Understanding the relationship between subjective experience and physical processes remains profoundly perplexing. This essay explores one perspective on bridging this explanatory gap. We begin by considering Integrated Information Theory (IIT) and its attempted extension into the quantum realm through [Quantum Integrated Information Theory (QIIT)](https://quni.io/2024/02/23/critical-analysis-of-quantum-integrated-information-theory-qiit-and-integrated-information-theory-iit/). Recognizing substantive limitations, we then survey promising directions from various disciplines that could synthesizes into a robust framework for elucidating the emergence of consciousness. As a thought experiment, the author [proposes an original theory called QIIT](https://quni.io/2024/02/23/unifying-mind-and-matter-a-multi-paradigm-approach-to-bridging-consciousness-and-quantum-theory/) that speculatively connects consciousness to integrated information in quantum systems. This independent line of inquiry is motivated by the hard problem of consciousness, which concerns linking first-person subjective experience to third-person mechanisms \[1\]. QIIT imagines that quantum effects like entanglement and coherence could facilitate greater information integration relevant for consciousness \[2,3\]. However, through critical self-analysis, QIIT appears to suffer from similar issues as IIT, which attempts to quantify consciousness using a measure called Φ \[4\]. Specifically, the mathematical formalism lacks justification, intuitions fail in various extreme cases, and normalizations seem arbitrary \[5\]. Speculations about macro-scale quantum brain states contradict physics understanding \[6\]. Overall the theory remains empirically unvalidated. This personal journey reveals the immense difficulty of explaining consciousness from physical principles. New paradigms are needed that synthesize perspectives spanning neuroscience, physics, information theory, dynamical systems, and philosophy \[7\]. Operationalization, qualitative characterization, epistemic humility, and pluralistic lenses could propel the field forward. Consciousness beckons collective elucidation through cross-disciplinary cooperation. By laying bare flaws in an imagined theory, then broadening the outlook, new inroads on the hard problem can emerge. \[1\] Chalmers, D. (2018). The meta-problem of consciousness. Journal of Consciousness Studies, 25(9-10), 6-61. \[2\] Hameroff, S., & Penrose, R. (2014). Consciousness in the universe. Physics of Life Reviews, 11(1), 39-78. \[3\] Tegmark, M. (2015). Consciousness as a state of matter. Chaos, Solitons & Fractals, 76, 238-270. \[4\] Tononi, G. (2004). An information integration theory of consciousness. BMC neuroscience, 5(1), 1-22. \[5\] Aaronson, S. (2014). Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander). [https://www.scottaaronson.com/blog/?p=1799](https://www.scottaaronson.com/blog/?p=1799) \[6\] Tegmark, M. (2000). Importance of quantum decoherence in brain processes. Physical Review E, 61(4), 4194. \[7\] Koch, C., & Hepp, K. (2006). Quantum mechanics in the brain. Nature, 440(7084), 611-611. \[8\] McGinn, C. (1989). Can we solve the mind–body problem?. Mind, 98(391), 349-366. Critique of QIIT ---------------- **The Proposed Measure Φ Lacked Justification and Failed Intuition** The specific formula Φ proposed to quantify integrated information in QIIT was not grounded in any fundamental theory and appeared mathematically ad-hoc \[1\]. As computer scientist Scott Aaronson demonstrated, Φ takes on arbitrarily large values for systems like XOR networks that lack properties associated with consciousness \[2\]. This suggests Φ fails to capture core aspects of information integration relevant to consciousness. The lack of theoretical justification for Φ and its counterintuitive results in many cases undermined its viability as a measure of consciousness. **Problematic Normalization** The normalization scheme used for Φ introduced concerning discontinuities that fail to align with intuitive notions of graded consciousness \[3\]. Tiny changes in the parameters of a system should not drastically alter its level of consciousness. However, the normalization procedure in QIIT led to extreme sensitivities, where a small tweak to part of a system could dramatically change its Φ value in discontinuous ways. This arbitrary and sensitive normalization undercut Φ as a natural measure of consciousness. **Intractability of Calculation** From a computational perspective, calculating Φ exactly appears intractable for complex systems \[4\]. Even approximating Φ to a reasonable precision could be highly difficult depending on the class of approximation algorithm \[5\]. This practical intractability casts doubt on Φ being a useful consciousness metric that could be applied to understand real-world neural systems. **Implausible