scholarly journals Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2338
Author(s):  
Júlio Medeiros ◽  
Ricardo Couceiro ◽  
Gonçalo Duarte ◽  
João Durães ◽  
João Castelhano ◽  
...  
Keyword(s):  
Software Development ◽  
Cognitive Load ◽  
Mental Effort ◽  
Research Area ◽  
Cognitive State ◽  
Accurate Identification ◽  
Cognitive States ◽  
Code Complexity ◽  
Time Accuracy ◽  
Future Evaluation

An emergent research area in software engineering and software reliability is the use of wearable biosensors to monitor the cognitive state of software developers during software development tasks. The goal is to gather physiologic manifestations that can be linked to error-prone scenarios related to programmers’ cognitive states. In this paper we investigate whether electroencephalography (EEG) can be applied to accurately identify programmers’ cognitive load associated with the comprehension of code with different complexity levels. Therefore, a controlled experiment involving 26 programmers was carried. We found that features related to Theta, Alpha, and Beta brain waves have the highest discriminative power, allowing the identification of code lines and demanding higher mental effort. The EEG results reveal evidence of mental effort saturation as code complexity increases. Conversely, the classic software complexity metrics do not accurately represent the mental effort involved in code comprehension. Finally, EEG is proposed as a reference, in particular, the combination of EEG with eye tracking information allows for an accurate identification of code lines that correspond to peaks of cognitive load, providing a reference to help in the future evaluation of the space and time accuracy of programmers’ cognitive state monitored using wearable devices compatible with software development activities.

scholarly journals Channel Selection and Feature Projection for Cognitive Load Estimation Using Ambulatory EEG

2007 ◽  
Vol 2007 ◽  
pp. 1-12 ◽  
Author(s):  
Tian Lan ◽  
Deniz Erdogmus ◽  
Andre Adami ◽  
Santosh Mathan ◽  
Misha Pavel
Keyword(s):  
Mutual Information ◽  
Cognitive Load ◽  
Channel Selection ◽  
Estimation Accuracy ◽  
Cognitive State ◽  
Load Estimation ◽  
Mental Load ◽  
Cognitive States ◽  
State Classification ◽  
Feature Projection

We present an ambulatory cognitive state classification system to assess the subject's mental load based on EEG measurements. The ambulatory cognitive state estimator is utilized in the context of a real-time augmented cognition (AugCog) system that aims to enhance the cognitive performance of a human user through computer-mediated assistance based on assessments of cognitive states using physiological signals including, but not limited to, EEG. This paper focuses particularly on the offline channel selection and feature projection phases of the design and aims to present mutual-information-based techniques that use a simple sample estimator for this quantity. Analyses conducted on data collected from 3 subjects performing 2 tasks (n-back/Larson) at 2 difficulty levels (low/high) demonstrate that the proposed mutual-information-based dimensionality reduction scheme can achieve up to 94% cognitive load estimation accuracy.

scholarly journals Eyewitness identification performance is not affected by time-of-day optimality

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sergii Yaremenko ◽  
Melanie Sauerland ◽  
Lorraine Hope
Keyword(s):  
Eyewitness Identification ◽  
Time Of Day ◽  
Decision Time ◽  
Identification Accuracy ◽  
Optimal Time ◽  
Identification Performance ◽  
Accurate Identification ◽  
Facial Stimuli ◽  
Time Accuracy ◽  
Accuracy Relationship

AbstractThe circadian rhythm regulates arousal levels throughout the day and determines optimal periods for engaging in mental activities. Individuals differ in the time of day at which they reach their peak: Morning-type individuals are at their best in the morning and evening types perform better in the evening. Performance in recall and recognition of non-facial stimuli is generally superior at an individual’s circadian peak. In two studies (Ns = 103 and 324), we tested the effect of time-of-testing optimality on eyewitness identification performance. Morning- and evening-type participants viewed stimulus films depicting staged crimes and made identification decisions from target-present and target-absent lineups either at their optimal or non-optimal time-of-day. We expected that participants would make more accurate identification decisions and that the confidence-accuracy and decision time-accuracy relationships would be stronger at optimal compared to non-optimal time of day. In Experiment 1, identification accuracy was unexpectedly superior at non-optimal compared to optimal time of day in target-present lineups. In Experiment 2, identification accuracy did not differ between the optimal and non-optimal time of day. Contrary to our expectations, confidence-accuracy relationship was generally stronger at non-optimal compared to optimal time of day. In line with our predictions, non-optimal testing eliminated decision-time-accuracy relationship in Experiment 1.

