Aberrant orbitofrontal cortex reactivity to erotic cues in Compulsive Sexual Behavior Disorder

Background and aimsCompulsive Sexual Behavior Disorder (CSBD) is characterized by increased reactivity to erotic reward cues. Cue-encoded reward parameters, such as type (e.g. erotic or monetary) or probability of anticipated reward, shape reward-related motivational processes, increase the attractiveness of cues and therefore might enhance maladaptive behavioral patterns in CSBD. Studies on the neural patterns of cue processing in individuals with CSBD have been limited mainly to ventral striatal responses. Therefore, here we aimed to examine the cue reactivity of multiple key structures in the brain's reward system, taking into account not only the type of predicted reward but also its probability.MethodsTwenty Nine men seeking professional help due to CSBD and 24 healthy volunteers took part in an fMRI study with a modified Incentive Delay Task with erotic and monetary rewards preceded by cues indicating a 25%, 50%, or 75% chance of reward. Analyses of functional patterns of activity related to cue type and probability were conducted on the whole-brain and ROI levels.ResultsIncreased anticipatory response to cues predictive of erotic rewards was observed among CSBD participants when compared to controls, in the ventral striatum and anterior orbitofrontal cortex (aOFC). The activity in aOFC was modulated by reward probability.Discussion and conclusionsType of anticipated reward (erotic vs monetary) affects reward-related behavioral motivation in CSBD more strongly than reward probability. We present evidence of abnormal aOFC function in CSBD by demonstrating the recruitment of additional subsections of this region by erotic reward cues.

Balanced release of neuropeptide FF and gonadotropin-releasing hormone 3 modulates male sexual behavior

Animals properly perform sexual behaviors by using multiple sensory cues. However, neural mechanisms integrating multiple sensory cues and regulating motivation for sexual behaviors remain unclear. Here, we focused on peptidergic neurons, terminal nerve gonadotropin-releasing hormone (TN-GnRH) neurons, which receive inputs from various sensory systems and co-express neuropeptide FF (NPFF) in addition to GnRH. Our behavioral analyses using knockout medaka of GnRH (gnrh3) and/or NPFF (npff) demonstrated that some sexual behavioral repertoires were 'delayed', not disrupted, in gnrh3-/- and npff-/- males, while the double knockout showed normal behaviors. We also found anatomical evidence to show that both neuropeptides modulate the sexual behavior-controlling brain areas. Furthermore, we demonstrated that NPFF activates neurons in the preoptic area via indirect pathway, which is considered to induce the increase in the motivation for male sexual behaviors. Considering these results, we propose a novel mechanism by which balanced release of co-existing peptides is important for the neuromodulatory function of TN-GnRH neurons in the control of behavioral motivation. Our results may go a long way toward understanding the functional significance of peptidergic neuromodulation in response to external environments.

A behavioral propagation and competition model based on pressure

The influence of node behavior by the relevant group behavior in complex networks is a topic of recent interest. In order to measure the direct and indirect influence of the neighborhoods, the behavioral propagation and competition model was established based on the pressure. The pressure is described by the impact of group behavior on nodes, which is related to the length and number of reachable paths between two nodes for measuring the nodal behavioral influence. In addition, the pressure range has an effect on the pressure. By modeling and analyzing the change of nodes motivation and the rules of behavioral propagation, and numerical simulations are performed on the small-world networks and the scale-free networks. The results show that pressure is the major factor in the node behavioral motivation, where the pressure generated from behavior in related group network is dependent on the relative location and number of participators. At the same time, network structure also plays an important role at behavior propagation process. Further, competition arises when multiple behaviors are spread among people, while winning behaviors are widely spread among people.

Modeling and analysis of motivation-driven network behavior communication

This paper presents a new SIRI propagation model based on SIR model. Behavioral motivation value and neighbor infection number influence value were added to the model to study the effects of these two quantities on behavior transmission. In order to make the model closer to the real situation, self-motivation value and neighbor influence value are added to the behavior motivation value. Compared with previous studies, our proposed experimental model is closer to the real world, improves the possibility of behavior prediction, and is validated by simulation. Finally, this paper takes Lanzhou Polytechnic University campus cartoon consumption data as an example to test and validate the model.