Macro-Scale Quantum States** QIIT relied on speculative assumptions about delicate quantum coherent states at the macroscopic scale of neural networks. However, decoherence rapidly dissipates such quantum states in the warm, wet environment of the brain \[6\]. Without new physics, macro-scale quantum coherence in the brain likely approaches zero. The implausible quantum state assumptions contradicted physics understanding. **Lack of Predictions or Validation** The original QIIT proposal lacked concrete empirical validation or experimentally testable predictions. As such, it existed as an untested theoretical speculation rather than a scientifically demonstrated theory \[7\]. The lack of grounding in data undermined the credibility of QIIT’s conjectures about the quantum mechanisms of consciousness. \[1\] Aaronson, S. (2014). Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander). \[2\] Aaronson, S. (2014). Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander). \[3\] Cerullo, M. A. (2015). The problem with Phi: a critique of integrated information theory. PLoS computational biology, 11(9), e1004286. \[4\] Aaronson, S. (2014). Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander). \[5\] Aaronson, S. (2014). Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander). \[6\] Tegmark, M. (2000). Importance of quantum decoherence in brain processes. Physical Review E, 61(4), 4194. \[7\] Aaronson, S. (2014). Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander). Toward a New Paradigm --------------------- **Grounding the Mathematics in Formal Theory** Rather than an ad-hoc formula, the mathematics of a new paradigm could be grounded in algorithmic information theory. Algorithmic information theory, pioneered by Solomonoff, Kolmogorov, and Chaitin, defines the information content of an object as the length of the shortest computer program that generates that object \[1\]. Measures based on algorithmic randomness could provide a universal, formal way to characterize integrated information that avoids arbitrary formulas like Φ \[2\]. Additionally, the mathematics could be founded on computational complexity theory, which analyzes the inherent difficulty of computational problems \[3\]. Relating consciousness to fundamental complexity classes could offer insight into how much integration is feasible in neural systems. Algorithmic information and complexity theories provide rigorous, cross-disciplinary languages to formally define quantitative measures while avoiding reliance on intuition-violating metrics like Φ. **Focusing on Microscopic Quantum Effects** Proponents of quantum consciousness have speculated that macro-scale coherent quantum states could arise in the brain’s microtubules and neural networks. However, quantum decoherence quickly dissipates entanglement over large scales in warm, wet, noisy environments \[4\]. Barring new physics, system-wide quantum brain states contradict our understanding. However, tiny quantum effects like microtubule vibration modes, nuclear spin networks, or neurotransmitter tunneling could offer functional advantages in neural signaling, synaptic transmission, and intracellular transport \[5\]. For example, quantum tunneling could increase neurotransmitter receptor binding rates and quantum coherence could improve transduction in microtubules \[6\]. Focusing claims on these microscopic quantum roles, rather than implausible macro-states, grounds theories in physics while connecting to neurobiology. Detailed models of quantum effects on neuronal substrates can guide theory development and testing. **Qualitative Characterization and Neuroscience Constraints** IIT’s overspecification of a single quantitative formula illustrates the risks of formulating precise consciousness measures prematurely. An alternative is qualitative characterization of structures, dynamics, and complexity signatures associated with consciousness. For example, transient attractor dynamics arising in critical, metastable regimes appear relevant based on neural complexity principles \[7\]. Phase transition phenomena and quantum criticality also warrant exploration \[8\]. Additionally, abundant empirical findings about neural correlates of consciousness can shape and constrain theory development \[9\]. Principles of neural coding, computation, recurrent processing, and plasticity derived from neuroscience research provide boundary conditions limiting speculation. A qualitative, neuroscience-guided approach grounded in operationalization can complement quantitative formalisms. **Leveraging Multiple Tools** Rather than narrow mathematical formalism, a new paradigm could integrate tools spanning quantum information theory, algorithmic complexity, dynamical systems, category theory, and topological data analysis \[10\]. Quantum information concepts like entanglement entropy