Higher-level Cognitive Activities Research Articles

Cognitive Neural Computation Modeling of Human Brain Information Storage and Extraction Based on Intelligent Computing

With the development of neurological and brain science, human beings have more understanding of the memory mechanism of the brain. Therefore, using the memory mechanism of the brain to store and retrieve images is one of the most popular research fields in the world. Memory is an important part of the human cognitive system, and it is the basis for the realization of higher-level cognitive activities. Human perception and memory are closely related. If people lose the ability to perceive, then people’s memory function will not be able to display. The current storage and extraction of brain information are mostly based on mathematical principles, without considering the memory mechanism in the brain, so the correctness and effectiveness of these methods are not high. Therefore, this study adopts an intelligent algorithm based on PCNN to denoise, segment, identify, and retrieve images. On this basis, a new learning method is adopted. This method can realize online incremental learning and can realize the storage of brain image data without predetermining the size and structure of the network. And when necessary, the information is extracted or not based on the distance between the detected versus the stored data. The test shows that when the number of images is 25, the present technique has an accuracy of 100% and the time required is 2345 s. Compared with the median filtering method, the efficiency of the present technique is greater.

A Commentary on Towards autonomous artificial agents with an active self: Modeling sense of control in situated action

Kahl et al., (2022) present a computational model of an autonomous agent implemented with an active self. With ideas based on the Free Energy Principle (Friston and Kiebel, 2009), their model tackles the challenge to unify higher-level cognitive activities and lower-level sensorimotor control as the autonomous agent maintains situational awareness while interacting with the environment. While Kahl et al., (2022) focus on modeling a single agent, we argue that this challenge similarly appears in modeling human–robot interaction (HRI). In this commentary, we discuss how the conceptual framework from Kahl et al., (2022) could inspire unified models of physical and cognitive HRI and how the modeling approach from Kahl et al., (2022) can potentially be applied to anticipatory thinking in robotics to support the human in daily life.

3D animation modelling using After Effect in biogeochemical cycle study to develop cognitive activities

The biogeochemical cycle is material that uses diagrams and is difficult to understand. Cognitive activity has a contribution in building understanding when studying a diagram. The purpose of this study was to obtain information about 3D animation modelling using after effect in biogeochemical cycle to develop cognitive activities. This research is a descriptive study. The model in this study is the biogeochemical cycle animation model using adobe after effect. Cognitive activity is measured before and during the study using a modelling example. All verbal data that appears is recorded and analysed according to think-aloud protocols (TAPs) which will then be translated and categorized into types of cognitive activity. The results of this study indicate that before using the modelling example the activity of activating the initial knowledge (K11) included in the high category. There was a development when study using modelling examples, namely elaboration (K41) most appeared with a high category. This study can be concluded that the 3D animation modelling using after effect can develop high-level cognitive activities, namely inference accurately (K31) and elaboration accurately (K41) in the biogeochemical cycle.

Over-expressed MST1 impaired spatial memory via disturbing neural oscillation patterns in mice.

The activated mammalian Ste20-like serine/threonine kinases 1 (MST1) was found in the central nervous system diseases, such as cerebral ischemia, stroke and ALS, which were related with cognitions. The aim of this study was to examine the effect of elevated MST1 on memory functions in C57BL/6J mice. We also explored the underlying mechanism about the pattern alteration of neural oscillations, closely associated with cognitive dysfunctions, at different physiological rhythms, which were related to a wide range of basic and higher-level cognitive activities. A mouse model of the adeno-associated virus (AAV)-mediated overexpression of MST1 was established. The behavioral experiments showed that spatial memory was significantly damaged in MST1 mice. The distribution of either theta or gamma power was clearly disturbed in MST1 animals. Moreover, the synchronization in both theta and gamma rhythms, and theta-gamma cross-frequency coupling were significantly weakened in MST1 mice. In addition, the expressions of GABAA receptor, GAD67 and parvalbumin (PV) were obviously increased in MST1 mice. Meanwhile, blocking MST1 activity could inhibit the activation of FOXO3a and YAP. The above data suggest that MST1-overexpression may induce memory impairments via disturbing the patterns of neural activities, which is possibly associated with the abnormal GABAergic expression level.

