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Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.

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Related Experiment Video

Updated: Oct 19, 2025

Visualizing Visual Adaptation

Visualizing Visual Adaptation

Published on: April 24, 2017

Adaptation supports short-term memory in a visual change detection task.

Brian Hu¹, Marina E Garrett¹, Peter A Groblewski¹

¹Allen Institute for Brain Science, Seattle, Washington, United States of America.

Plos Computational Biology

|September 17, 2021

Summary

This summary is machine-generated.

Short-term memory in mice relies on neural adaptation, not just persistent activity. A synaptic depression model (STPNet) better explains mouse behavior in a visual change detection task than a recurrent neural network (RNN).

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Last Updated: Oct 19, 2025

Visualizing Visual Adaptation

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Published on: April 24, 2017

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

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Eye Movement Monitoring of Memory

Eye Movement Monitoring of Memory

Published on: August 15, 2010

Area of Science:

Neuroscience
Computational Neuroscience
Machine Learning

Background:

Short-term memory is vital for survival in changing environments.
Two proposed mechanisms for short-term memory are persistent neural activity and synaptic plasticity.
Understanding the neural basis of memory is a key challenge in neuroscience.

Purpose of the Study:

To compare the predictive power of persistent neural activity versus short-term synaptic plasticity for memory maintenance.
To investigate the neural and behavioral correlates of short-term memory in a visual change detection task.
To model mouse behavior using artificial neural networks.

Main Methods:

Mice performed a visual change detection task with natural images.
Neural activity was recorded using two-photon calcium imaging.
Two artificial neural networks, a recurrent neural network (RNN) and a feedforward network with short-term synaptic depression (STPNet), were trained on the same task.

Main Results:

Both RNN and STPNet learned the task, but STPNet units showed activity more similar to in vivo data.
STPNet errors more closely mirrored mouse behavioral errors.
Mice and STPNet exhibited similar behavioral responses to image omissions, unlike the RNN model.

Conclusions:

Simple neural adaptation mechanisms, like synaptic depression, may provide crucial bottom-up memory signals.
These adaptation mechanisms can inform downstream decision-making processes.
Synaptic plasticity offers a more parsimonious explanation for observed memory behaviors than persistent neural activity alone.