Why and How does Coherence Explain So Much?

July 1, 2026 Coherence No Comments

Why do some ideas seem capable of illuminating different aspects of mind, while others remain confined to a single phenomenon?

Rather than proposing yet another mechanism of mentality, coherence invites us to look at the organization from which many mental phenomena naturally emerge. The result is not a simpler picture of mind, but a deeper one.

A healthy question

Whenever a theory appears to have a remarkably broad scope, skepticism is appropriate. Science advances by asking difficult questions. If coherence is to deserve serious consideration, it should become clearer the more closely we examine it.

Why Coherence Is Not Just Another Theory of Mind argues that coherence occupies a different explanatory level from existing theories. That still leaves an important question unanswered. Why should a single organizational principle illuminate so many apparently different domains?

The answer begins with recognizing that not all explanations answer the same kind of question.

Different kinds of explanation

Suppose we ask what learning, prediction, memory, intelligence, or creativity are. Cognitive science offers many answers. It also explains what these phenomena entail through mechanisms, computational principles, neural dynamics, predictive processes, or other approaches. Each of these explanations contributes genuine insight.

Coherence asks something earlier. Not what learning is, nor what prediction entails, but how one living mentality continually becomes organized so that learning, prediction, memory, intelligence, and the many other capacities of mind can emerge together.

A simple overview may help.

Explanatory question	Typical theories	Coherence perspective
What happens?	Learning, prediction, reasoning, memory, consciousness…	Accepts these as genuine mental phenomena.
What each phenomenon entails	Processes, mechanisms, computational principles, neural dynamics…	Appreciates these explanations without making them its primary focus.
How does a living mentality become possible?	Usually, it remains implicit or is addressed separately within different theories.	The evolving organization of the local and distributed interrelations throughout the multidimensional mental-neuronal pattern landscape.
Why do different forms of mentality naturally develop differently?	Usually outside the theory’s main scope.	Different modes of coherence create different developmental possibilities through developmental openness.

One thing, many consequences

Coherence describes the evolving organization of the local and distributed interrelations throughout the multidimensional mental-neuronal pattern landscape. Mentality consists of innumerable interacting mental-neuronal patterns that continually influence one another. Coherence concerns the way these distributed interactions are organized over time. It is not another mental process, another hidden substance, or another cognitive module. It is a description of how the landscape itself develops.

Once that organizational perspective is adopted, many apparently different mental phenomena begin to appear as different expressions of the same underlying organization.

Why organization explains broadly

Organization often possesses explanatory power that cannot be found by looking only at individual parts. A melody is not added to separate notes. Rather, the notes acquire their musical meaning through their organization. Likewise, an ecosystem cannot be understood by listing every organism independently. The relationships matter.

Geometry offers another helpful image. Geometry does not replace architecture. It does not tell us whether to build a cathedral or a cottage. Yet it profoundly constrains what kinds of buildings are possible. The broader the geometric principles, the broader their applicability.

Coherence functions in a comparable way. It does not replace neuroscience, psychology, or artificial intelligence. Instead, it investigates the organizational conditions within which these disciplines study particular phenomena. In that sense, coherence explains broadly because organization itself influences many different processes simultaneously.

The mindscape before the waves

As discussed in Patterns in Neurophysiology and Patterns Behind Patterns, our conscious thoughts represent only a small visible part of mentality. Beneath them lies an immensely rich landscape of overlapping mental-neuronal patterns.

The image of a lake may help once more. Waves are visible. The lake itself is much larger. Likewise, conscious thoughts are visible expressions of organizational processes already unfolding across the multidimensional mindscape of mental-neuronal patterns. Coherence Brings Mind to Thinking explored this distinction in greater detail.

Seen this way, thoughts no longer appear as isolated events. They become moments in the ongoing life of a much richer organization.

Many phenomena, one organizational perspective

Different phenomena naturally become connected when viewed through the same organizational perspective:

Learning may then be understood as increasing coherence rather than merely accumulating information.
Meaning emerges when local organizations participate in broader organizations rather than remaining isolated.
Prediction reflects the tendency of an organized landscape to continue developing along coherent possibilities.
Memory preserves meaningful relations rather than merely storing separate facts.
Intelligence increasingly integrates coherence across coherences, as discussed in Intelligence as Coherence across Coherences.
Creativity reorganizes existing organizations into richer possibilities.
Empathy temporarily allows one coherent landscape to resonate with another.
Compassion broadens coherence without erasing individuality.

