Elementary Cognitive Tasks Research Articles

Effect of Immersive Virtual Reality Environment on Reaction Time, Agility and Coordination among Collegiate Students

Background: Virtual reality is the sum of the hardware and software systems that seek to perfect an all-inclusive, sensory illusion of being present in another environment which is applied to a broad range of sports such as skiing, goalkeeping rugby union, baseball and basketball, pistol shooting and cycling speed. Reaction time is the elapsed time between stimulus onset and an individual’s response on elementary cognitive tasks. Coordination is the capability to perform a sequence of movements rhythmically smoothly and accurately. Agility refers to the capacity to quickly change the location of the entire body in space with quickness and accuracyObjectives: The main objective of this study was to see the effect of virtual reality table tennis on coordination, reaction time and agility among collegiate students.Material and Methods: Based on inclusion and exclusion criteria, 60 collegiate students of age group 18-24 years were taken. The subjects were divided into two groups as group A and group B of 30 each. Group A played table tennis game in real environment and group B played table tennis in virtual environment. Pre and post score were taken for coordination, reaction time and agility using hand eye coordination test, plate tapping test and Davies test respectively. The data was collected, compiled and analyzed.Result:Descriptive statistics, paired & unpaired ‘t’ test were used for the intra-group and intergroup comparison.Significant improvements were seen in post scores of coordination, reaction time and agility in both groups at 0.05 level in both real and virtual table tennis groups. However, when both groups were compared, non-significant differences were observed in all the variables.Conclusion:The study concluded that virtual reality table tennis is as effective as real table tennis in improving reaction time, coordination and agility among collegiate students.

The differences between cerebral dominance patterns in the speed and accuracy of information processing among university students

IntroductionThe subject of cerebral dominance has received great attention by researchers; however, there is a paucity of studies that have examined its relationship to information processing. ObjectiveThe current study aims to reveal the differences between the cerebral dominance patterns (left cerebral dominance, right cerebral dominance, integrated parallel cerebral dominance) in the speed and accuracy of information processing. MethodA sample of (182) volunteers university students, (mean age±SD, 19.92±2.76 years; range, 18–24years; 68 male, 114 females). The Human Information processing survey was applied to the participants. Each subject was exposed to two elementary cognitive tasks (Stroop task and Eriksen flanker task). Each task included two experimental conditions: first, the congruent condition that reflects the automatic processing of information; second, the incongruent condition that reflects the controlled processing of information. ResultsThe results of the study revealed that there were no differences between the patterns of cerebral dominance in the speed and accuracy of information processing. ConclusionAlthough the relationship between cerebral dominance and information processing is not significant, we need more studies to examine this relationship in other samples and in other experimental conditions.

General Intelligence: An Analysis of the Saudi Students’ General Mental Ability and Elementary Cognitive Task Performance

Previous studies on human intelligence has revealed that varied factors influence cognitive performance, and some studies have hypothesized the presence of “general intelligence” (g factor) that is responsible for intelligence. However, most studies have been centered on Western cultures. This study thus examines the Saudi students and the g factor hypothesis. A group of Saudi college students participated in a battery of general mental ability tests and elementary cognitive tasks and were assessed for the influence of various factors on cognitive performance. The study results revealed an increase in the average of Saudi students’ intelligence compared to the results of the previous studies, but it did not yield a g factor.

Binding Costs in Processing Efficiency as Determinants of Cognitive Ability.

Performance in elementary cognitive tasks is moderately correlated with fluid intelligence and working memory capacity. These correlations are higher for more complex tasks, presumably due to increased demands on working memory capacity. In accordance with the binding hypothesis, which states that working memory capacity reflects the limit of a person’s ability to establish and maintain temporary bindings (e.g., relations between items or relations between items and their context), we manipulated binding requirements (i.e., 2, 4, and 6 relations) in three choice reaction time paradigms (i.e., two comparison tasks, two change detection tasks, and two substitution tasks) measuring mental speed. Response time distributions of 115 participants were analyzed with the diffusion model. Higher binding requirements resulted in generally reduced efficiency of information processing, as indicated by lower drift rates. Additionally, we fitted bi-factor confirmatory factor analysis to the elementary cognitive tasks to separate basal speed and binding requirements of the employed tasks to quantify their specific contributions to working memory capacity, as measured by Recall−1-Back tasks. A latent factor capturing individual differences in binding was incrementally predictive of working memory capacity, over and above a general factor capturing speed. These results indicate that the relation between reaction time tasks and working memory capacity hinges on the complexity of the reaction time tasks. We conclude that binding requirements and, therefore, demands on working memory capacity offer a satisfactory account of task complexity that accounts for a large portion of individual differences in ability.

