J. A. Gray's Reinforcement Sensitivity Theory (RST) has produced a wealth of quasi-experimental studies in more than 35 years of research on personality and reinforcement sensitivity. The present meta-analysis builds on this literature by investigating RST in conflict and nonconflict reinforcement tasks in humans. Based on random-effects meta-analysis, we confirmed RST predictions of performance parameters (e.g., number of responses, reaction time) in reinforcement tasks for impulsivity- and anxiety-related traits. In studies on anxiety-related traits, the effect size variance was smaller for conflict tasks than for nonconflict tasks. A larger mean effect size and a larger variability of effect sizes were found for conflict compared to nonconflict tasks in studies on impulsivity-related traits. Our results suggest that problems with RST confirmation in reinforcement tasks are at least partly caused by insufficient statistical power of primary studies, and thus, encourage future research on RST.
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http://dx.doi.org/10.1177/1088868308316891 | DOI Listing |
Sci Rep
January 2025
Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan.
Humans exploit motor synergies for motor control; however, how they emerge during motor learning is not clearly understood. Few studies have dealt with the computational mechanism for generating synergies. Previously, optimal control generated synergistic motion for the upper limb; however, it has not yet been applied to the high-dimensional whole-body system.
View Article and Find Full Text PDFPLoS One
January 2025
Portugal Football School, Portuguese Football Federation, Oeiras, Portugal.
This study aimed to investigate the impact of different offensive-reward-related rules on the physical performance, perceived exertion and enjoyment of young basketball players during small-sided games (SSG). Eighteen youth male players (age: 13.3±0.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
UT Health San Antonio, San Antonio, TX, USA.
Background: Motivational disturbances are a major harbinger for dementia, being associated with a two- to seven-fold higher conversion rate from mild cognitive impairment. However, there are currently no objective assessment methods for identifying motivational disturbances in older adults (OA). Here, we present preliminary findings from a larger study which aims to validate an objective behavioral measure of effort in OAs by investigating the effects of age, risk, and reward (gain vs.
View Article and Find Full Text PDFSci Rep
January 2025
School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China.
Mobile edge computing offloads compute-intensive tasks generated on mobile wireless devices (WD) to edge servers (ES), which provides mobile users with low-latency computing services. Opportunistic computing offloading is effective to enhance computing performance in dynamic edge network environments; however, careless offloading of tasks to ESs can lead to WDs preempting network computing resources with limited bandwidth, thereby resulting in inefficient allocation of computing resources. To address these challenges, this paper proposes the density clustering and ensemble learning training-based deep reinforcement learning (DCEDRL) method for task offloading decision-making in mobile edge computing (MEC).
View Article and Find Full Text PDFNeural Netw
December 2024
Laboratory of Speech and Intelligent Information Processing, Institute of Acoustics, CAS, Beijing, China; University of Chinese Academy of Sciences, Beijing, China. Electronic address:
In multi-agent cooperative tasks, the presence of heterogeneous agents is familiar. Compared to cooperation among homogeneous agents, collaboration requires considering the best-suited sub-tasks for each agent. However, the operation of multi-agent systems often involves a large amount of complex interaction information, making it more challenging to learn heterogeneous strategies.
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