Merge-based syntax is mediated by distinct neurocognitive mechanisms: A clustering analysis of comprehension abilities in 84,000 individuals with language deficits across nine languages

Merge-based syntax is mediated by distinct neurocognitive mechanisms: A clustering analysis of comprehension abilities in 84,000 individuals with language deficits across nine languages | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Merge-based syntax is mediated by distinct neurocognitive mechanisms: A clustering analysis of comprehension abilities in 84,000 individuals with language deficits across nine languages Elliot Murphy, Rohan Venkatesh, Edward Khokhlovich, Andrey Vyshedskiy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7294415/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract In the modern language sciences, the core computational operation of syntax, ‘Merge’, is defined as an operation that combines two linguistic units (e.g., ‘brown’, ‘cat’) to form a categorized structure (‘brown cat’, a Noun Phrase). This can then be further combined with additional linguistic units based on this categorial information, respecting non-associativity such that abstract grouping is respected. Some linguists have embraced the view that Merge is an elementary, indivisible operation that emerged in a single evolutionary step. From a neurocognitive standpoint, different mental objects constructed by Merge may be supported by distinct mechanisms: (1) simple command constructions (e.g., “eat apples”); (2) the merging of adjectives and nouns (“red boat”); and (3) the merging of nouns with spatial prepositions (“laptop behind the sofa”). Here, we systematically investigate participants’ comprehension of sentences with increasing levels of syntactic complexity. Clustering analyses revealed behavioral evidence for three distinct structural types, which we discuss as potentially emerging at different developmental stages and subject to selective impairment. While a Merge-based syntax may still have emerged suddenly in evolutionary time, responsible for the structured symbolic turn our species took, different cognitive mechanisms seem to underwrite the processing of various types of Merge-based objects. Humanities/Language and linguistics Social science/Language and linguistics Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology Merge language evolution recursive language syntax acceptability Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 Introduction In modern linguistics, Merge is a proprietary cognitive operation that combines two linguistic units (e.g., ‘blue’, ‘cat’) to form a categorized, labeled set (‘blue cat’, a Noun Phrase), which can then be further combined with additional linguistic units (Chomsky, 1995 , 2000 ). The field of linguistics has largely coalesced around the hypothesis that unbounded Merge is a uniquely human ability, serving as the generative engine underlying the human capacity to generate or communicate an infinite number of expressions (Tanaka et al., 2019 ). Some researchers, such as Berwick and Chomsky, have noted that due to the ‘absolute’ nature of Merge (one either has it, or does not have it), no partial or ‘proto-Merge’ is plausible: “The elementary operation of binary set formation (Merge) appeared in a single step” (Berwick & Chomsky, 2019 ). From a neurocognitive standpoint, it may be plausible to decompose distinct generic cognitive operations that subserve distinct components of a Merge-based syntax (e.g., the formation of hierarchical objects, the categorization of phrases, the short-term maintenance of categorial identity) (Murphy, 2015 ). From the perspective of linguistic formalism, the simplicity of the Merge operation is strikingly elegant. Its concise formulation echoes (intentionally) the parsimony of Hamilton’s principle of least action and fundamental physical laws, such as the conservation of energy and the conservation of momentum (Murphy, Holmes, et al., 2024). But from a neurocognitive standpoint, it is becoming increasingly plausible that different levels of Merge-based complexity may be supported by distinct nodes in the extended language network (Murphy, 2020 , 2024 , 2025 ; Murphy et al., 2022 , 2023 ; Murphy, Rollo, et al., 2024 ). Studies involving large numbers of participants with language deficits offer a powerful approach to investigating the nature of Merge-based syntax. By including tens of thousands of individuals with a range of conditions associated with language impairments, researchers can observe the effect of a wide variety of genetic abnormalities linked to linguistic deficits. Merge interfaces with various conceptual and performance systems, and if some of these exhibit digital/discrete representations but others exhibit analog/graded representations (Jackendoff & Erk, 2025 ), we may expect to find genetic abnormalities that cause a gradual degradation of syntactic and semantic performance. Conversely, if Merge outputs to a single restricted and homogeneous domain-general interface, its loss should be catastrophic and complete. Yet, previous studies have shown that neither of these two hypotheses is strongly supported. Two studies of tens of thousands of individuals identified three distinct general levels of what a Merge-based syntax can output: Syntactic, Modifier, and Command (Vyshedskiy, Venkatesh, & Khokhlovich, 2024 ; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). The Syntactic Phenotype is exhibited by most adults and by children aged four years and older (Vyshedskiy et al., 2025 ). Individuals with this phenotype can comprehend sentences containing spatial prepositions, reversible word order, verb tenses, possessive pronouns, complex explanations, and elaborate fairytales demanding an array of these construction types (Table 1 , Syntactic Mechanism ). Approximately 2% of adults, as well as children between the ages of three and four, exhibit the Modifier Phenotype. Their ability is limited to combinations of nouns and adjectives (e.g., they can select ‘a small green pencil’ from a set of pencils, straws, and Lego pieces of different sizes and colors; Table 1 , Modifier Mechanism ). Finally, about 1% of adults, and children aged two to three years, exhibit the Command Phenotype, being restricted to simple commands (e.g., ‘eat apple’; Table 1 , Command Mechanism ). Note that these categories delimit overt linguistic performance and major aspects of competence, but may not reflect the full extent of underlying competence. Table 1 Three language comprehension mechanisms—Syntactic, Modifier, and Command—have been identified in previous studies (Vyshedskiy, Venkatesh, & Khokhlovich, 2024 ; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). When one mechanism is acquired, the entire range of associated comprehension abilities is also gained. The Command-level abilities (Items 1 to 4) are acquired first. The Modifier-level abilities (Items 5 to 8) are attained next. The Syntactic-level abilities (Items 9 to 15) are acquired last. The language comprehension items are presented exactly as surveyed with parents in both this and earlier studies. Response options were: very true, somewhat true, and not true. Items 1 to 3 were assessed as part of the Expressive Language ATEC (Rimland & Edelson, 1999 ) subscale 1; the rest of items were a part of the MSEC subscale (Braverman et al., 2018 ). Language comprehension items (verbatim) Abbreviations used in dendrograms Command Mechanism 1 Knows own name Knows Name 2 Responds to ‘No’ or ‘Stop’ No and Stop 3 Responds to praise Resp. to Praise 4 Can follow some commands Commands Modifier Mechanism 5 Understands some simple modifiers (i.e., green apple vs. red apple or big apple vs. small apple) Color or Size / Modifiers 6 Understands several modifiers in a sentence (i.e., small green apple) Two Modifiers 7 Understands size (can select the largest/smallest object out of a collection of objects) Size Superlatives 8 Understands NUMBERS (i.e., two apples vs. three apples) Numbers Syntactic Mechanism 9 Understands spatial prepositions (i.e., put the apple ON TOP of the box vs. INSIDE the box vs. BEHIND the box) Sp. Prepositions 10 Understands verb tenses (i.e., I will eat an apple vs. I ate an apple) Verb Tenses 11 Understands simple stories that are read aloud Simple Stories 12 Understands elaborate fairytales that are read aloud (i.e., stories describing FANTASY creatures) Elab. Fairytales 13 Understands possessive pronouns (i.e., your apple vs. her apple) Poss. Pronouns 14 Understands the change in meaning when the order of words is changed (i.e., understands the difference between 'a cat ate a mouse' vs. 'a mouse ate a cat') Flexible Syntax 15 Understands explanations about people, objects or situations beyond the immediate surroundings (e.g., “Mom is walking the dog,” “The snow has turned to water”). Explanations These findings suggest that while Merge-based syntax can degrade in a seemingly catastrophic manner, it does not vanish entirely. For example, individuals functioning at the intermediate Modifier level lose the ability to comprehend fairytales, spatial prepositions, verb tense, and possessive pronouns, but they retain the capacity to integrate adjectives with nouns, form noun phrases with superlatives, and perform similar compositional tasks. This dovetails with the observation that even in the most severe cases of lesion-based syntactic disruption, some capacity to execute basic hierarchical structure-formation is often preserved (in some format) (Dragoy et al., 2017 ). Within this context of open questions, the goals of the present study were: (1) to relate the Command, Modifier, and Syntactic Mechanisms to Merge-based syntax; (2) to analyze a larger cohort of participants than previous work; and (3) to confirm the dissociation among the three Mechanisms within each of the nine languages analyzed individually. Languages differ significantly in their grammatical structures, word order, word order flexibility, and morphological complexity. For instance, English typically follows a subject–verb–object word order, whereas languages like Japanese and Korean follow a subject–object–verb structure. In English, adjectives are generally pre-nominal—one would say “ the large cat ”, not “ the cat large ”. In contrast, Romance languages often place adjectives after the nouns they modify. Morphological complexity also varies widely: Russian, for example, features an extensive system of inflectional case endings, in contrast to the relatively simple morphology of English. This greater morphological richness in Russian contributes to its more flexible word order. If the Command, Modifier, and Syntactic Mechanisms differ across languages, we might be able to associate these grammatical differences with corresponding variations in those mechanisms. Conversely, if no such differences are observed, it would suggest that these three mechanisms—Command, Modifier, and Syntactic—may be universal across languages. Methods Study Participants Participants were children and adolescents using a language therapy app that was made freely available at all major app stores in September 2015 (Dunn, Elgart, Lokshina, Faisman, Khokhlovich, et al., 2017b, 2017a; Dunn, Elgart, Lokshina, Faisman, Waslick, et al., 2017; Vyshedskiy et al., 2020 ; Vyshedskiy & Dunn, 2015 ). The app provides various structured language comprehension therapy exercises and is primarily used by caregivers of children with language impairments. Most of the caregivers are presumed to be parents. Once the app was downloaded, caregivers were asked to register and to provide demographic details, including the child’s diagnosis and age. Caregivers consented to pseudonymized data analysis and completed a 133-item questionnaire (77-item Autism Treatment Evaluation Checklist (ATEC) (Rimland & Edelson, 1999 ), Supplementary Tables 1–4; 20-item Mental Synthesis Evaluation Checklist (MSEC) (Braverman et al., 2018 ), Supplementary Table 5; 10-item screen time checklist (Fridberg et al., 2021 ); 25-item diet checklist (Acosta et al., 2023 ); and 1-item parent education survey) approximately every three months. In what follows, we reproduce much of the Methods details from one of our previous publications (Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). All fifteen available language comprehension items from the 133-item questionnaire were included in the cluster analysis as in previously published articles (Vyshedskiy, Venkatesh, & Khokhlovich, 2024 ; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024) (Table 1 ). Answer choices were as follows: very true (0 points), somewhat true (1 point), and not true (2 points). A lower score indicates better language comprehension ability. The inclusion criteria for this study remained consistent with those of previous studies (Vyshedskiy, Venkatesh, & Khokhlovich, 2024 ; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024): absence of seizures (which commonly result in intermittent, unstable language comprehension deficits (Forman et al., 2022 )), absence of serious and moderate sleep problems (which are also associated with intermittent, unstable language comprehension deficits (Levin et al., 2022 )), age range of 4 to 22 years (the lower age cutoff was chosen to ensure that participants were exposed to complete set of sentence structures listed in Table 1 (Arnold & Vyshedskiy, 2022 ); the upper age cutoff was chosen to avoid analysis of participants who may be linguistically declining due to aging). Previous studies were limited to individuals diagnosed with Autism Spectrum Disorder (ASD) (Vyshedskiy, Venkatesh, & Khokhlovich, 2024 ) and individuals with fluid speech (Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). This study included all participants who submitted their assessments through the app, speaking one of the nine languages that the app is available in: English, Spanish, Portuguese, Italian, Russian, Chinese, French, German, and