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Related Experiment Video

Updated: May 17, 2026

An Unbiased Approach of Sampling TEM Sections in Neuroscience

An Unbiased Approach of Sampling TEM Sections in Neuroscience

Published on: April 13, 2019

Waiting and weighting: Information sampling is a balance between efficiency and error-reduction.

Kimberly M Meier¹, Mark R Blair

¹Cognitive Science Program & Department of Psychology, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia, Canada V5A 1S6. kmeier@psych.ubc.ca

|October 27, 2012

Summary

Participants prioritize planning efficiency over information utility when sampling data for classification tasks. This suggests that minimizing the number of steps, or samples, is key to efficient information gathering.

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Area of Science:

Cognitive psychology
Decision-making
Information processing

Background:

Prior research highlights probability gain in single-sample scenarios.
Information utility and planning efficiency are key factors in information sampling.
Classification tasks involve strategic data acquisition.

Purpose of the Study:

To investigate the influence of information utility versus planning efficiency on information-sampling strategies.
To determine which factor guides participants' initial information search in an unrestricted sampling context.
To examine how feature access costs affect the preference for efficient versus high-gain information.

Main Methods:

Monitoring participants' information sampling behavior in a classification task.
Recording whether participants initiated their search with high probability gain or efficient features.
Manipulating feature access costs across two experiments, with eye-tracking used in the second.
Analyzing the influence of probability gain and efficiency on sampling patterns.

Main Results:

Participants consistently preferred sampling efficient features first, especially when access costs were high.
Even when access costs were minimal (Experiment 2), efficiency remained the primary driver of initial sampling.
Probability gain influenced information access patterns but was secondary to efficiency.
The study observed a clear preference for strategies minimizing the number of samples.

Conclusions:

Planning efficiency, aiming to reduce the total number of samples, is a dominant factor in information-sampling strategies.
Information utility, specifically probability gain, plays a role but is often subordinate to efficiency.
These findings have implications for understanding decision-making and optimizing information search in complex tasks.