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Per-Unit Sequence Models

An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
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Related Experiment Video

Updated: May 19, 2026

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
10:39

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

Published on: May 3, 2018

Only correlated sequences that are actively processed contribute to implicit sequence learning.

Beat Meier1, Brigitte Weiermann, Josephine Cock

  • 1Department of Psychology and Center for Cognition, Learning & Memory, University of Bern, Switzerland. beat.meier@psy.unibe.ch

Acta Psychologica
|August 7, 2012
PubMed
Summary
This summary is machine-generated.

Implicit sequence learning is enhanced when secondary information is actively processed and relevant to task performance. Irrelevant but correlated secondary information does not improve sequence learning.

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Learning Sciences

Background:

  • Implicit sequence learning involves acquiring knowledge about regularities in a sequence without conscious awareness.
  • Previous research indicated that correlation between sequences is important for learning, but other factors may also be involved.
  • The role of secondary information, particularly its relevance and active processing, in sequence learning requires further investigation.

Purpose of the Study:

  • To investigate the impact of correlated but irrelevant secondary information on implicit sequence learning.
  • To determine if relevant secondary information enhances implicit sequence learning compared to irrelevant information.
  • To understand the conditions under which secondary information benefits sequence learning.

Main Methods:

  • Utilized a task sequence learning paradigm to assess implicit learning.
  • Manipulated the presence and relevance of secondary information streams correlated with a primary sequence.
  • Compared learning performance across different experimental conditions.

Main Results:

  • Primary sequence learning was unaffected by secondary information that was sequenced but irrelevant to performance, despite correlation.
  • Sensitivity to the primary sequence increased when secondary information was both correlated and relevant to performance.
  • These findings suggest that sequence learning is enhanced through information integration.

Conclusions:

  • Active processing of secondary sequence information, involving selective attention and task necessity, is crucial for beneficial impact.
  • Implicit sequence learning is facilitated when learners integrate relevant and correlated information streams.
  • The findings highlight the importance of information relevance and active engagement for optimizing sequence learning.