Task Performance Research Articles

Exercising with virtual reality is potentially better for the working memory and positive mood than cycling alone

Background and aimsAlthough virtual reality (VR) exercise has attracted attention as a factor in exercise habituation due to its mood-enhancing effects, its impact on brain function remains unclear. This study aimed to explore how VR exercise affects working memory, a key executive function, and its underlying neural mechanisms. MethodsThe study involved 23 healthy university students who engaged in exercise in a VR environment. Outcomes included cardiorespiratory and psychological assessments, as well as functional magnetic resonance imaging (fMRI). ResultsOur findings indicate that a 10-min VR exercise session improved mood (arousal and vitality level) and working memory task performance (3-back task) more effectively than exercise or rest alone. Furthermore, the results confirmed that increased vitality from both exercise and VR exercise interventions was associated with improved 3-back task performance. However, specific brain regions contributing to this enhancement remain unidentified. ConclusionThese results highlight VR exercise as an optimal exercise program for enhancing working memory function by increasing vitality levels. These insights underscore the potential of VR as a novel exercise modality, with benefits extending beyond exercise adherence to potentially prevent dementia and depression.

The effects of experimental pain on episodic memory and its top-down modulation: a preregistered pooled analysis.

Pain can automatically interfere with ongoing cognitive processes such as attention and memory. The extent of pain's negative effects on cognitive functioning seems to depend on a balance between top-down and bottom-up factors. In this large, preregistered, pooled reanalysis of 8 studies, we investigated the robustness of the detrimental effect of acute pain on recognition memory and whether top-down mechanisms such as pain-related expectations or cognitions (pain-related fear, pain catastrophizing) modulate this effect. Two hundred forty-seven healthy participants underwent similar experimental paradigms, including a visual categorization task with images randomly paired with (or without) concomitant painful stimulation and a subsequent unannounced recognition task. Recognition memory (ie, d', recollection, and familiarity) and categorization performance (ie, reaction time, accuracy) served as proxies for the effect of pain on cognitive performance. Acute painful stimulation significantly impaired recognition performance (d', familiarity). However, recognition performance was not significantly modulated by participants' expectations regarding the effect of pain on task performance or pain-related cognitions in this sample of healthy participants. Our results corroborate the negative effects of pain on (visual) memory encoding reported in previous studies and reports of "memory problems" from patients with chronic pain. To characterize the role of bottom-up and top-down factors for the detrimental effects of pain, large-scale studies with more nuanced study designs are necessary. Future studies in patient cohorts must unravel the interaction of maladaptive pain-related cognitions and the often-reported impaired cognitive performance in chronic pain patients.

The impact of attention and task performance on antiphishing performance: a multigoal perspective

PurposePeople are often recognized as the weakest part of thwarting phishing attacks. The goal of preventing phishing can conflict with the goal of keeping a good level of productivity in daily work; however, we still lack an understanding of this multigoal scenario. This paper aims to develop and test a new model of antiphishing performance, especially in relation to individuals' task performance in daily work. Drawing on the extended multiple-goal pursuit model (MGPM*), we examined the relationship between task performance at a time point and the subsequent antiphishing performance as well as how this relationship differs across varying types of phishing emails and attention levels to phishing cues.Design/methodology/approachWe tested the model by conducting a field experiment with a survey questionnaire. Four legitimate work emails and four phishing emails (consisting of two work-related and two work-unrelated emails) were sent to 357 participants. The data were analyzed using generalized estimating equations.FindingsThe results indicate that task performance at a time point has a curvilinear relationship with subsequent antiphishing performance. This relationship is moderated by the types of phishing emails and individuals' attention to phishing cues. For work-related phishing emails, task performance is negatively associated with antiphishing performance when it reaches an intermediate level; however, when task performance is low, or high to an extent, it is positively related to antiphishing performance. For work-unrelated phishing emails, there is a positive association between task performance and antiphishing performance. Moreover, attention to phishing cues moderates the curvilinear relationship between task performance and antiphishing performance such that when task performance reaches an intermediate level, as attention to phishing cues increases, the relationship between task performance and antiphishing performance will turn from negative to positive.Practical implicationsThis paper has practical implications that bear on the conflict between antiphishing performance and task performance.Originality/valueThis paper sheds light on the potential of the extended multiple-goal pursuit model in studying antiphishing behavior.

The influence of categorical stimuli on relational memory binding.

