Both fluid intelligence and visual object recognition ability relate to nodule detection in chest radiographs

Visual arts require the ability to process, categorize, recognize, and understand a variety of visual inputs. These challenges may engage and even influence mechanisms that are also relevant for visual object recognition beyond visual arts. A domain-general object recognition ability that applies broadly across a range of visual tasks was recently discovered. Here, we ask whether experience with visual arts is correlated with this domain-general ability. We developed a new survey to measure general visual arts experience and use it to measure arts experience in 142 individuals in whom we also estimated domain-general object recognition ability. Despite our measures demonstrating high reliability in a large sample size, we found substantial evidence (BF01 = 9.52) for no correlation between visual arts experience and general object recognition ability. This suggests that experience in visual arts has little influence on object recognition skills or vice versa, at least in our sample ranging from low to moderately high levels of arts experience. Our methods can be extended to other populations and our results should be replicated, as they suggest some limitations for the generalization of programs targeting visual literacy beyond the visual arts.

Measurement of object recognition (OR) ability could predict learning and success in real-world settings, and there is hope that it may reduce bias often observed in cognitive tests. Although the measurement of visual OR is not expected to be influenced by the language of participants or the language of instructions, these assumptions remain largely untested. Here, we address the challenges of measuring OR abilities across linguistically diverse populations. In Study 1, we find that English–Spanish bilinguals, when randomly assigned to the English or Spanish version of the novel object memory test (NOMT), exhibit a highly similar overall performance. Study 2 extends this by assessing psychometric equivalence using an approach grounded in item response theory (IRT). We examined whether groups fluent in English or Spanish differed in (a) latent OR ability as assessed by a three-parameter logistic IRT model, and (2) the mapping of observed item responses on the latent OR construct, as assessed by differential item functioning (DIF) analyses. Spanish speakers performed better than English speakers, a difference we suggest is due to motivational differences between groups of vastly different size on the Prolific platform. That we found no substantial DIF between the groups tested in English or Spanish on the NOMT indicates measurement invariance. The feasibility of increasing diversity by combining groups tested in different languages remains unexplored. Adopting this approach could enable visual scientists to enhance diversity, equity, and inclusion in their research, and potentially in the broader application of their work in society.

The selection, use, and memory for the information that support visual object recognition is a general ability that applies across varied tasks and categories. In convergence with cross-modal experimental studies, individual differences research suggests that this ability also predicts haptic object recognition. An important component in the measurement of a general construct for haptic object recognition is the use of multiple tasks to form a latent construct that can explain behavior across tasks with different constraints. While the ultimate goal is to use latent variable modeling, as an intermediate step, we developed two new haptic tests and use the principle of aggregation to create representative estimates for abilities of interest. One test emphasizes the use of texture features with Braille stimuli and another test emphasizes shape features using palm-sized 3D-printed Greebles. We measured object recognition ability using existing visual and haptic object recognition tests alongside our new tests (n=87). Our new tests have acceptable reliability (omegas > .72). The new Braille test correlates with an existing haptic test also using texture features with flat buttons (r=.40, BF10=1490). Similarly, the new Greebles test correlates with an existing shape-reliant test with 3D-printed spaceships, though weaker (r=.19, BF10=2.33). Combining these pairs of tests into two aggregate measures of haptic object recognition ability dependent on feature type reveals a correlation (r=.41, BF10=2999). Furthermore, combining all four haptic test scores into a single haptic object recognition measure reveals a correlation with general visual object recognition ability measured by two tests (r=.34, BF10=132.41). Our results suggest a general factor for haptic object recognition regardless of feature types, one that overlaps with visual object recognition ability. This is an important step in building a latent construct for general haptic object recognition ability to test its relationship with the analogous general visual ability.

The investment hypothesis proposes that fluid intelligence drives the accumulation of crystallized intelligence, such that crystallized intelligence increases more substantially in individuals with high rather than low fluid intelligence. However, most investigations have been conducted on adolescent cohorts or in two-wave data sets. There are few longitudinal representative studies with which to observe the growth of intelligence in young adulthood. A large community representative sample of 20- to 24-year-olds was recruited in 1999 and followed in 2003 and 2007. The Spot-the-Word Test Version A, a lexical decision task, was used to assess crystallized intelligence. The Symbol–Digit Modalities Test, a test of perceptual speed, was used as a measure of fluid intelligence. Latent growth models were used to examine whether growth in fluid intelligence drives the acquisition of crystallized intelligence. Fluid and crystallized intelligence are coupled; crystallized intelligence accrues in the 20s, but the rate of increase of crystallized intelligence is not associated with the level of fluid intelligence. Although young adulthood is associated with “the getting of wisdom,” accelerated development of crystallized intelligence in those with high fluid intelligence was not observed. Hence, no support was found for the investment hypothesis.

