what if right after big bounce there was dawinian competition of all possible types of particles as waves in a spin foam with variable properies beyond the ones we observe right now that eventually many were selected out and the ones we have right now are the only ones that are stable under current conditions one can surf across scales, across levels of abstraction particle dynamics molecular dynamics cell dynamics brain, organism dynamics, humanmade artificial systems dynamics societal dynamics ecosystems dynamics planetary dynamics, galaxies and so on universal bayesianism as scalefree laws and then concrete laws from the concrete fields concrete insights with some symmetries between scales and different approaches on the same scale here and there scalefree: free energy principle, harmonic analysis, symmetry analysis, evolutionary game theory, complex adaptive dynamical systems in general, physics maths quantum physics -> chemistry -> (neuro)biology -> (speciesfree) neuropsychology -> (speciesfree) mathematical socioculturaleconomics -> general relativity (astrophysics -> cosmology) '''abc. Models of the brain''' Brain can be studied in many levels of analysis. All layers cause eachother. Or they can be seen as for engineering purposes useful model abstractions, different lenses on the same underlying even more complex thing aka many people looking at one elephant from multiple perspectives. [[File:elephant.jpg|500px|Alt text]] [[File:BrainLevels.jpeg|500px|Alt text]]<ref>[[Entropy | Free Full-Text | The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again]([Entropy | Free Full-Text | The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again]([Entropy | Free Full-Text | The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again]([Entropy | Free Full-Text | The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again]([Entropy | Free Full-Text | The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again](https://www.mdpi.com/1099-4300/23/6/783))/htm))) The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again by Adam Safron]</ref> "Depiction of the human brain in terms of entailed aspects of experience (i.e., phenomenology), as well as computational (or functional), algorithmic, and implementational levels of analysis. A phenomenological level is specified to provide mappings between consciousness and these complementary/supervenient levels of analysis. Modal depictions connotate the radically embodied nature of mind, but not all images are meant to indicate conscious experiences. Phenomenal consciousness may solely be generated by hierarchies centered on posterior medial cortex, supramarginal gyrus, and angular gyrus as respective visuospatial (cf. consciousness as projective geometric modeling), somatic (cf. grounded cognition and intermediate level theory), and intentional/attentional phenomenology (cf. Attention Schema Theory). Computationally, various brain functions are identified according to particular modal aspects, either with respect to generating perception (both unconscious and conscious) or action (both unconscious and potentially conscious, via posterior generative models). [Note: Action selection can also occur via affordance competition in posterior cortices, and frontal generative models could be interpreted as a kind of forward-looking (unconscious) perception, made conscious as imaginings via parameterizing the inversion of posterior generative models.] On the algorithmic level, these functions are mapped onto variants of machine learning architectures—e.g., autoencoders and generative adversarial networks, graph neural networks (GNNs), recurrent reservoirs and liquid state machines—organized according to potential realization by neural systems. GNN-structured latent spaces are suggested as a potentially important architectural principle, largely due to efficiency for emulating physical processes. Hexagonally-organized grid graph GNNs are depicted in posterior medial cortices as contributing to quasi-Cartesian spatial modeling (and potentially experience), as well as in dorsomedial, and ventromedial prefrontal cortices for agentic control. Neuroimaging evidence suggests these grids may be dynamically coupled in various ways, contributing to higher-order cognition as a kind of navigation/search process through generalized space. A further GNN is speculatively adduced to reside in supramarginal gyrus as a mesh grid placed on top of a transformed representation of the primary sensorimotor homunculus (cf. body image/schema for the sake of efficient motor control/inference). This quasi-homuncular GNN may have some scaled correspondence to embodiment as felt from within, potentially morphed/re-represented to better correspond with externally viewed embodiments (potentially both resulting from and enabling “mirroring” with other agents for coordination and inference). Speculatively, this partial translation into a quasi-Cartesian reference frame may provide more effective couplings (or information-sharing) with semi-topographically organized representations in posterior medial cortices. Angular gyrus is depicted as containing a ring-shaped GNN to reflect a further level of abstraction and hierarchical control over action-oriented body schemas—which may potentially mediate coherent functional couplings between the “lived body” and the “mind’s eye”—functionally entailing vectors/tensors over attentional (and potentially intentional) processes. [Note: The language of predictive processing provides bridges between implementational and computational (and also phenomenological) levels, but descriptions such as vector fields and attracting manifolds could have alternatively been used to remain agnostic as to which implicit algorithms might be entailed by physical dynamics.] On