact removal and signal denoising for EEG and MEG. | Signal Processing | 31 | — | 8 | 3 | — | 2 | Python | L2 | ● | |
| 36 | Elata-Biosciences/elata-bio-sdk Elata SDK is the cross-platform biosignal toolkit for buildi… | Protocols & OS | 93 | +1 | 8 | 4 | — | — | TypeScript | L3 | ● | |
| 37 | upsidedownlabs/Chords-Web Chords is a web application that transforms your Arduino boa… | Hardware & Acquisition | 39 | — | 15 | 7 | — | — | TypeScript | L2 | ● | |
| 38 | JuliaHealth/NeuroAnalyzer.jl Julia toolbox for analyzing neurophysiological data | Hardware & Acquisition | 22 | — | 5 | 7 | — | 2 | Julia | L2 | ● | |
| 39 | tradecatlabs/human_infra Human Infra: docs-as-code knowledge base for human runtime i… | Protocols & OS | 103 | +1 | 10 | 1 | — | — | Python | L3 | ● | |
| 40 | NexusDynamic/liblsl.dart Dart interface for Lab Streaming Layer / liblsl | Protocols & OS | 6 | — | 4 | 3 | 24 | 9 | Dart | L2 | ● | |
| 41 | cbrnr/mnelab MNELAB – a GUI for MNE-Python | Hardware & Acquisition | 295 | — | 82 | 21 | 2.4k | 57 | Python | L2 | ● | |
| 42 | zubara/mneflow Neural networks for EEG-MEG decoding with MNE-python and Ten… | Decoding & ML | 46 | — | 13 | 15 | — | — | Python | L3 | ● | |
| 43 | sdraeger/DDALAB DDALAB is a software platform for analyzing physiological ti… | Hardware & Acquisition | 5 | — | 1 | 2 | 37 | 5 | Python | L2 | ● | |
| 44 | TBC-TJU/MetaBCI MetaBCI: China’s first open-source platform for non-invasive… | Other | 569 | +1 | 254 | 28 | — | 4 | Python | L3 | ○ | |
| 45 | dav0dea/goofi-pipe real-time neuro-/biosignal processing and streaming pipeline | Signal Processing | 44 | +1 | 12 | 7 | — | — | Python | L2 | ● | |
| 46 | neuroinformatics-unit/spikewrap A package to manage electrophysiology analysis. | Other | 22 | — | 17 | 9 | — | 8 | Python | L2 | ● | |
| 47 | fieldtrip/fieldtrip The MATLAB toolbox for MEG, EEG and iEEG analysis | Hardware & Acquisition | 988 | — | 771 | 243 | — | 17 | MATLAB | L2 | ● | |
| 48 | neural-interfaces26/neural-interfaces26.github.io The Neural Interface Foundation Challenge — NeurIPS 2026 Syd… | Decoding & ML | 9 | — | 0 | 7 | — | — | HTML | L3 | ● | |
| 49 | delvendahl/miniML A deep learning framework for synaptic event detection | Decoding & ML | 31 | — | 12 | 5 | — | 3 | Python | L2 | ● | |
| 50 | dervinism/minis 'minis' is a software for electrophysiological data analysis… | Protocols & OS | 12 | — | 4 | 1 | 378 | 4 | MATLAB | L2 | ● | |
| 51 | brainflow-dev/BrainFlowAndroidTest Learning-focused BrainFlow Android example for Muse BLE EEG,… | Hardware & Acquisition | 10 | — | 6 | 2 | 126 | 2 | Java | L3 | ● | |
| 52 | neuromodulation/PyPARRM Python port of the PARRM algorithm for removing periodic art… | Signal Processing | 10 | — | 6 | 4 | — | 3 | Python | L2 | ● | |
| 53 | dipterix/three-brain-js Javascript engine for 3D brain model (used by RAVE project) | Hardware & Acquisition | 21 | — | 7 | 1 | — | — | JavaScript | L2 | ● | |
| 54 | windwerfer/neurofeed A EEG monitor + feedback programm for Muse 2 / S / Athena (+… | Hardware & Acquisition | 2 | — | 0 | 1 | 6 | 9 | Dart | L2 | ● | |
