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This study investigated the neural substrate of processing gesture-speech semantic variation which arises when the same entity word is uttered along with an iconic gesture that depicts object knowledge or event knowledge of the entity concept, or with a beat gesture that enacts a rhythmic movement, or with a grooming gesture. The fMRI results attested that the observation of gestures with speech, as compared to speech alone, centers on the high-level visual processing and recognition of complex stimuli in the bilateral fusiform gyrus, and the association of various sensory information in spatio-motoric and semantic processing of the inputs in the left inferior/superior parietal gyrus, upon which multiple functional networks are engaged in response to cross-modal semantic variation. The visuo-sensorimotor network of gesture processing with speech does not resemble the processing of hand actions on real objects in the frontal and parietal lobes for the recognition of object-directed motor acts.

Abstract With recent proposal suggesting the multifaceted nature of impulsivity, researchers have been intrigued by the question of whether the impulsive behaviour measured in the traditionally psychological paradigms is unitary. One such paradigm, the differential reinforcement of low-rate responding (DRL), has been used to assess response inhibition, but its underlying mechanism has still been debated. In present research, we examined and differentiated the effects of both response inhibition and interval timing on a multisession DRL-10 s (DRL-10 s) in a large sample of normally developing young adults, as well as with three other measures including the stop-signal reaction task (SSRT), time production task-10 s (TPT-10 s), and the Barrett impulsivity scale-11 (BIS-11). The results showed that behavioural changes existed in DRL. As the task sessions progressed, there was an increase in both reinforcement probability and peak time, but a decrease in burst responses. Most importantly, both principal component analysis and generalized multilevel modeling yielded consistent results that as the task progressed, there was an increasing involvement of the TPT in the late sessions of DRL. However, none of the effect of SSRT was found. In sum, the differential degrees of involvement of the timing process, relative to response inhibition, were observed in DRL.

This paper empirically studies the extent to which career concerns as part of a typical contract offer influence employees' work performance in a Japanese auto dealership firm. Because career movements and base-wage adjustments rely on performance evaluation over time, we develop a dynamic structural model that allows concerns for future payoffs to impact an employee's current work effort. A reform in personnel-management policies of the firm during the data period enables us not only to compare the performances across individuals, but also to compare within an individual the performance before and after the reform—this enhances the model identification. Our estimation results show that the added value from career movements on top of the monetary payoffs is more important than the monetary payoffs. Individuals respond to career movements and commissions differently, mainly due to varying cost of effort and different payoffs from career movements. Our counterfactual exercises suggest that, compared with the scenario when there is only monetary compensation, adding career movements in a contract package will greatly improve the firm's gross profit. The firm can improve its net profit by making commission and promotion more performance-based. This paper was accepted by Matt Shum, marketing. Funding: Financial support from the Social Sciences and Humanities Research Council of Canada [Grant 20190410-01] is gratefully acknowledged. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4956. [ABSTRACT FROM AUTHOR]

The development and refinement of functional brain circuits crucial to human cognition is a continuous process that spans from childhood to adulthood. Research increasingly focuses on mapping these evolving configurations, with the aim to identify markers for functional impairments and atypical development. Among human cognitive systems, nonsymbolic magnitude representations serve as a foundational building block for future success in mathematical learning and achievement for individuals. Using task‐based frontoparietal (FPN) and salience network (SN) features during nonsymbolic magnitude processing alongside machine learning algorithms, we developed a framework to construct brain age prediction models for participants aged 7–30. Our study revealed differential developmental profiles in the synchronization within and between FPN and SN networks. Specifically, we observed a linear increase in FPN connectivity, concomitant with a decline in SN connectivity across the age span. A nonlinear U‐shaped trajectory in the connectivity between the FPN and SN was discerned, revealing reduced FPN‐SN synchronization among adolescents compared to both pediatric and adult cohorts. Leveraging the Gradient Boosting machine learning algorithm and nested fivefold stratified cross‐validation with independent training datasets, we demonstrated that functional connectivity measures of the FPN and SN nodes predict chronological age, with a correlation coefficient of.727 and a mean absolute error of 2.944 between actual and predicted ages. Notably, connectivity within the FPN emerged as the most contributing feature for age prediction. Critically, a more matured brain age estimate is associated with better arithmetic performance. Our findings shed light on the intricate developmental changes occurring in the neural networks supporting magnitude representations. We emphasize brain age estimation as a potent tool for understanding cognitive development and its relationship to mathematical abilities across the critical developmental period of youth. Practitioner Points: This study investigated the prolonged changes in the brain's architecture across childhood, adolescence, and adulthood, with a focus on task‐state frontoparietal and salience networks.Distinct developmental pathways were identified: frontoparietal synchronization strengthens consistently throughout development, while salience network connectivity diminishes with age. Furthermore, adolescents show a unique dip in connectivity between these networks.Leveraging advanced machine learning methods, we accurately predicted individuals' ages based on these brain circuits, with a more mature estimated brain age correlating with better math skills. [ABSTRACT FROM AUTHOR]

