Domain-specific Cognitive Abilities Research Articles

Are science competitions meeting their intentions? a case study on affective and cognitive predictors of success in the Physics Olympiad

Contemporary science competitions particularly have two intentions: (1) identifying the students demonstrating the highest levels of domain-specific cognitive abilities and (2) recognizing and valuing the efforts of engaged and motivated students, even those without exceptional abilities. This study aimed to examine the relative influence of affective and cognitive variables on predicting success among 136 participants of the first two rounds of the German Physics Olympiad, and based on that, evaluate the extent to which the Physics Olympiad meets the outlined intentions. Our findings indicate that the competition’s initial round erects a hurdle for engaged and motivated students who lack sufficient cognitive abilities, which goes against the above mentioned second intention. Conversely, the Physics Olympiad appears to effectively align with its first intention by successfully identifying students with high developed physics-specific abilities. Building on our findings, we discuss ways for better aligning the competition with its intentions, thus contributing to the ongoing further development of science competitions.

Cognitive abilities are associated with specific conjunctions of structural and functional neural subnetworks

Cognitive neuroscience assumes that different mental abilities correspond to at least partly separable brain subnetworks and strives to understand their relationships. However, single-task approaches typically revealed multiple brain subnetworks to be involved in performance. Here, we chose a bottom-up approach of investigating the association between structural and functional brain subnetworks, on the one hand, and domain-specific cognitive abilities, on the other. Structural network was identified using machine-learning graph neural network by clustering anatomical brain properties measured in 838 individuals enroled in the WU-Minn Young Adult Human Connectome Project. Functional network was adapted from seven Resting State Networks (7-RSN). We then analyzed the results of 15 cognitive tasks and estimated five latent abilities: fluid reasoning (Gf), crystallized intelligence (Gc), memory (Mem), executive functions (EF), and processing speed (Gs). In a final step we determined linear associations between these independently identified ability and brain entities. We found no one-to-one mapping between latent abilities and brain subnetworks. Analyses revealed that abilities are associated with properties of particular combinations of brain subnetworks. While some abilities are more strongly associated to within-subnetwork connections, others are related with connections between multiple subnetworks. Importantly, domain-specific abilities commonly rely on node(s) as hub(s) to connect with other subnetworks. To test the robustness of our findings, we ran the analyses through several defensible analytical decisions. Together, the present findings allow a novel perspective on the distinct nature of domain-specific cognitive abilities building upon unique combinations of associated brain subnetworks.

Intelligence, cognition, and major neurocognitive disorders: From constructs to measures

The study of intelligence's role in development of major neurocognitive disorders (MND) is influenced by the approaches used to conceptualize and measure these constructs. In the field of cognitive impairment, the use of single ‘intelligence’ tests is a common approach to estimate intelligence. Despite being a practical compromise between feasibility and constructs, variance of these tests is only partially explained by general intelligence, and some tools (e.g., lexical tasks for premorbid intelligence) presented inherent limitations. Alternatively, factorial models allow an actual measure of intelligence as a latent factor superintending all mental abilities. Royall and colleagues used structural equation modeling to decompose the Spearman's general intelligence factor g in δ (shared variance across cognitive and functional measures) and g’ (shared variance across cognitive measures only). Authors defined δ as the ‘cognitive correlates of functional status’, and thus a ‘phenotype for all cause dementia’. Compared to g’, δ explained a little rate of cognitive measures’ variance, but it demonstrated a higher accuracy in dementia case-finding. From the methodological perspective, given g ‘indifference’ to its indicators, further studies are needed to identify the minimal set of tools necessary to extract g, and to test also non-cognitive variables as measures of δ. From the clinical perspective, general intelligence seems to influence MND presence and severity more than domain specific cognitive abilities. Giving δ ‘blindness’ to etiology, its association with biomarkers and contribution to differential diagnosis might be limited. Classical neuropsychological approaches based on patterns of performances at cognitive tests remained fundamental for differential diagnosis.

The Prognostic Value of Domain-Specific Cognitive Abilities Assessed by Chinese Version of Oxford Cognitive Screen on Determining ADLs Recovery in Patients with Post-Stroke Cognitive Impairment.