Binding of arbitrary information into distinct memory representations that can be used to guide behavior is a hallmark of relational memory. What is and is not bound into a memory representation and how those things influence the organization of that representation remain topics of interest. While some information is intentionally and effortfully bound-often the information that is consistent with task goals or expectations about what information may be required later-other information appears to be bound automatically. The present set of experiments sought to investigate whether spatial memory would be systematically influenced by the presence and absence of distinct categories of stimuli on a spatial reconstruction task. In this task, participants must learn multiple item-location bindings and place each item back in its studied location after a short delay. Across three experiments, participants made significantly more within-category errors (i.e., misassigning one item to the location of a different item from the same category) than between-category errors (i.e., misassigning one item to the location of an item from a different category) when categories were perceptually or semantically distinct. These data reveal that category information contributed to the organization of the memory representation and influenced spatial reconstruction performance. Together, these results suggest that categorical information can influence memory organization, and not always to the benefit of overall task performance.

Association between neurovascular coupling and neural signals in the resting state as revealed by a combined fMRI and magnetoencephalography study in humans.

The blood oxygenation level-dependent (BOLD) activation reflects hemodynamic events mediated by neurovascular coupling. During task performance, the BOLD hemodynamic response in a relevant area is mainly driven by the high levels of synaptic activity (reflected in local field potentials, LFPs) but, in contrast, during a task-free, resting state, the contribution to BOLD of such neural events is small, as expected by the comparatively (to the task state) low level of neural events. Concomitant recording of BOLD and LFP at rest in animal experiments has estimated the neural contribution to BOLD to ∼10%. Such experiments have not been performed in humans. As an approximation, we recorded (in the same subject, n = 57 healthy participants) at a task-free, resting state the BOLD signal and, in a different session, the magnetoencephalographic (MEG) signal, which reflects purely neural (synaptic) events. We then calculated the turnover of these signals by computing the successive moment-to-moment difference in the BOLD and MEG time series and retaining the median of the absolute value of the differenced series (BOLD and TMEG, respectively). The correlation between normalized turnovers of BOLD (TBOLD) and turnovers of MEG (TMEG) was r = 0.336 (r2 = 0.113; P = 0.011). These results estimate that 11.3% of the variance in TBOLD can be explained by the variance in TMEG. This estimate is close to the aforementioned estimate obtained by direct recordings in animal experiments. NEW & NOTEWORTHY Here, we report on a weak positive association between turnovers of blood oxygenation level-dependent (TBOLD) and magnetoencephalographic (TMEG) signals in 57 healthy human subjects in a resting, task-free state. More specifically, we found that the purely neural TMEG accounted for 11.1% of the TBOLD, a percentage remarkably close to that found between resting-state local field potentials (LFPs) and BOLD recorded concurrently in animal experiments.

Default at fault? Exploring neural correlates of default mode network in children with ADHD, their unaffected siblings versus neurotypical controls: A quantitative EEG study

BackgroundSustained activation of default mode network has been implicated for momentary lapses of attention and higher errors during performance of cognitive tasks in attention deficit hyperactive disorder (ADHD) children. Despite emerging evidence indicating the genetic basis of ADHD, there is paucity of literature investigating the alteration of DMN in children with ADHD and their unaffected siblings. AimTo study the cortical sources of DMN in children with ADHD compared to their siblings and neurotypical controls. MethodsEighty-six participants (35 ADHD (12.4(±2.7) years), 16 unaffected siblings (11.8(±4.3) years) and 35 matched neurotypical controls (12.6 (±3.6) years) participated in the study. 128 channel EEG data was acquired during rest and Stroop cognitive task and analyzed for cortical source estimation using LORETA software. ResultsHigher activation of DMN and DMN associated areas were observed during encoding of the color-word stimuli in children with ADHD. Sustained activation of core DMN areas namely medial frontal gyrus, posterior cingulate gyrus, parahippocampal gyrus and inferior parietal lobule was observed across all groups. Among the three groups, distinct cortical source activation differences were identified solely in the DMN and its associated areas among children with ADHD during the task encoding phase compared to baseline. In contrast, both siblings and neurotypical controls displayed activation in fronto-parieto-temporal areas subserving executive function were also observed. ConclusionSustained activity of DMN areas with minimal activity in executive network in ADHD children and unaffected siblings during encoding of stimulus implies potential endophenotypic marker in children with ADHD compared to neurotypical controls.

Spatial Contextual Information Modulates Affordance Processing and Early Electrophysiological Markers of Scene Perception.

