A review of predictive coding algorithms.

By Michael W. Spratling. Brain and Cognition, 2017

425 citations recorded by the source corpus.

Predictive coding is a leading theory of how the brain performs probabilistic inference. However, there are a number of distinct algorithms which are described by the term "predictive coding". This article provides a concise review of these different predictive coding algorithms, highlighting their similarities and differences. Five algorithms are covered: linear predictive coding which has a long and influential history in the signal processing literature; the first neuroscience-related application of predictive coding to explaining the function of the retina; and three versions of predictive coding that have been proposed to model cortical function. While all these algorithms aim to fit a generative model to sensory data, they differ in the type of generative model they employ, in the process used to optimise the fit between the model and sensory data, and in the way that they are related to neurobiology.

Subfields: Biophysics, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/79c8e933d40c078ba20a09b4f9e0534885d6766e

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Citations in the corpus

Neural Elements for Predictive Coding (2016, background): “Whilst the various algorithms implementing these ideas may differ in their computational strategy (Spratling, 2016), they share a common set of tenets: that the brain intrinsically generates a model of the world in which it finds itself (both the external and internal milieu) which is refined – but…”
Predictive Processing: A Canonical Cortical Computation (2018, positive): “Note, we do not wish to diminish the importance of the discrepancies between the different theories we are grouping here (see e.g. (Spratling, 2017) for a review of different variants of predictive coding), but will focus on their common premise.”
Vanilla PP for Philosophers: A Primer on Predictive Processing (2017, background): ““ (Spratling 2016, p. 1 preprint).”
Visualising mental representations: A primer on noise-based reverse correlation in social psychology (2017, background): “In the framework of predictive coding, these ideas are formalised as the interplay of (bottom-up) sensory inputs and (top-down) inferences, described in computational models with plausible neural substrates (Bastos et al., 2012; Spratling, 2017).”
How Do Expectations Shape Perception? (2018, background): “Different versions of predictive coding have been developed [117], differing primarily in how the error is computed (by subtraction or division) and in how prediction and prediction error neurons are connected [118].”