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Higher Mental Functions of Brain: Learning and Memory01:26

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Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or playing an...
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Related Experiment Video

Updated: May 9, 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

Sequential effects in response time reveal learning mechanisms and event representations.

Matt Jones1, Tim Curran, Michael C Mozer

  • 1Department of Psychology and Neuroscience, University of Colorado Boulder, 345 UCB, Boulder, CO 80309-0345, USA. mcj@colorado.edu

Psychological Review
|August 7, 2013
PubMed
Summary

Sequential effects in binary choice tasks are explained by learning two key statistics: response base rate and stimulus repetition rate. This learning mechanism utilizes associative learning and error correction, offering insights into cognitive representations.

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Last Updated: May 9, 2026

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Published on: January 11, 2016

Area of Science:

  • Cognitive Psychology
  • Computational Neuroscience
  • Behavioral Science

Background:

  • Binary choice tasks exhibit complex sequential effects influencing responses and reaction times based on prior trials.
  • Existing models struggle to fully capture the intricate patterns observed in these sequential effects.

Purpose of the Study:

  • To explain the complex sequential effects in binary choice tasks using a novel learning framework.
  • To identify the specific statistics and learning mechanisms underlying these sequential effects.
  • To investigate the dissociation between stimulus and response processing in sequential learning.

Main Methods:

  • Simultaneous incremental learning of base rate and repetition rate statistics.
  • Application of associative learning and cue-competition mechanisms.
  • Analysis of event-related potentials and stimulus discriminability manipulations.
  • Reanalysis of existing experimental data.

Main Results:

  • Sequential effects are well-explained by learning the base rate and repetition rate of trial sequences.
  • A cue-competition mechanism influences the learning of these sequence statistics.
  • Learning of base rate and repetition rate are dissociated into response and stimulus processing, respectively.
  • Sequential effects are driven by learning the response base rate and stimulus repetition rate.

Conclusions:

  • Sequential effects in binary choice tasks arise from learning simple sequence statistics.
  • These findings provide a unified account of sequential effects, integrating associative learning and error correction.
  • Sequential effects serve as a powerful tool for uncovering cognitive representations and learning mechanisms.