Super great to get a practitioner’s perspective—thanks!
Completely agree that structural imaging, EEG and fMRI, and existing stim methods are likely not differentially important (except as enablers for other tech, e.g. structural imaging being used for targeting for transcranial approaches like TUS).
I only included these methods for completeness in the review of current R&D. They’re absent from the recommendations.
My contentions above are: (1) that more advanced neurotechnologies, which are currently in clinical and preclinical development, could have large-scale impacts in 30 years (1-5 decade range) (2) neurotechnologies whose performance vastly exceeds the methods you mentioned above that might be differentially beneficial could be developed in 1-2 decades with concerted effort. Some of which we have fundable ideas for.
I think computational neuroscience will eventually be useful, but its utility is dependent on the quality of measurement and manipulation we can achieve of the brain. Neurotechnology is the key to better measurement and manipulation.
Seems like minimally invasive ultrasound, endovascular BCI, and optogenetic cell therapy all get around the “core barriers” you cite to CNS BCI.
None were around 15 years ago.
https://pubmed.ncbi.nlm.nih.gov/33756104/
https://clinicaltrials.gov/ct2/show/NCT03834857?term=synchron&draw=2 (endovascular BCI in humans)
https://www.biorxiv.org/content/10.1101/333526v1.full
I think I did a bad job highlighting the recent successes in my attempt to be comprehensive. And I probably shouldn’t have listed the iBCIs first, b/c readers will think that’s the state-of-the-art.
Definitely agree that non-medical BCI will have a slow adoption curve. As I discuss, though, they don’t need a fast adoption curve to be relevant to AI safety.