Thesis.
Living-neuron compute is moving from research curiosity to commercial substrate, and the field has a tooling gap. Labs working with multi-electrode arrays each rebuild the same analysis pipeline in slightly different ways, with no shared baseline against which to compare results.
I'm not a domain expert. I'm a founder who reads the peer-reviewed literature directly and ships what the field needs — with AI-assisted engineering as a force multiplier. NeuroBridge is the first artefact of that approach.
What's inside.
Nine peer-reviewed analysis methods, each shipped with the citation to its original source:
- Burst detection — Bakkum 2013
- Functional connectivity via transfer entropy — Schreiber 2000
- Criticality fitting — Clauset 2009
- IIT Φ approximation via Queyranne MIP — Tononi 2004
- Kuramoto metastability
- Predictive coding proxy
- Sleep–wake HMM staging
- Composite scoring & comparative profiling against ten reference neural systems
- Surrogate-based significance testing with Bonferroni correction
137 REST API endpoints. ~12,000 lines of Python. Stack: Python 3.12 / FastAPI / NumPy / SciPy on the backend, Next.js 16 + React 19 + D3.js on the frontend. Deployed on Vercel with a VPS running Caddy and PM2 for the API.
Validation.
Validated end-to-end on FinalSpark's public fs437 dataset:
A methods preprint is forthcoming on arXiv this April.
Design priorities.
Three calls I made deliberately, because the field punishes overclaiming:
- Citation chain. Every method names its source paper in the UI and the API response.
- Honest labels. The composite score is "Network Complexity Index", not "IQ". Φ is "network irreducibility measure", not "consciousness".
- Auditable end-to-end. MIT license, source on GitHub, package on PyPI. Anyone can rerun the pipeline on their own data and check my work.
Get involved.
Open to dataset exchanges, method validation, and joint methodological work with academic and industry labs working on MEA, organoid, or cell-culture electrophysiology. If that's you — write me directly.
Get in touch