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Updated: Jun 17, 2026

Eye Tracking Young Children with Autism

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Published on: March 27, 2012

Spatiotemporal Evidence Accumulation Through Saccadic Sampling for Object Recognition.

Zhihao Zheng¹, Jiaqi Hu^1,2, Gouki Okazawa^3,2

¹Institute of Neuroscience, Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, International Center for Primate Brain Research, Chinese Academy of Sciences, Shanghai 200031, China.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience

|September 16, 2025

Summary

This summary is machine-generated.

Object recognition during natural viewing, involving eye movements (saccades), is explained by a simple evidence accumulation model. This parsimonious approach bypasses complex visual-oculomotor interactions for understanding trans-saccadic integration.

Keywords:

decision making evidence accumulation face recognition object recognition saccadic eye movement

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Area of Science:

Cognitive Neuroscience
Computational Vision
Oculomotor Systems

Background:

Natural object recognition relies on scanning features via eye movements (saccades).
Mechanistic models for saccade-based recognition integrating visual and oculomotor systems are lacking.
Previous studies often required controlled eye movements, limiting natural viewing insights.

Purpose of the Study:

To develop and test a quantitative model for object categorization during free viewing with saccades.
To investigate the role of sensory evidence accumulation versus oculomotor signals in trans-saccadic integration.
To propose a parsimonious explanation for object recognition during natural gaze behavior.

Main Methods:

Utilized a perceptual decision-making framework based on evidence accumulation.
Recruited human participants (both sexes) for face and object categorization tasks.
Allowed participants to freely make saccades to scan object features during categorization.

Main Results:

A simple evidence accumulation model quantitatively explained human categorization behavior during free viewing with saccades.
The model successfully fit data from naturalistic viewing conditions, unlike prior models.
Experimental results indicated that efference copy (saccade commands) did not significantly contribute to evidence accumulation.

Conclusions:

Object recognition with saccades can be effectively modeled by simple sensory evidence accumulation.
Complex interactions between visual and oculomotor systems are not necessary to explain saccade-based recognition.
This parsimonious model advances our understanding of naturalistic visual perception and decision-making.