Context-specific abnormalities of the central executive network in first-episode psychosis: relationship with cognition

2020 ◽  
pp. 1-10
Author(s):  
Deepak K. Sarpal ◽  
Goda Tarcijonas ◽  
Finnegan J. Calabro ◽  
William Foran ◽  
Gretchen L. Haas ◽  
...  
Keyword(s):  
Cognitive Control ◽  
Psychotic Disorders ◽  
First Episode Psychosis ◽  
First Episode ◽  
Cognitive State ◽  
Cognitive States ◽  
Episode Psychosis ◽  
Dorsolateral Prefrontal ◽  
Parietal Lobule ◽  
Context Specific

Abstract Background Cognitive impairments, which contribute to the profound functional deficits observed in psychotic disorders, have found to be associated with abnormalities in trial-level cognitive control. However, neural tasks operate within the context of sustained cognitive states, which can be assessed with ‘background connectivity’ following the removal of task effects. To date, little is known about the integrity of brain processes supporting the maintenance of a cognitive state in individuals with psychotic disorders. Thus, here we examine background connectivity during executive processing in a cohort of participants with first-episode psychosis (FEP). Methods The following fMRI study examined background connectivity of the dorsolateral prefrontal cortex (DLPFC), during working memory engagement in a group of 43 patients with FEP, relative to 35 healthy controls (HC). Findings were also examined in relation to measures of executive function. Results The FEP group relative to HC showed significantly lower background DLPFC connectivity with bilateral superior parietal lobule (SPL) and left inferior parietal lobule. Background connectivity between DLPFC and SPL was also positively associated with overall cognition across all subjects and in our FEP group. In comparison, resting-state frontoparietal connectivity did not differ between groups and was not significantly associated with overall cognition, suggesting that psychosis-related alterations in executive networks only emerged during states of goal-oriented behavior. Conclusions These results provide novel evidence indicating while frontoparietal connectivity at rest appears intact in psychosis, when engaged during a cognitive state, it is impaired possibly undermining cognitive control capacities in FEP.

Annotated Translation of Udayana's Aatmatattvaviveka

2021 ◽  
Vol 26 ◽  
pp. 155-164
Author(s):  
Kisor Kumar Chakrabarti ◽  
Keyword(s):  
Cognitive State ◽  
Perceptual Awareness ◽  
Cognitive States ◽  
Fig Tree ◽  
Annotated Translation

One approaching a thing from a distance may perceive it as existent, then as a substance, then as a tree and, finally, as a fig tree. Thus, the same fig tree can be the object of all these different perceptions. This shows, Udayana argues, that difference in cognitive states does not necessarily prove that their objects are different. This argument is in response to the Buddhist claim that since perceptual cognitive states and non-perceptual cognitive states are different, their respective objects are also different; unique particulars (svalakSaNa) that alone are real, are grasped in perception; general features (saamaanyalakSaNa) that are not real are grasped in non-perceptual cognitive states. The Buddhist objects: when the same thing appears to be the object of different cognitive states, only that cognitive state which leads to useful result is reliable. Udayana replies: More than one cognitive state in the above situation may lead to useful result; it is not justified to accept only one of them as reliable and reject the others. The Buddhist objects again: perceptual awareness is direct but non-perceptual awareness is indirect: hence their objects are different. Udayana replies: The same thing may be perceived when there is sensory connection with it and then inferred from an invariably connected sign when there is no sensory connection. Thus, the same thing may be the object of both direct and indirect cognitive states depending on different causal conditions.

scholarly journals Taxing the brain to uncover lying? Meta-analyzing the effect of imposing cognitive load on the reaction-time costs of lying

2018 ◽  
Author(s):  
Bruno Verschuere ◽  
Nils Köbis ◽  
yoella meyer ◽  
David Gertler Rand ◽  
Shaul Shalvi
Keyword(s):  
Reaction Time ◽  
Response Time ◽  
Cognitive Load ◽  
Lie Detection ◽  
Mental Effort ◽  
Cognitive Resources ◽  
Truth Telling ◽  
Total N ◽  
The Difference ◽  
The Brain

Lying typically requires greater mental effort than telling the truth. Imposing cognitive load may improve lie detection by limiting the cognitive resources needed to lie effectively, thereby increasing the difference in speed between truths and lies. We test this hypothesis meta-analytically. Across 21 studies using response-time (RT) paradigms (11 unpublished; total N = 792), we consistently found that truth telling was faster than lying, but found no evidence that imposing cognitive load increased that difference (Control, d = 1.45; Load, d = 1.28). Instead, load significantly decreased the lie-truth RT difference by increasing the RT of truths, g = -.18, p = .027. Our findings therefore suggest that imposing cognitive load does not necessarily improve RT-based lie detection, and may actually worsen it by taxing the mental system and thus impeding people’s ability to easily—and thus quickly—tell the truth

scholarly journals Changing what you see by changing what you know: the role of attention

2017 ◽  
Author(s):  
Gary Lupyan
Keyword(s):  
Perceptual Content ◽  
Current Evidence ◽  
Cognitive State ◽  
Perceptual Process ◽  
Cognitive Influences ◽  
Cognitive States ◽  
Visual Hierarchy ◽  
Visual Inputs ◽  
Perceptual Representations ◽  
Perceptual Systems