Korean. Table 2 reports participants’ demographics in each language group as communicated by caregivers. Males outnumber females by approximately four to one, reflecting the predominance of autism among participants and its known male-to-female prevalence ratio. Table 2 Participants’ demographics. Number of Participants Percent of Total Age, Mean(SD) Percent Males English 27187 32.3 6.7(2.9) 75.8 Spanish 33488 39.8 6.1(2.2) 68.3 Portuguese 7504 8.9 6.3(2.5) 76.3 Italian 6484 7.7 7.6 (3.2) 78.3 Russian 4778 5.7 6.8(2.5) 77.9 Chinese 2217 2.6 6.1(2.0) 79.2 French 1060 1.3 7.2(3.2) 72.5 German 927 1.1 7.2(3.2) 69.9 Korean 454 0.5 6.6(2.7) 74.2 Total 84099 100 6.5(2.7) 74.7 Table 3 reports participants’ diagnoses as communicated by caregivers. Autism level (mild/Level 1, moderate/Level 2, or severe/Level 3) was reported by caregivers. Pervasive Developmental Disorder and Asperger Syndrome were combined with mild autism for analysis as recommended by DSM-5 (American Psychiatric Association, 2013 ). A good reliability of such parent-reported diagnosis has been previously demonstrated (Jagadeesan et al., 2022 ). Table 3 Participants’ diagnoses. Number of Participants Percent of Total Age, Mean(SD) Percent Males Mild Autism Spectrum Disorder (ASD) 29292 34.8 6.2(2.4) 75.8 Moderate ASD 19094 22.7 6.9(2.8) 79.5 Severe ASD 10839 12.9 7.6(3.3) 80.0 Not-diagnosed 9869 11.7 5.7(1.6) 54.2 Specific Language Impairment 4884 5.8 6.0(2.2) 69.2 Mild Language Delay 3973 4.7 5.4(1.7) 67.4 ADHD 1630 1.9 6.4(2.2) 72.8 Down Syndrome 1427 1.7 8.5(3.5) 60.4 Other Genetic Disorder 1104 1.3 8.0(3.5) 57.7 Social Communication Disorder 794 0.9 6.3(2.3) 69.1 Sensory Processing Disorder 727 0.9 6.8(2.7) 70.2 Apraxia 466 0.6 6.8(2.9) 64.6 Total 84099 100 6.5(2.7) 74.7 When caregivers have completed several evaluations, the last evaluation was used for analysis as in previous studies (Vyshedskiy, Venkatesh, & Khokhlovich, 2024 ; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). Thus, the study included a total of 84,099 participants, the average age was 6.5 ± 2.7 years (range of 4 to 21.9 years), 74.7% participants were males. The education level of participants’ parents was the following: 90.9% with at least a high school diploma, 68.6% with at least college education, 35.8% with at least a master’s, and 5.6% with a doctorate. All caregivers consented to pseudonymized data analysis and publication of results. The study was conducted in compliance with the Declaration of Helsinki (World Medical Association, 2013 ). Using the Department of Health and Human Services regulations found at 45 CFR 46.101(b)(4), the Biomedical Research Alliance of New York (BRANY) LLC Institutional Review Board (IRB) determined that this research project is exempt from IRB oversight (IRB File # 22-12-205-1120). The data was accessed on July 9, 2025. Statistics and Reproducibility Unsupervised Hierarchical Cluster Analysis (UHCA) was performed using Ward’s agglomeration method with a Euclidean distance metric. The clustering analysis was data-driven without any design or hypothesis. A two-dimensional heatmap was generated using the “pheatmap” package of R, freely available language for statistical computing (R Foundation for Statistical Computing, 2021 ). Code and data can be downloaded ( doi.org/10.17605/OSF.IO/2QK5B ). Results Clustering analysis of 15 language comprehension abilities Caregivers assessed 15 language comprehension abilities (Table 1). To examine patterns of co-occurrence among these abilities, we applied unsupervised hierarchical cluster analysis—a data-driven method that groups items based on their similarity. This technique produces tree-like diagrams, called dendrograms , which visually represent the hierarchical relationships between clusters of items. Abilities that frequently co-occur are positioned closely together, while those that co-occur less often appear farther apart. Figure 1A depicts the dendrogram generated from the analysis of English-speaking participants. The height of the branches indicates the distance between clusters. A larger distance corresponds to greater dissimilarity between the clusters. Previous studies identified three clusters stable across different evaluation methods, age groups, time points, genders, and parental education (Vyshedskiy, Venkatesh, & Khokhlovich, 2024; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). The first cluster included knowing the name, responding to ‘No’ or ‘Stop’, responding to praise , and following some commands (items 1 to 4 in Table 1) and was termed the Command Mechanism. The second cluster included understanding color and size modifiers, several modifiers in a sentence, size superlatives , and numbers (items 5 to 8 in Table 1) and was termed the Modifier Mechanism. The third cluster included understanding of spatial prepositions, verb tenses, flexible syntax, possessive pronouns, explanations about people and situations, simple stories , and elaborate fairytales (items 9 to 15 in Table 1) and was termed the Syntactic Mechanism. The analysis of English-speaking participants in Fig. 1A identified the same three clusters with inter-cluster distances that were significantly larger than the distances between subclusters. Principal component analysis (PCA) (Fig. 1B) also showed a clear separation between the three clusters: Command, Modifier and Syntactic. As a control we calculated unsupervised hierarchical cluster analysis and PCA of the 15 comprehension abilities along with the “ hyperactivity ” (Figures S1), “ bed-wetting ” (Figure S2), and “ demands sameness ” (Figure S3) items. These items are not related to language and therefore should cluster into their own group. As expected, both unsupervised hierarchical cluster analysis and PCA clustered these items into their own group at a significant distance from the Command, Modifier, and Syntactic clusters, validating both clustering techniques. Clustering analysis across spoken languages Clustering analysis was conducted in all language groups with 400 or more participants. The three-cluster solution was consistent across all language groups explored: English, Spanish, Portuguese, Italian, Russian, Chinese, French, German, and Korean (Figs. 1–9). In all spoken languages, unsupervised hierarchical cluster analysis sorted the 15 comprehension abilities into congruent three clusters (Command, Modifier, and Syntactic) and PCA showed a clear separation between the three clusters. Some language groups, such as Russian (Fig. 5B), demonstrated a greater separation between clusters in PCA. These findings suggest that the three-cluster solution is not a result of differential cultural upbringing but rather a potentially general cognitive phenomenon constrained, consistent across spoken languages. Language comprehension phenotypes in participants Previous studies have employed unsupervised hierarchical cluster analysis to identify distinct language comprehension phenotypes of participants (Vyshedskiy, Venkatesh, & Khokhlovich, 2024; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). The principles underlying participant clustering are identical to those used for clustering abilities: participants with similar patterns of abilities are automatically organized into hierarchical dendrograms. Previous studies identified three distinct phenotypes: 1) Command Phenotype–participants who acquired only the Command Mechanism; 2) Modifier Phenotype–participants who acquired both the Command and Modifier Mechanisms; and 3) Syntactic Phenotype–participants who acquired the Command, Modifier, and Syntactic Mechanisms. The close correspondence between comprehension mechanisms and the resulting phenotypes is noteworthy. While various combinations of the three mechanisms are theoretically possible, such combinations were not observed empirically. For example, a hypothetical phenotype combining the Command and Syntactic Mechanisms (but not the Modifier Mechanism) could exist in theory. Another possibility would be a phenotype lacking all three mechanisms. However, these configurations did not emerge from the data. This absence suggests that the ‘morphospace’ of comprehension phenotypes is constrained by cognitive faculties. To investigate whether these constraints are consistent across different languages, this study conducted the unsupervised hierarchical cluster analysis of participants separately within each language group. The results are presented in Figs. 10–18, which relate participant clusters to comprehension mechanisms. The three mechanism clusters (Command, Modifier, and Syntactic) are shown as rows (the dendrogram from Fig. 1A representing comprehension mechanisms is shown vertically on the left in Fig. 10) and the 27,187 English-speaking participants are shown as columns (the dendrogram representing participants is shown horizontally on the top). Blue indicates the presence of a linguistic ability (parent’s response = very true ); white indicates an intermittent presence of a linguistic ability (parent’s response = somewhat true ); and red indicates the complete lack of a linguistic ability (parent’s response = not true ). In the heatmap of English-speakers (Fig. 10), the middle cluster of participants (marked “Syntactic Phenotype”) shows the predominant blue color (representing good skills) across all abilities indicating that these participants acquired the Command, Modifier, and Syntactic Mechanisms. The leftmost cluster of participants (marked “Command Phenotype”) shows the predominant blue color only among the Command Mechanism items and red colors across Syntactic and Modifier Mechanisms items, indicating that these individuals only acquired the Command Mechanism. The rightmost cluster of participants (marked “Modifier Phenotype”) shows the predominant blue color only across Command and Modifier Mechanisms items and white to red colors across Syntactic Mechanism items, indicating that these individuals acquired the Command and Modifier Mechanisms. This pattern was reproduced across all language groups (Figs. 10–18). Participants acquired either: 1) the Command Mechanism alone (marked as the Command Phenotype), or 2) both the Command and Modifier Mechanisms (marked as the Modifier Phenotype), or 3) the Command, Modifier, and Syntactic Mechanisms (marked as the Syntactic Phenotype). Discussion We conducted a clustering analysis to examine the co-occurrence of fifteen language comprehension abilities in 84,099 individuals who spoke English, Spanish, Portuguese, Italian, Russian, Chinese, French, German, or Korean. The three identified clusters were identical between languages and congruent to those found in previous analyses (Vyshedskiy, Venkatesh, & Khokhlovich, 2024 ; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). Crucially, the clustering analysis in all studies was devoid of any design or hypothesis, as both unsupervised hierarchical clustering analysis and principal component analysis (PCA) were entirely driven by the data. The outcome of our clustering analyses is a set of three coherent, discrete language ability clusters that appear to revolve around similar linguistic deficits concerning modifiers and complex syntactic operations—not a mixed amalgam of different patterns that would be expected if language abilities were mediated by many unrelated mechanisms. We note here some limitations of our work: A 133-item survey completed repeatedly by motivated parents is invaluable, but still prone to optimism, fatigue, and socioeconomic skew. Future work could strengthen the validity of findings by quantifying inter-rater reliability (e.g., by having both parents independently complete the survey). While one study has demonstrated a strong correlation between the parent-reported survey used in this study and a clinicians-administered Language Phenotype Assessment ( r = 0.78, p < 0.0001) (Vyshedskiy et al., 2025 ), further validation could involve comparing a subsample of parent responses with results from standardized clinician-administered instruments (e.g., PLS-5 (Zimmerman et al., 2011 ), Token Test (A. De Renzi & Vignolo, 1962 ; E. De Renzi & Faglioni, 1978 ), CELF-5 (Wiig et al., 2013 ), TROG (Bishop, 2009 )). Our enrollment protocol also filters for relatively “tech-savvy”, intervention-seeking parents and may under-represent low-SES households. A comparison of census-matched demographics would help establish external validity. In addition, the disorders reported in our study differ in etiology and linguistic phenotype; since the same caregiver questionnaire supplies both phenotype and explanatory variable, latent correlations may inflate cluster separability. The replication of the three-cluster solution across English, Spanish, Portuguese, Italian, Russian, Chinese, French, German, and Korean likely points to language-independent constraints. Notable, the languages examined in this study vary widely in morphological complexity, word order and word order flexibility. For example, Russian has a much richer morphological system and greater word order flexibility than English; while Korean follows subject–object–verb structure, which differs from the subject–verb–object order typical of Indo-European languages. Despite these structural differences, all nine languages consistently revealed clear distinctions among the three linguistic mechanisms—Command, Modifier, and Syntactic—indicating that these distinctions may be universal. Some may argue here that the three clusters reflect emergent probabilistic constructions rather than discrete cognitive mechanisms. However, the sharp boundaries we observe (especially the near-absence of Modifier-without-Command or Syntactic-without-Modifier profiles) are difficult to reconcile with a purely continuous competence model. Future work could operationalize the predictions of usage-based linguistic theories to more carefully explore these topics. The present behavioral gradient (Command → Modifier → Syntactic) demonstrates that a single