AutismologyAutistic studies
Autism and ASD: Current State of Knowledge and Main Theories Under Discussion
B — Critical examination
Object of study, levels of explanation, causality, and contradictions
B.1 — A clinical category is not automatically a natural essence
An ASD diagnosis can be useful for identifying needs, organizing services, forming research cohorts, and facilitating access to rights. That usefulness does not, by itself, demonstrate that the category corresponds to a homogeneous natural entity with a single mechanism.
The issue becomes methodological when one moves, without saying so, from:
“these people meet the same diagnostic criteria”
to:
“they necessarily have the same thing at the same causal level.”
That transition is not logically required.
B.2 — Heterogeneity can be both a scientific finding and a signal about how the object is constructed
The literature rightly emphasizes the heterogeneity of diagnosed populations. But two possible interpretations must be distinguished.
The first is that autism itself is extraordinarily heterogeneous.
The second is that the category used to construct the groups may bring together several different phenomena, which may share some manifestations without sharing all of their mechanisms.
These two hypotheses are not equivalent.
When successive studies find very different genetic, neurobiological, cognitive, and developmental profiles, heterogeneity should not only be statistically “corrected”; it may also provide information about the relevance of the initial category.
B.3 — Precisely measuring a category does not guarantee that the category is correctly constructed
Research can be technically excellent and produce accurate measurements while studying an object that was defined too broadly or too compositely.
This is a general methodological point: precision of measurement does not compensate for uncertainty about what has been grouped together.
If a category combines autistic functioning, adaptive difficulties, associated conditions, intellectual disability, reactions to the environment, and very different levels of support needs, then the search for one gene, biomarker, or unique mechanism for that category will inevitably encounter a great diversity of results.
That does not mean the data are false. It means their interpretation depends on the quality of the object defined at the outset.
B.4 — Observation, interpretation, and explanatory hypothesis
A large part of the controversies can be clarified by separating three levels.
- Observation: a result was measured in a task or a group.
- Interpretation: the result is described as a deficit, preference, strategy, compensation, increased precision, rigidity, and so on.
- Explanatory hypothesis: a broader mechanism is proposed to account for several observations.
For example, better performance on a local perceptual task is an observation. Describing it as “superior local processing” is already an interpretation. Making it the consequence of a particular neurodevelopmental organization is an additional hypothesis.
The distinction does not prohibit any theory; it only prevents one level from being presented as though it automatically contained the next ones.
B.5 — Correlation, association, and causality
Genetic associations illustrate this problem particularly well.
A variant may be statistically more frequent in a diagnosed population without being a unique cause of the diagnosis. A variant associated with several different developmental presentations does not justify concluding that it specifically produces “autism” as a single-mechanism disease.
The same principle applies to imaging, EEG, metabolism, or the microbiome: an average difference between groups does not automatically establish a complete causal chain.
The proper question is therefore not only “is there a difference?”, but also:
- in which population?
- with what effect size?
- does this difference precede the phenomenon being studied?
- is it specific?
- is it necessary or sufficient?
- could it be a consequence, an adaptation, or an indirect correlation?
B.6 — Several levels of analysis are often placed on the same plane
The source document juxtaposes genetics, neurophysiology, perception, categorization, social interaction, identity politics, and support needs. All of these domains are relevant, but they do not answer the same question.
A genetic variant, an EEG latency, a perceptual preference, a categorization strategy, a conversational difficulty, and an administrative category are objects at different levels.
A theory becomes fragile when it claims to move directly from one level to another without a sufficiently established intermediate mechanism.
Saying that a phenomenon is “biological” does not replace an explanation of how it becomes an experience, a behaviour, or a concrete difficulty.
B.7 — Vocabulary can introduce a conclusion before the analysis
Apparently technical words sometimes carry an implicit interpretation.
“Autism risk” presents autistic existence itself as the undesirable event whose occurrence should be prevented. When a study actually measures a statistical association with the probability of receiving an ASD diagnosis, it is more precise to describe that association.
“Severity” may summarize a useful operational score, but it becomes ambiguous unless one specifies what is severe: support need, communication difficulties, epilepsy, intellectual disability, anxiety, functional impact, or deviation from a behavioural norm.
“Deficit” may be legitimate when a measured mechanism or capacity is genuinely reduced. But the same result can sometimes be described as a different priority, a processing style, or a strategy. The word should not decide among those possibilities in advance.