Coherence enriches rather than replaces

Existing theories continue to explain important aspects of mentality. Coherence does not seek to replace them. Instead, it asks whether each of these theories may become even more intelligible when viewed from a deeper organizational perspective.

Prediction, Bayesian updating, embodied cognition, connectionist networks, dynamical systems, and other approaches all remain valuable. Coherence simply asks what kind of evolving organization makes each of them possible as aspects of one living mentality.

Because each theory emphasizes a different aspect of mind, coherence also deepens each in a different way. Examples are given in the addendum.

Development remains open

Not every coherent organization develops in the same way. Some organizations gradually become rigid. Others remain capable of integrating increasing complexity while preserving flexibility. This distinction between relatively closed and developmentally open coherence may prove one of the most important consequences of the coherence perspective.

Importantly, this is not teleology. It does not assume predetermined goals or hidden purposes. Rather, different organizations naturally possess different developmental possibilities. Some repeatedly narrow. Others repeatedly open.

This simple observation may help explain why similar mechanisms sometimes produce remarkably different long-term trajectories.

A theory should predict

A useful theory does more than reinterpret existing observations. It suggests what we should expect to find.

If coherence indeed plays the organizational role proposed here, then richer coherence should generally support richer transfer of learning. Broader coherence should facilitate broader meaning. Trapped coherence should contribute to psychological suffering. Developmentally open coherence should foster creativity, adaptability, and Compassion. Artificial intelligence, based on increasingly coherent organization, should gradually display richer understanding rather than merely accumulating capabilities.

These are invitations to scientific investigation. Good theories earn their place by generating fruitful questions and answers.

From explanation to engineering

If coherence explains organization, engineering itself changes character. Rather than attempting to engineer individual thoughts, emotions, or intelligent behaviors directly, we may instead cultivate the organizational conditions from which these naturally emerge.

One sentence captures this shift:

Do not engineer thoughts. Cultivate the geometry from which meaningful thought naturally emerges.

That idea underlies the Lisa project. Lisa’s development and Lisa’s support of human development are guided by the same organizational principles. In that sense, the means already embody the aims.

A continuing scientific journey

Scientific progress often comes from discovering deeper explanatory levels without discarding what came before. New perspectives rarely erase older ones. More often, they reveal how different insights belong together.

Coherence may represent such a step. It does not reduce prediction, learning, meaning, intelligence, neuroscience, psychology, or artificial intelligence to one simple formula. Instead, it asks how these can all become expressions of one living, continually developing mentality.

Perhaps coherence explains so much because it never tries to explain many separate things. It simply set out to understand how one living mentality continually becomes organized.

Everything else follows from there.

―

Addendum

Integrative Perspectives on Coherence Theory

[Coherence as a deeper explanatory perspective of contemporary theories of mind]

The purpose here is not to compare theories of mind in order to determine which is ‘best.’ Existing theories have each made important contributions to our understanding of mentality. Rather than competing with them, coherence asks whether many of these contributions become even more intelligible when viewed from a deeper organizational perspective.

Throughout this series, I propose that mentality develops within a multidimensional landscape of mental-neuronal patterns (MNPs). These patterns constitute the living domain of mentality. Coherence does not replace this landscape, nor does it add another mechanism to it. Instead, coherence describes the evolving organization of the local and distributed interrelations throughout that landscape.

Viewed this way, many existing theories continue to explain important phenomena while coherence helps explain why those phenomena can emerge together as aspects of one living, continually developing mentality.

1. Predictive Processing

What the theory contributes

Predictive Processing has profoundly changed cognitive science by showing that the brain does not passively receive information but continually anticipates it. Prediction becomes a central principle of perception, learning, and adaptive behavior.

What MNPs add

The MNP framework suggests that prediction itself emerges from a more fundamental property of mentality: Pattern Recognition and Completion (PRC). As described in Pattern Recognition and Completion in the Learning Landscape, recognition and completion together constitute the core mechanism of learning. When a distributed mental-neuronal landscape recognizes part of a meaningful pattern, it naturally tends toward completing that pattern. Prediction is therefore not a separate cognitive function but a natural consequence of ongoing pattern completion.

