REVIEW 6 cited by
Predictive Coding: a Theoretical and Experimental Review
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
Predictive coding offers a potentially unifying account of cortical function -- postulating that the core function of the brain is to minimize prediction errors with respect to a generative model of the world. The theory is closely related to the Bayesian brain framework and, over the last two decades, has gained substantial influence in the fields of theoretical and cognitive neuroscience. A large body of research has arisen based on both empirically testing improved and extended theoretical and mathematical models of predictive coding, as well as in evaluating their potential biological plausibility for implementation in the brain and the concrete neurophysiological and psychological predictions made by the theory. Despite this enduring popularity, however, no comprehensive review of predictive coding theory, and especially of recent developments in this field, exists. Here, we provide a comprehensive review both of the core mathematical structure and logic of predictive coding, thus complementing recent tutorials in the literature. We also review a wide range of classic and recent work within the framework, ranging from the neurobiologically realistic microcircuits that could implement predictive coding, to the close relationship between predictive coding and the widely-used backpropagation of error algorithm, as well as surveying the close relationships between predictive coding and modern machine learning techniques.
Forward citations
Cited by 6 Pith papers
-
Shunting Inhibition and Dendritic Branching Shape Local Credit Assignment
Exact dendritic gradients factor into local eligibility times path-transported compartment error, and shunting inhibition can improve restricted-feedback local learning by reshaping that error field.
-
Forward Target Propagation: A Forward-Only Approach to Global Error Credit Assignment via Local Losses
FTP trains neural networks using only forward passes, propagating random-projection target signals through the network, and achieves near-backpropagation accuracy on small shallow benchmarks.
-
Contextual Semantic Relevance and Word Surprisal Predict N400 and P600 Dynamics During Naturalistic Reading
Attention-aware contextual semantic relevance predicts N400 and especially P600 EEG voltages during naturalistic reading beyond GPT-2 surprisal and lexical controls.
-
Introduction to Predictive Coding Networks for Machine Learning
The paper derives standard predictive coding update rules and claims a 99.92% CIFAR-10 accuracy that would beat the published leaderboard, but the claim is unverified and internally inconsistent.
-
Redefining Robot Generalization Through Interactive Intelligence
A conceptual proposal that robot foundation models should be rebuilt around interactive multi-agent coordination with humans, illustrated for wearable 'cyborg' devices, without empirical validation.
-
Bridging Predictive Coding and MDL: A Two-Part Code Framework for Deep Learning
A theoretical framework claims that predictive coding performs block-coordinate descent on a two-part code objective and bounds true risk by empirical risk plus codelength divided by sample size.
Discussion (0). Continue with ORCID to comment.