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Updated: Apr 14, 2026
07:12
Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
Published on: July 1, 2014
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Visual processing of informative multipoint correlations arises primarily in V2.
Yunguo Yu1, Anita M Schmid1, Jonathan D Victor1
1Brain and Mind Research Institute, Weill Cornell Medical College, New York, United States.
Elife
|April 28, 2015
Summary
Researchers found that neurons in visual area V2 process complex image features. This demonstrates how the brain efficiently codes visual information, explaining V2
Area of Science:
- Neuroscience
- Computational Neuroscience
- Visual Processing
Background:
- The efficient coding principle suggests sensory systems allocate resources to process the most informative statistical features of sensory input.
- Previous work demonstrated this principle in central sensory processing when image sampling is limited.
Purpose of the Study:
- To identify the location within the visual system where computations sensitive to multipoint correlations occur.
- To link these computations to known neural processing characteristics of visual area V2.
Main Methods:
- Single-unit recordings were performed in the macaque monkey visual system.
- Neuronal responses were analyzed for sensitivity to specific multipoint correlations relevant to natural images.
Main Results:
- Computations involving sensitivity to multipoint correlations were localized to visual area V2.
- This sensitivity was primarily found in the supragranular layers of V2.
- V2 neurons demonstrated sensitivity to image statistics that are highly informative about natural scenes.
Conclusions:
- Visual area V2 neurons are sensitive to the informative multipoint correlations of natural images.
- This sensitivity provides a unified computational basis for various V2 functions, including processing of corners, junctions, and illusory contours.
- The findings support the efficient coding principle's role in organizing visual computations in V2.
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