The relationship between baseline pupil size and intelligence

The underlying cognitive mechanisms explaining why speakers sometimes make communication errors are not well understood. Some scholars have theorized that audience design engages automatic processes when a listener is present; others argue that it relies on effortful resources, even if a listener is present. We hypothesized that working memory is engaged during communicative audience design and that the extent to which working memory is engaged relies on individual differences in cognitive abilities and concurrent amount of resources available. In Experiment 1, participants completed a referential task under high, low, or no cognitive load with a present listener whose perspective differed from the speaker’s. Speakers made few referential errors under no and low load, but errors increased when cognitive load was highest. In Experiment 2, the listener was absent. Speakers made few referential errors under no and low load, but errors increased when cognitive load was highest, suggesting that audience design is still effortful under high cognitive load, both when the listener was present and when the listener was absent. Experiment 3 tested whether cognitive abilities predicted communication performance. Participants with higher fluid intelligence and working memory capacity made fewer communication errors. Our findings suggest that communication relies on available cognitive resources, and therefore errors occur as a function of factors like cognitive load and individual differences.

Cognition, the process by which animals acquire, process, store and use information from their environment, plays a major role in various behaviours across all aspects of an individuals’ life. However, despite this overall importance of cognitive abilities, we still know little about how cognitive traits evolved. In the past, research on cognitive evolution focussed on comparing different species in their cognitive abilities and linked variation in cognition to inter-specific differences in ecological and social conditions. This comparative approach helps to understand when in evolutionary history and under which conditions particular cognitive abilities evolved. Individual variation in cognitive abilities has been widely ignored in these studies on the species level, however. This changed only recently when the interest in how and why individuals differ in cognitive traits emerged. Only by investigating inter-individual variation in cognitive abilities and their link with fitness outcomes, we can begin to understand the causes and consequences of this variation and finally unravel how cognition evolved. Because fitness can only be studied in wild, free-ranging individuals, the study of individual differences in cognitive abilities and their fitness consequences is challenging and has been conducted mainly in different species of birds until today. The few studies so far focused largely on single measures of cognition and fitness and revealed not only positive but also negative and not significant correlations between cognitive performance and fitness outcomes. With my thesis, I contribute to this young field of research aiming to better understand the adaptive value of cognitive traits. I investigated cognitive abilities in five cognitive tasks in wild grey mouse lemurs (Microcebus murinus), a primate species endemic to Madagascar, and linked cognitive performance with different fitness proxies. The cognitive tasks addressed different ecologically relevant cognitive abilities. They included associative and motor learning during repeated problem solving, causal reasoning and spontaneous problem solving in a string-pulling task, spatial learning, inhibitory control and behavioural flexibility during reversal learning. Subjects were tested during short-term captivity of up to three nights and subsequently released back into the wild. Furthermore, individuals were tested in two personality tests and their neophilia and activity during a novel object and an open field test was assessed. In the first part of my thesis, I focused on inter- and intra-individual differences of cognitive performance: the potential confounding effects of non-cognitive factors on cognitive performance and the structure of cognitive performance across different cognitive abilities. My results demonstrated that, first of all, subjects differed greatly in cognitive performance and performance was not systematically affected by non-cognitive factors such as personality, body condition, motivation, age or sex. Furthermore, performance in one cognitive task was generally a weak predictor of performance in any other tasks of the test battery and could not be summarized into a general factor. Thus, I could not find evidence for a general factor of cognitive performance similar to the general intelligence factor (g) in humans, where performance is positively correlated across cognitive tasks and domains. In the second part of the thesis, I studied different fitness-related traits in grey mouse lemurs and linked cognitive performance with two fitness proxies. I found that efficient repeated solving of a food extraction task correlated positively with the ability to maintain body condition during the long dry season with low food availability. This suggests that the ability to quickly apply a newly discovered motor technique during problem solving also facilitates the exploitation of new, natural food resources when food is scarce. By contrast, cognitive performance, irrespective of cognitive task, did not correlate with survival or longevity, suggesting that the assessed cognitive abilities did not provide (net) benefits in survival. Moreover, difficulties in validating a physiological condition factor, that summarized measures of body condition, hematocrit and long-term cortisol levels, demonstrated that identifying and operationalizing meaningful fitness proxies can be challenging for many taxa. In summary, my thesis contributes the first study on a wild primate to the growing body of research investigating individual differences in cognitive abilities and their link with fitness outcomes. Together with the other recent findings revealing heterogenous links between cognitive performance and fitness measures, my thesis demonstrates that cognitive abilities are involved in complex interactions between various traits. At the same time, they are likely to have costs and benefits, and thus do not necessarily correlate positively with fitness outcomes. Further studies in different species in the wild, that investigate multiple cognitive traits and fitness outcomes as well as potentially confounding covariates simultaneously, will help to unravel this complex system, the evolution of cognition.

