Modulation of resource allocation by intelligent individuals in linguistic, mathematical and visuo-spatial tasks

Evaluation of physiological responses to mental workload in n-back and arithmetic tasks

Working memory tasks, such as n-back and arithmetic tasks, are frequently used in studying mental workload. The present study investigated and compared the sensitivity of several physiological measures at three levels of difficulty of n-back and arithmetic tasks. The results showed significant differences in fixation duration and pupil diameter among three task difficulty levels for both n-back and arithmetic tasks. Pupil diameters increase with increasing mental workload, whereas fixation duration decreases. Blink duration and heart rate (HR) were significantly increased as task difficulty increased in the n-back task, while root mean square of successive differences (RMSSD) and standard deviation of R-R intervals (SDNN) were significantly decreased in the arithmetic task. On the other hand, blink rate and Galvanic Skin Response (GSR) were not sensitive enough to assess the differences in task difficulty for both tasks. All significant physiological measures yielded significant differences between low and high task difficulty except for SDNN.Practitioner summary: This study aimed to assess the sensitivity levels of several physiological measures of mental workload in n-back and arithmetic tasks. It showed that pupil diameter was the most sensitive in both tasks. This study also found that most physiological indices are sensitive to an extreme change in task difficulty levels.

Does mathematics anxiety moderate the effect of problem difficulty on cognitive effort?

A negative relationship between mathematics anxiety (MA) and mathematics performance is well documented. One suggested explanation for this relationship is that MA interferes with the cognitive processes needed when solving mathematics problems. A demand for using more cognitive effort (e.g., when performing harder mathematics problems), can be traced as an increase in pupil dilation during the performance. However, we lack knowledge of how MA affects this relationship between the problem difficulty and cognitive effort. This study investigated, for the first time, if MA moderates the effect of arithmetic (i.e., multiplication) problem difficulty on cognitive effort. Thirty-four university students from Norway completed multiplication tasks, including three difficulty levels of problems, while their cognitive effort was also measured by means of pupil dilation using an eye tracker. Further, the participants reported their MA using a questionnaire, and arithmetic competence, general intelligence, and working memory were measured with paper-pencil tasks. A linear mixed model analysis showed that the difficulty level of the multiplication problems affected the cognitive effort so that the pupil dilated more with harder multiplication problems. However, we did not find a moderating effect of MA on cognitive effort, when controlling for arithmetic competence, general intelligence, and working memory. This suggests that MA does not contribute to cognitive effort when solving multiplication problems.

High fluid intelligence is characterized by flexible allocation of attentional resources: Evidence from EEG

Recently, the integrated control hypothesis (Lu et al., 2020) was proposed to explain the relationship between fluid intelligence (Gf) and attentional resource allocation. This hypothesis suggested that individuals with higher Gf tend to flexibly and adaptively allocate their limited resources according to the task type and task difficulty rather than simply exert more or fewer resources in any condition. To examine this hypothesis, the present study used electroencephalogram (EEG) indicators (i.e., frontal theta-ERS and parietal-occipital alpha-ERD) as the measurements of participants' resource allocation during the exploration task and exploitation task with different difficulties. The results found that higher Gf individuals tend to allocate fewer resources in all difficulty levels in the exploitation task compared to average Gf participants. In contrast, in the exploration task, higher Gf participants would allocate more resources in the medium- and high-difficulty levels than average Gf participants, but this phenomenon was only found in males. These findings provided supportive evidence for the integrated control hypothesis that flexible and adaptive attentional control ability are important characteristics of human intelligence.

A Brief Period of Wakeful Rest after Learning Enhances Verbal Memory in Stroke Survivors

OBJECTIVE

Accumulating evidence suggests that wakeful rest (a period of minimal cognitive stimulation) enhances memory in clinical populations with memory impairment. However, no study has previously examined the efficacy of this technique in stroke survivors, despite the high prevalence of post-stroke memory difficulties. We aimed to investigate whether wakeful rest enhances verbal memory in stroke survivors and healthy controls.

