Cognitive Tasks Research Articles

Understanding the Psychosis Spectrum Using a Hierarchical Model of Social Cognition.

Social cognitive impairments are central to psychosis, including lower severity psychosis-like experiences (PLEs). Nonetheless, progress has been hindered by social cognition's poorly defined factor structure, as well as limited work examining the specificity of social cognitive impairment to psychosis. The present study examined how PLEs relate to social cognition in the context of other psychopathology dimensions, using a hierarchical factors approach to social cognition. Online community participants (N = 1026) completed psychosis, autism, and personality disorder questionnaires, as well as 3 social cognitive tasks that varied in methodology (vignette vs video) and construct (higher- vs lower-level social cognition). Exploratory (EFA) and confirmatory factor analyses (CFA) were used to model social cognition, with the best models being examined in association with PLEs and psychopathology dimensions. EFA and CFA supported a hierarchical model of social cognition, with 2 higher-order factors emerging: verbal/vignette task methodology and a multimethod general social cognition factor. These higher-order factors accounted for task-level associations to psychopathology, with relations to positive symptoms (r = .23) and antagonism (r = .28). After controlling for other psychopathology, positive symptoms were most clearly related to tasks with verbal methodology (β = -0.34). These results suggest that broad social cognitive processes and method effects may account for many previous findings in psychosis and psychopathology research. Additionally, accounting for broad social cognitive impairment may yield insights into more specific social cognitive processes as well.

Absence of BOLD adaptation in chronic fatigue syndrome revealed by task functional MRI.

Neurological symptoms are central to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), yet its underlying neurophysiological mechanisms remain elusive. We examined a neglected aspect of task-based functional MRI, focusing on how blood oxygenation level-dependent (BOLD) signals alter during cognitive tasks in ME/CFS. This prospective observational study utilised MRI scans on ME/CFS participants and healthy controls (HCs) with sedentary lifestyles (ACTRN12622001095752). Participants completed two blocks of a Symbol Digit Modalities Test, with 30 trials per block split into two sets. The fMRI signal changes between blocks and sets were compared within and between groups. Thirty-four ME/CFS participants (38 years ± 10; 27 women) and 34 HCs (38 ± 10; 27 women), were evaluated. In the second task block, ME/CFS participants exhibited increased activation in the right postcentral gyrus, contrasting with decreased activation in multiple regions in HCs. These results were further confirmed by significantly higher bilateral dynamic changes (2nd vs 1st set) in the motor, sensory and cognitive cortex in ME/CFS compared to HCs and significant correlations between those changes in the left primary motor cortex with fatigue severities. BOLD adaptation, potentially improving energy economy, was absent in ME/CFS, which may provide an underlying neurophysiological process in ME/CFS.

Interspecies-chimera machine vision with polarimetry for real-time navigation and anti-glare pattern recognition

Cutting-edge humanoid machine vision merely mimics human systems and lacks polarimetric functionalities that convey the information of navigation and authentic images. Interspecies-chimera vision reserving multiple hosts’ capacities will lead to advanced machine vision. However, implementing the visual functions of multiple species (human and non-human) in one optoelectronic device is still elusive. Here, we develop an optically-controlled polarimetry memtransistor based on a van der Waals heterostructure (ReS2/GeSe2). The device provides polarization sensitivity, nonvolatility, and positive/negative photoconductance simultaneously. The polarimetric measurement can identify celestial polarizations for real-time navigation like a honeybee. Meanwhile, cognitive tasks can be completed like a human by sensing, memory, and synaptic functions. Particularly, the anti-glare recognition with polarimetry saves an order of magnitude energy compared to the traditional humanoid counterpart. This technique promotes the concept of interspecies-chimera visual systems that will leverage the advances of autonomous vehicles, medical diagnoses, intelligent robotics, etc.

