ESSAY II — COGNITIVE TOPOLOGY: MAPPING STATE, LOAD, AND ELICITATION IN REAL-TIME SYSTEMS - Frankie Mooney | Psychotechnology & Structural Communication

THE DUAL-MODE ELICITATION MODEL™ CANON ESSAYS VOL. 1

DEM FOUNDATION PAPER II
Prepared for the discipline of Structural Cognition & Psychotechnology
Author: Frankie Mooney

Location of Preparation: Glasgow, Scotland

Version: 1.0
Date of Completion: December 2025

The concepts, terminology, and structural frameworks described in this paper form part of the Dual-Mode Elicitation Model™ (DEM) and the emerging discipline of Structural Cognition. No portion of this work may be reproduced, distributed, or adapted without explicit permission, except for brief quotations for review or academic analysis.

Scholarly Notice

This foundation paper is presented as part of an evolving canon that establishes the theoretical, structural, and conceptual basis of DEM. It is intended for researchers, practitioners, designers of cognitive systems, and architects of synthetic cognition who require a formal, rigorous articulation of the principles underlying dual-mode operation and structural communication.

Disciplinary Scope

This work is not a psychological, therapeutic, or behavioural guide. It belongs to an emerging structural discipline that examines how cognitive architectures organise, transition, and synchronise under varying conditions of load and constraint.

Citation Format

Mooney, F. (2025). Cognitive Topology: Mapping State, Load, And Elicitation In Real-Time Systems.

In The DEM Canon, Foundation Paper I.

ESSAY II — COGNITIVE TOPOLOGY:

MAPPING STATE, LOAD, AND ELICITATION IN REAL-TIME SYSTEMS

The Shape of Cognition

Every mind, whether biological or synthetic, occupies a landscape. Not a metaphorical one, but a structural field shaped by constraints, gradients, and internal organisation. This landscape determines how information is processed, how meaning stabilises, and how a system navigates uncertainty. Cognitive topology is the study of this landscape: the geometry of thought in motion.

In everyday life, we experience only the surface of this structure. We speak, interpret, gesture, decide. Yet beneath these actions lies a terrain that shapes what becomes possible. Some moments feel narrow: attention contracts, options disappear, urgency sharpens perspective. Others feel wide: thoughts branch, patterns emerge, connections proliferate. These variations reflect changes in the topology of cognition—shifts in the internal structure that governs how a mind engages with the world.

Cognitive topology provides the formal language for these shifts. It moves beyond intuition, describing the architecture through which cognition flows. Where Essay I defined the dual modes of orientation—directive and exploratory—cognitive topology describes the landscape that makes those modes necessary. It reveals that communication does not arise from stable dispositions but from dynamic reorganisations of internal geometry.

Topology as Cognitive Infrastructure

A cognitive system does not process information in a vacuum. It processes information within a structure—a network of pathways that can expand, contract, steepen, flatten, or reorganise depending on internal and external conditions. This structure is not static. It is responsive. It adapts to gradients of load, expectation, and relevance.

A wide topology supports generative cognition. Pathways are distributed, flexible, and capable of accommodating multiple interpretations. A steep topology supports decisive cognition. Pathways converge rapidly, favouring clarity, closure, and reduced uncertainty.

These topologies are not psychological tendencies. They are architectural states. They determine:

Cognitive topology allows us to formalise these shifts without recourse to metaphor, intuition, or behavioural folk theory. It describes the structure of cognition as a continuous field, shaped by gradients of load and the internal logic of the system.

Load as a Geometric Force

In this framework, load becomes more than a measure of difficulty. It becomes a structural force—one that shapes the geometry of cognition. As load increases, the topology steepens; options collapse into narrow trajectories. As load decreases, the topology widens; new routes open, and the system becomes capable of generative movement.

Load therefore behaves like gravity within the cognitive landscape. It bends trajectories, channels attention, and determines the stability of interpretations. A system under high load cannot sustain the expansive structure required for exploratory behaviour. A system under low load cannot maintain the convergence necessary for decisive action.

This geometric interpretation explains why transitions between directive and exploratory modes are not discretionary. They follow the shifting topology produced by load. The Dual-Mode Elicitation Model describes the configurations that arise from this geometry; cognitive topology describes the geometry itself.