Do Non-Decision Times Mediate the Association between Age and Intelligence across Different Content and Process Domains?

In comparison to young adults, middle-aged and old people show lower scores in intelligence tests and slower response times in elementary cognitive tasks. Whether these well-documented findings can both be attributed to a general cognitive slow-down across the life-span has become subject to debate in the last years. The drift diffusion model can disentangle three main process components of binary decisions, namely the speed of information processing, the conservatism of the decision criterion and the non-decision time (i.e., time needed for processes such as encoding and motor response execution). All three components provide possible explanations for the association between response times and age. We present data from a broad study using 18 different response time tasks from three different content domains (figural, numeric, verbal). Our sample included people between 18 to 62 years of age, thus allowing us to study age differences across young-adulthood and mid-adulthood. Older adults generally showed longer non-decision times and more conservative decision criteria. For speed of information processing, we found a more complex pattern that differed between tasks. We estimated mediation models to investigate whether age differences in diffusion model parameters account for the negative relation between age and intelligence, across different intelligence process domains (processing capacity, memory, psychometric speed) and different intelligence content domains (figural, numeric, verbal). In most cases, age differences in intelligence were accounted for by age differences in non-decision time. Content domain-general, but not content domain-specific aspects of non-decision time were related to age. We discuss the implications of these findings on how cognitive decline and age differences in mental speed might be related.

Human personality reflects spatio-temporal and time-frequency EEG structure.

The reliable and objective assessment of intelligence and personality has been a topic of increasing interest of contemporary neuroscience and psychology. It is known that intelligence can be measured by estimating the mental speed or velocity of information processing. This is usually measured as a reaction time during elementary cognitive task processing, while personality is often assessed by means of questionnaires. On the other hand, human personality affects the way a subject accomplishes elementary cognitive tasks and, therefore, some personality features can define intelligence. It is expected that these features, as well as mental abilities in performing cognitive tasks are associated with the brain’s electrical neural activity. Although several studies reported correlation between event-related potentials, mental ability and intelligence, there is a lack of information about time-frequency and spatio-temporal structures of neural activity which characterize this relation. In the present work, we analyzed human electroencephalograms (EEG) recorded during the performance of elementary cognitive tasks using the Schulte test, which is a paper-pencil based instrument for assessing elementary cognitive ability or mental speed. According to particular features found of the EEG structure, we divided the subjects into three groups. For subjects in each group, we applied the Sixteen Personality Factor Questionnaire (16PF) to assess the their personality traits. We demonstrated that each group exhibited a different score on the personality scale, such as warmth, reasoning, emotional stability and dominance. Summing up, we found a link between EEG features, mental abilities and personality traits. The obtained results can be of great interest for testing human personality to create automatized intelligent programs which combine simple tests and EEG measurements for real estimation of human personality traits and mental abilities.

Modeling Mental Speed: Decomposing Response Time Distributions in Elementary Cognitive Tasks and Correlations with Working Memory Capacity and Fluid Intelligence

Previous research has shown an inverse relation between response times in elementary cognitive tasks and intelligence, but findings are inconsistent as to which is the most informative score. We conducted a study (N = 200) using a battery of elementary cognitive tasks, working memory capacity (WMC) paradigms, and a test of fluid intelligence (gf). Frequently used candidate scores and model parameters derived from the response time (RT) distribution were tested. Results confirmed a clear correlation of mean RT with WMC and to a lesser degree with gf. Highly comparable correlations were obtained for alternative location measures with or without extreme value treatment. Moderate correlations were found as well for scores of RT variability, but they were not as strong as for mean RT. Additionally, there was a trend towards higher correlations for slow RT bands, as compared to faster RT bands. Clearer evidence was obtained in an ex-Gaussian decomposition of the response times: the exponential component was selectively related to WMC and gf in easy tasks, while mean response time was additionally predictive in the most complex tasks. The diffusion model parsimoniously accounted for these effects in terms of individual differences in drift rate. Finally, correlations of model parameters as trait-like dispositions were investigated across different tasks, by correlating parameters of the diffusion and the ex-Gaussian model with conventional RT and accuracy scores.

