Behavioral Phenomena Research Articles

Detection of Mild Cognitive Impairment Through Hand Motor Function Under Digital Cognitive Test: Mixed Methods Study.

Early detection of cognitive impairment or dementia is essential to reduce the incidence of severe neurodegenerative diseases. However, currently available diagnostic tools for detecting mild cognitive impairment (MCI) or dementia are time-consuming, expensive, or not widely accessible. Hence, exploring more effective methods to assist clinicians in detecting MCI is necessary. In this study, we aimed to explore the feasibility and efficiency of assessing MCI through movement kinetics under tablet-based "drawing and dragging" tasks. We iteratively designed "drawing and dragging" tasks by conducting symposiums, programming, and interviews with stakeholders (neurologists, nurses, engineers, patients with MCI, healthy older adults, and caregivers). Subsequently, stroke patterns and movement kinetics were evaluated in healthy control and MCI groups by comparing 5 categories of features related to hand motor function (ie, time, stroke, frequency, score, and sequence). Finally, user experience with the overall cognitive screening system was investigated using structured questionnaires and unstructured interviews, and their suggestions were recorded. The "drawing and dragging" tasks can detect MCI effectively, with an average accuracy of 85% (SD 2%). Using statistical comparison of movement kinetics, we discovered that the time- and score-based features are the most effective among all the features. Specifically, compared with the healthy control group, the MCI group showed a significant increase in the time they took for the hand to switch from one stroke to the next, with longer drawing times, slow dragging, and lower scores. In addition, patients with MCI had poorer decision-making strategies and visual perception of drawing sequence features, as evidenced by adding auxiliary information and losing more local details in the drawing. Feedback from user experience indicates that our system is user-friendly and facilitates screening for deficits in self-perception. The tablet-based MCI detection system quantitatively assesses hand motor function in older adults and further elucidates the cognitive and behavioral decline phenomenon in patients with MCI. This innovative approach serves to identify and measure digital biomarkers associated with MCI or Alzheimer dementia, enabling the monitoring of changes in patients' executive function and visual perceptual abilities as the disease advances.

Desiderata for Normative Models of Synaptic Plasticity.

Normative models of synaptic plasticity use computational rationales to arrive at predictions of behavioral and network-level adaptive phenomena. In recent years, there has been an explosion of theoretical work in this realm, but experimental confirmation remains limited. In this review, we organize work on normative plasticity models in terms of a set of desiderata that, when satisfied, are designed to ensure that a given model demonstrates a clear link between plasticity and adaptive behavior, is consistent with known biological evidence about neural plasticity and yields specific testable predictions. As a prototype, we include a detailed analysis of the REINFORCE algorithm. We also discuss how new models have begun to improve on the identified criteria and suggest avenues for further development. Overall, we provide a conceptual guide to help develop neural learning theories that are precise, powerful, and experimentally testable.

Optimal Income Taxation

This article explores subjects in optimal income taxation characterized by recent research interest, practical importance in light of concerns about inequality, potential for misunderstanding, and prospects for advancement. Throughout the analysis, paths for further investigation are highlighted. Areas of focus include multidimensional abilities and endogenous wages; asymmetric information and the income of founders; production and consumption externalities from labor effort; market power and rents; behavioral phenomena relating to perceptions of the income tax schedule, myopic labor supply, and the interactions of savings, savings policies, and labor supply; optimal income transfers; the relationship between optimal income taxation and the use of other instruments; and issues relating to the social welfare function and utility functions, including non-welfarist objectives, welfare weights, heterogeneous preferences, and taxation of the family. (JEL D63, D82, D91, H21, H24, H53, J22)

International retirement migration for Japanese retirees: Motivational push-pull factors and behavioral phenomena towards cultural assimilation

International retirement migration for Japanese retirees: Motivational push-pull factors and behavioral phenomena towards cultural assimilation

A thin line between conflict and reaction time effects on EEG and fMRI brain signals

