Autism Spectrum Disorder: The Neuroscience

Autism spectrum disorder neuroscience is a field with a lot of confident claims and fewer settled answers. About 1 in 31 eight-year-olds in the United States was identified with autism in 2022, according to the CDC, up from 1 in 150 in 2000. Researchers have found strong genetic influences, early differences in brain growth, and distinctive patterns of sensory processing, yet no single brain mechanism explains every autistic person. This article separates what is well established from what is still a hypothesis, from diagnosis and genetics to connectivity, sensory processing, and the vaccine question.

Educational content, not medical advice. This article summarizes research and does not recommend any diagnosis, treatment, or decision for any individual. Talk to a qualified clinician about any specific situation.

What autism spectrum disorder is and how it is diagnosed

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR, American Psychiatric Association, 2022) describes autism spectrum disorder (ASD) through two groups of features. The first is persistent differences in social communication and interaction, such as back-and-forth conversation, sharing interests, nonverbal communication, and building relationships. The second is restricted, repetitive patterns of behavior, interests, or activities, including insistence on sameness, intense focused interests, repetitive movements, and unusual reactions to sound, texture, light, or other sensory input.

Features must be present from early development, although they may become obvious only when social demands grow, and they must affect daily functioning. The CDC's guidance lists examples that clinicians and parents look for. Examples include limited eye contact or not responding to a name by about 9 months, not sharing interests or pointing things out by 15 to 18 months, and not pretending during play by age 4. The CDC also lists lining up objects, repeating words or phrases, and repetitive movements such as hand-flapping as typical examples of the second group.

The three support levels

Before 2013, clinicians used separate labels such as autistic disorder, Asperger syndrome, and pervasive developmental disorder not otherwise specified (PDD-NOS). The DSM-5 merged them into one spectrum diagnosis and added a rating of how much support a person needs. The CDC notes that the diagnosis now includes what were previously diagnosed separately.

Level	Support needed	What it means in practice
Level 1	Requires support	Difficulties are noticeable without supports; switching between activities and starting conversations can be hard
Level 2	Requires substantial support	Marked difficulties even with supports in place; repetitive behaviors are obvious to a casual observer
Level 3	Requires very substantial support	Severe difficulties in communication; change is extremely hard and affects functioning in every area

Source: DSM-5-TR severity specifiers. The APA's public overview notes that the need for services and supports varies among individuals.

A level describes support needs in a given setting, not intelligence, potential, or worth. The same person's needs can differ between a quiet home and a loud workplace, and they can change across the lifespan. A level is best read as a snapshot rather than a permanent label.

How diagnosis works

There is no blood test or brain scan that diagnoses autism. The CDC describes a sequence: developmental monitoring, then developmental screening, then a formal evaluation by trained specialists such as a developmental pediatrician, child psychologist, or speech-language pathologist. A screening tool alone does not produce a diagnosis. The American Academy of Pediatrics recommends general developmental screening at 9, 18, and 30 months, plus autism-specific screening at 18 and 24 months. By age 2, according to the CDC, a diagnosis by an experienced professional can be considered reliable.

Research is exploring whether brain imaging could flag risk earlier. A 2017 study in Nature followed 106 infants with an older autistic sibling and 42 low-risk infants with MRI scans. Among the 15 high-risk children later diagnosed at 24 months, cortical surface area expanded unusually between 6 and 12 months. A deep-learning model trained mainly on that measure predicted the diagnosis with a positive predictive value of 81% and a sensitivity of 88% (Hazlett and colleagues, Nature, 2017). The result is a research finding in a small, high-risk sample. It is not a clinical test.

How common is autism, and why do the numbers keep rising?

The CDC's Autism and Developmental Disabilities Monitoring (ADDM) Network reviews health and school records for 8-year-olds in selected communities. Its 2022 estimate, published in 2025, was 32.2 per 1,000 children, about 1 in 31. That figure compares with 1 in 36 for 2020, and in the 11 communities that took part in both years, prevalence rose by 22.2% (CDC, MMWR Surveillance Summaries, 2025).

Surveillance year	Prevalence per 1,000	Approximate ratio
2000	6.7	1 in 150
2008	11.3	1 in 88
2020	27.6	1 in 36
2022	32.2	1 in 31

Source: CDC ADDM Network data pages and MMWR Surveillance Summaries, vol. 74, no. SS-2 (2025).