Background Poststroke cognitive impairment (PSCI) has been increasingly recognized in patients. However, it remains unclear whether ADLs recovery is more susceptible to domain-specific cognitive abilities after a stroke. Therefore, the study was designed to investigate the cognitive functions of patients with PSCI at admission by using the Chinese (Putonghua) Version of the Oxford Cognitive Screen (OCS-P) as well as to identify the prognostic value of domain-specific cognitive abilities on the recovery of ADLs when discharged. Methods A total of 153 hospitalized stroke patients were included in this prospective study. Cognitive function was assessed by OCS-P when participants were admitted to the hospital. The ADLs were measured at admission and discharge, and recovery was estimated by the improvement between admission and discharge. A diagnostic model using logistic regression was constructed to identify the prognostic value of domain-specific cognitive abilities for ADLs. The efficacy and accuracy of the diagnostic model were assessed by receiver operating characteristic (ROC) and Hosmer-Lemeshow's goodness of fit test. The diagnostic model was validated by 10-fold cross-validation and presented as a nomogram. Results The score of OCS-P was 60(49.75, 69). The most frequently impaired cognitive domain was number writing (60.8%), followed by verbal memory (52.9%). Multivariate logistic regression showed executive dysfunction was a risk prognostic factor of ADLs recovery (P < 0.001, OR = 3.176 [95% CI, 1.218∼8.278]). The ROC curve of the diagnostic model was 0.839, with a good diagnostic efficacy. Hosmer–Lemeshow test showed diagnostic model had good calibration ability (χ2 = 8.939.3, P=0.347 > 0.05). The average error rate after adjustment of 10-fold cross-validation was 20.93%, within the acceptable range. Conclusions Post-stroke patients generally suffered from multidimensional cognitive impairments. Executive dysfunction screened with OCS-P at clinical admission was a reliable and accessible predictive factor ADLs recovery in patients with PSCI. Early targeted rehabilitation programs are suggested to make them as earlier as possible, especially for those having executive dysfunction while hospitalized.

Lesion symptom mapping of domain-specific cognitive impairments using routine imaging in stroke

IntroductionThis large-scale lesion-symptom mapping study investigates the necessary neuro-anatomical substrates of 5 cognitive domains frequently affected post stroke: Language, Attention, Praxis, Number, and Memory. This study aims to demonstrate the validity of using routine clinical brain imaging and standard bedside cognitive screening data from a large, real-world patient cohort for lesion-symptom mapping. Patients and methodsBehavioural cognitive screening data from the Oxford Cognitive Screen and routine clinical neuroimaging from 573 acute patients was used in voxel-based lesion-symptom mapping analyses. Patients were classed as impaired or not on each of the subtests within 5 cognitive domains. ResultsDistinct patterns of lesion damage were associated with different domains. Language functions were associated with damage to left hemisphere fronto-temporal areas. Visuo-spatial functions were associated with damage to posterior occipital areas (Visual Field) and the right temporo-parietal region (Visual Neglect). Different memory impairments were linked to distinct voxel clusters within the left insular and opercular cortices. Deficits which were not associated with localised voxels (e.g. executive function, praxis) represent distributed, bilateral functions. DiscussionThe standardised, brief Oxford Cognitive Screen was able to reliably differentiate distinct neural correlates critically involved in supporting domain-specific cognitive abilities. ConclusionBy demonstrating and replicating known brain anatomy correlates within real-life clinical cohorts using routinely collected scans and standard bedside screens, we open up VLSM techniques to a wealth of clinically relevant studies which can capitalise on using existing clinical data.

The Cognitive-Affective-Motivation Model of Learning (CAMML): Standing on the Shoulders of Giants

The Cognitive-Affective-Motivation Model of Learning (CAMML) is a proposed framework for integrating contemporary motivation, affective (Big 5 personality) and cognitive (CHC theory) constructs in the practice of school psychologists (SPs). The central tenet of this article is that SPs need to integrate motivation alongside affective and cognitive constructs vis-à-vis an updated trilogy-of-the-mind (cognitive, conative, affective) model of intellectual functioning. CAMML builds on Richard Snow’s seminal research on academic aptitudes—which are not synonymous with cognitive abilities. Learning aptitude complexes are academic domain-specific cognitive abilities and personal investment mechanisms (motivation and self-regulation) that collectively produce a student’s readiness to learn in a specific domain. CAMML incorporates the “crossing the Rubicon” commitment pathway model of motivated self-regulated learning. It is recommended SPs take a fresh look at motivation theory, constructs, and research, embedded in the CAMML aptitude framework, by going back-to-the-future guided by the wisdom of giants from the field of cognition, intelligence, and educational psychology.