Implicit learning provides advantage over explicit learning for gait-cognitive dual-task interference

Dual-task performance holds significant relevance in real-world scenarios. Implicit learning is a possible approach for improving dual-task performance. Analogy learning, utilizing a single metaphor to convey essential information about motor skills, has emerged as a practical method for fostering implicit learning. However, evidence supporting the effect of implicit learning on gait-cognitive dual-task performance is insufficient. This exploratory study aimed to examine the effects of implicit and explicit learning on dual-task performance in both gait and cognitive tasks. Tandem gait was employed on a treadmill to assess motor function, whereas serial seven subtraction tasks were used to gauge cognitive performance. Thirty healthy community-dwelling older individuals were randomly assigned to implicit or explicit learning groups. Each group learned the tandem gait task according to their individual learning styles. The implicit learning group showed a significant improvement in gait performance under the dual-task condition compared with the explicit learning group. Furthermore, the implicit learning group exhibited improved dual-task interference for both tasks. Our findings suggest that implicit learning may offer greater advantages than explicit learning in acquiring autonomous motor skills. Future research is needed to uncover the mechanisms underlying implicit learning and to harness its potential for gait-cognitive dual-task performance in clinical settings.

Self-interest and preferences for the regulation of artificial intelligence

ABSTRACT Workers have often advocated for regulation to protect themselves from labor market threats. Artificial intelligence (AI) is expected to transform many jobs in the coming years, especially those of white collar professionals. Yet we know little about the attitudes these and other workers hold or may develop toward the regulation of such technology. We argue that both self-interested and sociotropic concerns likely shape AI regulatory attitudes, and examine these arguments using a survey experiment exposing individuals to information about how technology will affect the work of people engaged in either routine, repetitive tasks or white collar, cognitive tasks. We anticipate that compared to a placebo group, individuals exposed to news about the impact of technology on jobs will favor regulation, and even more strongly when it is their own job type highlighted in the treatment. We find only modest responsiveness to the treatments on average, but observe that individuals with more knowledge of technology are strongly responsive to the AI treatments in the hypothesized manner.

Presentation of multiple task instructional sets impacts auditory Stroop performance during dual task locomotion.

The auditory Stroop is a modification of the classic Stroop paradigm commonly used in dual-task research when the motor task requires the visual system. Despite its use, there are gaps in our understanding of this tool. For example, in visual/auditory Stroop paradigms, neutral cues irrelevant to the required response, which theoretically cause less interference/facilitation, are used to elucidate effects of visual/auditory demands on neural processes. Specifically, in auditory Stroop paradigms the use and choice of neutral cue words is inconsistent. To address these gaps, we instrumented participants with kinematic markers and a digital microphone and asked them to respond to auditory Stroop cues and neutral cue words consisting of either one or two syllables, while simultaneously performing an unobstructed locomotor task. Two blocks of trials were collected. In one block, participants had prior knowledge that either an auditory Stroop or a neutral word stimulus would be presented (Known); a second block presented both types of cognitive cues in a random order to participants (Mixed). We observed main effects of cognitive task (neutral, incongruent, congruent) and instructional set (Known, Mixed) on response times, but not on center of mass velocity. Also, more time was required to verbally respond to an incongruent compared to congruent or neutral task across all conditions, and neutral task words with one syllable resulted in longer response times compared to two syllable neutral words. We recommend that researchers include neutral cues when using the auditory Stroop test and to carefully consider their neutral word choice.

Big data analytics-artificial intelligence and supply chain ambidexterity impacts on corporate image and green communication

PurposeThe theoretical background bases on the big data analytics-artificial intelligence (BDA-AI) technologies and supply chain ambidexterity (SCAX) in the firms to assess their sustainability endeavors such as green supply chain management (GSCM) to improve their green communication and corporate image.Design/methodology/approachAround 220 participants in the manufacturing firms are participants' industry expertise, diverse roles, and representation as key stakeholders.FindingsThe results show BDA-AI and SCAX affected on GSCM and found the significant relationships with green communication and corporate image. Green communication was discovered to impact corporate image significantly.Originality/valuePrior studies are neglected to address the relationship among the AI, powered by rapid computational and BDA breakthroughs, redefines cognitive tasks, achieving feats previously deemed impossible-making implicit judgments, simulating emotions, and driving operations. This study selects manufacturing firms as respondents due to their forefront of BDA-AI and supply chain ambidexterity adoption to benefit the operational efficiency and competitiveness. The firms intricate supply chains, diverse stakeholders, and strategic emphasis on corporate image make it an ideal context to examine the nuanced impact of these technologies.

