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You can see how the system is so coherent, it naturally derives , or let say realities aspects emerge from simple random numbers. This is very similar to constructing endless geometrical structures from the simple line segments combinations. Space and matter emerge naturally as in your theory! The theory is inherently non-local, EPR is very natural.

Moreover, there are no unnatural 12 fields on top of each other being scalar, spinor, vectors,vector bosons!, tensors........on and on. No virtual particles(exist, no don't exist just mathematical), and many other concepts that try to push an elephant into a needles's eye. I am not saying that the present models are wrong, they are just so twisted because of the historical developments.

Dear Torsten,

With great interest I read your essay, which of course is worthy of high rating. Excellently written.

Your work is related to my interests

«My current work is in direction of quantum gravity and cosmology. There, I used mathematical methods from topology to understand quantum gravity.»

«I had the feeling that the loop hypothesis is correct. I was thing that there is an interaction between neurons which can be not directly realized (so that it forms a loop).»

The cycles you already have, they are connected to your torus loops

«the two generators of non-contractable loops of the torus (or doughnut) as example.»

About how torus loops function from a physical point of view and how they form large loops by which they interact with each other at resonant frequencies, is shown in my essay.

I wish you success in the contest.

Kind regards,

Vladimir

Dear Torsten,

you propose an intriguing new way of looking at neural networks in terms of topologically stable structures---feedback loops. I'm not sure, however, I understand it fully. I would see an analogy to (topological) error correction here: the whole network, i.e. the detailed states (firing or not-firing) of all the neurons, yields the codespace, while only the topologically protected structures encode information; that way, the information is robust to small, random fluctuations within the network, i.e. noise. Is this somewhat close?

I'm not sure, then, what exactly you mean by the 'strength' and 'phase' of a signal. Are you referring to the signal carried by a given feedback loop? If so, is the strength related to the rate of firing, and the phase to the timing?

In the end, it's an interesting proposal, which however I feel could benefit from a more in-depth treatment (but of course, that's hard to do within the length constraints of this essay contest).

Hope you do well!

Cheers,

Jochen

    Dear Sirs!

    Physics of Descartes, which existed prior to the physics of Newton returned as the New Cartesian Physic and promises to be a theory of everything. To tell you this good news I use «spam».

    New Cartesian Physic based on the identity of space and matter. It showed that the formula of mass-energy equivalence comes from the pressure of the Universe, the flow of force which on the corpuscle is equal to the product of Planck's constant to the speed of light.

    New Cartesian Physic has great potential for understanding the world. To show it, I ventured to give "materialistic explanations of the paranormal and supernatural" is the title of my essay.

    Visit my essay, you will find there the New Cartesian Physic and make a short entry: "I believe that space is a matter" I will answer you in return. Can put me 1.

    Sincerely,

    Dizhechko Boris

    Dear Jochen,

    thanks for your words and for reading my essay.

    you are right that the whole approach is invariant for small fluctuations because of the topological structure. You are also right that strngth is the rate of firing and phase is the timing (I thought that I wrote at some place).

    In principle, I describe the topological structure of the space of neuron firing. Also this topologicval structure is robust w.r.t. fluctuations.

    Here is also where the structure change happens: for higher rates of firing and long time, this structure changes from a network (as picture of the brain network) into a tree.

    You are right I have to present more details but there was not room. Furthermore, the math is not so easy to present.

    So thanks again

    Best

    Torsten

    Dear Torsten,

    Your description of the dynamic loops reminded me of the dynamic theory of consciousness by T Fekete and S Edelman (e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4961712/). I like the approach. What always bothered me a bit is that there is no good examples of the consequences of their proposal. A good model often goes a long way and maybe your work could be a good starting point for that!

    All the best!

    Larissa

      Dear Torsten,

      I've found your essay very passionating. I'm also sure that complexity can emerge from a multitude of simple events playing few simple rules.

      Nevertheless in my essay I take into account also concepts like choice and freedom, that make the difference between an expert-system (that you can call mind) and a concious entity.

      I would appreciate that you would give me your opinion on my paper and give a score.

      Best wishes,

      Claudio B Borsello

        Dear Tejinder,

        thanks for your words and voting. I will certainly dig deeper in your theory.

        All the best and good luck for the contest

        Torsten

        PS: I'm of course eager to read your comments.

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        • Post #64

        Dear Larissa,

        thanks for your comment. Certainly I havt to look in this paper. Many thanks for the reference.

        Many thanks for your words. The model was the first trail during the course of writing the essay. So, the model is absolutely new and I had also not so much time to think about all consequences.

        All the best,

        Torsten

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