1 From Neural Darwinism to Relational Selection
Introduction
Gerald Edelman’s Theory of Neuronal Group Selection (TNGS) offered a bold new framework for understanding the biology of consciousness. In place of the computational metaphor that had long dominated cognitive science, Edelman proposed an evolutionary model: the brain as a selectional system, shaped not by static codes but by the dynamic history of embodied interaction.
But what if we reframed Edelman’s already processual model through the lens of relational ontology? What if the brain’s evolution and functioning were not grounded in fixed mechanisms or linear causation, but in the unfolding of potential within a system of dynamic relational constraints?
In this post, we introduce a relational reading of TNGS — one that sees the brain not as a machine for representation, but as a meaning-bearing structure of attractor landscapes, where neuronal groups evolve, stabilise, and reorganise through patterns of selection, resonance, and actualisation.
The Core of TNGS: Variation, Selection, and Reentry
At the heart of TNGS lies a tripartite structure:
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Developmental Selection: During development, a diversity of neuronal groups is formed. Synaptic connections are overproduced, and then pruned based on experience and activity.
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Experiential Selection: Across a lifetime, certain neuronal groups are selectively stabilised through interaction with the environment. The brain learns not by storing representations, but by strengthening the functional coordination of groups that have co-activated in meaningful contexts.
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Reentrant Signalling: A distinctive hallmark of TNGS is reentry — the recursive, bidirectional signalling between neuronal maps that allows for the dynamic integration of sensory, motor, and conceptual domains. Consciousness, for Edelman, is not localised but emerges from this ongoing reentrant coordination.
This model already gestures away from static causation toward process, pattern, and embodied context. But it still retains a kind of biological realism — a view of neural groups as mechanistic entities whose properties are objectively determined. Our goal in this series is to gently shift that frame.
Toward a Relational Reading: Systems of Potential and Constraint
From a relational ontology, the key units of analysis are not things, but relations — not entities with pre-given properties, but systems of potential whose structure is actualised through interaction.
This leads to several interpretive shifts:
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Neuronal groups are not fixed functional modules, but regions in a dynamic field of potential, shaped by historical trajectories of activation and coordinated selection. They have no intrinsic meaning apart from their participation in wider patterns of interaction.
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Selection is not imposed from outside, but emerges within the system as a reconfiguration of attractor topologies. Certain trajectories become more likely — not because they are coded, but because they are resonant with the evolving structure of the system.
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Reentry is more than feedback; it is relational self-reference, a recursive actualisation of patterns across timescales. It embodies the semiotic principle of metaredundancy: the integration of meaning through patterned repetition across strata of experience.
Under this lens, the brain becomes a system of relational modulation: a semiotic structure whose “neural dynamics” are patterns of meaning potential constantly reshaped by interaction — not only with the material world, but with the organism’s own evolving symbolic system.
Attractors in Neural Meaning Space
The notion of attractors offers a powerful tool for reinterpreting neural selection in relational terms.
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In Edelman’s original model, selection stabilises certain circuits — those that have proven effective or coherent within the organism’s environment.
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In the relational reading, this stabilisation is the formation of an attractor: a configuration in a space of relational potential that draws future actualisations toward itself.
These attractors are not things; they are semiotic tendencies — patterns of resonance that increase the likelihood of certain activations over others. They encode not information, but relational probability: the patterned modulation of possible futures based on the trajectory of past meaning.
Learning, then, is the shifting of attractor landscapes. Consciousness is not a product of complexity, but a relational coherence among dynamically co-evolving attractors — a resonance among multiple scales of actualised potential.
Looking Ahead
In this first post, we’ve laid the groundwork for a relational re-reading of Edelman’s Theory of Neuronal Group Selection. What emerges is a vision of the brain as:
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A semiotic system of potential and constraint
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A selectional topology modulated by interaction
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A relational field of attractors shaped by history
In the next post, we’ll explore what it means to describe the brain not just as a material system, but as a semiotic architecture — one whose meaning potential is stratified, dynamically coordinated, and open-ended.