Abstract Introduction Math anxiety severely impacts individuals’ learning and future success. However, limited is understood about the profile in East Asian cultures where students genuinely show high‐level math anxiety, despite that they outperform their Western counterparts. Here, we investigate the relation between math anxiety and math achievement in children as young as first and second graders in Taiwan. Further, we evaluate whether intensive exposure to digital game‐based learning in mathematics could ameliorate math anxiety. Methods The study first evaluated a group of 159 first and second graders’ math anxiety and its correlation with math performance. Subsequently, a quasi‐experimental design was adopted: 77 of the children continued and participated in multi‐component digital game training targeting enumeration, speeded calculation, and working memory. Post‐assessment was administered afterward for further evaluation of training‐associated effects. Results Results confirmed that math anxiety was negatively associated with school math achievement, which assessed numerical knowledge and arithmetic calculation. Furthermore, children's math anxiety was remarkably reduced via digital training in mathematics after 6‐week intensive remediation. Crucially, this math anxiety relief was more prominent in those with high‐level math anxiety. Although the children who underwent the training showed training‐induced math achievement and working memory enhancement, this cognitive improvement appeared to be independent of the math anxiety relief. Conclusion Our findings demonstrate that students can show highly negative emotions and perceptions toward learning even in high‐achieving countries. Auspiciously, the feeling of distress toward learning has the feasibility to be relieved from short‐term intensive training. Our study suggests a new approach of early treatments to emotional disturbance that can lead to permanent consequences in individuals.

We study the behavior of an individual avoiding peer information from a natural field experiment of charity crowdfunding. The unique experimental design enables us to employ an instrumental variable strategy to identify how the behavior influences individual giving to and promotion of charity campaigns. We find that, even with free access, 89% of individuals chose not to seek peer information. These individuals were less likely, whereas their peers were more likely to give and help promote in the past. The behavior would reduce the total distribution of campaigns by 8.5% and the total donation amount by 7.7%. A stylized model is used to illustrate how the pressure from peer comparison drives the individuals not to seek the information and how this behavior could influence giving and promoting behaviors of a group of marginal individuals. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: The project was supported by the National Natural Science Foundation of China [Grants 72103110]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4807. [ABSTRACT FROM AUTHOR]

We study dealer compensation in the indirect auto lending market that increases lender's market share and protects consumers from potential discrimination. We study dealer compensation in the indirect auto lending market, where most lenders give dealers the discretion to mark up interest rates and the markup constitutes a dealer's compensation. To protect consumers from potential discrimination by this dealer discretion, several banks adopted a policy that removes dealer discretion and compensates dealers by a fixed percentage of the loan amount. We document that this policy decreased (increased) the interest rates for low-credit (high-credit) consumers; however, the market share of these banks also decreased (increased) in low-credit (high-credit) segments—a reversal of the usual demand curve. This reversal highlights a significant influence of auto dealers on consumer choices. Accordingly, we develop an empirical model that features dealer-consumer bargaining. Our estimation results show systematically different levels of bargaining power across consumer groups. We use the model to explore alternative compensation schemes that remove dealer discretion. We find that a lump-sum compensation scheme obtains the most market share. In addition, the optimized lump-sum scheme improves consumer welfare compared with the adopted policy. Our study highlights the importance of accounting for the incentives and bargaining power of middlepersons. History: Puneet Manchanda served as the senior editor. Supplemental Material: The data files are available at https://doi.org/10.1287/mksc.2022.1418. [ABSTRACT FROM AUTHOR]

This paper studies the collaboration of talents in rank-order tournaments under incomplete information. This paper studies the collaboration of talents in rank-order tournaments. We use a structural matching model with unobserved transfers among participants to capture the differentiated incentives of participants that spur collaboration, with a specific focus on incorporating incomplete information and competition in the matching game. We estimate our model using data from a leading data science competition platform and recover the heterogeneous preferences and abilities of participants that determine whether and with whom they form teams. Overall, teamwork enhances performance and competition fosters collaboration, whereas incomplete information about potential coworkers' ability hinders collaboration. Using the estimation results, we conduct counterfactuals to investigate how the information on potential collaborators' ability and competitive pressure affect collaboration and performance outcome. Our results suggest that the platform could further improve collaboration and yield better outcomes by providing more informative signals of ability and further concentrating the allocation of rewards to top performers. History: K. Sudhir served as the senior editor for this article. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mksc.2022.1417. [ABSTRACT FROM AUTHOR]

Combustion in a porous medium can be beneficial for enhancing reaction rate and temperature uniformity. Therefore, considering the combination with oxy-fuel combustion can address some shortcomings in oxy-fuel burners, a cylindrical two-layer porous burner model is established based on OpenFOAM in this paper. A two-temperature equation model is adopted for the simulation of the heat transfer process. The CH4 skeletal kinetic mechanism is adopted for complex chemistry integration based on OpenSMOKE++. Corresponding experimental methods were used for complementary studies. The walls of the burner are wrapped with three types of thermal insulation materials to present different levels of heat loss. The results show that considering the convection and radiative heat loss of the burner wall, the temperature near the wall is reduced by more than 300 K compared to the adiabatic condition. As a result, the flame propagation speed and CO oxidation rate slowed down. The stable range will be destructively narrowed by more than 50%, and CO emissions will increase by more than 10 times. These defects will be aggravated by increasing the diameter of the burner. It is observed that when the diameter of the burner increases from the initial 5 cm to 10 cm, the effect of heat loss on the stable range is insignificant. [ABSTRACT FROM AUTHOR]