Scene perception allows humans to extract information from their environment and plan navigation efficiently. The automatic extraction of potential paths in a scene, also referred to as navigational affordances, is supported by scene-selective regions (SSRs) that enable efficient human navigation. Recent evidence suggests that the activity of these SSRs can be influenced by information from adjacent spatial memory areas. However, it remains unexplored how these contextual information could influence the extraction of bottom-up information, such as navigational affordances, from a scene and the underlying neural dynamics. Therefore, we analyzed ERPs in 26 young adults performing scene and spatial memory tasks in artificially generated rooms with varying numbers and locations of available doorways. We found that increasing the number of navigational affordances only impaired performance in the spatial memory task. ERP results showed a similar pattern of activity for both tasks, but with increased P2 amplitude in the spatial memory task compared with the scene memory. Finally, we reported no modulation of the P2 component by the number of affordances in either task. This modulation of early markers of visual processing suggests that the dynamics of SSR activity are influenced by a priori knowledge, with increased amplitude when participants have more contextual information about the perceived scene. Overall, our results suggest that prior spatial knowledge about the scene, such as the location of a goal, modulates early cortical activity associated with SSRs, and that this information may interact with bottom-up processing of scene content, such as navigational affordances.

Психологическая компетентность юриста как средство совершенствования взаимодействия участников правоотношений

The article is devoted to the topic of developing the psychological competence of a lawyer as a professionally important personal characteristic in the context of considering his professional success from the point of view of economic theory. The analysis of economic risks in the field of legal practice in the specific area of bankruptcy of individuals is carried out, the factors of professional success of a lawyer in the process of interaction with debtor citizens are revealed. A practical study conducted among practicing lawyers is presented, which identifies the main indicators of their psychological competence, and proves its role as a means of improving the interaction of participants in legal relationships in the process of bankruptcy of individuals. Based on the results of the diagnostic study, the conditions and opportunities for the development of psychological competence of lawyers were determined through a special psychological training program developed taking into account the current requests of lawyers practicing in the field of bankruptcy of citizens. The importance of the psychological competence of a lawyer practicing in the field of bankruptcy of citizens as a professionally important personal education is substantiated. The need for a lawyer to have highly developed competencies in the psychological field in order to build effective interaction at different levels and the presence of diverse social contacts in the performance of professional tasks is proved.

Investigating causal effects of pupil size on visual discrimination and visually evoked potentials in an optotype discrimination task.

Pupil size primarily changes to regulate the amount of light entering the retina, optimizing the balance between visual acuity and sensitivity for effective visual processing. However, research directly examining the relationship between pupil size and visual processing has been limited. While a few studies have recorded pupil size and EEG signals to investigate the role of pupil size in visual processing, these studies have predominantly focused on the domain of visual sensitivity. Causal effects of pupil size on visual acuity, therefore, remain poorly understood. By manipulating peripheral background luminance levels and target stimulus contrast while simultaneously recording pupillometry and EEG signals, we examined how absolute pupil size affects visual discrimination and visually evoked potentials (VEP) in a task using optotype mimicking the Snellen eye chart, the most common assessment of visual acuity. Our findings indicate that both higher background luminance levels and higher target contrast were associated with improved target discrimination and faster correct reaction times. Moreover, while higher contrast visual stimuli evoked larger VEPs, the effects of pupil size on VEPs were not significant. Additionally, we did not observe inter-individual correlations between absolute pupil size and discrimination performance or VEP amplitude. Together, our results demonstrate that absolute pupil size, regulated by global luminance level, played a functional role in enhancing visual discrimination performance in an optotype discrimination task. The differential VEP effects of pupil size compared to those of stimulus contrast further suggested distinct neural mechanisms involved in facilitating visual acuity under small pupils.

Building a Multimodal Dataset of Academic Paper for Keyword Extraction

ABSTRACTUp to this point, keyword extraction task typically relies solely on textual data. Neglecting visual details and audio features from image and audio modalities leads to deficiencies in information richness and overlooks potential correlations, thereby constraining the model's ability to learn representations of the data and the accuracy of model predictions. Furthermore, the currently available multimodal datasets for keyword extraction task are particularly scarce, further hindering the progress of research on multimodal keyword extraction task. Therefore, this study constructs a multimodal dataset of academic paper consisting of 1,000 samples, with each sample containing paper text, images, audios and keywords. Based on unsupervised and supervised methods of keyword extraction, experiments are conducted using textual data from papers, as well as text extracted from images and audio. The aim is to investigate the differences in performance in keyword extraction task with respect to different modal information and the fusion of multimodal information. The experimental results indicate that text from different modalities exhibits distinct characteristics in the model. The concatenation of paper text, image text and audio text can effectively enhance the keyword extraction performance of academic papers.

