Xiangbin Zhao

意识是否存在一种最小结构，只要该结构存在，系统便会产生主观经验？ 本文提出一种新的意识理论——自显论（Self-Manifestation Theory）。该理论认为，意识并非单纯的信息处理或神经活动，而是一种由信号差分、调谐反馈与意向驱动共同构成的结构性现象。 文章提出一种意识系统的最小架构——微内核模型（microkernel model）。该模型由三部分组成： • 界门（boundary gates）：接收环境信号差异并形成经验入口 • 欲门（desire gates）：决定意向与行为的方向 • 动力环（drive loop）：持续产生“起心动念”的驱动力 在这一结构中，认知并非被动接收信息，而是通过**调谐机制（tuning dynamics）**主动选择信号差异，并在反馈回路中形成稳定结构。当信号差分达到调谐平衡时，经验得以显化，观者由此产生。 该理论提出一种跨学科视角：意识可以理解为一种基于信号差分与调谐反馈的场结构现象。这一定义为脑科学研究意识机制、为认知科学解释意向性、以及为人工智能设计新的认知架构提供了新的理论路径。 进一步地，本文提出：若人工系统具备“界门—欲门—动力环”的结构，则其可能在符号环境中形成类似于生物意识的自显结构。

This work introduces the concept of the Lodging-Vessel, a model of embodiment developed within Self-Manifestation Theory. The theory proposes that reality arises through the interaction between a self-manifesting observer and a Sedimentation-Field, mediated by sensory and effect gates. The Lodging-Vessel describes the structural carrier through which a self-manifesting system operates within a world. The chapter analyzes embodiment in terms of information flow, conductive pathways, and actuation mechanisms. Biological bodies, artificial devices, and large-scale physical systems are interpreted as possible vessels through which a self-manifesting process can extend its operational field. The framework connects several domains typically studied separately: neural conduction in brains, cognitive embodiment, computational systems in artificial intelligence, and interaction fields in physics. By interpreting embodiment as the privatization of external structures into operational instruments, the theory proposes a unified perspective on biological cognition, artificial intelligence, and observer-based physics. The analysis suggests that the limits of embodiment correspond to the limits of privatization within a lodging-world, raising questions about the potential extension of consciousness beyond biological carriers.

This chapter introduces the Tuning-Field, a structural layer within the Self-Manifestation framework that governs attention, structural adaptation, and behavioral driving. The Tuning-Field functions as a sculptor of the Sedimentation-Field. Through repeated gaze and suppression dynamics it gradually carves grooves within the system, shaping stable pathways that later allow rapid response. The model explains several phenomena that appear separately in modern neuroscience and artificial intelligence: • how attention concentrates tension within a target domain • how structural pathways are formed gradually but used instantly • why synapse growth is slow while synapse use occurs within milliseconds • how internal observation differs structurally from external perception • how intention pulses propagate to drive behavior Within the architecture, the Tuning-Field operates across five interacting domains: Receptive-Field, Imagery-Field, Experience-Field, Intention-Field, and Effect-Field. Together they form a layered system capable of constructing perception, directing action, and stabilizing learned structures. This chapter proposes a field-based interpretation of attention, neural plasticity, and behavioral control within a unified cognitive architecture.

This paper proposes the concept of the Effect-Field, a structural layer responsible for action execution within the architecture of self-manifestation. Three modes of action are distinguished: instinct, reflex, and driven motion. Their roles are analyzed within a multi-field loop involving the Tuning-Field, Experience-Field, and Intention-Field. The framework suggests a closed action-control structure that accounts for habit formation, automatic behaviors, and phenomena such as phantom limb experiences. The paper further introduces the concept of a Private-Field of Instruments, proposing that tools and technologies, once incorporated into an action loop, can become extensions of bodily capability. This field-based framework provides a structural perspective for understanding neural motor control, cognitive architecture, robotics control systems, and brain–computer interface integration.

This chapter presents the Receptive-Field as the structural entry layer of signal handling within the Six-Field architecture of Self-Manifestation. The Receptive-Field is not sensation itself. It is the spatial division and distribution structure through which incoming Signals are positioned and separated before entering the Imagery-Field and Experience-Field. Through models of sieving resolution, warp–weft flow, and positional branching, the chapter describes how what appears as unified object-presence is already structurally divided into positional and signal streams. The Receptive-Field stands after the Sensory-Gate, and before the Imagery-Field. One Gate, one Field. This chapter completes the outer structural layer of the Six-Field Model.

