Toward a neurodiversity-affirming model of allostasis, salience, interoception, and environmental mismatch
Trauma matters. For many people, trauma is one of the clearest names we have for how the past keeps living in the body. Trauma-informed care earned its place by moving a generation of clinicians, educators, and caregivers from What is wrong with you? to What happened to you? — and that shift was not cosmetic. It changed who got believed, who got punished, and who got helped.
But somewhere along the way, “trauma” started doing too much work.
It became a catch-all for states that are not always trauma in origin: sensory overwhelm, metabolic shutdown, social prediction failure, interoceptive confusion, chronic fatigue, immune activation, high-gain threat detection, and the ordinary daily exhaustion of living inside environments that were never built to match one’s regulatory architecture. When every danger-state, every meltdown, every collapse, every chronic-illness pattern gets routed through a single explanatory word, the word stops clarifying and starts flattening.
This is not an argument against trauma-informed care. It is an argument against making trauma carry the entire weight of human distress. From the perspective of the Evolutionary Stress Framework (ESF), trauma is one pathway into threat physiology — a real and important one — but it is not the whole architecture of threat physiology.
So this piece proposes a third question to sit alongside the first two. Not only What is wrong with you? Not only What happened to you? But also: What is your system trying to regulate, and what architecture is making regulation impossible?
A note on framing: ESF is a conceptual lens for thinking about brain-body-environment systems. It is not a diagnostic tool and nothing here is medical advice. Where I describe mechanisms, I am pointing at promising models and live debates, not settled facts.
Trauma is real — but not everything is trauma
Part of the problem is linguistic. We use one word for a dozen different survival-shaped states.
Even the definitions don’t agree with each other. SAMHSA describes trauma broadly — an event, a series of events, or a set of circumstances experienced as harmful or life-threatening, with lasting adverse effects (SAMHSA, 2014). Clinical PTSD criteria are far narrower, requiring exposure to actual or threatened death, serious injury, or sexual violence (National Center for PTSD). Those are not the same construct. A person can live in a durable, body-deep threat-regulation state without their situation fitting either frame cleanly.
And the surrounding vocabulary is just as slippery. Chronic stress, toxic stress, allostatic load, early-life stress, childhood adversity, trauma, ACEs — these terms are routinely defined and operationalized in inconsistent ways across the literature, even as foundational sources like the ACEs study (Felitti et al., 1998) and the toxic-stress framework (Shonkoff et al., 2012) gave individual terms real precision. That inconsistency is not a footnote. It is precisely why the field keeps reaching for “trauma” as a default: it is the term with the most cultural traction, so it absorbs everything nearby.
The ESF move here is not to build rigid new boxes. It is to stop using one survival word for every survival-shaped state — and to ask, each time, which kind of regulation is actually under strain.
When the claim becomes total
Everything above stays abstract until you put it next to the slogans it is actually answering. Two of them circulate widely, and if you spend any time in autistic or ADHD communities you will hear them stated as settled:
“There is no such thing as an untraumatized autistic.”
“You can’t untangle ADHD and trauma.”
Neither is foolish. Each is reaching toward something true, and this argument would be dishonest if it pretended otherwise. So take them one at a time — generously first.
“No such thing as an untraumatized autistic.” The kernel here is real and worth saying plainly: autistic people do not grow up in neutral conditions. A childhood of sensory environments that run too hot, of being corrected for the way you move and speak, of masking to stay safe, of social rejection that arrives before you understand what you did — that is, in the broad SAMHSA sense, a life shaped by adverse circumstance. The slogan is right that the autistic baseline is rarely a calm one.
But notice what it does. If every autistic life counts as traumatized by definition, then “trauma” no longer distinguishes anything — it has quietly become a synonym for “autistic and alive in this world.” A word that applies to everyone in a category explains no one in it. The claim also smuggles the clinical weight of narrow-sense trauma onto a broad-sense sociological observation, as if lifelong mismatch and a discrete overwhelming event were the same kind of thing calling for the same kind of care. And it forecloses the very pathways this piece is about: a sensory system that ran hot from the first week of life, an interoceptive signal that was noisy from the start, a metabolic load that no memory explains. None of those require a wound. Worst of all, the slogan can be quietly invalidating in the other direction — it tells autistic people who do not experience their neurology as injury that they must be mistaken about their own lives.
