Predictive Coding Theories of Cortical Function

Predictive coding is a unifying framework for understanding perception, action and neocortical organization. In predictive coding, different areas of the neocortex implement a hierarchical generative model of the world that is learned from sensory inputs. Cortical circuits are hypothesized to perfor...

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Bibliographic Details
Published in:arXiv.org
Main Authors: Linxing Preston Jiang, Rao, Rajesh P N
Format: Paper
Language:English
Published: Ithaca Cornell University Library, arXiv.org 19.05.2023
Subjects:
Bayesian analysis
Cerebral cortex
Coding
Errors
Predictions
Statistical inference
ISSN:2331-8422
Online Access:Get full text
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Summary:Predictive coding is a unifying framework for understanding perception, action and neocortical organization. In predictive coding, different areas of the neocortex implement a hierarchical generative model of the world that is learned from sensory inputs. Cortical circuits are hypothesized to perform Bayesian inference based on this generative model. Specifically, the Rao-Ballard hierarchical predictive coding model assumes that the top-down feedback connections from higher to lower order cortical areas convey predictions of lower-level activities. The bottom-up, feedforward connections in turn convey the errors between top-down predictions and actual activities. These errors are used to correct current estimates of the state of the world and generate new predictions. Through the objective of minimizing prediction errors, predictive coding provides a functional explanation for a wide range of neural responses and many aspects of brain organization.
Bibliography:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
content type line 50
ISSN:2331-8422
DOI:10.48550/arxiv.2112.10048