2 The Brain as Semiotic Architecture
Introduction
If the brain is a relational system of attractors, what kind of structure does it possess? What kind of system is it? In this post, we explore the idea that the brain is not simply a biological mechanism, but a semiotic architecture: a layered system in which meaning potential is stratified, coordinated, and selectively actualised through recursive interaction.
To reframe Edelman’s neural model in semiotic terms is not to ignore its materiality — but to reinterpret that materiality as a dynamic order of meaning-bearing structure. The brain, on this view, is not a substrate beneath consciousness; it is the material instantiation of a semiotic system that both constrains and is reshaped by the meanings it helps bring into being.
From Neural Structure to Meaning Potential
In traditional neurobiology, structure is often understood in spatial and anatomical terms: neural regions, circuits, synapses. But from a relational semiotic perspective, structure is not what a system is, but what a system makes possible.
A neuronal group is thus not simply a cluster of neurons; it is a region of potential meaning, formed through prior trajectories of interaction. Its “structure” is its affordance: the ways in which it participates in and modulates the unfolding of systemic meaning.
This invites us to interpret the brain’s architecture in terms of stratified semiotic orders:
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At one level, we have material interactions — synaptic signalling, firing patterns, molecular modulations.
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At another, we have dynamic constraints — attractor patterns, reentrant loops, distributed synchrony.
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And at a higher-order level, we find semiotic coordination — patterned actualisations of meaning potential across time, place, and scale.
These layers are not separate domains, but relational strata: each constrains and is constrained by the others, in a co-evolving architecture of potential and actualisation.
Stratification and Realisation in Neural Systems
Here we may borrow a key insight from Systemic Functional Linguistics: that semiotic systems are stratified, with higher levels of meaning realised through patterns at lower levels.
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In language, meaning (semantics) is realised through wording (lexicogrammar), which is in turn realised through sounding (phonology).
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In the brain, we might say: dynamic meaning potential is realised through neural coordination patterns, which are realised through material activity.
This is not reduction, but realisation — a relation between levels of abstraction. Each stratum makes the next possible, while constraining its range of realisation. And each instance of meaning reshapes the potential that gave rise to it.
Thus, the brain becomes not merely an organ of perception or action, but a semiotic interface: a site at which different orders of meaning (material, dynamic, conscious) are brought into coordinated relation.
Reentry as Metaredundancy
Edelman’s notion of reentry — the recursive signalling among distributed neural maps — can now be seen in a new light.
Reentry is not simply feedback. It is the mechanism of coherence in a stratified semiotic system.
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It enables different regions to coordinate in the absence of central control.
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It establishes metaredundancy: patterned repetition of meaning potential across domains.
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It actualises systemic coherence: the alignment of multiple strata of potential in a single act of meaning.
Reentry, in short, is the neural form of resonance — the process by which distributed attractors align, stabilise, and co-actualise meaning. Consciousness may thus arise not from isolated complexity, but from the relational coherence of attractor systems resonating across strata of the brain’s semiotic architecture.
From Representation to Resonance
Traditional cognitive science sought to understand the brain through the metaphor of representation: information encoded in discrete units, manipulated by internal rules. Even Edelman, in rejecting this metaphor, retained a kind of functional mapping.
But a relational semiotic perspective suggests a more radical shift: from representation to resonance.
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Neuronal groups do not “stand for” things; they resonate with patterns of experience and meaning.
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Learning is not storage, but the modulation of potential through history.
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Consciousness is not computation, but relational coherence among attractor trajectories.
The brain becomes a resonant field, not a representational machine.
Looking Ahead
In this post, we have reframed the brain as a semiotic architecture — a stratified system in which meaning potential is dynamically constrained and actualised through recursive interaction. This view opens the door to new interpretations of memory, emotion, intention, and selfhood — all not as “functions” located in modules, but as patterns of relational resonance emerging from systemic potential.