The ESF reframe doesn’t deny what the slogan sees. It renames it. The thing the claim is reaching for has a more precise name: architectural mismatch and accumulated allostatic load. “You have spent your whole life regulating under conditions calibrated against your architecture” is both more accurate and more actionable than “you must be traumatized.” It points at the environment, the energy budget, and the design — things that can actually be changed — rather than locating a wound that may not be there.
“You can’t untangle ADHD and trauma.” This one is pointing at a genuine difficulty, not an imagined one. The presentations really do overlap: inattention, hypervigilance, emotional intensity, executive strain, restless bodies, disrupted sleep. Co-occurrence is common, developmental influences are shared, and our current measures genuinely struggle to pull the threads apart. A clinician who finds them tangled is not being lazy.
But “impossible to untangle” does something subtle and consequential. In practice it tends to collapse into “so default to trauma” — the tangle becomes a reason to reach for the most culturally available explanation. It mistakes current measurement difficulty for ontological sameness: hard-to-distinguish-with-our-tools is not the same as identical-in-nature. And it assumes the two are competing explanations for one underlying thing — two threads of a single rope — when they may be different routes into overlapping regulatory states.
Here ESF offers something close to relief: you may not have to untangle them at all. If you stop asking which master-cause and start asking the access questions — what regulation is failing, what signal is missed, what action is blocked, what affordance is absent — the support that follows is largely the same regardless of which etiological thread dominates. The untangling problem partly dissolves because it was the wrong question. Both-and is permitted. So is neither as primary — both as the downstream signature of a system running near the edge of its bandwidth.
That is the deeper point underneath both slogans. The totalizing move — it’s all trauma; it’s all entangled, so call it trauma — feels like taking suffering seriously. But it actually narrows the field of response. ESF’s wager is the opposite: you take the suffering more seriously, not less, when you let it have more than one name.
Danger mode: from cells to selfhood
The body can behave as though it is under threat because some level of the system genuinely is.
Robert Naviaux’s cell danger response (Naviaux, 2014) describes an evolutionarily conserved metabolic reaction to threats that exceed a cell’s homeostatic capacity. The triggers are not limited to psychological events — they include biological, chemical, physical, and psychological stressors. In plain terms: a body can enter defense physiology from infection, toxic exposure, injury, immune activation, chronic strain, or sheer sensory overload, none of which require a traumatic memory to explain them.
Said the other way around:
The body can act like it is under threat because some level of the system is under threat. That threat may be remembered trauma — but it may also be inflammation, sensory overload, sleep loss, pain, illness, uncertainty, hunger, social demand, or an environment that never gives the nervous system a chance to downshift.
In ESF terms, trauma is one etiological route into defensive allostatic and metabolic states. It should not be treated as the master category for every prolonged organismic threat response. The cell danger framework is best held as a useful systems-biology lens — not a proven universal explanation for autism, chronic illness, or trauma. But even held loosely, it does something important: it breaks the assumption that “danger mode” must mean “remembered danger.”
Energy conservation: shutdown as strategy
Allostasis is the brain-body process of maintaining viability by adjusting physiology in anticipation of demand (Sterling & Eyer, 1988; Sterling, 2012). Bruce McEwen’s allostatic load model (McEwen & Stellar, 1993; McEwen, 1998) describes what happens when that process is pushed too hard for too long: repeated activation, a failure to switch stress systems off, or inadequate responses accumulate into a physiological burden over time.
This is where “energy-saving mode” becomes more than a metaphor. Shutdown, avoidance, fatigue, flattened executive function, social withdrawal — these are routinely read as noncompliance, as depression-only, or as trauma-response-only. ESF suggests another reading: they may be energy triage.
What looks like refusal may be conservation. What looks like emotional collapse may be a system reallocating energy away from optional performance and toward survival, prediction, and repair.
