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Related Experiment Video

Updated: Jun 5, 2026

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions

Published on: July 16, 2015

Varying temporal contiguity and interference in a human avoidance task.

Daniel S J Costa¹, Robert A Boakes

¹School of Psychology, University of Sydney, Australia.

Journal of Experimental Psychology. Animal Behavior Processes

|January 26, 2011

Summary

This summary is machine-generated.

Learning to associate events depends on interference, not just time. Too many distractors slow down learning in avoidance tasks.

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Area of Science:

Cognitive Psychology
Human Learning
Behavioral Science

Background:

Temporal contiguity is crucial for associative learning.
Interference from other events can impact learning speed and accuracy.

Purpose of the Study:

To investigate how temporal contiguity and interference affect learning in a human avoidance task.
To determine the relative importance of time interval versus distractor number in associative learning.

Main Methods:

A human avoidance task (Martians) was used, manipulating signal-offset to shield-onset (S-S) interval and the number of distractor symbols.
Participants learned to release a space bar to prevent an "invasion" upon signal presentation.
Path analysis was employed to examine the relationships between variables.

Main Results:

Learning speed decreased linearly with increased trace interval and number of distractors.
The impact of the S-S interval on learning was primarily mediated by the number of distractors.
Failure to suppress responses correlated with an inability to identify the warning signal, suggesting contingency detection was impaired.

Conclusions:

Associative learning between temporally separated events is more dependent on the amount of interference than the time interval itself.
Distractors significantly impair contingency detection, hindering performance in avoidance tasks.
Minimizing interference is key to optimizing learning of temporal associations.