🌀 Evolutionary Adaptive Cognition: Autism, Trauma, and the Ecology of Mind
Beyond Diagnosis: Toward a Recursive, Relational Understanding of Cognition
Positionality & Epistemic Grounding
Before we begin, let me be clear about who’s speaking and how I hold this space.
I approach this work through a framework of liberation pedagogy and a commitment to epistemic justice. That means I believe knowledge is not something to extract or control—it is something to co-create. Lived experience, especially from the margins, is not a secondary form of data—it is a primary site of truth.
My focus is neurodevelopment, cognition, and trauma—not as isolated categories, but as emergent, relational, adaptive systems. I work from a complexity science lens, asking how bodies and minds respond to overwhelming or incoherent environments—not just how they function under controlled conditions.
That said:
I am not a reductionist.
I do not believe gene expression explains the soul.
I’m not here to decode autism down to molecules.
I am a Cognitive Ecologist. I’m here to ask: What does it mean to be a mind in the world?
Especially a mind shaped by friction, intensity, and unmet needs.
This is not a conclusion. It’s an open-loop hypothesis—an offering in diunital logic, where paradox can live without being resolved. I believe multiple, even contradictory truths can exist simultaneously—because we are not studying machines. We are studying living systems.
I also want to say this plainly:
When you say “autism” and “evolution” in the same sentence, people get uncomfortable. That discomfort is valid. The phrase carries the weight of eugenics, abuse, and historical trauma. I reject any framing that suggests worth is tied to utility, or that cognitive variation must justify itself through evolutionary logic.
This is not that.
This is about asking:
What if autism—at least for some people—is not a fixed condition, but an emergent adaptive response?
What if what we call disorder is sometimes a system recalibrating under stress?
What if what looks like breakdown is actually the start of a different kind of coherence?
These are not answers. They are questions held in motion.
And I hold them as an autistic person in an autistic body-mind.
Not from the outside.
Not as an observer.
But from inside the system—trying to name what it feels like to live in tension with the world, and to still be alive to its beauty.
I hold this space with compassion, with complexity, and with care. I expect you to do the same.
I am autistic.
And I deserve to be treated like a human being.
Shall we begin?
I. Introduction: The Emergence of a New Paradigm
Autism has long been framed through the lens of deficit—a static neurodevelopmental disorder characterized by impairments in social communication and restrictive behaviors (American Psychiatric Association, 2013). However, emerging genetic and systems-level research calls for a profound reframing. In 2025, a large-scale study from Princeton University presented compelling evidence that autism is not a singular condition, but a diverse collection of developmental trajectories, each shaped by unique patterns of gene expression, environmental sensitivity, and temporal dynamics (Litman et al., 2025). By leveraging phenotypic data from over 5,000 individuals in the SPARK cohort, the researchers identified four distinct classes of autism, each with its own genetic architecture, clinical profile, and developmental timing.
These findings reinforce a growing body of work suggesting that autism’s heterogeneity is not merely a complication to be reduced, but an intrinsic feature of its biological and developmental nature (Warrier et al., 2018; Lombardo, Lai, & Baron-Cohen, 2019). In other words, what we observe as “symptoms” may instead be adaptive strategies, emergent responses to early stressors, sensory landscapes, or relational incoherence.
This paper proposes a radical thesis: that autism—and potentially other forms of neurodivergence—may not be fixed, pathological states, but emergent, complex adaptive responses to environmental and developmental challenges. Rather than residing solely in the brain, autism may be the expression of a living system, shaped recursively by genes, experiences, relationships, and context.
To investigate this, we adopt a lens from complexity science—a transdisciplinary framework used to understand nonlinear systems characterized by feedback loops, attractor states, and emergent behavior (Mitchell, 2009). Complexity science allows us to treat cognition not as a linear process but as a self-organizing ecology, in which minute perturbations during critical periods (such as trauma, care, or environmental mismatch) can significantly alter a child’s cognitive and developmental trajectory (McEwen & Morrison, 2013).
Our aim is to synthesize current findings from neuroscience, genetics, trauma theory, ecological psychology, and developmental systems theory. Drawing from both empirical research and systems metaphors, we argue that the autistic mind is not an error but an expression of a wider ecological intelligence—one that evolves, adapts, and recalibrates in response to both coherence and chaos.
In doing so, we hope to offer not just a new framework for autism, but a new understanding of cognition itself: as a recursive, relational, and deeply adaptive process. This reframing has implications not only for diagnosis and care but also for how society recognizes, nurtures, and supports wild minds—those whose forms of knowing may lie at the edge of the human future.