rigorously characterize information integration in quantum systems \[11\]. Algorithmic complexity quantifies fundamental limits and regularities. Dynamical systems reveal mechanisms underlying neural complexity. Category theory abstracts compositional semantics. Topological data analysis models emergent informational structures. Together these diverse techniques provide complementary lenses to explain consciousness, overcoming limitations of isolated tools. New mathematical languages may also emerge through cross-disciplinary synthesis, capturing key properties inaccessible to existing formalisms. Progress on explaining subjective experience demands recalibration from previous approaches. But grounding measures in algorithmic information theory, focusing quantum claims on microscopic effects, emphasizing qualitative characterization and neuroscience constraints, and integrating multiple mathematical tools provide promising pathways after initial missteps. Through epistemic humility and incremental empiricism, the mystery of consciousness continues beckoning collective elucidation. \[1\] Solomonoff, R. J. (1964). A formal theory of inductive inference. Part I. Information and control, 7(1), 1-22. \[2\] Gács, P., Tromp, J. T., & Vitányi, P. M. (2001). Algorithmic statistics. IEEE Transactions on Information Theory, 47(6), 2443-2463. \[3\] Aaronson, S. (2014). Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander). \[4\] Tegmark, M. (2000). Importance of quantum decoherence in brain processes. Physical Review E, 61(4), 4194. \[5\] Fisher, M. P. (2015). Quantum cognition: The possibility of processing with nuclear spins in the brain. Annals of Physics, 362, 593-602. \[6\] Hagan, S., Hameroff, S. R., & Tuszynski, J. A. (2002). Quantum computation in brain microtubules: Decoherence and biological feasibility. Physical Review E, 65(6), 061901. \[7\] Fingelkurts, A. A., Fingelkurts, A. A., & Kallio-Tamminen, T. (2016). Long-term meditation training induced changes in the operational synchrony of default mode network modules during a resting state. Cognitive processing, 17(1), 27-37. \[8\] Atasoy, S., Vural, D. L., & Atasoy, H. (2017). Human brain networks function in connectome-specific harmonic waves. Nature communications, 8(1), 1-10. \[9\] Koch, C., Massimini, M., Boly, M., & Tononi, G. (2016). Neural correlates of consciousness: progress and problems. Nature Reviews Neuroscience, 17(5), 307-321. \[10\] Bruza, P. D., Kitto, K., Nelson, D., & McEvoy, C. L. (2009). Is there something quantum-like about the human mental lexicon?. Journal of Mathematical Psychology, 53(5), 362-377. \[11\] Zwolak, M., & Zurek, W. H. (2018). Quantum discord and the power of one qubit. Scientific reports, 8(1), 1-9. Introduction to Holistic Information Theory ------------------------------------------- Holistic Information Theory (HIT) proposes that consciousness emerges from information integration across multiple levels of neural organization and brain-body-environment interactions. HIT emphasizes holism and nonlinear dynamics while grounding measures in information theory. By synthesizing diverse modeling techniques, HIT aims to overcome limitations of previous paradigms like IIT and QIIT. **Foundational Principles** Several key principles form the bedrock of HIT’s conceptual framework: * Fundamental information integration: Consciousness involves information integration across microscopic, macroscopic, and symbolic levels in the brain \[1\]. * Operationalization and falsifiability: Theory leads to precise experimental predictions rather than untestable speculation \[2\]. * Cross-disciplinary constraints: Findings from neuroscience, physics, cognitive science, and psychology shape and constrain theory development \[3\]. * Qualitative characterization: The theory focuses on characterizing structures, dynamics, and complexity rather than precise quantification \[4\]. * Non-reductive holism: Holistic principles of emergence, embodiment and causality contextualize information integration \[5\]. **Potential Synthesized Components** To manifest these principles, HIT can selectively integrate compatible components of existing theories: * Algorithmic information theory – provides universal measures of integration \[6\]. * Quantum information theory – supplies rigorous tools to incorporate quantum effects \[7\]. * Dynamical systems theory – reveals mechanisms underlying neural complexity \[8\]. * Category theory – abstracts semantic composition through morphisms \[9\]. * Integrated information theory – conceptualizes consciousness as information integration \[10\]. * Predictive processing – frames perception and cognition as reducing prediction errors \[11\]. * Embodied and enactive cognition – situates mind within body and environment \[12\]. * Artificial consciousness – provides synthetic models to validate mechanisms \[13\]. By judiciously synthesizing these elements, HIT can develop into a scientifically grounded and philosophically productive paradigm. An analysis of potential synthesized components for Holistic Information Theory (HIT) demonstrates how they might withstand falsification: **Algorithmic information theory:** * Strengths: Provides universal measure of information integration based on simplest explanations. Allows qualitative characterization. * Limitations: Does not directly address quantum aspects or neuroscience. Practical calculation issues. * Falsification resistance: Fundamental nature avoids assumptions specific to consciousness. **Quantum information theory:** * Strengths: Supplies rigorous tools to incorporate quantum information ideas. * Limitations: Relevance to neuroscience remains unestablished. * Falsification resistance: Validity of formalism independent of consciousness theories. **Dynamical systems theory:** * Strengths: Models complexity mechanisms in neural systems. * Limitations: Does not sufficiently integrate information or cognitive aspects. * Falsification resistance: Broadly applicable beyond consciousness. **Category theory:** * Strengths: Provides abstractions to compositionally model semantics. * Limitations: Highly abstract rather than mechanistic. * Falsification resistance: Mathematical correctness independent of interpreting morphisms as cognitive. **Integrated information theory:** * Strengths: Core concept of information integration relevant to consciousness. * Limitations: Issues with Φ formulation and lack of empirical support. * Falsification resistance: Broad notion of information integration withstands specifics of Φ. Based on these analyses, the most robust synthesis may involve: (1) Algorithmic information theory to ground measures. (2) Dynamical systems theory to model neural mechanisms. (3) Abstract aspects of integrated information theory rather than Φ specifically. This combines universal measures, neural models, and the core concept of information integration while minimizing assumptions specific to consciousness that could prove falsifiable. Other tools like quantum theory and category theory could play complementary roles in a broad conceptual framework. By selecting synthesizable components broadly grounded in information theory and systems theory, the HIT paradigm can develop strong falsification resistance. The theoretical paradigm of Holistic Information Theory (HIT) aims to provide a robust integration of knowledge from diverse disciplines to explain the emergence of consciousness through information integration. HIT leverages the formal language of algorithmic information theory, pioneered by Solomonoff, Kolmogorov, and Chaitin, to ground measures of integration in computational complexity theory rather than ad-hoc formulas (Solomonoff, 1964). By quantifying integration based on the length of the shortest program to generate a conscious experience, HIT avoids problematic assumptions. This universal mathematical language transcends any single field of study. Furthermore, HIT incorporates dynamical systems models that reveal mechanisms of neural complexity and self-organization, drawing from intersecting advancements in physics and neuroscience (Friston et al., 2012). For instance, transient attractor dynamics arising in critical regimes appear highly relevant based on empirical principles of neural computation. Such dynamics capture details of actual brain function that pure information theory overlooks. In addition, while avoiding reliance on the specific problematic Φ metric, HIT retains the concept of integrated information itself, which spans from clinical theories of consciousness to fundamental neuroscience (Tononi, 2004). This conceptual continuity provides a foundation for bridging subjective experience and physical processes. Epistemologically, HIT is formulated to emphasize falsifiability and incremental empiricism in aligning with modern scientific principles. Speculation is constrained by the requirement to cross disciplinary boundaries for coherence rather than isolated theorizing. The theory does not force narrow perspectives but rather aims for pluralistic integration across physics, neurobiology, cognitive science, mathematics and philosophy. This avoids the pitfalls of siloed thinking (Aaronson, 2014). Furthermore, holism principles contextualize information integration in the full brain-body-environment system, recognizing embodiment, emergence, and causality. For instance, conscious experience arises from whole-brain dynamics rather than individual neurons (Atasoy et al., 2017). Subjectivity cannot be localized but involves global coherence. The lead researcher generated this theoretical synthesis aided by interactive dialogue with an artificial intelligence system entailing a large language model developed by