IMR Press / JIN / Volume 21 / Issue 1 / DOI: 10.31083/j.jin2101012
Open Access Original Research
Lack of general learning ability factor in a rat test battery measuring a wide spectrum of cognitive domains
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1 Department of Pharmacology and Pharmacotherapy, Semmelweis University, 1089 Budapest, Hungary
2 Institute of Cognitive Neuroscience and Psychology, Hungarian Academy of Sciences, 1117 Budapest, Hungary
*Correspondence: gyertyan.istvan@med.semmelweis-univ.hu (István Gyertyán); ernyey.aliz@med.semmelweis-univ.hu (Aliz J. Ernyey)
J. Integr. Neurosci. 2022, 21(1), 12; https://doi.org/10.31083/j.jin2101012
Submitted: 30 April 2021 | Revised: 15 June 2021 | Accepted: 27 August 2021 | Published: 28 January 2022
Copyright: © 2022 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract

Objective: In the framework of a larger project aiming to test putative cognitive enhancer drugs in a system with improved translational validity, we established a rodent test battery, where different, clinically relevant cognitive domains were investigated in the same animal population. The aim of the current study was to check whether performances in the different tasks representing different cognitive functions are assay-specific or may originate in an underlying general learning ability factor. Methods: In the experiments 36 Long-Evans and 36 Lister Hooded rats were used. The test battery covered the following cognitive domains: attention and impulsivity (measured in the 5-choice serial reaction time task), spatial memory (Morris water-maze), social cognition (cooperation task), cognitive flexibility (attentional set shifting test), recognition memory (novel object recognition) and episodic memory (water-maze based assay). The outcome variables were analyzed by correlation analysis and principal component analysis (PCA). The datasets consisted of variables measuring learning speed and performance in the paradigms. From the raw variables composite variables were created for each assay, then from these variables a composite score was calculated describing the overall performance of each individual in the test battery. Results: Correlations were only found among the raw variables characterizing the same assay but not among variables belonging to different tests or among the composite variables. The PCAs did not reduce the dimensionality of the raw or composite datasets. Graphical analysis showed variable performance of the animals in the applied tests. Conclusions: The results suggests the assay outcomes (learning performance) in the system are based on independent cognitive domains.

Keywords
Cognition
g factor
Principal component analysis
Population with widespread knowledge
Figures
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