Sex differences in physiological correlates of affectively driven decision-making behavior in adult ADHD.

BACKGROUND: Sex differences in the symptomatology of adults with attention-deficit/hyperactivity disorder (ADHD) have often been overlooked when studying behavioral abnormalities. However, it is known that women exhibit considerably more stronger symptoms related to emotional competence than men. Since affective functions significantly influence the processing of risky decision-making and risk-engagement, we assume that risky behavior in ADHD is affected by sex differences. Therefore, we specifically investigated sex-specific effects on the interaction between emotionally induced changes in physiology and behavioral performance on a decision-making task. METHODS: Skin conductance responses of twenty-nine adults with ADHD (n = 16 male; n = 13 female) and thirty-three adults in the control group (n = 14 male; n = 19 female) were recorded during the performance in a modified version of the Balloon Analogue Risk Task (BART). Additional questionnaires were used to reveal insights in the self-assessment of emotional competence, risk perception, and feedback sensitivity. Emotional arousal and decision-making behavior were analyzed using linear mixed-effects models. RESULTS: Results showed different effects of sex on risk behaviors in controls and ADHD. In contrast to healthy controls, female adults with ADHD showed a significantly greater risk engagement in the BART compared to males with ADHD. This contrary sex relation was not observed in skin conductance responses and revealed a significantly different sex-dependent correlation of body response and behavioral task performance in ADHD. Comparisons with results from self-assessments furthermore indicate a reduced behavioral self-perception in women with ADHD, but not in men. CONCLUSION: In summary, we found an altered interaction between physiological activity and risky behavior in women with ADHD. Thus, the present study indicates a reduced sensitivity towards the own bodily responses in women with ADHD, which could consequently cause increased risky DM behavior in daily life. The current results suggest that more consideration needs to be given to sex-specific effects on physiological processes and behavior in adults with ADHD.

Analysis of Lane-Changing Decision-Making Behavior of Autonomous Vehicles Based on Molecular Dynamics.

Along with the rapid development of autonomous driving technology, autonomous vehicles are showing a trend of practicality and popularity. Autonomous vehicles perceive environmental information through sensors to provide a basis for the decision making of vehicles. Based on this, this paper investigates the lane-changing decision-making behavior of autonomous vehicles. First, the similarity between autonomous vehicles and moving molecules is sought based on a system-similarity analysis. The microscopic lane-changing behavior of vehicles is analyzed by the molecular-dynamics theory. Based on the objective quantification of the lane-changing intention, the interaction potential is further introduced to establish the molecular-dynamics lane-changing model. Second, the relationship between the lane-changing initial time and lane-changing completed time, and the dynamic influencing factors of the lane changing, were systematically analyzed to explore the influence of the microscopic lane-changing behavior on the macroscopic traffic flow. Finally, the SL2015 lane-changing model was compared with the molecular-dynamics lane-changing model using the SUMO platform. SUMO is an open-source and multimodal traffic experimental platform that can realize and evaluate traffic research. The results show that the speed fluctuation of autonomous vehicles under the molecular-dynamics lane-changing model was reduced by 15.45%, and the number of passed vehicles was increased by 5.93%, on average, which means that it has better safety, stability, and efficiency. The molecular-dynamics lane-changing model of autonomous vehicles takes into account the dynamic factors in the traffic scene, and it reasonably shows the characteristics of the lane-changing behavior for autonomous vehicles.

Sex differences and the modulating effects of gonad intactness on behavioral conformity in a mouse model.