explanatory construct, Merge, can be developmentally unpacked into sub-routines mastered at different developmental stages: the Command Mechanism by 1.6 years of age, the Modifier mechanism by 3.0 years of age, and the Syntactic Mechanism by 3.7 years of age (Vyshedskiy et al., 2025 ). From an evolutionary perspective, this aligns with a “saltation-plus-scaffolding” model: an initial binary set-forming capacity may have arisen abruptly (Berwick & Chomsky, 2019 ), but its efficient deployment in real-time cognition and communication required incremental recruitment of domain-general resources such as working memory, attention (Murphy, 2019 , 2024 ) and articulate speech (Vyshedskiy, 2022 ). It is possible that the layered neurocognitive architecture that supports modern human syntax may provide some basis for the behavioral results we document here. Isolating behavioral dynamics of “Command”, “Modifier”, and “Syntactic” mechanisms might allow us to refine long-standing psycholinguistic debates about the grain-size of syntactic representations accessed during real-time comprehension. For example, classic garden-path effects show that comprehenders incrementally commit to local syntactic analyses that sometimes require costly reanalysis when later input forces revision. If the Modifier mechanism licenses phrase-internal operations such as adjective-noun union, while the Command mechanism governs clausal argument structure, then garden-path costs should be sharply magnified whenever disambiguation pivots on Command-level information (e.g., NP-attachment vs. VP-attachment ambiguities). Conversely, ambiguities resolvable within the Modifier mechanism (e.g., prenominal adjective stacking) should yield milder slow-downs. Our results suggest that the conceptual and performance systems that access Merge-based syntax are fractionated behaviorally into distinct mechanistic groups. We hope that these results play some role in addressing a long-standing gap between formal linguistic theory and large-scale behavioral phenotyping. Our reported sample is an order of magnitude larger than typical language-impairment studies, improving power to detect stable substructures, but many further questions remain concerning the granularity of the documented sets of language deficits. Declarations Funding This research received no external funding. Acknowledgements We wish to thank all participants’ caregivers who found time to complete children’s assessments. The language therapy app used to collect the data presented in this manuscript was made possible by the contributions of Rita Dunn, Alexander Faisman, Jonah Elgart, Lisa Lokshina, and Yulia Dumov. Author Contributions AV designed the study. EK developed the statistical paradigm. RV wrote the statistical analysis software. AV analyzed the data. EM and AV wrote the paper. Competing Interests Authors declare no competing interests. Data Availability De-identified raw data from this manuscript are available from the corresponding author upon reasonable request. Code Availability Code is available from the corresponding author upon reasonable request. Ethics Statement The study was conducted in compliance with the Declaration of Helsinki. Informed consent was obtained from the caregivers of all participants. The study protocol was approved by the Biomedical Research Alliance of New York (BRANY) LLC Institutional Review Board (IRB). References Acosta, A., Khokhlovich, E., Reis, H., & Vyshedskiy, A. (2023). Dietary factors impact developmental trajectories in young autistic children. Journal of Autism and Developmental Disorders . https://doi.org/10.1007/s10803-023-06074-8 American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®) . American Psychiatric Pub. Arnold, M., & Vyshedskiy, A. (2022). Combinatorial language parent-report score differs significantly between typically developing children and those with Autism Spectrum Disorders. Journal of Autism and Developmental Disorders . https://doi.org//10.1007/s10803-022-05769-8 Berwick, R. C., & Chomsky, N. (2019). All or nothing: No half-Merge and the evolution of syntax. PLoS Biology , 17 (11), e3000539. Bishop, D. V. (2009). TROG 2: Test for reception of grammar-version 2. Edizioni Giunti OS, Firenze . Braverman, J., Dunn, R., & Vyshedskiy, A. (2018). Development of the Mental Synthesis Evaluation Checklist (MSEC): A Parent-Report Tool for Mental Synthesis Ability Assessment in Children with Language Delay. Children , 5 (5), Article 5. https://doi.org/10.3390/children5050062 Chomsky, N. (1995). The minimalist program. MIT Press, Cambridge, MA . Chomsky, N. (2000). Minimalist inquiries: The framework. Step by Step: Essays on Minimalist Syntax in Honor of Howard Lasnik , 89–155. De Renzi, A., & Vignolo, L. A. (1962). Token test: A sensitive test to detect receptive disturbances in aphasics. Brain: A Journal of Neurology . De Renzi, E., & Faglioni, P. (1978). Normative data and screening power of a shortened version of the Token Test. Cortex , 14 (1), Article 1. Dragoy, O., Akinina, Y., & Dronkers, N. (2017). Toward a functional neuroanatomy of semantic aphasia: A history and ten new cases. Cortex , 97 , 164–182. Dunn, R., Elgart, J., Lokshina, L., Faisman, A., Khokhlovich, E., Gankin, Y., & Vyshedskiy, A. (2017a). Children With Autism Appear To Benefit From Parent-Administered Computerized Cognitive And Language Exercises Independent Of the Child’s Age Or Autism Severity. Autism Open Access , 7 (217). https://doi.org/10.4172/2165-7890.1000217 Dunn, R., Elgart, J., Lokshina, L., Faisman, A., Khokhlovich, E., Gankin, Y., & Vyshedskiy, A. (2017b). Comparison of performance on verbal and nonverbal multiple-cue responding tasks in children with ASD. Autism Open Access , 7 , 218. https://doi.org/10.4172/2165-7890.1000218 Dunn, R., Elgart, J., Lokshina, L., Faisman, A., Waslick, M., Gankin, Y., & Vyshedskiy, A. (2017). Tablet-Based Cognitive Exercises as an Early Parent-Administered Intervention Tool for Toddlers with Autism—Evidence from a Field Study. Clinical Psychiatry , 3 (1). https://doi.org/10.21767/2471-9854.100037 Forman, P., Khokhlovich, E., & Vyshedskiy, A. (2022). Longitudinal Developmental Trajectories in Young Autistic Children Presenting with Seizures, Compared to those Presenting without Seizures, Gathered via Parent-report Using a Mobile Application. Journal of Developmental and Physical Disabilities . https://doi.org/10.1007/s10882-022-09851-y Fridberg, E., Khokhlovich, E., & Vyshedskiy, A. (2021). Watching Videos and Television Is Related to a Lower Development of Complex Language Comprehension in Young Children with Autism. Healthcare , 9 (4), 423. https://doi.org/doi.org/10.3390/healthcare9040423 Jackendoff, R. S., & Erk, K. E. (2025). Toward a Deeper Lexical Semantics. Topics in Cognitive Science , tops.70013. https://doi.org/10.1111/tops.70013 Jagadeesan, P., Kabbani, A., & Vyshedskiy, A. (2022). Parent-reported assessment scores reflect ASD severity level in 2- to 7- year-old children. Children , 9 (5), 701. https://doi.org/doi.org/10.3390/children9050701 Levin, J., Khokhlovich, E., & Vyshedskiy, A. (2022). Longitudinal developmental trajectories in young autistic children presenting with sleep problems, compared to those presenting without sleep problems, gathered via parent-report using a mobile application. Research in Autism Spectrum Disorders , 97 , 102024. Murphy, E. (2015). Labels, cognomes, and cyclic computation: An ethological perspective. Frontiers in Psychology , 6 , 715. Murphy, E. (2019). No Country for Oldowan Men: Emerging Factors in Language Evolution. Frontiers in Psychology , 10 . https://doi.org/10.3389/fpsyg.2019.01448 Murphy, E. (2020). The Oscillatory Nature of Language (1st ed.). Cambridge University Press. https://doi.org/10.1017/9781108864466 Murphy, E. (2024). ROSE: A neurocomputational architecture for syntax. Journal of Neurolinguistics , 70 , 101180. Murphy, E. (2025). ROSE: A Universal Neural Grammar. Cognitive Neuroscience , 1–32. https://doi.org/10.1080/17588928.2025.2523875 Murphy, E., Forseth, K. J., Donos, C., Snyder, K. M., Rollo, P. S., & Tandon, N. (2023). The spatiotemporal dynamics of semantic integration in the human brain. Nature Communications , 14 (1). https://doi.org/10.1038/s41467-023-42087-8 Murphy, E., Holmes, E., & Friston, K. (2024). Natural language syntax complies with the free-energy principle. Synthese , 203 (5), 154. https://doi.org/10.1007/s11229-024-04566-3 Murphy, E., Rollo, P. S., Segaert, K., Hagoort, P., & Tandon, N. (2024). Multiple dimensions of syntactic structure are resolved earliest in posterior temporal cortex. Progress in Neurobiology , 241 , 102669. https://doi.org/10.1016/j.pneurobio.2024.102669 Murphy, E., Woolnough, O., Rollo, P. S., Roccaforte, Z. J., Segaert, K., Hagoort, P., & Tandon, N. (2022). Minimal Phrase Composition Revealed by Intracranial Recordings. The Journal of Neuroscience , 42 (15), 3216–3227. https://doi.org/10.1523/jneurosci.1575-21.2022 R Foundation for Statistical Computing. (2021). R: A language and environment for statistical computing [Computer software]. https://www.R-project.org Rimland, B., & Edelson, S. M. (1999). Autism treatment evaluation checklist (ATEC). Autism Research Institute, San Diego, CA . http://www.autism.com Tanaka, K., Nakamura, I., Ohta, S., Fukui, N., Zushi, M., Narita, H., & Sakai, K. L. (2019). Merge-generability as the key concept of human language: Evidence from neuroscience. Frontiers in Psychology , 10 , 2673. Vyshedskiy, A. (2022). Language evolution is not limited to speech acquisition: A large study of language development in children with language deficits highlights the importance of the voluntary imagination component of language. Research Ideas and Outcomes , 8 , e86401. Vyshedskiy, A., & Dunn, R. (2015). Mental Imagery Therapy for Autism (MITA)-An Early Intervention Computerized Brain Training Program for Children with ASD. Autism Open Access , 5 (1000153), 2. Vyshedskiy, A., Khokhlovich, E., Dunn, R., Faisman, A., Elgart, J., Lokshina, L., Gankin, Y., Ostrovsky, S., deTorres, L., & Edelson, S. M. (2020). Novel prefrontal synthesis intervention improves language in children with autism. Healthcare , 8 (4), Article 4. https://doi.org/doi.org/10.3390/healthcare8040566 Vyshedskiy, A., Pevzner, A., Mack, B., Shrayer, E., Zea, M., Bunner, S., Wong, N., Baskina, E., Sheikh, A., Tagliavia, A., Schmiedel Fucks, A., Schmiedel Sanches Santos, A., Pavoski Poloni, L. E., Fucks, E., Bolotovsky, Y., & Kang, S. J. S. (2025). Language Comprehension Developmental Milestones in Typically Developing Children Assessed by the New Language Phenotype Assessment (LPA). Children (Basel, Switzerland) , 12 (6), 793. https://doi.org/10.3390/children12060793 Vyshedskiy, A., Venkatesh, R., & Khokhlovich, E. (2024). Are there distinct levels of language comprehension in autistic individuals – cluster analysis. Npj Mental Health Research , 3 (19). https://doi.org/10.1038/s44184-024-00062-1 Vyshedskiy, A., Venkatesh, R., Khokhlovich, E., & Satik, D. (2024). Three mechanisms of language comprehension are revealed through cluster analysis of individuals with language deficits. Npj Science of Learning , 9 (1), 1–12. https://doi.org/10.1038/s41539-024-00284-0 Wiig, E. H., Secord, W. A., & Semel, E. (2013). Clinical evaluation of language fundamentals: CELF-5 . Pearson. World Medical Association. (2013). World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA , 310 (20), Article 20. Zimmerman, I. L., Steiner, V. G., & Pond, R. E. (2011). PLS-5: Preschool language scale-5 [measurement instrument]. San Antonio, TX: Psychological Corporation . Additional Declarations No competing interests reported. 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(B) Principal component analysis (PCA) plot, where ovals highlight clusters identified by UHCA. The PCA reveals a distinct separation among Command, Modifier and Syntactic Mechanisms. Principal component 1 accounts for 47% of the variance in the data. Principal component 2 accounts for 11.1% of the variance in the data.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/520ab8778a11d4b8c71a283b.png"},{"id":91489512,"identity":"e2b723ad-5ad2-41a0-8bd6-54a92044c6ed","added_by":"auto","created_at":"2025-09-17 05:14:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":149521,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering analysis of 15 language comprehension items in Spanish-speaking participants. \u003c/strong\u003e(A) A dendrogram representing the unsupervised hierarchical clustering analysis of language comprehension abilities. (B) Principal component analysis (PCA) plot, where ovals highlight clusters identified by UHCA. The PCA reveals a distinct separation among Command, Modifier and Syntactic Mechanisms. Principal component 1 accounts for 32.4% of the variance in the data. Principal component 2 accounts for 11.5% of the variance in the data.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/a7da5301c14a0baa823828a0.png"},{"id":91817146,"identity":"bd615340-912e-47d2-829a-4d302c4fadf4","added_by":"auto","created_at":"2025-09-22 06:53:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":132807,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering analysis of 14 language comprehension items in Portuguese-speaking participants. \u003c/strong\u003eOne item (“spatial prepositions”) was translated incorrectly and was therefore excluded from analysis.\u003cstrong\u003e \u003c/strong\u003e(A) A dendrogram representing the hierarchical clustering of language comprehension abilities. (B) Principal component analysis (PCA) plot, where ovals highlight clusters identified by UHCA. The PCA reveals a distinct separation among Command, Modifier and Syntactic Mechanisms. Principal component 1 accounts for 40.4% of the variance in the data. Principal component 2 accounts for 11.3% of the variance in the data.