Substance abuse research depends on precise and sensitive assessments of reinforcer efficacy in animal models. However, conventional methods often lack theoretical rigor and specificity to support these assessments. To address these gaps, the Modular Maximization Theory (MMT) is introduced as a comprehensive framework for understanding instrumental behavior. Like earlier maximization theories, MMT posits that behavior is distributed across alternatives to maximize utility over time. This concept is structured through five foundational postulates that define alternative actions and rules for choosing between them as budget constraints and utility functions. A key innovation of MMT is its incorporation of reinforcer utilization-encompassing both consummatory and post-consummatory activities-into the budget-constraint function. A model of ratio-schedule performance is developed under the assumption that utilization is proportional to demand, with utility represented as an additive power function of reinforcer magnitude. This model, termed PURSPU (Proportional Utilization, Ratio Schedule, Power Utility), effectively explains how reinforcer magnitude, response effort, non-contingent reinforcement, and income influence demand curves, behavior-output functions, dose-response relationships, and progressive-ratio breakpoints, while accounting for rate-dependent effects. The model also offers novel insights into choice behavior, including concurrent-schedule performance, income dependency, and delay discounting, as well as post-reinforcement pauses and run rates. Variations in budget constraints and utility functions are proposed as alternative models. Potential theoretical advancements, more targeted assessments of drug abuse liability, and the broader role of MMT in understanding human drug abuse are explored.
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http://dx.doi.org/10.1016/j.neubiorev.2025.106010 | DOI Listing |
Neurosci Biobehav Rev
January 2025
Arizona State University, United States.
Substance abuse research depends on precise and sensitive assessments of reinforcer efficacy in animal models. However, conventional methods often lack theoretical rigor and specificity to support these assessments. To address these gaps, the Modular Maximization Theory (MMT) is introduced as a comprehensive framework for understanding instrumental behavior.
View Article and Find Full Text PDFSensors (Basel)
January 2025
State Key Laboratory of Intelligent Vehicle Safety Technology, Chongqing 401133, China.
With the advancement of federated learning (FL), there is a growing demand for schemes that support multi-task learning on multi-modal data while ensuring robust privacy protection, especially in applications like intelligent connected vehicles. Traditional FL schemes often struggle with the complexities introduced by multi-modal data and diverse task requirements, such as increased communication overhead and computational burdens. In this paper, we propose a novel privacy-preserving scheme for multi-task federated split learning across multi-modal data (MTFSLaMM).
View Article and Find Full Text PDFPNAS Nexus
January 2025
Department of Mathematics, Aston University, Birmingham B4 7ET, United Kingdom.
Understanding the relation between cortical neuronal network structure and neuronal activity is a fundamental unresolved question in neuroscience, with implications to our understanding of the mechanism by which neuronal networks evolve over time, spontaneously or under stimulation. It requires a method for inferring the structure and composition of a network from neuronal activities. Tracking the evolution of networks and their changing functionality will provide invaluable insight into the occurrence of plasticity and the underlying learning process.
View Article and Find Full Text PDFJ Surg Res
January 2025
Department of Surgery, Amsterdam UMC, Location Vrije Universiteit, Amsterdam, The Netherlands; Cancer Center Amsterdam, Amsterdam, The Netherlands.
Introduction: Laparoscopic intestinal anastomosis requires specific technical skills and should be trained in a safe simulation environment before performing surgery in daily practice. However, anastomosis simulation training with objective feedback is not widely available. This study aimed to analyze a laparoscopic intestinal anastomosis training task that utilizes objective force, motion, and time measurements.
View Article and Find Full Text PDFACS Synth Biol
January 2025
Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan.
Bacterial outer membrane vesicles (OMVs) have emerged as promising vehicles for anticancer drug delivery due to their inherent tumor tropism, immune-stimulatory properties, and potential for functionalization with therapeutic proteins. Despite their advantages, the high lipopolysaccharide (LPS) endotoxin content in the OMVs raises significant safety and regulatory challenges. In this work, we produce LPS-attenuated and LPS-free OMVs and systematically assess the effects of LPS modification on OMVs' physicochemical characteristics, membrane protein content, immune-stimulatory capacity, tolerability, and anticancer efficacy.
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