C-38Executive Functioning Elementary Cognitive Tasks: a Concurrent Validity Study

C-38Executive Functioning Elementary Cognitive Tasks: a Concurrent Validity Study

Decomposing speed of information processing in elementary cognitive tasks

Generalised models of positive change following adversity do not fully account for differences in adjustment among populations who experience posttraumatic growth (PTG). The contributions of event intentionality, frequency of the adversity types, age at serious event, spirituality/religiousness, active coping, PTSD symptoms and social support were explored as predictors of PTG across three samples of university students (N = 101; Study 1), survivors of violent crime recruited from support services (N = 71; Study 2) and those working with survivors of adversity (N = 96; Study 3). The results of Study 1 revealed that age at serious event, active coping, PTSD symptoms and social support positively predicted PTG. Within Study 2, spirituality/religiousness, active coping and social support were the significant positive predictors of PTG. Finally in Study 3, spirituality/religiousness, active coping and social support were the significant positive predictors of PTG. Across all studies, event intentionality and frequency of adversity types did not determine PTG. These results indicate that while participants within each of the populations have the ability to experience PTG, different factors predicted whether PTG was observed. The findings offer greater insight into the multifarious nature of adjustment following adversity.

Transitions between Multiband Oscillatory Patterns Characterize Memory-Guided Perceptual Decisions in Prefrontal Circuits.

Neurons in the brain communicate through electrical impulses and coordinate this activity in ensembles that pulsate rhythmically, very much like musical instruments in an orchestra. These rhythms change with "brain state," from sleep to waking, but also signal with different oscillation frequencies rapid changes between sensory and cognitive processing. Here, we studied rhythmic electrical activity in the monkey prefrontal cortex, an area implicated in working memory, decision making, and executive control. Monkeys had to identify and remember a visual motion pattern and compare it to a second pattern. We found orderly transitions between rhythmic activity where the same frequency channels were active in all ongoing prefrontal computations. This supports prefrontal circuit dynamics that transitions rapidly between complex rhythmic patterns during structured cognitive tasks.

Decomposing the relationship between mental speed and mental abilities

It is unclear whether different elementary cognitive tasks (ECTs) are associated with intelligence because these tasks tap the same basic cognitive process (suggesting a single mental speed factor) or different ones (suggesting several mental speed factors), as it is not known which specific cognitive processes are measured in ECTs and because the factor structure of these processes is unknown. To address these questions, 40 participants (50% males) between 18 and 75years drawn from a community sample completed the Hick paradigm, the Sternberg memory scanning paradigm, and the Posner letter matching paradigm while an EEG was recorded. We applied a diffusion model approach to the response-time data, which allows the mathematical decomposition of different cognitive parameters involved in speeded binary decisions. Behavioral and electrophysiological results indicated that ECT conditions varied in different neuro-cognitive components of information processing. Further analyses revealed that all speed and latency variables had substantial loadings on a second-order general factor marked by general intelligence, and that the association between ERP latencies and general intelligence was mediated by reaction times. These results suggest that there is a general neuro-cognitive speed factor across different tasks and different levels of measurement that is associated with general intelligence.

The relationship of choice reaction time variability and intelligence: A meta-analysis

Frequently the relationship of the variability of reaction times (RTSD) on elementary cognitive tasks and psychometric general intelligence (g) has been investigated. A typical finding is that stable reaction times (low RTSDs) on very basic choice reaction tasks are associated with high g. This meta-analysis quantifies the phenomenon by integrating 24 studies of 27 independent samples with a total of 3968 subjects using comparable, Hick-derived paradigms (Hick 0, 1, 2, 3bit; odd-man-out). Special attention was given to the disattenuation of correlations for reliability artefacts. Random effect meta-analysis yielded small to moderate relationships between intelligence and reaction time variability, the pooled Pearson correlation ranging between −.18 (0bit) and −.28 (2bit). The relationship did not, however, prove consistently larger than the one between intelligence and reaction time, in contrast to earlier findings.