The numbers describe children who were identified, not children who exist with a given biology. The CDC itself notes that prevalence measures identified cases, so the data alone cannot show how much of the rise reflects real changes in occurrence and how much reflects changes in identification. Several details in the 2022 report show how much identification matters. Prevalence ranged from 9.7 per 1,000 in Laredo, Texas, to 53.1 per 1,000 in California. The median age of earliest diagnosis was 47 months overall, ranging from 36 months in California to 69.5 months in Laredo. Since 2020, the proportion of Asian or Pacific Islander, Hispanic, and Black children identified has been higher than among White children, and the 2022 data continued that pattern.

Those differences point to access: communities with more evaluators, earlier screening, and more services identify more children. The DSM-5 merger of older diagnoses also widened what counts. A true biological increase cannot be ruled out, and researchers continue to study it. The honest summary is that identification has changed a great deal, and the data cannot yet separate it from any change in underlying occurrence.

Boys are identified more often than girls. The 2022 report found 49.2 per 1,000 among boys and 14.3 per 1,000 among girls, a ratio of 3.4 to 1. Researchers debate how much of that gap reflects girls being missed, for instance because they may mask their traits more, and how much reflects real differences. Globally, the World Health Organization estimates that about 1 in 127 people had autism in 2021, an average across studies that vary widely, with unknown rates in many low- and middle-income countries.

What genetics says about autism

Autism is highly heritable. In a Swedish population study of 37,570 twin pairs, 2,642,064 full-sibling pairs, and hundreds of thousands of half-sibling pairs, born between 1982 and 2006 and followed through 2009, the best-fitting model put heritability at 0.83 (95% confidence interval 0.79 to 0.87). Among twins alone the estimate was 0.87. The authors concluded that genetic factors may explain most of the risk and that the shared family environment contributed minimally (Sandin and colleagues, JAMA, 2017).

Two caveats matter. Heritability is a population statistic, not a measure of how much of an individual's autism is "caused by genes," and it does not mean any single gene determines the outcome. The authors also note that estimates are sensitive to method, partly because autism is rare and few families have more than one affected child. Using the same data, an earlier analysis estimated heritability at about 0.50.

The classic twin evidence points the same way. In a 1995 British study, 60% of identical twin pairs were concordant for autism compared with none of the fraternal pairs, and for a broader range of cognitive or social difficulties the rates were 92% and 10% (Bailey and colleagues, Psychological Medicine, 1995). The gap between identical and fraternal twins is the signature of strong genetic influence.

Many genes, not one

Autism does not follow a single-gene pattern. Think of it like a recipe that can be spoiled in hundreds of different ways: too much salt, too little heat, a missing ingredient. The results can look similar even when the causes differ. Genetic findings fall into several families. For a plain-language foundation, see how genes actually work.

• Many common variants of small effect. Each nudges risk a little, and together they account for a substantial share of the heritability. No single common variant has a large effect on its own.
• Rare, high-impact variants. A 2020 exome sequencing study in Cell examined 35,584 samples, including 11,986 people with autism, and identified 102 risk genes at a false discovery rate of 0.1 or lower (Satterstrom and colleagues, Cell, 2020). Genes frequently discussed in this literature include CHD8, which helps regulate other genes during brain development, SHANK3, which builds scaffolding at synapses, and SCN2A, which encodes a sodium channel needed for neurons to fire.
• Copy number variants. Deleted or duplicated stretches of chromosome, such as the 16p11.2 deletion, raise risk. The reciprocal duplication of the same region is associated with a different profile that includes schizophrenia, which suggests that the dose of genes in the region matters for typical brain development.

Many of these variants arise as new mutations in the child, which explains why autism can appear in families with no history of it. Others are inherited. The genetic picture has enough diversity that researchers now talk about many autisms rather than one, a view reflected in the 102-gene list, which clusters into genes for brain development and genes for the machinery of neural signaling.

What about the environment?