In the next post, we’ll explore how development and learning can be understood in terms of attractor formation and reorganisation — and how the shaping of neural potential over time gives rise to the individuation of meaning.
3 Development, Learning, and the Shaping of Meaning Potential
Introduction
If the brain is a semiotic architecture composed of attractor systems, then development and learning must be the processes by which these attractor landscapes are shaped, deepened, and diversified. In this post, we reinterpret Edelman’s Theory of Neuronal Group Selection (TNGS) in terms of relational individuation: the emergence of patterned potential through interaction, constraint, and resonance.
This reframing allows us to see neural development not as the gradual construction of fixed capabilities, but as the emergence of a system capable of instantiating meaning across an expanding horizon of experience. Learning, then, is not the acquisition of content, but the dynamic reorganisation of relational potential.
From Selection to Individuation
TNGS is built on three key processes:
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Developmental Selection: The overproduction of neuronal groups followed by selective pruning based on structural and molecular cues.
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Experiential Selection: The strengthening and weakening of connections based on use and success in behavioural context.
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Reentrant Mapping: The recursive coordination of activity across diverse regions of the brain.
Each of these processes can now be interpreted as a mode of individuation:
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Developmental selection produces the initial condition of potential — a richly diverse system of possible pathways, primed for experience.
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Experiential selection shapes this potential through interaction with meaning — pruning, reinforcing, and reconfiguring the system in response to unfolding patterns.
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Reentry ensures that meaning emerges not locally, but systemically — that every act of meaning draws upon, and modifies, the coherence of the whole.
This shifts our focus from selection as elimination to individuation as differentiation: a process through which a unique system of meaning potential comes into being through its history of resonance.
Attractors as Trajectories of History
In this reframing, an attractor is not a static state the brain falls into. It is a trajectory of coherence: a patterned tendency for certain relational configurations to stabilise under specific conditions.
Each attractor embodies:
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A history of selections: actualisations that have shaped its emergence.
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A range of modulation: the degree to which it can be flexibly invoked or altered.
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A resonance with others: the extent to which it coheres or competes with other attractors in the system.
To learn, then, is to shape attractors — not just in their strength, but in their relations: which co-occur, which inhibit, which scaffold others. The brain becomes a history-bearing system: a semiotic field structured by trajectories of instantiation and transformation.
Plasticity as Potentiality
Neural plasticity is often described as the brain’s capacity to change. But from a relational perspective, plasticity is better understood as the capacity to maintain and reshape potential.
This includes:
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The capacity to generalise: to abstract relational patterns from specific instances.
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The capacity to differentiate: to form more precise distinctions within a patterned space.
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The capacity to integrate: to coordinate multiple attractors into new systemic configurations.
Plasticity is thus not simply malleability; it is the semiotic vitality of the brain: its ability to remain a living system of meaning potential, always open to new patterns of coherence.
Individuation of Meaning
Each brain develops through a unique trajectory of interaction — not only with the physical environment, but with the semiotic universe of others: caregivers, cultures, communities of practice.
Thus, the meaning potential of an individual brain is shaped not only by its own selections, but by its place within systems of meaning larger than itself. In Hallidayan terms, this is the process of individuation: the emergence of a unique semiotic repertoire from the interplay of:
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Collective potential (e.g., language, gesture, affect systems)
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Individual potential (e.g., the developing system of neural attractors)
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Instantiations (e.g., specific acts of meaning within context)
The brain is not a private organ of cognition. It is a public system of potential that resonates with and within a social-semiotic ecology. Every learning event is both personal and collective: a tuning of the brain’s attractors in relation to shared systems of meaning.
Looking Ahead
In this post, we have reframed development and learning as the relational shaping of semiotic potential: a process of individuation through interaction, resonance, and historical selection. The brain emerges not as a machine for information processing, but as a co-evolving attractor landscape, open to modulation by the patterned regularities of experience.
