I havenāt posted in 3 years. Iām pursuing some private study / learning into Neuroscience generally, and trying to find some interesting, solvable problems I can commit to contributing to, bringing my previous experience in general software engineering.
Iām deliberately avoiding academic research - something like pursuing a PhD. Iāll post about why one day.
What I want to do is share what Iām learning and looking into with some cadence. I could note this privately, but I think there are some benefits to it being public.
- Iām loosely committed to continue to work and post by talking about it publicly
- Writing about things forces one to have clarity of thought, so I get a chance to refine my own thinking
- Assuming I do āget somewhereā with this, it could provide a useful roadmap for myself or others on how I got here. (Iād love to elaborate also on what āget somewhereā means - again Iāll post why one day.)
The format will evolve as I go.
Hereās what Iām thinking about now
Current wider ideas:
- For the most part, academic code is poorly readable, not highly reusable, and slow.
- There is starting to be a heap of data available online, which, so far as I can tell, noone is using cohesively. See OpenNeuro
- There are a heap of documented problems available online, usually in the form of PhD breifings. See The Florey Institute for an example.
Specific Learnings:
- It seems like the most available and useful format for gathering information from living brains is the MRI. An MRI can retrieve different data based on running MRI sequences.
- Tractography is a specific imaging technique based on a set of particular MRI sequences, the DWI (Diffusion Weighted Image)
- I think this is a good starting resource for tractography, which I got to by following a more recent article on tractography, which was part of a PhD brief: Hot topics in diffusion tractography