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Related Experiment Video

Updated: Jan 10, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

A new algorithm of human attention.

Ilker Yildirim¹, Mario Belledonne¹

¹Department of Psychology, Yale University, New Haven, CT, USA ilker.yildirim@yale.edu mario.belledonne@yale.edu.

The Behavioral and Brain Sciences

|November 26, 2025

Summary

This summary is machine-generated.

Goals guide perception by rationing computational resources. Adaptive computation prioritizes perceptual tasks based on their decision-making impact, offering a novel explanation for attentional control.

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Area of Science:

Cognitive Science
Neuroscience
Computational Vision

Background:

Goals significantly influence how individuals process sensory information.
Existing models often explain this by task-specific mechanisms or computational specifications of perception.
A unified algorithmic account for goal-directed attention remains an active area of research.

Purpose of the Study:

To propose and investigate adaptive computation as a unifying algorithmic framework for attention.
To explain how perceptual processing is modulated by current goals.
To demonstrate how attentional resources are allocated based on decision-making relevance.

Main Methods:

Developed a novel algorithmic model of adaptive computation.
Simulated perceptual tasks where computational resources are limited.
Analyzed how resource allocation impacts task performance and decision outcomes.

Main Results:

Adaptive computation effectively rations perceptual resources based on their utility for decision-making.
The model explains how attention prioritizes information relevant to achieving current goals.
Resource allocation varied dynamically with the changing impact of perceptual computations on decisions.

Conclusions:

Adaptive computation offers a parsimonious explanation for goal-directed attention.
This framework suggests attention is an active rationing process, not merely selection.
Future research should explore empirical validation of adaptive computation in human perception and decision-making.