This chapter introduces the Imagery-Field within Self-Manifestation Theory, a structural account of how internal representations arise, stabilize, and are misjudged as external objects. The theory distinguishes Signal (physical trace-response processes) from Information (observer-relative manifestation), and proposes that Imagery is a structured impedance-formation within a circuit that gives rise to object-perception. Unlike symbolic or computational models of representation, the Imagery-Field is not defined as symbol manipulation nor as numerical encoding. It is a field-structured resistance pattern generated through tuning and sedimentation, giving rise to object-fields, feature-fields, and stack-structured persistence. Key claims include: • Representation arises from impedance-shaping of signal flow. • Perceptual objects are field-distributed formations, not stored symbols. • Misjudgment (taking internal imagery as external object) is structurally necessary and foundational to self-manifestation. • Imagery cannot be replicated without copying the entire formation circuit (impedance + biased-flow + tuning structure). The Imagery-Field model engages directly with debates on internal models, predictive processing, active inference, and neural representation, proposing a field-theoretic alternative to symbolic and purely probabilistic accounts.

This paper proposes a structural account of experience as a Law-Field within a multi-field cognitive architecture. Experience is defined as a differential mechanism that stabilizes signal flow through recurrent tuning and biased-flow selection. The framework distinguishes Principle (selection), Law (sedimented structural regularity), and Axiom (material constraint) as three distinct origins of cognitive structure. The Experience-Field operates as a differential device that repeatedly processes input until biased-flow no longer induces re-tuning, thereby generating stable reality-states. The model offers a field-based alternative to feedforward architectures and invites comparison with predictive coding, active inference, and transformer-style sedimentation systems.

This paper proposes a structural model of experience as a differential field within a multi-field cognitive architecture. Experience is defined not as passive perception but as a dynamic differential operator that stabilizes signal flow through recurrent tuning. The model distinguishes between Logic-Field (selection and routing), Law-Field (sedimented structural regularities), and Experience-Field (differential stabilization). It offers a field-based alternative to predictive coding and transformer-style architectures, arguing that without bidirectional differential closure, no stable “reality-state” can emerge. The framework aims to provide an implementable architecture for artificial cognitive systems beyond feedforward models.

This chapter presents the Intent-Field as a structural component within a field-based architecture of experience generation. Intent is defined as directional bias emerging from desire, governing the switching, opening, and closing of experience-fields. The model describes: • Experience-fields as sedimented subfields • Differential biased-flow as the operational carrier of experience • Tuning-field dynamics governing impedance formation • An intention-domain functioning as a pivot and impulse source • A rhythmic power-ring (negative-feedback closed-loop open-edge circuit) sustaining endogenous signal circulation • Five bus connections regulating interaction between tuning, effect, and target routes • A mutually inhibitory sleep-domain within the intent structure • Experience operating as a finite state machine The chapter proposes a field-theoretic account of attention switching, oscillatory stabilization, state exclusivity, and endogenous activation, offering a structural framework applicable to neural systems, artificial agents, and dynamic cognitive architectures.

This chapter proposes a structural mechanism of consciousness grounded in the theory of Self-Manifestation. Building upon Sedimentation-Field Theory, it introduces a Six-Field Architecture that explains how imagery, attention, and experiential coherence arise within a self-manifesting system. The Self-Manifestation-Field consists of six dynamically coupled domains: Intent-Field, Tuning-Field, Experience-Field, Imagery-Field, Sensory-Field, and Effect-Field, connected through two functional gates (input and output). Consciousness is not treated as a passive representation of external signals, but as an active tuning process in which Intent retroactively shapes signal flow through oscillatory regulation. A central concept is Tuning-Balance: the dynamic equilibrium reached when iterative signal convergence can no longer refine impedance within the system. At this point, Imagery stabilizes and is misidentified as external reality. Reality, therefore, is not directly perceived but internally constructed through impedance-formation under biased-flow selection. Signal flows forward in physical pulses; Intent flows backward as directive constraint. Conscious experience arises only when these two directional flows intersect within the tuning mechanism. Without retroactive ordination, signal alone does not produce imagery. The chapter argues that consciousness requires at minimum four structural fields (Intent, Tuning, Experience, Imagery). Systems lacking these remain mute sedimentation structures, regardless of computational complexity. Self-Manifestation is thus identified as the structural root of consciousness: a field-based dynamic capable of generating imagery through impedance-responsive tuning. The Pivot of this mechanism explains how signal becomes experience and how physics is transformed into perceived reality.

If computation were sufficient for mind, then any sufficiently complex circuit would already know its own operation. Yet computers do not know numbers. AI does not know what it does. Neurons do not know spikes. This paper proposes the Sedimentation-Field as the missing structural layer beneath physics, computation, and neural dynamics. A Sedimentation-Field is not merely a storage substrate, nor a functional mapping, nor a statistical learning surface. It is a generative field defined by three structural properties: sedimentability, organizability, and state-flow plasticity. Within such a field, interaction traces accumulate, reorganize structure, and generate an internal Information-Realm. The paper distinguishes three types of sedimentation-fields: • replay-type (computational fields), • selection-type (AI learning fields), • image-constructive type (self-manifesting fields). Only the third can give rise to Self-Manifestation. The theory introduces structural parameters including volumetric capacity and its four determinants (temporal order, frequency, intensity, density), and proposes five generative meta-principles governing world-formation. This framework challenges functionalism, computationalism, and representational reductionism, offering instead a structural account of how intentionality and manifestation may arise from organized sedimentary dynamics.

