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Key Figures and Diagrams

An index of the theory's core visual representations, what each one shows, and where each appears across the wiki.

The Standard Model of Consciousness relies on a small set of recurring visual representations. Each diagram captures a different aspect of the framework -- architecture, ontology, dynamics, or comparison. This article catalogs all key figures, provides their Mermaid or image reference, and lists the articles where each appears.

1. The 2x2 Model Table

What it shows: The four model kinds arranged along two axes -- scope (world vs. self) on the horizontal and mode (implicit vs. explicit) on the vertical. Mode is an orthogonal contrast; scope is a nesting, since the self-model's content is part of the world-model's (ESM ⊆ EWM, ISM ⊆ IWM). The real side (IWM + ISM) occupies the top row; the virtual side (EWM + ESM) occupies the bottom row.

Why it matters: This is the theory's most fundamental diagram. The 2x2 layout demonstrates that the four models are not an arbitrary list but a principled minimum generated by two dimensions. The four are extremal points in a continuous space of overlapping models and mark functional distinctions, not brain regions: four is the floor, not the ceiling. Every other diagram in the theory builds on this structure.

Image source: figures/figure1-four-model-architecture.svg (color), figures/figure1-four-model-architecture-bw.svg (black and white)

quadrantChart
    title The Four Models
    x-axis "World (Everything)" --> "Self Only"
    y-axis "Explicit (Generated)" --> "Implicit (Learned)"
    quadrant-1 "ISM: Implicit Self Model"
    quadrant-2 "IWM: Implicit World Model"
    quadrant-3 "EWM: Explicit World Model"
    quadrant-4 "ESM: Explicit Self Model"

The four models arranged by scope (horizontal) and mode (vertical). The top row (implicit) is the "real side" -- substrate-level, learned, non-conscious. The bottom row (explicit) is the "virtual side" -- generated, transient, phenomenal.

Appears in:

2. The Real/Virtual Split (Bubble Diagram)

What it shows: The ontological division between the real side (implicit models -- physical, structural, learned, non-conscious, "lights off") and the virtual side (explicit models -- generated, transient, phenomenal, "lights on"). The virtual side is depicted as a simulation bubble generated by the substrate, with software-like properties: forkable, cloneable, redirectable, reconfigurable.

Why it matters: This single diagram captures the theory's central ontological insight. Placing experience at the virtual level rather than the substrate level reframes the Hard Problem as resting on a category error. Asking why neurons "feel like something" is the wrong question -- neurons generate the computation in which feeling is constitutive.

Image source: figures/figure2-real-virtual-split-simple.svg (canonical color version), figures/figure2-real-virtual-split-simple.png (300 DPI render), figures/figure2-real-virtual-split-bw.svg (black and white)

graph TB
    subgraph Real["REAL SIDE (Substrate)"]
        direction LR
        IWM["IWM<br/>All learned world knowledge<br/>Synaptic weights"]
        ISM["ISM<br/>All learned self-knowledge<br/>Body schema, habits"]
    end

    subgraph Boundary["IMPLICIT-EXPLICIT BOUNDARY<br/>(Variable permeability)"]
        direction LR
        PB["Permeability varies:<br/>&#8593; Psychedelics | &#8595; Anosognosia"]
    end

    subgraph Virtual["VIRTUAL SIDE (Simulation)"]
        direction LR
        EWM["EWM<br/>The conscious world<br/>Sensory experience"]
        ESM["ESM<br/>The conscious self<br/>&#x21BA; Self-referential closure"]
    end

    Real --> Boundary --> Virtual

    style Real fill:#2d2d3d,stroke:#666,color:#ccc
    style Boundary fill:#8b6914,stroke:#d4a017,color:#fff
    style Virtual fill:#1a3a5c,stroke:#4a9eff,color:#fff

The real/virtual split. The substrate (real side) generates the simulation (virtual side) across a boundary whose permeability varies dynamically. "Lights off" above the boundary; "lights on" below.

