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Related Experiment Video

Updated: Jan 8, 2026

Revealing Neural Circuit Topography in Multi-Color

Revealing Neural Circuit Topography in Multi-Color

Published on: November 14, 2011

Investigating action topography in visual cortex and deep artificial neural networks.

Davide Cortinovis¹, Nhut Truong², Hans Op de Beeck³

¹Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy. davide.cortinovis@unitn.it.

Nature Communications

|December 21, 2025

Summary

Action properties organize the visual cortex, creating a distinct topographic map in the brain. Deep artificial neural networks (DANNs) failed to replicate this action-based organization found in human brains.

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Area of Science:

Neuroscience
Cognitive Science
Artificial Intelligence

Background:

High-level visual cortex exhibits topographic organization for categories like animacy and size.
The role of action properties in shaping visual cortex topography remains underexplored.

Purpose of the Study:

To propose and investigate action as a fundamental organizing principle in visual cortex topography.
To evaluate the capacity of topographic deep artificial neural networks (DANNs) in capturing action-based visual organization.

Main Methods:

Functional magnetic resonance imaging (fMRI) was used to analyze brain responses to images.
Stimuli included body parts and objects varying in action properties.
Multivariate analyses were employed to identify organizational principles.

Main Results:

A topographically organized action gradient was identified in the left lateral occipitotemporal cortex.
This gradient showed overlapping activations for bodies, hands, tools, and manipulable objects.
Deep artificial neural networks (DANNs) demonstrated organization based on shape and animacy, but not action.

Conclusions:

Action serves as a significant organizing principle within the human visual cortex, distinct from animacy and size.
The identified action dimension advances our understanding of visual cortex organization.
Current DANN models do not fully capture the action-based organization observed in the human visual system.