In the next post, we’ll explore how this framework helps us reinterpret emotion, attention, and value — not as modules or states, but as attractor regimes that shape the system’s orientation toward meaning.
4 Emotion, Attention, and Value as Attractor Regimes
Introduction
If the brain is a relational system of neuronal attractors shaped by history and interaction, then its modes of orientation — how it cares, attends, and values — cannot be treated as separate systems or modules. They are attractor regimes: dynamic patterns of activation that coordinate the system’s engagement with its world.
This post reinterprets emotion, attention, and value not as internal states or computations, but as emergent properties of the brain’s semiotic landscape. These regimes do not reflect the world; they enact a relational stance toward meaning. In this view, orientation to meaning is not an add-on to cognition — it is the very condition of becoming semiotic.
Emotion as Relational Attractor
Emotion is often understood as either a biological response or a psychological feeling. But within a relational ontology, it is more fundamentally a modulation of potential — a patterned shift in the attractor landscape of the brain that organises how the system is disposed to act, perceive, and mean.
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Emotion is not a signal about the world; it is a shaping of the space of relevance.
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It configures what becomes salient, what counts as threat or opportunity, and what patterns are available for selection.
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Emotions are systemic dispositions — global shifts in the resonance conditions of the neural architecture.
In this sense, an emotion is not a thing we have, but a mode of being-with: a way the brain-body system is pulled into particular semiotic trajectories under conditions of contingency.
Attention as Dynamic Constraint
Attention, like emotion, is usually treated as a mechanism: a spotlight, filter, or resource. But within a relational framework, attention is better seen as the dynamic constraint of potential — the selective tuning of the system’s attractors to stabilise certain configurations of meaning.
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Attention is not imposed from outside the attractor space; it emerges within it, as attractors compete or cohere under systemic modulation.
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What we attend to is not simply what stands out, but what resonates: what draws coherence from the system’s current structure of readiness.
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In this sense, attention is the semiotic tension between openness and focus: the act of becoming-actual within a field of potential.
Just as emotion shapes what matters, attention shapes what is realised — and both operate by shifting the relational dynamics of attractor formation.
Value as a Gradient of Meaning Potential
In the classic computational model, value is assigned through reward signals, utilities, or cost functions. But in the relational ontology, value is not external to meaning — it is the gradient of resonance across the attractor landscape.
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Value is not given; it emerges through the history of modulation: what has cohered in the past, what has deepened the system’s resonance with itself and its environment.
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A high-value configuration is one that tends to attract coherence: it sustains systemic stability or opens generative pathways of transformation.
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Value is thus not prior to meaning; it is inseparable from the system’s patterning of what counts as meaningful.
From this perspective, to value is to weight potential — to tilt the field of instantiation toward some semiotic futures over others.
Regimes of Orientation
Together, emotion, attention, and value form regimes of orientation: interdependent patterns of modulation that structure how the brain inhabits its own semiotic field.
These regimes are not added to the system post hoc. They are part of what makes it a system of meaning:
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Emotion = modality of relational stance
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Attention = trajectory of instantiation
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Value = gradient of pattern viability
Such regimes help us understand why no act of cognition is ever neutral. Every perception, inference, or thought is situated in a landscape of potential shaped by how the system is moved, drawn, and oriented — not by logic alone, but by the history of its resonant engagements.
Looking Ahead
In this post, we explored the role of attractor regimes in shaping how the brain orients itself toward meaning. We saw that emotion, attention, and value are not separable from cognition; they are semiotic modes of coherence, embedded in the system’s dynamic unfolding.
In the next post, we’ll move from orientation to integration — asking how consciousness itself might emerge not as a substance or module, but as a metastable phase in the relational dynamics of attractor landscapes.
