Effects of working memory load and CS-US intervals on delay eyeblink conditioning

Leila Etemadi, Dan Anders Jirenhed, Anders Rasmussen*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
29 Downloads (Pure)

Abstract

Eyeblink conditioning is used in many species to study motor learning and make inferences about cerebellar function. However, the discrepancies in performance between humans and other species combined with evidence that volition and awareness can modulate learning suggest that eyeblink conditioning is not merely a passive form of learning that relies on only the cerebellum. Here we explored two ways to reduce the influence of volition and awareness on eyeblink conditioning: (1) using a short interstimulus interval, and (2) having participants do working memory tasks during the conditioning. Our results show that participants trained with short interstimulus intervals (150 ms and 250 ms) produce very few conditioned responses after 100 trials. Participants trained with a longer interstimulus interval (500 ms) who simultaneously did working memory tasks produced fewer conditioned responses than participants who watched a movie during the training. Our results suggest that having participants perform working memory tasks during eyeblink conditioning can be a viable strategy for studying cerebellar learning that is absent of influences from awareness and volition. This could enhance the comparability of the results obtained in human studies with those in animal models.

Original languageEnglish
Article number16
Journalnpj Science of Learning
Volume8
Issue number1
DOIs
Publication statusPublished - 20 May 2023

Bibliographical note

Acknowledgements
This study was supported by grants to CCL from the Swedish Research Council (2015–00276), and to Anders Rasmussen from the Swedish Research Council (2020–01468), the Crafoord Foundation (20180704, 20200729, 20220776), Per-Eric och Ulla Schybergs foundation (42630), the Segerfalk foundation (2019–2246), Åke-Wibergs foundation (M18-0070 & M19-0375, M20-0008), Fredrik & Ingrid Thurings foundation (2018-00366 & 2019-00516), and Magnus Bergvalls foundation (2020-03788). PsyToolkit is developed by and belongs to Professor Gijsbert Stoet.

Funding
Open access funding provided by Lund University.

Publisher Copyright: © 2023, The Author(s).

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