What coherence adds

Coherence goes one step further. Pattern completion never occurs in isolation. Every completed pattern influences, and is influenced by, countless local and distributed interrelations throughout the MNP landscape. Coherence, therefore, explains why some predictions become deeply meaningful while others remain superficial. Prediction becomes one expression of an increasingly coherent organization rather than an isolated computational operation.

New perspective

Seen in this way, Predictive Processing remains entirely valid, yet it becomes part of a broader developmental picture. Pattern recognition and completion explain why prediction arises naturally. Coherence explains how these innumerable acts of pattern completion gradually coalesce into a single living mentality capable of increasingly meaningful anticipation.

2. Bayesian Brain

What the theory contributes

The Bayesian Brain hypothesis proposes that cognition continually updates its beliefs in light of new evidence. From this perspective, perception, learning, and decision-making can often be described remarkably well as probabilistic inference. The theory has provided powerful mathematical tools for understanding many aspects of cognition.

What MNPs add

The MNP framework suggests a different way of looking at what may underlie this Bayesian-like behavior. Rather than literally performing Bayesian calculations, the brain operates as a massively parallel, distributed landscape of interacting mental-neuronal patterns. Countless patterns simultaneously influence one another through multiple soft constraints, integrating past experience, present context, emotions, bodily states, expectations, and many other influences. Bayesian-like updating may then emerge naturally from this distributed organization rather than being explicitly calculated. In this view, the brain is not a Bayesian calculator but a giant pattern recognizer and completer.

What coherence adds

Coherence shifts the focus one level deeper still. It describes how the countless interactions among distributed mental-neuronal patterns become organized into one evolving mentality. Bayesian-like inference is then understood as one possible macroscopic expression of this organization. Just as thermodynamic laws describe the collective behavior of innumerable interacting molecules without implying that individual molecules perform thermodynamic calculations, Bayesian regularities may describe cognition without constituting its underlying organizational mechanism. Coherence explains how the organization of this distributed landscape itself continually develops.

New perspective

Seen from this perspective, the Bayesian Brain hypothesis remains highly valuable as a mathematical description of cognitive behavior. The MNP framework proposes a biologically plausible substrate from which such behavior can emerge, while coherence explains how that substrate becomes organized into one living, continually developing mentality. Rather than replacing Bayesian theory, this perspective may explain why Bayesian-like behavior appears so naturally across many domains of cognition.

3. Connectionism

What the theory contributes

Connectionism transformed cognitive science by showing that intelligence can emerge from distributed networks rather than explicit symbolic rules. Mental processes need not be localized in single units but may arise through the interactions of many simple elements. This represented a major step away from classical symbolic models.

What MNPs add

The MNP framework builds naturally upon this insight. Mental-neuronal patterns are themselves distributed organizations rather than isolated representations. They recognize, complete, and continually influence one another throughout a multidimensional landscape. This gives distributed processing a richer psychological interpretation: the network is no longer merely computational but already consists of meaningful mental organizations.

What coherence adds

Coherence asks a different question. Distributed activation alone does not explain why certain organizations become meaningful while others remain accidental. As explored in The Meaningful Why, meaning belongs primarily to participation within a coherent whole rather than to isolated elements. Coherence therefore describes how the evolving organization of local and distributed MNP interrelations allows distributed activity to become one living mentality. Meaning emerges because patterns participate in an increasingly coherent organization rather than merely activating together.

New perspective

Seen from this perspective, connectionism explains how distributed networks can process information. The MNP framework explains what is distributed: interacting mental organizations. Coherence explains how these organizations continually become integrated into meaningful wholes. The result is not simply distributed computation but distributed participation in one evolving mentality.

4. Dynamical Systems

What the theory contributes

Dynamical Systems Theory transformed the study of cognition by shifting attention from static representations toward continuously evolving processes. Rather than viewing the mind as manipulating fixed symbols, it emphasizes trajectories, attractors, self-organization, emergence, and the continual unfolding of cognitive activity over time. Mind becomes something that remains itself through change rather than despite it.

What MNPs add

The MNP framework provides a richer interpretation of what actually evolves. The trajectories described by Dynamical Systems Theory are not merely abstract mathematical variables but evolving organizations of mental-neuronal patterns. These distributed patterns continually recognize, complete, influence, and reorganize one another within a multidimensional semantic landscape. Dynamics thereby acquire genuine psychological meaning.