Abstract The last two decades of electrophysiological and neuroimaging research converged that the activity in the medial frontal cortex plays a pivotal role in cognitive control processes. Notably, the midfrontal theta (MFT) oscillatory EEG power as well as activity in the anterior midcingulate cortex (aMCC) or pre-supplementary motor area (preSMA) were consistently proclaimed as markers of conflict processing. However, these brain signals are strongly correlated with response time (RT) variability in various non-conflict tasks, which overshadows the true nature of their involvement. Our previous study (Beldzik et al., 2022) successfully identified these brain signals during a simultaneous EEG-fMRI experiment implementing Stroop and Simon tasks. Based on the assumption that overcoming the habitual prepotent response during high interference trials requires additional neural resources beyond simple decision variable represented in RTs, here we aim to verify if these markers exhibit a congruency effect beyond RT variations. Furthermore, we explored if these brain signals represent either proactive or reactive cognitive control mechanisms by investigating two widely known behavioral phenomena observed in conflict tasks: proportion congruency and congruency sequence effects. The results revealed partially null findings for MFT activity, yet a distinct cognitive control specialization between aMCC and preSMA. Our study provides novel evidence that the former is involved in proactive control mechanisms, possibly contingency learning, whereas the latter reflects reactive control mechanisms by exhibiting a strong congruency effect regardless of RT variation and responding to adaptive behavior.

Strategies for Teaching About Physiological Mechanisms of Obesity in Undergraduate Pathophysiology Courses

Obesity is often viewed as a consequence of “lack of willpower” or other behavioral choices, rather than a complex array of biological and other factors. Many undergraduates in pre-nursing or biology programs have minimal exposure to the physiology and pathophysiology of obesity, including learning about leptin and other hormones involved in appetite control. Because obesity was not previously explicitly covered as s standalone topic in the pre-nursing pathophysiology course at my institution, I developed materials for teaching about the pathophysiology of obesity. These materials were designed at two different levels for use in two different pathophysiology courses: one, a survey of pathophysiology topics for pre-nursing majors, and the other, an in-depth exploration of the molecular and cellular basis of selected diseases for upper division biology majors. In both courses, a case of human leptin deficiency and the ob/ob mouse model are used to introduce the importance of hormones in appetite control and body weight. In the molecular basis of disease course, obesity is covered as part of a unit organized around metabolic syndrome. The discussion includes molecular and cellular mechanisms that link obesity to several other diseases, including type 2 diabetes and atherosclerosis. Informal feedback from students in the pre-nursing course at the end of the course suggested that students shifted their thinking about obesity from a purely behavioral phenomenon to a more nuanced understanding of obesity as a multifactorial condition. Overall, devoting class time to biological mechanisms of obesity has resulted in increased student understanding of the complex nature of body weight regulation. None. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Persons with Parkinson`s disease show the motor behavioral phenomenon repeated bout rate enhancement during cycling

Persons with Parkinson`s disease show the motor behavioral phenomenon repeated bout rate enhancement during cycling

Resolving uncertainty on the fly: modeling adaptive driving behavior as active inference.

Understanding adaptive human driving behavior, in particular how drivers manage uncertainty, is of key importance for developing simulated human driver models that can be used in the evaluation and development of autonomous vehicles. However, existing traffic psychology models of adaptive driving behavior either lack computational rigor or only address specific scenarios and/or behavioral phenomena. While models developed in the fields of machine learning and robotics can effectively learn adaptive driving behavior from data, due to their black box nature, they offer little or no explanation of the mechanisms underlying the adaptive behavior. Thus, generalizable, interpretable, computational models of adaptive human driving behavior are still rare. This paper proposes such a model based on active inference, a behavioral modeling framework originating in computational neuroscience. The model offers a principled solution to how humans trade progress against caution through policy selection based on the single mandate to minimize expected free energy. This casts goal-seeking and information-seeking (uncertainty-resolving) behavior under a single objective function, allowing the model to seamlessly resolve uncertainty as a means to obtain its goals. We apply the model in two apparently disparate driving scenarios that require managing uncertainty, (1) driving past an occluding object and (2) visual time-sharing between driving and a secondary task, and show how human-like adaptive driving behavior emerges from the single principle of expected free energy minimization.