Reward processing in young people with self-harm behaviour

Twenty percent of young people report a lifetime presence of self-harm (SH) behaviour, associated with negative health and functional outcomes. Understanding the underlying cognitive mechanisms is needed to develop targeted early interventions. Reward processing biases may underlie SH, aligning with accounts of the behaviour acquiring “addictive” characteristics. However, the specific nature of such biases remains unclear, particularly its relationship with negative affect (NA) that frequently triggers SH. In Study 1, we compared young people (aged 16–25) with SH to a group with NA but no SH history and a healthy control group on performance of a novel Incentive Delay Task (IDT), with SH-related (SH trials), positive social (social trials) or monetary images (money trials) as stimuli. In Study 2, a different sample of SH and HC participants completed the same IDT following NA induction via an online Trier Social Stress Test. For both studies, we hypothesised faster and more correct responses in the SH group than control groups on SH trials. Contradicting our hypothesis, there were no significant between-group differences in IDT performance on SH, social and money trials in either study. Certain SH characteristics (positive reinforcement, SH mental imagery, urge) were significantly correlated with better performance on SH trials in SH participants. Thus, broadly SH behaviour may not be underpinned by motivational biases towards SH-related cues or naturalistic rewards. Future studies should clarify whether incentivisation of SH-related cues instead explains individual differences in SH behaviour and its relation with treatment and prognosis.

Table Transformers for imputing textual attributes

Missing data in tabular dataset is a common issue as the performance of downstream tasks usually depends on the completeness of the training dataset. Previous missing data imputation methods focus on numeric and categorical columns, but we propose a novel end-to-end approach called Table Transformers for Imputing Textual Attributes (TTITA) based on the transformer to impute unstructured textual columns using other columns in the table. We conduct extensive experiments on three datasets, and our approach shows competitive performance outperforming baseline models such as recurrent neural networks and Llama2. The performance improvement is more significant when the target sequence has a longer length. Additionally, we incorporate multi-task learning to simultaneously impute for heterogeneous columns, boosting the performance for text imputation. We also qualitatively compare with ChatGPT for realistic applications.

A new two-stage low-light enhancement network with progressive attention fusion strategy

Low-light image enhancement is a very challenging subject in the field of computer vision. It has a large number of degradation problems such as accumulated noise, artifacts, and color distortion. Therefore, how to solve the degradation problems and obtain clear images with high visual quality has become an important issue. It can effectively improve the performance of high-level computer vision tasks. In this study, we propose a new two-stage low-light enhancement network with a progressive attention fusion strategy, and the two hallmarks of this method are the use of global feature fusion (GFF) and local detail restoration (LDR), which can enrich the global content of the image and restore local details. Experimental results on the LOL dataset show that the proposed model can achieve good enhancement effects. Moreover, on the benchmark dataset without reference images, the proposed model also obtains a better NIQE score, which outperforms most existing state-of-the-art methods in both quantitative and qualitative evaluations. All these verify the effectiveness and superiority of the proposed method.

Design and Practice of Virtual Experimental Scenes Integrating Computer Vision and Image Processing Technologies

In this work, we introduce a novel framework, GAN-based Image Processing (GAN-IP), to design and manipulate digital experimental settings that effectively combine computer vision and image processing technology. Using the skills of Generative Adversarial Networks (GANs), GAN-IP creates and complements virtual scenes and affords rich, adaptive surroundings for analysing and creating computationally smart and perceptive algorithms. GAN-IP solves the pressing troubles of variability and absence of data through synthesising realistic pictures and scenarios, enabling simulations of the diverse environments in which computer vision structures have to function. Our approach improves the fidelity and sort of digital scenes and introduces a way to mechanically alter and evoke a pleasant image, enabling more accurate and powerful computer vision and prescient models. Through extensive experimentation, GAN-IP demonstrates remarkable improvements in the performance of computer vision tasks, including object detection, segmentation, and recognition in complicated virtual environments. This research lays the foundation for future studies in this field and provides an adaptive tool for researchers and practitioners to simulate and test superior computer imaginative and prescient image processing technologies.