Towards a Standard Model of the Cognitive Science of Nationalism – the Calendar

The Cognitive Science of Nationalistic Behavior (CSNB), presented in this paper, integrates the political sciences of nationalities as invented communities with an evolutionary cognitive analysis of social forms as products of the human mind. The framework is modeled after the Cognitive Science of Religion, where decades of cross-disciplinary work has generated standards, predictions, and data about the role of individual cognitive tendencies in shaping societies. We study the nationalistic calendar as a cultural attractor and draw on cue-based behavioral motivation and differential autobiographical memory systems to explain its appeal to the human mind. Calendrical elements are analyzed in the context of essentialist thought patterns and action representation systems. We conclude with the implications of calendrical thinking on the control of elites who aim to forge and reinforce national identities. This paper lays the groundwork for applying a similar approach to the study of other nationalistic elements.

Bi-directional encoding of context-based odor signals and behavioral states by the nucleus of the lateral olfactory tract neurons

The nucleus of the lateral olfactory tract (nLOT) is not only a part of the olfactory cortex that receives olfactory sensory inputs from the olfactory bulb, but also one of the cortical amygdala areas that regulates motivational behaviors. To examine how the neural ensemble activity of the nLOT is modulated by motivational processes that occur during various states of learned goal-directed behaviors, we recorded nLOT spike activities of mice performing odor-guided go/no-go tasks for obtaining a water reward. We found that the majority of the nLOT neurons exhibited sharp go-cue excitation and persistent no-go-cue inhibition responses triggered by an odor onset. The bi-directional cue encoding introduced nLOT population response dynamics and provided a high odor decoding accuracy before executing cue-odor-evoked behaviors. The go-cue preferred neurons were also activated in the reward drinking state, indicating context-based odor-outcome associations. These findings suggest that the nLOT neurons play an important role in the translation from context-based odor information to appropriate behavioral motivation.

A lab test on the decision not to decide

Decisions are often postponed even when future profits are not expected to compensate for the losses. This is especially relevant for financial and entrepreneurial disinvestment choices, as investors often have a disposition to hold on to losing assets for too long. We use an experiment with real real-options to study one possible behavioral motivation. Studies in psychology suggest that individuals have different styles of handling the stress involved in making decisions. We find that participants' styles of decision-making and risk aversion as well as the interaction of those can assist in predicting the likelihood that the participants will make investments and the timing of their disinvestment decisions. We also find the overall structure of the findings to be in line with a planner–doer model.

An Analysis of the Employee Behavior on Sales in L'Oreal: A Case Study of Pakistan

This research is carried out to investigate the most important traits of employee behavior. A quantitative approach was employed for this study. Data were collected from 120 participants using an online questionnaire. These participants are active users of Facebook who are residents of Pakistan and currently working on L'Oreal Pakistan, who are at a different position in L'Oreal Pakistan. Statistical analysis, such as binomial regression which is used for qualitative analysis used together with descriptive analysis, was used to 'assess factors affecting employee behavior in L'Oreal Pakistan. The findings of the research show that the independent variable is indicators of leadership and reward has changed the behavioral motivation of company employees and this motivational, behavioral change has a positive impact on sales of L'Oreal Pakistan. This research investigated the factors which industry can use as a tool to change their employee behavior and sales. This will help to gain increasing generous offers and valuable insights to marketing practitioners and academics.

INTELLIGENT SERVICE PUSH METHOD BASED ON ACTIVE GEOGRAPHIC PERCEPTION

In view of the lack of consideration of user behavior motives in traditional personalized precision service systems, the accuracy of service content is not high.In order to solve this problem, research on personalized accurate service push method based on active geographic perception. By constructing a geographic feature information model, get the characteristics of the user's destination in real time, and then infer the user's behavioral motivation. Focusing on active geographic awareness technology and personalized precision service methods, the concept, principle, process and key technologies of active geographic sensing are studied, determined the main research content of active geographic perception and the relationship. Then analyze and discuss the construction method of active geographic awareness architecture, developed a geographic feature content system and studied its extraction and weight calculation methods. By the way, according to the characteristics of active geo-sensing, an active awareness API conforming to high efficiency and real-time is designed. Then explored the personalized accurate service push method based on active geographic perception,designed three processes of geographic awareness, service retrieval and service push, a service retrieval and delivery method is proposed. Finally, a personalized precise service system based on active geographical perception is designed. By adding geographic features to the personalized precision service, it can make up for the lack of service personalization and lack of precision caused by ignoring user motivation, which provides a new idea for more accurate and personalized service push.