II. Complexity Science and Nonlinear Development
To understand autism as an adaptive process, we must move beyond static models of the brain and embrace the principles of complexity science. Complexity theory, as articulated by scholars like Mitchell (2009), deals with systems that are open, dynamic, and far from equilibrium. Such systems exhibit nonlinear behavior, meaning that small changes in input can lead to disproportionately large changes in output—a concept essential to understanding the diversity of cognitive outcomes in neurodevelopment.
In this framework, the brain is not a pre-programmed computational machine but a self-organizing, adaptive system, continually shaped by its internal states and environmental interactions (Clark, 2008). From prenatal gene expression to postnatal relational patterns, the nervous system engages in recursive feedback loops, adjusting its architecture in real-time in response to stimuli, affect, and experience (McEwen & Morrison, 2013). This recursive nature makes the brain exquisitely sensitive to initial conditions—especially during critical periods of development when plasticity is highest.
Nested Systems and Multi-Level Inputs
Cognitive development unfolds through nested systems, where genetic, epigenetic, neurobiological, and relational layers interact to shape the architecture of the mind (Zhang & Meaney, 2010). A supportive relational environment can amplify neural resilience; conversely, early-life stress can lead to cascading dysregulation across neural, endocrine, and immune systems (Teicher et al., 2014). These interactions are not additive—they are multiplicative, nonlinear, and context-sensitive.
In the Princeton study, Litman et al. (2025) provide compelling evidence for this systemic interaction: different classes of autism were not just genetically distinct but also developmentally distinct, with their associated gene sets being expressed during different windows of brain maturation. For example, genes associated with the Mixed ASD with DD class were highly active during fetal neurodevelopment, while those in the Social/Behavioral class were expressed predominantly after birth. This finding underscores how timing functions as a bifurcation point in cognitive development.
Developmental Bifurcations and Attractor States
In dynamic systems theory, an attractor state is a pattern toward which a system tends to evolve. The brain, too, can be understood as existing within a landscape of developmental attractors—configurations of neural function that stabilize over time. During early development, the system is more plastic and capable of transitioning between states. But as experiences reinforce specific neural pathways, those paths become entrenched, forming the basis of a cognitive “style” or neurotype (Thelen & Smith, 1994).
In such a system, tiny perturbations—a lack of secure attachment, sensory overload, or early neglect—can serve as bifurcation points, diverting the system toward very different attractor basins. These are not necessarily pathological. They may represent adaptive reorganizations suited to specific environmental constraints. For example, heightened sensory sensitivity might arise as an attunement mechanism in a chaotic or unpredictable environment.
In this view, autistic traits may not reflect internal dysfunction but external adaptation—a recalibration of the brain’s attractor landscape in response to systemic incoherence.
Recursive Feedback and Nonlinear Outcomes
One of the most powerful aspects of this model is its explanation of phenotypic variability. As Litman et al. (2025) demonstrate, individuals with similar genetic variants may exhibit vastly different clinical profiles depending on the timing of gene expression, the presence of co-occurring stressors, and the relational environment. This supports a nonlinear, person-centered model of neurodevelopment, where traits are not fixed outcomes but emergent phenomena shaped by recursive feedback loops.
Moreover, these recursive processes do not end in childhood. They continue throughout the lifespan, with neural circuits adapting to new environments, relationships, and meaning-making strategies (Herring et al., 2022). This makes diagnosis based on static traits not only inadequate but ontologically inaccurate—because cognition is not a trait but a process.
III. Genetic Potential as Latent Capacity
Modern neuroscience is gradually shifting away from deterministic models of genes as unidirectional “blueprints” for behavior. Instead, we are beginning to understand genes as part of a conditional system—a complex web of possibilities shaped by timing, context, and interaction (Zhang & Meaney, 2010). This framing aligns with the core insight of the 2025 Princeton study: that autism is not a uniform condition, but a set of phenotypically distinct classes, each governed by specific gene expression profiles with distinct temporal and cellular signatures (Litman et al., 2025).
Radial Glia and Developmental Architecture
Among the most striking findings of the study is the identification of cell-type-specific alternative splicing events concentrated in radial glia—neural progenitor cells that play a pivotal role during fetal brain development (Litman et al., 2025). Radial glia act as scaffolds and guides for migrating neurons, forming the layered architecture of the cortex. Genes associated with the Mixed ASD with DD class were especially enriched for expression in these cells during prenatal windows, suggesting that disruptions in this early scaffolding phase can lead to long-term structural and functional divergence.