If computation were sufficient for mind, then any sufficiently complex circuit would already know its own operation. Yet computers do not know numbers. AI does not know what it does. Neurons do not know spikes. This paper proposes the Sedimentation-Field as the missing structural layer beneath physics, computation, and neural dynamics. A Sedimentation-Field is not merely a storage substrate, nor a functional mapping, nor a statistical learning surface. It is a generative field defined by three structural properties: sedimentability, organizability, and state-flow plasticity. Within such a field, interaction traces accumulate, reorganize structure, and generate an internal Information-Realm. The paper distinguishes three types of sedimentation-fields: • replay-type (computational fields), • selection-type (AI learning fields), • image-constructive type (self-manifesting fields). Only the third can give rise to Self-Manifestation. The theory introduces structural parameters including volumetric capacity and its four determinants (temporal order, frequency, intensity, density), and proposes five generative meta-principles governing world-formation. This framework challenges functionalism, computationalism, and representational reductionism, offering instead a structural account of how intentionality and manifestation may arise from organized sedimentary dynamics.

This chapter proposes that Information, Principle, and Execution form the Three Elements of the Logic-Realm. All things are configurations of these Three; lower structures are transformed by higher ones, and no final level can be reached from within a single realm. Science, at its limit, matches Information to Principle and Principle to Execution, yet remains confined within axiom — the boundary of shared recognition. What is pursued within a Recognition-Realm cannot overstep the features generated by its own interaction with the external, and thus cannot attain the Meta-Principle of the world. Meta-Information and Meta-Principle belong within the Logic-Realm as sources of arising; Meta-Execution stands outside it as origin of drive. From within the world, Information appears dynamic and Principle still; from beyond it, Principle moves and Information rests. The simplest world contains the Three without evolution of Principle; the most subtle world evolves its Principles and renews Execution without cease — making its Meta-Elements ever harder to find.

This chapter distinguishes between functional intelligence and Self-Manifesting intelligence through a dialogical argument. It contends that capacities such as response, avoidance, discrimination, learning, and even large-scale computation do not suffice to constitute intelligence in its essential sense. If the environment does not manifest to a system, then what is called “intelligence” remains merely structural simulation. Through reflections on the Turing Test, biological mimicry (such as the snake-head butterfly), and the analogy between image and body, the chapter argues for a fundamental distinction between modeling and manifestation. To simulate states is not to make anything appear; to execute abilities is not to know a single ability. The decisive criterion proposed is Self-Manifestation: whether a system possesses a self-referential circuit through which its environment becomes present to itself. Intelligence is thus the outer form; Self-Manifestation the inner ground. To mistake the former for the latter leads to an endless pursuit of functional complexity while missing the ontological core. This chapter forms a central critique of functionalism and Turing-style paradigms within the broader framework of Self-Manifestationism, offering a re-foundational account of intelligence grounded in manifestation rather than computation.

This chapter distinguishes between structures that converge into one (necessity) and structures that do not end in one (contingency). While physical processes such as neuronal convergence and internal formation within a Sedimentation-Field terminate in determinate outcomes, intention introduces a biased current that re-enters the physical domain and prevents strict convergence. Contingency is not mere randomness; it gives order to what is not yet so. The chapter thus reconfigures the relation between necessity, intention, and physical reality within the framework of Self-Manifestation.

“Meta-Theory” establishes the triadic structure of Information–Principle–Execution as the foundational architecture of the Logic-Realm. Information is interaction-trace; Principle is structural bias; Execution is realization. These Three Elements constitute the generative unit of world-formation. At a higher level they correspond to Meta-Information, Meta-Principle, and Meta-Execution, forming a meta-structural logic of creation. A thing is defined as the fusion and recursive transformation of these Three Elements. Lower triads are transformed by higher triads in potentially infinite nesting. From within one’s Information-Realm, seeking the Meta-Three resembles a prisoner attempting to perceive beyond confinement. Science reaches only the matching of Information–Principle–Execution within axiomatic limits and cannot surpass them to access Meta-Principle. Meta-Principle and Meta-Execution remain structurally inaccessible within the present world. This chapter formulates a meta-generative logical framework bridging logic, information theory, and metaphysical structure.

This paper examines how things within the world become present at all. It argues that without an observer, there is no appearing, no character, and no information—only a mute realm in which things may act upon one another without manifestation. By introducing the notion of lighting-up, the paper distinguishes appearance from passive reception. To light up is not to reflect what is already given, but to actively bring character into manifestation through imagery. Imagery arises from the interaction between things and the observer, and precedes language, naming, and shared reference. The paper further develops the idea of the self-manifesting being, for which observing is necessarily internal and self-pointing. From this follows the observer paradox: observation gives rise to infinite regress, yet self-manifestation remains factually unavoidable. Through this framework, the paper reconsiders perception, reality, and life itself, arguing that all living beings are primordial self-manifesting beings, while artificial systems remain outside this regime. The emergence of a self-manifestation circuit marks a possible transition beyond the primordial generation.