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Passive exposure to task-relevant stimuli enhances categorization learning

Learning to perform a perceptual decision task is generally achieved through sessions of effortful practice with feedback. Here, we investigated how passive exposure to task-relevant stimuli, which is relatively effortless and does not require feedback, influences active learning. First, we trained...

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Autores principales: Schmid, Christian, Haziq, Muhammad, Baese-Berk, Melissa M., Murray, James M., Jaramillo, Santiago
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104059/
https://www.ncbi.nlm.nih.gov/pubmed/37066276
http://dx.doi.org/10.1101/2023.04.04.535463
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author Schmid, Christian
Haziq, Muhammad
Baese-Berk, Melissa M.
Murray, James M.
Jaramillo, Santiago
author_facet Schmid, Christian
Haziq, Muhammad
Baese-Berk, Melissa M.
Murray, James M.
Jaramillo, Santiago
author_sort Schmid, Christian
collection PubMed
description Learning to perform a perceptual decision task is generally achieved through sessions of effortful practice with feedback. Here, we investigated how passive exposure to task-relevant stimuli, which is relatively effortless and does not require feedback, influences active learning. First, we trained mice in a sound-categorization task with various schedules combining passive exposure and active training. Mice that received passive exposure exhibited faster learning, regardless of whether this exposure occurred entirely before active training or was interleaved between active sessions. We next trained neural-network models with different architectures and learning rules to perform the task. Networks that use the statistical properties of stimuli to enhance separability of the data via unsupervised learning during passive exposure provided the best account of the behavioral observations. We further found that, during interleaved schedules, there is an increased alignment between weight updates from passive exposure and active training, such that a few interleaved sessions can be as effective as schedules with long periods of passive exposure before active training, consistent with our behavioral observations. These results provide key insights for the design of efficient training schedules that combine active learning and passive exposure in both natural and artificial systems.
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spelling pubmed-101040592023-04-15 Passive exposure to task-relevant stimuli enhances categorization learning Schmid, Christian Haziq, Muhammad Baese-Berk, Melissa M. Murray, James M. Jaramillo, Santiago bioRxiv Article Learning to perform a perceptual decision task is generally achieved through sessions of effortful practice with feedback. Here, we investigated how passive exposure to task-relevant stimuli, which is relatively effortless and does not require feedback, influences active learning. First, we trained mice in a sound-categorization task with various schedules combining passive exposure and active training. Mice that received passive exposure exhibited faster learning, regardless of whether this exposure occurred entirely before active training or was interleaved between active sessions. We next trained neural-network models with different architectures and learning rules to perform the task. Networks that use the statistical properties of stimuli to enhance separability of the data via unsupervised learning during passive exposure provided the best account of the behavioral observations. We further found that, during interleaved schedules, there is an increased alignment between weight updates from passive exposure and active training, such that a few interleaved sessions can be as effective as schedules with long periods of passive exposure before active training, consistent with our behavioral observations. These results provide key insights for the design of efficient training schedules that combine active learning and passive exposure in both natural and artificial systems. Cold Spring Harbor Laboratory 2023-10-05 /pmc/articles/PMC10104059/ /pubmed/37066276 http://dx.doi.org/10.1101/2023.04.04.535463 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Schmid, Christian
Haziq, Muhammad
Baese-Berk, Melissa M.
Murray, James M.
Jaramillo, Santiago
Passive exposure to task-relevant stimuli enhances categorization learning
title Passive exposure to task-relevant stimuli enhances categorization learning
title_full Passive exposure to task-relevant stimuli enhances categorization learning
title_fullStr Passive exposure to task-relevant stimuli enhances categorization learning
title_full_unstemmed Passive exposure to task-relevant stimuli enhances categorization learning
title_short Passive exposure to task-relevant stimuli enhances categorization learning
title_sort passive exposure to task-relevant stimuli enhances categorization learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104059/
https://www.ncbi.nlm.nih.gov/pubmed/37066276
http://dx.doi.org/10.1101/2023.04.04.535463
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