Wonderlic, working memory capacity, and fluid intelligence

A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database

Studies in cultural evolution have uncovered many types of social learning strategies that are adaptive in certain environments. The efficiency of these strategies also depends on the individual characteristics of both the observer and the demonstrator. We investigate the relationship between intelligence and the ways social and individual information is utilised to make decisions in an uncertain environment. We measure fluid intelligence and study experimentally how individuals learn from observing the choices of a demonstrator in a 2-armed bandit problem with changing probabilities of a reward. Participants observe a demonstrator with high or low fluid intelligence. In some treatments they are aware of the intelligence score of the demonstrator and in others they are not. Low fluid intelligence individuals imitate the demonstrator more when her fluid intelligence is known than when it is not. Conversely, individuals with high fluid intelligence adjust their use of social information, as the observed behaviour changes, independently of the knowledge of the intelligence of the demonstrator. We provide evidence that intelligence determines how social and individual information is integrated in order to make choices in a changing uncertain environment.

Prospective associations between intelligence, working memory capacity, and intrusive memories of a traumatic film: Potential mediating effects of rumination and memory disorganization

The influence of white matter lesions on depressive symptoms in healthy ageing populations remains unclear. In this study, we examined the relationship between depressive symptoms and magnetic resonance imaging (MRI) detected cerebrovascular disease in a normal population living independently in the community, and measured the influence of location of brain abnormalities, fluid intelligence, living alone, and sex. Prospective cohort: 497 community dwelling individuals all born in 1936, who took part in the Scottish Mental Survey of 1947, were followed up in 2000 and at biannual intervals in a longitudinal study of health and cognitive aging. Two hundred forty-four volunteered for brain MRI in 2004-2006. Suitable data were available in 219/244, of whom 115 were men. Brain hyperintensities in lobar white matter, basal ganglia , periventricular, and infratentorial regions were measured using Scheltens' scale. Depressed mood was assessed using the Hospital Anxiety and Depression Scale (HADS) on three biannual intervals. Relationships between Scheltens' scores, HADS-D scores, fluid intelligence, living alone, and sex were assessed using general linear modeling. The main predictor of depressive symptom scores was poorer fluid intelligence (partial η(2) =0.023-0.028, P < .05). Ischemic change in the brainstem (partial η(2) = 0.026, P ≤.05) and basal ganglia (partial η(2) =0.018, P ≤ .05) also predicted HADS-D scores. There was no relationship with sex or living alone. Hyperintensities in the brainstem and basal ganglia are associated with depressive symptoms. Higher fluid intelligence is associated with lower depressive symptoms in this normal, ageing population.

Emotion recognition has been a focus of considerable attention for several decades. However, despite this interest, the underlying structure of individual differences in emotion recognition ability has been largely overlooked and thus is poorly understood. For example, limited knowledge exists concerning whether recognition ability for one emotion (e.g., disgust) generalizes to other emotions (e.g., anger, fear). Furthermore, it is unclear whether emotion recognition ability generalizes across modalities, such that those who are good at recognizing emotions from the face, for example, are also good at identifying emotions from nonfacial cues (such as cues conveyed via the body). The primary goal of the current set of studies was to address these questions through establishing the structure of individual differences in visual emotion recognition ability. In three independent samples (Study 1: n = 640; Study 2: n = 389; Study 3: n = 303), we observed that the ability to recognize visually presented emotions is based on different sources of variation: a supramodal emotion-general factor, supramodal emotion-specific factors, and face- and within-modality emotion-specific factors. In addition, we found evidence that general intelligence and alexithymia were associated with supramodal emotion recognition ability. Autism-like traits, empathic concern, and alexithymia were independently associated with face-specific emotion recognition ability. These results (a) provide a platform for further individual differences research on emotion recognition ability, (b) indicate that differentiating levels within the architecture of emotion recognition ability is of high importance, and (c) show that the capacity to understand expressions of emotion in others is linked to broader affective and cognitive processes.

The Job Demands–Resources Theory (JD-R) is one of the most influential theoretical frameworks for explaining work engagement. The JD-R postulates the existence of a health impairment process in which job demands lead to strain, and of a motivational process in which job resources lead to work engagement. Although cognitive functions are among the most important characteristics of employees related to job, still little is known about its moderating role in JD-R processes; hence in this study we make a novel attempt to test the invariance of JD-R propositions among employees at different levels of cognitive functioning. A group of 383 multioccupational employees completed a set of questionnaires measuring job resource: co-worker support, supervisor support, performance feedback; job demands: emotional demands, occupational constraints, work-home interferences; Utrecht Work Engagement Scale; Oldenburg Burnout Inventory along with 2 working memory and 3 fluid intelligence tests. The multigroup invariance analysis with latent variables revealed that both the health impairment process and the motivational process as postulated by JD-R are invariant across groups of employees with either high or low levels of fluid intelligence and working memory capacity. This result provides the first piece of evidence for JD-R robustness among employees at different levels of cognitive functioning. Our findings counterintuitively suggest that employees with high cognitive functioning are not more resistant to job demands than employees with low cognitive functioning and that in order to be work-engaged they need job resources, no less than their colleagues with low cognitive functioning. Med Pr 2018;69(5):483–496

Early life multiple exposures and child cognitive function: A multi-centric birth cohort study in six European countries