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/bf39d555e0a9aa88b4764b57.png"},{"id":91817071,"identity":"3fcf8fb6-c04e-4036-8267-d0afc23dd534","added_by":"auto","created_at":"2025-09-22 06:53:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":140198,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering analysis of 15 language comprehension items in Italian-speakers. \u003c/strong\u003e(A) A dendrogram representing the hierarchical clustering of language comprehension abilities. (B) Principal component analysis (PCA) plot, where ovals highlight clusters identified by UHCA. The PCA reveals a distinct separation among Command, Modifier and Syntactic Mechanisms. Principal component 1 accounts for 43% of the variance in the data. Principal component 2 accounts for 10.8% of the variance in the data.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/758a33b11f993a6920f24211.png"},{"id":91816939,"identity":"78038c0e-cb29-4cfc-91fb-3818c2632402","added_by":"auto","created_at":"2025-09-22 06:53:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":136896,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering analysis of 15 language comprehension items in Russian-speaking participants.\u003c/strong\u003e (A) A dendrogram representing the hierarchical clustering of language comprehension abilities. (B) Principal component analysis (PCA) plot, where ovals highlight clusters identified by UHCA. The PCA reveals a distinct separation among Command, Modifier and Syntactic Mechanisms. Principal component 1 accounts for 52.7% of the variance in the data. Principal component 2 accounts for 10.3% of the variance in the data.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/ac9f752fef51f7c315affbd2.png"},{"id":91489519,"identity":"66e80645-8166-4280-9195-48d2d30ccd86","added_by":"auto","created_at":"2025-09-17 05:14:11","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":118827,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering analysis of 13 language comprehension items in Chinese-speaking participants. \u003c/strong\u003eTwo items (“spatial prepositions” and “possessive pronouns”) were translated incorrectly and were therefore excluded from analysis.\u003cstrong\u003e \u003c/strong\u003e(A) A dendrogram representing the hierarchical clustering of language comprehension abilities. (B) Principal component analysis (PCA) plot, where ovals highlight clusters identified by UHCA. The PCA reveals a distinct separation among Command, Modifier and Syntactic Mechanisms. Principal component 1 accounts for 49.7% of the variance in the data. Principal component 2 accounts for 12.3% of the variance in the data.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/6fc5b850490d2dde3832600f.png"},{"id":91816958,"identity":"75b4e75b-eb6e-4a93-adf5-8ca4ec32b59f","added_by":"auto","created_at":"2025-09-22 06:53:06","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":140245,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering analysis of 15 language comprehension items in French-speaking participants. \u003c/strong\u003e(A) A dendrogram representing the hierarchical clustering of language comprehension abilities. (B) Principal component analysis (PCA) plot, where ovals highlight clusters identified by UHCA. The PCA reveals a distinct separation among Command, Modifier and Syntactic Mechanisms. Principal component 1 accounts for 42.6% of the variance in the data. Principal component 2 accounts for 11.3% of the variance in the data.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/2ba680fd1c0bfcad3bd6cd86.png"},{"id":91816634,"identity":"3fc4eee8-2250-483c-a64b-32a4ae83dfd6","added_by":"auto","created_at":"2025-09-22 06:52:20","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":142206,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering analysis of 15 language comprehension items in German-speaking participants. \u003c/strong\u003e(A) A dendrogram representing the hierarchical clustering of language comprehension abilities. (B) Principal component analysis (PCA) plot, where ovals highlight clusters identified by UHCA. The PCA reveals a distinct separation among Command, Modifier and Syntactic Mechanisms. Principal component 1 accounts for 42.4% of the variance in the data. Principal component 2 accounts for 10.7% of the variance in the data.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/77e800ef2faa2193f327f048.png"},{"id":91489528,"identity":"9c661d42-ba44-4832-9e67-5849a9fb9f6c","added_by":"auto","created_at":"2025-09-17 05:14:11","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":137867,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering analysis of 15 language comprehension items in Korean-speaking participants. \u003c/strong\u003e(A) A dendrogram representing the hierarchical clustering of language comprehension abilities. (B) Principal component analysis (PCA) plot, where ovals highlight clusters identified by UHCA. The PCA reveals a distinct separation among Command, Modifier and Syntactic Mechanisms. Principal component 1 accounts for 49.5% of the variance in the data. Principal component 2 accounts for 8.7% of the variance in the data.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/a45ef55276a397f89b2f00c4.png"},{"id":91816668,"identity":"f546eba4-c00a-4f21-9539-73312c8afa32","added_by":"auto","created_at":"2025-09-22 06:52:29","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":154903,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-dimensional heatmap relating English-speaking participants to their language comprehension abilities. \u003c/strong\u003eThe 15 language comprehension abilities are shown as rows. The dendrogram representing language comprehension abilities is shown on the left. Participants are shown as 27,187 columns. The dendrogram representing participants is shown on the top. Blue color indicates the presence of a linguistic ability (the “very true” answer), red indicates the lack of a linguistic ability (the “not true” answer), and white-yellow indicates the “somewhat true” answer.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/d8e0900dd409075534a32054.png"},{"id":91816891,"identity":"348e0ee0-2c72-4594-a912-54b264d83d3d","added_by":"auto","created_at":"2025-09-22 06:52:53","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":154697,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-dimensional heatmap relating Spanish-speaking participants to their language comprehension abilities. \u003c/strong\u003eThe 15 language comprehension abilities are shown as rows. The dendrogram representing language comprehension abilities is shown on the left. Participants are shown as 33,488 columns. The dendrogram representing participants is shown on the top. Blue color indicates the presence of a linguistic ability (the “very true” answer), red indicates the lack of a linguistic ability (the “not true” answer), and white-yellow indicates the “somewhat true” answer.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/44ed4ef6af03be3034e033b6.png"},{"id":91489538,"identity":"ac96782e-efbd-487e-b8bf-d3d76cb50feb","added_by":"auto","created_at":"2025-09-17 05:14:12","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":148872,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-dimensional heatmap relating Portuguese-speaking participants to their language comprehension abilities. \u003c/strong\u003eThe 14 language comprehension abilities are shown as rows. The dendrogram representing language comprehension abilities is shown on the left. Participants are shown as 7,504 columns. The dendrogram representing participants is shown on the top. Blue color indicates the presence of a linguistic ability (the “very true” answer), red indicates the lack of a linguistic ability (the “not true” answer), and white-yellow indicates the “somewhat true” answer.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/677eae2104a07d404f1ee3f6.png"},{"id":91489534,"identity":"2c537b33-259f-4266-ba9c-ca54837c07fe","added_by":"auto","created_at":"2025-09-17 05:14:11","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":156483,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-dimensional heatmap relating Italian-speaking participants to their language comprehension abilities. \u003c/strong\u003eThe 15 language comprehension abilities are shown as rows. The dendrogram representing language comprehension abilities is shown on the left. Participants are shown as 6,484 columns. The dendrogram representing participants is shown on the top. Blue color indicates the presence of a linguistic ability (the “very true” answer), red indicates the lack of a linguistic ability (the “not true” answer), and white-yellow indicates the “somewhat true” answer.\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/15e79c39a36a284d483c754c.png"},{"id":91816818,"identity":"9bdedf29-468f-44b3-b701-1abab0014e2a","added_by":"auto","created_at":"2025-09-22 06:52:47","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":153897,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-dimensional heatmap relating Russian-speaking participants to their language comprehension abilities. \u003c/strong\u003eThe 15 language comprehension abilities are shown as rows. The dendrogram representing language comprehension abilities is shown on the left. Participants are shown as 4,778 columns. The dendrogram representing participants is shown on the top. Blue color indicates the presence of a linguistic ability (the “very true” answer), red indicates the lack of a linguistic ability (the “not true” answer), and white-yellow indicates the “somewhat true” answer.\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/00ad5b4b8e0608ca27d14ff8.png"},{"id":91489554,"identity":"6d0f2710-890a-4aa9-bae5-13213cdaca52","added_by":"auto","created_at":"2025-09-17 05:14:12","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":139397,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-dimensional heatmap relating Chinese-speaking participants to their language comprehension abilities. \u003c/strong\u003eThe 13 language comprehension abilities are shown as rows. The dendrogram representing language comprehension abilities is shown on the left. Participants are shown as 2,217 columns. The dendrogram representing participants is shown on the top. Blue color indicates the presence of a linguistic ability (the “very true” answer), red indicates the lack of a linguistic ability (the “not true” answer), and white-yellow indicates the “somewhat true” answer.\u003c/p\u003e","description":"","filename":"15.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/8717904d8fb9b313c16c8568.png"},{"id":91489542,"identity":"b9bf837a-4070-41a1-9f70-c73efd914f69","added_by":"auto","created_at":"2025-09-17 05:14:12","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":149236,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-dimensional heatmap relating French-speaking participants to their language comprehension abilities. \u003c/strong\u003eThe 15 language comprehension abilities are shown as rows. The dendrogram representing language comprehension abilities is shown on the left. Participants are shown as 1,060 columns. The dendrogram representing participants is shown on the top. Blue color indicates the presence of a linguistic ability (the “very true” answer), red indicates the lack of a linguistic ability (the “not true” answer), and white-yellow indicates the “somewhat true” answer.\u003c/p\u003e","description":"","filename":"16.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/3dc29318da59ad4f379b495c.png"},{"id":91489548,"identity":"1e5c7253-b7f1-4a6d-aee3-488a0ca07c79","added_by":"auto","created_at":"2025-09-17 05:14:12","extension":"png","order_by":17,"title":"Figure 17","display":"","copyAsset":false,"role":"figure","size":155680,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-dimensional heatmap relating German-speaking participants to their language comprehension abilities. \u003c/strong\u003eThe 15 language comprehension abilities are shown as rows. The dendrogram representing language comprehension abilities is shown on the left. Participants are shown as 927 columns. The dendrogram representing participants is shown on the top. Blue color indicates the presence of a linguistic ability (the “very true” answer), red indicates the lack of a linguistic ability (the “not true” answer), and white-yellow indicates the “somewhat true” answer.\u003c/p\u003e","description":"","filename":"17.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/c85e9cb5143be29aa4961b69.png"},{"id":91816956,"identity":"462d45f4-a07e-49f8-a65a-e0200df9ef23","added_by":"auto","created_at":"2025-09-22 06:53:05","extension":"png","order_by":18,"title":"Figure 18","display":"","copyAsset":false,"role":"figure","size":154863,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-dimensional heatmap relating Korean-speaking participants to their language comprehension abilities. \u003c/strong\u003eThe 15 language comprehension abilities are shown as rows. The dendrogram representing language comprehension abilities is shown on the left. Participants are shown as 454 columns. The dendrogram representing participants is shown on the top. Blue color indicates the presence of a linguistic ability (the “very true” answer), red indicates the lack of a linguistic ability (the “not true” answer), and white-yellow indicates the “somewhat true” answer.