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Vision

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Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.

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Related Experiment Video

Updated: Sep 22, 2025

Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex

Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex

Published on: February 8, 2020

How Stimulus Statistics Affect the Receptive Fields of Cells in Primary Visual Cortex.

Ali Almasi¹, Shi Hai Sun¹, Molis Yunzab¹

¹National Vision Research Institute, Carlton, Victoria 3053, Australia.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience

|May 24, 2022

Summary

The visual cortex (V1) in cats uses more complex receptive fields (RFs) for natural scenes (NSs) than for white Gaussian noise (WGN). This indicates context-dependent visual information processing in neurons.

Keywords:

adaptation data-driven modeling primary visual cortex receptive field stimulus statistics visual information processing

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Last Updated: Sep 22, 2025

Monocular Visual Deprivation and Ocular Dominance Plasticity Measurement in the Mouse Primary Visual Cortex

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Published on: February 8, 2020

Topographical Estimation of Visual Population Receptive Fields by fMRI

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Published on: February 3, 2015

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

Published on: May 12, 2019

Area of Science:

Neuroscience
Computational Neuroscience
Visual Processing

Background:

Neuronal receptive fields (RFs) are fundamental to understanding visual processing.
The impact of stimulus statistics on RF structure and function remains an active area of research.
Previous studies often used simplified stimuli like white Gaussian noise (WGN).

Purpose of the Study:

To investigate how neuronal RF models change when stimulus statistics shift from WGN to natural scenes (NSs).
To determine if visual cortical neurons exhibit context-dependent processing.
To explore the implications for efficient information transmission in sensory systems.

Main Methods:

Multielectrode recordings from the primary visual cortex (V1) of female cats.
Fitting neuronal RF models, including linear filters and static nonlinearities, to recorded data.
Comparing RF models derived from responses to WGN versus NS stimuli.

Main Results:

V1 neurons showed higher spike rates and shorter latencies when responding to NSs compared to WGN.
NS stimuli elicited RFs with additional, previously uncovered filters, indicating increased complexity.
This complexity was not an artifact of firing rate but a change in neural coding, revealing greater nonlinear processing.

Conclusions:

Natural scenes drive more complex receptive field structures in V1 neurons than white Gaussian noise.
V1 neurons exhibit context-dependent processing, adapting their operational modes based on stimulus statistics.
These findings suggest that the complexity of neural coding in V1 is influenced by the complexity of the visual input, impacting efficient information transmission.