Associations between total MRI-visible small vessel disease burden and domain-specific cognitive abilities in a community-dwelling older-age cohort

Cerebral small vessel disease (SVD) is a leading cause of vascular cognitive impairment, however the precise nature of SVD-related cognitive deficits, and their associations with structural brain changes, remain unclear. We combined computational volumes and visually-rated MRI markers of SVD to quantify total SVD burden, using data from the Lothian Birth Cohort 1936 (n = 540; age: 72.6 ± 0.7 years). We found negative associations between total SVD burden and general cognitive ability (standardized β: -0.363; 95%CI: [-0.49, -0.23]; p(FDR) < 0.001), processing speed (-0.371 [-0.50, -0.24]; p(FDR) < 0.001), verbal memory (-0.265; [-0.42, -0.11]; p(FDR) = 0.002), and visuospatial ability (-0.170; [-0.32, -0.02]; p(FDR) = 0.029). Only the association between SVD burden and processing speed remained after accounting for covariance with general cognitive ability (-0.325; [-0.61, -0.04]; p(FDR) = 0.029). This suggests that SVD's association with poorer processing speed is not driven by, but is independent of its association with poorer general cognitive ability. Tests of processing speed may be particularly sensitive to the cognitive impact of SVD, but all major cognitive domains should be tested to determine the full range of SVD-related cognitive characteristics.

Psychometric models of individual differences in reading comprehension: A reanalysis of Freed, Hamilton, and Long (2017)

• Advocate network models complement latent variable models of individual differences. • Reviews best practices for data cleaning and diagnostics for psychometric modeling. • Reanalysis of Freed et al. (2017) reveals problematic measurement model. • Measures of reading comprehension and language experience load on one latent factor. • Network models corroborate findings and alternative conclusions are proposed. Individual differences in reading comprehension have often been explored using latent variable modeling (LVM), to assess the relative contribution of domain-general and domain-specific cognitive abilities. However, LVM is based on the assumption that the observed covariance among indicators of a construct is due to a common cause (i.e., a latent variable; Pearl, 2000). This is a questionable assumption when the indicator variables are measures of performance on complex cognitive tasks. According to Process Overlap Theory (POT; Kovacs & Conway, 2016), multiple processes are involved in cognitive task performance and the covariance among tasks is due to the overlap of processes across tasks. Instead of a single latent common cause, there are thought to be multiple dynamic manifest causes, consistent with an emerging view in psychometrics called network theory (Barabási, 2012; Borsboom & Cramer, 2013). In the current study, we reanalyzed data from Freed et al. (2017) and compared two modeling approaches: LVM (Study 1) and psychometric network modeling (Study 2). In Study 1, two exploratory LVMs demonstrated problems with the original measurement model proposed by Freed et al. Specifically, the model failed to achieve discriminant and convergent validity with respect to reading comprehension, language experience, and reasoning. In Study 2, two network models confirmed the problems found in Study 1, and also served as an example of how network modeling techniques can be used to study individual differences. In conclusion, more research, and a more informed approach to psychometric modeling, is needed to better understand individual differences in reading comprehension.

Association of SBP and BMI with cognitive and structural brain phenotypes in UK Biobank.

To test for associations between SBP and BMI, with domain-specific cognitive abilities and examine which brain structural phenotypes mediate those associations. Using cross-sectional UK Biobank data (final N = 28 412), we examined SBP/BMI vs. cognitive test scores of pairs-matching, matrix completion, trail making test A/B, digit symbol substitution, verbal-numerical reasoning, tower rearranging and simple reaction time. We adjusted for potential confounders of age, sex, deprivation, medication, apolipoprotein e4 genotype, smoking, population stratification and genotypic array. We tested for mediation via multiple structural brain imaging phenotypes and corrected for multiple testing with false discovery rate. We found positive associations for higher BMI with worse reaction time, reasoning, tower rearranging and matrix completion tasks by 0.024-0.067 SDs per BMI SD (all P < 0.001). Higher SBP was associated with worse reasoning (0.034 SDs) and matrix completion scores (-0.024 SDs; both P < 0.001). Both BMI and SBP were associated with multiple brain structural metrics including total grey/white matter volumes, frontal lobe volumes, white matter tract integrity and white matter hyperintensity volumes: specific metrics mediated around one-third of the associations with cognition. Our findings add to the body of evidence that addressing cardiovascular risk factors may also preserve cognitive function, via specific aspects of brain structure.