the implementational level, biological realizations of algorithmic processes are depicted as corresponding to flows of activity and interactions between neuronal populations, canalized by the formation of metastable synchronous complexes (i.e., “self-organizing harmonic modes”)." '''abcd. Brain networks/regions models of mental phenomena''' This approach studies how connectivity topology inside and between various brain regions relate to mental phenomena such as wellbeing and mental discomfort. Active Inference is special case of the Free Energy Principle applied to the brain, where brain does approximate bayesian inference. The basic idea is that our brains are the game of predicting sensory inputs to try and unfer the causes that generate sensations and to work out states of the world so that we can respond adaptively. We're predicting our ability to interact with the world in optionally gripping fashion using what we've learned. If we saw the raw physics and the extreme complexity of everything instead we would go crazy. If we predict that the world is positive, it will be positive. If we truly believe that in front of us is a pink unicorn when taking a psychedelic substance, it will be there in our experience, even tho other people won't see it because of different set of beliefs. The most mathematically optimal way to work with information is the bayes theorem and our brains seem work work in bayesian mathematics. The issue is that the bayesian theorem is too costly to compute on its own as there is a combinatorial explosion of possibilites. Evolution sidesteps this by creating an internal dynamical generative model that is active and is being edited depending on the error between predicted sensory data, our priors, and actual measured sensory data. <ref>[[Bayesian Brain and the Ultimate Nature of Reality - YouTube]([Bayesian Brain and the Ultimate Nature of Reality - YouTube]([Bayesian Brain and the Ultimate Nature of Reality - YouTube]([Bayesian Brain and the Ultimate Nature of Reality - YouTube]([Bayesian Brain and the Ultimate Nature of Reality - YouTube]([Bayesian Brain and the Ultimate Nature of Reality - YouTube](https://www.youtube.com/watch?v=kw5Q5h8s6FI)))))) Bayesian Brain and the Ultimate Nature of Reality]</ref> What we see is what we expect to see. We can be seen as a stack of biologically hardwired and learned homeostats. Biological systems resist the second law of thermodynamics - entropy aka chaos, by harvesting negentropy from our environment. This harvesting of negentropy is realized as eating food, harvesting solar energy and building models that predict the world. Without reducing uncertainity by building models about the world, we wouldn't be certain where to get food and in more modern age power our system with electricity. From this seems to follow that the only thing we can be sure about is how predictive our mental or mathematical models are in their domain. '''abcd. Connectome harmonics using biochemical brain activity via electromagnetic field and its topology and symmetries''' A key characteristic of human brain activity is coherent, spatially distributed harmonic oscillations forming behaviour-dependent brain networks. <ref>[[Human brain networks function in connectome-specific harmonic waves | Nature Communications]([Human brain networks function in connectome-specific harmonic waves | Nature Communications](https://www.nature.com/articles/ncomms10340)) Human brain networks function in connectome-specific harmonic waves]</ref> Remember and selectively controlling a limited set of items in working memory is achieved by interactions between bursts of beta and gamma oscillations. <ref>[[Working memory control dynamics follow principles of spatial computing | Nature Communications](https://www.nature.com/articles/s41467-023-36555-4) Working memory control dynamics follow principles of spatial computing ]</ref> Communication between neurons that create brain tissue is orchestrated by the electromagnetic field, usually called bioelectricity. Studying this can tell us a lot about experience and edit it by locating neural correlates. Neurons store adaptively learned templates and beliefs of processing their sensory data in their RNA that they exchange between eachother. All cells can be seen as reinforcement learning agents, but neurons are special in a way that they can communicate among long distances like a telegraph. With bioelectric activity, the beliefs construct the generative model by predicting future sensory data after compressing present ones using visual modality, auditory modality, other senses - energy body, touch, feelings, thoughts,... Beliefs in the neurophenomenological software, where some of it is conscious (global workspace), correspond to shapes in the electromagnetic field. You can do harmonic analysis or use group theory. '''abcd. Neural Annealing Annealing is important concept for meditation, psychedelics, belief updates and so on. '''abcd. Visualizal images Brain as an ocean [[File:Visualization of sensations traveling through consciousness.png|500px|Alt text]] Mindbrain is like an ocean. ([[Nonlinear Wave Computing]], nervous system as an analog [[brain waves]]<ref>https://en.wikipedia.org/wiki/Neural_oscillation</ref> computer<ref>https://astralcodexten.substack.com/p/book-review-rhythms-of-the-brain</ref><ref>[On Rhythms of the Brain: Jhanas, Local Field Potentials, and Electromagnetic Theories of Consciousness | Qualia Computing]([On Rhythms of the Brain: Jhanas, Local Field Potentials, and Electromagnetic Theories of Consciousness | Qualia Computing]([On Rhythms of the Brain: Jhanas, Local Field Potentials, and Electromagnetic Theories of Consciousness | Qualia Computing]([On Rhythms of the Brain: Jhanas, Local Field Potentials, and