Glossary
Canonical notation for all BMC documents. When a document conflicts with this glossary, the glossary is authoritative.
Core Model: BMC = (G, M, I, S)
BMC
Biomemetic Complex. The full system: $BMC = (G, M, I, S)$. A universal model, fractally applicable at any scale — from memes within a mind to cultures within civilization.
G
Genetic layer. Fixed programs: Panksepp's 7 affective systems. Vector $T = (T_{SEEK}, T_{FEAR}, \ldots, T_{PLAY})$. Substrate: brainstem, hypothalamus, amygdala.
M
Memetic layer. Network of acquired knowledge (memeplex). Physically = cell assemblies in the cortex. Dynamic, heavy-tailed topology.
I
Interface / Immune filter. Mechanisms of G↔M interaction: Redirection, Suppression, Interpretation. Mediates conflict between drives and memes; filters incompatible information at 4 levels. Substrate: ACC, insula, OFC.
S
Substrate. Dual nature: (1) physical medium (neurons, neurotransmitters); (2) sensory architecture (input channels). Brain, silicon, or any system supporting replicator dynamics.
Key Mechanisms and Metrics
SMC
Self-Model Cluster. A subgraph of the memeplex that models the system itself: $SMC = \{m \in M : target(m) \in M \cup G \cup I\}$. Three recursion levels: L0 (bodily), L1 (narrative self), L2 (metacognition). Substrate: mPFC + TPJ + PCC.
SIT
Structural Incompleteness Tension. Tension arising from structural gaps in the memeplex. When $SIT > \theta$, triggers SEEKING. Subjectively experienced as curiosity, anxiety, or the feeling of "unfinished business."
CL
Consciousness Level. $CL(t) = \sigma_{SW}(t) \cdot A_{SMC}(t) \cdot f(Balance(t))$. A single scalar metric capturing the degree of consciousness at time $t$.
SMR
Shared Memplex Repository. The collective knowledge store of a population of agents. Fractal: $SMR = (G_{SMR}, M_{SMR}, I_{SMR}, S_{SMR})$. Cultural ratchet mechanism.
LP
Learning Progress. $LP(C, t) = \frac{d}{dt} closure(C, t)$. LP > 0 = productive reflection; LP ≈ 0 = rumination.
PE
Prediction Error. Sharp SIT increase when incoming information diverges from expectation.
Mod(t)
Modulation vector. 8-component global state: $(\lambda_{lr}, \theta_{act}, \lambda_{speed}, \lambda_{plast}, \lambda_{inh}, \lambda_{soc}, \lambda_{noise}, \lambda_{diff})$. Maps to neurotransmitter systems.
PA
Preferential Attachment. $\Pi(k_i) = k_i / \sum_j k_j$. Network growth mechanism: popular nodes attract more connections (the rich get richer).
RIF
Retrieval-Induced Forgetting. Retrieving one meme suppresses competitors. $RIF \propto 1/C_E$ (hubs are protected).
SET
Structural Equivalence Test. Formal procedure for determining whether a property transfers across scales. Three zones: green (unconditional), yellow (with correction), red (impossible).
R_expr
Replication Expression pressure. $R_{expr} = a \cdot F \cdot rel \cdot (1 + \alpha \cdot C_E)$. M-driven pressure for a meme to be expressed outward. Not a genetic drive but an emergent property of memetic replication.
Network Metrics
σ_SW
Small-Worldness. $\sigma_{SW} = (C/C_{rand}) / (L/L_{rand})$. Healthy networks ≫ 1. Do not confuse with $\sigma$ (branching ratio), which is a different quantity.
Q
Modularity. How well the network partitions into dense clusters. High Q = rigidity; healthy range involves a balance between integration and differentiation.
C_E
Eigenvector Centrality. Measures the "strength" of a node: not just how many connections it has, but whether those connections are themselves well-connected.
C_B
Betweenness Centrality. Identifies bridge nodes that connect otherwise separate clusters.
κ
Consolidation level. $\kappa \in \{0, 1, 2\}$: 0 = sensory buffer, 1 = short-term memory, 2 = long-term memory.
ψ
Synaptic trace. Activity-silent working memory: a hidden variable enabling latent WM. $\psi \in [0,1]$.
D_eff
Effective Directionality. Measures the communicative asymmetry of the graph.
N_bid
Bidirectional connections. Fractal invariant: $N_{bid}(L) \approx bandwidth(L) - 1$.
Memory and Consolidation
WM
Working Memory. Active WM (~3–4 pointers in focus) + Latent WM ($\psi > \theta_\psi$) ≈ 7 ± 2.
STM
Short-Term Memory. $\kappa = 1$. High activation, low fidelity, not yet consolidated.
LTM
Long-Term Memory. $\kappa = 2$. Consolidated memes with strong connections.
LTP / LTD
Long-Term Potentiation / Long-Term Depression. Strengthening and weakening of synaptic connections. LTP has early (E-LTP, CaMKII) and late (L-LTP, CREB) phases.
SWR
Sharp-Wave Ripple. Hippocampal reactivation mechanism; tags experiences for sleep consolidation.
SHY
Synaptic Homeostasis Hypothesis (Tononi & Cirelli). Sleep = global synaptic downscaling.