Genes are not the whole story. The WHO says autism probably arises from a combination of genetic and environmental factors. It lists associated factors including advanced parental age, maternal diabetes during pregnancy, prematurity, severe birth complications, low birth weight, prenatal exposure to the medicines valproate or carbamazepine, and prenatal exposure to certain air pollutants or heavy metals. Association is not causation, and several of these may reflect shared underlying risks rather than direct causes. For the broader question of how environment interacts with gene activity, see epigenetics and how the environment changes the way DNA is read, and for why association alone cannot settle cause, see how correlation differs from causation.

What differs in the autistic brain? Four hypotheses, honestly labeled

Brain research in autism has produced real findings and a tangle of competing theories. A fair summary is that some early developmental differences are well documented, while the popular, tidy stories about connectivity and neurotransmitters are hypotheses with mixed support. The sections below keep that distinction visible. For background on the organ itself, see how the brain works.

Early growth differences

The best-documented finding is about timing. In the 2017 Nature study described above, children later diagnosed with autism showed faster expansion of cortical surface area between 6 and 12 months, followed by faster brain volume growth between 12 and 24 months, and the volume growth was linked to the onset and severity of social difficulties. The authors concluded that brain changes occur during the same period when autistic behaviors first begin to appear. The sample was modest, and it concerned infants at high familial risk, so it should be replicated before it is generalized.

The excitation-inhibition hypothesis

Neurons communicate partly through excitatory signals, mainly from the chemical glutamate, which push a neighboring neuron toward firing, and inhibitory signals, mainly from GABA, which hold it back. Picture a car with an accelerator and a brake. Smooth driving needs both in balance, and a system with too much accelerator or too little brake behaves erratically. In 2003, Rubenstein and Merzenich proposed that some forms of autism result from an elevated ratio of excitation to inhibition across key neural systems, and that genetic and environmental factors acting together could produce it (Genes, Brain and Behavior, 2003). For more on how these chemical messengers work, see how neurotransmitters work.

The idea explains a lot at once, including sensory sensitivity and seizure risk, and it has guided animal-model research. Reviews still describe it as a putative mechanism rather than an established one. Autism has hundreds of genetic routes, and it is unlikely that all of them converge on the same imbalance in the same circuits. Treat the E/I hypothesis as a useful organizing idea, not a diagnosis of what is wrong in any particular brain.

The connectivity story is more complicated than the headlines

A popular summary says that autistic brains have too much local connectivity and too little long-range connectivity. The roots lie in a 2004 fMRI study of high-functioning autistic adults reading sentences: synchronization between cortical regions was consistently lower than in controls, and the authors proposed that language difficulties reflect weaker information integration across the network, which they called underconnectivity (Just and colleagues, Brain, 2004). That study opened a long line of work.

Later research did not deliver a clean pattern. A systematic review of resting-state fMRI studies described an unresolved debate, with reports of general over-connectivity, under-connectivity, and combinations of both, and suggested that age, sex, scan design, and analysis methods may explain the inconsistency (Hull and colleagues, Frontiers in Psychiatry, 2017). In other words, "local over, long-range under" is a theory with some support, not a consistent signature. Brain imaging itself adds noise: for how fMRI works and what it can and cannot show, see fMRI versus MRI brain imaging.

A related idea concerns cognitive style. The weak central coherence account proposed that autistic people favor details over the big picture. After reviewing more than 50 empirical studies, Happé and Frith concluded that evidence for a local processing bias is robust, with mixed findings on weak global processing. They argued that the detail focus may reflect superior local processing rather than a deficit, and that it may occur alongside social differences rather than explain them (Journal of Autism and Developmental Disorders, 2006). The practical reading is that attention to detail is a real, measurable strength in many autistic people, not merely the shadow of a deficit.

The default mode network and social thinking

The default mode network (DMN) is a set of brain regions, including the medial prefrontal cortex and posterior cingulate cortex, that is active during rest, self-reflection, and thinking about other people's minds. A review in 2017 linked DMN differences to two areas of social cognition in autism, self-referential processing and theory of mind (the ability to infer what others think). It described altered functional and structural organization and an atypical developmental trajectory, and it called proposed mechanisms, including E/I imbalance, putative (Padmanabhan and colleagues, Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2017). For a primer on the network, see the default mode network. Brain differences do not map straightforwardly onto deficits. They describe a different processing strategy whose costs and benefits depend on the environment.

