Results 301 to 310 of about 6,561,703 (356)

Omissions of threat trigger subjective relief and prediction error-like signaling in the human reward and salience systems. [PDF]

Elife
Willems AL, Van Oudenhove L, Vervliet B.
europepmc   +1 more source

Risk factors for biometry prediction error by Barrett Universal II intraocular lens formula in Chinese patients. [PDF]

Int J Ophthalmol
Chen XH, Hong Y, Ke XH, Song SJ, Cen YJ, Zhang C.   +5 more
europepmc   +1 more source

Two Prediction Error Systems in the Nonlemniscal Inferior Colliculus: "Spectral" and "Nonspectral". [PDF]

J Neurosci
Carbajal GV, Casado-Román L, Malmierca MS.   +2 more
europepmc   +1 more source

Temporal dynamics of uncertainty and prediction error in musical improvisation across different periods. [PDF]

Sci Rep
Daikoku T.
europepmc   +1 more source

Optimal Hedging of Prediction Errors Using Prediction Errors

Optimal Hedging of Prediction Errors Using Prediction Errors
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Reversible Data Hiding Based on Dual Pairwise Prediction-Error Expansion

IEEE Transactions on Image Processing, 2021
Reversible data hiding generally exploits the redundancy of the cover medium and prediction-error expansion (PEE) has become the most effective mechanism.
Wenguang He, Z. Cai
semanticscholar   +1 more source

Neural Circuitry of Reward Prediction Error

Annual Review of Neuroscience, 2017
Dopamine neurons facilitate learning by calculating reward prediction error, or the difference between expected and actual reward. Despite two decades of research, it remains unclear how dopamine neurons make this calculation. Here we review studies that
Mitsuko Watabe-Uchida, Neir Eshel, Naoshige Uchida   +2 more
exaly   +2 more sources

Review and recommendations for univariate statistical analysis of spherical equivalent prediction error for intraocular lens power calculations.

Journal of cataract and refractive surgery, 2020
PURPOSE To provide a reference for study design comparing intraocular lens (IOL) power calculation formulas, to show that the standard deviation of the prediction error is the single most accurate measure of outcomes, and to provide the most recent ...
J. Holladay, R. Wilcox, D. Koch, Li Wang
semanticscholar   +1 more source

Dialogues on prediction errors

Trends in Cognitive Sciences, 2008
The recognition that computational ideas from reinforcement learning are relevant to the study of neural circuits has taken the cognitive neuroscience community by storm. A central tenet of these models is that discrepancies between actual and expected outcomes can be used for learning.
Yael, Niv, Geoffrey, Schoenbaum
openaire   +2 more sources