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A model of visual backward masking.

Guido Bugmann¹, John G Taylor

¹School of Computing, Communications and Electronics, University of Plymouth, Plymouth PL4 8AA, UK. gbugmann@plymouth.ac.uk

|January 15, 2005

Summary

Backward masking impairs target recognition, especially metacontrast masking. A neural network model explains this by showing how local competition interrupts sustained neural activity, affecting response duration but not reaction times.

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Area of Science:

Computational Neuroscience
Visual Perception

Background:

Backward masking impairs recognition of a target stimulus by a subsequent mask.
Metacontrast masking, a form of backward masking, occurs with spatially proximate, non-overlapping stimuli.
Masking effects are strongest at stimulus intervals of 60-100 ms.

Purpose of the Study:

Investigate activity propagation in a feedforward neural network to understand metacontrast masking.
Model the neural mechanisms underlying the U-shaped masking curve.
Explain how masking affects cortical response duration while preserving reaction times.

Main Methods:

Simulated a feedforward network of leaky integrate-and-fire neurons.
Incorporated a local amplification mechanism with excitatory lateral connections.
Modeled masking as local competition between neural representations.

Main Results:

Without amplification, neural activity decayed layer by layer, ceasing propagation.
Local amplification supported prolonged self-sustained neural activity.
Masking reduced the duration of cortical responses to the target, creating a U-shaped masking curve.
Masking did not alter the onset of the cortical response.

Conclusions:

The model replicates the U-shaped masking curve by modulating the duration of sustained neural activity.
Local competition and amplification mechanisms are crucial for understanding metacontrast masking.
The model preserves reaction times, consistent with unconscious priming phenomena observed in backward masking.

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