The effect of linguistic comprehension instruction on generalized language and reading comprehension skills: A systematic review.

The effect of linguistic comprehension instruction on generalized language and reading comprehension skills: A systematic review.

An EEG-Based Study on Perception of Video Distortion Under Various Content Motion Conditions

Human perception sensitivity to video distortion is vital for visual quality assessment (VQA). Different from the perception mechanism of image distortion that has been thoroughly studied, the perception of video distortion is inevitably influenced by motion of dynamic content due to the characteristics of the human visual system (HVS). In this paper, electroencephalography (EEG) is used as a novel psychophysiological method to study the human perception sensitivity to quantification-aroused video distortion under various content motion conditions. For this purpose, we conduct experiments to record the EEG signals of the subjects when they are watching distorted videos. According to the feature analysis of EEG data, the P300 component aroused by human perception of video quality change is selected as the indicator of human perception of distortion. By the means of classification based on linear discriminant analysis (LDA), it is found that the separability of the P300 component, which is measured by the area under curve (AUC) of the receiver operating characteristic (ROC), is positively correlated with the perceptibility of distortion. The correlation provides a valid psychophysiological method, which is exempt from being influenced by subjective bias due to human high-level cognitive activities, for evaluating distortion perceptibility. In addition, the regression analysis results demonstrate a sigmoid-typed quantitative relation between the perceptibility of distortion and separability of the P300 component. Based on such relation, the perceptibility thresholds of distortion corresponding to various content motion speeds are calibrated by EEG signals and it is found that the content motion speed has a significant impact on distortion perceptibility.

Productive Disciplinary Engagement in High- and Low-Outcome Student Groups: Observations From Three Collaborative Science Learning Contexts

This study explored how productive disciplinary engagement (PDE) is associated with the level of cognitive activity and collective group outcome in collaborative learning across multiple contexts. Traditionally, PDE has been studied in a single collaborative learning environment, without analysis of how these environments fulfill the supporting conditions for PDE. In addition, research on the quality of a collective learning outcome and product in relation to the extent of the group’s PDE during actual collaborative learning processes is scarce. In this study, the learning processes of low- and high-outcome small groups were compared within three collaborative learning contexts: high school general science, second year university veterinary science, and fourth year university engineering. Two meaningful and self-contained phases from each context were selected for analysis. The same theory-based analytical methods were used across contexts. The findings revealed similar patterns in the high school science and second year university veterinary science data sets, where high-outcome groups displayed a greater proportion of high-level cognitive activity while working on the task. Thus, they could be distinctively perceived as high- and low-performing groups. These high-performing groups’ interactions also reflected more of the supporting conditions associated with PDE than the low-performing groups. An opposite pattern was found in the fourth year university engineering data set, calling for interpretation grounded in the literature on the nature and development of expertise. This study reveals the criticality of using comparable analytical methods across different contexts to enable discrepancies to emerge, thus refining our contextualized understanding of PDE in collaborative science learning.

ANALYSIS OF THE SCIENCE LEARNING OBJECTS OF THE GREEK DIGITAL LEARNING OBJECT REPOSITORY FROM A LEARNING ACTIVITIES PERSPECTIVE

In recent years, learning objects have been playing a crucial role in the teaching process. However, research focused on the analysis of science learning objects is particularly limited. The present study aims to analyze the science learning objects of the Greek Digital Learning Object Repository that are intended for primary school from a learning activities perspective. A total of 178 learning objects were analyzed. The analysis of learning objects from the perspective of the learning activities (cognitive and metacognitive) they activate in the students was carried out in line with the analysis framework of Overman, Vermunt, Meijer, Bulte and Brekelmans (2013). The analysis of learning objects showed that they are dominated by low level cognitive learning activities, while the learning objects that activate high level cognitive learning activities are limited. Finally, no learning objects activating metacognitive learning activities in the students were detected.

The Research on Influences of Emotion on Sports Decision Making

The sport decision making was a high-level cognitive activity. The emotional factors had effect on the decision making on some extent besides the cognitive factors. This study analyzed the process of sport decision making and the appearance and development of emotion based on the decision making and emotion in sports, then it discussed the influencing mechanisms and results.