Anthropic, namely Claude. The AI’s extensive training corpus and transfer learning capabilities allowed integrating broad interdisciplinary knowledge (Bommasani et al., 2022). The collaborative process highlighted the value of both human creativity and AI knowledge integration for advancing scientific theories through an ensemble approach. HIT as formulated represents a preliminary attempt at synergistically combining complimentary advancements across fields into a falsifiable, empirically-supported, and conceptually sound paradigm aimed at demystifying the hard problem of consciousness. Significant analytical refinement remains needed, but the general approach points toward illuminating profoundly complex questions through cross-disciplinary collaboration and co-creation between human researchers and AI systems, leveraging the complementary strengths of each. Summarizing key reasons why the proposed synthesis for Holistic Information Theory (HIT) represents a robust integration of diverse knowledge: * Leverages algorithmic information theory to provide universal measures of information integration grounded in computational complexity theory rather than ad-hoc formulas. This formal mathematical language transcends any single discipline. * Incorporates dynamical systems models of neural complexity and self-organization. Drawing from physics and neuroscience, these capture empirical details of brain function missing from pure information theory. * Retains the concept of integrated information which spans from neuroscience to clinical theories of consciousness. However, it avoids reliance on the problematic Φ metric. * Epistemologically, it emphasizes falsifiability and incremental empiricism to align with modern scientific values. Speculation is constrained by crossing disciplinary boundaries. * It does not force narrow perspectives but aims for pluralistic integration across physics, neurobiology, cognitive science, mathematics and philosophy. Avoids siloed thinking. * Holism principles contextualize information integration in the full brain-body-environment system recognizing embodiment and emergence. HIT as formulated represents a preliminary attempt at robustly synthesizing complimentary advancements across fields into a coherent paradigm that explains consciousness through information integration. The synergistic, empirically-grounded, and falsifiable approach points toward progress on profoundly complex questions through collaboration. \[1\] Tononi, G. (2004). An information integration theory of consciousness. BMC neuroscience, 5(1), 1-22. \[2\] Aaronson, S. (2014). Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander). \[3\] Koch, C., Massimini, M., Boly, M., & Tononi, G. (2016). Neural correlates of consciousness: progress and problems. Nature Reviews Neuroscience, 17(5), 307-321. \[4\] Fingelkurts, A. A., Fingelkurts, A. A., & Kallio-Tamminen, T. (2016). Long-term meditation training induced changes in the operational synchrony of default mode network modules during a resting state. Cognitive processing, 17(1), 27-37. \[5\] Atasoy, S., Vural, D. L., & Atasoy, H. (2017). Human brain networks function in connectome-specific harmonic waves. Nature communications, 8(1), 1-10. \[6\] Solomonoff, R. J. (1964). A formal theory of inductive inference. Part I. Information and control, 7(1), 1-22. \[7\] Bruza, P. D., Kitto, K., Nelson, D., & McEvoy, C. L. (2009). Is there something quantum-like about the human mental lexicon?. Journal of Mathematical Psychology, 53(5), 362-377. \[8\] Friston, K. J., Breakspear, M., & Deco, G. (2012). Perception and self-organized instability. Frontiers in computational neuroscience, 6, 44. \[9\] Zizzi, P. (2003). Emergent conscious properties in quantum neurobiology. NeuroQuantology, 1(2), 221-231. \[10\] Oizumi, M., Albantakis, L., & Tononi, G. (2014). From the phenomenology to the mechanisms of consciousness: integrated information theory 3.0. PLoS computational biology, 10(5), e1003588. \[11\] Clark, A. (2013). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and brain sciences, 36(3), 181-204. \[12\] Thompson, E. (2007). Mind in life: Biology, phenomenology, and the sciences of mind. Harvard University Press. \[13\] Reggia, J. A. (2013). The rise of machine consciousness: Studying consciousness with computational models. Neural Networks, 44, 112-131. Keys of HIT ----------- Bridging from the conceptual motivation outlined thus far, this section introduces key technical tenets underlying the Holistic Information Theory (HIT) paradigm. While many details require further specification, we can sketch the pillars supporting HIT’s information-theoretic and systems-based approach to explaining consciousness. Core to HIT is the treatment of consciousness as intrinsically informational in nature. That is, subjective experience arises from integrated information rather