Although gender differences in conformity are noticed in human studies, cultural norms and psychosocial factors inevitably affect such differences. Biological factors, especially the gonadal hormones and the brain regions involved, contributing to the sex differences in behavioral conformity remained scarcely explored. To prevent psychosocial and cultural norm confounds, intact and gonadectomized male and female mice were used to assess the modulating effects of gonadal hormones on behavioral conformity and such conformity-related brain regions using an approach of choice paradigm. Intact and gonadectomized mice' choices for the nonrewarded runway were assessed when these experimental mice were alone versus with a group, consisting of three same-sex noncagemates choosing the respective experimental mice' nonrewarded runway, in a double-J-shaped maze test. Although male and female mice exhibited comparable rewarded runway choices at the conclusion of the operant training procedures and in the test individually, male mice demonstrated greater conformity index as compared to female mice when group tested. Gonadectomy, done at their 4 or 9 weeks of age, decreased males' conformity index but did not affect females' when both sexes were group tested. Such gonadectomy did not affect the conditioning or conformity index when tested individually in either sex. Female mice had higher serum corticosterone (CORT) levels when group tested as compared to the female mice tested individually and male mice. Finally, the number of FOS-staining cells in high conformity-displaying mice was found less than it in the low conformity-performing mice in the nucleus accumbens. Taken together, we conclude that testis-derived hormones, at least, play a role in enhancing behavioral conformity in male mice. CORT and nucleus accumbal neuronal activity deserve further investigation for their involvement in behavioral conformity.

Research on the tripartite evolutionary game promoting the transformation of traditional buildings to prefabricated buildings.

The practices of prefabricated buildings illustrate the incentives in prefabricated markets as well as the decision-making behavior of stakeholders, which can influence the transformation, upgrading, and sustainability of the buildings sector. The game between the stakeholders in the prefabricated buildings market becomes complicated by the fact that they dynamically adjust their strategies in response to changing market conditions. With the aim of quantitatively studying the implications of the dynamic decision behavior of prefabricated construction stakeholders on the prefabricated construction market, this study introduces component suppliers as participating agents and government subsidies and penalties as the main measures. And a three-way model of the evolutionary game involving government subsidies and punitive schemes is constructed by this study. The essay examines the evolutionary equilibrium strategies of each game subject as well as the effect of original strategies and different parameter choices on the decision-making of each subject using MATLAB. The findings reveal that (1) decision-making behaviors among the government, component suppliers, and developers are both interrelated and constrained, but governments are the dominant agents in the evolution of prefabricated buildings. (2) Parameters such as subsidies, penalties, costs, and benefits affect the stability of the tripartite evolutionary model, which remains consistent with the previous research. (3) Component suppliers have an equally important position in the development of prefabricated buildings as recognized entities such as developers and contractors. (4) When subsidies are kept at 40% of the incremental cost and penalties at 80% of the incremental cost, the model combines a fast evolutionary rate with stable model evolution. In conclusion, the article's research findings not only validate the rationality and feasibility of component suppliers as research subjects and confirm the importance of component suppliers but also propose a more reasonable boundary value for penalties and subsidies, which provides a reference for the government to improve the incentive and punishment measures as well as the dynamic adjustment strategy of stakeholders and also provides a new perspective to achieve the goal of sustainable development of construction.

Altered interaction of physiological activity and behavior affects risky decision-making in ADHD.

Background: Adult attention-deficit/hyperactivity disorder (ADHD) is often associated with risky decision-making behavior. However, current research studies are often limited by the ability to adequately reflect daily behavior in a laboratory setting. Over the lifespan impairments in cognitive functions appear to improve, whereas affective functions become more severe. We assume that risk behavior in ADHD arises predominantly from deficits in affective processes. This study will therefore aim to investigate whether a dysfunction in affective pathways causes an abnormal risky decision-making (DM) behavior in adult ADHD. Methods: Twenty-eight participants with ADHD and twenty-eight healthy controls completed a battery of questionnaires regarding clinical symptoms, self-assessment of behavior and emotional competence. Furthermore, skin conductance responses were measured during the performance in a modified version of the Balloon Analogue Risk Task. A linear mixed-effects model analysis was used to analyze emotional arousal prior to a decision and after feedback display. Results: Results showed higher emotional arousal in ADHD participants before decision-making (ß = -0.12, SE = 0.05, t = -2.63, p < 0.001) and after feedback display (ß = -0.14, SE = 0.05, t = -2.66, p = 0.008). Although risky behavior was greater in HC than in ADHD, we found a significant interaction effect of group and anticipatory skin conductance responses regarding the response behavior (ß = 107.17, SE = 41.91, t = 2.56, p = 0.011). Post hoc analyses revealed a positive correlation between anticipatory skin conductance responses and reaction time in HC, whereas this correlation was negative in ADHD. Self-assessment results were in line with the objective measurements. Conclusion: We found altered changes in physiological activity during a risky decision-making task. The results confirm the assumption of an aberrant relationship between bodily response and risky behavior in adult ADHD. However, further research is needed with respect to age and gender when considering physiological activities.