Getting the Joke: Insight during Humor Comprehension - Evidence from an fMRI Study.

As a high-level cognitive activity, humor comprehension requires incongruity detection and incongruity resolution, which then elicits an insight moment. The purpose of the study was to explore the neural basis of humor comprehension, particularly the moment of insight, by using both characters and language-free cartoons in a functional magnetic resonance imaging study. The results showed that insight involving jokes elicited greater activation in language and semantic-related brain regions as well as a variety of additional regions, such as the superior frontal gyrus (SFG), the inferior frontal gyrus (IFG), the middle temporal gyrus (MTG), the superior temporal gyrus (STG), the temporoparietal junctions (TPJ), the hippocampus and visual areas. These findings indicate that the MTG might play a role in incongruity detection, while the SFG, IFG and the TPJ might be involved in incongruity detection. The passive insight event elicited by jokes appears to be mediated by a limited number of brain areas. Our study showed that the brain regions associated with humor comprehension were not affected by the type of stimuli and that humor and insight shared common brain areas. These results indicate that one experiences a feeling of insight during humor comprehension, which contributes to the understanding of humor comprehension.

Applying the Flipped Classroom Methodology in a First-Year Undergraduate Music Research Methods Course

ABSTRACTOnline learning environments and teaching tools are becoming increasingly present on University campuses and continue to impact the way information literacy instruction is delivered. The flipped classroom is a methodology that allows students to access lecture content before class as homework, leaving room during class time for higher level cognitive activities and assessments. This article discusses a program review of a first-year undergraduate music library research methods course. A pre- and posttest survey was administered to collect students’ perceptions of the methodology as well as information literacy skill development.

Resting-state networks distinguish locked-in from vegetative state patients.

PurposeLocked-in syndrome and vegetative state are distinct outcomes from coma. Despite their differences, they are clinically difficult to distinguish at the early stage and current diagnostic tools remain insufficient. Since some brain functions are preserved in locked-in syndrome, we postulated that networks of spontaneously co-activated brain areas might be present in locked-in patients, similar to healthy controls, but not in patients in a vegetative state.MethodsFive patients with locked-in syndrome, 12 patients in a vegetative state and 19 healthy controls underwent a resting-state fMRI scan. Individual spatial independent component analysis was used to separate spontaneous brain co-activations from noise. These co-activity maps were selected and then classified by two raters as either one of eight resting-state networks commonly shared across subjects or as specific to a subject.ResultsThe numbers of spontaneous co-activity maps, total resting-state networks, and resting-state networks underlying high-level cognitive activity were shown to differentiate controls and locked-in patients from patients in a vegetative state. Analyses of each common resting-state network revealed that the default mode network accurately distinguished locked-in from vegetative-state patients. The frontoparietal network also had maximum specificity but more limited sensitivity.ConclusionsThis study reinforces previous reports on the preservation of the default mode network in locked-in syndrome in contrast to vegetative state but extends them by suggesting that other networks might be relevant to the diagnosis of locked-in syndrome. The aforementioned analysis of fMRI brain activity at rest might be a step in the development of a diagnostic biomarker to distinguish locked-in syndrome from vegetative state.

Multilayer cognitive architecture for UAV control

Extensive use of unmanned aerial vehicles (UAVs) in recent years has induced the rapid growth of research areas related to UAV production. Among these, the design of control systems capable of automating a wide range of UAV activities is one of the most actively explored and evolving. Currently, researchers and developers are interested in designing control systems that can be referred to as intelligent, e.g. the systems which are suited to solve such tasks as planning, goal prioritization, coalition formation, etc. and thus guarantee high levels of UAV autonomy. One of the principal problems in intelligent control system design is tying together various methods and models traditionally used in robotics and aimed at solving such tasks as dynamics modeling, control signal generation, location and mapping, path planning, etc. with the methods of behavior modeling and planning which are thoroughly studied in cognitive science. Our work is aimed at solving this problem. We propose layered architecture—STRL (strategic, tactical, reactive, layered)—of the control system that automates the behavior generation using a cognitive approach while taking into account complex dynamics and kinematics of the control object (UAV). We use a special type of knowledge representation—sign world model—that is based on the psychological activity theory to describe individual behavior planning and coalition formation processes. We also propose path planning methodology which serves as the mediator between the high-level cognitive activities and the reactive control signals generation. To generate these signals we use a state-dependent Riccati equation and specific method for solving it. We believe that utilization of the proposed architecture will broaden the spectrum of tasks which can be solved by the UAV’s coalition automatically, as well as raise the autonomy level of each individual member of that coalition.