How do animals weigh conflicting information about reward sources over time? Comparing dynamic averaging models

Optimal foraging theory suggests that animals make decisions which maximize their food intake per unit time when foraging, but the mechanisms animals use to track the value of behavioral alternatives and choose between them remain unclear. Several models for how animals integrate past experience have been suggested. However, these models make differential predictions for the occurrence of spontaneous recovery of choice: a behavioral phenomenon in which a hiatus from the experimental environment results in animals reverting to a behavioral allocation consistent with a reward distribution from the more distant past, rather than one consistent with their most recently experienced distribution. To explore this phenomenon and compare these models, three free-operant experiments with rats were conducted using a serial reversal design. In Phase 1, two responses (A and B) were baited with pellets on concurrent variable interval schedules, favoring option A. In Phase 2, lever baiting was reversed to favor option B. Rats then entered a delay period, where they were maintained at weight in their home cages and no experimental sessions took place. Following this delay, preference was assessed using initial responding in test sessions where levers were presented, but not baited. Models were compared in performance, including an exponentially weighted moving average, the Temporal Weighting Rule, and variants of these models. While the data provided strong evidence of spontaneous recovery of choice, the form and extent of recovery was inconsistent with the models under investigation. Potential interpretations are discussed in relation to both the decision rule and valuation functions employed.

Time Will Tell: The Case for an Idiographic Approach to Behavioral Cybersecurity Research

Many of the theories used in behavioral cybersecurity research have been applied with a nomothetic approach, which is characterized by cross-sectional data (e.g., one-time surveys) that identify patterns across a population of individuals. Although this can provide valuable between-person, point-in-time insights (e.g., employees who use neutralization techniques, such as denying responsibility for cybersecurity policy violations, tend to comply less), it is unable to reveal within-person patterns that account for varying experiences and situations over time. This paper articulates why an idiographic approach, which undertakes a within-person analysis of longitudinal data, can: (1) help validate widely used theories in behavioral cybersecurity research that imply patterns of behavior within a given person over time and (2) provide distinct theoretical insights on behavioral cybersecurity phenomena by accounting for such within-person patterns. To these ends, we apply an idiographic approach to an established theory in behavioral cybersecurity research—neutralization theory—and empirically test a within-person variant of this theory using a four-week experience sampling study. Our results support a more granular application of neutralization theory in the cybersecurity context that considers the behavior of a given person over time. We conclude the paper by highlighting the contexts and theories that provide the most promising opportunities for future behavioral cybersecurity research using an idiographic approach.

BASIC PSYCHOLOGICAL NEEDS, MOTIVATION, AND FOREIGN LANGUAGE VOCABULARY LEARNING STRATEGIES AND SKILLS OF INDONESIAN UNIVERSITY STUDENTS

Foreign language vocabulary learning can be pursued if the students have motivation and interest in which psychological factors play an important role in enacting learning strategies toward increased skills. This study aims to examine the integrated process model of the BasicPsychological Needs (BPN) variable as a behavioural phenomena in relation to autonomous and controlled motivation individually or collectively toward Vocabulary Learning Strategies (VLSs) and Vocabulary Skills (VSs). A total of 186 students of one university participated in this research. The Basic Psychological Needs of Second Language Scale (BPNSLS) was employed to assess the BPN, meanwhile the Self-Determination Theory of Second Language Scale (SDTSLS) was to assess the autonomous and controlled motivation. There are three questionnaires (BPNSLS, SDTSLS, VLSs) were adopted and adapted of the previous study. The fourth research instrument was Vocabulary Level Test (VLT) version b to assess vocabulary skills. A partial least square was used to contest the research model. The structural model of the relationship between the variables of basic psychological needs, self-determination theory, vocabulary learning strategies, and vocabulary mastery, revealed that vocabulary learning strategies play a crucial role in looking at the influence of motivational orientation on vocabulary skills described in the proposed model. This study suggests that further research can explore more on how motivation relates to learning strategies in general and comparing between autonomous versus controlled motivation.