What matters here is not just the presence of genetic variants, but when and where they express. In other words, a genetic variant may have minimal effect if expressed postnatally, but major consequences if expressed during critical periods of cortical layering. This challenges static models of heritability and pushes us toward a developmentally situated genomics.
Genes are not scripts. They are conditional programs—activated or silenced depending on the system’s recursive feedback with its environment (Clark, 2008).
Alternative Splicing as Systemic Flexibility
The Princeton study also highlighted the role of alternative splicing—a process by which a single gene can produce multiple proteins depending on cellular context. This molecular flexibility echoes the macro-scale flexibility of cognition itself: just as a gene can take multiple forms depending on conditions, so too can cognitive outcomes diverge under the influence of stress, care, and environment.
This molecular complexity helps explain how similar genetic variants can manifest in radically different ways—depending not only on co-occurring mutations, but on epigenetic markers, hormonal profiles, and developmental timing (McEwen & Morrison, 2013; Herring et al., 2022).
Genetic Variants as Conditional Affordances
In ecological psychology, the concept of an affordance refers to what the environment offers to an organism based on its capacities (Gibson, 1979). Here, we reframe genetic variants not as defects, but as conditional affordances: latent potentials that may emerge or remain dormant depending on the system’s overall configuration.
In this view:
A “risk” allele for autism is not universally pathogenic—it may confer heightened pattern recognition, sensory sensitivity, or moral clarity in one context, and cognitive dysregulation in another (Warrier et al., 2018).
These affordances interact with trauma, care, and sensory coherence to determine what form the system stabilizes into.
The gene is not destiny—it is a fork in the road, whose path depends on the quality and coherence of surrounding systems.
The Cognitive Bifurcation Model
To capture this, we propose a metaphor from complexity science: cognitive bifurcation. During early development, the brain exists in a fluid state, capable of moving toward multiple attractor basins. Epigenetic stressors—such as chronic dysregulation, emotional neglect, or prenatal inflammation—can push the system past a threshold, forcing it to settle into a different developmental trajectory (Zhang & Meaney, 2010; Teicher et al., 2014).
In some cases, this may result in outcomes currently framed as "impairment"—but in other cases, these same pathways may yield deep perception, creative intelligence, or environmentally sensitive cognition. Which path is taken is less a matter of “defective wiring” and more a matter of recursive interaction with context.
IV. Trauma as a Systemic Trigger
Trauma is often narrowly conceptualized as a singular, catastrophic event—an accident, loss, or act of violence. However, neuroscience, somatic psychology, and developmental theory increasingly recognize trauma as a systemic overload: a prolonged mismatch between the needs of a developing organism and the responsiveness of its environment (van der Kolk, 2014; Teicher et al., 2014).
In this view, trauma is not only what happens to us—it is what happens inside us when the nervous system becomes overwhelmed and cannot metabolize, regulate, or contextualize experience. It creates dysregulated feedback loops across neural, endocrine, immune, and perceptual systems, altering both the brain's development and its ongoing patterns of interaction with the world (McEwen & Morrison, 2013).
Trauma doesn’t just leave a psychological imprint—it recalibrates the organism.
Epigenetics: The Biology of Experience
One of the key mechanisms by which trauma shapes development is through epigenetic modification. Experiences of chronic stress can lead to chemical alterations in DNA expression—without changing the underlying genetic code. For example, methylation of the NR3C1 gene (which codes for glucocorticoid receptors) has been associated with dysregulation of the HPA axis, the brain-body system responsible for managing stress (Zhang & Meaney, 2010). This can lead to lifelong changes in stress reactivity, emotional regulation, and cognitive style.
These biological changes are often most pronounced during critical windows of plasticity—such as fetal development, infancy, and early childhood—when the architecture of the nervous system is being laid down (Teicher et al., 2014). If the system is flooded with incoherent or unsafe input during this time, it may adapt in ways that appear “maladaptive” later in life—but which, in context, were functional responses to dysregulation.
What we call “disorder” may in fact be the body’s best attempt at order under unlivable conditions.
Gene × Environment Interactions: A Parallel Model
This dynamic echoes a well-known model in schizophrenia research: gene–environment interaction. A landmark study by Caspi et al. (2005) showed that adolescent cannabis use was associated with an increased risk of psychosis only in individuals with a particular COMT gene variant. In other words, the gene alone was not predictive, and the environment alone was not sufficient—only the interaction mattered.
