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Related Experiment Video

Updated: Feb 20, 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

Biased guessing in a complete-identification visual-working-memory task: Further evidence for mixed-state models.

Robert M Nosofsky¹, Jason M Gold¹

¹Department of Psychological and Brain Sciences, Indiana University Bloomington.

Journal of Experimental Psychology. Human Perception and Performance

|October 17, 2017

Summary

This summary is machine-generated.

This study reveals that guessing strategies significantly impact visual working memory (VWM) performance. When memory fails, participants strategically guess, favoring high-payoff responses, which mixed-state models accurately capture.

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Published on: December 5, 2025

Area of Science:

Cognitive Psychology
Neuroscience

Background:

Visual working memory (VWM) is crucial for cognitive tasks.
Understanding the underlying mechanisms of VWM, including potential biases and errors, is essential.

Purpose of the Study:

To investigate the role of mixed states and guessing processes in visual working memory.
To compare the explanatory power of mixed-state models versus variable-resources (VR) models in a complete-identification VWM task.

Main Methods:

Participants completed a complete-identification VWM task with 16 colors.
Payoffs for correct responses were manipulated across trials.
Individual-subject identification-confusion data were analyzed and modeled.

Main Results:

Evidence for a systematic guessing process was found, where participants used high-payoff responses when memory was absent.
Mixed-state models, incorporating memory and guessing, accurately accounted for the data.
Standard VR models without a guessing state struggled to explain the observed performance patterns.

Conclusions:

Discrete, mixed states play a significant role in visual working memory.
Future VR models should incorporate sophisticated decision rules for tasks like complete identification.