Is there a unitary neuro-cognitive basis of mental speed?

There is ample evidence that speed of information processing is related to mental abilities, as more intelligent individuals have shorter reaction times in elementary cognitive tasks (ECTs). The aim of this study is to identify neuro-cognitive processes that might be responsible for this association, and to investigate their factor structure and its relation to general intelligence. 40 participants drawn from a community sample completed a choice reaction time task and two binary decision tasks while an EEG was recorded. A diffusion model approach was applied to the RT data, which decomposes different cognitive processes involved in speeded binary decisions. Behavioral and electrophysiological results indicate that ECT conditions vary in different neuro-cognitive components of information processing. Additionally, factor analysis shows that all mental speed variables have substantial loadings on a second-order general factor marked by intelligence. These results suggest that there is a common neuro-cognitive speed factor associated with general intelligence.

Further evidence for a multifaceted model of mental speed: Factor structure and validity of computerized measures

The purpose of this study was to replicate the structure of mental speed and relations evidenced with fluid intelligence (Gf) found in a number of recent studies. Specifically, a battery of computerized tasks examined whether results with paper-and-pencil assessments held across different test media. Participants (N=186) completed the battery, which incorporated 20 elementary cognitive tasks, 4 broad speediness (Gs) measures, and 5 Gf markers. Competing measurement models were tested. A higher-order model, with a general mental speed factor and 7 task-class specific factors fit the data well. Gs could not be distinguished from general mental speed. Besides the general mental speed factor, two task-class specific factors were moderately related to Gf. These findings strengthen the evidence for a multifacted structure of mental speed, and highlight the importance of specific speed task-classes in accounting for meaningful outcomes.

Effects of processing speed training on cognitive functions and neural systems

Processing speed (PS) is an individual cognitive ability that measures the speed with which individuals execute cognitive tasks, particularly elementary cognitive tasks. PS has been proposed to be a key cognitive component, along with working memory, and is psychologically and clinically important. Various types of speed training affect performance of untrained cognitive measures. In this article, we review studies of PS training or training involving speeded tasks and describe the methodologies along with the psychological and neuroimaging findings related to PS training. There are various types of PS (speed) training tasks. Evidence indicates that PS training can enhance performance on untrained speeded tasks. However, the extent of transfer may vary depending on the methodology. A particular type of speed training seems to affect mental health in older adults. Neuroimaging studies of speed training have shown that the effects of speed training on neural mechanisms may vary depending on the training tasks. Adaptive procedures to modulate the difficulties of training tasks based on a subject's performance by modulating the task speed can be applied to various cognitive tasks, and these procedures can perhaps be used to develop training protocols for enhancing various cognitive functions.

A diffusion model decomposition of the effects of alcohol on perceptual decision making

RationaleEven in elementary cognitive tasks, alcohol consumption results in both cognitive and motor impairments (e.g., Schweizer and Vogel-Sprott, Exp Clin Psychopharmacol 16: 240–250, 2008).ObjectivesThe purpose of this study is to quantify the latent psychological processes that underlie the alcohol-induced decrement in observed performance.MethodsIn a double-blind experiment, we administered three different amounts of alcohol to participants on different days: a placebo dose (0 g/l), a moderate dose (0.5 g/l), and a high dose (1 g/l). Following this, participants performed a “moving dots” perceptual discrimination task. We analyzed the data using the drift diffusion model. Model parameters drift rate, boundary separation, and non-decision time allow a decomposition of the alcohol effect in terms of their respective cognitive components, that is, rate of information processing, response caution, and non-decision processes (e.g., stimulus encoding, motor processes).ResultsWe found that alcohol intoxication causes higher mean RTs and lower response accuracies. The diffusion model decomposition showed that alcohol intoxication caused a decrease in drift rate and an increase in non-decision time.ConclusionsIn a simple perceptual discrimination task, even a moderate dose of alcohol decreased the rate of information processing and negatively affected the non-decision component. However, alcohol consumption left response caution largely intact.