Individuals scoring higher in tests of general cognitive abilities tend to perform better on novel and familiar mathematical tasks. It has been scarcely investigated how this superior mathematical performance relates to the amount of cognitive resources that is invested to solve a given task. In this study we propose that, on novel tasks, individuals with high cognitive abilities outperform less able individuals, because they allocate a higher amount of resources. On familiar tasks, however, individuals with higher abilities profit from more efficient processes compared to individuals of lower cognitive abilities. We tested this hypothesis by administering to 11th graders a geometric analogy task not practiced at school and an algebraic transformation task comprising operations that are routinely required during mathematical courses. General cognitive abilities were measured with Ravens Advanced Progressive matrices (fluid intelligence), the d2 (focused attention) and KAI-N (working memory capacity). Resource allocation was measured by assessing pupil diameter during the problem-solving process. Performance on both the analogy and the algebra task was correlated with general cognitive abilities, especially fluid intelligence. In line with our assumptions, a positive correlation between fluid intelligence and resource allocation was observed in the novel geometric analogy task, whereas the correlation was not significant in the more familiar algebra task.

Although the existing literature has explored the link between cognitive functioning and speech recognition in noise, the specific role of fluid intelligence still needs to be studied. Given the established association between working memory capacity (WMC) and fluid intelligence and the predictive power of WMC for speech recognition in noise, we aimed to elucidate the mediating role of fluid intelligence. We used data from the n200 study, a longitudinal investigation into aging, hearing ability, and cognitive functioning. We analyzed two age-matched samples: participants with hearing aids and a group with normal hearing. WMC was assessed using the Reading Span task, and fluid intelligence was measured with Raven's Progressive Matrices. Speech recognition in noise was evaluated using Hagerman sentences presented to target 80% speech-reception thresholds in four-talker babble. Data were analyzed using mediation analysis to examine fluid intelligence as a mediator between WMC and speech recognition in noise. We found a partial mediating effect of fluid intelligence on the relationship between WMC and speech recognition in noise, and that hearing status did not moderate this effect. In other words, WMC and fluid intelligence were related, and fluid intelligence partially explained the influence of WMC on speech recognition in noise. This study shows the importance of fluid intelligence in speech recognition in noise, regardless of hearing status. Future research should use other advanced statistical techniques and explore various speech recognition tests and background maskers to deepen our understanding of the interplay between WMC and fluid intelligence in speech recognition.

The relationship among baseline pupil size, fixation stability, and inhibitory control were examined in this study. Participants performed a baseline eye measure in which they were instructed to stare at a fixation dot on screen for 2 min. Following the baseline eye measure, participants completed an antisaccade task to measure inhibitory control ability. We found a correlation between baseline pupil size variability and inhibitory control, as well as between fixation stability and inhibitory control. We showed that participants with better inhibitory control exhibited larger variability in pupil size, and those with better fixation stability showed superior inhibitory control ability. Overall, our results indicate that there are significant correlations between inhibitory control and baseline pupil size, as well as between inhibitory control and fixation stability.