This is not a romantic claim. A system in conservation is not thriving, and naming it as triage does not make it healthy. But it is biologically intelligible. A person operating near the edge of their regulatory bandwidth will protect the metabolically expensive functions last — and the first things to go are often exactly the things the surrounding environment values most: speech, flexibility, sociability, output. The behavior that gets labeled as a failure of will may be the visible signature of an energy budget that ran out before the demand did (Picard & McEwen, 2018; Dantzer et al., 2008).
Salience and prediction: why neutral does not feel neutral
The brain is not a passive receiver of the world. It is constantly predicting, comparing what arrives against what it expected, and updating (Friston, 2010). Interoceptive active-inference models (Seth, 2013; Barrett & Simmons, 2015; Quigley et al., 2021) go further, placing metabolism and bodily regulation at the very center of emotion, perception, and action — the brain is, on this view, in the business of keeping the body viable, and perception is shaped accordingly.
For autism, predictive-processing accounts often propose atypical weighting of prediction errors or sensory precision (Pellicano & Burr, 2012; Lawson et al., 2014; Van de Cruys et al., 2014). But the honest summary is that the evidence is mixed. Some reviews report differences in predictive learning; other studies find predictive processing largely intact in autistic adults, depending heavily on the task and the construct being measured (Cannon et al., 2021). This is a promising model for salience, sensory precision, and uncertainty — not a proof that prediction “explains autism.”
Held carefully, though, it reframes a familiar accusation:
The issue is not that a person “cannot tell what matters.” It may be that their system is assigning salience differently — because uncertainty, sensory intensity, social ambiguity, or interoceptive noise has made more signals biologically expensive to ignore.
That is a very different claim from “they are overreacting,” and a very different claim from “they are traumatized.” A high-gain system is not a broken system. It is a system for which more of the world has been flagged as worth attending to — which is costly, but is not the same thing as damage.
Need without access: the hidden architecture of “dysregulation”
This may be the most useful reframe of all.
A person may need food, deep pressure, solitude, movement, darkness, quiet, an explanation, relational repair, a temperature change, pain relief, rest, or simply an exit from uncertainty. But if their interoceptive signals are unclear, delayed, overwhelming, or socially punished, they may not know what they need until the system has already escalated past the point where any of it would have helped.
Recent work supports the relevance of interoception in autism while also flagging real measurement difficulty and heterogeneity (DuBois et al., 2016; Loureiro et al., 2024). Autistic people may differ in how they sense, interpret, or use internal bodily signals — and those differences can ripple outward into self-regulation, emotion, and daily functioning.
So consider what the word “dysregulation” is actually naming:
“Emotional dysregulation” often names the visible endpoint of a hidden regulatory failure: the person had a need, lacked access to the signal, lacked a usable action, or lacked an environment that permitted the action in time.
ESF suggests swapping the diagnostic reflex. Instead of What trauma caused this behavior?, ask a sequence:
- What regulation was needed?
- What signal was missed, delayed, or drowned out?
- What action was blocked?
- What environmental affordance was simply absent?
Call it failed regulatory access rather than emotional dysregulation. The endpoint may look identical from the outside. The intervention it points toward is completely different.
Beyond neurotypical blame: from moral accusation to design responsibility
There is a tempting shortcut in neurodiversity discourse, and it deserves naming. It is the move from “autistic people are deficient” to “neurotypical people are harmful.” Both can contain truth. Both can also flatten the biology and reproduce the very error they set out to critique — locating the problem in a category of person rather than in a relational and environmental system.
Damian Milton’s double empathy problem (Milton, 2012) offers a better foundation. It reframes autistic / non-autistic social difficulty as a breakdown in mutual understanding between differently-situated people, not as a one-sided autistic deficit. Monotropism — developed by Murray, Lesser, and Lawson (2005) — similarly frames autistic cognition through attention allocation and interest-based attentional tunnels, rather than through pathology. Put together, they describe social friction as bidirectional prediction failure across neurotypes, not unilateral defect and not unilateral blame (Crompton et al., 2020; Heasman & Gillespie, 2018).
That gives us a model that is accountable without being accusatory:
We do not need to replace “autistic people are deficient” with “neurotypical people are harmful.” We need a better model: neurotypes carry different sensory, predictive, attentional, metabolic, and social assumptions. Harm emerges when one set of assumptions gets built into schools, clinics, workplaces, homes, communication norms, and moral expectations as if it were universal.