Sensory processing: a central feature, not a side effect

For decades, sensory reactions were treated as peripheral. A 2017 review in Nature Reviews Neuroscience notes that the revision of diagnostic criteria brought sensory processing into focus as another key feature of autism, and argues that sensory traits are important for building models of the condition (Robertson and Baron-Cohen, 2017). The DSM-5 added unusual reactions to sensory input to the second group of features.

In everyday life this can mean hyper-reactivity, where a fluorescent light flickers unbearably or a clothing tag feels like sandpaper, and hypo-reactivity, where pain or temperature barely registers or a person seeks intense input such as pressure or spinning. Many autistic people experience both, depending on the sense and the day. These differences shape food choices, clothing, travel, school, and work, which is why many adults describe them as among the most practically significant parts of being autistic. They also give the E/I hypothesis its intuitive appeal, since an over-responsive sensory system would produce exactly this kind of overload, although the link remains a hypothesis.

Conditions that often travel with autism

Autism rarely comes alone. A 2019 meta-analysis in The Lancet Psychiatry pooled 96 studies and found that co-occurring mental health conditions are more prevalent in autistic people than in the general population. Prevalence was higher in clinical samples than in population-based or registry-based studies, which is a reminder that who gets counted changes the number.

Condition	Pooled prevalence (95% CI)	Notes
ADHD	28% (25 to 32)	Substantial genetic and cognitive overlap; see ADHD neuroscience
Anxiety disorders	20% (17 to 23)	An older meta-analysis of children found 39.6% with at least one anxiety disorder
Sleep-wake disorders	13% (9 to 17)	Often affects whole families
Depressive disorders	11% (9 to 13)
Obsessive-compulsive disorder	9% (7 to 10)
Bipolar disorders	5% (3 to 6)
Schizophrenia spectrum	4% (3 to 5)

Sources: Lai and colleagues, The Lancet Psychiatry, 2019; van Steensel and colleagues, Clinical Child and Family Psychology Review, 2011 (anxiety in children).

The anxiety figures show how method changes results. The 2011 child-focused meta-analysis found that 39.6% of young people with ASD had at least one anxiety disorder, nearly double the 2019 pooled estimate, and the authors reported that prevalence differed by ASD subtype, age, IQ, and whether assessment used a questionnaire or an interview. Neither number is wrong. They answer slightly different questions about different samples. For the neuroscience of anxiety itself, see anxiety and the neuroscience of fear.

Other conditions are also common. The WHO lists epilepsy, depression, anxiety, and attention deficit hyperactivity disorder as frequent co-occurring conditions. Intellectual functioning varies widely: in the 2022 CDC data, 5,292 of 8,613 children with autism (61.4%) had cognitive testing data, and 39.6% of those had an IQ of 70 or lower, which means that most had IQs above that line.

The vaccine question: what the evidence shows

In 1998, a paper in The Lancet by Andrew Wakefield and colleagues described 12 children with bowel problems and developmental regression and suggested a link to the MMR vaccine. The Lancet formally retracted the paper in 2010. The WHO's fact sheet describes the study as later shown to be fraudulent and withdrawn. The claim prompted a wave of large studies designed to test it.

The largest direct test of MMR is a Danish nationwide cohort of 657,461 children born from 1999 through 2010 and followed until August 2013. Among 6,517 autism diagnoses over about 5 million person-years, the fully adjusted hazard ratio for MMR-vaccinated versus unvaccinated children was 0.93 (95% confidence interval 0.85 to 1.02), with no increased risk in any subgroup or time period studied (Hviid and colleagues, Annals of Internal Medicine, 2019). A 2025 Danish cohort of 1,224,176 children examined aluminum in vaccines, found no evidence of increased risk of neurodevelopmental disorders, and reported an adjusted hazard ratio of 0.93 per 1-milligram increase in aluminum for neurodevelopmental disorders as a group (95% CI 0.90 to 0.97; Annals of Internal Medicine, 2025). The WHO's fact sheet states that extensive research has found that the MMR vaccine does not cause autism and that childhood vaccines containing thiomersal or aluminium have not been found to increase the risk.

