Prediction error, defined by the discrepancy between real and expected outcomes, lies at the core of associative learning. Behavioural investigations have provided evidence that prediction error up- and down-regulates associative relationships, and allocates attention to stimuli to enable learning. These behavioural advances have recently been followed by investigations into the neurobiological substrates of prediction error. In the present paper, we review neuroscience data obtained using causal and recording neural methods from a variety of key behavioural designs. We explore the neurobiology of both appetitive (reward) and aversive (fear) prediction error with a focus on the mesolimbic dopamine system, the amygdala, ventrolateral periaqueductal gray, hippocampus, cortex and locus coeruleus noradrenaline. New questions and avenues for research are considered.
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http://dx.doi.org/10.1016/j.neubiorev.2020.10.029 | DOI Listing |
Sci Rep
January 2025
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.
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January 2025
Crop and Horticultural Science Research Department, Mazandaran Agricultural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Tajrish, Iran.
Plum fruit fresh weight (FW) estimation is crucial for various agricultural practices, including yield prediction, quality control, and market pricing. Traditional methods for estimating fruit weight are often destructive, time-consuming, and labor-intensive. In this study, we addressed the problem of predicting plum FW using artificial intelligence (AI) methods based on fruit dimensions.
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January 2025
Department of Mechanical Engineering, College of Engineering and Computer Sciences, Jazan University, P.O Box 45124, Jazan, Saudi Arabia.
Fluid flow across a Riga Plate is a specialized phenomenon studied in boundary layer flow and magnetohydrodynamic (MHD) applications. The Riga Plate is a magnetized surface used to manipulate boundary layer characteristics and control fluid flow properties. Understanding the behavior of fluid flow over a Riga Plate is critical in many applications, including aerodynamics, industrial, and heat transfer operations.
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January 2025
Shandong Yankuang Intelligent Manufacturing Co., Jining, 272000, China.
The hydraulic column is a core component in the coal mine support system, however, the real-time monitoring of the hydraulic column during the service process of the hydraulic support faces challenges. To address these issues, a high-precision stress mapping method of hydraulic column is proposed. The hydraulic column loss function was constructed to guide the data-driven model training, and the cylinder stress mechanism model was established by using the elastic-plastic theory of thick-walled cylinder.
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January 2025
Electronics and Communication Engineering Dept. Faculty of Engineering, Horus University, New Damietta, Egypt.
Electric vehicles (EVs) rely heavily on lithium-ion battery packs as essential energy storage components. However, inconsistencies in cell characteristics and operating conditions can lead to imbalanced state of charge (SOC) levels, resulting in reduced capacity and accelerated degradation. This study presents an active cell balancing method optimized for both charging and discharging scenarios, aiming to equalize SOC across cells and improve overall pack performance.
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