Repetition Suppression and Related Effects

We present an extensive review of the repetition effect aiming to understand a simple experimental fact: why the repetition of a stimulus leads to reduced neural activity as compared to unrepeated stimuli. Previous attempts to understand this fact were connected mainly with the application of the mechanisms of local models (synchrony, facilitation and sharpening). We show that the Neurolocator model earlier proposed for the explanation of neural memory, focused attention, and Pavlovian conditioning can also successfully explain most difficult cases of repetition effects. The Supplement Material includes wide range of related effects such as habituation and sensitization, negative priming, inhibition of return, whole brain segregation and integration. All of them need an additional works to build specific models in each case, but we believe that their successful modeling will be closely connected with the Neurolocator model.

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Publication Details

Journal
Mathematical Biology and Bioinformatics
Published
2025-01-09
DOI
https://doi.org/10.17537/2024.19.609
Primary Topic
Face Recognition and Perception
Type
article
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article

Repetition Suppression and Related Effects

Vitaliy I. Kryukov
Mathematical Biology and Bioinformatics
Face Recognition and Perception
article

Repetition Suppression and Related Effects

Vitaliy I. Kryukov
article en

Abstract

We present an extensive review of the repetition effect aiming to understand a simple experimental fact: why the repetition of a stimulus leads to reduced neural activity as compared to unrepeated stimuli. Previous attempts to understand this fact were connected mainly with the application of the mechanisms of local models (synchrony, facilitation and sharpening). We show that the Neurolocator model earlier proposed for the explanation of neural memory, focused attention, and Pavlovian conditioning can also successfully explain most difficult cases of repetition effects. The Supplement Material includes wide range of related effects such as habituation and sensitization, negative priming, inhibition of return, whole brain segregation and integration. All of them need an additional works to build specific models in each case, but we believe that their successful modeling will be closely connected with the Neurolocator model.

Mathematical Biology and BioinformaticsVol. 19(2)
Fondazione Toscana Gabriele Monasterio (IT)
Openalex Percentile: Top 99%
Face Recognition and Perception
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