A notable change in official messaging

Readers will also encounter a different message from a U.S. government source. A CDC page dated July 22, 2026 says that the statement "vaccines do not cause autism" is not evidence-based and is being corrected. It argues that studies have not ruled out a link between infant vaccines and autism and notes that the Department of Health and Human Services has launched a broad assessment of autism's causes. The same page reports that reviews of MMR found a high strength of evidence of no association, though it says the underlying observational studies have limitations. It also states that reviews by the Institute of Medicine and the Agency for Healthcare Research and Quality judged the evidence insufficient to accept or reject a causal link for several other childhood vaccines, and it highlights a supplementary analysis in a Danish aluminum study that reported an increased risk of Asperger syndrome per milligram of aluminum, which the page says warrants further study.

How should a reader weigh these? A few points help.

• "Insufficient evidence" is not the same as "evidence of harm." A review that finds too few studies to decide is describing a gap in the literature, not a signal.
• Observational studies can bound an effect even when they cannot prove a negative. In the Danish MMR cohort the upper end of the confidence interval was 1.02, which means the data are compatible with at most a very small increase and with a decrease.
• Multiple comparisons produce occasional false signals. A study that tests 50 outcomes will produce some nominally significant results by chance, which is why supplementary findings, in either direction, need replication. The authors of the aluminum study also note that small effects for some rarer disorders cannot be statistically ruled out.
• Institutions disagree in public. The WHO and the authors of the large cohorts read the evidence one way, and the July 2026 CDC page reads parts of it another way.

This article does not tell any family what to do. Vaccination decisions belong in a conversation with a trusted clinician, informed by the primary studies linked below. For how vaccines work biologically, see how vaccines actually work.

Support and intervention: what is known

There is no medication that treats the core features of autism. The CDC says medications can address co-occurring issues such as anxiety, depression, sleep problems, or seizures and should be managed by a doctor experienced in autism. The American Psychiatric Association names risperidone and aripiprazole as the two medications approved by the FDA for irritability associated with autism, when that irritability does not respond to behavioral approaches.

The CDC groups the main supports into categories:

• Behavioral: applied behavior analysis (ABA) is the best-known example, and the CDC says behavioral approaches have the most evidence for treating autism symptoms
• Developmental: speech and language therapy, occupational and physical therapy, and the Early Start Denver Model for children 12 to 48 months old
• Educational: structured approaches such as TEACCH, which adapts classroom structure and uses visual instructions
• Social-relational: social skills groups and related programs
• Psychological: cognitive behavioral therapy, adapted for co-occurring anxiety and depression

ABA is also contested. Some autistic self-advocates have criticized forms of it that aim to suppress behaviors such as stimming (repetitive self-stimulating movements) rather than to build skills the person wants, and defenders point to newer approaches that are play-based and child-led. The APA advises caution about special diets, supplements, and other unproven treatments, and about any treatment claiming to cure autism.

The neurodiversity perspective

Autistic self-advocates, joined by some researchers, have argued since the late 1990s that autism is a natural variation in human neurology rather than a disease to be cured. This neurodiversity view, which grew through online communities, rests on several ideas. Many autistic adults prefer identity-first language ("autistic person") because they see autism as part of who they are, although others prefer person-first wording and preferences vary. Advocates question interventions that aim to make a person pass as non-autistic. They push for accommodations, such as quieter environments and flexible communication, and they argue that much distress comes from environments built for other minds.

This position is compatible with supporting people who want therapy. The shift is in whose goals drive support: the autistic person's wellbeing and chosen goals, rather than the appearance of typical behavior. The tension with the medical model is genuine, partly because autism spans people who need minimal support and people who need round-the-clock care, and no single framing fits every case. Both views capture something real.

Common misconceptions

Claim	What the evidence supports
"Autism is a single condition"	It is a spectrum with many genetic routes and wide variation in support needs
"Autism is caused by parenting"	Heritability estimates are around 0.8, with shared family environment contributing minimally
"Rising rates prove an epidemic"	Counts reflect identification, which has changed; real change cannot be fully ruled out
"Only boys are autistic"	Boys are identified about 3.4 times as often, but girls are also autistic and may be missed
"The brain wiring story is settled"	Connectivity findings are mixed; E/I balance is a hypothesis
"There is one best treatment"	No treatment suits everyone; supports are matched to goals and needs

Frequently asked questions

Q: What is the difference between autism levels 1, 2, and 3? A: The DSM-5 levels describe how much support a person needs: requiring support, requiring substantial support, or requiring very substantial support. They do not measure intelligence or worth, and they can differ by setting and change over time with development and with supports.