MAIN STAGES OF EMPLOYEE EMPOWERMENT STRENGTHENING IN PRODUCTION ORGANIZATIONS

As management strategies and organizational structures change, the aim is to discover ways that will help make the activities of each employee, as well as the entire production organization, more efficient. In each successful organization, the leader’s and employee's ability to understand each other and to work together in a team is very important. At present, a new term is being emphasized and promoted- empowerment – the leader's actions towards the employee in order to successfully achieve the goals of the organization. Dimensions of structural empowerment: opportunities - the employee's perception of the extent to which he has opportunities to perform challenging work using existing abilities and at the same time acquiring new abilities, information - to the extent that, in the employee's perception, information is available to him in a wider context than his individual work, support - to the extent that the employee feels that he can receive advice or feedback during the performance of various tasks, resources - to what extent all the necessary resources are available to the employee to perform the planned tasks. Empowerment is essentially a democratic process that allows employees to have more say in decisions that are currently made by managers in traditional command and control centers. A model for strengthening employee empowerment is presented, consisting of 3 stages, which allows identifying employee empowerment problems when making decisions on quality issues and providing solutions. The quantity of features and characteristics of a product reflects its quality. One of the most important aspects is that managers and executors (team members) must understand the importance of quality and know what factors affect it and what solutions take place with identified problems. Based on the identification of product quality from the point of view of managers and executives, problems are identified, and solutions are provided to change the situation. If they do not have a common understanding of product quality issues, the situation in production only worsens. Organizations must empower their frontline employees with the authority and training to make decisions related to equipment operation and maintenance. The obtained results of a quantitative study carried out in a manufacturing company proved that employees partially feel empowered by managers to make decisions: especially in the second stage, which is associated with work performance, quality requirements, job satisfaction and efficiency. Recommendations are provided for management to develop a sense of personal efficacy through employee empowerment. The role of managers is to empower their subordinates to make decisions on their own, relying on established (approved) requirements. This research about employee empowerment can be useful for organizations in assessing the effectiveness of measures, enabling leadership, and the innovations implemented, as well as in forming a holistic approach to the phenomenon of employee empowerment, combining the assumptions that make up empowerment into a common system and the consequences that are significant for work and the organization.

СУТЬ І СТРУКТУРА ЕКОНОМІЧНОЇ КУЛЬТУРИ МАЙБУТНІХ ТЕХНІКІВ З ТРАНСПОРТНИХ ТЕХНОЛОГІЙ ТА УПРАВЛІННЯ ПЕРЕВЕЗЕННЯМИ НА АВТОМОБІЛЬНОМУ ТРАНСПОРТІ

The relevance of the article is due to the need to define and substantiate the essence and structure of the economic culture of future technicians in transport technologies and transportation management in road transport, to reveal the content of each component of the structure of economic culture, as well as to determine the key factors that contribute to its formation in the process of professional training of future technicians in transport technologies technologies and management of road transport. The purpose of the article is to determine the essence and structure of the economic culture of future technicians in transport technologies and management of road transport. Methods: the study of scientific sources regarding the interpretation of the essence of the concept "economic culture of the culture of future technicians in transport technologies and management of transportation by road transport" - to formulate one's own views on defining the content of this phenomenon; structural-component analysis - to distinguish the components of the economic culture of future technicians in transport technologies and transportation management by road transport; generalization and systematization - and formulation of conclusions and prospects for further research. Results: the main approaches in scientific sources to the interpretation of the concept of "economic culture of future technicians in transport technologies and management of road transport" were determined; the main components of the structure of economic culture and the components of the formation of the economic culture of future technicians in transport technologies and management of road transport are characterized. Conclusions: the essence of the economic culture of future technicians in transport technologies and transportation management in road transport is an integrative formation of the personality of a specialist, reflecting a system of professionally important qualities, values, knowledge, abilities and skills in planning technologies for the organization of transportation, providing transport and warehouse services, using resource potential for development transport enterprises in market conditions; characterized by a high degree of discipline, responsibility, independence with an awareness of the priorities of economic culture in the performance of professional tasks. The component structure of the economic culture of technicians in transport technologies and transportation management in road transport includes motivational-value, innovative-cognitive, activity-technological, personal-reflexive.

