Neural Annealing: Toward a Neural Theory of Everything (crosspost)

https://www.lesswrong.com/posts/zcYJBTGYtcftxefz9/neural-annealing-toward-a-neural-theory-of-everything

The following is QRI’s unified theory of music, meditation, psychedelics, depression, trauma, and emotional processing. Implications for how the brain implements Bayesian updating, and future directions for neuroscience. Crossposted from http://​​opentheory.net ----------------- Context: follow-up to The Neuroscience of Meditation and A Future For Neuroscience; a unification of (1) the Entropic Brain & REBUS (Carhart-Harris et al. 2014; 2018; 2019), (2) the Free Energy Principle (Friston 2010), (3) Connectome-Specific Harmonic Waves (Atasoy et al. 2016; 2017), and (4) QRI’s Symmetry Theory of Valence (Johnson 2016; Gomez Emilsson 2017). 0. Introduction Why is neuroscience so hard? Part of the problem is that the brain is complicated. But we’ve also mostly been doing it wrong, trying to explain the brain using methods that couldn’t possibly generate insight about the things we care about. On QRI’s lineages page, we suggest there’s a distinction between ‘old’ and ‘new’ neuroscience: > Traditionally, neuroscience has been concerned with cataloguing the brain, e.g. collecting discrete observations about anatomy, observed cyclic patterns (EEG frequencies), and cell types and neurotransmitters, and trying to match these facts with functional stories. However, it’s increasingly clear that these sorts of neat stories about localized function are artifacts of the tools we’re using to look at the brain, not of the brain’s underlying computational structure.**> What’s the alternative? Instead of centering our exploration on the sorts of raw data our tools are able to gather, we can approach the brain as a self-organizing system, something which uses a few core principles to both build and regulate itself. As such, if we can reverse-engineer these core principles and use what tools we have to validate *these bottom-up models, we can both understand the internal logic of the brain’s algorithms — the how and why the brain does what it does — as well as find more elegant intervention points for altering it.*That’s a big check to try to cash. What might this look like? I. Annealing metaphors for the brain In my post about the neuroscience of meditation, I talked about simulated annealing, a natural implication of Robin Carhart-Harris’s work on entropic disintegration in the brain: *> Annealing involves heating a metal above its recrystallization temperature, keeping it there for long enough for the microstructure of the metal to reach equilibrium, then slowly cooling it down, letting new patterns crystallize. This releases the internal stresses of the material, and is often used to restore ductility (plasticity and toughness) on metals that have been ‘cold-worked’ and have become very hard and brittle— in a sense, annealing is a ‘reset switch’ which allows metals to go back to a more pristine, natural state after being bent or stressed. I suspect this is a useful metaphor for brains, in that they can become hard and brittle over time with a build-up of internal stresses, and these stresses can be released by periodically entering high-energy states where a more natural neural microstructure can reemerge.*In his work on the entropic brain, Carhart-Harris studies how psychedelics like LSD and psilocybin add enough energy (neural activity) to the brain that existing neural patterns are disrupted, much like how heating a metal disrupts its existing molecular bonds. Recently, Carhart-Harris and Friston have unified their frameworks under the REBUS (RElaxed Beliefs Under pSychedelics) model, which also imports the annealing metaphor for brains: *> The hypothesized flattening of the brain’s (variational free) energy landscape under psychedelics can be seen as analogous to the phenomenon of simulated annealing in computer science—which itself is analogous to annealing in metallurgy, whereby a system is heated (i.e., instantiated by increased neural excitability), such that it attains a state of heightened plasticity, in which the discovery of new energy minima (relatively stable places/​trajectories for the system to visit/​reside in for a period of time) is accelerated (Wang and Smith, 1998). Subsequently, as the drug is metabolized and the system cools, its dynamics begin to stabilize—and attractor basins begin to steepen again (Carhart-Harris et al., 2017). This process may result in the emergence of a new energy landscape with revised properties.*It’s a powerful metaphor since it ties together and recontextualizes so many core neuroscience concepts: free energy landscapes, Bayesian modeling, the ‘handshake’ between bottom-up sense-data and top-down priors. For a general overview of the math, see Wikipedia on simulated annealing, Metropolis-Hastings algorithm, Parallel tempering; for more on Carhart-Harris’s and Friston’s work, see Scott Alexander’s and Milan Griffes’ commentary. There seems to be some convergence on this metaphor: as Scott Alexander noted, > F&CH aren’t the first people to discuss this theory of psychedelics. It’s been in the air for a couple of years now – and props to local bloggers at the Qualia Research Institute and Mad.Science.Blog *for getting good explanations up before the parts had even all come together in journal articles. I’m especially interested in QRI’s theory that meditation has the same kind of annealing effect, which I think would explain a lot.*The basics: how does annealing work? Carhart-Harris’s and Friston’s model does many very clever things and is a substantial addition to the literature; I start from a similar frame but describe the process slightly differently. The following is QRI’s model (based on my talk on the Neuroscience of Meditation in Thailand):

Comment

https://www.lesswrong.com/posts/zcYJBTGYtcftxefz9/neural-annealing-toward-a-neural-theory-of-everything?commentId=f7Rx4vKPDKfsdEKhE

I think this post is 90% likely to make very little sense, but, ever since reading it I can’t get rid of the spark of doubt that maybe this post is saying something really important and valuable and all study of rationality that does not understand it is doomed from the start. I do think even without this post being anywhere close to right I got some useful things out of it, but by far the strongest reason for why I am nominating this post is because I want people to review it and engage with it critically.

https://www.lesswrong.com/posts/zcYJBTGYtcftxefz9/neural-annealing-toward-a-neural-theory-of-everything?commentId=Zxi7XKBm3vnNq4SMQ

I would like to see this post reviewed. (Jacob Falkovich, here’s looking at you.)