Rreverse-engineering the most complex processor in the universe could be much easier if we had a complete schematic of the computing elements and how they interconnect. Connectomics attempts to build this schematic from real neural systems using incredibly advanced neurotechnology. I'm interested in extracting understanding from the resulting schematics. What are the repeat patterns of connectivity? What are the canonical microcircuits? What are the types of computing elements?
The follow-on to that project was joint work with Srini Turaga at HHMI/Janelia on using continuous, latent-space models for uncovering network structure, and is still ongoing. We presented a poster at COSYNE in 2016.
publications & posters
Kernel Latent Space Models for understanding neural Connectomes Eric Jonas and Srini Turaga, COSYNE 2016 [poster pdf here]
"How the Emerging Revolution in Neural Wiring Diagrams is About to Change Biology" - The Physics arXiv Blog