| 55 | yjunechoe/jlmerclusterperm Fast cluster-based permutation test for densely-sampled, mul… | Hardware & Acquisition | 14 | — | 1 | 1 | — | 14 | R | L2 | ● | |
| 56 | calderast/jdb_to_nwb Converts electrophysiology, photometry, and behavioral data … | Other | 7 | — | 3 | 4 | — | 9 | Jupyter Notebook | L0 | ● | |
| 57 | CheickDiakite-yikes/neurodecodekit Open-source, local-first EEG/MEG language-decoding research … | Decoding & ML | 5 | +1 | 0 | 2 | — | — | Python | L3 | ● | |
| 58 | ford442/brain_viz Real-time 3D brain data visualization powered by EEG/tensors… | Hardware & Acquisition | 4 | +1 | 0 | 6 | — | — | JavaScript | L3 | ● | |
| 59 | indos-costaction/indos-costaction.github.io Website for the INDoS COST action | Hardware & Acquisition | 4 | — | 9 | 10 | — | — | CSS | L2 | ● | |
| 60 | Neuradock/eeg-workstation-agent Open-source EEG analysis agent workflows and prompts for Neu… | Hardware & Acquisition | 15 | +2 | 2 | 2 | 16 | 1 | Python | L3 | ● | |
| 61 | GWeindel/hmp Repository for the hmp python package | Signal Processing | 57 | +1 | 13 | 13 | — | 18 | Python | L2 | ○ | |
| 62 | alesantuz/musclesyneRgies R package to extract muscle synergies from electromyogram | Hardware & Acquisition | 52 | +1 | 7 | 6 | — | 45 | HTML | L2 | ● | |
| 63 | pyRiemann/pyRiemann Machine learning for multivariate data through the Riemannia… | Decoding & ML | 778 | +1 | 191 | 46 | — | 13 | Python | L3 | ● | |
| 64 | INM-6/viziphant Visualization of electrophysiological data from Elephant | Other | 25 | — | 7 | 17 | — | 4 | Python | L2 | ● | |
| 65 | cia-ulaval/Site_Club_IA Official repository for the Club d'Intelligence Artificielle… | Hardware & Acquisition | 4 | — | 1 | 4 | — | — | TypeScript | L2 | ● | |
| 66 | wzpan/wukong-robot 🤖 wukong-robot 是一个简单、灵活、优雅的中文语音对话机器人/智能音箱项目，支持ChatGPT多轮对话能力，… | Other | 7.1k | −1 | 1.4k | 23 | — | — | Python | L3 | ○ | |
| 67 | BananaPuke/pdf-brain 📚 Index and enrich your PDFs and Markdown files locally for … | Decoding & ML | 3 | — | 1 | 3 | — | — | TypeScript | L3 | ● | |
| 68 | eugenehp/muse-rs Rust client for Muse EEG headsets over BLE | Hardware & Acquisition | 8 | — | 1 | 1 | — | 4 | Rust | L2 | ● | |
| 69 | DertMatt24/Apnoea-EEG Deep learning functional/statistical analysis of multichanne… | Hardware & Acquisition | 4 | — | 0 | 3 | — | — | Python | L2 | ● | |
| 70 | ivsemenkov/LISA Compact and interpretable MEG-to-audio retrieval with explic… | Decoding & ML | 19 | +1 | 0 | 1 | — | — | Python | L2 | ● | |
| 71 | open-ephys/liboni API for controlling ONI-compliant hardware | Hardware & Acquisition | 2 | — | 8 | 24 | — | — | C | L2 | ● | |
| 72 | fangq/redbird Redbird - A Model-Based Diffuse Optical Imaging Toolbox | Other | 7 | — | 0 | 3 | — | 1 | MATLAB | L0 | ● | |
| 73 | lebidan/sbnd Train and evaluate syndrome-based neural decoders on your fa… | Decoding & ML | 2 | — | 0 | 1 | — | 3 | Python | L2 | ● | |
| 74 | mne-tools/mne-bids MNE-BIDS is a Python package that allows you to read and wri… | Hardware & Acquisition | 182 | −1 | 115 | 70 | — | 22 | Python | L2 | ● | |
