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Neuronal normalization in monkey MT is an intensity-weighted average.

Chery Cherian1,2, John H R Maunsell2,3

  • 1Committee on Neurobiology, University of Chicago, Chicago, IL 60637.

Proceedings of the National Academy of Sciences of the United States of America
|November 6, 2025
PubMed
Summary
This summary is machine-generated.

Normalization in the brain stabilizes neural activity. An intensity-weighted model better explains how neuronal responses vary with stimulus location, improving understanding of visual processing and contrast sensitivity.

Keywords:
middle temporal visual areamodelingnonhuman primatenormalizationvisual neuroscience

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Visual System Research

Background:

  • Neuronal normalization stabilizes brain activity and preserves stimulus selectivity across neuron populations.
  • Normalization is crucial in higher visual areas with large receptive fields (RFs) encountering multiple stimuli.
  • Current models struggle to explain normalization with stimuli at varied RF locations in complex scenes.

Purpose of the Study:

  • Investigate how normalization changes with stimulus spatial offset from neuronal RF centers.
  • Develop and validate a new model for neuronal normalization in complex visual environments.
  • Clarify the role of spontaneous activity in normalization.

Main Methods:

  • Recorded neuronal responses in the macaque monkey middle temporal area.
  • Tested existing normalization models against experimental data with stimuli at different RF locations.
  • Developed and evaluated an intensity-weighted normalization model.

Main Results:

  • Existing normalization models showed poor performance with stimuli at arbitrary RF locations.
  • An intensity-weighted normalization model, considering stimulus contrast and RF weights, accurately predicted neuronal responses.
  • This model explained increased contrast sensitivity near RF centers and revealed spontaneous activity's role in normalization.

Conclusions:

  • Neuronal normalization is better described by an intensity-weighted model that accounts for stimulus location and contrast.
  • This model provides a more accurate framework for understanding visual processing in complex natural scenes.
  • Spontaneous neural activity contributes to normalization similarly to stimuli.