Investigating Variations in Gameplay: Cognitive Implications

There is increasing interest in creating computer games for learning, problem solving, and other high-level cognitive activities. When investigating whether gameplay is conducive to such activities, gameplay is often studied as a whole. As a result, cognitive implications can be linked to the game but not to its structural elements. Given that gameplay arises from interaction between the player and the game, it is the structural components of interaction that should be investigated to better understand the design of gameplay. Furthermore, minor variations in the components of interaction can have significant cognitive implications. However, such variation has not been studied yet. Thus, to gain a better understanding of how we can study the effect of interaction on the cognitive aspect of gameplay, we conducted an exploratory investigation of two computer games. These games were isomorphic at a deep level and only had one minor difference in the structure of their interaction. Volunteers played these games and discussed the cognitive processes that emerged. In one game, they primarily engaged in planning, but in the other game they primarily engaged in visualizing. This paper discusses the results of our investigation as well as its implications for the design of computer games.

Memory for serial order across domains: An overview of the literature and directions for future research.

From vocabulary learning to imitating sequences of motor actions, the ability to plan, represent, and recall a novel sequence of items in the correct order is fundamental for many verbal and nonverbal higher level cognitive activities. Here we review phenomena of serial order documented across the verbal, visual, and spatial short-term memory domains and interpret them with reference to the principles of serial order and ancillary assumptions instantiated in contemporary computational theories of memory for serial order. We propose that functional similarities across domains buttress the notion that verbal, visual, and spatial sequences are planned and controlled by a competitive queuing (CQ) mechanism in which items are simultaneously active in parallel and the strongest item is chosen for output. Within the verbal short-term memory CQ system, evidence suggests that serial order is represented via a primacy gradient, position marking, response suppression, and cumulative matching. Evidence further indicates that output interference operates during recall and that item similarity effects manifest during both serial order encoding and retrieval. By contrast, the principles underlying the representation of serial order in the visual and spatial CQ systems are unclear, largely because the relevant studies have yet to be performed. In the spatial domain, there is some evidence for a primacy gradient and position marking, whereas in the visual domain there is no direct evidence for either of the principles of serial order. We conclude by proposing some directions for future research designed to bridge this and other theoretical gaps in the literature.

Improved Working Memory Performance through Self-Regulation of Dorsal Lateral Prefrontal Cortex Activation Using Real-Time fMRI

Working memory is important for a wide range of high-level cognitive activities. Previous studies have shown that the dorsal lateral prefrontal cortex (DLPFC) plays a critical role in working memory and that behavioral training of working memory can alter the activity of DLPFC. However, it is unclear whether the activation in the DLPFC can be self-regulated and whether any self-regulation can affect working memory behavior. The recently emerged real-time functional magnetic resonance imaging (rtfMRI) technique enables the individuals to acquire self-control of localized brain activation, potentially inducing desirable behavioral changes. In the present study, we employed the rtfMRI technique to train subjects to up-regulate the activation in the left DLPFC, which is linked to verbal working memory. After two rtfMRI training sessions, activation in the left DLPFC was significantly increased, whereas the control group that received sham feedback did not show any increase in DLPFC activation. Pre- and post-training behavioral tests indicated that performance of the digit span and letter memory task was significantly improved in the experimental group. Between-group comparison of behavioral changes showed that the increase of digit span in the experimental group was significantly greater than that in the control group. These findings provide preliminary evidence that working memory performance can be improved through learned regulation of activation in associated brain regions using rtfMRI.