Q: Is autism genetic? A: Strongly so. A Swedish population study estimated heritability at 0.83, and a 1995 British twin study found 60% concordance in identical twins versus none in fraternal twins. No single gene determines autism. Sequencing studies have identified more than 100 risk genes, alongside many common variants and chromosomal changes.

Q: Why are more children being diagnosed with autism? A: CDC surveillance counts identified cases, and identification has changed with broader criteria, more screening, and better access to evaluation. Prevalence in 2022 ranged from 9.7 to 53.1 per 1,000 across communities. The data cannot separate changes in identification from any change in underlying occurrence.

Q: Do vaccines cause autism? A: Large studies, including a Danish cohort of 657,461 children, found no association between MMR vaccination and autism, and the WHO says extensive research supports this. A CDC page dated July 2026 takes a different line on infant vaccines generally, arguing that a link has not been ruled out. Discuss vaccine decisions with a clinician.

Q: What causes autistic sensory sensitivities? A: The cause is not settled. The excitation-inhibition hypothesis proposes that sensory circuits are over-responsive, and research reviews describe sensory processing as a central feature of autism, but the mechanism is still being studied. Experiences differ widely between individuals.

Q: Can adults be diagnosed with autism? A: Yes. The National Institute of Mental Health notes that autism can be diagnosed at any age, and many people, especially those whose traits were missed in childhood, receive a diagnosis as adults. An evaluation by a qualified specialist is the usual route, and a diagnosis can open access to services and community.

Q: Is there a medication for autism? A: No medication treats the core features. Risperidone and aripiprazole are FDA-approved for irritability associated with autism, and other medications may be used for co-occurring conditions such as anxiety or seizures, under the care of an experienced doctor. Behavioral, developmental, and educational supports form the main part of care.

The takeaway

The most reliable findings in autism science are the plain ones: strong heritability, many contributing genes, differences visible in infancy, and a high rate of co-occurring conditions. The tidy explanatory stories, such as too much glutamate or wiring that is strong locally and weak globally, are better treated as working hypotheses that explain some people and some features. Prevalence numbers tell us more about how well communities identify autism than about biology, and the vaccine debate shows how a settled-looking question can be reopened in public even when the primary studies have not changed. The most useful frame is neither "disease to cure" nor "difference with no costs," but a developmental condition in which supports, accommodations, and a person's own goals matter as much as the mechanism.

Sources and further reading

• CDC: Autism prevalence and data and MMWR Surveillance Summaries, vol. 74, no. SS-2 (2025), ADDM Network 2022 estimates
• CDC: Clinical testing and diagnosis, signs and symptoms, and treatment
• World Health Organization: Autism fact sheet
• American Psychiatric Association: What is autism spectrum disorder?
• Sandin and colleagues, "The Heritability of Autism Spectrum Disorder," JAMA 2017
• Hviid and colleagues, "Measles, Mumps, Rubella Vaccination and Autism," Annals of Internal Medicine 2019
• Bailey and colleagues, "Autism as a strongly genetic disorder: evidence from a British twin study," Psychological Medicine 25(1), 1995
• Satterstrom and colleagues, "Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism," Cell 180(3), 2020
• Hazlett and colleagues, "Early brain development in infants at high risk for autism spectrum disorder," Nature 542, 2017
• Rubenstein and Merzenich, "Model of autism: increased ratio of excitation/inhibition in key neural systems," Genes, Brain and Behavior, 2003
• Just and colleagues, Brain 127(8), 2004; Hull and colleagues, Frontiers in Psychiatry 7, 2017; Happé and Frith, Journal of Autism and Developmental Disorders 36(1), 2006; Padmanabhan and colleagues, Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2(6), 2017; Robertson and Baron-Cohen, Nature Reviews Neuroscience 18(11), 2017
• Lai and colleagues, The Lancet Psychiatry 6(10), 2019; van Steensel and colleagues, Clinical Child and Family Psychology Review 14(3), 2011
• Wakefield and colleagues, The Lancet 351(9103), 1998, and its retraction, The Lancet 375(9713), 2010
• American Psychiatric Association, DSM-5-TR, 2022; Silberman, S., NeuroTribes, Avery, 2015

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