Analysis of Factors Influencing the Decision-Making Behavior of Beef Cattle Farmers: An Empirical Analysis Based on Logit-ISM Model.

The beef cattle industry is an important part of herbivorous animal husbandry and an important industry to enrich the dietary structure of residents and promote the income of farmers and herdsmen. The cow is an important foundation to support the healthy development of the beef cattle industry, which is related to the stability of cattle sources and the sustainable development of the industry. However, in recent years, the shortage of cows in our country has led to the shortage of cattle resources and the high price of calves, which has restricted the further development of our beef cattle industry. In order to explore the factors that affect the decision-making behavior behind cow breeding and to find the right policy to mobilize the enthusiasm for cow breeding, based on the field survey of five provinces (cities and regions), including Inner Mongolia Autonomous Region and Ningxia Hui Autonomous Region, this paper conducts an empirical analysis through the Logit ISM model. The results show that market expectation is the surface factor that directly affects the decision-making behavior of cow breeding. The influencing factors of the middle layer are policy propaganda, policy subsidies, breeding years, and feeding methods. The deep root factors are the age of the breeder, the amount of loan, and whether to plant feed crops. Based on this, this paper proposes that we should actively promote the importance of cow breeding, strengthen policy support for cow breeding, formulate scientific and reasonable subsidy policies for cows, innovate financial support methods to solve the problem of fund shortage of farmers, and develop forage resources and reduce the breeding cost of cows.

An Emerging Market: The Impact of User Selection on the Decision-Making Behavior of Mobile Medical Businesses in China.

Background: User selection is an important guarantee for the sustainable development of mobile medical businesses. Under the background of increasingly fierce competition, the decision-making behavior of mobile medical businesses will directly affect the choice of the behavior of users. Methods: The study constructs the decision-making behavior model of mobile medical business based on the user choice and adds the role of people in government. It uses the game method to explore the relationship between the government, mobile medical business, and users. Finally, it makes an example analysis. Empirical research is conducted to demonstrate the influence of different parameter changes on the results. Results: The results show that in the absence of government intervention, users' choice of filtering information will create a bad environment for mobile medical businesses, and further will be reduced, and the expected utility of businesses will not be affected causing a reduction in expected utility of companies. Similarly, government regulations can effectively improve the mobile medical environment and enhance the expected utility of mobile medical companies. Conclusion: The government needs to formulate relevant laws and regulations to ensure the orderly operation of the mobile medical market and strengthen government supervision. It is necessary to conduct publicity and education to protect the fundamental interests of users and businesses.

Sequential and efficient neural-population coding of complex task information.

Recent work has highlighted that many types of variables are represented in each neocortical area. How can these many neural representations be organized together without interference and coherently maintained/updated through time? We recorded from excitatory neural populations in posterior cortices as mice performed a complex, dynamic task involving multiple interrelated variables. The neural encoding implied that highly correlated task variables were represented by less-correlated neural population modes, while pairs of neurons exhibited a spectrum of signal correlations. This finding relates to principles of efficient coding, but notably utilizes neural population modes as the encoding unit and suggests partial whitening of task-specific information where different variables are represented with different signal-to-noise levels. Remarkably, this encoding function was multiplexed with sequential neural dynamics yet reliably followed changes in task-variable correlations throughout the trial. We suggest that neural circuits can implement time-dependent encodings in a simple way using random sequential dynamics as a temporal scaffold.

A Novel Recurrent Neural Network to Classify EEG Signals for Customers' Decision-Making Behavior Prediction in Brand Extension Scenario.