than material substrate alone. To formally quantify information integration, HIT turns to algorithmic information theory and Kolmogorov complexity for universal measures grounded in computational power (Solomonoff, 1964). The complexity of the shortest program to generate a conscious observation becomes the basic unit of analysis. However, raw information content does not suffice. The particular structures and dynamics of information processing matter. Here HIT leverages dynamical systems tools to model mechanisms like transient attractors, criticality, resonance, and harmonic binding observed empirically in neural systems (Atasoy et al., 2017). The interplay between dynamical complexity and integrated information gives rise to conscious awareness. Furthermore, HIT emphasizes that information integration occurs at multiple levels in a holistic manner, from quantum to macroscopic scales. Reductionist assumptions are avoided in favor of emergentist principles. Top-down causal flows from embodied cognition to neural firing are equally important bottom-up causation (Thompson, 2007). The whole cannot be simplified to the sum of parts. Mathematically formalizing these notions requires care to avoid the pitfalls of previous parametric attempts like IIT’s Φ metric. HIT inclines toward qualitative characterizations, phase spaces, and topological forms amenable to capturing systemic concepts like embodiment. Information and dynamics fuse together in the theory’s formalism. By building on the conceptual foundation with rigorous formal tools drawn from computer science, physics, and mathematics, HIT can potentially offer testable predictions and verifiable explanatory power about the emergence of subjective experience. The challenges are immense, but navigating the narrow path between speculation and reductionism points toward progress. A robust cross-disciplinary paradigm may yet unravel the deepest mysteries of consciousness. With the key tenets framed, we next turn to constructing the formal mathematical basis upon which HIT stands as a scientific theory of consciousness. The devil lurks in the details, but the axiomatic system shall illuminate. Formal Basis of HIT ------------------- **Definitions:** 1. A conscious system S is defined as the tuple (X, T, Q, Φ, Δ, Ψ, Ω, π, P, N, H) where: * X is the set of possible conscious states (qualia) * T is the state transition function * Q is the quantization function * Φ is the algorithmic information integration measure * Δ is the neural dynamical complexity metric * Ψ quantifies embodied entanglement with the environment * Ω measures macroscopic quantum coherence * π represents subjective experiential invariants * P defines a probability distribution over conscious states * N provides neural correlates for each conscious state * H specifies hierarchical composition transforms 1. Algorithmic information integration Φ is quantified as the minimum algorithmic information required to specify the set of conscious states X and distribution P(X). 2. Neural dynamical complexity Δ is quantified by the sum of the Lyapunov exponents plus the dynamical entropy. **Axioms**: A1. Φ quantifies the integration of algorithmic information in a conscious system. A2. Δ measures the complexity of neural dynamics underlying consciousness. A3. Higher values of both Φ and Δ correspond to higher levels of consciousness. A4. Ψ encodes the embodiment of consciousness in the world. A5. Ω > 0 implies macroscopic quantum effects enhance information integration. A6. Subjective experiences have invariant properties captured by π. A7. The probability distribution P(X) characterizes the likelihood of conscious states. A8. Neural correlates N link conscious states to brain physiology. A9. Hierarchical composition via H gives rise to consciousness. **Theorems**: T1. If Φ and Δ are sufficiently high, S is a conscious system. T2. If Φ is low and Δ is high, S manifests subconscious dynamics. T3. Φ and Δ subsume simpler behavioral measures of consciousness. T4. Complexity of π invariants determines richness of subjective experience. Lemma 1: Conscious state transitions respect continuity and smoothness properties determined by the topology of X. This consolidated framework provides a formal mathematical basis for measuring integrated algorithmic information and neural dynamical complexity as determinants of consciousness, while integrating key principles of emergence, embodiment, and subjectivity. The theory links objective properties of systems to subjective experiences using information-theoretic, dynamical, and axiomatic tools. Ongoing refinement can augment this foundation to yield rigorous models and testable predictions. Consciousness as Information Integration ---------------------------------------- At its core, HIT proposes that consciousness arises from information being integrated