\u003c/p\u003e","description":"","filename":"18.png","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/9b48ea79d6f04b0942c77f52.png"},{"id":99172325,"identity":"54015b0f-3d7d-4770-b0f6-654f5620be13","added_by":"auto","created_at":"2025-12-29 16:07:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4137276,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/55841127-caf2-468e-a68f-85e642ed7265.pdf"},{"id":91489518,"identity":"2a26ffd9-d7c4-419b-8a40-5ef90c3c135b","added_by":"auto","created_at":"2025-09-17 05:14:11","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":921665,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial20250717.docx","url":"https://assets-eu.researchsquare.com/files/rs-7294415/v1/182f35260d7951237f042e2b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Merge-based syntax is mediated by distinct neurocognitive mechanisms: A clustering analysis of comprehension abilities in 84,000 individuals with language deficits across nine languages","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn modern linguistics, Merge is a proprietary cognitive operation that combines two linguistic units (e.g., \u0026lsquo;blue\u0026rsquo;, \u0026lsquo;cat\u0026rsquo;) to form a categorized, labeled set (\u0026lsquo;blue cat\u0026rsquo;, a Noun Phrase), which can then be further combined with additional linguistic units (Chomsky, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1995\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The field of linguistics has largely coalesced around the hypothesis that unbounded Merge is a uniquely human ability, serving as the generative engine underlying the human capacity to generate or communicate an infinite number of expressions (Tanaka et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Some researchers, such as Berwick and Chomsky, have noted that due to the \u0026lsquo;absolute\u0026rsquo; nature of Merge (one either has it, or does not have it), no partial or \u0026lsquo;proto-Merge\u0026rsquo; is plausible: \u0026ldquo;The elementary operation of binary set formation (Merge) appeared in a single step\u0026rdquo; (Berwick \u0026amp; Chomsky, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). From a neurocognitive standpoint, it may be plausible to decompose distinct generic cognitive operations that subserve distinct components of a Merge-based syntax (e.g., the formation of hierarchical objects, the categorization of phrases, the short-term maintenance of categorial identity) (Murphy, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFrom the perspective of linguistic formalism, the simplicity of the Merge operation is strikingly elegant. Its concise formulation echoes (intentionally) the parsimony of Hamilton\u0026rsquo;s principle of least action and fundamental physical laws, such as the conservation of energy and the conservation of momentum (Murphy, Holmes, et al., 2024). But from a neurocognitive standpoint, it is becoming increasingly plausible that different levels of Merge-based complexity may be supported by distinct nodes in the extended language network (Murphy, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Murphy et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Murphy, Rollo, et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eStudies involving large numbers of participants with language deficits offer a powerful approach to investigating the nature of Merge-based syntax. By including tens of thousands of individuals with a range of conditions associated with language impairments, researchers can observe the effect of a wide variety of genetic abnormalities linked to linguistic deficits. Merge interfaces with various conceptual and performance systems, and if some of these exhibit digital/discrete representations but others exhibit analog/graded representations (Jackendoff \u0026amp; Erk, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), we may expect to find genetic abnormalities that cause a gradual degradation of syntactic and semantic performance. Conversely, if Merge outputs to a single restricted and homogeneous domain-general interface, its loss should be catastrophic and complete.\u003c/p\u003e\u003cp\u003eYet, previous studies have shown that neither of these two hypotheses is strongly supported. Two studies of tens of thousands of individuals identified three distinct general levels of what a Merge-based syntax can output: Syntactic, Modifier, and Command (Vyshedskiy, Venkatesh, \u0026amp; Khokhlovich, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). The Syntactic Phenotype is exhibited by most adults and by children aged four years and older (Vyshedskiy et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Individuals with this phenotype can comprehend sentences containing spatial prepositions, reversible word order, verb tenses, possessive pronouns, complex explanations, and elaborate fairytales demanding an array of these construction types (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cem\u003eSyntactic Mechanism\u003c/em\u003e). Approximately 2% of adults, as well as children between the ages of three and four, exhibit the Modifier Phenotype. Their ability is limited to combinations of nouns and adjectives (e.g., they can select \u0026lsquo;a small green pencil\u0026rsquo; from a set of pencils, straws, and Lego pieces of different sizes and colors; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cem\u003eModifier Mechanism\u003c/em\u003e). Finally, about 1% of adults, and children aged two to three years, exhibit the Command Phenotype, being restricted to simple commands (e.g., \u0026lsquo;eat apple\u0026rsquo;; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cem\u003eCommand Mechanism\u003c/em\u003e). Note that these categories delimit overt linguistic performance and major aspects of competence, but may not reflect the full extent of underlying competence.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eThree language comprehension mechanisms\u0026mdash;Syntactic, Modifier, and Command\u0026mdash;have been identified in previous studies\u003c/b\u003e (Vyshedskiy, Venkatesh, \u0026amp; Khokhlovich, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). When one mechanism is acquired, the entire range of associated comprehension abilities is also gained. The Command-level abilities (Items 1 to 4) are acquired first. The Modifier-level abilities (Items 5 to 8) are attained next. The Syntactic-level abilities (Items 9 to 15) are acquired last. The language comprehension items are presented exactly as surveyed with parents in both this and earlier studies. Response options were: very true, somewhat true, and not true. Items 1 to 3 were assessed as part of the Expressive Language ATEC (Rimland \u0026amp; Edelson, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) subscale 1; the rest of items were a part of the MSEC subscale (Braverman et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLanguage comprehension items (verbatim)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAbbreviations used in dendrograms\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eCommand Mechanism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKnows own name\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKnows Name\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResponds to \u0026lsquo;No\u0026rsquo; or \u0026lsquo;Stop\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo and Stop\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResponds to praise\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResp. to Praise\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCan follow some commands\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCommands\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eModifier Mechanism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands some simple modifiers (i.e., green apple vs. red apple or big apple vs. small apple)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eColor or Size / Modifiers\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands several modifiers in a sentence (i.e., small green apple)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTwo Modifiers\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands size (can select the largest/smallest object out of a collection of objects)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSize Superlatives\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands NUMBERS (i.e., two apples vs. three apples)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumbers\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003eSyntactic Mechanism \u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands spatial prepositions (i.e., put the apple ON TOP of the box vs. INSIDE the box vs. BEHIND the box)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSp. Prepositions\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands verb tenses (i.e., I will eat an apple vs. I ate an apple)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVerb Tenses\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands simple stories that are read aloud\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSimple Stories\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands elaborate fairytales that are read aloud (i.e., stories describing FANTASY creatures)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eElab. Fairytales\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands possessive pronouns (i.e., your apple vs. her apple)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePoss. Pronouns\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands the change in meaning when the order of words is changed (i.e., understands the difference between 'a cat ate a mouse' vs. 'a mouse ate a cat')\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFlexible Syntax\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstands explanations about people, objects or situations beyond the immediate surroundings (e.g., \u0026ldquo;Mom is walking the dog,\u0026rdquo; \u0026ldquo;The snow has turned to water\u0026rdquo;).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExplanations\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThese findings suggest that while Merge-based syntax can degrade in a seemingly catastrophic manner, it does not vanish entirely. For example, individuals functioning at the intermediate Modifier level lose the ability to comprehend fairytales, spatial prepositions, verb tense, and possessive pronouns, but they retain the capacity to integrate adjectives with nouns, form noun phrases with superlatives, and perform similar compositional tasks. This dovetails with the observation that even in the most severe cases of lesion-based syntactic disruption, some capacity to execute basic hierarchical structure-formation is often preserved (in some format) (Dragoy et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e Within this context of open questions, the goals of the present study were: (1) to relate the Command, Modifier, and Syntactic Mechanisms to Merge-based syntax; (2) to analyze a larger cohort of participants than previous work; and (3) to confirm the dissociation among the three Mechanisms within each of the nine languages analyzed individually.\u003c/p\u003e\u003cp\u003eLanguages differ significantly in their grammatical structures, word order, word order flexibility, and morphological complexity. For instance, English typically follows a subject\u0026ndash;verb\u0026ndash;object word order, whereas languages like Japanese and Korean follow a subject\u0026ndash;object\u0026ndash;verb structure. In English, adjectives are generally pre-nominal\u0026mdash;one would say \u0026ldquo;\u003cem\u003ethe large cat\u003c/em\u003e\u0026rdquo;, not \u0026ldquo;\u003cem\u003ethe cat large\u003c/em\u003e\u0026rdquo;. In contrast, Romance languages often place adjectives after the nouns they modify. Morphological complexity also varies widely: Russian, for example, features an extensive system of inflectional case endings, in contrast to the relatively simple morphology of English. This greater morphological richness in Russian contributes to its more flexible word order.\u003c/p\u003e\u003cp\u003eIf the Command, Modifier, and Syntactic Mechanisms differ across languages, we might be able to associate these grammatical differences with corresponding variations in those mechanisms. Conversely, if no such differences are observed, it would suggest that these three mechanisms\u0026mdash;Command, Modifier, and Syntactic\u0026mdash;may be universal across languages.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Participants\u003c/h2\u003e\u003cp\u003eParticipants were children and adolescents using a language therapy app that was made freely available at all major app stores in September 2015 (Dunn, Elgart, Lokshina, Faisman, Khokhlovich, et al., 2017b, 2017a; Dunn, Elgart, Lokshina, Faisman, Waslick, et al., 2017; Vyshedskiy et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Vyshedskiy \u0026amp; Dunn, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The app provides various structured language comprehension therapy exercises and is primarily used by caregivers of children with language impairments. Most of the caregivers are presumed to be parents. Once the app was downloaded, caregivers were asked to register and to provide demographic details, including the child\u0026rsquo;s diagnosis and age. Caregivers consented to pseudonymized data analysis and completed a 133-item questionnaire (77-item Autism Treatment Evaluation Checklist (ATEC) (Rimland \u0026amp; Edelson, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), Supplementary Tables\u0026nbsp;1\u0026ndash;4; 20-item Mental Synthesis Evaluation Checklist (MSEC) (Braverman et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Supplementary Table\u0026nbsp;5; 10-item screen time checklist (Fridberg et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); 25-item diet checklist (Acosta et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e); and 1-item parent education survey) approximately every three months.\u003c/p\u003e\u003cp\u003eIn what follows, we reproduce much of the Methods details from one of our previous publications (Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024).\u003c/p\u003e\u003cp\u003eAll fifteen available \u003cem\u003elanguage comprehension\u003c/em\u003e items from the 133-item questionnaire were included in the cluster analysis as in previously published articles (Vyshedskiy, Venkatesh, \u0026amp; Khokhlovich, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Answer choices were as follows: very true (0 points), somewhat true (1 point), and not true (2 points). A lower score indicates better language comprehension ability.