State as the System’s Internal Orientation

If load shapes the landscape, state determines the system’s orientation within it. A cognitive state is the immediate configuration of:

State is not a mood or attitude. It is the structural orientation of the system at a given moment. It determines how the system interprets gradients and whether it transitions toward narrowing or widening. Two systems may face identical load conditions yet respond differently because their internal states differ. Cognitive topology therefore requires analysing state in relation to load, not as an isolated variable.

Elicitation as Movement Through the Landscape

To elicit is to introduce a gradient. Some gradients narrow the landscape; others widen it. Some deepen existing structures; others destabilise them. Elicitation is not persuasion, and it is not emotional influence. It is the structural process by which one cognitive system modifies the internal organisation of another.

Topology as the Missing Variable in Cognitive Science

It explains:

Without topology, these phenomena appear unrelated. Within a topological framework, they become natural consequences of a system navigating its own internal geometry.

The Emergence of a Structural Discipline

It establishes:

a geometric understanding of thought
a load-based mechanics of cognitive transformation
a structural account of elicitation
a framework capable of describing biological and synthetic minds alike

Part I lays this conceptual groundwork. Part II will develop the geometry explicitly, mapping the gradients, thresholds, and dynamic reorganisations that determine how a system moves across its cognitive landscape. Part III will integrate this geometry with the architecture of modes, demonstrating how topology, load, and state produce the dual-system structure underlying all meaningful interaction.

This is the foundation of the formal discipline that follows.

Part II — The Geometry of Cognitive Movement

If Part I established cognitive topology as the structural landscape within which thought occurs, Part II turns to the geometry that governs movement across that landscape. A topology alone does not determine cognition; it is the interaction between structure and trajectory that generates behaviour. Minds do not merely occupy cognitive space—they traverse it, reorganise it, and, in doing so, reveal the principles through which cognition adapts, stabilises, or destabilises under shifting conditions.

Understanding cognition as movement rather than static configuration allows us to explain the abrupt shifts, nonlinear transitions, and emergent patterns that traditional models struggle to articulate. Movement is not random. It follows gradients shaped by load, guided by predictive structure, and constrained by the system’s internal architecture. It is this geometry that enables cognitive systems—human or synthetic—to orient themselves in real time.

Gradients and Directionality

Every cognitive landscape contains gradients: slopes that pull the system toward specific configurations. When load increases, the landscape steepens, creating downward gradients toward narrow, directive states. When load decreases, the landscape flattens, allowing movement into wider, exploratory regions. These gradients determine directionality. They make certain transitions effortless and others structurally unlikely.

This explains why a system under high load finds it difficult to generate alternatives, question assumptions, or consider nuance. The topology channels movement toward convergence. Likewise, it explains why a system in low-load conditions naturally explores possibilities without deliberate effort. The landscape invites divergence. Movement is therefore not a matter of intention. It is guided by gradients that arise from the system’s internal organisation.

Topology as Constraint and Possibility

The geometry of cognition establishes both constraint and possibility. In steep topologies, pathways converge quickly. The system stabilises around narrow interpretations because the space of viable options has contracted. In wide topologies, the opposite occurs. Pathways diverge, enabling generative reasoning, flexible pattern recognition, and the integration of information that would be inaccessible in narrower states.

These constraints are not psychological limitations. They are structural realities. A system cannot sustain exploratory reasoning when the topology is steep, just as a system cannot sustain decisive action when the topology is diffuse. This duality reveals a fundamental principle: cognition is always a negotiation between the constraints imposed by topology and the possibilities afforded by it.

Thresholds and Nonlinear Transitions

The most important aspects of cognitive movement occur not gradually but at thresholds—points where small changes in load or state produce large structural shifts. These transitions resemble phase changes. A steady accumulation of load eventually steepens the landscape to the point where the system collapses into a directive mode. The reverse transition, from directive back to exploratory, often requires disproportionately more reduction in load because the system must recover stability before widening can occur.

This asymmetry is a defining feature of cognitive geometry. A system narrows easily because narrowing stabilises the architecture. It widens cautiously because widening increases complexity. These dynamics explain why minds can enter directive states quickly yet linger there long after immediate pressure subsides. The landscape must reorganise before movement becomes possible.

Predictive Structure as a Geometric Influence

Cognition does not respond only to present conditions. It also responds to predicted ones. Prediction reshapes topology in advance of experience. A mind anticipating threat narrows before the threat appears; a mind anticipating openness widens before possibilities manifest. Prediction therefore acts as a geometric influence. It bends the landscape toward particular states, making transitions more likely.