It was meaningful to predict the customers' decision-making behavior in the field of market. However, due to individual differences and complex, non-linear natures of the electroencephalogram (EEG) signals, it was hard to classify the EEG signals and to predict customers' decisions by using traditional classification methods. To solve the aforementioned problems, a recurrent t-distributed stochastic neighbor embedding (t-SNE) neural network was proposed in current study to classify the EEG signals in the designed brand extension paradigm and to predict the participants' decisions (whether to accept the brand extension or not). The recurrent t-SNE neural network contained two steps. In the first step, t-SNE algorithm was performed to extract features from EEG signals. Second, a recurrent neural network with long short-term memory (LSTM) layer, fully connected layer, and SoftMax layer was established to train the features, classify the EEG signals, as well as predict the cognitive performance. The proposed network could give a good prediction with accuracy around 87%. Its superior in prediction accuracy as compared to a recurrent principal component analysis (PCA) network, a recurrent independent component correlation algorithm [independent component analysis (ICA)] network, a t-SNE support vector machine (SVM) network, a t-SNE back propagation (BP) neural network, a deep LSTM neural network, and a convolutional neural network were also demonstrated. Moreover, the performance of the proposed network with different activated channels were also investigated and compared. The results showed that the proposed network could make a relatively good prediction with only 16 channels. The proposed network would become a potentially useful tool to help a company in making marketing decisions and to help uncover the neural mechanisms behind individuals' decision-making behavior with low cost and high efficiency.

Self-reported daily sleep quality modulates the impact of the framing effect on outcome evaluation in decision-making under uncertainty: An ERP study.

A growing body of research has largely confirmed and supported the idea that experimental sleep loss, such as sleep deprivation or sleep restriction, could affect individuals' risk-taking behavior and brain activity. However, whether self-reported sleep quality resulting from daily life modulates how feedback is evaluated during decision-making is still unclear. In this study, we used event-related potentials (ERPs) with a Balloon Analogue Risk Task (BART) to investigate how self-reported daily sleep quality modulates the brain's response to feedback from decision-making in the gain and loss frames. Behavioral data showed an increased aversion to uncertainty in the gain frame relative to the loss frame for individuals with higher sleep quality. However, this was not true for individuals with lower voluntary sleep quality. Similarly, the ERP data demonstrated that individuals with lower self-reported daily sleep quality displayed no changes in feedback-related negativity (FRN) in response to outcomes from decision-making in the gain and loss frames; however, individuals with higher self-reported daily sleep quality showed a greater FRN in response to decision-making in the gain frame than that in the loss frame. A Pearson correlation analysis showed that self-reported daily sleep quality was positively related to the variance of the FRN amplitude in response to the gain and loss frames. These findings suggest that framing effects on decision-making under uncertainty may depend on self-reported daily sleep quality and that the effects disappear when the sleep quality declines.

Exploring the valence-framing effect: Gain frame enhances behavioral and brain sensitivity to the failure of decision-making under uncertainty.

The framing effect, which is one of the cognitive biases, can play a major role in changing preferences and the decision-making process. However, whether the gain and loss frames modulate the evaluation of feedback during decision-making is still unclear. In this study, we used event-related potentials (ERPs) with a Balloon Analogue Risk Task (BART) paradigm to examine the effects of a gain and loss frame on the evaluation of feedback during the decision-making process of the brain. Behavioral data showed an increased uncertainty-aversion, especially after receiving negative feedback (balloon explosion) during the completion of the BART in the gain frame relative to the loss frame. The ERP data demonstrated a more negative feedback-related negativity (FRN) after receiving negative feedback in the gain frame relative to the loss frame. Additionally, the FRN amplitude elicited by the negative feedback correlated with the future decision-making behavior in both the gain and loss frames. These findings demonstrated that, in comparison to the loss frame, the gain frame increased behavior and brain sensitivity to the failure of decision-making under uncertainty.

Paying out one versus paying out all trials and the decrease in behavioral and brain activity in the Balloon Analogue Risk Task.