| 75 | djoshea/trial-data Interfaces and utilities for analysis of neurophysiology and… | Other | 6 | — | 4 | 3 | — | — | MATLAB | L2 | ● | |
| 76 | dll-ncai/NMT-4k-EEG-Dataset Code, notebooks, validation scripts, and analysis outputs fo… | Hardware & Acquisition | 3 | — | 0 | 2 | — | 3 | Jupyter Notebook | L2 | ● | |
| 77 | ANCPLabOldenburg/BIDS-Manager GUI and CLI tool for raw-to-BIDS conversion, curation, metad… | Hardware & Acquisition | 10 | +1 | 5 | 3 | — | — | — | Python | L2 | ● |
| 78 | GazzolaLab/MiV-Simulator Bio-physical neural network simulator for Mind-in-Vitro | Other | 6 | — | 6 | 7 | — | — | Python | L2 | ● | |
| 79 | josephreggy23-coder/IBL-Brain-Wide-Map Real-data IBL Neuropixels analysis of decision-related neura… | Decoding & ML | 3 | +1 | 0 | 3 | — | — | Python | L2 | ● | |
| 80 | open-ephys/onix-fmc-host FMC board to acquire from ONIX headstages and breakout board… | Hardware & Acquisition | 4 | — | 2 | 6 | — | 5 | HTML | L2 | ● | |
| 81 | Zbezz-git/NeuroScope 🔍 Visualize and analyze neural network execution in real-tim… | Hardware & Acquisition | 3 | — | 0 | 2 | — | — | Python | L2 | ● | |
| 82 | analyticalmonk/awesome-neuroscience A curated list of awesome neuroscience libraries, software a… | Hardware & Acquisition | 1.7k | +5 | 183 | 16 | — | — | — | L2 | ○ | |
| 83 | jonescompneurolab/hnn-core Simulation and optimization of neural circuits for MEG/EEG s… | Hardware & Acquisition | 83 | — | 96 | 46 | 26 | 12 | Python | L2 | ● | |
| 84 | m-beau/NeuroPyxels NeuroPyxels (npyx) is a python library built for electrophys… | Hardware & Acquisition | 157 | +2 | 33 | 14 | — | 3 | Python | L2 | ○ | |
| 85 | BurhanxGodhra/bci-ssl-pretrain Self-supervised contrastive pretraining for subject-independ… | Decoding & ML | 3 | — | 0 | 2 | 3 | 1 | Python | L3 | ● | |
| 86 | OS-EEG-COLLECT/eeg-collect Application for simplified EEG data collection | Hardware & Acquisition | 3 | — | 1 | 2 | — | — | Vue | L3 | ● | |
| 87 | toniIepure25/Imagina AI-powered EEG research platform for mental imagery analysis… | Protocols & OS | 2 | — | 0 | 1 | — | — | Python | L3 | ● | |
| 88 | Jalte-Diye-Foundation/NuroLab Smart devices for Improvement of Mental Health | Other | 7 | — | 5 | 2 | — | — | Kotlin | L3 | ● | |
| 89 | GBeurier/nirs4all A library for Near Infrared Sprectroscopy prediction. NIRS M… | Decoding & ML | 40 | +2 | 1 | 2 | 13 | 69 | Python | L0 | ● | |
| 90 | omar4a/NeuroTechASU NeuroTech Ain Shams University — First NeuroTechX student ch… | Hardware & Acquisition | 2 | — | 1 | 2 | — | — | Python | L3 | ● | |
| 91 | neurotuning/GEDAI-master GEDAI denoising plugin for Matlab (EEGLAB, Brainstorm and Fi… | Hardware & Acquisition | 70 | — | 14 | 4 | 52 | 9 | MATLAB | L2 | ● | |
| 92 | Kahaan83/Biomechanical-throw-tracker Wearable glove that streams IMU + EMG + grip data over ESP-N… | Hardware & Acquisition | 5 | — | 0 | 2 | — | — | HTML | L2 | ● | |
| 93 | Neuradock/eeg-workstation Project overview for NeuraDock EEG Workstation, a 7-channel … | Hardware & Acquisition | 2 | — | 0 | 2 | — | — | HTML | L3 | ● | |
| 94 | LorenFrankLab/spyglass Neuroscience data analysis framework for reproducible resear… | Protocols & OS | 119 | — | 60 | 37 | — | 7 | Jupyter Notebook | L2 | ● | |