Sleep Phases
| Phase | Function |
|---|---|
| DECOMPOSE | Decomposition of episodes into components |
| CONNECT | Binding components to existing structures |
| BLEND | Stochastic recombination (REM) |
| PRUNE | Removal of weak connections |
| STRENGTHEN | Reinforcement of strong connections |
| REPLAY | Reactivation of tagged episodes |
G-Programs (Panksepp’s 7 Systems)
| System | Function | Valence | Neurotransmitter | WM capture |
|---|---|---|---|---|
| SEEKING | Exploration, curiosity | + | DA | 0 (directs WM) |
| FEAR | Threat avoidance | − | NE, cortisol | 1.0 (full capture) |
| RAGE | Frustration, boundary defense | − | NE + Adrenaline | 0.8 |
| LUST | Goal pursuit | + | DA + OXT + VP | 0.3 |
| CARE | Nurturance, attachment | + | OXT | 0.2 |
| PANIC/GRIEF | Separation distress | − | CRF, glutamate | 0.7 |
| PLAY | Social learning | + | Endorphins, endocannabinoids | 0 (releases WM) |
DISGUST is not an 8th Panksepp system. It is an I-layer mechanism (immune filter).
Three Computational Engines
| Engine | Mechanism | What it determines | Substrate |
|---|---|---|---|
| Graph Engine | Synaptic transmission | WHAT is active: activations, edges, WM competition | AP → NT → PSP |
| Modulation Engine | Neuromodulation | HOW the graph works: speed, plasticity, noise | DA, 5-HT, NE, ACh |
| Diffusion Engine | Volume transmission | BACKGROUND: priming, warming of semantically close memes | NT spillover |
Neuroanatomy
| Abbreviation | Full name | Role in BMC |
|---|---|---|
| DMN | Default Mode Network | Substrate for SIT scanning and reflection |
| CEN | Central Executive Network | Task-oriented processing |
| ACC | Anterior Cingulate Cortex | I-layer: conflict detection |
| mPFC | medial Prefrontal Cortex | Part of SMC and DMN |
| dlPFC | dorsolateral Prefrontal Cortex | WM control |
| OFC | Orbitofrontal Cortex | I-layer: reward and context integration |
| TPJ | Temporoparietal Junction | Part of SMC: Theory of Mind |
| PCC | Posterior Cingulate Cortex | Part of SMC and DMN |
| VTA | Ventral Tegmental Area | Dopaminergic region (SEEKING) |
| PAG | Periaqueductal Gray | Substrate for G-programs |
| DMS / DLS | Dorsomedial / Dorsolateral Striatum | Goal-directed vs automatic behavior |
Neurotransmitters
| Abbreviation | Substance | Role in Modulation Engine |
|---|---|---|
| DA | Dopamine | $\lambda_{lr}$ (learning rate), $\lambda_{noise}$ |
| 5-HT | Serotonin | $\theta_{act}$ (activation threshold), $\lambda_{inh}$ |
| NE | Norepinephrine | $\lambda_{speed}$, arousal |
| ACh | Acetylcholine | $\lambda_{plast}$ (plasticity) |
| OXT | Oxytocin | $\lambda_{soc}$ (social bonding) |
| GABA | Gamma-Aminobutyric Acid | Inhibitory: lateral inhibition, WM competition |
Related Theories of Consciousness (Limiting Cases)
| Theory | Author | Limiting case in BMC |
|---|---|---|
| IIT | Tononi | BMC at $M = \emptyset$; $\sigma_{SW}$ metric |
| GNW | Dehaene & Changeux | WM broadcasting mechanism |
| AST | Graziano | SMC as attention schema |
| HOT | Rosenthal | $SMC^{(2)}$ as higher-order representation |
| RPT | Lamme | Spreading activation + feedback loops |
| FEP | Friston | SIT + G-homeostasis = active inference |
| PP | Clark, Hohwy | SIT + G-homeostasis (paired with FEP) |
Each theory retains independent value for its own formalism; BMC recovers it as a limiting case under stated restrictions — it does not replace it.
Measurement Proxies
| Abbreviation | Full name | BMC mapping |
|---|---|---|
| PCI | Perturbational Complexity Index | Proxy for $\sigma_{SW}$ in CL metric (TMS-EEG) |
| DCM | Dynamic Causal Modeling | Proxy for $f(Balance)$ in CL metric |
| HEP | Heartbeat Evoked Potential | Proxy for $I_{intero}$ (interoceptive integration) |
Cross-Pillar References
| Abbreviation | Full name | Scope |
|---|---|---|
| EMT | Extended Meme Theory | Conceptual core: memes, SMC, dual replicator |
| BM | Biomemetics | Neurobiological grounding |
| NM | Network Memetics | Mathematical formalization, metrics |
| AGI_F | AGI Foundations | Engineering blueprint |
| SM | Swarm Memetics | Fractal scaling |
Notation Conventions
- First mention: always expanded — “SMC (Self-Model Cluster)”
- In formulas: abbreviation only — $A_{SMC}$, $\sigma_{SW}$, $SIT(C)$
- PANIC/GRIEF: slash in text, underscore in code (
PANIC_GRIEF) - σ: always specify context — $\sigma_{SW}$ (small-worldness) vs $\sigma$ (branching ratio)
- λ: always with subscript — $\lambda_{plast}$, $\lambda_{lr}$, $\lambda_{diff}$. Bare λ is ambiguous (>8 different parameters)
- S: in BMC tuple = Substrate. In sensors = $S_{spatial}$, $S_{resource}$, etc.