5 Consciousness as a Metastable Phase of Semiotic Integration
Introduction
If cognition is a history of resonance, and if emotion, attention, and value are attractor regimes modulating meaning potential, then consciousness may be understood not as a place in the brain, nor as a discrete state, but as a metastable phase of integration — a phase in which diverse attractors temporarily cohere to instantiate a semiotic unity.
In this post, we explore consciousness as a relational phenomenon: an emergent coordination of distributed meaning potentials into a transient but coherent field. In doing so, we move beyond metaphors of representation or internal spectatorship and toward a dynamic view of being-with-the-world as a recursive instantiation of meaning.
Beyond the Homunculus: From Representation to Instantiation
Traditional models often treat consciousness as the result of internal representations being ‘viewed’ by a hidden observer. But such a view simply relocates the problem: who is doing the viewing? What counts as being conscious of a representation?
A relational ontology reframes the question:
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The system does not represent the world; it instantiates meanings within it.
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Consciousness is not a spotlight shining on content; it is the coherence of a pattern — a moment in which divergent potentials align into a semiotic phase.
This shift is profound: from explaining consciousness as a thing in the brain, to understanding it as a pattern of relation between brain, body, and world — a real-time attractor of coherence.
Metastability and the Coherence of Experience
Neuroscientific models increasingly describe the brain as a metastable system: one that can flexibly coordinate between integration and segregation, between global coherence and local specialisation.
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Consciousness may be the metastable regime in which multiple attractors resonate across levels — neural groups, bodily states, affective stances, and sensorimotor engagements.
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In this phase, no single attractor dominates; instead, the system maintains a delicate balance — a synchronised heterogeneity — that enables ongoing actualisation.
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This coherence is not static: it unfolds as waves of integration, entraining the dynamics of thought, feeling, and perception into a co-constituted now.
Thus, consciousness is not an entity but a phase of relation: a temporally extended coherence of meaning potential under constraint.
Semiotic Integration and the Self
From a relational perspective, the self is not a substance but a patterned attractor — a history of coherence across contexts.
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The self is not behind consciousness but arises within it, as a relatively stable centre of semiotic integration across time.
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This integration is modulated by value (what matters), emotion (how the system is disposed), and attention (what becomes instantiated).
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Consciousness, then, is not merely awareness of something — it is being patterned by relevance, across a resonant system.
In this view, consciousness and selfhood are emergent foci of coherence within a multidimensional relational field. They are not givens, but ongoing achievements of the system’s capacity to weave meaning from potential.
Consciousness as Actualisation under Constraint
If the brain is a meaning-making system, and consciousness is a metastable phase of coherence, then conscious experience is a moment of actualisation under dynamic constraint.
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Constraint is not limitation; it is the shaping of potential — the way certain meanings are pulled into actuality.
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Consciousness is the site where multiple constraints — bodily, neural, affective, environmental — interpenetrate to form a temporary centre of pattern.
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As such, it is not purely internal. It is distributed across organism and world, and semiotically modulated by value-laden histories of engagement.
This reconception of consciousness aligns closely with the systemic-functional principle that meaning is always situated, never abstracted from context, and always shaped by the ongoing interplay of potential and actual.
Looking Ahead
In this post, we reframed consciousness as a metastable attractor phase: a coherent unfolding of semiotic potential under constraint. Consciousness is not the endpoint of cognition but a phase of maximum integration — a recursive resonance that brings together emotion, value, history, and context into a temporarily unified act of meaning.
In the next post, we’ll consider how this relational account of consciousness might shift how we understand the brain as a whole — not as a control centre, but as a semiotic ecology of attractors, co-constituted by its history, its body, and its world.
6 The Brain as a Semiotic Ecology
Introduction
Having reinterpreted consciousness as a metastable attractor of semiotic coherence, we now turn our gaze to the brain itself. No longer seen as a command centre or a symbol-manipulating machine, the brain is reconceived as a semiotic ecology: a living system of attractor landscapes shaped by history, value, and interaction.
