Connectomics

This functions as an R&D compass heading.

Connectomics has historically been an expensive, tedious discipline where mapping neural structures via electron microscopy consumed decades of academic funding.

The moment Google proves this anatomical data can serve as an open substrate for viral rapid-fire computational experiments, the economics of biological crossover computing shift.

If FLM-style hybrid architectures demonstrate even marginal sample efficiency improvements or unlock spatial reasoning capabilities, that current transformer pipelines require billions of additional parameters to approximate, biological connectomes will transition from academic novelties into dedicated enterprise research line items.

related news, I just added this below that.

A Connectomics milestone, Google has mapped the complete male fruit fly brain.

Wow.

Wow.

It is sort of a time-varying estimation of that.

So a few years ago, I think it was 2024, the Wellcome Trust put out a report, I think it was called Scaling Connectomics, and they projected, you know, the order of like $10 billion or something and like a 15-year project basically to do a good job of the mouse brain.

Most of that was the part that I'm indicating, I think can make massive progress from some combination of AI and clever labeling of the neurons.

That was presupposing essentially electron microscopy as the way of doing it.

And that leads us to the methodological breakthrough of this paper.

Individualized Functional Connectomics, or IFC.

Connectomics, the study of how the brain connects to itself.

Yes.

So instead of looking for which part of the brain is like working hard during a reading test, IFC looks at the baseline communication between brain regions over time.