Autism may operate similarly. The Princeton study showed that different autism phenotypes corresponded not only to different genetic signatures, but also to different developmental timings—suggesting that certain variants may only lead to divergent outcomes if activated by stress, trauma, or relational incoherence during key developmental windows (Litman et al., 2025).
Thus, trauma functions as a bifurcation pressure: a force that can push the developing system into a new attractor state.
Trauma-Informed Embodiment: Perception as Adaptation
The effects of trauma are not only neural—they are embodied. Somatic neuroscience shows that trauma changes the way the body processes sensation, time, and relational cues (van der Kolk, 2014). Many traits associated with autism—such as sensory hypersensitivity, motor coordination challenges, and interoceptive confusion—can be understood as bodily adaptations to an overwhelming environment.
Rather than viewing these as deficits, we might interpret them as tuned responses:
This view is supported by both trauma theory and embodied cognition research (Gallagher, 2005; Clark, 2008). It suggests that autistic embodiment is not broken—it is reorganized in response to unmanageable sensory or emotional input.
The autistic body may encode trauma not as pathology, but as perception.
Complexity Revisited: Trauma as Phase Shift
In complex systems theory, a phase shift occurs when a system absorbs enough stress to reorganize into a qualitatively new state. Trauma, especially in early development, can serve as a catalyst for such a phase shift—pushing the system out of one cognitive attractor and into another.
This shift may bring both costs and gifts: disruption of regulation, but also emergence of new sensitivities; social withdrawal, but also enhanced pattern recognition or ethical acuity. These are not “symptoms”—they are emergent properties of a system adapting under pressure.
V. Embodied & Ecological Cognition
What if the mind does not live in the brain, but through the body and the environment?
This is the premise of two influential paradigms—embodied cognition and ecological cognition—which challenge the classical notion that cognition is internal, abstract, and computational. Instead, these frameworks position cognition as a situated, sensorimotor, and context-sensitive process (Gallagher, 2005; Clark, 2008).
This shift in perspective is not merely theoretical. It offers a powerful, integrative framework for understanding autism and neurodivergence—not as dysfunctions in brain “wiring,” but as alternative styles of embodied adaptation.
Embodied Cognition: Thinking Through the Body
Embodied cognition posits that our thoughts, emotions, and sense of self are inextricably shaped by bodily processes—muscle tension, breath, movement, and interoception (Gallagher, 2005). The nervous system is not a passive conduit for sensory input; it is a dynamic feedback system that co-constructs experience.
Neurodivergent individuals often report:
Hyper- or hypo-sensitive interoception (difficulty interpreting internal bodily signals)
Motor planning challenges or proprioceptive disruptions
Somatic anxiety, which may precede or exceed conscious thought
These are often labeled as “symptoms,” but within an embodied lens, they are core components of cognition—reflecting how the nervous system has learned to interact with the world (van der Kolk, 2014).
For an autistic child, a crowded cafeteria is not just noisy—it’s uninhabitable. Their body thinks through the chaos and signals withdrawal or shutdown as intelligent adaptive responses.
Rather than viewing such responses as errors, we might understand them as perceptual recalibrations: the nervous system reorganizing around what it perceives as threat or incoherence.
Ecological Cognition: Mind as Interface with Environment
Building on this, ecological cognition (rooted in the work of Gibson, 1979) frames the mind as an interface between the organism and its surroundings. Cognition, in this view, is not just about internal processing—it is about attunement to affordances: what the environment offers or demands.
In a predictable, coherent environment, a neurotypical child may learn to filter stimuli and prioritize social cues. But in a chaotic or threatening context—sensory overload, relational inconsistency, trauma—the same filtering mechanisms may be reorganized into heightened sensitivity or withdrawal.
This recontextualizes autistic traits:
Autistic cognition, in this view, is not defective—it is differently situated.
Relational Mismatch, Not Individual Disorder
What if autism is not a disorder of the individual, but a mismatch between nervous systems and social environments?
As van der Kolk (2014) and Clark (2008) argue, when a person’s body-based way of knowing is invalidated, overwhelmed, or misunderstood, they adapt. They withdraw, mask, dissociate, or resist—not due to deficit, but because their ecological logic demands it.
This logic is recursive. A child exposed to emotional neglect may develop enhanced pattern recognition and vigilance—not because of genetic dysfunction, but because their system adapts to the predictive demands of incoherence (Teicher et al., 2014).
Cognition as Relational Adaptation
When viewed through these lenses, autism may not represent a failure of development—it may be a systemic adaptation to incoherent relational and sensory input. As Lombardo et al. (2019) note, the heterogeneity of autism arises not just from genetic diversity, but from the divergent developmental ecologies in which those genes express themselves.