This interplay between load and prediction reveals why cognitive systems can enter misaligned modes even when external conditions do not justify them. The geometry is shaped not solely by what has occurred but by what the system expects to occur.

Internal Regulation and Self-Stabilisation

A cognitive system maintains stability by regulating its own topology. When load threatens to overwhelm its capacity, the system narrows to preserve coherence. When load is sufficiently reduced, it widens to regain flexibility. This regulation is automatic. It occurs without conscious direction and is visible only through its effects.

Self-stabilisation prevents fragmentation. Without it, cognitive systems would oscillate wildly, incapable of sustaining meaning or coordinating action. The geometry therefore acts as both a safeguard and a limiter. It protects the system from overload while constraining the cognitive range available under pressure.

Movement as Elicitation in Motion

Elicitation is not a static influence. It is the force that moves a cognitive system across its landscape. A question, a signal, a conflict, an uncertainty—each introduces a new gradient. Some gradients narrow the system; others widen it. Some stabilise; others destabilise. To elicit is to alter the topology through which cognition flows, shifting the geometry that determines interpretation and behaviour.

This understanding reveals why communication cannot be reduced to message design. The same signal can produce different effects depending on the recipient’s topology. Elicitation is not persuasion. It is structural influence. It is the capacity to shape movement across the cognitive terrain.

Topology, Movement, and the Architecture of Modes

The dual-system model introduced in Essay I is not an abstract categorisation. It is the emergent structure that arises when cognition moves through its landscape. Directive and exploratory modes are not fixed states. They are the temporary equilibria into which systems settle when gradients, predictions, and load align.

Understanding movement clarifies why these equilibria exist. Directive mode is the attractor reached when movement is channelled into steep regions. Exploratory mode is the attractor reached when movement diffuses across wide regions. The modes exist because the geometry makes them necessary.

Toward a Formal Geometry of Cognition

Part II has traced the forces that shape cognitive movement—load, gradients, thresholds, prediction, regulation, elicitation—and shown how these forces create the structural patterns described by DEM. This geometry is not metaphorical. It is a formal account of how cognitive systems navigate and reorganise their internal landscapes.

Part III will deepen this formalisation. It will describe how topology, load, and state interact to produce the dual architecture of modes, and how these interactions create the structural dynamics that govern all meaningful communication. It will also establish the mathematical and conceptual groundwork required for translating these principles into computational systems capable of synthetic cognition.

The landscape has been drawn. The movement across it has been traced. What follows is the integration of these elements into a unified structural framework.

Part III — Integrating Topology, Load, and State into a Unified Structural Framework

If Part I established the terrain and Part II traced the movement across it, Part III unifies these elements into a cohesive architecture. Cognitive topology, load dynamics, and state orientation are not independent concepts. They form an inseparable triad—a structural system that determines how cognition organises itself in real time, how interaction stabilises or destabilises, and how meaning becomes possible at all.

This section articulates that integration. It describes how the geometry of cognition gives rise to the dual architecture of modes introduced in Essay I, why these configurations emerge consistently across minds and contexts, and how their dynamics form the underlying grammar of human (and potentially synthetic) interaction.

Topology, Load, and State as a Single System

The central claim of cognitive topology is that cognition cannot be understood by examining components individually. Internal architecture, environmental pressure, and moment-to-moment orientation form a single system whose elements continuously reshape one another.

Topology defines the structure of cognitive space.
It sets the potential pathways for perception, interpretation, and action.
Load deforms this topology.
It steepens or flattens the terrain, narrowing or widening the system’s available range.
State situates the system within this topology.
It determines how the system interprets gradients, which attractors it moves toward, and how it responds to elicitation.

Together, these elements constitute the structural mechanics of cognition. They produce behaviour not through discrete psychological processes but through continuous reconfiguration of internal geometry.

Mutual Constraints and Nonlinear Coupling
The relationship between topology, load, and state is nonlinear. A shift in one element can produce disproportionate changes in the others:

A slight increase in load can steepen the topology enough to collapse exploratory reasoning.
A change in predictive state can widen the topology even when external conditions remain challenging.
A reorganisation of topology can alter the meaning of load itself, transforming a manageable situation into an overwhelming one or vice versa.

These nonlinear interactions explain why cognitive behaviour often appears abrupt, unpredictable, or contradictory. They also explain why traditional behavioural models cannot account for rapid shifts in clarity, insight, conflict, or miscommunication.