Potential of the Blue Calm® food supplement in the treatment of alcohol withdrawal-induced anxiety in adult zebrafish (Danio rerio)

Alcohol use disorder (AUD) is characterized by a set of behavioral, cognitive, nutritional, and physiological phenomena derived from the uncontrolled use of alcoholic beverages. There are cases in which AUD is associated with anxiety disorder, and when untreated, it requires careful pharmacotherapy. Blue Calm® (BC) is a food supplement indicated to aid restorative sleep, which has traces of medicinal plant extracts, as well as myo-inositol, magnesium bisglycinate, taurine, and L-tryptophan as its main chemical constituents. In this context, this study aimed to evaluate the potential of the BC in the treatment alcohol withdrawal-induced anxiety in adult zebrafish (aZF). Initially, BC was submitted to antioxidant activity against 2,2-diphenyl-1-picrylhydrazyl radical. Subsequently, the aZF (n = 6/group) were treated with BC (0.1 or 1 or 10 mg/mL; 20 μL; p.o.), and the sedative effect and acute toxicity (96 h) were evaluated. Then, the anxiolytic-like effect and the possible GABAergic mechanism were analyzed through the Light & Dark Test. Finally, BC action was evaluated for treating alcohol withdrawal-induced anxiety in aZF. Molecular docking was performed to evaluate the interaction of the major chemical constituents of BC with the GABAA receptor. BC showed antioxidant potential, a sedative effect, was not toxic, and all doses of BC had an anxiolytic-like effect and showed potential for the treatment of alcohol withdrawal-induced anxiety in aZF. In addition to the anxiolytic action, the main chemical constituents of BC were confirmed in the molecular docking, thus suggesting that BC is an anxiolytic that modulates the GABAergic system and has pharmacological potential for the treatment of alcohol withdrawal-induced anxiety.

Parent–child couples display shared neural fingerprints while listening to stories

Neural fingerprinting is a method to identify individuals from a group of people. Here, we established a new connectome-based identification model and used diffusion maps to show that biological parent–child couples share functional connectivity patterns while listening to stories. These shared fingerprints enabled the identification of children and their biological parents from a group of parents and children. Functional patterns were evident in both cognitive and sensory brain networks. Defining “typical” shared biological parent–child brain patterns may enable predicting or even preventing impaired parent–child connections that develop due to genetic or environmental causes. Finally, we argue that the proposed framework opens new opportunities to link similarities in connectivity patterns to behavioral, psychological, and medical phenomena among other populations. To our knowledge, this is the first study to reveal the neural fingerprint that represents distinct biological parent–child couples.

Examining changes in sexual lifestyles in Britain between 1990–2010: a latent class analysis approach

