The Fractal Nature of Consciousness and Intuition by Torsten Asselmeyer-Maluga

Correction: So, it is basically a mechanism cortex-thalamus-cortex-thalamus. The cerebellum here may also include cerebellum, for extremely repetitive and fast processing.

The correct is

So, it is basically a mechanism cortex-thalamus-cortex-thalamus. The "brain" here may also include cerebellum, for extremely repetitive and fast processing.

Torsten,

Great essay! I discuss very much the same thing in my essay which is in line with MERA or tensor networks. There is a sort of analogue between quantum cosmology, or quantum bits in cosmology and general information networks. The universe is a network of causal sets. There is I think a switch between blue and green in the pictorial representation of contractible and noncontractible loops.

Cheers LC

This post was from me, but for some reason I was logged out. I boosted your score a bit!

LC

Dear Torsten,

I enjoyed reading your essay. I like how you applied the theory developed by Morgan and Shalen for 3-manifolds to neural networks and feedback loops, to explain learning and intuition. The essay was clear, self-contained, and well written. I think this approach may make interesting applications to the study of the processes taking place in the consciousness.

Best wishes,

Cristi Stoica

The Tablet of the Metalaw

Dear Torsten,

You deal with important issues; in particular, "The interaction between neurons given by the feedback loops controls the behavior of the neurons in the loop. In philosophy, one calls this behavior top-down causation: Top-down causation refers to the effects on components of organized systems that cannot be fully analyzed in terms of component-level behavior but instead requires reference to the higher-level system itself. This model serves as a simple example of this principle."

This is indeed a good example, which I appreciate. The concept is dealt with in more general contexts in my recent book How Can Physics Underlie the Mind?.

Regards

George Ellis

I will try to respond tomorrow. I got the flu a few weeks ago and now I have bronchitis that is sort of dragging me down. I do have a question concerning the Uhlenbeck, Freed, Donaldson type of result, but I will have to wait until tomorrow if I am better.

Cheers LC

Hi Torsten

Since I am not conversant with hyperbolic geometry and quantum physics, I cannot pretend to have understood all the fine details present in your modeling of the neural network, but I certainly found it to be intriguing, since my own essay was attempting a different type of modeling, that of the social system. What I found most interesting about your model was that the top-down flow of neural activity is more predictive of conscious awareness than the bottom-up flow of activity. You go on to state in the conclusion, "Top down causation refers to the effects on components of organized systems that cannot be fully analyzed in terms of component-level behavior but instead requires reference to the higher-level system itself".

Speaking purely from what I would expect to be the case for intelligent systems, (without much knowledge of the brain as an organ), I would expect such top down causation to be present if a system is to be considered as intelligent. And although I have not thought about it in precisely those terms in my essay, I think you might be able to recognize this top down behavior in it as well. I think you have written a great essay and I rate it accordingly.

Warm Regards, Willy

Hello Torsten..

I wanted to thank you for the comments left on my essay page, and to let you know I have begun to read and enjoy your essay. There is a lot to digest! I like the way you introduce the need for top-down interactions, to provide a faithful model of perception. I think both the universe and our awareness of it are participatory, even though much is automatic. I think learning about the non-automatic part is the key to understanding perception. Playing with ideas gives more insight than memorizing.

I appreciate the link to your paper with a no-go result for an n-qubit Spin-2 Hamiltonian simulation. This could be relevant to the matter of quantum computing via a BEC/BH event horizon analogy, I imagine. I apologize for the delay responding. I submerged myself to finish my first ever essay for the Gravity Research Foundation contest, but that is now sent in. Back to you soon, with more on your essay.

All the Best,

Jonathan

Torsten,

Remember you from the last contest.

I wonder if topology could shed light to the 1.8 billion light-years across supervoid, seemingly an anomaly scientists have discovered, something I reference in my essay.

Neural network models are a quite intriguing addition to neural studies. I would think that a qualitative approach for the brain is especially effective considering the multitudinous neural pathways of the brain.

Mindless rules will generate mind! Clever.

Hope you get a chance to comment on mine.

Jim Hoover

This is excellent work Torsten!

I have a quibble, that in human brain learning studies it was found that the naive view holding that similarities of structure between table result in similar memory encoding is untrue, but it was found that memory images were grouped by function instead. So there are several places a coffee cup appears represented in the brain, depending on whether it is empty or full, clean or dirty, and so on. It's usage determines how it is stored. So we might find table and couch represented in the same brain areas.

But this is in keeping with your observation of the importance of top-down influences, because to a living being in the real world objects are meant to be used or to have uses - which affects how we conceive of it. The old Chinese proverb is that the value of an urn is the space it contains. But this is an object fashioned by humans because it can fulfill a particular purpose. It is interesting though, that this purpose orientation is a driver of neurological specialization.

It was worth taking the time needed to digest the Maths, so I could get a better perspective of your intended meaning. But more digestion is required; you have given me a lot of food for thought, between your essay and comments, so I'll likely have some questions or a few comments of my own. An excellent read overall, and I hope you do well in the contest.

All the Best,

Jonathan

Gee whiz...

That was meant to be 'a chair and a couch.'

Best, JJD

I wanted to cycle back and say more..

First; I love the notion that consciousness is a fractal, and the fact it is the end result of your test process is very cool. It appears that the definition arises solely by imposing topological conditions and mapping the resulting parameter space; is this correct?

I've become fond of the idea that fractals are a way for nature to squeeze in more information than would otherwise fit in the constraints of certain geometrical or topological parameters. The folding of space at the boundaries provides an extensive working surface, and the self-similarity assures a consistent rule will emerge for entities exploring that parameter space. So it is, I guess, natural that emergent consciousness would be characterized by fractality. I will continue to ponder what you have written.

I hope that, at some point, we can expand our conversation beyond the contest topic. My current research carries me into areas where your expertise would be very helpful. The Mandelbrot Set suggests a geometrical route to unifying gravity with the rest of Physics. At (-0.75, 0i); the 5-d black hole --> 4-d spacetime scenario proposed by Pourhasan, Afshordi, and Mann is realized (if embedding M in the octonions is assumed), because Cartan's rolling-ball analogy of G2 symmetries is precisely modeled. And so is the set-up for DGP gravity!

Further down; the Misiurewicz point near (-1.543689, 0i) is an exact model for the quantum critical point of BEC formation, where an analogy can be made with Schwarzschild event horizons. This connection was first suggested by Sakharov, but has been extensively treated in recent papers by Dvali and colleagues. As you know, this has deep connections with topology, exploring degrees of freedom, and so on. But there is much work to be done, to carry this to fruition.

More later,

Jonathan

I was pleased to see I'd boosted your score to par with mine..

But now I see someone has knocked it back down again. This essay deserves to be in the finals, so that it will receive a review by someone intelligent enough to rate its quality fairly. Again I wish you luck Torsten.

Regards,

Jonathan

Hi Torsten

Since you haven't yet reviewed, I thought I'll sneak in a comment here. You are probably familiar with Conant's Good Regulator Theorem, since it explicitly deals with brains as an example. I would greatly value your feedback on whether it is applicable to my work.

http://pespmc1.vub.ac.be/books/Conant_Ashby.pdf

At present my understanding is that it is applicable. My interpretation of Conant, in the domain of brains, would be that it is the regulational part of the brain that is a model of the brain's basic perturbations. This is a slightly different emphasis from Conant, since in his work he suggested that the entire brain 'must' model its environment.

On modeling the external world, the brain may not be a perfect at it, but if enough focus is given to a certain area of the external world, the brain could eventually be trained to model that part of the external world very well. Please let me know what you think.

Warm Regards, Willy