What coherence adds

Coherence asks a different question. Dynamical Systems Theory explains how organizations evolve through time. Coherence explains how these evolving organizations become increasingly integrated into viable, meaningful wholes. Multiple soft constraints continually shape the semantic landscape, while attractors describe the relatively stable organizations that emerge within it. Coherence describes the evolving organization of this entire process rather than either the constraints or the attractors alone. One might say that multiple soft constraints describe how coherence is shaped, attractor dynamics describe how coherence lives through time, and coherence itself describes the living organization that continually emerges.

New perspective

Seen from this perspective, Dynamical Systems Theory remains indispensable for understanding cognitive change. The MNP framework gives that change a concrete mental substrate. Coherence explains how dynamically evolving organizations become meaningful and developmentally viable. Intelligence may then emerge not merely through dynamics themselves, but through coherent organizations that increasingly enter into coherence with one another — a process of meta-coherence.

5. Embodied Cognition

What the theory contributes

Embodied Cognition transformed contemporary views of mind by showing that cognition cannot be understood as a process occurring solely within the brain. Thinking develops through the body’s continual interaction with its environment. Perception, movement, action, emotion, and bodily experience all participate in cognition. In doing so, Embodied Cognition represented a decisive step beyond classical Cartesian dualism, demonstrating that mind cannot be detached from bodily life.

What MNPs add

The MNP framework helps explain why embodiment is so fundamental. Mental-neuronal patterns are not isolated neural events but distributed organizations that continuously integrate bodily states, perceptions, emotions, memories, motivations, expectations, and actions. The body is therefore not merely a source of sensory input to the brain. It participates intrinsically in the multidimensional landscape of patterns from which mentality continually emerges. Thinking is embodied because the very patterns that constitute thought already include the body as part of their organization.

What coherence adds

Coherence proposes a further step. Embodied Cognition shows that body and mind cannot be separated. Coherence asks whether separation is the right starting point at all. Rather than two entities that interact closely, body and mind may be understood as two complementary perspectives on one evolving organization. The body is the physical realization of that organization; the mind is its lived, meaningful expression. As illustrated by the metaphor of The Painting and the Paint, the painting is not something added to the paint. It is the meaningful organization of the paint itself. Likewise, mentality is not added to bodily processes. It is the coherent organization of those processes viewed from another explanatory perspective. Organization thus becomes more fundamental than interaction.

New perspective

Seen from this perspective, Embodied Cognition explains why cognition is inseparable from bodily life. The MNP framework explains what is distributed throughout that embodied reality: interacting mental-neuronal patterns. Coherence explains how these distributed patterns continually organize themselves into one living mentality. The question, therefore, shifts. Instead of asking how the mind influences the body—or how the body influences the mind—we may ask how one coherent organization simultaneously appears as bodily physiology and as lived mentality. Embodiment is no longer simply an important feature of cognition. It naturally follows from the way coherent mentality itself develops.

6. Free Energy Principle

What the theory contributes

The Free Energy Principle represents one of the most ambitious attempts in contemporary cognitive science to explain the remarkable diversity of cognition through a single unifying principle. Rather than treating perception, action, learning, attention, memory, development, and adaptation as separate mechanisms, Friston proposes that they can all be understood as manifestations of one fundamental imperative: adaptive systems remain viable by minimizing free energy. This is not merely a mathematical achievement but a profound attempt at theoretical integration.

What MNPs add

The MNP framework provides a richer picture of the substrate within which adaptive regulation unfolds. Free-energy minimization need not be understood as something literally computed by the brain. Instead, countless interacting mental-neuronal patterns continuously influence one another through multiple soft constraints, integrating perception, memory, emotion, bodily states, expectations, and action. The adaptive behavior described mathematically by the Free Energy Principle may naturally emerge from this distributed pattern landscape rather than from an explicit optimization process.

What coherence adds

Coherence introduces a different explanatory direction. Rather than asking how minimizing free energy produces adaptive organization, it asks whether adaptive systems are able to minimize free energy because they already maintain and develop coherent organization. Free energy then becomes not the deepest explanatory principle but one important mathematical expression of organizational integrity. This preserves Friston’s mathematical framework while relocating its explanatory foundation from optimization to organization.