Exploring cognitive load through neuropsychological features: an analysis using fNIRS-eye tracking.

Cognition is crucial to brain function, and accurately classifying cognitive load is essential for understanding the psychological processes across tasks. This paper innovatively combines functional near-infrared spectroscopy (fNIRS) with eye tracking technology to delve into the classification of cognitive load at the neurocognitive level. This integration overcomes the limitations of a single modality, addressing challenges such as feature selection, high dimensionality, and insufficient sample capacity. We employ fNIRS-eye tracking technology to collect neural activity and eye tracking data during various cognitive tasks, followed by preprocessing. Using the maximum relevance minimum redundancy algorithm, we extract the most relevant features and evaluate their impact on the classification task. We evaluate the classification performance by building models (naive Bayes, support vector machine, K-nearest neighbors, and random forest) and employing cross-validation. The results demonstrate the effectiveness of fNIRS-eye tracking, the maximum relevance minimum redundancy algorithm, and machine learning techniques in discriminating cognitive load levels. This study emphasizes the impact of the number of features on performance, highlighting the need for an optimal feature set to improve accuracy. These findings advance our understanding of neuroscientific features related to cognitive load, propelling neural psychology research to deeper levels and holding significant implications for future cognitive science.

Investigating and improving student understanding of the basics of quantum computing

Quantum information science and engineering (QISE) is a rapidly developing field that leverages the skills of experts from many disciplines to utilize the potential of quantum systems in a variety of applications. It requires talent from a wide variety of traditional fields, including physics, engineering, chemistry, and computer science, to name a few. To prepare students for such opportunities, it is important to give them a strong foundation in the basics of QISE, in which quantum computing plays a central role. In this study, we discuss the development, validation, and evaluation of a Quantum Interactive Learning Tutorial, on the basics and applications of quantum computing. These include an overview of key quantum mechanical concepts relevant to quantum computation (including ways a quantum computer is different from a classical computer), properties of single- and multiqubit systems, and the basics of single-qubit quantum gates. The tutorial uses guided inquiry-based teaching-learning sequences. Its development and validation involved conducting cognitive task analysis from both expert and student perspectives and using common student difficulties as a guide. For example, before engaging with the tutorial, after traditional lecture-based instruction, one reasoning primitive that was common in student responses is that a major difference between an N-bit classical and N-qubit quantum computer is that various things associated with a number N for a classical computer should be replaced with the number 2N for a quantum computer (e.g., 2N qubits must be initialized and 2N bits of information are obtained as the output of the computation on the quantum computer). This type of reasoning primitive also led many students to incorrectly think that there are only N distinctly different states available when computation takes place on a classical computer. Research suggests that this type of reasoning primitive has its origins in students learning that quantum computers can provide exponential advantage for certain problems, e.g., Shor’s algorithm for factoring products of large prime numbers, and that the quantum state during the computation can be in a superposition of 2N linearly independent states. The inquiry-based learning sequences in the tutorial provide scaffolding support to help students develop a functional understanding. The final version of the validated tutorial was implemented in two distinct courses offered by the physics department with slightly different student populations and broader course goals. Students’ understanding was evaluated after traditional lecture-based instruction on the requisite concepts and again after engaging with the tutorial. We analyze and discuss their improvement in performance on concepts covered in the tutorial. Published by the American Physical Society 2024

Stylometric Analysis of AI Chatbot-Generated Emails: Are Students Losing Their Linguistic Fingerprint?

The integration of artificial intelligence (AI) in education, particularly through AI chatbots like ChatGPT, Copilot, Gemini, and Bing, has revolutionized second language teaching and learning. These chatbots, which utilize advanced natural language processing and machine learning algorithms, hold great potential. They can operate complex cognitive tasks, provide immediate feedback, enhance motivation and self-confidence, reduce anxiety and improve language skills. Despite these advantages, concerns about academic integrity, loss of unique voice, and lack of emotional depth have emerged. This research aims at conducting a stylometric analysis on 25 AI chatbot-generated emails produced by undergraduate English language learners at Sultan Qaboos University. By examining stylistic features like tone, lexical density, lexical diversity, choice of words, repetition, formality level and emotional depth, the study will provide insights into the strengths and limitations of AI chatbots in enhancing email writing skills while preserving the unique voice of student writing. Findings reveal that AI-generated emails are characterized by a repetitive structure, a high level of formality and politeness, a high lexical diversity and a lack of emotional depth and personal anecdotes. The outcomes of this research will shed light on the awareness and skills students need to acquire to optimize the use of AI chatbots without losing their linguistic fingerprint.