\u003c/p\u003e\u003cp\u003eThe inclusion criteria for this study remained consistent with those of previous studies (Vyshedskiy, Venkatesh, \u0026amp; Khokhlovich, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024): absence of seizures (which commonly result in intermittent, unstable language comprehension deficits (Forman et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)), absence of serious and moderate sleep problems (which are also associated with intermittent, unstable language comprehension deficits (Levin et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)), age range of 4 to 22 years (the lower age cutoff was chosen to ensure that participants were exposed to complete set of sentence structures listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (Arnold \u0026amp; Vyshedskiy, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); the upper age cutoff was chosen to avoid analysis of participants who may be linguistically declining due to aging). Previous studies were limited to individuals diagnosed with Autism Spectrum Disorder (ASD) (Vyshedskiy, Venkatesh, \u0026amp; Khokhlovich, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and individuals with fluid speech (Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). This study included all participants who submitted their assessments through the app, speaking one of the nine languages that the app is available in: English, Spanish, Portuguese, Italian, Russian, Chinese, French, German, and Korean. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reports participants\u0026rsquo; demographics in each language group as communicated by caregivers. Males outnumber females by approximately four to one, reflecting the predominance of autism among participants and its known male-to-female prevalence ratio.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticipants\u0026rsquo; demographics.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Participants\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercent of Total\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAge, Mean(SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePercent Males\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEnglish\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27187\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.7(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e75.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSpanish\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.1(2.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e68.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePortuguese\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7504\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.3(2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e76.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eItalian\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6484\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.6 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e78.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRussian\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4778\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.8(2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e77.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eChinese\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.1(2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e79.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFrench\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.2(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e72.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGerman\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.2(3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e69.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eKorean\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e454\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.6(2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e74.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e84099\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e6.5(2.7)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e74.7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e reports participants\u0026rsquo; diagnoses as communicated by caregivers. Autism level (mild/Level 1, moderate/Level 2, or severe/Level 3) was reported by caregivers. Pervasive Developmental Disorder and Asperger Syndrome were combined with mild autism for analysis as recommended by DSM-5 (American Psychiatric Association, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). A good reliability of such parent-reported diagnosis has been previously demonstrated (Jagadeesan et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticipants\u0026rsquo; diagnoses.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Participants\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercent of Total\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAge, Mean(SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePercent Males\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMild Autism Spectrum Disorder (ASD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29292\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.2(2.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e75.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eModerate ASD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.9(2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e79.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSevere ASD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10839\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.6(3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e80.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNot-diagnosed\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.7(1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e54.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSpecific Language Impairment\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.0(2.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e69.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMild Language Delay\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3973\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.4(1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e67.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eADHD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.4(2.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e72.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDown Syndrome\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1427\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.5(3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e60.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOther Genetic Disorder\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.0(3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e57.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial Communication Disorder\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e794\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.3(2.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e69.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSensory Processing Disorder\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.8(2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e70.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eApraxia\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e466\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.8(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e64.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e84099\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e6.5(2.7)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e74.7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhen caregivers have completed several evaluations, the last evaluation was used for analysis as in previous studies (Vyshedskiy, Venkatesh, \u0026amp; Khokhlovich, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). Thus, the study included a total of 84,099 participants, the average age was 6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 years (range of 4 to 21.9 years), 74.7% participants were males. The education level of participants\u0026rsquo; parents was the following: 90.9% with at least a high school diploma, 68.6% with at least college education, 35.8% with at least a master\u0026rsquo;s, and 5.6% with a doctorate. All caregivers consented to pseudonymized data analysis and publication of results. The study was conducted in compliance with the Declaration of Helsinki (World Medical Association, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Using the Department of Health and Human Services regulations found at 45 CFR 46.101(b)(4), the Biomedical Research Alliance of New York (BRANY) LLC Institutional Review Board (IRB) determined that this research project is exempt from IRB oversight (IRB File # 22-12-205-1120). The data was accessed on July 9, 2025.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStatistics and Reproducibility\u003c/h3\u003e\n\u003cp\u003eUnsupervised Hierarchical Cluster Analysis (UHCA) was performed using Ward\u0026rsquo;s agglomeration method with a Euclidean distance metric. The clustering analysis was data-driven without any design or hypothesis. A two-dimensional heatmap was generated using the \u0026ldquo;pheatmap\u0026rdquo; package of R, freely available language for statistical computing (R Foundation for Statistical Computing, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Code and data can be downloaded (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.17605/OSF.IO/2QK5B\u003c/span\u003e\u003cspan address=\"10.17605/OSF.IO/2QK5B\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\"\u003e\n \u003ch2\u003eClustering analysis of 15 language comprehension abilities\u003c/h2\u003e\n \u003cp\u003eCaregivers assessed 15 language comprehension abilities (Table\u0026nbsp;1). To examine patterns of co-occurrence among these abilities, we applied unsupervised hierarchical cluster analysis—a data-driven method that groups items based on their similarity. This technique produces tree-like diagrams, called \u003cem\u003edendrograms\u003c/em\u003e, which visually represent the hierarchical relationships between clusters of items. Abilities that frequently co-occur are positioned closely together, while those that co-occur less often appear farther apart.\u003c/p\u003e\n \u003cp\u003eFigure 1A depicts the dendrogram generated from the analysis of English-speaking participants. The height of the branches indicates the distance between clusters. A larger distance corresponds to greater dissimilarity between the clusters. Previous studies identified three clusters stable across different evaluation methods, age groups, time points, genders, and parental education (Vyshedskiy, Venkatesh, \u0026amp; Khokhlovich, 2024; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). The first cluster included \u003cem\u003eknowing the name, responding to ‘No’ or ‘Stop’, responding to praise\u003c/em\u003e, and \u003cem\u003efollowing some commands\u003c/em\u003e (items 1 to 4 in Table\u0026nbsp;1) and was termed the Command Mechanism. The second cluster included \u003cem\u003eunderstanding color and size modifiers, several modifiers in a sentence, size superlatives\u003c/em\u003e, and \u003cem\u003enumbers\u003c/em\u003e (items 5 to 8 in Table\u0026nbsp;1) and was termed the Modifier Mechanism. The third cluster included \u003cem\u003eunderstanding of spatial prepositions, verb tenses, flexible syntax, possessive pronouns, explanations about people and situations, simple stories\u003c/em\u003e, and \u003cem\u003eelaborate fairytales\u003c/em\u003e (items 9 to 15 in Table\u0026nbsp;1) and was termed the Syntactic Mechanism. The analysis of English-speaking participants in Fig.\u0026nbsp;1A identified the same three clusters with inter-cluster distances that were significantly larger than the distances between subclusters. Principal component analysis (PCA) (Fig.\u0026nbsp;1B) also showed a clear separation between the three clusters: Command, Modifier and Syntactic.\u003c/p\u003e\n \u003cp\u003eAs a control we calculated unsupervised hierarchical cluster analysis and PCA of the 15 comprehension abilities along with the “\u003cem\u003ehyperactivity\u003c/em\u003e” (Figures S1), “\u003cem\u003ebed-wetting\u003c/em\u003e” (Figure S2), and “\u003cem\u003edemands sameness\u003c/em\u003e” (Figure S3) items. These items are not related to language and therefore should cluster into their own group. As expected, both unsupervised hierarchical cluster analysis and PCA clustered these items into their own group at a significant distance from the Command, Modifier, and Syntactic clusters, validating both clustering techniques.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eClustering analysis across spoken languages\u003c/h3\u003e\n\u003cp\u003eClustering analysis was conducted in all language groups with 400 or more participants. The three-cluster solution was consistent across all language groups explored: English, Spanish, Portuguese, Italian, Russian, Chinese, French, German, and Korean (Figs.\u0026nbsp;1–9). In all spoken languages, unsupervised hierarchical cluster analysis sorted the 15 comprehension abilities into congruent three clusters (Command, Modifier, and Syntactic) and PCA showed a clear separation between the three clusters. Some language groups, such as Russian (Fig.\u0026nbsp;5B), demonstrated a greater separation between clusters in PCA.