Thus, cognition is not simply internal. It is ecological. It is:
Shaped by how the body learns to move, feel, and protect itself.
Informed by what the environment demands or fails to provide.
Emergent from recursive loops between organism and world.
Autism is not a closed circuit. It is a conversation with the environment—and sometimes, a refusal to answer incoherent questions.
VI. Dabrowski, Disintegration, and Meta-Development
In conventional models of mental health, internal distress—anxiety, disorganization, emotional overwhelm—is typically framed as dysfunction. But what if, instead, such disintegration is a necessary precondition for growth?
This is the central insight of Kazimierz Dabrowski’s Theory of Positive Disintegration (TPD). Developed in the mid-20th century and revived by neurodivergent and giftedness researchers today, TPD posits that inner conflict, breakdown, and existential crisis are not signs of failure, but signs of a higher developmental potential—especially in individuals with heightened sensitivities and intensities (Dabrowski, 1964; Piechowski, 2006).
“Disintegration is not pathology. It is the crucible of a more authentic self.”
— Dabrowski (1964)
Overexcitabilities and Neurodivergence
Dabrowski identified five areas of overexcitability (OE)—heightened responsiveness to stimuli—that are often present in individuals with high developmental potential:
Psychomotor (restlessness, intensity of movement)
Sensual (heightened sensory processing)
Emotional (deep empathy, existential anxiety)
Intellectual (love of truth, recursive analysis)
Imaginational (vivid inner world, symbolic thinking)
These mirror traits frequently observed in autistic and gifted individuals, particularly emotional depth, sensory intensity, and recursive cognitive style (Piechowski, 2006; Baron-Cohen, 2020). Within the TPD framework, such traits are not liabilities, but catalysts—pressures that disrupt conformity and initiate the meta-developmental process of self-authorship.
From Primary to Secondary Integration
Dabrowski’s theory maps psychological development across five levels, with three major phases:
Many autistic and twice-exceptional individuals may never fully experience primary integration because their sensory, emotional, or cognitive systems are already out of sync with normative expectations. Instead, they may enter disintegration early—especially when exposed to trauma, incoherent education systems, or pathologizing diagnoses (van der Kolk, 2014; Teicher et al., 2014).
In this view, what looks like developmental “failure” may be an accelerated entry into meta-development.
Recursive Selfhood and Metamodern Identity
Recent work in metamodernism and complexity psychology echoes Dabrowski’s view of selfhood as recursive, emergent, and multi-leveled (Stein, 2019). Identity is not fixed—it is continually reorganized through experiences of contradiction, breakdown, and synthesis.
This aligns strikingly with neurodivergent developmental profiles, especially in those who:
Engage in hyper-reflexive self-inquiry (often mislabeled as rumination)
Experience intense moral reasoning from a young age
Resist roles and systems that feel unethical or incoherent
Rather than seeing these traits as “rigid” or “disordered,” they can be interpreted as signs of a recursive developmental arc—one that values integrity over compliance, coherence over ease.
Autistic Cognition as Evolutionary Feedback
From a systems perspective, individuals who embody these traits may serve a cybernetic function in society. That is, they act as error detectors—sensing incoherence in social, moral, or environmental systems and responding with internal crisis, innovation, or resistance.
This aligns with the broader theory of evolutionary adaptive cognition: that neurodivergent traits represent early-warning signals or developmental experiments, especially under conditions of relational breakdown or ecological instability (Baron-Cohen, 2020; Lombardo et al., 2019).
These minds are not just outliers—they may be prototypes of what’s to come.
When the world becomes chaotic, it may be the wildminded, the recursive thinkers, the ones who disintegrate under false systems, who hold the keys to coherent reorganization.
VII. The Neurodivergent Edge of Evolution
What if the traits we pathologize in neurodivergent individuals are not deficits, but evolutionary prototypes—adaptive responses arising in a world increasingly marked by complexity, unpredictability, and systemic incoherence?
This is the hypothesis at the heart of evolutionary adaptive cognition: that neurodivergence—particularly forms such as autism, ADHD, and highly sensitive cognition—may represent emergent variations in the human cognitive system. These variations, far from being “broken” configurations, may reflect the system’s attempt to adapt to modern ecological, sensory, and relational environments (Baron-Cohen, 2020; Lombardo et al., 2019).