It is well established that pupil activity indexes cognitive processing. For instance, research has consistently demonstrated that the pupil reacts to working memory span task performance. However, little is known about pupil reaction to cognitive processing in Alzheimer's Disease (AD). We thus investigated whether span tasks can modulate pupil size in patients with AD. We invited 24 patients with AD and 24 healthy older adults to perform backward and forward spans, as well as to count aloud in a control condition, while their pupil activity was recorded with eye tracking glasses. In patients with AD, analysis demonstrated larger pupil size during backward spans (M = 2.12, SD = .39) than during forward spans (M = 1.98, SD = .36) [t(23) = 3.22, p = .004], larger pupil size during forward spans than during counting (M = 1.67, SD = .33) [t(23) = 4.75, p < .001], as well as larger pupil size during backward spans than during counting [t(23) = 10.60, p < .001]. In control participants, analysis demonstrated larger pupil size during backward spans (M = 3.36, SD = .49) than during forward spans (M = 2.85, SD = .68) [t(23) = 5.82, p < .001], larger pupil size during forward spans than during counting (M = 2.09, SD = .62) [t(23) = 5.42, < .001], as well as larger pupil size during backward spans than during counting [t(23) = 9.70, p < .001]. Results also demonstrated a significant interaction effect between groups and conditions [F(2,92) = 16.63, p < .001]; in other words, patients with AD have shown fewer variations on the pupil size across the conditions compared to the control participants. The larger pupil size during backward spans, compared with forward spans or counting, can be attributed to the high cognitive load of backward spans. The modulation of pupil size, as observed across backward/forward spans and counting, can possibly be attributed to sympathetic/adrenergic and parasympathetic/cholinergic activities. Our study demonstrates the value of pupillometry as a potential biomarker of cognitive processing in AD.

Attentional effort relates to the allocation of limited-capacity attentional resources to meet current task demands and involves the activation of top-down attentional systems in the brain. Pupillometry is a sensitive measure of this intensity aspect of top-down attentional control. Studies relate pupillary changes in response to cognitive processing to activity in the locus coeruleus (LC), which is the main hub of the brain's noradrenergic system and it is thought to modulate the operations of the brain's attentional systems. In the present study, participants performed a visual divided attention task known as multiple object tracking (MOT) while their pupil sizes were recorded by use of an infrared eye tracker and then were tested again with the same paradigm while brain activity was recorded using fMRI. We hypothesized that the individual pupil dilations, as an index of individual differences in mental effort, as originally proposed by Kahneman (1973), would be a better predictor of LC activity than the number of tracked objects during MOT. The current results support our hypothesis, since we observed pupil-related activity in the LC. Moreover, the changes in the pupil correlated with activity in the superior colliculus and the right thalamus, as well as cortical activity in the dorsal attention network, which previous studies have shown to be strongly activated during visual tracking of multiple targets. Follow-up pupillometric analyses of the MOT task in the same individuals also revealed that individual differences to cognitive load can be remarkably stable over a lag of several years. To our knowledge this is the first study using pupil dilations as an index of attentional effort in the MOT task and also relating these to functional changes in the brain that directly implicate the LC-NE system in the allocation of processing resources.