Appears in:

3. The Five-System Hierarchy

What it shows: Five hierarchically nested systems in the brain: (1) Physical, (2) Electrochemical, (3) Proteomic, (4) Topological (where implicit models are stored as synaptic weight configurations), (5) Virtual (where consciousness exists as the running simulation). Each level is fully physical and fully determined by the level below.

Why it matters: The hierarchy makes the category error concrete. Seeking experiential properties at Levels 1-4 is asking why transistor switching "is" a spreadsheet. Consciousness exists at Level 5 -- as a process running on the substrate, not as a property of the substrate itself.

Image source: figures/figure-five-layer-stack-bw.svg (black and white), figures/figure-five-layer-stack-bw.png (render)

graph TB
    L5["Level 5: VIRTUAL<br/>Consciousness exists here<br/>EWM + ESM (simulation)"]
    L4["Level 4: TOPOLOGICAL<br/>Implicit models stored here<br/>IWM + ISM (synaptic weight configurations)"]
    L3["Level 3: PROTEOMIC<br/>Receptor/ion channel properties<br/>Molecular machinery"]
    L2["Level 2: ELECTROCHEMICAL<br/>Action potentials, synaptic transmission<br/>Neural signaling"]
    L1["Level 1: PHYSICAL<br/>Atoms, molecules, tissue<br/>Substrate material"]

    L1 --> L2 --> L3 --> L4 --> L5

    style L5 fill:#1a3a5c,stroke:#4a9eff,color:#fff
    style L4 fill:#2d4a2d,stroke:#4a9e4a,color:#fff
    style L3 fill:#3d3d2d,stroke:#9e9e4a,color:#fff
    style L2 fill:#3d2d2d,stroke:#9e4a4a,color:#fff
    style L1 fill:#2d2d3d,stroke:#666,color:#ccc

Five nested systems. Each level is fully physical. The category error occurs when one seeks Level 5 properties (experience) at Levels 1-4 (substrate).

Appears in:

4. The Criticality Convergence Timeline

What it shows: A timeline of independent convergence between the theory's Class 4 commitment (derived from Wolfram 2002, published in Gruber 2015) and empirical findings on neural criticality: neuronal avalanches (Beggs & Plenz 2003), Entropic Brain Hypothesis (Carhart-Harris 2014), anesthetic-criticality convergence (Alkire et al. 2000; Casali et al. 2013), sleep-dependent restoration of the computational regime (Xu et al. 2024), sleep onset as bifurcation (Li et al. 2025), the Hengen & Shew (2025) meta-analysis of ~140 datasets, and the ConCrit framework (Algom & Shriki 2026).

Why it matters: The timeline shows that the Class 4 commitment is not a post-hoc accommodation of known data: it was derived from Wolfram's computational universality framework in 2015, and independent research programs have since supported it. Two limits apply. The convergence concerns the Class 4 commitment, which FMT shares with other criticality-based frameworks. And Sipling et al. (2026) show that the same statistical signatures can arise across an extended long-range-ordered phase with no critical point; such a phase also counts as a Class 4 regime, and whether the cortical operating point is tuned remains open.

timeline
    title Criticality Convergence Timeline
    2002 : Wolfram publishes A New Kind of Science
         : Class 4 = universal computation
    2003 : Beggs & Plenz discover neuronal avalanches
    2013 : Casali et al. — complexity index for consciousness
         : Priesemann et al. — avalanches differ wake vs sleep
    2014 : Carhart-Harris — Entropic Brain Hypothesis
    2015 : Gruber — Class 4 / edge-of-chaos requirement for consciousness
    2017 : Atasoy et al. — LSD, connectome harmonics at the edge of criticality
         : Schartner et al. — psychedelics increase signal diversity
         : Pinto et al. — split brain holographic degradation
    2024 : Xu et al. — sleep restores an optimal computational regime
    2025 : Li et al. — sleep onset is bifurcation
         : Hengen & Shew — meta-analysis of ~140 datasets, near-critical setpoint
    2026 : Algom & Shriki — ConCrit framework
         : Sipling et al. — same signatures from an extended phase, no critical point

Timeline showing the theory's Class 4 commitment (2015, derived from Wolfram 2002) and subsequent independent support. No research group had contact with the theory.