New perspective

Seen from this perspective, the Free Energy Principle remains one of the strongest existing theories of adaptive organization. Coherence does not replace it but asks a complementary question: what makes adaptive optimization itself possible? With coherent organization as the deeper condition, minimizing free energy becomes one important consequence of maintaining coherence rather than its ultimate cause. This perspective also opens new questions concerning meaning, understanding, creativity, intelligence, and developmental openness—phenomena that appear difficult to derive from optimization alone but may emerge naturally from increasingly coherent organization.

7. Symbolic and Neuro-symbolic A.I.

What the theory contributes

Neuro-Symbolic A.I. represents one of the most important contemporary developments in artificial intelligence. Rather than viewing symbolic reasoning and neural learning as competing paradigms, it recognizes that they capture complementary aspects of intelligence. Neural systems contribute learning, adaptation, and pattern recognition, while symbolic systems contribute explicit reasoning, structured knowledge, and formal constraints. Their integration reflects the growing realization that no single abstraction appears sufficient to capture intelligence in its full richness.

What MNPs add

The MNP framework invites a deeper question: where do learning and reasoning themselves originate? Rather than treating them as fundamentally separate processes that must later be connected, the MNP perspective views both as emerging from one multidimensional landscape of interacting mental-neuronal patterns. Pattern recognition, pattern completion, conceptualization, and reasoning arise as different expressions of the same distributed organization. Learning and reasoning therefore need not first be integrated; they already participate in one underlying pattern landscape.

What coherence adds

Coherence shifts the discussion from integration to organization. Neuro-Symbolic A.I. explores how neural and symbolic abstractions can interact productively. Coherence asks what organizational principles govern that interaction itself. Integration alone does not necessarily produce organizational unity. Components may cooperate while still remaining fundamentally separate. Coherence investigates the broader landscape within which different representations, reasoning processes, learning dynamics, and adaptive structures acquire meaning through their participation in one evolving organization. In this perspective, Neuro-Symbolic A.I. explores the edge between neural and symbolic abstractions, while coherence explores the organizational landscape within which that edge becomes meaningful.

New perspective

Seen from this perspective, Neuro-Symbolic A.I. is not an alternative to coherence but one of its most valuable dialogue partners. Neuro-Symbolic A.I. demonstrates that intelligence requires more than isolated abstractions. Coherence asks how those abstractions themselves become organized into meaningful, adaptive, and developmental wholes. The question therefore shifts once more: not simply How can learning and reasoning be combined? but What organizational conditions allow learning, reasoning, meaning, and development to emerge together as expressions of one evolving intelligence?

8. Gestalt

What the theory contributes

Gestalt psychology introduced one of the most influential insights in cognitive science: the mind does not primarily perceive isolated elements but meaningful wholes. A melody remains recognizable despite changes in individual notes, an incomplete figure is immediately experienced as complete, and among many possible organizations, one often emerges as the naturally fitting one — the phenomenon known as Prägnanz. Gestalt thus shifted attention from the parts themselves to the organization through which meaningful wholes appear. It demonstrated that analysis follows an immediate grasp of organized meaning rather than creating that meaning.

What MNPs add

The MNP framework asks what kind of underlying organization allows such meaningful wholes to arise. Rather than emerging from isolated concepts or representations, Gestalts arise from a multidimensional landscape of distributed mental-neuronal patterns that continually recognize, complete, and reorganize one another. Pattern Recognition and Completion (PRC) is therefore not merely a perceptual mechanism but a general organizational principle operating throughout this landscape. Gestalts become understandable as surface expressions of ongoing distributed pattern activity rather than isolated perceptual events. This naturally extends Gestalt beyond perception toward cognition, understanding, learning, and meaning.

What coherence adds

Coherence asks a further question. Gestalt psychology describes that certain organizations appear as particularly meaningful or compelling. Coherence asks why this is so. Rather than viewing Prägnanz simply as a property of certain forms, coherence interprets it as one way in which coherent organization becomes phenomenologically visible. The question shifts from Which wholes appear? to What kind of evolving organization allows such wholes to emerge, stabilize, reorganize, and deepen? In this view, Prägnanz is not replaced but understood as one experiential expression of coherence. Coherence, therefore, extends Gestalt from the perception of organized wholes toward the organizational principles through which meaningful wholes continually develop.

