Predictive Coding as a Model of Response Properties in Cortical Area V1

By Michael W. Spratling. 2010

217 citations recorded by the source corpus.

A simple model is shown to account for a large range of V1 classical, and nonclassical, receptive field properties including orientation tuning, spatial and temporal frequency tuning, cross-orientation suppression, surround suppression, and facilitation and inhibition by flankers and textured surrounds. The model is an implementation of the predictive coding theory of cortical function and thus provides a single computational explanation for a diverse range of neurophysiological findings. Furthermore, since predictive coding can be related to the biased competition theory and is a specific example of more general theories of hierarchical perceptual inference, the current results relate V1 response properties to a wider, more unified, framework for understanding cortical function.

Subfields: Cognitive Neuroscience

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Citations in the corpus

Theory of Mind: A Neural Prediction Problem (2013, positive): “This proposal is a hybrid of multiple approaches (Friston, 2010; Clark, 2013; Wacongne et al., 2012; de Wit et al., 2010; Spratling, 2010), seems to capture the essential common ideas, and is reasonably consistent with existing data.”
How Do Expectations Shape Perception? (2018, background): “First, extra-classical receptive field effects, both in space [5,125] and time [126], are readily explained by predictive coding as originating from predictive feedback.”
A review of predictive coding algorithms. (2017, background): “…and Ballard (1999) showed that error neuron responses could explain the phenomena of end-stopping observed in primary visual cortex pyramidal cells, Spratling (2010) showed that prediction neuron behaviour could explain end-stopping and a very wide range of other response properties observed in…”
Predictive Processing: A Canonical Cortical Computation (2018, unknown): “The idea that the brain uses an internal model to predict sensory input based on movements and past sensory experience has been formalized in several different variants: predictive coding, hierarchical temporal memory, and Bayesian inference (Friston, 2005; Hawkins and Blakeslee, 2004; Körding and W”
Primary Visual Cortex Represents the Difference Between Past and Present (2013, methodology): “…et al. 1982; Hosoya et al. 2005) and have been used in recent modeling frameworks of cortical visual responses (Rao and Ballard 1999; Friston 2005; Spratling 2010, 2012; Boerlin and Dèneve 2011), also suggesting a combination of stimulus and error-like coding within single neurons (Eriksson et…”
Attention, Uncertainty, and Free-Energy (2010, background): “Electrophysiologically, desynchronization with increased gamma activity (between 30 and 100 Hz) is seen during attentional tasks in invasive (Steinmetz et al., 2000; Bichot et al., 2005; Fries et al., 2008), and non-invasive EEG and MEG studies (Gruber et al., 1999; Sokolov et al., 1999; Pavlova et…”
A Neuronal Model of Predictive Coding Accounting for the Mismatch Negativity (2012, methodology): “Predictive coding models of the MMN have been previously proposed (Friston, 2005; Friston et al., 2006; Garrido et al., 2009; Spratling, 2010) but only as abstract mathematical descriptions without a precise neurobiological implementation (Marreiros et al., 2009; but see Fiorillo, 2008).”
A Sensorimotor Circuit in Mouse Cortex for Visual Flow Predictions. (2017, unknown): “Evidence for predictive coding has mainly come from theoretical considerations (Rao and Ballard, 1999; Spratling, 2010) and the discovery of mismatch signals in primary sensory areas of cortex and avian pallium (Eliades and Wang, 2008; Fiser et al., 2016; Keller and Hahnloser, 2009; Keller et al.,…”
A mechanistic cortical microcircuit of attention for amplification, normalization and suppression. (2015, methodology): “A different version of his model (Spratling, 2010) can replicate additionally the data of MacEvoy et al.”