Attending is a cognitive process that incorporates a person’s knowledge, goals, and expectations. What we perceive when we attend to one thing is different from what we perceive when we attend to something else. Yet, it is often argued that attentional effects do not count as evidence that perception is influenced by cognition. I investigate two arguments often given to justify excluding attention. The first is arguing that attention is a post-perceptual process reflecting selection between fully constructed perceptual representations. The second is arguing that attention as a pre-perceptual process that simply changes the input to encapsulated perceptual systems. Both of these arguments are highly problematic. Although some attentional effects can indeed be construed as post-perceptual, others operate by changing perceptual content across the entire visual hierarchy. Although there is a natural analogy between spatial attention and a change of input, the analogy falls apart when we consider other forms of attention. After dispelling these arguments, I make a case for thinking of attention not as a confound, but as one of the mechanisms by which cognitive states affect perception by going through cases in which the same or similar visual inputs are perceived differently depending on the observer’s cognitive state, and instances where cuing an observer using language affects what one sees. Lastly, I provide two compelling counter-examples to the critique that although cognitive influences on perception can be demonstrated in the laboratory, it is impossible to really experience them for oneself in a phenomenologically compelling way. Taken together, the current evidence strongly supports the thesis that what we know routinely influences what we see, that the same sensory input can be perceived differently depending on the current cognitive state of the viewer, and that phenomenologically salient demonstrations are possible if certain conditions are met.

This Is Your Brain on Autopilot: Neural Indices of Driver Workload and Engagement During Partial Vehicle Automation

2021 ◽  
pp. 001872082110390
Author(s):  
Amy S. McDonnell ◽  
Trent G. Simmons ◽  
Gus G. Erickson ◽  
Monika Lohani ◽  
Joel M. Cooper ◽  
...  
Keyword(s):  
Mental Workload ◽  
Cognitive State ◽  
Alpha Power ◽  
Age Cohorts ◽  
Cognitive States ◽  
Driver Workload ◽  
Automated Technology ◽  
Vehicle Automation ◽  
Visual Engagement ◽  
Insight Into

Objective This research explores the effect of partial vehicle automation on neural indices of mental workload and visual engagement during on-road driving. Background There is concern that the introduction of automated technology in vehicles may lead to low driver stimulation and subsequent disengagement from the driving environment. Simulator-based studies have examined the effect of automation on a driver’s cognitive state, but it is unknown how the conclusions translate to on-road driving. Electroencephalographic (EEG) measures of frontal theta and parietal alpha can provide insight into a driver’s mental workload and visual engagement while driving under various conditions. Method EEG was recorded from 71 participants while driving on the roadway. We examined two age cohorts, on two different highway configurations, in four different vehicles, with partial vehicle automation both engaged and disengaged. Results Analysis of frontal theta and parietal alpha power revealed that there was no change in mental workload or visual engagement when driving manually compared with driving under partial vehicle automation. Conclusion Drivers new to the technology remained engaged with the driving environment when operating under partial vehicle automation. These findings suggest that the concern surrounding driver disengagement under vehicle automation may need to be tempered, at least for drivers new to the experience. Application These findings expand our understanding of the effects of partial vehicle automation on drivers’ cognitive states.

An Integrated Evaluation Approach for E-Learning Systems in Career and Technical Education

2009 ◽  
pp. 396-407 ◽  
Author(s):  
Wenhao David Huang ◽  
Steven R. Aragon
Keyword(s):  
Cognitive Load ◽  
Learning Process ◽  
Integrated Approach ◽  
Learning Systems ◽  
Evaluation Framework ◽  
Evaluation Data ◽  
Career And Technical ◽  
Evaluation Approach ◽  
E Learning ◽  
Future Evaluation

As E-learning is gaining popularity in higher education, its evaluation becomes more critical than ever, to ensure the achievement of intended learning outcome. The effectiveness of E-learning system evaluation under current practices, however, remains questionable. One reason for such uncertainty is the lack of direct measurement while learning occurs since most evaluation data is collected after the learning process. Thus this chapter proposes an integrated evaluation approach for E-learning systems based on Cognitive Load Theory and grounded in the 4C/ID-model. Both direct and indirect measurements will be deployed in the integrated approach in the context of cognitive load. Furthermore all evaluation data can be translated into practical E-learning design solutions by triangulating with the 4C/ID-model. This chapter also suggests that future evaluation framework on E-learning should include factors from attitudinal and social aspects of learning process.

Complex Mobile Learning that Adapts to Learners' Cognitive Load

2016 ◽  
pp. 1850-1862
Author(s):  
Robin Deegan
Keyword(s):  
Mobile Computing ◽  
Cognitive Load ◽  
Mobile Devices ◽  
Mobile Learning ◽  
Cognitive Load Theory ◽  
Learning Task ◽  
Cognitive State ◽  
Load Theory ◽  
Load Types

Mobile learning is cognitively demanding and frequently the ubiquitous nature of mobile computing means that mobile devices are used in cognitively demanding environments. This paper examines the use of mobile devices from a Learning, Usability and Cognitive Load Theory perspective. It suggests scenarios where these fields interact and presents an experiment which determined that several sources of cognitive load can be measured simultaneously by the learner. The experiment also looked at the interaction between these cognitive load types and found that distraction did not affect the performance or cognitive load associated with a learning task but it did affect the perception of the cognitive load associated with using the application interface. This paper concludes by suggesting ways in which mobile learning can benefit by developing cognitive load aware systems that could detect and change the difficulty of the learning task based on the cognitive state of the learner.

Sign in / Sign up

Export Citation Format

Share Document