Introduction: Surgeons’ cognitive workload should be controlled during a surgical intervention for a successful and safe performance. Eye tracking technologies could be used for cognitive workload monitoring by analyzing the pupil size and blink frequency of surgeons. This work aims to study the surgeons’ cognitive workload watching an advanced laparoscopic video. Methods: 16 surgeons (5 experts, 11 novices) participated in the study watching a colectomy video consisting of eight steps with introductory titles. Surgeons’ gaze was recorded with eye tracking glasses while visualizing the video, from which pupil size and blink frequency were analyzed. Results: Pupil diameter of surgeons increased during the visualization of steps and decreased during the titles. Two specific steps of the intervention produced the highest pupil diameter of surgeons. When the pupil diameter increased the blink frequency decreased. Pupil diameter tended to decrease as the video is watched, which is mainly due to expert surgeons, who had a lower pupil diameter than novices. Conclusions: Eye tracking technologies allow monitoring the cognitive workload of surgeons in surgical procedures. Larger pupil size and shorter blink frequency means greater cognitive workload. Such metrics could be used to objectively label the difficult tasks within the surgical procedure. Surgical videos used for training of surgeons should be short, according to micro-learning, since cognitive workload decreases over time while visualizing them. Based on proposed metrics, eye tracking technologies could be used to distinguish the level of experience of surgeons, since cognitive workload is sensitive to the skill level of surgeons.

Differential and experimental approaches to studying intelligence in humans and non-human animals

High throughput analyses in reproductive biology research: gene profiling and sensor properties of the endometrium

Driving in monotonous road environments may cause drivers to become bored and impair their alertness. This inattention may increase the risk of road accidents. Drivers usually respond to visual signals on the road. A large body of research has shown that the level of a driver’s visual attention is closely related to traffic accidents. Visual attention is often studied by tracking drivers’ eye movements. However, few studies to date have explored eye-movement patterns in different road environments such as open roads and tunnel expressways. This dissertation aims to address that research gap by studying drivers’ eye movements and visual characteristics in different driving conditions in real and simulated environments. In the pilot study, drivers’ eye movement patterns were recorded during high-speed driving in tunnels and on expressways in Singapore. Twenty-two drivers participated in the study; they drove a total of 55 km, which included a 9-km section of tunnel. The results of the study showed that drivers experienced longer fixation duration when driving in tunnels than on the open road but experienced a higher number of fixations, higher instantaneous velocity, acceleration, and dispersion on open roads than in tunnels. These findings suggest that drivers’ eye movements are more concentrated and have longer fixation durations in tunnels than in open road driving, indicating that drivers have a greater mental workload when driving in tunnels. However, testing drivers in a real environment has limitations. For example, weather and road characteristics cannot be manipulated. To address this limitation, Experiment 1 was conducted in a driving simulator using virtual reality simulations in UC-win/road. Experiment 1 sought to investigate drivers’ eye movements in various driving environments. Eighteen drivers participated in the experiment and drove on normal roads, expressways, and through underground tunnels in both sunny and rainy weather. The comparisons of their eye-movement patterns (e.g., saccadic parameters and pupil size) in the simulated environments were consistent with those in real open-road environments and tunnels in sunny conditions. The findings suggest that the eye-movement patterns of drivers in a simulator are comparable to those in real environments, indicating its ecological validity. Previous literature has suggested a relationship between eye movement patterns and mental workload. To verify that relationship, mental workloads in Experiments 2 and 3 were directly measured using questionnaires. Dynamic and static hazardous scenarios were simulated to induce different levels of mental workload. Experiment 2 investigated eye movements, driving performance, and mental workload of drivers who encountered static and dynamic obstacles while manual driving. The results from 23 drivers found that their mental workload in dynamic conditions was higher than in static hazardous conditions; it was also higher before encountering hazards than afterwards. The results indicated that pupil size and saccade numbers are effective indicators of mental workload. Experiment 3 was conducted under conditionally automated driving conditions, where participants were involved in tasks related to or not related to driving and requested to resume control manually when their vehicle was in semi-automated driving mode. Drivers’ eye movements and mental workloads were measured when they were driving, especially during the transitions from semi-automated to manual driving. Similar to Experiment 2, the results from 32 drivers found that mental workload was higher for dynamic hazards than for static hazards and higher before hazards were encountered than after. The results also indicated that pupil size is the only effective indicator of mental workload. Taken together, the results of these experiments reveal that pupil size is the most reliable way to measure drivers’ mental workload. Furthermore, in line with the load theory of attention and De Waard (1996)’s theory of workload and performance, it can be concluded that mental workload (indicated by pupil size) and visual workload (by saccadic dispersion) are the key determinants of driving performance and that drivers can only respond to emergencies during periods of medium levels of mental and visual workload (not underload or overload) with available attentional capacity. The findings from this thesis on eye movement and mental workload may be used to monitor drivers’ real-time attention and workload and thus provide guidance for the design of safe-driving autonomous vehicles that consider drivers’ capacity for information processing when driving. Knowledge about the limitations and capacity of human drivers in tandem with automated systems may also help improve user acceptance of autonomous vehicles in the future.