Effects of Cognitive Task During Unstable Walking on the Frontal Cerebral Blood Flow in Elderly Retirement Home Residents Leading an Independent Daily Life.

This study aimed to examine the effects of cognitive tasks during walking with perturbation on the cerebral blood flow. The subjects were a total of 20 persons, consisting of 12 healthy adults aged 21-47 years (adult group) and 8 retirement home residents aged 67-85 years who led an independent daily life and could walk independently (elderly group). Oxyhemoglobin was measured using wireless functional near-infrared spectroscopy (fNIRS). An analysis was conducted using the Wilcoxon rank sum test to compare the variation of oxyhemoglobin between walking with perturbation (WP) and walking with perturbation and cognitive tasks (WPC) in each group. In addition, we compared the variation of oxyhemoglobin between groups by analysis of covariance adjusting for the value of WP. In the adult group, the left and right oxyhemoglobin significantly increased under WPC (p=0.0122, 0.0015, respectively). On the other hand, in the elderly group, the right and left oxyhemoglobin did not significantly change under WPC. These results suggest that the effect of a cognitive task during unstable walking conditions differs between healthy adults and elderly persons, and that this may be important when considering postural control strategies, especially in the elderly.

The unpleasantness of thinking: A meta-analytic review of the association between mental effort and negative affect.

Influential theories in psychology, neuroscience, and economics assume that the exertion of mental effort should feel aversive. Yet, this assumption is usually untested, and it is challenged by casual observations and previous studies. Here, we meta-analyze (a) whether mental effort is generally experienced as aversive and (b) whether the association between mental effort and aversive feelings depends on population and task characteristics. We meta-analyzed a set of 170 studies (from 125 articles published in 2019-2020; 358 different tasks; 4,670 unique subjects). These studies were conducted in a variety of populations (e.g., health care employees, military employees, amateur athletes, college students; data were collected in 29 different countries) and used a variety of tasks (e.g., equipment testing tasks, virtual reality tasks, cognitive performance tasks). Despite this diversity, these studies had one crucial common feature: All used the NASA Task Load Index to examine participants' experiences of effort and negative affect. As expected, we found a strong positive association between mental effort and negative affect. Surprisingly, just one of our 15 moderators had a significant effect (effort felt somewhat less aversive in studies from Asia vs. Europe and North America). Overall, mental effort felt aversive in different types of tasks (e.g., tasks with and without feedback), in different types of populations (e.g., university-educated populations and non-university-educated populations), and on different continents. Supporting theories that conceptualize effort as a cost, we suggest that mental effort is inherently aversive. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Structure-function coupling in macroscale human brain networks.

Precisely how the anatomical structure of the brain gives rise to a repertoire of complex functions remains incompletely understood. A promising manifestation of this mapping from structure to function is the dependency of the functional activity of a brain region on the underlying white matter architecture. Here, we review the literature examining the macroscale coupling between structural and functional connectivity, and we establish how this structure-function coupling (SFC) can provide more information about the underlying workings of the brain than either feature alone. We begin by defining SFC and describing the computational methods used to quantify it. We then review empirical studies that examine the heterogeneous expression of SFC across different brain regions, among individuals, in the context of the cognitive task being performed, and over time, as well as its role in fostering flexible cognition. Last, we investigate how the coupling between structure and function is affected in neurological and psychiatric conditions, and we report how aberrant SFC is associated with disease duration and disease-specific cognitive impairment. By elucidating how the dynamic relationship between the structure and function of the brain is altered in the presence of neurological and psychiatric conditions, we aim to not only further our understanding of their aetiology but also establish SFC as a new and sensitive marker of disease symptomatology and cognitive performance. Overall, this Review collates the current knowledge regarding the regional interdependency between the macroscale structure and function of the human brain in both neurotypical and neuroatypical individuals.