Appears in:

5. The Recursive Loop Diagram

What it shows: The closed amplification loop at the heart of the Recursive Intelligence Model: Knowledge enhances Performance (better learning strategies improve processing), Performance enhances Knowledge (greater capacity enables deeper learning), Motivation allocates engagement to both, and success revises Motivation. The loop is recursive and self-amplifying -- small initial advantages compound over time. The three nodes are different kinds of thing: Performance is a capacity, Knowledge is stored content, and Motivation is the policy that allocates the loop's time -- a schedule rather than a substance.

Why it matters: This diagram captures why intelligence is a dynamic, self-reinforcing process rather than a static trait. It accounts for the Matthew effect and the reversal of the Flynn effect, and it places motivation inside the loop as its allocation policy, where the tradition had treated it as a confound to be minimized.

graph LR
    K["Knowledge<br/>(Factual + Operational)"]
    P["Performance<br/>(Processing Capacity)"]
    M["Motivation<br/>(Allocation Policy:<br/>Wissensdrang +<br/>Handlungsdrang)"]

    K -->|"Learning strategies<br/>improve processing"| P
    P -->|"Greater capacity<br/>enables deeper learning"| K
    M -->|"Allocates<br/>engagement"| K
    M -->|"Allocates<br/>engagement"| P
    K -->|"Success<br/>reinforces"| M
    P -->|"Success<br/>reinforces"| M

    style K fill:#1a3a5c,stroke:#4a9eff,color:#fff
    style P fill:#2d4a2d,stroke:#4a9e4a,color:#fff
    style M fill:#5c1a3a,stroke:#ff4a9e,color:#fff

The recursive intelligence loop. The three constituents reinforce each other, producing compounding dynamics; Motivation sets how much of the loop runs, on what, and for how long. Without it the loop does not iterate.

Appears in:

6. The Comparative Scoreboard

What it shows: A systematic comparison of FMT against all major consciousness theories (IIT, GNW, HOT, PP, AST, RPT, Illusionism) across all eight requirements. Each cell indicates whether a theory addresses, partially addresses, minimally touches, or is silent on each requirement, as judged by the paper's author. FMT is the only theory rated as addressing or partially addressing all eight; its Hard Problem, Explanatory Gap and Combination ratings are partial.

Why it matters: The scoreboard is a structured challenge: if another theory addresses requirements that FMT misses, or if FMT's claimed coverage is shown to be inadequate, the table identifies precisely where. It makes the comparison falsifiable rather than rhetorical.

graph TD
    A["Eight Requirements"] --> B["Hard Problem"]
    A --> C["Explanatory Gap"]
    A --> D["Boundary Problem"]
    A --> E["Structure of Experience"]
    A --> F["Unity & Binding"]
    A --> G["Combination & Emergence"]
    A --> H["Causal Role"]
    A --> I["Meta-Problem"]

    B --> J["FMT: Reframed via virtual qualia (partial)"]
    C --> K["FMT: Reframed via level distinction (partial)"]
    D --> L["FMT: Two thresholds"]
    E --> M["FMT: Four-model architecture"]
    F --> N["FMT: Criticality binding"]
    G --> O["FMT: Weak emergence (partial)"]
    H --> P["FMT: Dual evaluation"]
    I --> Q["FMT: ISM-ESM opacity"]

    style A fill:#4a148c,stroke:#e94560,color:#fff

The eight requirements mapped to FMT's specific answers. The full scoreboard table (in the Comparative Scoreboard article) includes IIT, GNW, HOT, PP, AST, RPT, and Illusionism for comparison.