METHOD

Twenty-four stroke survivors and 24 healthy controls were presented with two short stories; one story was followed by a 10-minute period of wakeful rest and the other was followed by a 10-minute visual interference task. A mixed factorial analysis of variance (ANOVA) with pairwise comparisons was used to compare participants' story retention at two time points.

RESULTS

After 15-30 minutes, stroke survivors (p = .002, d = .73), and healthy controls (p = .001, d = .76) retained more information from the story followed by wakeful rest, compared with the story followed by an interference task. While wakeful rest remained the superior condition in healthy controls after 7 days (p = .01, d = .58), the beneficial effect was not maintained in stroke survivors (p = .35, d = .19).

CONCLUSIONS

Wakeful rest is a promising technique, which significantly enhanced verbal memory after 15-30 minutes in both groups; however, no significant benefit of wakeful rest was observed after 7 days in stroke survivors. Preliminary findings suggest that wakeful rest enhances early memory consolidation processes by protecting against the effects of interference after learning in stroke survivors.

Pupillary light reflex as a diagnostic aid from computational viewpoint: A systematic literature review

This work presents a detailed and complete review of publications on pupillary light reflex (PLR) used to aid diagnoses. These are computational techniques used in the evaluation of pupillometry, as well as their application in computer-aided diagnoses (CAD) of pathologies or physiological conditions that can be studied by observing the movements of miosis and mydriasis of the human pupil. A careful survey was carried out of all studies published over the last 10 years which investigated, electronic devices, recording protocols, image treatment, computational algorithms and the pathologies related to PLR. We present the frontier of existing knowledge regarding methods and techniques used in this field of knowledge, which has been expanding due to the possibility of performing diagnoses with high precision, at a low cost and with a non-invasive method.

Tonic pupil size and its variability are associated with fluid intelligence in adolescents aged 11-14 years

Tonic pupil size and its variability are sensitive to cognitive abilities (such as fluid intelligence [Gf]) among individuals. The present study aimed to examine this relationship in a new sample set (i.e., adolescents aged 11-14 years) with several important factors considered. We conducted two task-free tasks (the blank-screen viewing task and the scene viewing task) to measure tonic pupil size and its variability in 11-14-year-old adolescents with different Gf levels and preliminarily tested the role of task type and stimuli's luminance on this relationship. The results found that high-Gf adolescents showed smaller tonic pupil size in both tasks but showed larger variability of tonic pupil size in the blank-screen viewing task. Task type and stimuli's luminance could influence tonic pupil size and its variability in different ways. Cognitive and underlying neural mechanisms of these results are discussed to provide an explanation and suggestions for future studies.

Preprocessing pupil size data: Guidelines and code

Pupillometry has been one of the most widely used response systems in psychophysiology. Changes in pupil size can reflect diverse cognitive and emotional states, ranging from arousal, interest and effort to social decisions, but they are also widely used in clinical practice to assess patients’ brain functioning. As a result, research involving pupil size measurements has been reported in practically all psychology, psychiatry, and psychophysiological research journals, and now it has found its way into the primatology literature as well as into more practical applications, such as using pupil size as a measure of fatigue or a safety index during driving. The different systems used for recording pupil size are almost as variable as its applications, and all yield, as with many measurement techniques, a substantial amount of noise in addition to the real pupillometry data. Before analyzing pupil size, it is therefore of crucial importance first to detect this noise and deal with it appropriately, even prior to (if need be) resampling and baseline-correcting the data. In this article we first provide a short review of the literature on pupil size measurements, then we highlight the most important sources of noise and show how these can be detected. Finally, we provide step-by-step guidelines that will help those interested in pupil size to preprocess their data correctly. These guidelines are accompanied by an open source MATLAB script (available at https://github.com/ElioS-S/pupil-size). Given that pupil diameter is easily measured by standard eyetracking technologies and can provide fundamental insights into cognitive and emotional processes, it is hoped that this article will further motivate scholars from different disciplines to study pupil size.