BackgroundUnderstanding sexual lifestyles and how they change over time is important for determining the likelihood of sexual health outcomes. Standard descriptive and regression methods are limited in their ability to capture multidimensional concepts such as sexual lifestyles. Latent Class Analysis (LCA) is a mixture modelling method that generates a categorical latent variable to derive homogenous groups from a heterogeneous population. Our study investigates (1) the potential of LCA to assess change over time in sexual lifestyles and (2) how quantifying this change using LCA compares to previous findings using standard approaches.MethodsProbability-sampled data from three rounds of the National Survey of Sexual Attitudes and Lifestyle (Natsal) were used, restricted to sexually active participants (i.e., those reporting sexual partners in the past year) aged 16–44 years (N1990 = 11,738; N2000 = 9,690; N2010 = 8,397). An LCA model was built from four variables: number of sexual partners (past year), number of partners without a condom (past year), age at first sex and self-perceived HIV risk. Covariates included age, ethnicity, educational attainment, same-sex attraction, and marital status. Multinomial regression analyses and Chi-Squared tests were used to investigate change over time in the size of each class.ResultsWe successfully used a LCA approach to examine change in sexual lifestyle over time. We observed a statistically significant increase between 1990 and 2010 in the proportion of men (χ2 = 739.49, p < 0.01) and women (χ2 = 1270.43, p < 0.01) in a latent class associated with reporting 2 or more partners in the last year, relatively high probabilities of reporting condomless sex partners, greater self-perceived HIV risk, and a high probability of first sex before age 16 years, increasing from 19.5% to 31.1% (men) and 9.9% to 22.1% (women).ConclusionOur results indicate the viability of LCA models to assess change over time for complex behavioural phenomena. They align with previous findings, namely changing sexual lifestyles in Britain in recent decades, partnership number driving class assignment, and significant sex differences in sexual lifestyles. This approach can be used to extend previous LCA models (e.g., to investigate the impact of COVID-19 on sexual lifestyles) and to support empirical evidence of change over time, facilitating more nuanced public health policy.

Sampling complex social and behavioral phenomena.

We comment on the limits of relying on prior literature when constructing the design space for an integrative experiment; the adaptive nature of social and behavioral phenomena and the implications for the use of theory and modeling when constructing the design space; and on the challenges of measuring random errors and lab-related biases in measurement without replication.

Exploring heart rate variability in alcohol-dependent subjects using frequency-domain analysis

Background: Alcohol-seeking behavior despite being aware of its adverse effects is defined as alcohol dependence (AD). AD syndrome is a cluster of physiological, behavioral, psychological, and perceptual phenomena that develop subsequent to chronic alcohol ingestion. Ethanol is a potent central nervous system depressant that causes toxic damage to the vasomotor and cardiac autonomic nerve fibers which leads to autonomic imbalance leading to arrhythmias and sudden cardiac deaths. Recording and analyzing the heart rate variability (HRV) using the frequency-domain method delineate the autonomic imbalance in alcoholic individuals which may be due to reduced parasympathetic activity and/or sympathetic hyperactivity. Aims and Objectives: The aim of the study was to assess and compare the cardiac autonomic function between the AD group and the non-alcoholic control group using the frequency domain method of HRV. Materials and Methods: A total of 55 alcohol-dependent individuals in the age group of 20–55 years were selected from the psychiatry outpatient department, based on the International Classification of Diseases-10 (Diagnostic and Statistical Manual -IV) criteria as the study population. Fifty-five age and gender-matched healthy volunteers from the master health check-up scheme from the Department of Community Medicine were selected as the control population. Institutional Ethical Committee clearance was obtained. After obtaining informed written consent from the individuals, the short-term 5 min HRV was recorded in the supine position with eyes closed. The results were analyzed and interpreted. Statistical analysis was done using the software Statistical Package for the Social Sciences version 21.0. Results: The frequency domain parameters high frequency (HF) which is a specific marker of parasympathetic activity was significantly reduced, and low frequency (LF) which is a marker of sympathetic activity was significantly increased in the alcoholic group compared to the non-alcoholic group, respectively. The LF: HF ratio which denotes sympathetic-vagal balance was increased in the alcohol-dependent group. Conclusion: HF was decreased, LF and LF: HF ratio was increased in alcoholic-dependent individuals indicating autonomic imbalance with reduced parasympathetic activity and increased sympathetic activity which suggests that alcohol affects the cardiac autonomic status. This concludes that the frequency domain method of HRV could be used as a short-term non-invasive test to assess cardiac autonomic dysfunction in alcohol-dependent individuals.

Risk preference as an outcome of evolutionarily adaptive learning mechanisms: An evolutionary simulation under diverse risky environments.