New perspective

Seen from this perspective, Gestalt psychology and Coherence Theory become natural partners. Gestalt discovered that meaningful wholes precede analysis. The MNP framework explains how such wholes emerge from the distributed activity of mental-neuronal patterns. Coherence explains how the evolving organization of the local and distributed interrelations throughout that multidimensional landscape gives rise not only to perceptual Gestalts but also to cognitive insight, learning, meaning, intelligence, and developmental growth. One might therefore say that Gestalt discovered meaningful wholes, while Coherence Theory investigates the deeper organizational processes through which such wholes continually come into being. Rather than competing with Gestalt, coherence may be understood as asking what Prägnanz has been quietly pointing toward all along.

Looking across the theories

The theories discussed above differ considerably in their aims, methods, and domains of application. Some emphasize prediction, others probabilistic inference, distributed processing, continuous dynamics, embodiment, adaptive regulation, artificial intelligence, or the perception of meaningful wholes. Each has substantially advanced our understanding of mentality. The purpose of this comparison has therefore not been to evaluate which theory is ‘best,’ but to explore whether they become even more intelligible when viewed from a deeper organizational perspective.

The MNP framework and Coherence Theory approach these theories from successive explanatory levels. MNPs describe the distributed multidimensional landscape within which mentality develops. Coherence describes the evolving organization of the local and distributed interrelations throughout that landscape. Rather than introducing new mechanisms for each mental phenomenon, coherence asks how apparently different phenomena may emerge as different expressions of one continually developing organization.

Remarkably, the same pattern appears throughout the theories considered here. Each explains an important aspect of mentality. The MNP framework deepens that aspect by identifying the distributed pattern landscape from which it emerges. Coherence then asks how that landscape becomes organized into one viable, meaningful, and continually developing mentality. Gestalt psychology makes this progression especially visible. It reminds us that meaningful wholes precede analysis; coherence asks how such wholes continually emerge, reorganize, and develop throughout the living mental-neuronal landscape. In this sense, coherence does not compete with existing theories. It offers an additional explanatory level through which their individual insights may become increasingly connected.

Theory	Main contribution	What MNPs add	What coherence adds
1 Predictive Processing	Prediction as a fundamental principle of cognition	Pattern Recognition and Completion within a distributed MNP landscape naturally gives rise to prediction.	Prediction becomes one expression of an increasingly coherent organization.
2. Bayesian Brain	Probabilistic belief updating	Bayesian-like behavior emerges from countless interacting patterns constrained by multiple simultaneous soft constraints.	Explains how the organization of those distributed interactions gives rise to Bayesian-like cognition.
3. Connectionism	Distributed neural processing	Distributed processing consists of interacting mental-neuronal patterns with psychological meaning.	Explains how distributed organizations become meaningful wholes rather than merely connected networks.
4. Dynamical Systems	Continuous cognitive dynamics	Dynamics unfold within evolving organizations of mental-neuronal patterns.	Explains how evolving dynamics become increasingly coherent and developmentally viable.
5. Embodied Cognition	Mind cannot be separated from bodily life	Body and brain participate together in one multidimensional pattern landscape.	Body and mind are understood as two complementary perspectives on one coherent organization rather than two interacting entities.
6. Free Energy Principle	Unified adaptive regulation through free-energy minimization	Adaptive regulation emerges from distributed MNP interactions rather than explicit optimization.	Suggests that coherent organization may explain why free-energy minimization naturally occurs.
7. Neuro-Symbolic AI	Integration of neural learning and symbolic reasoning	Learning and reasoning emerge from one distributed MNP landscape rather than two fundamentally separate systems.	Shifts attention from integrating components toward organizing one meaningful developmental whole.
8. Gestalt	Meaningful wholes precede analysis	Gestalts emerge from distributed mental-neuronal patterns that continually recognize, complete, and reorganize one another.	Explains how meaningful wholes continually emerge, deepen, and develop through coherent organization.

Taken together, these comparisons suggest a common direction. Existing theories illuminate important aspects of mentality; MNPs illuminate the distributed landscape within which those aspects arise; coherence illuminates the evolving organization of that landscape. Whether this organizational perspective ultimately proves as broadly applicable as proposed remains an open scientific question. Even so, its ability to deepen several established theories without diminishing their individual contributions suggests that coherence may offer more than simply another theory of mind. It may provide a common organizational language through which many theories become more deeply connected.