| 95 | Mattbusel/NeuroPulseML-AI-for-Human-Electrical-Signal-Diagnostics Research concept for flagging early neurological and cardiac… | Hardware & Acquisition | 2 | — | 0 | 1 | — | — | Python | L2 | ● | |
| 96 | xiangzhang1015/Deep-Learning-for-BCI Resources for Book: Deep Learning for EEG-based Brain-Comput… | Decoding & ML | 300 | +2 | 71 | 3 | — | — | Jupyter Notebook | L3 | ○ | |
| 97 | pieeg-club/EEGwithRaspberryPI Not supported. Measure 8 EEG channels with Shield PiEEG and … | Hardware & Acquisition | 946 | — | 90 | 4 | — | — | Python | L3 | ○ | |
| 98 | vlawhern/arl-eegmodels This is the Army Research Laboratory (ARL) EEGModels Project… | Decoding & ML | 1.6k | +1 | 334 | 3 | — | — | Python | L3 | ○ | |
| 99 | IgarashiAkatuki/HuiduRep Representation Learning Framework for Extracellular Recordin… | Other | 10 | — | 2 | 2 | — | — | Python | L2 | ● | |
| 100 | beukkung/Motor-imagery-EEG-Classification Using one-dimension CNN architecture to MI-EEG classificatio… | Decoding & ML | 2 | — | 0 | 1 | — | — | Jupyter Notebook | L3 | ● | |
| 101 | brainbench-org/ibl-bwb Benchmarking large-scale pretraining and across-animal trans… | Protocols & OS | 2 | — | 3 | 1 | — | — | Python | L2 | ● | |
| 102 | sccn/eegprep EEGPrep is an automated preprocessing tool for human EEG dat… | Signal Processing | 37 | +1 | 6 | 12 | 4 | 4 | Python | L2 | ● | |
| 103 | calderast/Hex-maze-spyglass Spyglass extension package for hex maze behavioral and neura… | Other | 3 | — | 3 | 2 | — | — | — | Jupyter Notebook | L2 | ● |
| 104 | callbacked/kinesis native macos controls for the meta neural band (highly exper… | Hardware & Acquisition | 101 | +14 | 6 | 1 | 37 | 6 | Swift | L2 | ● | |
| 105 | vferat/pycrostates | Hardware & Acquisition | 51 | — | 12 | 11 | — | 11 | Python | L2 | ● | |
| 106 | hed-standard/hed-python Python validation, summary, and analysis tools for HED (Hier… | Hardware & Acquisition | 18 | — | 13 | 12 | — | 16 | Python | L2 | ● | |
| 107 | AxonOS-BCI/axonos-community-radar AxonOS Radar — a living, auto-updated map of the open brain-… | Hardware & Acquisition | 4 | — | 0 | 3 | 14 | 77 | Python | L3 | ● | |
| 108 | hed-standard/hed-specification Specification documents for HED (Hierarchical Event Descript… | Hardware & Acquisition | 12 | — | 11 | 9 | 26 | 8 | Python | L2 | ● | |
| 109 | SUSE/BCI-dockerfile-generator Generator for the SUSE Linux BCI Build recipes | Other | 18 | — | 37 | 33 | — | — | Python | L3 | ● | |
| 110 | AxonOS-org/axonos-signal-pipeline Deterministic, vector-pinned BCI signal pipeline for AxonOS:… | Signal Processing | 3 | — | 0 | 1 | — | 13 | Rust | L3 | ○ | |
| 111 | HNXJ/jaxfne Tensor-Field Neural Equations (TFNE) in JAX | Other | 2 | — | 0 | 4 | 13 | 39 | HTML | L2 | ● | |
| 112 | spm/spm-docs SPM Documentation | Hardware & Acquisition | 25 | — | 7 | 15 | — | — | — | L2 | ● | |
| 113 | josephdong1000/neurodent Pipeline to analyze and generate figures from rodent EEGs | Hardware & Acquisition | 9 | +1 | 1 | 8 | — | 10 | Python | L2 | ● | |