Placing inspection time, reaction time, and perceptual speed in the broader context of cognitive ability: The VPR model in the Lothian Birth Cohort 1936

The idea that information processing speed is related to cognitive ability has a long history. Much evidence has been amassed in its support, with respect to both individual differences in general intelligence and developmental trajectories. Two so-called elementary cognitive tasks, reaction time and inspection time, have been used to compile this evidence, but most studies have used either one or the other. Relations between speed and fluid intelligence have tended to be stronger than those between speed and crystallized intelligence, but studies testing this have confounded verbal abilities with crystallized intelligence and spatial/perceptual abilities with fluid intelligence. Questions have also been raised regarding whether speed contributes directly to general intelligence or to more specific cognitive abilities to which general intelligence also contributes. We used 18 ability and speed measures in the Lothian Birth Cohort 1936, assessed at approximately age 70, to construct alternative versions of the Verbal–Perceptual–Image Rotation (Johnson & Bouchard, 2005a) model of cognitive ability to test different hypotheses regarding these issues. Though differences in the extents to which our models fit the data were relatively small, they suggested that reaction and inspection time tasks were comparable indicators of information processing speed with respect to general intelligence, that verbal and spatial abilities were similarly related to information processing speed, and that spatial, verbal, and perceptual speed abilities were more directly related to information processing speed than was general intelligence. We discuss the theoretical implications of these results.

The Relationship Between the ASVAB and Multitasking in Navy Sailors: A Process-Specific Approach

This study investigated the relationship between ASVAB scores and multitasking performance in Navy Sailors. Sailors performed a “synthetic work” task designed to simulate demands for multitasking common to many different jobs, as well as elementary cognitive tasks designed to measure two mental processes—the ability to update the contents of working memory (memory updating) and the ability to switch flexibly between tasks (task switching). Structural equation modeling revealed that a general factor of ASVAB subtest scores positively predicted multitasking. Furthermore, memory updating partially accounted for this relationship and added incrementally to the prediction of multitasking, above and beyond the ASVAB.

Speed of processing, anticipation, inhibition and working memory in bilinguals

Literature on the so-called bilingual advantage is directed towards the investigation of whether the mastering of two languages fosters cognitive skills in the non-verbal domain. The present study aimed to evaluate whether the bilingual advantage in non-verbal skills could be best defined as domain-general or domain-specific, and, in the latter case, at identifying the basic cognitive skills involved. Bilingual and monolingual participants were divided into two different age groups (children, youths) and were tested on a battery of elementary cognitive tasks which included a choice reaction time task, a go/no-go task, two working memory tasks (numbers and symbols) and an anticipation task. Bilingual and monolingual children did not differ from each other except for the anticipation task, where bilinguals were found to be faster and more accurate than monolinguals. These findings suggest that anticipation, which has received little attention to date, is an important cognitive domain which needs to be evaluated to a greater extent both in bilingual and monolingual participants.

A Phase Transition Model for the Speed-Accuracy Trade-Off in Response Time Experiments

Most models of response time (RT) in elementary cognitive tasks implicitly assume that the speed-accuracy trade-off is continuous: When payoffs or instructions gradually increase the level of speed stress, people are assumed to gradually sacrifice response accuracy in exchange for gradual increases in response speed. This trade-off presumably operates over the entire range from accurate but slow responding to fast but chance-level responding (i.e., guessing). In this article, we challenge the assumption of continuity and propose a phase transition model for RTs and accuracy. Analogous to the fast guess model (Ollman, 1966), our model postulates two modes of processing: a guess mode and a stimulus-controlled mode. From catastrophe theory, we derive two important predictions that allow us to test our model against the fast guess model and against the popular class of sequential sampling models. The first prediction--hysteresis in the transitions between guessing and stimulus-controlled behavior--was confirmed in an experiment that gradually changed the reward for speed versus accuracy. The second prediction--bimodal RT distributions--was confirmed in an experiment that required participants to respond in a way that is intermediate between guessing and accurate responding.