Neurotypicality is not the enemy. Unexamined neurotypical-default architecture is the problem (Chapman, 2021; Chapman & Botha, 2023; Ne’eman & Pellicano, 2022). Harm can be structural, cumulative, and entirely unintentional — and still be completely real.
Architectural medicine: redesigning the conditions of regulation
If regulation is shaped by the systems a person lives inside, then care has to widen its field of view. Architectural medicine asks not only What happened to you? but What regulatory architecture are you living inside?
That architecture has layers:
- Sensory architecture — light, sound, texture, crowding, movement, visual complexity
- Temporal architecture — pace, transitions, recovery time, predictability
- Relational architecture — communication norms, repair practices, consent, co-regulation
- Metabolic architecture — sleep, food, pain, inflammation, hormones, infection, mitochondrial capacity
- Cognitive architecture — attention demands, uncertainty, executive load, relevance filtering
- Social architecture — stigma, masking demand, class, race, gender, disability access, institutional rigidity
Some of this is literal. An emerging line of work on architecturally-mediated allostasis and architectural allostatic overload (Valentine, 2023, 2024, 2025) argues that features of the built environment — lighting, sound, spatial planning, temperature, air quality, sensory design — may themselves shape stress physiology and allostatic burden (Tola et al., 2021; Black et al., 2022; Evans, 2003; Ulrich, 1984). That field is still young, and its claims should be held as promising rather than settled. But it makes the metaphor concrete: the room is not neutral. The schedule is not neutral. The lighting is not neutral.
And some of it is broader. Architectural medicine, as an orientation, asks clinicians, educators, employers, designers, and families to stop treating regulation as a private achievement and start treating it as a distributed property of bodies, relationships, and environments. Regulation is not something a person simply has or lacks. It is something a system supports or fails to support.
The shorthand, and the more precise version
Much of this comes down to a habit of language. Here is the translation ESF keeps reaching for:
| Common shorthand | More precise framing |
|---|---|
| “That is trauma.” | “That may be a trauma-mediated threat state — but it may also be sensory, metabolic, immune, relational, architectural, or allostatic.” |
| “They are emotionally dysregulated.” | “They are regulating under constraint, without enough access to usable signals, energy, safety, prediction, or co-regulation.” |
| “They are overreacting.” | “Their salience system may be assigning high precision to signals others classify as irrelevant.” |
| “They can’t read people.” | “There may be bidirectional prediction failure across neurotypes, contexts, and communication styles.” |
| “Neurotypicals are harming neurodivergent people.” | “Dominant environments are often calibrated around neurotypical assumptions; harm can be structural, cumulative, and unintentional without being unreal.” |
| “They need trauma work.” | “They may need regulation architecture — metabolic support, sensory predictability, relational translation, environmental redesign — and trauma processing when trauma is genuinely central.” |
What “beyond trauma” does and does not mean
A few guardrails, because this argument is easy to misread.
Beyond trauma does not mean not harmed. It means harm may be structural, metabolic, sensory, relational, environmental, developmental, or cumulative — not always trauma in the narrow clinical sense.
It does not mean abandoning trauma-informed care. It means extending it. Trauma-informed care was necessary. ESF suggests it is not, by itself, sufficient.
And it does not mean reaching for grand mechanistic certainty. The cell danger response is a useful frame, not a proven universal cause. Predictive processing is a promising model, not a finished theory of autism. Architectural allostasis is an emerging field, not an established one. The argument doesn’t need any of them to be the whole story. It only needs the trauma frame to stop being the only story.
The thesis, stated plainly
If there is one sentence to carry out of this piece, it is this:
Trauma is one way a system learns danger. It is not the only reason a system stays organized around protection, conservation, heightened salience, and blocked regulation.
Or, in fuller ESF form:
Many so-called symptoms are emergent adaptations of brain-body-environment systems trying to preserve viability under conditions of excessive uncertainty, insufficient energy, mismatched sensory-social architecture, and inadequate regulatory affordance.