The 2025 Princeton study adds a compelling layer to this idea. By identifying multiple classes of autism with distinct genetic and developmental pathways, the study undermines the notion of autism as a monolithic condition—and instead positions it as a multilinear spectrum of adaptive potential (Litman et al., 2025). Some of these pathways may lead to impairment in rigid or sensory-hostile environments, but others may produce deep pattern recognition, moral sensitivity, or creative resistance—traits increasingly vital in an unstable world.
Latent Traits in the Population
Large-scale genomic studies, including those by Warrier et al. (2022), suggest that the genetic components of autism and related traits are broadly distributed across the general population. This supports the idea of neurodivergence as a spectrum of potential, not a binary diagnosis.
In this model:
Most people carry some genes associated with neurodivergent traits.
These traits are latent—emerging under certain conditions (e.g., trauma, stimulation, incoherence).
The expression of these traits is shaped by the interaction of genetics, development, and context.
Thus, not all people will become autistic or ADHD-diagnosed, but many may express partial or context-sensitive versions of those cognitive styles.
Neurodivergence, then, may be less like a rare disorder and more like mycelium—invisible beneath the surface, blooming only under the right conditions.
Adaptive Value in Complex Environments
In systems under stress—climate collapse, institutional breakdown, digital oversaturation—certain cognitive traits become more adaptive:
While these traits may create friction in stable, rule-bound systems, they become assets in volatile, nonlinear systems (Mitchell, 2009). The rise in visibility of neurodivergent minds, then, may not be an epidemic of dysfunction—but a signal of cognitive transition in the species.
Wildmindedness and Neurocomplexity
To fully embrace this shift, we must move beyond diagnostic language altogether. Terms like “disorder,” “spectrum,” or even “divergence” still imply a deviation from a normative center. Instead, we propose new descriptors:
Wildmindedness: Cognition that resists domestication; responsive to intensity, depth, and pattern rather than social hierarchy or rote logic.
Neurocomplexity: A systems-based, ecological model of mind that emphasizes divergent pathways, context sensitivity, and recursive feedback.
These concepts make room for the nonconforming, the nonlinear, the deeply perceptive, and even the disintegrative. They ask not “What’s wrong with this mind?” but “What is this mind doing in response to its environment?”
In this sense, neurodivergent minds are not just different—they are messages. They tell us something about the world, about its incoherence, and about the kind of minds needed to navigate it.
Evolution as Feedback, Not Perfection
Classical models of evolution often assume linear progress toward fitter outcomes. But complexity theory and epigenetics suggest a different story: evolution as feedback, not direction. Systems shift, loop, and adapt—not always to become “better,” but to become coherent with their environments (Zhang & Meaney, 2010).
Neurodivergent cognition, especially when shaped by early trauma or relational incoherence, may represent the system’s recalibration toward new adaptive basins. These adaptations may carry costs—sensory overwhelm, emotional volatility—but they also carry capacities the system didn’t previously have.
In this framing, autistic cognition is not a disorder to be cured, but an evolutionary signal—an emergent feature of cognitive ecology in transition.
VIII. Implications for Diagnosis, Care, and Society
If autism and neurodivergence are emergent, adaptive responses within complex relational and environmental systems, then our prevailing diagnostic frameworks are not just inadequate—they are structurally misaligned with the phenomena they attempt to capture.
The current medical model is grounded in static, categorical thinking. It frames neurodevelopmental conditions as discrete disorders defined by deficits: failures in social communication, rigid behaviors, attention dysregulation. These definitions arise from behavioral observation, decontextualized from relational, developmental, or environmental conditions (American Psychiatric Association, 2013). They are then used to determine eligibility for services or treatments, often reinforcing a pathology-centered identity.
This framing may offer utility for access—but it obscures the underlying systems dynamics and limits our capacity to respond meaningfully.
The Limits of the Medical Model
The DSM framework, while operationally useful, treats cognition as a set of traits, measured and coded outside of context. Yet, as research from Litman et al. (2025) and Lombardo et al. (2019) demonstrates, the autistic phenotype is heterogeneous, developmentally dynamic, and interactively shaped by gene × environment interactions. Phenotypic expression may depend not only on what genes are present, but when, where, and under what conditions they are expressed.
Moreover, the behavioral model rarely accounts for:
Trauma histories
Relational ecology
Sensory environments
Epigenetic states
Somatic feedback loops
As van der Kolk (2014) and Teicher et al. (2014) show, many traits interpreted as “disorders” may in fact be adaptive responses to unintegrated experiences, especially in developing nervous systems. Without attending to the context of these adaptations, diagnosis becomes an act of systemic misreading.
