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Dynamic predictive coding by the retina.

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TLDR
It is shown that a network model with plastic synapses can account for the large variety of observed adaptations in retinal ganglion cells, and that when this happens, the retina adjusts its processing dynamically.
Abstract
Retinal ganglion cells convey the visual image from the eye to the brain. They generally encode local differences in space and changes in time rather than the raw image intensity. This can be seen as a strategy of predictive coding, adapted through evolution to the average image statistics of the natural environment. Yet animals encounter many environments with visual statistics different from the average scene. Here we show that when this happens, the retina adjusts its processing dynamically. The spatio-temporal receptive fields of retinal ganglion cells change after a few seconds in a new environment. The changes are adaptive, in that the new receptive field improves predictive coding under the new image statistics. We show that a network model with plastic synapses can account for the large variety of observed adaptations.

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Whatever next? Predictive brains, situated agents, and the future of cognitive science

TL;DR: This target article critically examines this "hierarchical prediction machine" approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action.
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Weak pairwise correlations imply strongly correlated network states in a neural population.

TL;DR: It is shown, in the vertebrate retina, that weak correlations between pairs of neurons coexist with strongly collective behaviour in the responses of ten or more neurons, and it is found that this collective behaviour is described quantitatively by models that capture the observed pairwise correlations but assume no higher-order interactions.
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Review: A review of novelty detection

TL;DR: This review aims to provide an updated and structured investigation of novelty detection research papers that have appeared in the machine learning literature during the last decade.
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The Neuronal Organization of the Retina

TL;DR: At least half of the encodings sent to the brain (ganglion cell response selectivities) remain to be discovered, indicating that diversity of the retina's outputs has yet to be incorporated into the understanding of higher visual function.
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Neuronal Reward and Decision Signals: From Theories to Data

TL;DR: Although all reward, reinforcement, and decision variables are theoretical constructs, their neuronal signals constitute measurable physical implementations and as such confirm the validity of these concepts.
References
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Journal ArticleDOI

Relations between the statistics of natural images and the response properties of cortical cells.

TL;DR: The results obtained with six natural images suggest that the orientation and the spatial-frequency tuning of mammalian simple cells are well suited for coding the information in such images if the goal of the code is to convert higher-order redundancy into first- order redundancy.
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Discharge patterns and functional organization of mammalian retina

TL;DR: The Limulus preparation shows many features which are similar to other simple sense organs, for instance, stretch receptors, however, instead of photochemical events, stretch-deformation acts as the adequate stimulus on sensory terminals and is translated into a characteristic discharge pattern.
Journal ArticleDOI

On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images.

TL;DR: In this paper, it was found that an occipital evoked potential can be elicited in the human by moving a grating pattern without changing the mean light flux entering the eye.
Journal ArticleDOI

The fundamental plan of the retina

TL;DR: The fundamental structural principles of the retina give a bottom-up view of the strategies used in the retina's processing of visual information and suggest new questions for physiological experiments and modeling.
Journal ArticleDOI

Predictive Coding: A Fresh View of Inhibition in the Retina

TL;DR: Comparisons suggest that, in the early stages of processing, the visual system is concerned primarily with coding the visual image to protect against subsequent intrinsic noise, rather than with reconstructing the scene or extracting specific features from it.
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