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Background: The nucleus accumbens (NAc) mediates reward learning and motivation. Despite an abundance of neuropeptides, peptidergic neurotransmission from the NAc has not been integrated into current models of reward learning. The existence of a sparse population of neurons containing corticotropin releasing factor (CRF) has been previously documented. Here we provide a comprehensive analysis of their identity and functional role in shaping reward learning.
Methods: To do this, we took a multidisciplinary approach that included florescent in situ hybridization (N ≥ 3), tract tracing (N = 5), ex vivo electrophysiology (N ≥ 30), in vivo calcium imaging with fiber photometry (N ≥ 4) and use of viral strategies in transgenic lines to selectively delete CRF peptide from NAc neurons (N ≥ 4). Behaviors used were instrumental learning, sucrose preference and spontaneous exploration in an open field.
Results: Here we show that the vast majority of NAc CRF-containing (NAc ) neurons are spiny projection neurons (SPNs) comprised of dopamine D1-, D2- or D1/D2-containing SPNs that primarily project and connect to the ventral pallidum and to a lesser extent the ventral midbrain. As a population, they display mature and immature SPN firing properties. We demonstrate that NAc neurons track reward outcomes during operant reward learning and that CRF release from these neurons acts to constrain initial acquisition of action-outcome learning, and at the same time facilitates flexibility in the face of changing contingencies.
Conclusion: We conclude that CRF release from this sparse population of SPNs is critical for reward learning under normal conditions.
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http://dx.doi.org/10.1101/2023.11.16.567495 | DOI Listing |
Antimicrob Resist Infect Control
September 2025
School of Medicine and Health Management, Guizhou Province, Guizhou Medical University, GUI'an New District, 6 Ankang Avenue, Guiyang, People's Republic of China.
Background: Although current evidence supports the effectiveness of social norm feedback (SNF) interventions, their sustained integration into primary care remains limited. Drawing on the elements of the antimicrobial SNF intervention strategy identified through the Delphi-based evidence applicability evaluation, this study aims to explore the barriers and facilitators to its implementation in primary care institutions, thereby informing future optimization.
Methods: Based on the five domains of the Consolidated Framework for Implementation Research (CFIR), we developed semi-structured interview and focus group discussion guides.
J Neurosci
September 2025
Center for Studies in Behavioural Neurobiology, Department of Psychology, Concordia University, Montreal, QC, Canada, H4B 1R6
Adaptive behavior depends on a dynamic balance between acquisition and extinction memories. Male and female rodents differ in extinction learning rates, suggestion potential sex-based differences in this balance. In males, deletion of extinction-recruited neurons in the central nucleus (CN) of the amygdala impairs extinction retrieval, shifting behavior toward acquisition (Lay et al.
View Article and Find Full Text PDFNeurobiol Learn Mem
September 2025
UNSW Sydney, Australia; University of Technology Sydney, Australia. Electronic address:
Pavlovian stimuli signalling potential punishment and reward have powerful effects on instrumental behaviours. For example, a cue associated with punishment will suppress well-learned instrumental responses. However, the degree to which Pavlovian stimuli interfere with the learning of instrumental responses is less well studied.
View Article and Find Full Text PDFJ Exp Anal Behav
September 2025
Fralin Biomedical Research Institute at VTC, Roanoke, VA, United States of America.
Reward delays are often associated with reduced probability of reward, although standard assessments of delay discounting do not specify degree of reward certainty. Thus, the extent to which estimates of delay discounting are influenced by uncontrolled variance in perceived reward certainty remains unclear. Here we examine 370 participants who were randomly assigned to complete a delay discounting task when reward certainty was either unspecified (n=184) or specified as 100% (n = 186) in the task trials and task instructions.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
September 2025
In essence, reinforcement learning (RL) solves optimal control problem (OCP) by employing a neural network (NN) to fit the optimal policy from state to action. The accuracy of policy approximation is often very low in complex control tasks, leading to unsatisfactory control performance compared with online optimal controllers. A primary reason is that the landscape of value function is always not only rugged in most areas but also flat on the bottom, which damages the convergence to the minimum point.
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