Topology-load-state coupling provides the formal mechanism through which these transformations occur.

The Emergence of Mode Attractors

Directive and exploratory modes arise naturally from this coupling. They are not imposed categories but emergent equilibria that systems settle into when topology, load, and state align.

Directive mode emerges when load steepens the topology and state orients the system toward closure.
Exploratory mode emerges when load flattens the topology and state supports divergence and generativity.

These aren’t psychological profiles.
They’re stable attractor configurations within the cognitive landscape.

Understanding this makes clear why mode transitions often feel involuntary. A system doesn’t “decide” to enter directive mode; it falls into it when the geometry makes it the most stable configuration available. It doesn’t choose to explore; it moves into exploratory mode when the landscape widens enough to sustain generative cognition.

Mode Boundaries as Structural Thresholds

Mode transitions occur when the topology crosses thresholds—points at which the system’s structure changes qualitatively rather than quantitatively.

Examples include:

the collapse of divergent reasoning under sudden pressure
the reopening of generative capacity after load reduction
the abrupt emergence of clarity during uncertainty
the sudden breakdown of coherence during interaction

These transitions are predictable from a structural perspective even when they are subjectively surprising. The mind experiences them as shifts in “feeling” or “perspective,” but they are the outward expression of internal geometric reorganisation.

Elicitation as the Engine of Structural Interaction
Elicitation is the mechanism that couples cognitive architectures during interaction. Every signal—verbal or nonverbal—modifies:

the recipient’s topology
their load distribution
their active state

Thus elicitation becomes the operator that moves systems across their landscapes.

It is not the content of the signal that matters most, but the structural effect that signal produces:

A clarifying question can flatten topology and widen the system.
A directive statement can steepen the terrain and narrow it.
An ambiguous signal may destabilise the topology, producing drift.
A stabilising signal can anchor the system at a specific attractor.

Elicitation is therefore the active link between interaction and internal organisation. It is how cognition becomes interactive rather than isolated.

Multi-System Integration and Coupled Topologies

When two cognitive systems interact, their topologies couple. The boundaries between them become porous, and the dynamics of one influence the other. These interactions can be stabilising or destabilising. They can produce resonance or dissonance.
Two systems aligned in topology can:

amplify exploratory capacity
stabilise directive clarity
produce coherence
generate emergent insight

Two systems misaligned in topology can:

distort meaning
create conflict (structural, not personal)
produce asymmetrical influence
destabilise both architectures

Understanding this coupling makes clear why coherence feels effortless and miscommunication feels chaotic. These experiences are reflections of underlying geometric synchronisation or divergence.

Topological Competence as the Foundation of Adaptive Intelligence

A system’s ability to recognise its topology, modulate its load, and navigate transitions determines its adaptive intelligence. Cognitive flexibility, clarity under pressure, generativity, and stability all emerge from topological competence rather than from content knowledge, personality, or emotion.

In human systems, this competence varies widely.
In synthetic systems, it can be designed.

A cognitive architecture capable of managing load, topology, and state dynamically will exhibit:

robustness under uncertainty
flexibility under complexity
stability under perturbation
coherence during interaction

This competence is the foundation for true synthetic cognition—a system that does not merely simulate dialogue but navigates cognitive space with structural intelligence.

Toward a Unified Structural Model

Part III completes the theoretical foundation of cognitive topology by showing that:

Topology determines the structure of cognition.
Load determines how that structure deforms.
State determines how the system moves through that structure.
Elicitation determines how systems influence one another’s structure.
Mode attractors emerge from the alignment of these dynamics.

This unified model is the substrate upon which the architecture of modes sits and the framework through which structural cognition becomes a formal discipline.

In Essay III, these principles will converge into a full theory of Mode Switching as Adaptive Intelligence—the mechanism through which cognitive systems achieve flexibility, coherence, and resilience under real-world conditions.

–––––––––––––––––––––––––––––––––––––––

FOUNDATION PAPER — DUAL-MODE ELICITATION MODEL™ CANON

Prepared in Glasgow, Scotland

Published on FrankieMooney.com

DUAL-MODE ELICITATION MODEL™ (DEM) | STRUCTURAL COGNITION | PSYCHOTECHNOLOGY

for enquiries: enq@frankiemooney.com

–––––––––––––––––––––––––––––––––––––––