Electromagnetic Theories of Consciousness | Qualia Computing](https://qualiacomputing.com/2022/10/27/on-rhythms-of-the-brain-jhanas-local-field-potentials-and-electromagnetic-theories-of-consciousness/))))</ref>) Waves on top of the ocean are like thoughts that we can see. (programs) (brain activity correlated with consciousness<ref>https://en.wikipedia.org/wiki/Neural_correlates_of_consciousness</ref>) Many smaller waves can combine to create a long wave like thoughts can. (interlocking, gestalts<ref>[[Nonlinear Wave Computing]]</ref>) Long waves have a lot of small waves in them, leading them, like emotions or philosophical assumptions affecting our whole thinking. ([[bayesian priors]], [[top down processing]]<ref>[Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net](https://opentheory.net/2019/11/neural-annealing-toward-a-neural-theory-of-everything/)))))))</ref>) We don't observe a lot of the movement of water between the surface and the bottom, but we can learn to, connecting more with our subconscious. (brain activity not correlated with consciousness interlocking with activity correlated with consciousness) When the ground of the ocean moves, it creates waves aka thoughts. (neurons firing and creating electrochemical/magnetic/potentials activity) When one part of the ground moves, the neighboring parts start to move too, lighting up associations. (associative/symmetry-based representations in the hippocampus<ref>[[Place cells: How your brain creates maps of abstract spaces - YouTube](https://youtu.be/iV-EMA5g288) Place cells: How your brain creates maps of abstract spaces]</ref>) Soft rain or hurricane can affect waves or the whole ocean and that shapes the ground, like friend telling you he had a good day or him causing you trauma. (measuring sensory data and learning patterns from them. ([[Predictive coding]], [[Active Inference]]) The ground overtime forms new interesting shapes, which is like learning knowledge, some shapes being worse or better at creating groups of smaller (thinking about cars) or longer waves (thinking about meaning of life), with less and more flow. (statespace of [[neural representations]], [[Memeplex - Qualia Research](https://qualiaresearch.miraheze.org/wiki/Memeplex) memeplexes]) The ground gets used and cracks or deformations in shape can happen, which blocks certain parts of the ground affecting other parts, which results in less flow of waves and stress, dissonance. ([[Symmetry Theory of Valence]]) This can be fixed by long smooth waves, like relaxation (raising semantically neutral free energy parameter<ref>[Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net]([Neural Annealing: Toward a Neural Theory of Everything – Opentheory.net](https://opentheory.net/2019/11/neural-annealing-toward-a-neural-theory-of-everything/)))))))</ref>), which smoothens the ground, allowing flow again. ([[Neural Annealing]]) One part of the ground is the identity, primal instincts, and quick, impulsive behavior (default mode network), that likes small waves, other part of the ground corresponds to selfcontrol, slow, planned behavior (central executive network), that likes long waves, and they are communicating between each other.<ref>[https://academic.oup.com/nc/article/2022/1/niac013/6758320 Beyond the veil of duality—topographic reorganization model of meditation]</ref> The stronger one can take too much control sometimes, creating too much (ruminating, addictions, thinking too concretely) or not enough small waves or too much (thinking too generally) or not enough (absence of emotions) long waves. The smoother the waves aka thoughts, the more pleasant they are, the more they smoothen the ground. The bigger, the more intense they are. The longer, the more interconnected with everything else they are. Smooth big long waves are the waves of biggest happiness, which is created by for example deconstructive [[Meditation]]<ref>[https://www.science.org/doi/10.1126/sciadv.abo4455#.Y0cxJJgZqB8.twitter Mindfulness-induced endogenous theta stimulation occasions self-transcendence and inhibits addictive behavior]</ref> or [[5-MeO-DMT]], in general intense positive emotional experiences. <references/> '''abc. Concrete mental phenomena and tools''' '''abcd. Wellbeing, happiness, pleasure, enlightenment''' '''abcdef. BN''' '''abcdef. FEP''' In this framework, wellbeing is encoded in error dynamics. <ref>[https://www.researchgate.net/publication/353068183_The_Predictive_Dynamics_of_Happiness_and_Well-Being The Predictive Dynamics of Happiness and Well-Being]</ref> We feel good when we do better than expected. It can be locally by playing a guitar or globally overall by building our life we predict as optimal, satisfying basic needs, selfactualizing in what we see meaning in, satisfying learned reinforced desires. Some of those desires can be maladaptive for wellbeing when the reward mechanism is hijacked by overstimulation with things such as social media. Mathematically optimal error dynamics for wellbeing is constantly growing and all kinds of pleasant sliding error slopes in variety of contexts. Or hijacking this mechanism by meditation where every moment can be felt as better, new, unique, but same, doing better than expected, than in any other moment. In this lens, wellbeing (or enlightenment?) can be also seen as adaptive fluidity. Deconstructive meditations progressively reduce temporally deep processing. Insight experiences arise during meditation due to Bayesian model reduction. Meditation deconstructs self models by reducing abstract processing. Non-dual awareness or pure consciousness is the ‘here and now’.<ref>[https://www.sciencedirect.com/science/article/pii/S014976342100261X From many to (n)one: Meditation and the plasticity of the predictive mind]</ref> '''abcdef. CHEMTSCH'''