An explainable deep learning model for automated classification and localization of microrobots by functionality using ultrasound images

The rapid advancements of untethered microrobots offer exciting opportunities in fields such as targeted drug delivery and minimally invasive surgical procedures. However, several challenges remain, especially in achieving precise localization and classification of microrobots within living organisms using ultrasound (US) imaging. Current US-based detection algorithms often suffer from inaccurate visual feedback, causing positioning errors. This paper presents a novel explainable deep learning model for the localization and classification of eight different types of microrobots using US images. We introduce the Attention-Fused Bottleneck Module (AFBM), which enhances feature extraction and improves the performance of microrobot classification and localization tasks. Our model consistently outperforms baseline models such as YOLOR, YOLOv5-C3HB, YOLOv5-TBH, YOLOv5 m, and YOLOv7. The proposed model achieved mean Average Precision (mAP) of 0.861 and 0.909 at an IoU threshold of 0.95 which is 2% and 1.5% higher than the YOLOv5 m model in training and testing, respectively. Multi-thresh IoU analysis was performed at IoU thresholds of 0.6, 0.75, and 0.95, and demonstrated that the microrobot localization accuracy of our model is superior. A robustness analysis was performed based on high and low frequencies, gain, and speckle in our test data set, and our model demonstrated higher overall accuracy. UsingScore-CAM in our framework enhances interpretability, allowing for transparent insights into the model’s decision-making process. Our work signifies a notable advancement in microrobot classification and detection, with potential applications in real-world scenarios using the newly available USMicroMagset dataset for benchmarking.

Fasudil attenuates lipopolysaccharide-induced cognitive impairment in C57BL/6 mice through anti-oxidative and anti-inflammatory effects: Possible role of aquaporin-4

IntroductionProcesses that generate systemic inflammation are strongly associated with neurodegenerative diseases. This study aimed to explore the potential anti-oxidative and anti-inflammatory effects of fasudil and its role in modulating aquaporin-4 (AQP-4) to improve cognitive impairment in a systemic inflammation model induced by lipopolysaccharide (LPS). Methodfourty C57BL/6 mice were assigned to four groups, including sham, LPS, sham+fasudil, and LPS+fasudil). Intraperitoneal LPS was given (500μg/kg/day) at hours 0, 24, 48, and 72, and fasudil (30mg/kg) administered intraperitoneal injections 2hours after LPS injection. The open field, Y-maze, and Novel object tasks was used to assess learning and memory. The levels of malondialdehyde (MDA), superoxide dismutase (SOD), interleukin-10 (IL-10), and tumor necrosis factor-α (TNF-α) in the hippocampus also measured as markers of oxidative stress and inflammation. Furthermore, the expression of AQP-4 measured in the intact and experimental groups. ResultsThe results showed that Fasudil significantly improved memory and anxiety behavior induced by LPS in the open field maze, spatial recognition memory in the Y-maze, and performance in the novel object recognition task. It also mitigates hippocampal MDA and SOD levels. Additionally, fasudil ameliorated LPS-induced hippocampal levels of TNFα and IL-10 and increased hippocampal levels of AQP-4 expression in mice. ConclusionOur results suggest that fasudil in the LPS model of systemic inflammation could improve cognition by suppressing oxidative stress and inflammation and increasing AQP-4 protein expression. These findings highlighted the potential of fasudil as a neuroprotective agent. However, further research is required to fully understand its neuroprotective properties in the treatment of neurodegenerative disorders.

A relative deprivation perspective of the differentiation of abusive supervision in groups

While prior research has found that leaders tend not to abuse subordinates equally, empirical studies exploring the differentiation phenomenon of abusive supervision still remain limited. Drawing on relative deprivation theory, the differentiation of abusive supervision is defined as the two operational indicators of relative abusive supervision and abusive supervision variability according to the dual influence this differentiation imposes on both individuals and groups. How the interactive effect of relative abusive supervision and abusive supervision variability impacts employees’ behaviors is examined and the solution to the abusive supervision differentiation dilemma is explored. The results of a two-wave empirical study including 254 employees from 84 groups demonstrate that focal employee relative abusive supervision negatively influences task performance and organizational citizenship behavior via relative deprivation. This effect is amplified when the group has lower levels of abusive supervision variability. This study contributes to a better understanding of abusive supervision in groups.

In silico modeling of reservoir-based predictive coding in biological neuronal networks on microelectrode arrays

Reservoir computing and predictive coding together yield a computational model for exploring how neuronal dynamics in the mammalian cortex underpin temporal signal processing. Here, we construct an in-silico model of biological neuronal networks grown on microelectrode arrays and explore their computing capabilities through a sine wave prediction task in a reservoir-based predictive coding framework. Our results show that the time interval between stimulation pulses is a critical determinant of task performance. Additionally, under a fixed feedback latency, pulse amplitude modulation is a favorable encoding scheme for input signals. These findings provide practical guidelines for future implementation of the model in biological experiments.