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Related Experiment Video

Updated: Jun 1, 2026

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

Published on: May 3, 2018

Category transfer in sequential causal learning: the unbroken mechanism hypothesis.

York Hagmayer¹, Björn Meder, Momme von Sydow

¹Department of Psychology, University of Göttingen, Germany. york.hagmayer@bio.uni-goettingen.de

Cognitive Science

|May 26, 2011

Summary

Learners transfer categories in causal learning tasks when they assume an unbroken causal mechanism between the relations. This challenges previous essentialist category transfer theories.

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Area of Science:

Cognitive Psychology
Causal Inference
Machine Learning

Background:

Humans can learn categories from causal input and apply them to new situations.
Category transfer is not always consistent, with learners sometimes abandoning learned categories.

Purpose of the Study:

To investigate the conditions under which categories are transferred in causal learning.
To propose and test the "unbroken mechanism hypothesis" as an alternative to essentialist explanations for category transfer.

Main Methods:

Two experiments were conducted to test the unbroken mechanism hypothesis.
Participants engaged in causal learning tasks involving category induction and transfer.

Main Results:

Findings support the unbroken mechanism hypothesis.
Category transfer is linked to the assumption of a continuous causal mechanism between related tasks.

Conclusions:

The unbroken mechanism hypothesis provides a novel explanation for category transfer in causal learning.
Learners' assumptions about the continuity of causal mechanisms significantly influence category transfer.