The next paradigm should not ask people to prove they were traumatized before their regulation needs are taken seriously. Nor should it require blaming a whole neurotype for every mismatch. The better question is architectural: What conditions make this body-brain system spend so much energy defending, predicting, masking, filtering, and recovering — and what would have to change so that regulation becomes possible before crisis, instead of only after it?
That is the conversation worth having. Not against trauma. Beyond reduction.
This is an ESF-perspective essay — a conceptual lens for thinking about brain-body-environment systems, not a diagnostic tool or clinical guidance. The frameworks below are presented as convergent mechanisms, not as one grand theory; trauma is one pathway into defensive regulation, while allostasis, immune-metabolic signaling, interoceptive uncertainty, sensory prediction, social mismatch, and built-environment demand can also organize a person around protection, conservation, and heightened salience.
References
Defining trauma without making trauma explain everything
SAMHSA. (2014). SAMHSA’s Concept of Trauma and Guidance for a Trauma-Informed Approach. Substance Abuse and Mental Health Services Administration. https://www.health.ny.gov/health_care/medicaid/program/medicaid_health_homes/docs/samhsa_trauma_concept_paper.pdf
U.S. Department of Veterans Affairs, National Center for PTSD. PTSD and DSM-5.
Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., Koss, M. P., & Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. American journal of preventive medicine, 14(4), 245–258. https://doi.org/10.1016/s0749-3797(98)00017-8
Shonkoff, J. P., Garner, A. S., Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood, Adoption, and Dependent Care, & Section on Developmental and Behavioral Pediatrics (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232–e246. https://doi.org/10.1542/peds.2011-2663
Allostasis, allostatic load, and predictive regulation
Sterling, P., & Eyer, J. (1988). Allostasis: A new paradigm to explain arousal pathology. In S. Fisher & J. Reason (Eds.), Handbook of Life Stress, Cognition and Health (pp. 629–649). Wiley.
McEwen, B. S., & Stellar, E. (1993). Stress and the individual: Mechanisms leading to disease. Archives of Internal Medicine, 153(18), 2093–2101. https://doi.org/10.1001/archinte.1993.00410180039004
McEwen, B. S. (1998). Protective and damaging effects of stress mediators. New England Journal of Medicine, 338(3), 171–179. https://doi.org/10.1056/NEJM199801153380307
McEwen, B. S., & Wingfield, J. C. (2003). The concept of allostasis in biology and biomedicine. Hormones and Behavior, 43(1), 2–15. https://doi.org/10.1016/S0018-506X(02)00024-7
Juster, R.-P., McEwen, B. S., & Lupien, S. J. (2010). Allostatic load biomarkers of chronic stress and impact on health and cognition. Neuroscience & Biobehavioral Reviews, 35(1), 2–16. https://doi.org/10.1016/j.neubiorev.2009.10.002
Guidi, J., Lucente, M., Sonino, N., & Fava, G. A. (2021). Allostatic load and its impact on health: A systematic review. Psychotherapy and Psychosomatics, 90(1), 11–27. https://doi.org/10.1159/000510696
Sterling, P. (2012). Allostasis: A model of predictive regulation. Physiology & Behavior, 106(1), 5–15. https://doi.org/10.1016/j.physbeh.2011.06.004
Schulkin, J., & Sterling, P. (2019). Allostasis: A brain-centered, predictive mode of physiological regulation. Trends in Neurosciences, 42(10), 740–752. https://doi.org/10.1016/j.tins.2019.07.010
Slavich, G. M. (2020). Social Safety Theory: A biologically based evolutionary perspective on life stress, health, and behavior. Annual Review of Clinical Psychology, 16, 265–295. https://doi.org/10.1146/annurev-clinpsy-032816-045159
Cell danger, immune-metabolic stress, and energy conservation
Naviaux, R. K. (2014). Metabolic features of the cell danger response. Mitochondrion, 16, 7–17. https://doi.org/10.1016/j.mito.2013.08.006
Picard, M., & McEwen, B. S. (2018). An energetic view of stress: Focus on mitochondria. Frontiers in Neuroendocrinology, 49, 72–85. https://doi.org/10.1016/j.yfrne.2018.01.001
Picard, M., & McEwen, B. S. (2018). Psychological stress and mitochondria: A conceptual framework. Psychosomatic Medicine, 80(2), 126–140. https://doi.org/10.1097/PSY.0000000000000544
Picard, M., McEwen, B. S., Epel, E. S., & Sandi, C. (2018). An energetic view of stress: Psychological stress and mitochondria. Psychosomatic Medicine, 80(2), 141–153.