The optimization of cognitive and learning mechanisms can reveal complicated behavioral phenomena. In this study, we focused on reinforcement learning, which uses different learning rules for positive and negative reward prediction errors. We attempted to relate the evolved learning bias to the complex features of risk preference such as domain-specific behavior manifests and the relatively stable domain-general factor underlying behaviors. The simulations of the evolution of the two learning rates under diverse risky environments showed that the positive learning rate evolved on average to be higher than the negative one, when agents experienced both tasks where risk aversion was more rewarding and risk seeking was more rewarding. This evolution enabled agents to flexibly choose more reward behaviors depending on the task type. The evolved agents also demonstrated behavioral patterns described by the prospect theory. Our simulations captured two aspects of the evolution of risk preference: the domain-specific aspect, behavior acquired through learning in a specific context; and the implicit domain-general aspect, corresponding to the learning rates shaped through evolution to adaptively behave in a wide range of environments. These results imply that our framework of learning under the innate constraint may be useful in understanding the complicated behavioral phenomena.

A study on eye movement test and visuospatial optimization of wayfinding perception in large-scale comprehensive transportation hubs

Abstract The integration of rail transit stations and the surrounding underground space presents volume scale and functional complexity, and it has gradually formed a complex integrated transportation hub. Wayfinding inside its space is also more difficult, and the behavioral phenomena of passengers stopping, wandering, and getting lost are common. This paper uses station A of a large transportation hub as an example. It combines target detection technology and the optical flow method, designs the traffic space guidance system, tests how well passengers can find their way by moving their eyes, and then looks at how the visual space can be improved in terms of color, comfort, and subjective comfort after getting feedback. The data from the passenger eye-movement test reveals that during the sub-processes of information perception and elevator path selection, the logo is the primary focus, with attention ratios of 72.35% and 61.28%. Orange, yellow, and green were the three colors that received the highest ratings for subjective spatial comfort from passengers, with ratings of 0.58, 0.55, and 0.35, respectively, which are data-supported for visuospatial optimization.

Dynamics of travel decision-making between organized packaged tourists and backpackers

Tourists are different in terms of their purpose of travel, the tourist type, the number of days spent, and how they spend time in a destination. Tourist decision-making models attempt to conceptualize how tourists make decisions during their pre-travel, onsite experiences, and post-travel stages. These models, including the grand models of tourist behavior, have paved the way to broaden our understanding of this complex behavioral phenomenon. Despite their remarkable contributions to the existing knowledge, these models display some limitations in terms of complexity, general nature of explanations, poor empirical support, and lack of consideration of different traveler types. Further examinations are necessary to understand the dynamic nature of decisions that take place under each broader stage. This study attempted to address some of these limitations through a qualitative inquiry with a comparison of tourist decision-making between two mainstream traveler types i.e. organized package tourists and backpackers. The findings uncovered empirical evidence to propose a research proposition that a general travel decision-making model cannot be derived for different traveler types and certain alterations need to be done with reference to different traveler types. These findings contribute to the literature on tourist behavior by inviting scholars to revisit the existing models in light of different traveler types.

Community Empowerment Through Community Tourism in Efforts to Develop Tourism in The Village of Kemenuh, Gianyar District (Study on Sumampan Waterfall Tourism)

The problem faced by Kemenuh Village in developing tourism is that all elements and actors of tourism development are not yet organized. Efforts must be made to overcome these problems through community empowerment programs. This community service aims to empower the community through community-based tourism, aimed at developing tourism in Kemenu village, Gianyar district. The type of research used is qualitative research which uses a descriptive approach to obtain a comprehensive understanding of behavioral phenomena, cognition, motivation, behavior and so on experienced by research subjects. The data sources used are primary data sources and secondary data sources. The implementation of community-based tourism as an effort to develop the Sumapang Waterfall tourist attraction has proven to be very effective. Forms of community participation in the management of Sumapang Waterfall have played an active role, including community participation in the form of ideas in the early stages of establishing the management of Sumapang Waterfall. Large community participation is manifested in the form of a gate that marks the entrance to Sumapang Waterfall. Community participation in the form of energy, namely mutual cooperation activities carried out every week