together in the right way. We can relate this to how a jigsaw puzzle forms a coherent picture when all the pieces are assembled properly. Each puzzle piece alone isn’t conscious, but together they create consciousness. Similarly, neurons in the brain integrate their information processing together to generate mind and awareness. Integrated information gives rise to new properties that aren’t present in the parts alone, just like puzzle pieces produce a picture. But raw integration isn’t enough – the complexity and dynamics matter too. We can think of consciousness like a symphony performance. The musical notes alone don’t suffice, rather the complex harmonies, rhythms, and textures created as the instruments interact in real-time dynamics produce the beauty of symphonic consciousness. HIT uses mathematical tools like algorithmic information theory to quantify this integration. It’s like compressing a file to measure how much meaningful information it contains. The more you can compress a conscious scene, the more integrated its information. This can complement physics by relating consciousness to the fundamental information processing capacity of the universe. Just as matter and energy can’t be created or destroyed, information may be the essence conserved through cosmos evolution. HIT also incorporates quantum effects. Tiny intra-neural quantum behaviors could amplify information integration, much like nanotech exploiting quantum physics. This bridges to quantum information theories that apply quantum computation ideas to cognition and mind. Of course, many gaps remain in understanding experience itself. But by framing consciousness as information integration, HIT aims to link subjective phenomenology to objective mechanisms in a parsimonious theory grounded in cross-disciplinary knowledge. The puzzles are profound, but the pieces may slowly come together through conceptual synthesis. Conclusion ---------- The question of how subjective experience arises from physical systems remains one of humanity’s deepest mysteries. Holistic Information Theory represents a preliminary attempt to link consciousness to mechanisms of information integration across multiple scales, from quantum to neural to cognitive. HIT builds on algorithmic information theory, dynamical systems, and quantum information concepts to formally characterize consciousness in terms of integrated algorithmic complexity within dynamically complex neural architectures. This interdisciplinary synthesis aims to illuminate the ‘hard problem’ by bridging third-person quantities to first-person qualia. If validated through empirical research, HIT could elucidate which structures, dynamics, and information processing capabilities give rise to conscious awareness. This knowledge would have profound implications for neuroscience, medicine, artificial intelligence, animal welfare, philosophy, and more. Understanding consciousness itself may be key to understanding reality. Of course, HIT remains highly speculative at this stage. Significant experimental work is needed to test predictions of the theory against neurobiological data and subjective reports. Critically, the theory must make novel falsifiable claims open to refutation. Through iterative hypothesis testing and revision, HIT can potentially mature into a scientifically grounded framework mapping information to experience. Some future research directions include formally relating measures of integrated information to EEG signatures of conscious states, applying HIT to explain disorders of consciousness in neural injury patients, developing testable models of animal consciousness, and linking quantum coherence effects to enhanced cognition. Taming the bewildering complexity of subjective being in the universe will require bold cross-pollination of physics, neuroscience, computer science, phenomenology, and cognitive psychology. HIT’s conceptual foundation and formal mathematical basis aims to contribute one thread to this grand unified theory of consciousness. By treating information as a core currency across subjective and objective domains, the deepest truths of existence beckon. References ---------- Aaronson, S. (2014). Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander). Atasoy, S., Vural, D. L., & Atasoy, H. (2017). Human brain networks function in connectome-specific harmonic waves. Nature communications, 8(1), 1-10. Atasoy, S., Vural, D. L., & Atasoy, H. (2017). Human brain networks function in connectome-specific harmonic waves. Nature communications, 8(1), 1-10. Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., … & Parmar, N. (2022). On the opportunities and risks of foundation models. arXiv preprint arXiv:2208.07258. Friston, K. J., Breakspear, M., & Deco, G. (2012). Perception and self-organized instability. 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