| 114 | AgneGris/swarm-contrastive-decomposition Decomposition of Neurophysiological Time Series Signals with… | Decoding & ML | 28 | — | 11 | 4 | 8 | 2 | Python | L2 | ● | |
| 115 | mne-rt-org/mne-rt Real-time M/EEG signal processing | Signal Processing | 26 | +1 | 4 | 2 | — | 1 | Python | L3 | ● | |
| 116 | Inria-NERV/happyFeat A framework for simplying BCI workflow in clinical applicati… | Hardware & Acquisition | 26 | — | 5 | 4 | 38 | 4 | Python | L3 | ● | |
| 117 | AxonOS-org/axonos-kernel Hard real-time Rust microkernel for brain-computer interface… | Real-time & Embedded | 9 | +1 | 0 | 2 | 10 | 8 | Rust | L3 | ● | |
| 118 | AxonOS-org/axonos-consent Kernel-level consent state machine for brain–computer interf… | Protocols & OS | 6 | +1 | 0 | 2 | — | 8 | Rust | L3 | ● | |
| 119 | AxonOS-org/axonos-protocol The AxonOS Consent Protocol — specification and reference im… | Protocols & OS | 9 | +1 | 0 | 1 | — | 11 | Rust | L3 | ● | |
| 120 | AxonOS-org/axonos-standard Canonical technical standard and architecture manual for Axo… | Protocols & OS | 6 | +1 | 0 | 2 | — | 2 | Python | L3 | ● |
Discovery. A zero-dependency Python pipeline queries the public GitHub API across a curated set of neurotech topics and keywords, de-duplicates, and relevance-filters every candidate before it appears here.
Evidence tiers. Each repository is graded L3–L0 by how strongly it signals a genuine BCI focus, with weak or adjacent matches flagged for review rather than hidden.
Scoring. A single published multi-signal formula — log-scaled stars and recency, plus enriched terms for release downloads, contributors and commit activity — applied identically to every project. AxonOS is ranked like everyone else and is never boosted.
Enriched signals. Per repository the pipeline additionally fetches real GitHub data: contributor counts (team size), release-asset download totals (adoption), a 52-week commit-activity histogram (maintenance) and declared funding channels (FUNDING.yml). GitHub exposes repository page views only to a repo’s own owners, so views are deliberately not shown rather than approximated.
Money & domicile. Capital raised and legal domicile are not in GitHub; when shown they come only from a hand-curated, source-cited overrides file and are labelled as such. Nothing is estimated.
The quadrant. Axes are raw GitHub metrics (stars; forks per star), min-max normalised across the projects shown. It is a descriptive map, not a vision or quality judgement.
Refresh. The whole field is re-scanned every three hours; the last good snapshot is kept if a scan partially fails, so the map never goes blank.
Coverage. This scan read 3,324 repositories across 33 topics. 554,742 more matched a query and could not be read: GitHub returns at most a thousand results per search and does not page beyond that. Those repositories exist and this map has not seen them, which is a limit of the method rather than of the field.
Honesty. Every number here is a real public signal. Inclusion is discovery, not endorsement, and nothing is fabricated from data the pipeline does not actually collect.