Both pay out for all the trials (pay-all) and pay out for only one randomly selected trial (pay-one), are widely used in economics experiments to elicit choices from study participants. However, whether pay-all and pay-one payments modulate risk-taking and decision-making in the same manner remains controversial. In the present study, we used event-related potentials (ERPs) with the Balloon Analogue Risk Task (BART) to investigate the effects of the pay-all and pay-one payments on dynamic sequential decision-making behavior under uncertainty and brain activity. Behavioral data showed an increased uncertainty aversion, especially after negative feedback (balloon explosion) during the BART in the pay-all condition, as compared to those in the pay-one condition. The ERP data demonstrated a larger feedback-related negativity (FRN) in response to the balloons that exploded during decision-making in the pay-all condition, as compared to those in the pay-one condition. In addition, in the pay-all condition, the FRN amplitude elicited by the explosion of the balloon correlated with the future decision-making behavior, although this correlation was not observed in the pay-one condition. In contrast, the P300 component was unresponsive to payment method manipulation. These findings demonstrate the differential effects of the pay-all versus the pay-one payments on decision-making behavior under uncertainty and brain activity, suggesting that the payment method plays an important role in dynamic decision-making studies.

Altruistic Behavior Depending on Opponents' Body Weight: An Experimental Approach.

BACKGROUND: Obesity is a worldwide public health issue, not only because it is associated with numerous comorbid diseases but also because of its impact on the social level. This study aims to investigate (a) whether altruistic behavior differs between people with obesity and people who are not obese, (b) altruistic behavior toward people who are obese, in particular, women who are obese, and (c) implicit and explicit attitudes toward people with obesity as predictors for divergent altruistic behavior. METHODS: An experimental approach called the dictator game was applied. In total, 168 participants of normal weight were asked to divide a monetary reward between themselves and two opponents, one person who was obese and one with normal weight. In addition, participants' implicit and explicit attitudes toward people with obesity as well as other sociodemographic data were assessed. RESULTS: We found that altruistic behavior did not differ between obese and nonobese opponents (t(166) = -0.57, p = 0.71), nor did we find less altruistic attitudes toward women with obesity (t(85) = -0.03, p = 0.39). Linear regression models show less altruistic behavior among people with stronger explicit antifat attitudes (p = 0.015). However, although we found that participants held implicit attitudes toward people with obesity, these attitudes did not predict altruistic behavior toward people with obesity. CONCLUSION: Although numerous studies reported discrimination toward people with obesity in several areas of life, we did not find discrimination in form of less altruistic behavior toward people with obesity. Moreover, although we found implicit antifat attitudes among the participants, these attitudes did not predict altruistic behavior toward people of divergent weight groups. Therefore, future research should investigate more intensively the diverse facets of discrimination toward people with obesity, if and to what extent implicit antifat attitudes have a quantifiable impact on the stigmatization and or discrimination process, and the hypotheses in a more hidden way, since manipulation check revealed that the majority of participants anticipated the underlying idea of the dictator game.

A decision-making model based on a spiking neural circuit and synaptic plasticity.

To adapt to the environment and survive, most animals can control their behaviors by making decisions. The process of decision-making and responding according to cues in the environment is stable, sustainable, and learnable. Understanding how behaviors are regulated by neural circuits and the encoding and decoding mechanisms from stimuli to responses are important goals in neuroscience. From results observed in Drosophila experiments, the underlying decision-making process is discussed, and a neural circuit that implements a two-choice decision-making model is proposed to explain and reproduce the observations. Compared with previous two-choice decision making models, our model uses synaptic plasticity to explain changes in decision output given the same environment. Moreover, biological meanings of parameters of our decision-making model are discussed. In this paper, we explain at the micro-level (i.e., neurons and synapses) how observable decision-making behavior at the macro-level is acquired and achieved.

Nucleus accumbens shell moderates preference bias during voluntary choice behavior.

The nucleus accumbens (NAc) shell lies anatomically at a critical intersection within the brain's reward system circuitry, however, its role in voluntary choice behavior remains unclear. Rats with electrolytic lesions in the NAc shell were tested in a novel foraging paradigm. Over a continuous two-week period they freely chose among four nutritionally identical but differently flavored food pellets by pressing corresponding levers. We examined the lesion's effects on three behavioral dynamics components: motivation (when to eat), preference bias (what to choose) and persistence (how long to repeat the same choice). The lesion led to a marked increase in the preference bias: i.e., increased selection of the most-preferred choice option, and decreased selection of the others. We found no effects on any other behavioral measures, suggesting no effect on motivation or choice persistence. The results implicate the NAc shell in moderating the instrumental valuation process by inhibiting excessive bias toward preferred choice options.