A novel IDEA(-R) for a small group teaching format.

We present a novel small group teaching format (termed IDEA-R), ideal for deliberate targeting and escalation of cognitive learning tasks. Additionally, this approach is ideal for smaller postgraduate programs which struggle to predict trainee attendance far in advance, as it provides a flexible format that can adapt to in-the-moment fluctuations in trainee numbers.

CBGTPy: An extensible cortico-basal ganglia-thalamic framework for modeling biological decision making.

Here we introduce CBGTPy, a virtual environment for designing and testing goal-directed agents with internal dynamics that are modeled on the cortico-basal-ganglia-thalamic (CBGT) pathways in the mammalian brain. CBGTPy enables researchers to investigate the internal dynamics of the CBGT system during a variety of tasks, allowing for the formation of testable predictions about animal behavior and neural activity. The framework has been designed around the principle of flexibility, such that many experimental parameters in a decision making paradigm can be easily defined and modified. Here we demonstrate the capabilities of CBGTPy across a range of single and multi-choice tasks, highlighting the ease of set up and the biologically realistic behavior that it produces. We show that CBGTPy is extensible enough to apply to a range of experimental protocols and to allow for the implementation of model extensions with minimal developmental effort.

The Effect of Total Knee Replacement on Dual-Task Gait Performance in Older Adults.

Total knee replacement (TKR) is a common solution for patients with advanced knee osteoarthritis (OA). Still, fall rates remain relatively high after surgery. TKR may alter pain and knee function, balance control, and proprioception. However, given the role of complex (dual-task) walking in fall prediction for older adults, it is unknown how TKR alters the attentional demand of walking in older adults. The goal of this study was to examine the effect of TKR on dual-task walking among older adults. Participants were evaluated 1month before surgery and 4.5months after surgery. Participants walked along an instrumented 7-meter path for 1minute with and without a cognitive task (serial-3 subtraction). Pain and knee function, knee proprioception, dynamic balance, and balance confidence, as well as dual-task costs (DTC) were compared before and after the surgery and factors associated with change in gait DTCs were assessed. Thirty-eight participants completed the study (age 72.6years, SD = 4.9; 11 men). A significant decrease in pain was found following TKR, with no change in balance, balance confidence, or proprioception. There were no differences in gait DTCs before and after the surgery. However, change in dynamic balance, specifically reactive postural control and dynamic gait, predicted changes in gait speed and stride time DTCs. The absence of an effect of TKR on gait DTCs can potentially underlie increased fall risk after TKR. Results from this study emphasize the significance of balance as a measure and focal point for rehabilitation after TKR. This study contributes to our understanding of the attentional cost of walking in people before and after TKR, as well as to factors associated with it. Results from this work can assist formulation of rehabilitation programs for people with knee OA.

Effects of the Regular Use of Virtual Environments on Spatial Navigation and Memory.

Introduction: The cognitive effects of video games have garnered increasing attention due to their potential applications in cognitive rehabilitation and evaluation. However, the underlying mechanisms driving these cognitive modifications remain poorly understood. Objectives: This study investigates the fundamental mnemonic processes of spatial navigation, pattern separation, and recognition memory, closely associated with the hippocampus. Our objective is to elucidate the interaction of these cognitive processes and shed light on rehabilitation mechanisms that could inform the design of video games aimed at stimulating the hippocampus. Method: In this study, we assessed 48 young adults, including both video game players and non-players. We utilized virtual reality and cognitive tasks such as the Lobato Virtual Water Maze and the Mnemonic Similarity Task to evaluate their cognitive abilities. Results: Our key findings highlight that gamers exhibit heightened pattern separation abilities and demonstrate quicker and more accurate spatial learning, attributed to the cognitive stimulation induced by video games. Additionally, we uncovered a significant relationship between spatial memory, guided by environmental cues, and pattern separation, which serves as the foundation for more efficient spatial navigation. Conclusions: These results provide valuable insights into the cognitive impact of video games and offer potential for monitoring changes in rehabilitation processes and early signs of cognitive decline through virtual reality-based assessments. Ultimately, we propose that examining the relationships between cognitive processes represents an effective method for evaluating neurodegenerative conditions, offering new possibilities for early diagnosis and intervention.