Cognitive predictors of children's development in mathematics achievement: A latent growth modeling approach.

Research has identified various domain-general and domain-specific cognitive abilities as predictors of children's individual differences in mathematics achievement. However, research into the predictors of children's individual growth rates, namely between-person differences in within-person change in mathematics achievement is scarce. We assessed 334 children's domain-general and mathematics-specific early cognitive abilities and their general mathematics achievement longitudinally across four time-points within the first and second grades of primary school. As expected, a constellation of multiple cognitive abilities contributed to the children's starting level of mathematical success. Specifically, latent growth modeling revealed that WM abilities, IQ, counting skills, nonsymbolic and symbolic approximate arithmetic and comparison skills explained individual differences in the children's initial status on a curriculum-based general mathematics achievement test. Surprisingly, however, only one out of all the assessed cognitive abilities was a unique predictor of the children's individual growth rates in mathematics achievement: their performance in the symbolic approximate addition task. In this task, children were asked to estimate the sum of two large numbers and decide if this estimated sum was smaller or larger compared to a third number. Our findings demonstrate the importance of multiple domain-general and mathematics-specific cognitive skills for identifying children at risk of struggling with mathematics and highlight the significance of early approximate arithmetic skills for the development of one's mathematical success. We argue the need for more research focus on explaining children's individual growth rates in mathematics achievement.

The evolution of intelligence in mammalian carnivores.

Although intelligence should theoretically evolve to help animals solve specific types of problems posed by the environment, it is unclear which environmental challenges favour enhanced cognition, or how general intelligence evolves along with domain-specific cognitive abilities. The social intelligence hypothesis posits that big brains and great intelligence have evolved to cope with the labile behaviour of group mates. We have exploited the remarkable convergence in social complexity between cercopithecine primates and spotted hyaenas to test predictions of the social intelligence hypothesis in regard to both cognition and brain size. Behavioural data indicate that there has been considerable convergence between primates and hyaenas with respect to their social cognitive abilities. Moreover, compared with other hyaena species, spotted hyaenas have larger brains and expanded frontal cortex, as predicted by the social intelligence hypothesis. However, broader comparative study suggests that domain-general intelligence in carnivores probably did not evolve in response to selection pressures imposed specifically in the social domain. The cognitive buffer hypothesis, which suggests that general intelligence evolves to help animals cope with novel or changing environments, appears to offer a more robust explanation for general intelligence in carnivores than any hypothesis invoking selection pressures imposed strictly by sociality or foraging demands.

Feasibility and efficacy of cognitive telerehabilitation in early Alzheimer&amp;rsquo;s disease: a&amp;nbsp;pilot study

BackgroundThis pilot study compared the effects of lexical-semantic stimulation through telecommunication technology (LSS-tele) with in-person LSS (LSS-direct) and unstructured cognitive treatment (UCS) in patients with early Alzheimer’s disease.MethodsTwenty-seven patients with Alzheimer’s disease in the very early stage (Mini-Mental State Examination [MMSE] >26/30) were divided into three groups: seven patients received LSS-tele treatment, ten received standard LSS-direct intervention, and ten participants underwent UCS as control condition. Intervention treatments consisted of two weekly sessions of LSS (through teleconference or face to face depending on group assignment) or UCS exercises administered to small groups throughout a 3-month period. The main outcome measures were changes of global cognitive performance, language abilities, and memory function. Secondary outcome measures were changes in attention, working memory, executive functions, and visual-spatial abilities tests.ResultsThe mean MMSE score improved significantly in LSS-tele and LSS-direct treatments; LSS-tele improved language abilities, both phonemic and semantic, and stabilized delayed verbal episodic memory with respect to an improved performance after the LSS-direct intervention and to a memory decline observed in the control group. Improvement was not achieved in any neuropsychological test score after UCS.ConclusionClinical application of telecommunication technology to cognitive rehabilitation of elderly patients with neurodegenerative cognitive impairment is feasible and may improve global cognitive performance. Technical aspects to ameliorate efficacy of delivery may further improve its impact on domain-specific cognitive abilities.