Appears in:

7. The Two-Threshold Matrix

What it shows: The relationship between the two independent thresholds required for consciousness: the computational threshold (free compute -- Class-4 capability actually deployed on self-modeling, of which near-criticality is the measurable biological signature) and the architectural threshold (four-model architecture -- the system must implement the four model kinds). Four quadrants result:

Outside the Class 4 regime In the Class 4 regime (near-critical)
Without 4-Model Architecture Inert matter, simple machines Complex but non-conscious systems
With 4-Model Architecture Brain under propofol at surgical depth, deep NREM sleep Conscious system

Why it matters: Neither threshold alone is sufficient; together they are. A system with critical dynamics but without the right architecture (e.g., a sandpile) is not conscious. A system with the right architecture pushed out of the regime (e.g., a brain under propofol at surgical depth) shows no reportable experience. This provides a principled boundary for consciousness and explains why propofol at surgical depth abolishes reportable experience (it crosses the computational threshold) without dismantling the architecture. The relation is one-directional: leaving the regime abolishes consciousness, but a near-critical cortex can also host heavy unconscious modeling, as in some sleep phases.

quadrantChart
    title Two Thresholds for Consciousness
    x-axis "Outside Class 4 Regime" --> "In Class 4 Regime"
    y-axis "Without 4-Model Architecture" --> "With 4-Model Architecture"
    quadrant-1 "CONSCIOUS: Awake brain, conscious AC system"
    quadrant-2 "Propofol at surgical depth, deep NREM"
    quadrant-3 "Inert matter, simple machines"
    quadrant-4 "Complex non-conscious: sandpiles, weather"

Consciousness requires both thresholds to be met simultaneously. Moving left (leaving the Class 4 regime, as under propofol at surgical depth) abolishes reportable experience. Moving down (losing architecture) produces complex non-conscious systems.

Appears in:

Additional Figures

FMT-RIM Bridge Diagram

The bridge between FMT and RIM, showing how the four-model architecture enables cognitive learning, which powers the recursive intelligence loop. This diagram appears in the Overview article and the Consciousness-Intelligence Bridge article.

Phenomenological Content Figure

A detailed breakdown of the content generated by each explicit model (EWM: sensory experience, spatial scene, object recognition; ESM: body ownership, agency, narrative self). Image source: figures/figure3-phenomenological-content-bw.svg.

Appears in:

Penfield Homunculus (Reference)

The cortical homunculus illustrating the somatotopic organization of the ISM's body schema in the primary somatosensory cortex. Used as a reference figure for the biological implementation of the Implicit Self Model. Image source: figures/figure-penfield-homunculus-bw.svg.

Appears in:

Figure

graph LR
    subgraph Architecture["Architecture Figures"]
        F1["2x2 Model Table"]
        F2["Real/Virtual Bubble"]
        F3["Five-System Hierarchy"]
        F7["Two-Threshold Matrix"]
    end

    subgraph Dynamics["Dynamics Figures"]
        F4["Criticality Timeline"]
        F5["Recursive Loop"]
    end

    subgraph Comparison["Comparison Figures"]
        F6["Comparative Scoreboard"]
    end

    F1 --> F2
    F2 --> F3
    F3 --> F7
    F1 --> F5
    F7 --> F4

    style Architecture fill:#1a1a2e,stroke:#e94560,color:#fff
    style Dynamics fill:#16213e,stroke:#0f3460,color:#fff
    style Comparison fill:#2d1a2e,stroke:#e94560,color:#fff

The seven core figures organized by type. Architecture figures describe structure; dynamics figures describe processes; comparison figures evaluate the theory against alternatives.

Key Takeaway

Seven recurring figures carry the visual weight of the Standard Model of Consciousness. Mastering what each one shows -- the 2x2 architecture, the real/virtual split, the five-system hierarchy, the criticality timeline, the recursive loop, the comparative scoreboard, and the two-threshold matrix -- provides a visual scaffold for the entire theory.

See Also

Based on: Gruber, M. (2026). The Four-Model Theory of Consciousness. Zenodo. doi:10.5281/zenodo.18669891

Based on: Gruber, M. (2026). The Four-Model Theory of Consciousness — A Criticality-Based Framework. doi:10.5281/zenodo.18669891