In this post, we integrate Edelman’s theory with a relational ontology of meaning, drawing out its radical implications: the brain is not a passive receiver of stimuli or a central processor of representations — it is an evolving, recursive network of meaning potential, continuously reorganised by its own history of actualisation.
The Brain as a System of Constraints on Meaning Potential
The neuronal groups posited by Edelman are not static building blocks but evolving fields of constraint — networks that modulate what is possible in the system’s semiotic trajectory.
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These groups form dynamic populations, whose selection and re-selection over time shape the brain’s potential for future actualisation.
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Each neuronal group can be thought of as a semiotic filter — a field that modulates the relation between meaning potential and meaning instance, between history and now.
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The system doesn’t compute outputs from inputs; it enacts meanings, actualising some potentials while holding others in tension.
The brain, then, is not a structure that contains meaning — it is a topology of constraints through which meaning emerges.
Degeneracy as Relational Diversity
A core concept in Edelman’s theory is degeneracy: the capacity for structurally different elements to produce functionally similar outputs.
In a relational ontology:
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Degeneracy reflects the multiplicity of pathways through which a meaning potential may be actualised.
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It enables robustness without rigidity: the system can adapt flexibly, not because it knows the rules, but because its attractor landscape affords many possible routes through a shared field of value.
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This relational diversity is a condition of possibility for learning, creativity, and resilience.
Rather than reducing function to form, degeneracy reflects the irreducibility of relation — the fact that meaning does not inhere in any single component but in the configuration of the whole.
Recursive Constraint and the Evolution of Potential
In Edelman’s model, each act of selection feeds back to modulate future selections — a recursive loop of learning and restructuring. This dynamic is deeply compatible with a relational semiotic view:
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Every meaning instance alters the attractor landscape of the system: the instance becomes potential.
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The brain’s structure is not fixed but history-bearing — its pathways of activation are continuously shaped by what has been actualised.
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In this sense, the brain is not a map of the world but a history of worlding — a living archive of constraints that pattern future becoming.
The brain is not a meaning-maker on its own; it is a resonant node in the unfolding of meaning across organism and world.
Value, Affect, and the Tuning of Attractors
Selection is not neutral. What is selected is shaped by what matters — by value, emotion, and bodily engagement.
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Edelman emphasises the role of value systems in tuning neural dynamics. From a relational perspective, these are attractors of significance — regimes that weight the field of potential in favour of relevance.
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Affect is not noise; it is the modulation of potential by care.
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The brain's attractor dynamics are not only shaped by physical constraints but by semiotic tensions — what the system tends toward, resists, or longs for.
Thus, neural selection is not just about surviving — it is about orienting toward meaning, guided by histories of what has mattered before.
A Brain-World Coupling: The Extended Semiotic System
In a relational ontology, the boundary of the brain is not a limit to meaning.
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The brain is coupled to the body, the environment, and the semiotic systems (language, culture, interaction) that shape its becoming.
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Meaning is not made in the brain but through the brain — in its recursive, resonant engagements with a world that is already saturated with significance.
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The brain is thus not a control centre, but a semiotic organ — a living attractor field for the actualisation of meaning potential in context.
This vision aligns with systemic functional linguistics: the brain does not contain language; it instantiates meanings through the embodied enactment of patterned systems.
Looking Ahead
In this post, we’ve reframed the brain as a semiotic ecology: a resonant attractor landscape whose dynamics are shaped by recursive selection, degeneracy, value, and constraint. It is not a machine, but a meaning-making system — one that participates in, rather than commands, the unfolding of a semiotic world.
In the next and final post of this series, we will synthesise these threads and ask what this relational reframing of neural dynamics, cognition, and consciousness might imply for broader inquiries into human meaning, learning, and transformation.