B.8 — Subcategories can move the problem without solving it
“Syndromic / non-syndromic,” “idiopathic / secondary,” “essential / complex,” “prototypical,” “profound”: each of these distinctions addresses a real problem.
But multiplying subcategories does not automatically guarantee better understanding.
A subcategory may be useful:
- for identifying a genetic etiology;
- for comparing developmental trajectories;
- for describing support needs;
- for constructing a more homogeneous research protocol.
It becomes problematic when it is treated as a new “species” without independent evidence that the boundary corresponds to a distinct mechanism.
B.9 — Why apparently contradictory theories can all find results
Weak central coherence, EPF, Bayesian models, predictive processing, categorization models, and “enhanced rationality” can appear incompatible if each is read as a general theory of autism.
But many of these studies actually concern different tasks, different levels, and different subgroups.
One person may simultaneously show:
- strong perceptual discrimination in one task;
- different use of context in another;
- good explicit learning ability;
- difficulty in a particular probabilistic-learning task;
- lower susceptibility to certain decision biases;
- and substantial difficulties in real-life social interaction.
These observations are not necessarily contradictory. The conflict appears when each is converted into a total explanation.
B.10 — Group studies do not automatically describe an individual
A statistically significant mean difference can coexist with substantial overlap between groups.
If the mean of an autistic group differs from that of a non-autistic group, this does not mean that every individual in the first group has the characteristic, nor that no individual in the second group has it.
Research must therefore avoid turning a probabilistic group difference into an essentialist individual description.
This is particularly important in public communication, where modest findings may be simplified into claims such as “the autistic brain does X.”
B.11 — Research instruments may incorporate the frame of reference they claim to measure
A social or cognitive task is never entirely neutral. It depends on instructions, conventions, a response format, the time allowed, a definition of the correct answer, and a laboratory context.
A test built from majority functioning may measure both the capacity of interest and familiarity with the format or with non-autistic expectations.
Research on Raven/Wechsler profiles and on double empathy shows precisely that the result may change when the tool or the interaction partner changes.
This does not make tests useless. It requires analysis of what they actually measure.
B.12 — Environment and interaction have long been secondary variables
Much clinical research begins with characteristics observed in the individual. That is logical for an individual diagnosis, but less sufficient for understanding phenomena that arise within an interaction or an environment.
A communication difficulty may depend on:
- the autistic person;
- the interaction partner;
- the channel used;
- noise or lighting;
- the processing time allowed;
- predictability;
- implicit expectations;
- reciprocal errors of interpretation.
Double empathy made this issue visible in the social domain. A similar approach may be necessary in other domains.
B.13 — The non-autistic frame of reference often remains implicit
Many expressions compare the autistic person with a norm without studying that norm with equal intensity.
“Weak coherence,” “restricted interest,” “rigidity,” “social atypicality,” “lack of flexibility,” or “abnormality of contact” describe a deviation. But a deviation only has meaning relative to a point of comparison.
Majority functioning is often treated as the zero point of the instrument: it does not need to be explained, while every deviation requires an explanation.
Scientifically, this asymmetry deserves to be made explicit. A rigorous comparison should be able to describe the properties of both forms of functioning and their interactions, rather than analyzing only one side of the difference.
B.14 — What can be retained without accepting every interpretation
Critical examination does not lead to rejecting existing research. On the contrary, it allows its findings to be used more effectively.
For each theory or result, one can distinguish:
- the probably robust observation;
- the interpretation proposed by the authors;
- assumptions that may be unnecessary or insufficiently demonstrated.
For example, a difference in susceptibility to certain perceptual illusions may be a robust result, while its interpretation as a deficit or as a superiority may remain debatable.
Likewise, a genetic association may be highly robust without providing a definition of autism.
This separation avoids two opposite errors: mechanically accepting all discourse produced within a medical framework, or discarding useful scientific data simply because an interpretation appears inadequate.
B.15 — Conclusion of the critical examination
The main problem in the current state of knowledge is not a lack of data. The data are numerous and often sophisticated.
The problem is determining which data concern which object, at what level, and within which frame of reference.
The diversity of findings may reflect the real complexity of human development. It may also reveal that several phenomena have been brought together under the same clinical category and that different levels of explanation are then compared as though they answered a single question.
Part C examines what this landscape becomes when the method of Autismology is explicitly taken as the starting point.