Attention is more than prediction precision.

Saved in:
Bibliographic Details
Title: Attention is more than prediction precision.
Authors: Bowman, Howard, Filetti, Marco, Wyble, Brad, Olivers, Christian
Source: Behavioral & Brain Sciences. Jun2013, Vol. 36 Issue 3, p206-208. 3p.
Subjects: Attention, Prediction models, Coding theory, Evoked potentials (Electrophysiology), Stimulus & response (Biology), Sensory neurons, Brain mapping
Abstract: A cornerstone of the target article is that, in a predictive coding framework, attention can be modelled by weighting prediction error with a measure of precision. We argue that this is not a complete explanation, especially in the light of ERP (event-related potentials) data showing large evoked responses for frequently presented target stimuli, which thus are predicted. [ABSTRACT FROM AUTHOR]
Copyright of Behavioral & Brain Sciences is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Description
Abstract:A cornerstone of the target article is that, in a predictive coding framework, attention can be modelled by weighting prediction error with a measure of precision. We argue that this is not a complete explanation, especially in the light of ERP (event-related potentials) data showing large evoked responses for frequently presented target stimuli, which thus are predicted. [ABSTRACT FROM AUTHOR]
ISSN:0140525X
DOI:10.1017/S0140525X12002324