Reward-evoked dopamine transients are well established as prediction errors. However, the central tenet of temporal difference accounts-that similar transients evoked by reward-predictive cues also function as errors-remains untested. In the present communication we addressed this by showing that optogenetically shunting dopamine activity at the start of a reward-predicting cue prevents second-order conditioning without affecting blocking. These results indicate that cue-evoked transients function as temporal-difference prediction errors rather than reward predictions.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007380 | PMC |
| http://dx.doi.org/10.1038/s41593-019-0574-1 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Revisiting the Visual Acuity Curves. A Proposed Methodology for the Evaluation of Postoperative Visual Acuity in Presbyopia.
Clin Ophthalmol
December 2024
Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece.
Purpose: To identify the minimally required number of distances of visual acuity (VA) measurements for the reliable estimation of the visual acuity curve (VAC) and area of the curve (AoC) in presbyopia correction.
Patients And Methods: The study was divided into a validation and a clinical phase with a total recruitment of 120 participants (120 eyes) who underwent uncomplicated pseudophakic presbyopia surgery with bilateral premium intraocular lenses (IOL) implantation. This study was conducted in the Department of Ophthalmology, University Hospital of Alexandroupolis, Alexandroupolis, Greece.
A multivariate soil temperature interval forecasting method for precision regulation of plant growth environment.
Front Plant Sci
December 2024
College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Foliage plants have strict requirements for their growing environment, and timely and accurate soil temperature forecasts are crucial for their growth and health. Soil temperature exhibits by its non-linear variations, time lags, and coupling with multiple variables, making precise short-term multi-step forecasts challenging. To address this issue, this study proposes a multivariate forecasting method suitable for soil temperature forecasting.
View Article and Find Full Text PDFOn the Bayesian generalized extreme value mixture autoregressive model with adjusted SNR in non-standard actuarial data.
MethodsX
June 2025
Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya 60111 Indonesia.
This research introduces the Generalized Extreme Value Mixture Autoregressive (GEVMAR) model as an innovative approach for examining non-standard actuarial datasets within general insurance. Information concerning claim reserves often reveals notable volatility and multimodal distributions, attributes that standard models, including previous method such as the Gaussian Mixture Autoregressive (GMAR) model and other autoregressive methodologies, find problematic to manage effectively. The GEVMAR model integrates the Generalized Extreme Value (GEV) distribution alongside Bayesian estimation techniques, augmented by a modified Signal-to-Noise Ratio (SNR) metric to improve predictive accuracy.
View Article and Find Full Text PDFGlobal reasons for missed nursing care: a systematic review and meta-analysis.
Int Nurs Rev
March 2025
College of Nursing, ShaoYang University, Shaoyang, China.
Background: While numerous studies have quantified the prevalence of reasons for missed care, a comprehensive synthesis of evidence across various health systems remains lacking.
Aim: To estimate the pooled prevalence of the reasons reported by nurses for missed care, using data from the MISSCARE surveys.
Introduction: Missed nursing care, which refers to any aspect of essential patient care that is omitted or delayed, presents substantial risks to patient safety and the quality of care.
Population Pharmacokinetic Modeling of Certepetide in Human Subjects With Metastatic Pancreatic Ductal Adenocarcinoma.
Clin Pharmacol Drug Dev
January 2025
Department of Pharmacometrics Modeling, A2-Ai LLC, Ann Arbor, MI, USA.
Certepetide (aka LSTA1 and CEND-1) is a novel cyclic tumor-targeting internalizing arginyl glycylaspartic acid peptide being developed to treat solid tumors. Certepetide is designed to overcome existing challenges in treating solid tumors by delivering co-administered anticancer drugs into the tumor while selectively depleting immunosuppressive T cells, enhancing cytotoxic T cells in the tumor microenvironment, and inhibiting the metastatic cascade. A population pharmacokinetic (PK) analysis was conducted to characterize the concentration-time profile of patients with metastatic exocrine pancreatic cancer receiving certepetide in combination with nab-paclitaxel and gemcitabine, and to investigate the effects of clinically relevant covariates on PK parameters.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!