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Can predictive coding explain repetition suppression?

Mareike Grotheer1, Gyula Kovács1

  • 1Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany; DFG Research Unit Person Perception, Friedrich Schiller University Jena, Jena, Germany.

Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
|February 11, 2016
PubMed
Summary
This summary is machine-generated.

Repetition suppression (RS) may involve top-down processes, particularly predictive coding (PC) models. This review examines evidence for and against PC in RS and proposes a new two-stage model for human cortical processing.

Keywords:
ExpectationPredictive codingRepetition suppressionSurprise

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • Repetition suppression (RS) has been traditionally explained by local, bottom-up neural mechanisms.
  • Emerging theories highlight the significant role of top-down processes in modulating neural responses to repeated stimuli.

Purpose of the Study:

  • To review evidence supporting the involvement of top-down processes in repetition suppression.
  • To critically evaluate Bayesian models of predictive coding (PC) as an explanation for RS.
  • To propose a refined model for understanding repetition and expectation phenomena in the human cortex.

Main Methods:

  • Literature review focusing on studies investigating top-down influences on repetition suppression.
  • Analysis of experimental findings related to predictive coding models and their explanatory power for RS.
  • Synthesis of current research to identify challenges and propose future directions.

Main Results:

  • Evidence suggests that top-down processes, consistent with predictive coding, contribute to repetition suppression.
  • The heterogeneity of experimental paradigms complicates direct comparisons of predictive processes.
  • Current findings offer support but also highlight limitations in fully explaining RS solely through predictive coding.

Conclusions:

  • Top-down predictive coding offers a valuable framework for understanding repetition suppression.
  • Further research is needed to delineate specific sub-processes involved in predictive mechanisms underlying RS.
  • A novel two-stage model is proposed to better integrate repetition and expectation phenomena in cortical function.