Differences in General Cognitive Abilities and Domain-Specific Skills of Higher- and Lower-Achieving Students in Stoichiometry

This paper reports a comparison of a group of higher- and lower-achieving undergraduate chemistry students, 17 in total, as separated on their ability in stoichiometry. This exploratory study of 17 students investigated parallels and differences in the students’ general and domain-specific cognitive abilities. Performance, strategies, and mistakes in the students’ problem solving in the field of stoichiometry were also investigated in detail. The study revealed that the major difference between higher- and lower-achieving students lies in their cognitive skills, especially in domain-specific (mole concept) skills and the ability to deal with complexity. Results suggest that a thoroughly differentiated set of tasks be applied in the undergraduate chemistry classroom: tasks with limited complexity and structured help or scaffolding are needed for lower-achieving students, whereas complex and abstract tasks are needed to challenge the higher-achieving students.

Components of air pollution and cognitive function in middle-aged and older adults in Los Angeles

While experiments in animals demonstrate neurotoxic effects of particulate matter (PM) and ozone (O3), epidemiologic evidence is sparse regarding the relationship between different constituencies of air pollution mixtures and cognitive function in adults. We examined cross-sectional associations between various ambient air pollutants [O3, PM2.5 and nitrogen dioxide (NO2)] and six measures of cognitive function and global cognition among healthy, cognitively intact individuals (n=1496, mean age 60.5 years) residing in the Los Angeles Basin. Air pollution exposures were assigned to each residential address in 2000–06 using a geographic information system that included monitoring data. A neuropsychological battery was used to assess cognitive function; a principal components analysis defined six domain-specific functions and a measure of global cognitive function was created. Regression models estimated effects of air pollutants on cognitive function, adjusting for age, gender, race, education, income, study and mood. Increasing exposure to PM2.5 was associated with lower verbal learning (β=−0.32 per 10μg/m3 PM2.5, 95% CI=−0.63, 0.00; p=0.05). Ambient exposure to NO2 >20ppb tended to be associated with lower logical memory. Compared to the lowest level of exposure to ambient O3, exposure above 49ppb was associated with lower executive function. Including carotid artery intima-media thickness, a measure of subclinical atherosclerosis, in models as a possible mediator did not attenuate effect estimates. This study provides support for cross-sectional associations between increasing levels of ambient O3, PM2.5 and NO2 and measures of domain-specific cognitive abilities.

Using IQ Discrepancy Scores To Examine the Neural Correlates of Specific Cognitive Abilities

The underlying neural determinants of general intelligence have been studied intensively, and seem to derive from the anatomical and functional characteristics of a frontoparietal network. Little is known, however, about the underlying neural correlates of domain-specific cognitive abilities, the other factors hypothesized to explain individual performance on intelligence tests. Previous preliminary studies have suggested that spatially distinct neural structures do not support domain-specific cognitive abilities. To test whether differences between abilities that affect performance on verbal and performance tasks derive instead from the morphological features of a single anatomical network, we assessed in two independent samples of healthy human participants (N=83 and N=58; age range, 5-57 years) the correlation of cortical thickness with the magnitude of the verbal intelligence quotient (VIQ)-performance intelligence quotient (PIQ) discrepancy. We operationalized the VIQ-PIQ discrepancy by regressing VIQ onto PIQ (VIQ-regressed-on-PIQ score), and by regressing PIQ onto VIQ (PIQ-regressed-on-VIQ score). In both samples, a progressively thinner cortical mantle in anterior and posterior regions bilaterally was associated with progressively greater (more positive) VIQ-regressed-on-PIQ scores. A progressively thicker cortical mantle in anterior and posterior regions bilaterally was associated with progressively greater (more positive) PIQ-regressed-on-VIQ scores. Variation in cortical thickness in these regions accounted for a large portion of the overall variance in magnitude of the VIQ-PIQ discrepancy. The degree of hemispheric asymmetry in cortical thickness accounted for a much smaller but statistically significant portion of variance in VIQ-PIQ discrepancy.

Cognitive ability, academic achievement and academic self‐concept: Extending the internal/external frame of reference model

Marsh's internal/external (I/E) frame of reference model depicts the relationship between achievement and self-concept in specific academic domains. Few efforts have been made to examine concurrent relationships among cognitive ability, achievement, and academic self-concept (ASC) within an I/E model framework. To simultaneously examine the influences of domain-specific cognitive ability and grades on domain self-concept in an extended I/E model, including the indirect effect of domain-specific cognitive ability on domain self-concept via grades. Tenth grade respondents (628 male, 452 female) to a national adolescent survey conducted in Taiwan. Respondents completed surveys designed to measure maths and verbal aptitudes. Data on Maths and Chinese class grades and self-concepts were also collected. Statistically significant and positive path coefficients were found between cognitive ability and self-concept in the same domain (direct effect) and between these two constructs via grades (indirect effect). The cross-domain effects of either ability or grades on ASC were negatively significant. Taiwanese 10th graders tend to evaluate their ASCs based on a mix of ability and achievement, with achievement as a mediator exceeding ability as a predictor. In addition, the cross-domain effects suggest that Taiwanese students are likely to view Maths and verbal abilities and achievements as distinctly different.