A Computational Aid for Problem Formulation in Early Conceptual Design

Conceptual design is a high-level cognitive activity that draws upon distinctive human mental abilities. An early and fundamental part of the design process is problem formulation, in which designers determine the structure of the problem space they will later search. Although many tools have been developed to aid the later stages of design, few tools exist that aid designers in the early stages. In this paper, we describe Problem Formulator, an interactive environment that focuses on this stage of the design process. This tool has representations and operations that let designers create, visualize, explore, and reflect on their formulations. Although this process remains entirely under the user's control, these capabilities make the system well positioned to aid the early stages of conceptual design.

Supporting cognitive processing with spatial information presentations in virtual environments

While it has been suggested that immersive virtual environments could provide benefits for educational applications, few studies have formally evaluated how the enhanced perceptual displays of such systems might improve learning. Using simplified memorization and problem-solving tasks as representative approximations of more advanced types of learning, we are investigating the effects of providing supplemental spatial information on the performance of learning-based activities within virtual environments. We performed two experiments to investigate whether users can take advantage of a spatial information presentation to improve performance on cognitive processing activities. In both experiments, information was presented either directly in front of the participant, at a single location, or wrapped around the participant along the walls of a surround display. In our first experiment, we measured memory scores and analyzed participant strategies for a memorization and recall task. In addition to comparing spatial and non-spatial presentations, we also varied field of view and background imagery. The results showed that the spatial presentation caused significantly better memory scores. Additionally, a significant interaction between background landmarks and presentation style showed that participants used more visualization strategies during the memorization task when background landmarks were shown with spatial presentations. To investigate whether the advantages of spatial information presentation extend beyond memorization to higher level cognitive activities, our second experiment employed a puzzle-like task that required critical thinking using the presented information. Focusing only on the effects of spatial presentations, this experiment measured task performance and mental workload. The results indicate that no performance improvements or mental workload reductions were gained from the spatial presentation method compared with a non-spatial layout for our problem-solving task. The results of these two experiments suggest that supplemental spatial information can affect mental strategies and support performance improvements for cognitive processing and learning-based activities. However, the effectiveness of spatial presentations is dependent on the nature of the task and a meaningful use of space and may require practice with spatial strategies.

Deduction without awareness

We investigated whether two basic forms of deductive inference, Modus Ponens and Disjunctive Syllogism, occur automatically and without awareness. In Experiment 1, we used a priming paradigm with a set of conditional and disjunctive problems. For each trial, two premises were shown. The second premise was presented at a rate designed to be undetectable. After each problem, participants had to evaluate whether a newly-presented target number was odd or even. The target number matched or did not match a conclusion endorsed by the two previous premises. We found that when the target matched the conclusion of a Modus Ponens inference, the evaluation of the target number was reliably faster than baseline even when participants reported that they were not aware of the second premise. This priming effect did not occur for any other valid or invalid inference that we tested, including the Disjunctive Syllogism. In Experiment 2, we used a forced-choice paradigm in which we found that some participants were able to access some information on the second premise when their attention was explicitly directed to it. In Experiment 3, we showed that the priming effect for Modus Ponens was present also in subjects who could not access any information about P 2. In Experiment 4 we explored whether spatial relations (e.g., “ a before b”) or sentences with quantifiers (e.g., “all a with b”) could generate a priming effect similar to the one observed for Modus Ponens. A priming effect could be found for Modus Ponens only, but not for the other relations tested. These findings show that the Modus Ponens inference, in contrast to other deductive inferences, can be carried out automatically and unconsciously. Furthermore, our findings suggest that critical deductive inference schemata can be included in the range of high-level cognitive activities that are carried out unconsciously.

N400 amplitude reduction correlates with an increase in pupil size.

Pupil dilation is classically associated with increase in cognitive load in humans. Here, we studied the potential link between human pupil dilation and meaning integration effort as indexed by event-related brain potentials (ERPs). We recorded pupil size variation and ERPs simultaneously while participants were presented with matching or unrelated picture–word pairs. Whilst relatedness in meaning between spoken words and pictures typically modulated ERPs, pupil size was also affected quickly after picture onset. Moreover, during the time-window associated with meaning integration, greater pupil dilation correlated with less negative N400 amplitudes elicited by unrelated pictures. Since pupil dilation has been linked to activity of the locus coeruleus–norepinephrine (LC–NE) system, these findings may provide new insights into the suggested link between human high-level cognitive function and activity of the LC–NE system.