I really enjoyed this piece and think it’s an important topic.
The question of how the brain implements priors, and how they can become maladaptively ‘trapped’, is an open question. I suggested last year that we could combine the “hemo-neural hypothesis” that bloodflow regulates the dynamic range of nearby neurons/nerves, with the “latch-bridge mechanism” where smooth muscle (inclusive of vascular muscle) can lock itself in a closed position. I.e. vascular tension is a prediction (Bayesian prior) about the world, and such patterns of microtension can be stored in a very durable form (“smooth muscle latches”) that can persist for days, weeks, months, years, decades.
This paints psychological release, releasing a trapped prior, and vasomuscular release as the same thing.
https://opentheory.net/2023/07/principles-of-vasocomputation-a-unification-of-buddhist-phenomenology-active-inference-and-physical-reflex-part-i/
I’m really glad to see this. I can’t say I fully grasp your particular approach, but what you’ve written about model fragments has really resonated.
My intuition around value extrapolation is that if we extrapolate the topic itself it’ll eventually turn into creating fine models of nervous system dynamics. Will be curious to see how your work intersects and what it assumes about neuroscience, and also what sort of neuroscience progress you think might make your work easier.
Good luck!
I do think that lower-frequency harmonics will be both better defined, and more useful for hanging functional or computational stories on. (Agree that low-harmonics-as-operators-on-bayesian-priors could be a very generative frame. I'm a little skeptical of the current stories being told of functional localization; some of the localization could indeed be spatial, but some could be temporal (information tacitly encoded into harmonics). I think the proof is in the pudding in terms of what each hypothesis can let us do. Probably no one-size-fits-all.
Thanks for the thoughtful comment. I would generally endorse the claims you make, but would differ on your analogy about psychologists not needing to know about advances in neuroscience for the same reason programmers don't need to know about transistors, and the conclusion you draw from that.
First, I'd stand behind the theme that:
The problem facing neuroscience in 2018 is that we have a lot of experimental knowledge about how neurons work– and we have a lot of observational knowledge about how people behave– but we have few elegant compressions for how to connect the two. CSHW promises to do just that, to be a bridge from bottom-up neural dynamics – things we... (read more)
I don't think folk psychology does a good job at ontology when it comes to speaking about subjects like depression or willpower.
I'd agree with that.
How does what you propose there differ from General Semantics?
I don't know enough about General Semantics to offer much here, but from a quick reading of Wikipedia it feels like GS is aimed at a slightly different goal, and relies on a much different algorithmic stack, than a CSHW-inspired theory of language and meaning. Would be glad to hear your thoughts.
Hi shminux,
You're welcome to follow the academic literature trail I link to. CSHW is a new paradigm so it would definitely would benefit from a close critical review, if you're able to provide that. (If you'd rather just critique something as pattern-matching to "crackpot red flags" and "pretty pictures" you can do that too, but I find this to be a content-free strategy of avoiding dealing with any of my object-level or methodological claims, and think that it needlessly lowers the level of discussion.)
I mention my personal intuitions about "limitations and potential failures" near the end of my piece; . My expectation is that CSHW, along with the predictive coding framework, is the most plausible route for neuroscience to develop knowledge in the five spheres I identified. ("Most plausible" does not mean "sure thing" of course.) The hard work still needs to be done of course. If you know of more plausible ways to unify neuroscience I'd be happy to read about it.
Crossposted and slightly adapted from opentheory.net.
I think all neuroscientists, all philosophers, all psychologists, and all psychiatrists should basically drop whatever they’re doing and learn Selen Atasoy’s “connectome-specific harmonic wave” (CSHW) framework. It’s going to be the backbone of how we understand the brain and mind in the future, and it’s basically where predictive coding was in 2011, or where blockchain was in 2009. Which is to say, it’s destined for great things and this is a really good time to get into it.
Elsewhere I've described CSHW as:
Selen Atasoy’s Connectome-Specific Harmonic Waves (CSHW) is a new method for interpreting neuroimaging which (unlike conventional approaches) may plausibly measure things directly relevant to phenomenology. Essentially, it’s a method... (read 5551 more words →)
Dark Energy seems pre-paradigmatic; it does appear we need some way to account for the blueshift of distant galaxies, but I'm hesitant to enshrine it as a 'type of stuff' and by implication the largest item on our ledger of future potential resources.
I'm a big fan of this sort of exploration about "what are the details of our cosmic endowment." Thanks for posting.