Working memory capacity consistently correlates with fluid intelligence. It has been suggested that this relationship is partly attributable to strategy use: Participants with high working memory capacity would use more effective strategies, in turn leading to higher performance on fluid intelligence tasks. However, this idea has never been directly investigated. In 2 experiments, we tested this hypothesis by directly manipulating strategy use in a combined experimental-correlational approach (Experiment 1; N = 250) and by measuring strategy use with a self-report questionnaire (Experiment 2; N = 93). Inducing all participants to use an effective strategy in Raven's matrices decreased the correlation between working memory capacity and performance; the strategy use measure fully mediated the relationship between working memory capacity and performance on the matrices task. These findings indicate that individual differences in strategic behavior drive the predictive utility of working memory. We interpret the results within a theoretical framework integrating the multiple mediators of the relationship between working memory capacity and high-level cognition.

Wonderlic, working memory capacity, and fluid intelligence

It is well established that measures of reasoning ability and of working memory capacity (WMC) correlate positively. However, the question of what explains this relationship remains open. The purpose of this study was to investigate the capacity hypothesis, which ascribes causality to WMC. This hypothesis holds that people high in WMC are more successful in capacity-demanding cognitive tasks than people lower in WMC because they can temporarily maintain more information in the form of sub-goals, hypotheses, and partial solutions. Accordingly, this hypothesis predicts that the correlation between WMC and reasoning performance should increase as the capacity demands of the reasoning items increase. We tested this prediction using items from Raven's Progressive Matrices and two measures of WMC, complex span and the k estimate from the Visual Arrays task. Neither WMC measure showed the effect predicted by the capacity hypothesis. Furthermore, the results cannot be attributed to restriction of range in performance on the individual reasoning items. This finding adds to existing evidence calling into question the capacity hypothesis, and, more generally, the view that WMC has a causal influence on fluid intelligence.

The capacity to deliberately control attention in order to hold and manipulate information in working memory is critical to higher cognitive functions. This suggests that between-subject differences in general cognitive ability might be related to observable differences in the activity of brain systems that support working memory and attention control. To test this notion, electroencephalograms were recorded from 80 healthy young adults during spatial working memory tasks. Measures of task-related neurophysiological and behavioral variables were derived from these data and compared to scores on a test battery commonly used to assess general cognitive ability (the WAIS-R). Subjects who scored high on the psychometric test also tended to respond faster in the experimental tasks without any loss of accuracy. The amplitude of the late positive component of the event-related potential was larger in high-ability subjects, and the frontal midline theta component of the EEG signal was also selectively enhanced in this group under conditions of sustained performance and high working memory load. These results suggest that subjects who scored high on the WAIS-R were better able to focus and sustain attention to task performance. Changes in the EEG alpha rhythm in response to manipulations of task practice and load were also examined and compared between frontal and parietal regions. The results indicated that high-ability subjects developed strategies that made relatively greater use of parietal regions, whereas low-ability subjects relied more exclusively on frontal regions. Other analyses indicated that hemispheric asymmetries in alpha band measures distinguish between individuals with relatively high verbal aptitude and those with relatively high nonverbal aptitude. In particular, subjects with a verbal cognitive style tended to make greater use of the left parietal region during task performance, and subjects with a nonverbal style tended to make greater use of the right parietal region. These results help clarify relationships between task-related brain activity and individual differences in cognitive ability and style.