We risk diagnosing the system’s adaptation as the individual’s failure.
A Cognitive Ecological Approach
What’s needed is not simply better diagnostics, but a new paradigm: a shift from deficit models to cognitive ecology.
A cognitive ecological model would assess:
The developmental context of the individual (prenatal, relational, environmental)
The coherence or incoherence of sensory and social inputs
The adaptive strategies employed by the nervous system
The latent potentials embedded in the person’s cognitive ecology
Such a model would move away from rigid categories and toward systemic attunement—examining the loops, layers, and bifurcations that shape a person’s developmental path (Mitchell, 2009; Clark, 2008).
In this model, intervention would not focus on “fixing the brain,” but on supporting the system—building environments of coherence, trust, and somatic safety.
Systems That Breathe with the Mind
This paradigm has profound implications for how we design institutions: schools, clinics, workplaces, and families.
Rather than forcing individuals to adapt to static, one-size-fits-all systems, we must build systems that adapt to the individual—that breathe with the mind, flex with the body, and co-regulate with the nervous system.
This means:
Such environments do not “treat” neurodivergence—they support its healthy emergence.
The goal is not normalization. The goal is coherence.
From Intervention to Co-Evolution
When we move from pathology to ecology, we shift from intervention to co-evolution. We begin to ask not “How can we fix this child?” but “How can this system evolve to meet the needs of this mind?”
This demands humility, flexibility, and a willingness to rethink not only our clinical tools but our societal values. It asks us to see wildmindedness not as a disruption, but as a developmental divergence worth listening to.
After all, if neurodivergence represents the leading edge of human adaptation, then our institutions must evolve not in spite of it—but because of it.
IX. Conclusion: Living Systems, Living Minds
Cognition is not a static capacity. It is a living process—emergent, recursive, embodied, and ecological.
What we call “the mind” does not reside solely in the brain. It unfolds through layers of interaction: with the body, with caregivers, with culture, with sensation, with time. And like all complex living systems, it is shaped not only by its internal code but by how it relates to the world around it (Mitchell, 2009; Clark, 2008).
From this perspective, autism is not a disorder frozen in brain architecture—it is a dynamic developmental trajectory, a recursive feedback loop between genes, trauma, context, and adaptation. As Litman et al. (2025) show, gene expression in radial glia during early fetal development, as well as postnatal transcriptional programs, interacts with epigenetic and environmental inputs to generate divergent—but not necessarily defective—outcomes.
These divergences are not breakdowns of the system. They are the system’s recalibrations—responses to overwhelm, to incoherence, to opportunity.
In complexity science, systems adapt by moving into new attractor basins when their current configuration can no longer sustain coherence. This is as true for ecosystems as it is for minds. What looks like regression or collapse may in fact be the early signal of a transformation—a shift toward a different mode of being.
From Deficit to Developmental Divergence
The dominant paradigm still frames neurodivergence—especially autism—as a pathology: a disruption of “normal” development, a condition to be managed, mitigated, or normalized. But the evidence increasingly tells a different story.
The brain is not a machine. It is a self-organizing system (McEwen & Morrison, 2013).
Genes are not blueprints. They are conditional affordances (Zhang & Meaney, 2010).
Trauma is not damage. It is a recursive signal that reorganizes development (van der Kolk, 2014; Teicher et al., 2014).
Sensory sensitivity is not fragility. It is high-resolution ecological attunement (Baron-Cohen, 2020).
When we adopt a systems lens, we begin to see that neurodivergence may not be what’s wrong with the system—it may be what’s trying to evolve within it.
A New Paradigm of Mind
In place of the deficit-based model, this paper proposes a paradigm of evolutionary adaptive cognition: a view of autism and related forms of neurocomplexity as adaptive responses within living systems. This paradigm values:
Recursion over reduction: seeing cognition as a loop, not a line.
Context over category: valuing where and how traits arise, not just what they are.
Coherence over control: prioritizing relational and sensory trust over behavioral conformity.
Divergence over normalization: embracing difference not as dysfunction, but as potential.
This paradigm is not only more accurate to the science—it is more compassionate, more human, and more hopeful.
Listening to the System
If we listen closely, we can hear what neurodivergence is telling us:
“Your systems are too rigid.”
“Your environments are too noisy.”
“Your rules do not match our relational logic.”
“Your metrics do not see what we see.”
These are not dysfunctions. They are cognitive signals. They are invitations to evolve.