Metabolic syndrome (MetS) refers to risk factors for cardiovascular disease associated with reduced physical fitness, higher disease burden, and impaired cognitive functions. Available evidence indicates that metabolic functioning is related to brain structure at the level of specific indicators, such as hypertension and voxel-based morphometry, respectively. However, attempts to relate metabolic load to brain morphology at the construct level using structural equation modeling are scarce. Here, we used confirmatory factor analysis to: (a) examine level and change associations among latent factors of metabolic risk, regional grey-matter integrity (GMI), and cognition; (b) test whether these associations differ by sex. Analyses were based on a sample of 1,100 healthy adults (52% female) aged 60 to 88 years from the Berlin Aging Study II, and included MRI data for a sub sample of 341 (37 % female) individuals. Metabolic risk was defined by waist circumference, triglycerides, fasting blood glucose, and high-density lipoprotein; regional GMI by mean diffusivity, magnetization ratio transfer ratio, and VBM-based volume estimates; and cognition, represented by the three latent constructs episodic memory, working memory and fluid intelligence. Initial analyses indicate that individuals with lower metabolic risk show greater GMI in prefrontal cortex. Also, we found that greater prefrontal GMI was associated with higher fluid intelligence and working memory in men only. Additionally, we investigated the effects of previous levels of metabolic risk and cognition on subsequent changes in both domains over time. We highlight the benefits of latent factors for establishing brain-behavior relations, and discuss putative physiological substrates of individual differences in GMI.

Objective: To investigate the detection and diagnostic efficacy of chest radiographs for ≤30 mm pulmonary nodules and the factors affecting them, and to compare the level of consistency among readers. Methods: A total of 43 patients with asymptomatic pulmonary nodules who consulted in Cancer Hospital, Chinese Academy of Medical Sciences from 2012 to 2014 and had chest CT and X-ray chest radiographs during the same period were retrospectively selected, and one nodule ≤30 mm was visible on chest CT images in the whole group (total 43 nodules in the whole group). One senior radiologist with more than 20 years of experience in imaging diagnosis reviewed CT images and recording the size, morphology, location, and density of nodules was selected retrospectively. Six radiologists with different levels of experience (2 residents, 2 attending physicians and 2 associate chief physicians independently reviewed the chest images and recorded the time of review, nodule detection, and diagnostic opinion. The CT imaging characteristics of detected and undetected nodules on X images were compared, and the factors affecting the detection of nodules on X-ray images were analyzed. Detection sensitivity and diagnosis accuracy rate of 6 radiologists were calculated, and the level of consistency among them was compared to analyze the influence of radiologists' seniority and reading time on the diagnosis results. Results: The number of nodules detected by all 6 radiologists was 17, with a sensitivity of detection of 39.5%(17/43). The number of nodules detected by ≥5, ≥4, ≥3, ≥2, and ≥1 physicians was 20, 21, 23, 25, and 28 nodules, respectively, with detection sensitivities of 46.5%, 48.8%, 53.5%, 58.1%, and 65.1%, respectively. Reasons for false-negative result of detection on X-ray images included the size, location, density, and morphology of the nodule. The sensitivity of detecting ≤30 mm, ≤20 mm, ≤15 mm, and ≤10 mm nodules was 46.5%-58.1%, 45.9%-54.1%, 36.0%-44.0%, and 36.4% for the 6 radiologists, respectively; the diagnosis accuracy rate was 19.0%-85.0%, 16.7%-6.5%, 18.2%-80.0%, and 0%-75.0%, respectively. The consistency of nodule detection among 6 doctors was good (Kappa value: 0.629-0.907) and the consistency of diagnostic results among them was moderate or poor (Kappa value: 0.350-0.653). The higher the radiologist's seniority, the shorter the time required to read the images. The reading time and the seniority of the radiologists had no significant influence on the detection and diagnosis results (P>0.05). Conclusions: The ability of radiographs to detect lung nodules ≤30 mm is limited, and the ability to determine the nature of the nodules is not sufficient, and the increase in reading time and seniority of the radiologists will not improve the diagnostic accuracy. X-ray film exam alone is not suitable for lung cancer diagnosis.

Recently, there has been an explosive growth in graphical modeling approaches for estimating brain functional networks. In a detailed study, we show that surprisingly, standard graphical modeling approaches for fMRI data may not yield accurate estimates of the brain network due to the inability to suitably account for temporal correlations. We propose a novel Bayesian matrix normal graphical model that jointly models the temporal covariance and the brain network under a separable structure for the covariance to obtain improved estimates. The approach is implemented via an efficient optimization algorithm that computes the maximum-a-posteriori network estimates having desirable theoretical properties and which is scalable to high dimensions. The proposed method leads to substantial gains in network estimation accuracy compared to standard brain network modeling approaches as illustrated via extensive simulations. We apply the method to resting state fMRI data from the Human Connectome Project involving a large number of time scans and brain regions, to study the relationships between fluid intelligence and functional connectivity, where it is not computationally feasible to apply existing matrix normal graphical models. Our proposed approach led to the detection of differences in connectivity between high and low fluid intelligence groups, whereas these differences were less pronounced or absent using the graphicallasso.