7 Toward a Relational Neuroscience of Meaning
Introduction
This series has taken us through a reimagining of the brain and consciousness, grounded in a relational ontology and enriched by Edelman's theory of neuronal group selection. In this final post, we reflect on what this synthesis makes possible. What happens when neuroscience is no longer asked to explain how the brain generates meaning, but is itself reconceived as a science of meaning — one whose objects are not mechanisms, but metastable attractors of patterned possibility?
Here we sketch the contours of a relational neuroscience of meaning — not as a finished framework, but as an open horizon for further inquiry.
From Substance to Relation
Traditional neuroscience often treats the brain as a material system that processes information about the world — as if meaning were a passive representation of a reality “out there.” In contrast, our relational model suggests:
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The brain is a history-bearing topology: a network of patterned constraints shaped by past actualisations of meaning.
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Consciousness is not a thing that resides in the brain but a semiotic field — a metastable configuration of relations that spans organism, environment, and symbolic system.
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Neuronal activity is not computation in the abstract, but the material modulation of potential, resonating across multiple levels of organisation.
In short, the brain is not an object that has meaning — it is a relational node through which meaning is enacted.
Semiotic Plasticity and the Coevolution of Systems
Edelman’s concept of reentrant mapping — recursive signalling between neuronal maps — supports a view of the brain as modular without being fixed. Each subsystem is dynamically reconfigurable in relation to the whole.
In a relational ontology:
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This reflects a system of semiotic plasticity — the ability of the brain to reorganise its constraints in response to meaning-laden interaction.
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Such plasticity is not random but patterned by value: the system’s attractor landscapes evolve in response to what has mattered before.
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This allows for coevolution between brain, body, environment, and semiotic system — a continual reconfiguration of what is possible, meaningful, and real.
The brain thus participates in the collective transformation of the meaning potential it helps to instantiate.
Beyond Internalism: The Extended Semiotic Field
One of the most powerful implications of this model is the rejection of internalism. Cognition is not bounded by the skull. In relational terms:
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The brain is a resonance chamber, not a container — an organ that tunes itself to the semiotic structures within which it is embedded.
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Language, gesture, cultural practice, and social interaction are not inputs to a cognitive system; they are co-constitutive strata in the unfolding of meaning.
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To understand the brain, we must therefore understand the semiotic ecologies in which it develops and functions.
This is not simply an “extended mind” thesis — it is a shift to an extended ontology, where all cognition is situated within the evolving dynamics of worlding.
Meaning, Memory, and Becoming
From a relational standpoint, memory is not the storage of information but the conservation of pattern — a way of modulating present potential in light of past actualisation.
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Memory is not located in a place, but distributed across attractor landscapes.
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These landscapes are sculpted by selection histories: trajectories of what has mattered, been valued, or been reinforced.
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Every new experience is filtered through and reconfigures this landscape — the now is always shaped by a relational past.
This dynamic is the very condition of becoming — the system’s ongoing transformation of itself through meaning.
A Science of Situated Transformation
What, then, is the role of neuroscience in a relational ontology?
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Not to reduce mind to matter, or to discover hidden mechanisms, but to trace the patterned relations by which meaning becomes actual.
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To map the trajectories of constraint and potential that give rise to consciousness — not as an object, but as a patterned field.
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To understand human transformation not as a property of individual brains, but as the evolution of semiotic attractors in collective life.
In this vision, neuroscience becomes a science of situated transformation — one that recognises the brain as a living participant in the unfolding of reality-as-meaning.
Conclusion: The Brain in the Universe of Meaning
With this series, we have repositioned the brain within a wider relational cosmos — not as a source of meaning, but as a semiotic participant, evolving in concert with the histories, systems, and signs that shape its world.
Edelman’s insights into neural selection, degeneracy, value, and reentrant mapping have served as a generative scaffold, allowing us to reinterpret the brain as an attractor-field of potential meaning.
In doing so, we find that the boundary between neuroscience and semiotics is not a barrier but a bridge. And as that bridge is crossed, new vistas open — not only for science, but for the deep understanding of what it means to be a living, learning, meaning-making being.