Social Cognition, Executive Functioning, Mood, and Disability in Cervical Dystonia.

Individuals with idiopathic adult-onset isolated cervical dystonia (CD) may have cognitive difficulties and increased mood challenges. Social cognition and executive functioning may be particularly affected. To explore social cognition and executive functioning performance in individuals with CD, using the Cambridge Neuropsychological Test Automated Battery (CANTAB), as previous research has used traditional, nondigital neuropsychological assessments. We sought to investigate the relationships between social cognition, executive functioning, mood, and disability in individuals with CD. We recruited 37 individuals with CD, including 26 women with an age range of 33 to 69 years (M = 56.64, SD = 8.31) from a dystonia clinic in a hospital neurology department. The individuals completed selected tasks from the CANTAB measuring social cognition and executive functioning. We compared the individuals' performance with CANTAB normative data. Depression, anxiety, disease severity, and disability were measured. The individuals with CD had significantly lower scores than the CANTAB normative data in both social cognition and executive functioning tasks, with the largest differences evident in problem-solving, attention, and positive emotion bias tasks. Poorer emotion recognition was associated with increased difficulties in problem-solving tasks. The individuals demonstrated a bias toward identifying happiness in facial affect, which was related to a poorer recognition of emotions. Cognitive performance was not related to CD severity or disability or to current mood symptoms. Difficulties with both social cognition and executive functioning were identified in the individuals with CD, and are likely important targets for clinical interventions.

Individual differences in attention and working memory modulate the process of tone merging: evidence from Macau Cantonese

Cognitive functions, including attention and working memory, have been recognized to be associated with tone processing. However, it remains unclear how these cognitive functions might modulate the process of tone merging. In Macau Cantonese, three pairs of tones are currently undergoing or have completed merging, exhibiting different rates and ranges of merging within the speech community, providing a valuable opportunity to investigate this issue. Through a perception task, a production task, and a series of cognitive function tasks, we examined differences in cognitive performances among individuals distinguishing different tone pairs and explored the correlations between various indices of tone processing and cognitive functions. The results revealed that the completed merging of the T2–T5 pair showed no significant correlation with cognitive functions in perception and production. The T3–T6 pair, with an intermediate merging speed, exhibited a significant positive correlation between cognitive functions and both their perception and production. In contrast, the T4–T6 pair, characterized by a slower merging speed, showed a correlation only in the perception modality. Our findings suggested that cognitive functions affect tones at different stages of the merging process, influencing their perception and production in distinct ways. The results provide a novel perspective on the origin of tonal variation and the relationship between perception and production.

Is precrastination related to updating and inhibition aspects of executive function?

ABSTRACT Precrastination is the act of completing a task as soon as possible even at the expense of extra effort. Past research has suggested that individuals precrastinate due to a desire to reduce their cognitive load, also known as the cognitive load-reduction (CLEAR) hypothesis [VonderHaar, R. L., McBride, D. M., & Rosenbaum, D. A. (2019). Task order choices in cognitive and perceptual-motor tasks: The cognitive-load-reduction (CLEAR) hypothesis. Attention, Perception, & Psychophysics, 81(7), 2517–2525. https://doi.org/10.3758/s13414-019-01754-z]. This idea stems from the notion that it is taxing to hold intentions in working memory and completing a task as soon as possible releases cognitive resources for other tasks. Based on this hypothesis, we predicted that aspects of executive function may play a role in precrastination. We tested this prediction using a box-moving task developed in a previous study to measure precrastination. We also incorporated tasks measuring updating and inhibition aspects of executive function: the Stroop interference (both experiments) and Simon tasks (Experiment 2) to measure inhibition and the 2-Back memory task (Experiment 1) to measure updating. We found that the majority of participants precrastinated significantly throughout the box-moving task trials, consistent with results from past studies. However, no relation was found between the executive function tasks and rates of precrastination. These results may be due to the automaticity of precrastination when cognitive resources are limited.