Association between the A1 allele of the DRD2 gene and reduced verbal abilities in adolescence and early adulthood

Behavioral genetic research has consistently revealed that genetic factors explain at least one half of the variance in measures of cognitive skills. However, the specific DNA markers involved in the etiology of cognitive abilities have remained elusive. The current study examined the association between the TaqI polymorphism in the dopamine D2 receptor gene (DRD2) and verbal skills. Analysis of data drawn from the National Longitudinal Study of Adolescent Health (Add Health) revealed that the A1 allele was associated with group membership in high-, average-, and low-verbal skills groups for Caucasians. The results suggest that DRD2 may be related to domain specific cognitive abilities, such as verbal skills.

The prognostic value of domain-specific cognitive abilities in acute first-ever stroke

To evaluate the prognostic value of domain-specific cognitive abilities in acute stroke with respect to long-term cognitive and functional outcome in addition to neurologic and demographic predictors. The authors evaluated 168 patients within the first 3 weeks after first-ever stroke. The prevalence of neuropsychological impairment was calculated vs 75 matched healthy controls. The authors also recorded demographic data, vascular risk factors, lesion characteristics, and clinical factors at admission. Independent predictor variables associated with long-term cognitive impairment (assessed with a follow-up neuropsychological examination) and functional impairment (assessed with the modified Barthel Index and the Frenchay Activities Index) were identified with stepwise multiple logistic regression. Areas under receiver operator characteristic curves were used to compare the predictive value of three models, i.e., a standard medical model, a purely cognitive model, and a model consisting of both medical and cognitive predictors. Thirty-one percent of patients showed long-term cognitive impairment. Basic and instrumental ADL disturbances remained present in 19% and 24% of patients. Domain-specific cognitive functioning predicted cognitive and functional outcome better than any other variable. Moreover, the prediction of instrumental ADL functioning improved when cognitive predictors were added to the standard medical model (p < 0.05). Impairments in abstract reasoning and executive functioning were independent predictors of long-term cognitive impairment. Inattention and perceptual disorders were more important in predicting long-term functional impairment. Domain-specific cognitive abilities in the early phase of stroke are excellent independent predictors of long-term cognitive and functional outcome.

Melissa Bowerman &amp; Stephen Levinson (eds.), Language acquisition and conceptual development. Cambridge: Cambridge University Press, 2001. Pp. ix, 602. Hb. $100.00, pb. $35.00.

This volume, dedicated to Martin Braine, is the outcome of a conference held at the Max Plank Institute in Nijmegen in 1995. The first of four parts covers general theoretical issues; part 2 focuses specifically on word learning, particularly nouns; in part 3, entities, individuation and quantification are examined; and in part 4, relational concepts in form-function mapping, with a focus on the influence of language-specific properties. Two main issues link the nineteen chapters: whether concepts are language-independent or constructed through language, and the role of experience in conceptual development. As emphasized by the editors in the introduction, past attempts to relate cognitive and linguistic development have not been too successful, possibly because of the focus on language structure within theoretical linguistics. Recent research on the domain-specific cognitive abilities of infants and on semantic and cross-linguistic aspects of language acquisition have provided new insights, and thus it is timely to reexamine the links.

Aristotelian Categories And Cognitive Domains

This paper puts together an ancientand a recent approach to classificatory language, thought, and ontology.It includes on the one hand an interpretation of Aristotle's ten categories,with remarks on his first category, called (or translated as) substancein the Categories or What a thing is in the Topics. On the other hand is the ideaof domain-specific cognitive abilities urged in contemporary developmentalpsychology. Each family of ideas can be used to understand the other. Neitherthe metaphysical nor the psychological approach is intrinsically morefundamental; they complement each other. The paper incidentally clarifies distinct uses of the word “category” in different disciplines, and also attempts to make explicit several notions of “domain”. It also examines Aristotle's most exotic and least discussed categories, being-in-a-position (e.g., sitting) and having-(on) (e.g., armour). Finally the paper suggests a tentative connectionbetween Fred Sommers' theory of types and Aristotle's first category.