Dantzer, R., O’Connor, J. C., Freund, G. G., Johnson, R. W., & Kelley, K. W. (2008). From inflammation to sickness and depression: When the immune system subjugates the brain. Nature Reviews Neuroscience, 9, 46–56. https://doi.org/10.1038/nrn2297
Miller, G. E., Chen, E., & Parker, K. J. (2011). Psychological stress in childhood and susceptibility to the chronic diseases of aging. Psychological Bulletin, 137(6), 959–997. https://doi.org/10.1037/a0024768
Predictive processing, interoception, salience, and relevance filtering
Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11, 127–138. https://doi.org/10.1038/nrn2787
Seth, A. K. (2013). Interoceptive inference, emotion, and the embodied self. Trends in Cognitive Sciences, 17(11), 565–573. https://doi.org/10.1016/j.tics.2013.09.007
Barrett, L. F., & Simmons, W. K. (2015). Interoceptive predictions in the brain. Nature Reviews Neuroscience, 16, 419–429. https://doi.org/10.1038/nrn3950
Kleckner, I. R., Zhang, J., Touroutoglou, A., et al. (2017). Evidence for a large-scale brain system supporting allostasis and interoception in humans. Nature Human Behaviour, 1, 0069. https://doi.org/10.1038/s41562-017-0069
Quigley, K. S., Kanoski, S., Grill, W. M., Barrett, L. F., & Tsakiris, M. (2021). Functions of interoception: From energy regulation to experience of the self. Trends in Neurosciences, 44(1), 29–38. https://doi.org/10.1016/j.tins.2020.09.008
Petzschner, F. H., Garfinkel, S. N., Paulus, M. P., Koch, C., & Khalsa, S. S. (2021). Computational models of interoception and body regulation. Trends in Neurosciences, 44(1), 63–76. https://doi.org/10.1016/j.tins.2020.09.012
Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: A network model of insula function. Brain Structure and Function, 214, 655–667.
Seeley, W. W., Menon, V., Schatzberg, A. F., et al. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience, 27(9), 2349–2356.
Autism, neurodivergence, sensory prediction, and interoceptive access
Pellicano, E., & Burr, D. (2012). When the world becomes “too real”: A Bayesian explanation of autistic perception. Trends in Cognitive Sciences, 16(10), 504–510. https://doi.org/10.1016/j.tics.2012.08.009
Lawson, R. P., Rees, G., & Friston, K. J. (2014). An aberrant precision account of autism. Frontiers in Human Neuroscience, 8, 302. https://doi.org/10.3389/fnhum.2014.00302
Van de Cruys, S., Evers, K., Van der Hallen, R., et al. (2014). Precise minds in uncertain worlds: Predictive coding in autism. Psychological Review, 121(4), 649–675. https://doi.org/10.1037/a0037665
Cannon, J., O’Brien, A. M., Bungert, L., & Sinha, P. (2021). Prediction in autism spectrum disorder: A systematic review of empirical evidence. Autism Research, 14(4), 604–630. https://doi.org/10.1002/aur.2482
Robertson, C. E., & Baron-Cohen, S. (2017). Sensory perception in autism. Nature Reviews Neuroscience, 18, 671–684. https://doi.org/10.1038/nrn.2017.112
DuBois, D., Ameis, S. H., Lai, M.-C., Casanova, M. F., & Desarkar, P. (2016). Interoception in autism spectrum disorder: A review. International Journal of Developmental Neuroscience, 52, 104–111. https://doi.org/10.1016/j.ijdevneu.2016.05.001
Loureiro, R., et al. (2024). Interoception in autism: A narrative review of behavioral and neurobiological data. Psychology Research and Behavior Management, 17, 1841–1853. https://doi.org/10.2147/PRBM.S410605
Kinnaird, E., Stewart, C., & Tchanturia, K. (2019). Investigating alexithymia in autism: A systematic review and meta-analysis. European Psychiatry, 55, 80–89. https://doi.org/10.1016/j.eurpsy.2018.09.004
Bird, G., & Cook, R. (2013). Mixed emotions: The contribution of alexithymia to the emotional symptoms of autism. Translational Psychiatry, 3, e285. https://doi.org/10.1038/tp.2013.61
