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Open AccessJournal ArticleDOI

Natural stimulus statistics alter the receptive field structure of v1 neurons.

TLDR
A large difference in predictive power suggests that natural spatiotemporal stimulus statistics activate nonlinear response properties in a different manner than the grating stimulus, which contributes to the modulatory effects of nonlinear temporal summation during natural vision.
Abstract
Studies of the primary visual cortex (V1) have produced models that account for neuronal responses to synthetic stimuli such as sinusoidal gratings. Little is known about how these models generalize to activity during natural vision. We recorded neural responses in area V1 of awake macaques to a stimulus with natural spatiotemporal statistics and to a dynamic grating sequence stimulus. We fit nonlinear receptive field models using each of these data sets and compared how well they predicted time-varying responses to a novel natural visual stimulus. On average, the model fit using the natural stimulus predicted natural visual responses more than twice as accurately as the model fit to the synthetic stimulus. The natural vision model produced better predictions in >75% of the neurons studied. This large difference in predictive power suggests that natural spatiotemporal stimulus statistics activate nonlinear response properties in a different manner than the grating stimulus. To characterize this modulation, we compared the temporal and spatial response properties of the model fits. During natural stimulation, temporal responses often showed a stronger late inhibitory component, indicating an effect of nonlinear temporal summation during natural vision. In addition, spatial tuning underwent complex shifts, primarily in the inhibitory, rather than excitatory, elements of the response profile. These differences in late and spatially tuned inhibition accounted fully for the difference in predictive power between the two models. Both the spatial and temporal statistics of the natural stimulus contributed to the modulatory effects.

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Citations
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Bayesian surprise attracts human attention.

TL;DR: A formal Bayesian definition of surprise is proposed to capture subjective aspects of sensory information and it is shown that Bayesian surprise is a strong attractor of human attention, with 72% of all gaze shifts directed towards locations more surprising than the average.
Journal ArticleDOI

Encoding and decoding in fMRI.

TL;DR: It is shown that encoding and decoding operations can both be used to investigate some of the most common questions about how information is represented in the brain, and a systematic modeling approach is proposed that begins by estimating an encoding model for every voxel in a scan and ends by using the estimated encoding models to perform decoding.
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Cognition does not affect perception: Evaluating the evidence for "top-down" effects.

TL;DR: This work suggests that none of these hundreds of studies – either individually or collectively – provides compelling evidence for true top-down effects on perception, or “cognitive penetrability,” and suggests that these studies all fall prey to only a handful of pitfalls.
Journal ArticleDOI

Do we know what the early visual system does

TL;DR: Research is progressing with the goals of defining a single “standard model” for each stage of the visual pathway and testing the predictive power of these models on the responses to movies of natural scenes, which would be an invaluable guide for understanding the underlying biophysical and anatomical mechanisms and relating neural responses to visual perception.
References
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Journal ArticleDOI

Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy

TL;DR: The bootstrap is extended to other measures of statistical accuracy such as bias and prediction error, and to complicated data structures such as time series, censored data, and regression models.
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Receptive fields of single neurones in the cat's striate cortex

TL;DR: The present investigation, made in acute preparations, includes a study of receptive fields of cells in the cat's striate cortex, which resembled retinal ganglion-cell receptive fields, but the shape and arrangement of excitatory and inhibitory areas differed strikingly from the concentric pattern found in retinalganglion cells.
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Sparse Coding with an Overcomplete Basis Set: A Strategy Employed by V1 ?

TL;DR: These deviations from linearity provide a potential explanation for the weak forms of non-linearity observed in the response properties of cortical simple cells, and they further make predictions about the expected interactions among units in response to naturalistic stimuli.
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Spatiotemporal energy models for the perception of motion

TL;DR: In this article, the first stage consists of linear filters that are oriented in space-time and tuned in spatial frequency, and the outputs of quadrature pairs of such filters are squared and summed to give a measure of motion energy.
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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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