\u003c/p\u003e\n\u003cp\u003eThese findings suggest that the three-cluster solution is not a result of differential cultural upbringing but rather a potentially general cognitive phenomenon constrained, consistent across spoken languages.\u003c/p\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eLanguage comprehension phenotypes in participants\u003c/h2\u003e\n \u003cp\u003ePrevious studies have employed unsupervised hierarchical cluster analysis to identify distinct language comprehension phenotypes of participants (Vyshedskiy, Venkatesh, \u0026amp; Khokhlovich, 2024; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). The principles underlying participant clustering are identical to those used for clustering abilities: participants with similar patterns of abilities are automatically organized into hierarchical dendrograms. Previous studies identified three distinct phenotypes: 1) Command Phenotype–participants who acquired only the Command Mechanism; 2) Modifier Phenotype–participants who acquired both the Command and Modifier Mechanisms; and 3) Syntactic Phenotype–participants who acquired the Command, Modifier, and Syntactic Mechanisms.\u003c/p\u003e\n \u003cp\u003eThe close correspondence between comprehension mechanisms and the resulting phenotypes is noteworthy. While various combinations of the three mechanisms are theoretically possible, such combinations were not observed empirically. For example, a hypothetical phenotype combining the Command and Syntactic Mechanisms (but not the Modifier Mechanism) could exist in theory. Another possibility would be a phenotype lacking all three mechanisms. However, these configurations did not emerge from the data. This absence suggests that the ‘morphospace’ of comprehension phenotypes is constrained by cognitive faculties.\u003c/p\u003e\n \u003cp\u003e To investigate whether these constraints are consistent across different languages, this study conducted the unsupervised hierarchical cluster analysis of participants separately within each language group. The results are presented in Figs.\u0026nbsp;10–18, which relate participant clusters to comprehension mechanisms. The three mechanism clusters (Command, Modifier, and Syntactic) are shown as rows (the dendrogram from Fig.\u0026nbsp;1A representing comprehension mechanisms is shown vertically on the left in Fig.\u0026nbsp;10) and the 27,187 English-speaking participants are shown as columns (the dendrogram representing participants is shown horizontally on the top). \u003cem\u003eBlue\u003c/em\u003e indicates the presence of a linguistic ability (parent’s response = \u003cem\u003every true\u003c/em\u003e); \u003cem\u003ewhite\u003c/em\u003e indicates an intermittent presence of a linguistic ability (parent’s response = \u003cem\u003esomewhat true\u003c/em\u003e); and \u003cem\u003ered\u003c/em\u003e indicates the complete lack of a linguistic ability (parent’s response = \u003cem\u003enot true\u003c/em\u003e).\u003c/p\u003e\n \u003cp\u003eIn the heatmap of English-speakers (Fig.\u0026nbsp;10), the middle cluster of participants (marked “Syntactic Phenotype”) shows the predominant blue color (representing good skills) across all abilities indicating that these participants acquired the Command, Modifier, and Syntactic Mechanisms. The leftmost cluster of participants (marked “Command Phenotype”) shows the predominant blue color only among the Command Mechanism items and red colors across Syntactic and Modifier Mechanisms items, indicating that these individuals only acquired the Command Mechanism. The rightmost cluster of participants (marked “Modifier Phenotype”) shows the predominant blue color only across Command and Modifier Mechanisms items and white to red colors across Syntactic Mechanism items, indicating that these individuals acquired the Command and Modifier Mechanisms.\u003c/p\u003e\n \u003cp\u003eThis pattern was reproduced across all language groups (Figs.\u0026nbsp;10–18). Participants acquired either: 1) the Command Mechanism alone (marked as the Command Phenotype), or 2) both the Command and Modifier Mechanisms (marked as the Modifier Phenotype), or 3) the Command, Modifier, and Syntactic Mechanisms (marked as the Syntactic Phenotype).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe conducted a clustering analysis to examine the co-occurrence of fifteen language comprehension abilities in 84,099 individuals who spoke English, Spanish, Portuguese, Italian, Russian, Chinese, French, German, or Korean. The three identified clusters were identical between languages and congruent to those found in previous analyses (Vyshedskiy, Venkatesh, \u0026amp; Khokhlovich, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Vyshedskiy, Venkatesh, Khokhlovich, et al., 2024). Crucially, the clustering analysis in all studies was devoid of any design or hypothesis, as both unsupervised hierarchical clustering analysis and principal component analysis (PCA) were entirely driven by the data. The outcome of our clustering analyses is a set of three coherent, discrete language ability clusters that appear to revolve around similar linguistic deficits concerning modifiers and complex syntactic operations\u0026mdash;not a mixed amalgam of different patterns that would be expected if language abilities were mediated by many unrelated mechanisms.\u003c/p\u003e\u003cp\u003eWe note here some limitations of our work: A 133-item survey completed repeatedly by motivated parents is invaluable, but still prone to optimism, fatigue, and socioeconomic skew. Future work could strengthen the validity of findings by quantifying inter-rater reliability (e.g., by having both parents independently complete the survey). While one study has demonstrated a strong correlation between the parent-reported survey used in this study and a clinicians-administered Language Phenotype Assessment (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.78, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Vyshedskiy et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), further validation could involve comparing a subsample of parent responses with results from standardized clinician-administered instruments (e.g., PLS-5 (Zimmerman et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), Token Test (A. De Renzi \u0026amp; Vignolo, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1962\u003c/span\u003e; E. De Renzi \u0026amp; Faglioni, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1978\u003c/span\u003e), CELF-5 (Wiig et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), TROG (Bishop, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)).\u003c/p\u003e\u003cp\u003eOur enrollment protocol also filters for relatively \u0026ldquo;tech-savvy\u0026rdquo;, intervention-seeking parents and may under-represent low-SES households. A comparison of census-matched demographics would help establish external validity. In addition, the disorders reported in our study differ in etiology and linguistic phenotype; since the same caregiver questionnaire supplies both phenotype and explanatory variable, latent correlations may inflate cluster separability.\u003c/p\u003e\u003cp\u003eThe replication of the three-cluster solution across English, Spanish, Portuguese, Italian, Russian, Chinese, French, German, and Korean likely points to language-independent constraints. Notable, the languages examined in this study vary widely in morphological complexity, word order and word order flexibility. For example, Russian has a much richer morphological system and greater word order flexibility than English; while Korean follows subject\u0026ndash;object\u0026ndash;verb structure, which differs from the subject\u0026ndash;verb\u0026ndash;object order typical of Indo-European languages. Despite these structural differences, all nine languages consistently revealed clear distinctions among the three linguistic mechanisms\u0026mdash;Command, Modifier, and Syntactic\u0026mdash;indicating that these distinctions may be universal.\u003c/p\u003e\u003cp\u003eSome may argue here that the three clusters reflect emergent probabilistic constructions rather than discrete cognitive mechanisms. However, the sharp boundaries we observe (especially the near-absence of Modifier-without-Command or Syntactic-without-Modifier profiles) are difficult to reconcile with a purely continuous competence model. Future work could operationalize the predictions of usage-based linguistic theories to more carefully explore these topics.\u003c/p\u003e\u003cp\u003eThe present behavioral gradient (Command \u0026rarr; Modifier \u0026rarr; Syntactic) demonstrates that a single explanatory construct, Merge, can be developmentally unpacked into sub-routines mastered at different developmental stages: the Command Mechanism by 1.6 years of age, the Modifier mechanism by 3.0 years of age, and the Syntactic Mechanism by 3.7 years of age (Vyshedskiy et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). From an evolutionary perspective, this aligns with a \u0026ldquo;saltation-plus-scaffolding\u0026rdquo; model: an initial binary set-forming capacity may have arisen abruptly (Berwick \u0026amp; Chomsky, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), but its efficient deployment in real-time cognition and communication required incremental recruitment of domain-general resources such as working memory, attention (Murphy, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and articulate speech (Vyshedskiy, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It is possible that the layered neurocognitive architecture that supports modern human syntax may provide some basis for the behavioral results we document here.\u003c/p\u003e\u003cp\u003eIsolating behavioral dynamics of \u0026ldquo;Command\u0026rdquo;, \u0026ldquo;Modifier\u0026rdquo;, and \u0026ldquo;Syntactic\u0026rdquo; mechanisms might allow us to refine long-standing psycholinguistic debates about the grain-size of syntactic representations accessed during real-time comprehension. For example, classic garden-path effects show that comprehenders incrementally commit to local syntactic analyses that sometimes require costly reanalysis when later input forces revision. If the Modifier mechanism licenses phrase-internal operations such as adjective-noun union, while the Command mechanism governs clausal argument structure, then garden-path costs should be sharply magnified whenever disambiguation pivots on Command-level information (e.g., NP-attachment vs. VP-attachment ambiguities). Conversely, ambiguities resolvable within the Modifier mechanism (e.g., prenominal adjective stacking) should yield milder slow-downs.\u003c/p\u003e\u003cp\u003eOur results suggest that the conceptual and performance systems that access Merge-based syntax are fractionated behaviorally into distinct mechanistic groups. We hope that these results play some role in addressing a long-standing gap between formal linguistic theory and large-scale behavioral phenotyping. Our reported sample is an order of magnitude larger than typical language-impairment studies, improving power to detect stable substructures, but many further questions remain concerning the granularity of the documented sets of language deficits.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe wish to thank all participants’ caregivers who found time to complete children’s assessments. The language therapy app used to collect the data presented in this manuscript was made possible by the contributions of Rita Dunn, Alexander Faisman, Jonah Elgart, Lisa Lokshina, and Yulia Dumov.\u003c/p\u003e\n\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\n\u003cp\u003eAV designed the study. EK developed the statistical paradigm. RV wrote the statistical analysis software. AV analyzed the data. EM and AV wrote the paper.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eAuthors declare no competing interests.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eDe-identified raw data from this manuscript are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCode is available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in compliance with the Declaration of Helsinki. Informed consent was obtained from the caregivers of all participants. The study protocol was approved by the Biomedical Research Alliance of New York (BRANY) LLC Institutional Review Board (IRB).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAcosta, A., Khokhlovich, E., Reis, H., \u0026amp; Vyshedskiy, A. (2023). Dietary factors impact developmental trajectories in young autistic children. \u003cem\u003eJournal of Autism and Developmental Disorders\u003c/em\u003e. https://doi.org/10.1007/s10803-023-06074-8\u003c/li\u003e\n \u003cli\u003eAmerican Psychiatric Association. (2013). \u003cem\u003eDiagnostic and statistical manual of mental disorders (DSM-5\u0026reg;)\u003c/em\u003e. American Psychiatric Pub.\u003c/li\u003e\n \u003cli\u003eArnold, M., \u0026amp; Vyshedskiy, A. (2022). Combinatorial language parent-report score differs significantly between typically developing children and those with Autism Spectrum Disorders. \u003cem\u003eJournal of Autism and Developmental Disorders\u003c/em\u003e. https://doi.org//10.1007/s10803-022-05769-8\u003c/li\u003e\n \u003cli\u003eBerwick, R. C., \u0026amp; Chomsky, N. (2019). All or nothing: No half-Merge and the evolution of syntax. \u003cem\u003ePLoS Biology\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(11), e3000539.\u003c/li\u003e\n \u003cli\u003eBishop, D. V. (2009). TROG 2: Test for reception of grammar-version 2. \u003cem\u003eEdizioni Giunti OS, Firenze\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eBraverman, J., Dunn, R., \u0026amp; Vyshedskiy, A. (2018). Development of the Mental Synthesis Evaluation Checklist (MSEC): A Parent-Report Tool for Mental Synthesis Ability Assessment in Children with Language Delay. \u003cem\u003eChildren\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(5), Article 5. https://doi.org/10.3390/children5050062\u003c/li\u003e\n \u003cli\u003eChomsky, N. (1995). The minimalist program. \u003cem\u003eMIT Press, Cambridge, MA\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eChomsky, N. (2000). Minimalist inquiries: The framework. \u003cem\u003eStep by Step: Essays on Minimalist Syntax in Honor of Howard Lasnik\u003c/em\u003e, 89\u0026ndash;155.