Computational Neuroscience

100,000 brains.
One model.

Neuraldyne builds digital twins of the human brain from the largest proprietary neural scan dataset ever assembled. The scans can't be downloaded. The compute can't be replicated. The models get better with every brain.

We don't sell software. We build understanding.

Most neurotech companies ship dashboards. We simulate entire brains. Our research combines high-resolution fMRI, dense EEG, and diffusion imaging into individualized computational models that predict neural behavior before it happens.

Connectomics

Whole-brain reconstruction

Multi-modal fusion pipelines that build individual connectomes from structural and functional scans. Not atlases. Not averages. Your brain, specifically.

Simulation

Digital twin dynamics

Biophysically realistic simulations running on quantum-classical hybrid compute. We model synaptic activity, not just connectivity graphs.

Prediction

Neural forecasting

Models trained on 100,000 longitudinal scans detect cognitive decline years before symptoms. The dataset is the moat.

The dataset nobody else has

Neuraldyne's proprietary brain scan archive is the foundation of everything we build. Consented, longitudinal, multi-modal. Collected over years across clinical and research partners. It cannot be scraped, licensed, or approximated.

100K+
Individual brain scans
across modalities
7T fMRI
High-field imaging
with sub-millimeter resolution
Longitudinal
Repeat scans tracking
change over years

Built for problems GPUs can't solve

Simulating a brain at biological fidelity requires compute architectures that don't exist in any cloud catalog. We build our own.

Quantum-classical hybrid
Variational quantum circuits handle the combinatorial explosion of synaptic state spaces. Classical GPUs handle everything else. Neither works alone.
Neuromorphic co-processors
Spiking neural network accelerators for real-time digital twin inference. Microsecond latency on models with billions of parameters.
Federated data plane
Brain scans never leave their source institution. Models train across distributed nodes without centralizing sensitive data. Privacy by architecture, not policy.
Cold storage archive
Petabytes of raw imaging data preserved at full resolution. When new algorithms emerge, we re-process the entire archive. The data appreciates.

Research inquiries

We work with a small number of research institutions and clinical partners. If you have data, compute, or problems worth solving, we should talk.