Neurodiversity, double empathy, monotropism, and moving beyond blame
Milton, D. E. M. (2012). On the ontological status of autism: The double empathy problem. Disability & Society, 27(6), 883–887. https://doi.org/10.1080/09687599.2012.710008
Crompton, C. J., Ropar, D., Evans-Williams, C. V. M., Flynn, E. G., & Fletcher-Watson, S. (2020). Neurotype-matching, but not being autistic, influences self and observer ratings of interpersonal rapport. Frontiers in Psychology, 11, 586171. https://doi.org/10.3389/fpsyg.2020.586171
Heasman, B., & Gillespie, A. (2018). Perspective-taking is two-sided: Misunderstandings between people with Asperger’s syndrome and their family members. Autism, 22(6), 740–750. https://doi.org/10.1177/1362361317708287
Murray, D., Lesser, M., & Lawson, W. (2005). Attention, monotropism and the diagnostic criteria for autism. Autism, 9(2), 139–156. https://doi.org/10.1177/1362361305051398
Chapman, R. (2021). Neurodiversity and the social ecology of mental functions. Perspectives on Psychological Science, 16(6), 1360–1372. https://doi.org/10.1177/1745691620959833
Chapman, R., & Botha, M. (2023). Neurodivergence-informed therapy. Developmental Medicine & Child Neurology, 65(3), 310–317. https://doi.org/10.1111/dmcn.15384
Ne’eman, A., & Pellicano, E. (2022). Neurodiversity as politics. Human Development, 66(2), 149–157. https://doi.org/10.1159/000524277
Architectural medicine, built environment, and regulatory affordance
Tola, G., Talu, V., Congiu, T., Bain, P., & Lindert, J. (2021). Built environment design and people with autism spectrum disorder: A scoping review. International Journal of Environmental Research and Public Health, 18(6), 3203. https://doi.org/10.3390/ijerph18063203
Black, M. H., et al. (2022). Considerations of the built environment for autistic individuals: A review of the literature. Autism. https://doi.org/10.1177/13623613221102753
Mostafa, M. (2014). Architecture for autism: Autism ASPECTSS in school design. International Journal of Architectural Research, 8(1), 143–158. https://doi.org/10.26687/archnet-ijar.v8i1.314
Evans, G. W. (2003). The built environment and mental health. Journal of Urban Health, 80, 536–555.
Ulrich, R. S. (1984). View through a window may influence recovery from surgery. Science, 224(4647), 420–421.
Valentine, P. A. (2023). Architectural allostatic overloading: The biopsychosocial effects of spatial cognition, environmental demands, and physiological stress. International Journal of Environmental Research and Public Health, 20(9), 5637. https://doi.org/10.3390/ijerph20095637
Valentine, P. A. (2024). The neurological effects of architectural form on physiological stress: A systematic review. Frontiers in Computer Science, 5, 1237531. https://doi.org/10.3389/fcomp.2023.1237531
Valentine, P. A. (2025). Architecturally mediated allostasis: The biopsychosocial effects of chronic stress, spatial cognition, and environmental demand. Brain Sciences, 15(2), 201.
Complex systems, network medicine, and emergent patterns
Barabási, A.-L., Gulbahce, N., & Loscalzo, J. (2011). Network medicine: A network-based approach to human disease. Nature Reviews Genetics, 12(1), 56–68. https://doi.org/10.1038/nrg2918
Barabási, A.-L. (2007). Network medicine: From obesity to the “diseasome.” New England Journal of Medicine, 357(4), 404–407. https://doi.org/10.1056/NEJMe078114
Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry, 16(1), 5–13.
Sturmberg, J. P. (2021). Health and disease are dynamic complex-adaptive states: A recursive view. Frontiers in Psychiatry, 12, 595124. https://doi.org/10.3389/fpsyt.2021.595124
Leave a Reply