\u003c/li\u003e\n \u003cli\u003eDe Renzi, A., \u0026amp; Vignolo, L. A. (1962). Token test: A sensitive test to detect receptive disturbances in aphasics. \u003cem\u003eBrain: A Journal of Neurology\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eDe Renzi, E., \u0026amp; Faglioni, P. (1978). Normative data and screening power of a shortened version of the Token Test. \u003cem\u003eCortex\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1), Article 1.\u003c/li\u003e\n \u003cli\u003eDragoy, O., Akinina, Y., \u0026amp; Dronkers, N. (2017). Toward a functional neuroanatomy of semantic aphasia: A history and ten new cases. \u003cem\u003eCortex\u003c/em\u003e, \u003cem\u003e97\u003c/em\u003e, 164\u0026ndash;182.\u003c/li\u003e\n \u003cli\u003eDunn, R., Elgart, J., Lokshina, L., Faisman, A., Khokhlovich, E., Gankin, Y., \u0026amp; Vyshedskiy, A. (2017a). Children With Autism Appear To Benefit From Parent-Administered Computerized Cognitive And Language Exercises Independent Of the Child\u0026rsquo;s Age Or Autism Severity. \u003cem\u003eAutism Open Access\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(217). https://doi.org/10.4172/2165-7890.1000217\u003c/li\u003e\n \u003cli\u003eDunn, R., Elgart, J., Lokshina, L., Faisman, A., Khokhlovich, E., Gankin, Y., \u0026amp; Vyshedskiy, A. (2017b). Comparison of performance on verbal and nonverbal multiple-cue responding tasks in children with ASD. \u003cem\u003eAutism Open Access\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e, 218. https://doi.org/10.4172/2165-7890.1000218\u003c/li\u003e\n \u003cli\u003eDunn, R., Elgart, J., Lokshina, L., Faisman, A., Waslick, M., Gankin, Y., \u0026amp; Vyshedskiy, A. (2017). Tablet-Based Cognitive Exercises as an Early Parent-Administered Intervention Tool for Toddlers with Autism\u0026mdash;Evidence from a Field Study. \u003cem\u003eClinical Psychiatry\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e(1). https://doi.org/10.21767/2471-9854.100037\u003c/li\u003e\n \u003cli\u003eForman, P., Khokhlovich, E., \u0026amp; Vyshedskiy, A. (2022). Longitudinal Developmental Trajectories in Young Autistic Children Presenting with Seizures, Compared to those Presenting without Seizures, Gathered via Parent-report Using a Mobile Application. \u003cem\u003eJournal of Developmental and Physical Disabilities\u003c/em\u003e. https://doi.org/10.1007/s10882-022-09851-y\u003c/li\u003e\n \u003cli\u003eFridberg, E., Khokhlovich, E., \u0026amp; Vyshedskiy, A. (2021). Watching Videos and Television Is Related to a Lower Development of Complex Language Comprehension in Young Children with Autism. \u003cem\u003eHealthcare\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(4), 423. https://doi.org/doi.org/10.3390/healthcare9040423\u003c/li\u003e\n \u003cli\u003eJackendoff, R. S., \u0026amp; Erk, K. E. (2025). Toward a Deeper Lexical Semantics. \u003cem\u003eTopics in Cognitive Science\u003c/em\u003e, tops.70013. https://doi.org/10.1111/tops.70013\u003c/li\u003e\n \u003cli\u003eJagadeesan, P., Kabbani, A., \u0026amp; Vyshedskiy, A. (2022). Parent-reported assessment scores reflect ASD severity level in 2- to 7- year-old children. \u003cem\u003eChildren\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(5), 701. https://doi.org/doi.org/10.3390/children9050701\u003c/li\u003e\n \u003cli\u003eLevin, J., Khokhlovich, E., \u0026amp; Vyshedskiy, A. (2022). Longitudinal developmental trajectories in young autistic children presenting with sleep problems, compared to those presenting without sleep problems, gathered via parent-report using a mobile application. \u003cem\u003eResearch in Autism Spectrum Disorders\u003c/em\u003e, \u003cem\u003e97\u003c/em\u003e, 102024.\u003c/li\u003e\n \u003cli\u003eMurphy, E. (2015). Labels, cognomes, and cyclic computation: An ethological perspective. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e, 715.\u003c/li\u003e\n \u003cli\u003eMurphy, E. (2019). No Country for Oldowan Men: Emerging Factors in Language Evolution. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e. https://doi.org/10.3389/fpsyg.2019.01448\u003c/li\u003e\n \u003cli\u003eMurphy, E. (2020). \u003cem\u003eThe Oscillatory Nature of Language\u003c/em\u003e (1st ed.). Cambridge University Press. https://doi.org/10.1017/9781108864466\u003c/li\u003e\n \u003cli\u003eMurphy, E. (2024). ROSE: A neurocomputational architecture for syntax. \u003cem\u003eJournal of Neurolinguistics\u003c/em\u003e, \u003cem\u003e70\u003c/em\u003e, 101180.\u003c/li\u003e\n \u003cli\u003eMurphy, E. (2025). ROSE: A Universal Neural Grammar. \u003cem\u003eCognitive Neuroscience\u003c/em\u003e, 1\u0026ndash;32. https://doi.org/10.1080/17588928.2025.2523875\u003c/li\u003e\n \u003cli\u003eMurphy, E., Forseth, K. J., Donos, C., Snyder, K. M., Rollo, P. S., \u0026amp; Tandon, N. (2023). The spatiotemporal dynamics of semantic integration in the human brain. \u003cem\u003eNature Communications\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1). https://doi.org/10.1038/s41467-023-42087-8\u003c/li\u003e\n \u003cli\u003eMurphy, E., Holmes, E., \u0026amp; Friston, K. (2024). Natural language syntax complies with the free-energy principle. \u003cem\u003eSynthese\u003c/em\u003e, \u003cem\u003e203\u003c/em\u003e(5), 154. https://doi.org/10.1007/s11229-024-04566-3\u003c/li\u003e\n \u003cli\u003eMurphy, E., Rollo, P. S., Segaert, K., Hagoort, P., \u0026amp; Tandon, N. (2024). Multiple dimensions of syntactic structure are resolved earliest in posterior temporal cortex. \u003cem\u003eProgress in Neurobiology\u003c/em\u003e, \u003cem\u003e241\u003c/em\u003e, 102669. https://doi.org/10.1016/j.pneurobio.2024.102669\u003c/li\u003e\n \u003cli\u003eMurphy, E., Woolnough, O., Rollo, P. S., Roccaforte, Z. J., Segaert, K., Hagoort, P., \u0026amp; Tandon, N. (2022). Minimal Phrase Composition Revealed by Intracranial Recordings. \u003cem\u003eThe Journal of Neuroscience\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(15), 3216\u0026ndash;3227. https://doi.org/10.1523/jneurosci.1575-21.2022\u003c/li\u003e\n \u003cli\u003eR Foundation for Statistical Computing. (2021). \u003cem\u003eR: A language and environment for statistical computing\u003c/em\u003e [Computer software]. https://www.R-project.org\u003c/li\u003e\n \u003cli\u003eRimland, B., \u0026amp; Edelson, S. M. (1999). Autism treatment evaluation checklist (ATEC). \u003cem\u003eAutism Research Institute, San Diego, CA\u003c/em\u003e. http://www.autism.com\u003c/li\u003e\n \u003cli\u003eTanaka, K., Nakamura, I., Ohta, S., Fukui, N., Zushi, M., Narita, H., \u0026amp; Sakai, K. L. (2019). Merge-generability as the key concept of human language: Evidence from neuroscience. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e, 2673.\u003c/li\u003e\n \u003cli\u003eVyshedskiy, A. (2022). Language evolution is not limited to speech acquisition: A large study of language development in children with language deficits highlights the importance of the voluntary imagination component of language. \u003cem\u003eResearch Ideas and Outcomes\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e, e86401.\u003c/li\u003e\n \u003cli\u003eVyshedskiy, A., \u0026amp; Dunn, R. (2015). Mental Imagery Therapy for Autism (MITA)-An Early Intervention Computerized Brain Training Program for Children with ASD. \u003cem\u003eAutism Open Access\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(1000153), 2.\u003c/li\u003e\n \u003cli\u003eVyshedskiy, A., Khokhlovich, E., Dunn, R., Faisman, A., Elgart, J., Lokshina, L., Gankin, Y., Ostrovsky, S., deTorres, L., \u0026amp; Edelson, S. M. (2020). Novel prefrontal synthesis intervention improves language in children with autism. \u003cem\u003eHealthcare\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(4), Article 4. https://doi.org/doi.org/10.3390/healthcare8040566\u003c/li\u003e\n \u003cli\u003eVyshedskiy, A., Pevzner, A., Mack, B., Shrayer, E., Zea, M., Bunner, S., Wong, N., Baskina, E., Sheikh, A., Tagliavia, A., Schmiedel Fucks, A., Schmiedel Sanches Santos, A., Pavoski Poloni, L. E., Fucks, E., Bolotovsky, Y., \u0026amp; Kang, S. J. S. (2025). Language Comprehension Developmental Milestones in Typically Developing Children Assessed by the New Language Phenotype Assessment (LPA). \u003cem\u003eChildren (Basel, Switzerland)\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(6), 793. https://doi.org/10.3390/children12060793\u003c/li\u003e\n \u003cli\u003eVyshedskiy, A., Venkatesh, R., \u0026amp; Khokhlovich, E. (2024). Are there distinct levels of language comprehension in autistic individuals \u0026ndash; cluster analysis. \u003cem\u003eNpj Mental Health Research\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e(19). https://doi.org/10.1038/s44184-024-00062-1\u003c/li\u003e\n \u003cli\u003eVyshedskiy, A., Venkatesh, R., Khokhlovich, E., \u0026amp; Satik, D. (2024). Three mechanisms of language comprehension are revealed through cluster analysis of individuals with language deficits. \u003cem\u003eNpj Science of Learning\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(1), 1\u0026ndash;12. https://doi.org/10.1038/s41539-024-00284-0\u003c/li\u003e\n \u003cli\u003eWiig, E. H., Secord, W. A., \u0026amp; Semel, E. (2013). \u003cem\u003eClinical evaluation of language fundamentals: CELF-5\u003c/em\u003e. Pearson.\u003c/li\u003e\n \u003cli\u003eWorld Medical Association. (2013). World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. \u003cem\u003eJAMA\u003c/em\u003e, \u003cem\u003e310\u003c/em\u003e(20), Article 20.\u003c/li\u003e\n \u003cli\u003eZimmerman, I. L., Steiner, V. G., \u0026amp; Pond, R. E. (2011). PLS-5: Preschool language scale-5 [measurement instrument]. \u003cem\u003eSan Antonio, TX: Psychological Corporation\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Merge, language evolution, recursive language, syntax, acceptability","lastPublishedDoi":"10.21203/rs.3.rs-7294415/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7294415/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the modern language sciences, the core computational operation of syntax, \u0026lsquo;Merge\u0026rsquo;, is defined as an operation that combines two linguistic units (e.g., \u0026lsquo;brown\u0026rsquo;, \u0026lsquo;cat\u0026rsquo;) to form a categorized structure (\u0026lsquo;brown cat\u0026rsquo;, a Noun Phrase). This can then be further combined with additional linguistic units based on this categorial information, respecting non-associativity such that abstract grouping is respected. Some linguists have embraced the view that Merge is an elementary, indivisible operation that emerged in a single evolutionary step. From a neurocognitive standpoint, different mental objects constructed by Merge may be supported by distinct mechanisms: (1) simple command constructions (e.g., \u0026ldquo;eat apples\u0026rdquo;); (2) the merging of adjectives and nouns (\u0026ldquo;red boat\u0026rdquo;); and (3) the merging of nouns with spatial prepositions (\u0026ldquo;laptop behind the sofa\u0026rdquo;). Here, we systematically investigate participants\u0026rsquo; comprehension of sentences with increasing levels of syntactic complexity. Clustering analyses revealed behavioral evidence for three distinct structural types, which we discuss as potentially emerging at different developmental stages and subject to selective impairment. While a Merge-based syntax may still have emerged suddenly in evolutionary time, responsible for the structured symbolic turn our species took, different cognitive mechanisms seem to underwrite the processing of various types of Merge-based objects.\u003c/p\u003e","manuscriptTitle":"Merge-based syntax is mediated by distinct neurocognitive mechanisms: A clustering analysis of comprehension abilities in 84,000 individuals with language deficits across nine languages","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-17 05:14:06","doi":"10.21203/rs.3.rs-7294415/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-10T01:27:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-09T00:09:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-14T14:42:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308795441160097767682869612353985644523","date":"2025-09-14T09:14:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"220925619035826640310964951659347252338","date":"2025-09-10T04:06:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-08T16:11:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-08T16:00:42+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-08T14:38:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-04T16:58:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-04T16:54:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e4f0e61a-80c9-454e-b3d0-a4d502d2ac91","owner":[],"postedDate":"September 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":54690166,"name":"Humanities/Language and linguistics"},{"id":54690167,"name":"Social science/Language and linguistics"},{"id":54690168,"name":"Biological sciences/Neuroscience"},{"id":54690169,"name":"Biological sciences/Psychology"},{"id":54690170,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2025-12-29T16:01:39+00:00","versionOfRecord":{"articleIdentity":"rs-7294415","link":"https://doi.org/10.1038/s41598-025-28008-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-24 15:57:54","publishedOnDateReadable":"December 24th, 2025"},"versionCreatedAt":"2025-09-17 05:14:06","video":"","vorDoi":"10.1038/s41598-025-28008-3","vorDoiUrl":"https://doi.org/10.1038/s41598-025-28008-3","workflowStages":[]},"version":"v1","identity":"rs-7294415","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7294415","identity":"rs-7294415","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}