In the same way that biodiversity protects ecosystems, neurodiversity strengthens our collective mind. It brings new perceptual grammars, new ethical logics, new sensitivities—and perhaps, new solutions to the crises we face.
A Living Mind for a Living World
We live in a time of accelerating change, systemic instability, and ecological uncertainty. In such times, complex minds are not luxuries—they are necessities.
Autistic, ADHD, and wildminded individuals may be at the leading edge of human evolution—offering new forms of sensing, patterning, resisting, and relating. But only if we stop trying to pathologize them. Only if we build systems that can hold their difference—and grow with it.
In a living world, we need living minds.
Minds that bend, sense, reflect, and resist.
Minds that remember: adaptation is not compliance.
It is transformation
References
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596
Baron-Cohen, S. (2020). The pattern seekers: How autism drives human invention. Basic Books.
Caspi, A., Moffitt, T. E., Cannon, M., McClay, J., Murray, R., Harrington, H., Taylor, A., Arseneault, L., Williams, B., Braithwaite, A., Poulton, R., & Craig, I. W. (2005). Moderation of the effect of adolescent-onset cannabis use on adult psychosis by a functional polymorphism in the COMT gene: Longitudinal evidence of a gene × environment interaction. Biological Psychiatry, 57(10), 1117–1127. https://doi.org/10.1016/j.biopsych.2005.01.026
Clark, A. (2008). Supersizing the mind: Embodiment, action, and cognitive extension. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195333213.001.0001
Dabrowski, K. (1964). Positive disintegration. Little, Brown.
Gallagher, S. (2005). How the body shapes the mind. Oxford University Press.
Gibson, J. J. (1979). The ecological approach to visual perception. Houghton Mifflin.
Herring, B. E., Patel, S., Huang, E., Schaefer, J., Tovar, K. R., & Nicoll, R. A. (2022). Complex feedback regulation in neural circuits and plasticity. Annual Review of Neuroscience, 45, 151–173. https://doi.org/10.1146/annurev-neuro-120720-102453
Litman, R., Reimand, J., Singh, T., Jaffe, A. E., Werling, D. M., Grove, J., Palmer, D. S., ... & Sullivan, P. F. (2025). Alternative splicing programs define phenotypic classes of autism. Nature Genetics, 57, 999–1011. https://doi.org/10.1038/s41588-025-02224-z
Lombardo, M. V., Lai, M.-C., & Baron-Cohen, S. (2019). Big data approaches to decomposing heterogeneity across the autism spectrum. Molecular Psychiatry, 24, 1435–1450. https://doi.org/10.1038/s41380-018-0321-0
McEwen, B. S., & Morrison, J. H. (2013). The brain on stress: Vulnerability and plasticity of the prefrontal cortex over the life course. Neuron, 79(1), 16–29. https://doi.org/10.1016/j.neuron.2013.06.028
Mitchell, M. (2009). Complexity: A guided tour. Oxford University Press.
Piechowski, M. M. (2006). "Mellow out," they say. If I only could: Intensities and sensitivities of the young and bright. Yunasa Books.
Stein, Z. (2019). Education in a time between worlds: Essays on the future of schools, technology, and society. Bright Alliance.
Teicher, M. H., Anderson, C. M., Ohashi, K., & Polcari, A. (2014). Childhood maltreatment: altered network centrality of cingulate, precuneus, temporal pole and insula. Biological Psychiatry, 76(4), 297–305. https://doi.org/10.1016/j.biopsych.2013.09.016
van der Kolk, B. A. (2014). The body keeps the score: Brain, mind, and body in the healing of trauma. Viking.
Warrier, V., Toro, R., Chakrabarti, B., Børglum, A. D., Grove, J., the 23andMe Research Team, Hinds, D. A., Bourgeron, T., & Baron‑Cohen, S. (2018). Genome-wide analyses of self‑reported empathy: correlations with autism, schizophrenia, and anorexia nervosa. Translational Psychiatry, 8, 35. https://doi.org/10.1038/s41398-017-0082-6
Zhang, T. Y., & Meaney, M. J. (2010). Epigenetics and the environmental regulation of the genome and its function. Annual Review of Psychology, 61, 439–466. https://doi.org/10.1146/annurev.psych.60.110707.163625
Sher! I am thrilled to have discovered you and your writing! You speak to something that is often felt but rarely named: that the autistic brain is not broken or defective -- it is exquisitely attuned to a different rhythm of the world. AND that our collective survival depends on protecting and honoring this neurodivergent rhythm! THANK YOU!
My whole system is singing in resonance!